Phylogenetic Relationships among Indigenous and Introduced

Bamboo Species and Genetic Diversity Study of Ethiopian Lowland

Bamboo [Oxytenanthera abyssinica (A. Rich.) Munro] Using cpDNA

Genes ( matK , ndhF and rps16 ) and ISSR Markers

Oumer Abdie Oumer

Addis Ababa University

Addis Ababa Ethiopia

July, 2020

Phylogenetic Relationships among Indigenous and Introduced

Bamboo Species and Genetic Diversity Study of Ethiopian Lowland

Bamboo [Oxytenanthera abyssinica (A. Rich.) Munro] Using cpDNA

Genes ( matK , ndhF and rps16 ) and ISSR Markers

Oumer Abdie Oumer

A Dissertation Submitted to Department of Microbial, Cellular and Molecular Biology in Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Biology (Applied Genetics)

Addis Ababa University

Addis Ababa Ethiopia

July, 2020

DECLARATION

I declare that this Dissertation entitled “Phylogenetic Relationships among Indigenous and

Introduced Bamboo Species and Genetic Diversity Study of Ethiopian Lowland Bamboo

[Oxytenanthera abyssinica (A. Rich.) Munro] Using cpDNA Genes ( matK , ndhF and rps16 )

and ISSR Markers” submitted for the Degree of Doctor of Philosophy (PhD) in Biology

(Applied Genetics) to the School of Graduate Studies, Addis Ababa University, is my original

work and its composition has never been submitted elsewhere for any other award. All sources

of materials used for the Dissertation have been duly acknowledged.

Name: Oumer Abdie

Signature: .

Date: 20- July-2020 .

i

ACKNOWLEDGMENT .( ْٱﻟ َﺤ ْﻤﺪ ُ ِ ﱠ ِ َ ﺭ ِّ ﺏ ْٱﻟ َٰﻌ َﻠ ِﻤ َﻴﻦ ) First and for most, I would like to thank the Almighty I am highly indebted to express my deepest and genuine appreciation and thanks to my supervisors: the late Dr. Kifle Dagne, Dr. Tileye Feyissa and Dr. Kassahun Tesfaye for their excellent guiding, follow-up and support. Without the encouragement and guidance, the completion of this work on this form may not have been possible. Next, I would also like to owe my special thanks to Pakistani supervisor Dr. Muhammad Zeeshan Hyder from Biochemistry, Molecular Biology and Biotechnology (BMBB) Lab., Department of Biosciences, faculty of Sciences, COMSATS University Islamabad (CUI), Islamabad, Pakistan, for inviting me to BMBB laboratory as a Visiting PhD Scholar via The World Academy of Science - COMSATS University Islamabad (the then COMSATS Institute of Information Technology) (TWAS-CIIT) scholarships and for his advice on phylogenetics study.

I extend my deepest acknowledgments to different institutions that have provided financial support: Department of Microbial, Cellular and Molecular Biology (MCMB) of Addis Ababa University (AAU), Assosa University (ASU), TWAS-CIIT scholarships, training the next generation of scientists provided by Carnegie Cooperation of New York (CCNY) through the Regional Universities Forum for Capacity Building in Agriculture (RUFORUM), International Network for Bamboo and Rattan (INBAR) head quarter and East Africa Regional Office. I am thankful to Ethiopian Biodiversity Institute (EBI) for providing bamboo seeds and export permit and Central Ethiopia Environment and Forest Research Center (CE-EFRC) for providing cars to collect samples from Ormoia, Gambella and South nations nationalities and peoples (SNNPs) region for this study.

I am also grateful to former Department Head of MCMB Dr. Gurja B., stream supervisor Dr. Dereje B., current Department Head Dr. Adey F., former Department Head of BMBB Dr. Teyab J. and all department staff members of MCMB for their retireless support and advice.

Dr. Solange U., the former manager for Partnerships and Business Management (PBM) at RUFORUM and currently deputy director general in charge of Animal Resources Research ii and Technology Transfer at Rwanda Agriculture and Animal Resources Development Board (RAB), Jayaraman D., project manager INBAR global programme East Africa Regional Office, Ernest N. A., project manager Inter Africa Bamboo Development Programme INBAR West Africa Regional Office, Dr. Abeje E., former CE-EFRC director and Dagnew Y., former program leader for non-timber forest products at CE-EFRC must be duly acknowledged for their contribution to get research funds.

I would like to thank also my colleagues Dr. Mohammed A., Dr. Fekadu G., Mr. Muluken B., Ms. Hawi N. Mr. Asmamaw A., Mr. Amare E., and Pakistani friends Sana B. A., M. Shoiab and M. Shafiq as well as many more others for their friendly advice and support.

Last but not least, my family (beloved mother Medina Zekat, brothers and sisters) deserves special thanks for their all sided support. My wife Hawa Alkadir, my son M. Amin and daughter Haniyah for their patience, encouragement and giving hope at all times of this study period.

Oumer Abdie

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TABLE OF CONTENTS DECLARATION...... i ACKNOWLEDGMENT ...... ii TABLE OF CONTENTS ...... iv LIST OF TABLES ...... viii LIST OF FIGURES ...... ix LIST OF APPENDICES ...... xii LIST OF ABBREVIATIONS ...... xiii ABSTRACT ...... xiv CHAPTER ONE ...... 1 1. General Introduction ...... 1 1.1. Background ...... 1 1.2. Statement of the problem ...... 4 1.3. Hypothesis ...... 7 1.4. Objectives ...... 8 1.4.1. General Objective ...... 8 1.4.2. Specific objectives ...... 8 CHAPTER TWO ...... 9 2. Literature Review ...... 9 2.1. Taxonomy of Bamboo ...... 9 2.2. Bamboo Cytogenetics, Ploidy Level and Genome Size ...... 10 2.3. Area Coverage and Geographical Distribution of Bamboo ...... 12 2.3.1. Bamboo Distribution in Africa, Ethiopia and Pakistan ...... 13 2.4. Assessment of Phylogenetics and Genetic Diversity Study ...... 15 2.4.1. Chloroplast Genes Based Phylogenetics and Genetic Diversity Study ...... 18 2.4.2. ISSR Based Phylogenetics, Genetic Diversity and Population Structure Study ..22 2.5. Phylogenetic Tree Construction Methods ...... 23 CHAPTER THREE ...... 25 3. Phylogenetic Relationships among the Indigenous and Introduced Bamboo Species using cpDNA Genes Sequences ...... 25 3.1. Materials and Methods ...... 25 iv

3.1.1. Plant Materials and Sample Collections ...... 25 3.1.2. DNA Extraction and Primer Screening ...... 25 3.1.3. PCR Product Profiling, Sequencing and Alignment ...... 26 3.1.4. Phylogenetics Analyses ...... 27 3.2. Results ...... 29 3.2.1. Chloroplast DNA Sequence Character and Sequence Divergence ...... 29 3.2.1.1. GC and AC content analysis ...... 29 3.2.2. Phylogenetic Inference and Relationship...... 31 3.2.2.1. Maximum Parsimony Method Phylogenetics Tree Construction ...... 31 3.2.2.2. Maximum Likelihood Method Phylogenetics Tree Construction ...... 32 3.2.2.3. Neighbor-Joining Method Phylogenetics Tree Construction ...... 33 3.3. Discussion ...... 39 CHAPTER FOUR ...... 42 4. Genetic Diversity, Population Structure and Gene Flow Analysis of Ethiopian Lowland Bamboo [Bambusinea: Oxytenanthera abyssinica (A. Rich.) Munro] Using cpDNA Genes Sequences ...... 42 4.1. Materials and Methods ...... 42 4.1.1. DNA Extraction and PCR amplification...... 44 4.1.2. PCR product profiling, sequencing, and alignment ...... 44 4.1.3. Evolutionary tree construction and network analysis ...... 45 4.1.4. Measuring nucleotide diversity, InDel polymorphism, and gene low and genetic differentiation ...... 46 4.2. Results ...... 47 4.2.1. Chloroplast DNA sequence character and sequence divergence ...... 48 4.2.2. Phylogenetic inference and relationship ...... 49 4.2.2.1. Maximum parsimony method evolutionary history analysis ...... 49 4.2.2.2. Neighbor-Joining method evolutionary history analysis ...... 49 4.2.3. Network Analysis...... 51 4.2.4. Nucleotide Diversity Analysis ...... 53 4.2.5. InDel Polymorphism Analysis ...... 54 4.2.6. Analysis of DNA Divergence ...... 55 v

4.2.7. Gene Flow and Genetic Differentiation ...... 58 4.3. Discussion ...... 59 CHAPTER FIVE ...... 64 5. Genetic Relationship among Indigenous and Introduced Bamboo Species and ISSR Markers Efficiency Analysis ...... 64 5.1. Materials and Methods ...... 64 5.1.1. Plant Material Collection and Sampling Strategy ...... 64 5.1.2. DNA Extraction and Primer Screening ...... 64 5.1.3. ISSR-PCR Amplification and Gel Electrophoresis ...... 66 5.1.4. Scoring and Data Analysis ...... 67 5.2. Results ...... 70 5.2.1. ISSR Marker Banding Patterns ...... 70 5.2.2. Level of polymorphism in ISSR primers ...... 71 5.2.2.1. ISSR primers on genetic polymorphism ...... 71 5.2.2.2. Calculating Markers Efficiency ...... 73 5.2.2.3. Band Pattern and Heterozygosity ...... 74 5.2.3. Nei’s Genetic Distance and Similarity ...... 76 5.2.4. Cluster Analysis ...... 76 5.2.5. Principal Coordinate (PCoA) Analysis ...... 80 5.3. Discussion ...... 83 CHAPTER SIX ...... 86 6. Genetic Diversity and Population Structure Analysis of Ethiopian Lowland Bamboo [Bambusinea: Oxytenanthera abyssinica (A. Rich.) Munro] Using ISSR Marker ...... 86 6.1. Materials and Methods ...... 86 6.1.1. Plant Material Collection and Sampling Strategy ...... 86 6.1.2. DNA Extraction and Primer Screening ...... 86 6.1.3. ISSR-PCR Amplification and Gel Electrophoresis ...... 88 6.1.4. Scoring and Data Analysis ...... 89 6.2. Results ...... 93 6.2.1. ISSR Marker Banding Patterns ...... 93 6.2.2. Level of Polymorphism of Ethiopian Lowland Bamboo ...... 95 vi

6.2.2.1. ISSR Primers on Genetic Polymorphism of Ethiopian Lowland Bamboo ....95 6.2.2.2. Calculating Markers Efficiency ...... 97 6.2.2.3. Band Pattern and Heterozygosity ...... 98 6.2.3. Genetic Polymorphism and Shanon’s Information Index ...... 100 6.2.4. Analysis of Molecular Variance ...... 103 6.2.5. Cluster Analysis ...... 104 6.2.6. Principal Coordinate (PCoA) Analysis ...... 108 6.2.7. Admixture Analysis ...... 109 6.3. Discussion ...... 111 6.3.1. ISSR Markers for the Genetic Polymorphism in Ethiopian Lowland Bamboo ( O. abyssinica ) Populations ...... 111 6.3.2. Genetic Differentiation and Population Structure...... 114 6.3.3. Levels of Genetic Diversity among and Within Populations...... 116 6.3.4. Patterns of relationship and admixture analysis...... 119 7. Conclusion and Recommendation ...... 121 7.1. Conclusion ...... 121 7.2. Recommendation ...... 122 8. References ...... 126 9. APPENDICES ...... 142

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LIST OF TABLES Table 3-1: cpDNA primer sequences, their approximate amplified size and PCR profile. ... 26 Table 3-2: GC and AT content of each and aggregate cpDNA genes...... 30 Table 3-3: List of bamboo species and an accurate and complete GenBank record and/or accession numbers at NCBI ...... 38 Table 4-1: Samples information along with their GPS location ...... 42 Table 4-2: An accurate and complete GenBank record (accession numbers at NCBI)...... 47 Table 4-3: GC and AT content of each and aggregate cpDNA genes...... 48 Table 4-4: Nucleotide diversity analysis on Ethiopian lowland bamboo populations in different Zones...... 53 Table 4-5: InDel polymorphism of Ethiopian lowland bamboo ( O. abyssinica )...... 54 Table 4-6: Effects of gene flow and genetic differentiation on Ethiopian lowland bamboo. 58 Table 5-1: ISSR primers used for PCR amplification...... 65 Table 5-2: Polymorphism of the fifteen ISSR primers on the phylogenetics study ...... 72 Table 5-3: Polymorphism statistics calculated with iMEC for different types of primers for the 31 taxa of woody bamboos based on fifteen ISSR primers data set...... 74 Table 5-4: Band patterns observed across 31 taxa of bamboos ...... 75 Table 6-1: ISSR primers used for PCR analysis for the study of Ethiopian lowland bamboo87 Table 6-2: Polymorphism of the nineteen ISSR primers on 13 populations of O. abyssinica along with molecular size ranges in bp...... 96 Table 6-3: Polymorphism statistics calculated with iMEC for different types of primers for the lowland bamboo ( O. abyssinica ) based on nineteen ISSR primers data set...... 97 Table 6-4: Band patterns observed across Ethiopian lowland bamboo populations using nineteen ISSR bands ...... 99 Table 6-5: Genetic diversity within populations and genetic differentiation parameters of thirteen populations of O. abyssinica...... 102 Table 6-6: Analysis of molecular variance (AMOVA) for thirteen populations of O. abyssinica with seven administrative Zonal groups and without grouping...... 104

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LIST OF FIGURES Figure 1-1: Invasive bamboo species and their associated region (Canavan et al., 2016)...... 5 Figure 2.1-1: Subtribe relationships and geographic distributions of the four major lineages of bamboos based on plastid (chloroplast) DNA sequences from five loci: ndhF , rpl16 intron, rps16 intron, trnD–trnT intergenic spacer, and trnL–trnF intergenic spacer. (Kelchner and BPG, 2013)...... 10 Figure 2.1-2: Worldwide distribution of bamboo. (A) Neotropical woody bamboos, (B) Temperate woody bamboos, (C) Paleotropical woody bamboos, and (D) Herbaceous bamboos (http://www.eeob.iastate.edu/bamboo/maps.html)...... 12 Figure 2.1-3: Schematic gene map representation of some woody bamboo chloroplast genomes (Zhang et al., 2011; Wu et al., 2015). Inner thick arcs represent the inverted repeat regions (IRA; IRB), large and small single copy (LSC; SSC) region. Genes inside and outside of the circle are transcribed clockwise and counterclockwise and colored according to their functional groups. *: genes used for the study...... 21 Figure 3-1: MP revealed genomic relationships among 31 taxa of Bambusoideae along with reference sequences (with accession numbers starting from “NC”) from NCBI using matK, ndhF and rps16 genes of cpDNA. The indigenous bamboo species are written in red font color and pointed with arrow...... 31 Figure 3-2: ML revealed genomic relationships among 31 taxa of Bambusoideae along with reference sequences using matK , ndhF and rps16 genes of cpDNA. The indigenous bamboo species are written in red font color and pointed with arrow...... 32 Figure 3-3: NJ revealed genomic relationships among 31 taxa of Bambusoideae along with reference sequences using matK gene of cpDNA. The indigenous bamboo species are written in red font color and pointed with arrow...... 34 Figure 3-4: NJ revealed genomic relationships among 31 taxa of Bambusoideae along with reference sequences using (A) ndhF and (B) ndhF plus matK genes of cpDNA. The indigenous bamboo species are written in red font color and pointed with arrow...... 35 Figure 3-5: NJ revealed genomic relationships among 31 taxa of Bambusoideae along with reference sequences using (A) rps16 and (B) cumulative of matK , ndhF and rps16 genes of cpDNA...... 36

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Figure 3-6: NJ revealed genomic relationships among 31 taxa of Bambusoideae along with reference sequences and Ethiopian lowland bamboo ( O. abyssinica ) using matK , ndhF and rps16 genes of cpDNA (I) - Bambusoideae (tropical woody bamboo) and (II) - Arundinareae (temperate woody bamboo)...... 37 Figure 4-1: (A) Bamboo cover map of Ethiopia (Zhao et al., 2018), (B) Map of Ethiopia with sample collection area and (C) Map of the sample collection area ...... 43 Figure 4-2: The Maximum Parsimony tree of O. abyssinica obtained based on pair-wise distance from the combined data of matK, ndhF and rps16...... 49 Figure 4-3: The neighbor joining tree of O. abyssinica obtained based on pair-wise distance from the combined data of matK, ndhF and rps16...... 50 Figure 4-4: The NJ tree obtained based on pair-wise distance from each genes A. matK , B. ndhF , and C. rps16 gene...... 51 Figure 4-5: Haplotype network of the combined cpDNA region obtained based on (A) gaps/missing data considered and (B) gaps/missing data not-considered...... 52 Figure 4-6: Frequency and percentage of InDel polymorphism of Ethiopian lowland bamboo (O. abyssinica )...... 55 Figure 4-7: DNA divergence between different Zones of Ethiopian lowland bamboo populations...... 57 Figure 5-1: A representative of ISSR electrophoresis profile of 31 species of bamboo using ISSR A) UBC-835, B) UBC-873 and C) UBC-841 (single sample representative for fourteen bamboo species)...... 70 Figure 5-2: UPGMA dendrogram depicting clustering patterns for 31 taxa of bamboo based on Jaccard’s similarity coefficient. A. Aggregate of total primers, B. Di-nucleotide also 3’ anchored, C. Tri-nucleotide, D. Tetra-nucleotide, E. Penta-nucleotide, F. 3’ anchored, G. 5’ anchored, H. 3’ and 5’ anchored and I. Unanchored ISSR primers...... 80 Figure 5-3: Three-dimensional representation of principal coordinate analysis of genetic relationships among 31 species of bamboo inferred from similarity matrix using (A) the Jaccard’s index using STATISTICA and (B) Pearson PCA method using XLSTAT...... 82 Figure 6-1: A representative of ISSR electrophoresis profile of 13 populations of O. abyssinica using ISSR markers A) UBC-834, B) UBC-845 and C) UBC-888...... 94

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Figure 6-2: UPGMA based dendrogram for thirteen O. abyssinica populations based on Jaccard’s similarity coefficient using ninteen ISSR primers...... 106 Figure 6-3: NJ analysis of 130 individuals based on Jaccard’s similarity coefficient...... 106 Figure 6-4: UPGMA dendrogram depicting clustering patterns for thirteen populations of O. abyssinica based on Jaccard’s similarity coefficient. A. Di-nucleotide also 3’ anchored, B. Tri- nucleotide, C. Tetra-nucleotide, D. Penta-nucleotide, E.5’ anchored, F. 3’ and 5’ anchored and G. Unanchored ISSR primers...... 107 Figure 6-5: Three-dimensional representation of principal coordinate analysis of genetic relationships among 130 individuals of 13 populations of Ethiopian lowland bamboo ( O. abyssinica ) inferred from similarity matrix using (A) the Jaccard’s index at STATISTICA and (B) Pearson PCA method using XLSTAT...... 109 Figure 6-6: STRUCTURE harvester and CLUMPAK Delta K value estimated using Evano et al. (2005) method and Bayesian model-based estimation of population structure for 130 Ethiopian lowland bamboos ( O. abyssinica ) based on ISSR markers in thirteen pre-determined populations. ( A), ΔK = mean(|L”(K)|)/sd(L(K)). ΔK = 11 indicates the maximum K value; (B), rate of change of the likelihood distribution (mean); (C), mean of estimated Ln probability; (D), absolute value of the 2 nd order rate of change of the likelihood distribution (mean). ... 110

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LIST OF APPENDICES Appendix 1 : SNPs based AMOVA result using GenAlex ...... 142 Appendix 2: Some of Ethiopian lowland bamboo ( O. abyssinica ) sample collection sites. 143 Appendix 3: DNA Dragon sequence alignment and nucleotide peaks for one of cpDNA gene ndhF ...... 144 Appendix 4: MAFFT alignment...... 144 Appendix 5: MEGA realignment...... 145 Appendix 6: Sequence submission to NCBI via Sequin...... 145

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LIST OF ABBREVIATIONS AMOVA Analysis of molecular variance BLAST Basic local alignment search tool BPG Bamboo phylogeny group cpDNA Chloroplast DNA CE-EFRC Central Ethiopia Environment and Forest Research Center CTAB Cetyltrimethyl ammonium bromide CUI COMSATS University Islamabad Dx Average number of nucleotide substitution per site between populations FAO Food and Agricultural Organization GPS Global positioning system He Expected heterozygosity/Nei’s gene diversity Ho Observed heterozygosity I Shannon information index INBAR International network for bamboo and rattan InDel Insertion-Deletion ISSR Inter simple sequence repeats k Average number of nucleotide differences per-sequence MAFFT Multiple sequence alignment software MEGA Molecular evolutionary genetics analysis MP Maximum parsimony MUSCLE Multiple sequence comparison by log-expectation Na Number of alleles NCBI National Centre for Biotechnology Information Ne Number of effective allele NJ Neighbor joining PCoA Principal coordinate analysis RAPD Randoml amplified polymorphic DNA RFLP Restriction fragment length polymorphism θw Population mutation rates per 100 sites π(t) Nucleotide diversity per-site xiii

ABSTRACT Phylogenetic Relationships among Indigenous and Introduced Bamboo Species and Genetic Diversity Study of Ethiopian Lowland Bamboo [Oxytenanthera abyssinica (A. Rich.) Munro] Using cpDNA Genes (matK , ndhF and rps16 ) and ISSR Markers

Oumer Abdie Addis Ababa University, July 2020.

Bamboo is one of the most important non-timber forest resources with potential alternative to wood and wood product, and is recognized as one of fastest-growing plant in the world (100 cm per day). There are two indigenous woody bamboo species in Ethiopia: the highland bamboo (A. alpina ) and the lowland bamboo (O. abyssinica ). There are more than 40 species of bamboo introduced to this country and those are under multiplication in different sites together with previously introduced ones. Although bamboos have immense ecological and economic importance, scientific inquiry particularly on phylogenetics on indigenous vs introduced bamboos as well as genetic diversity on lowland bamboo in Ethiopia is lacking substantially. CTAB solution immersed and silica-gel dried young leaves from 31 species of bamboo and 13 populations of Ethiopian lowland bamboo ( O. abyssinica ) were collected for DNA extraction and PCR amplification. DNA of each site was isolated separately using a modified CTAB DNA isolation method. PCR products were analyzed using 1% agarose gel electrophoresis and purified and pair-end sequenced. Each of the sequences of amplified cpDNA alignments were used to calculate an average number of nucleotide differences (k), nucleotide diversity (π) and population mutation rates per 100 sites (θw), InDel (Insertion-Deletion), DNA divergence, gene flow and genetic differentiation and to construct network analysis, neighbor-joining (NJ), maximum parsimony (MP) and maximum likelihood (ML) trees. Each of the amplified ISSR fragments were used to study band pattern and heterozigosity, level of polymorphism, calculate marker efficiency, Nei`s genetic diversity (H), Shannon diversity index (I), analysis of molecular variance (AMOVA), analysis for cluster, principal coordinates (PCoA), and admixture results. The total sequence generated by cpDNA genes viz. matK , ndhF and rps16 were 1,790 for phylogenetics and 3,694 for genetic diversity study. In the aggregate cpDNA genes, average GC and AT content and total sequence was observed (66.49, 33.51 and 3508.41). Highest AT content (67.4) in G. ampelxifolia and least (66.2) in D. diannanesis was observed by the aggregate genes. cpDNA genes based phylogenetics study shows, mostly O. abyssinica was clustered with genus Bambusa whereas, A. alpina was clustered with genus Phyllostachys . Ethiopian lowland bamboo collected from Gambella region associated differently than other O. abyssinica samples and mostly it is associating with genus Bambusa and Gigantochloa . ISSR based phylogenetics also gives almost similar result with cpDNA genes with few inconsistencies to choose the closest taxa. Partitioning xiv of genetic diversity by analysis of molecular variance (AMOVA) using grouped populations revealed that out of the total genetic diversity, most of the ISSR diversity was distributed within the populations (61.05%), with the remaining diversity being distributed among groups (31.80%) and among populations within groups (7.15%) with F ST = 0.38949, FSC = 0.10486 and F CT = 0.31797. AMOVA with and without grouping revealed the same patterns of genetic diversity and support the larger genetic diversity found within the populations rather than among the populations and are similar to Shannon’s diversity index. Likewise, cluster analysis in all the cases grouped the populations into sharply distinct clusters, which could be attributed to cross pollination nature of the plant and long lived to the area. STRUCTURE analyses for all population gives a result of K = 2. In this study, we provide the first assessment of the phylogenetic relationships of the indigenous and introduced bamboo species and the first wide assessment of genetic diversity, population structure, and gene flow analysis of Ethiopian lowland bamboo (O. abyssinica) using cpDNA genes and ISSR markers. The closest bamboo species for indigenous Ethiopian bamboos were identified and the extent of genetic diversity, gene flow and population structure of O. abyssinica populations also examined. The closest species for lowland bamboo was B. lapidea and B. longinternode where as, highland bamboo was P. pubescenc and P. edulis . Ethiopian lowland bamboo collected from Gambella region associated differently than other O. abyssinica samples and mostly it is associating with genus Bambusa and Gigantochloa . Both cpDNA genes and ISSR markers show Metekel zone of B-Gumuz region was the most diversified population and needs more conservation attention. We believed this is important for understanding the plant's genetic diversity and structure for its conservation and management and to study the phylogenetic relationships of indigenous and introduced bamboo species.

Key words : Bamboo, cpDNA genes, evolutionary tree, gene flow and genetic differentiation, indigenous vs introduced bamboos, ISSR primers, Oxytenanthera abyssinica, population structure, phylogenetics.

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CHAPTER ONE

1. General Introduction

1.1. Background

Bamboo is a member of the grass family (i.e., Poaceae ) and constitutes a single subfamily

Bambusoideae with 121 genera and 1,662 species (Bamboo Phylogeny Group (BPG),

2012; Goyal et al., 2013; Chokthaweepanich, 2014; Canavan et al., 2016). It is one of the most important non-timber forest resources or a potential alternative to wood and wood product (Ekhuemelo et al., 2018) and fastest-growing plant in the world (100 cm per day)

(Zhang et al., 2002; Li et al., 2020).

Bamboo serves as an important part of nature-based development. Known in some parts of the world as “green gold”, “poor man’s timber”, this fast ‐growing grass plant covers over

31.5 million hectares (ha) of land across the tropics and subtropics. Bamboo plants has been proven to help combat a number of global challenges, including rural poverty, land degradation, deforestation, urban development, unsustainable resource use (or reducing pressure on forestry resources) and climate change (Yuen et al., 2017; Ekhuemelo et al.,

2018; Kaushal et al., 2018; Bau and Trinh, 2019). Two and half billion people are estimated to be directly involved in the production and consumption of bamboos (Scurlock et al.,

2000).

Bamboo a multi-purpose plant with over 10, 000 documented uses and applications, with rapid regeneration capacity and the possibility of annual harvesting within a few years of planting has significant advantages over the other forest species (Diver, 2006; Akinlabi et al., 2017). It has been also proven to address a number of global challenges and contributes to United Nations Sustainable Development Goals: SDG 1 (no poverty), SDG 7 (affordable and clean energy), SDG 11 (sustainable and resilient housing), SDG 12 (efficient use of resources), SDG 13 (address climate change); and SDG 15 (life on land) (Yuen et al., 2017;

Ekhuemelo et al., 2018; Kaushal et al., 2018; Bau and Trinh, 2019). Due to its potential for soil erosion and water recharge, bamboo also provides an opportunity for restoration of degraded areas and watershed development (Kaushal et al., 2019; Kaushal et al., 2020).

Furthermore, bamboo is an herbal medicine for a mild case patients for currently occurred

outbreak corona virus disease (COVID-19) (Xu and Zhang, 2020; Shahrajabian et al.,

2020), a food for humans (researcher observed youngsters collecting newly growing shoots

for food in Kemash, Yasso, Manbuk, and Guba districts and generally newly growing

shoots are common for human food consumption in Benishangul-Gumuz Region (BGR))

and feed and fodder for livestock, and it contributes to ensuring food security (Halvorson

et al., 2011; Choudhury et al., 2012; Nongdam and Tikendra, 2014; Mulatu et al., 2019;

Andriarimalala et al., 2019). Bamboo has huge economic potential; the global production

and local consumption are estimated at the USD 60 billions, and the international export is

valued at USD 2 billion per annum (International Network for Bamboo and Rattan

(INBAR), 2019).

Bamboo matures in 3 - 5 years and thereafter can be harvested annually for about 20 years

(Tariyal, 2016; Dalagnol et al, 2018) or longer, depending on the gregarious flowering period, after which bamboo dies. The bamboo gregarious flowering interval can be between 20 and 120 years, depending on the species (Bau and Trinh, 2019).

2

Bamboo plant grows naturally in areas receiving annual rainfall ranging from 1,200 to

4,000 mm, with an average annual temperature of 8 to 36 ° C. They also can grow well in different soil types, ranging rich alluvium to hard lateritic, sandy, and loamy soils. The multi - functional use of bamboo grass taking into account its rapid growth rates, resilience, and the possibility of multiple harvesting in a few years time are significant advantages over the other forest species (Diver, 2006; Akinlabi et al., 2017).

Most common and useful bamboos are those with “woody” (lignified) stems belonging to the tribes Bambuseae and Arundinarieae that show a wide geographical and altitudinal distribution. The roughly 1,300 woody bamboo species often play critical roles in maintaining the ecology of forest habitats and have great economic importance to humans

(Kelchner and BPG, 2013). Herbaceous bamboos (tribe Olyreae) differ from woody bamboos they have not or only weakly lignified culms, usually no culm leaves, and no outer ligules. In addition, they are less popularly known and they are found in tropical forests, predominantly in the New World (BPG, 2012; Kelchner and BPG, 2013).

Phylogeny is the descent history of a group of taxa such as species from their common ancestors including the branching order and even the divergence periods. The expression

"phylogeny" comes from a combination of Greek words. Phylon means "tribe" or "clan" or "race" and genesis mean "source" or "origin." It may have a meaning in genealogy of genes; derived from a common ancestral gene and in molecular phylogeny, the relationships among organisms or genes are studied by comparing DNA homologues or protein sequences. Dissimilarities among the sequences indicate genetic divergence as a

3 result of molecular evolution during the course of time. Major sources of information for molecular evolutions are; morphological characteristics of an organism in classical phylogenetics and nucleotide sequences of DNA, RNA and sequences of amino acids of a protein of molecular approaches. By comparing homologous molecules from different

organisms, it is possible to establish their degree of similarity thereby establishing or

revealing a hierarchy of relationship (Patwardhan et al., 2014).

Genetic diversity is crucial for the effective conservation, management, and efficient

utilization of plant genetic resources, basis of an organism’s ability to adapt to changes in its environment, and can be affected by many factors (Amos and Harwood, 1998).

Environmental (e.g. temperature and precipitation) and geographical (e.g. landscape, latitude, longitude and altitude) factors affect the species genetic diversity and population structure and individuals among populations (Wellenreuther et al., 2011; Pauls et al.,

2013).

1.2. Statement of the problem

The multipurpose function and use of bamboos has led to many species being intentionally moved outside of their native ranges (Canavan et al., 2016). Species movement is often

influenced by its direct human value (McKinney and Lockwood, 1999). Morphological

features have been shown to be significant in promoting the introduction of species (Pysek

and Richardson, 2007). Some traits at the introduction level may be of high value to

humans and thus influence the initial movement of these species into new ranges (Canavan et al., 2016).

4

Bamboos have seen a rise in popularity over the past few decades, driven largely by a view of certain species as wonderful plants or miracle crops, i.e., plants that are thought to be valuable in meeting current economic, environmental and social needs (Hoogendoorn and

Benton, 2014; Liese and Köhl, 2015). In addition, modern processing methods have expanded the product range that can be made from bamboo. Therefore, the rate of introduction and cultivation of species in new areas has increased; in particular, bamboo cultivation in response to increased global demand for timber products (Hunter, 2003;

INBAR, 2003). But out of 1,662 species in 121 genera of Bambusoideae, 232 species

(14%) have been introduced outside of their native ranges and 12 species (0.7%) (Figure

1-1) were found to be invasive (Canavan et al., 2016).

Figure 1-1: Invasive bamboo species and their associated region (Canavan et al., 2016).

5

Genetic erosion of bamboo and their wild relatives are accelerating at a high rate because of human activities such as deforestation, wild firing, overexploitation and introduction of exotic species without investigation and proper research on the potential impact of genetic pollution and general problems associated with transfer of exotic germplasm (Canavan et al., 2016). Ethiopia introduced around twenty-three new species of bamboo in two rounds since 2007. The first entries were by the Ministry of Agriculture and INBAR. Seven species of the 1st entries have been tested for their adaptability and growth performance in different locations without adequate studies and inquiry. The second entries that comprise sixteen species were introduced by Morel Agroindustries LTD. These species are under multiplication at Holetta and Gurd-shola nurseries of CE-EFRC, Addis Ababa (Yigardu et al., 2016). Generally, there are more than 40 species of bamboo introduced to the country and they are under multiplication in different places of the country together with previously introduced bamboo species. Pakistan has also three species that grows naturally and introduced twenty-five species of bamboo from Bangladesh, Thiland and China.

The study by Bystriakova et al. (2004), indicated that as many as half of the world`s woody bamboo species have become vulnerable to extinction as a result of massive forest destruction. The most important problems currently facing bamboos in Ethiopia are related to high abandonment of bamboo plant due to lack of sufficient knowledge on its biology and genetics, presence of high genetic erosion and destruction of the plant due to human activities (Grand Ethiopian Renaissance Dam (GERD) with catchment area of 172, 250 km 2 (Abtew & Dessu, 2019) is built primarily on major lowland bamboo growing areas of

Metekel Zone of BGR. The lack of research studies conducted in Ethiopia especially on

6 the phylogenetics of the introduced bamboo species, diversity and systematics of O.

abyssinica at DNA level prompted the commencement of this research. Therefore, for the present study, we sequenced coding ( matK and ndhF ) and non-coding ( rps16 ) regions of

cpDNA genes and we used 38 ISSR primers aiming to assess the genetic diversity, population structure, and gene flow analysis of Ethiopian lowland bamboo ( O. abyssinica )

collected from lowland bamboo growing areas of the country and to observe the phylogenetic relationships of 31 taxa of bamboos with the indigenous bamboos of Ethiopia.

1.3. Hypothesis

The following null hypotheses have been stated;

- There is a high phylogenetic relationship between introduced and Ethiopian

indigenous bamboo species.

- Ethiopian indigenous bamboo species is distinct as compared to the introduced.

- The sequence based cpDNA and ISSR markers show the same phylogenetics

pattern among introduced and indigenous bamboo species and identify the same

closest species to the Ethiopian bamboos.

- There is high genetic diversity within thirteen populations of Ethiopian lowland

bamboos ( O. abyssinica )

- Genetic distance goes with geographic distance

7

1.4. Objectives

1.4.1. General Objective

To investigate the phylogenetic relationship of the indigenous and introduced bamboo species, to assess the extent of genetic diversity and population structure of lowland bamboo populations and to generate information for conservation and sustainable use of bamboo resources in Ethiopia.

1.4.2. Specific objectives

- To investigate the phylogenetic relationship of the indigenous and introduced

bamboo species and identify closest species to the Ethiopian and Pakistani bamboos

using selected cpDNA genes.

- To investigate the genetic relationship of introduced and indigenous bamboo

species and identify closest species to the Ethiopian and Pakistani bamboos using

selected ISSR primers.

- To screen and develop polymorphic cpDNA genes and ISSR markers.

- To determine the level of genetic variation and its patterns of distribution that exist

within and among Ethiopian lowland bamboo populations using cpDNA genes and

ISSR primers.

- To design relevant recommendations on sustainable development and management

system regarding the phylogenetics on introduced bamboo species and genetic

diversity of Ethiopian lowland bamboo populations.

8

CHAPTER TWO

2. Literature Review

2.1. Taxonomy of Bamboo

Bamboo is an arborescent perennial, giant and wood like grass appears to be the most successful and diverse conspicuous group of plants belonging to order Poales, family

Poaceae (grass family), subfamily Bambusoideae and tribe Bambuseae (Ohrnberger, 1999;

Grass Phylogeny Working Group (GPWG), 2001; Bamboo Phylogeny Group (BPG),

2012; Goyal et al., 2013; Chokthaweepanich, 2014; Canavan et al., 2016; Vorontsova et al., 2016), encompassing 121 genera in ca. 1,662 species (Canavan et al., 2016;

Vorontsova et al., 2016) and 100 species are commercially cultivated around the world (Li et al., 2020).

.

Based on molecular and morphological characteristics, true bamboos (Bambusoideae) are greatly supported as a monophyletic lineage and categorized into three tribes (Figure 2:1):

Bambuseae (tropical woody bamboos), Arundinarieae (temperate woody bamboos) and

Olyreae (herbaceous bamboos) (Sungkaew et al., 2009; BPG, 2012; Kelchner and BPG,

2013; Saarela et al., 2018). The Bambuseae tribe differs from the Olyreae on the basis of

the presence of an abaxial ligules (Zhang and Clark 2000; Grass Phylogeny Working Group

(GPWG), 2001). Within the tribe Bambuseae, there are two clades comprising neotropical

woody bamboos (NWB) and paleotropical woody bamboos (PWB). The NWB clade is

composed of three subtribes: Guaduinae, Arthrostylidiinae, and Chusqueinae whereas

clade PWB has Bambusinae, Racemobambosinae, Melocanninae, and Hickeliinae sub-

tribes. The Olyreae contains three subtribes: Buergersiochloinae and Olyrinae Parianinae

9

(Clark et al., 2007; Sungkaew et al., 2009; BPG, 2012, Kelchner and BPG, 2013; Clark et al., 2015).

Figure 2.1-1: Subtribe relationships and geographic distributions of the four major lineages of bamboos based on plastid (chloroplast) DNA sequences from five loci: ndhF , rpl16 intron, rps16 intron, trnD–trnT intergenic spacer, and trnL–trnF intergenic spacer. (Kelchner and BPG, 2013).

2.2. Bamboo Cytogenetics, Ploidy Level and Genome Size

Chromosome records of woody bamboos show that seemingly consistent ploidy levels define each woody bamboo clade: PWB are mostly hexaploid; NWB, tetraploid; and the

Arundinarieae (temperate woody bamboos), also tetraploid. Woody bamboo genera have a typical basic chromosome number of x = 12, with the exception of Chusquea (x = 10)

(Pohl and Clark, 1992; Chen et al., 2004; Clark et al., 2010). The Ethiopian bamboos O.

10 abyssinica and Y. alpina has a chromosome number of 2n = 6x = 72 and 2n = 4x = 48

with basic chromosome number x = 6 and x = 4.

The previously reported higher number chromosome in bamboos was 2n = 108 recorded in Bambusa schizostachyoides (Kurz) Gamble (Sobita Devi and Sharma, 1993) followed by 2n = 104 in six Chinese species (Chen et al., 2004). But, 2n = 192 is the highest

chromosome number in the entire bamboo family reported for the first time in

Pseudoxytenanthera (Mathu et al., 2015).

Genome size assessments are useful in studying evolutionary and adaptation mechanisms.

Further, this information is pre-requisite for genome sequencing and analysis projects.

However, only 1 % of angiosperms have been investigated for DNA content estimations

(Bennett and Leitch, 1995). Moreover, such information is limited to only few species of bamboo. Flow cytometric studies explored genome size variation among temperate and

tropical bamboo species ranged from 2.04 Gb - 2.6 Gb in temperate and 1.14 Gb - 1.6 Gb

in tropical bamboo species (Gielis 1997). These inferences also suggest that polyploidy is

the imperative powerhouse in the evolution of woody bamboos. Recently, two independent

flow cytometric studies on 37 bamboo species (Kumar et al., 2011) and a tetraploid

Phyllostachys pubescens (Gui et al., 2007) showed that genome size in different bamboo

species ranges from 1.2 Gb to 2.9 Gb, which is slightly higher in range as compared to prior studies by Gielis (1997). Further, these estimates revealed that the genome sizes in bamboo species are more than three to seven folds larger than the genome sizes of

Nipponbare ( Japonica rice) and 10 - 24 times larger than Arabidopsis thaliana genome

11 size and much more smaller than bread wheat (allohexaploid 16 Gb) and durum wheat

(allotetraploid 11 Gb) species respectively (Ganal and Röder, 2007; Mayer et al., 2014).

2.3. Area Coverage and Geographical Distribution of Bamboo

Bamboo is widely distributed in the tropical, subtropical, and temperate countries in Asia,

Latin America, and Africa from sea level to highlands. (Figure 2-2) (BPG, 2012; GPWG

II, 2012; Kelchner and BPG, 2013). About 31.5 million hectares of the earth's surface is

covered by bamboos. The highest species richness is observed in Asia-pacific followed by

South America, while Africa has the least number of species (Bystriakova et al., 2003). It

has been reported that there are no native bamboo species in Europe and the Antarctica

(Zhao et al., 2018). According to the world bamboo resources assessment report, Ethiopia,

Kenya, and Uganda possess most of the bamboo resources in Africa (Lobovikov et al.,

2005; Zhao et al., 2018).

Figure 2.1-2: Worldwide distribution of bamboo. (A) Neotropical woody bamboos, (B) Temperate woody bamboos, (C) Paleotropical woody bamboos, and (D) Herbaceous bamboos (http://www.eeob.iastate.edu/bamboo/maps.html ).

12

2.3.1. Bamboo Distribution in Africa, Ethiopia and Pakistan

Africa has forty-three (43) species occurring on 1.5 million hectares. Of these, 40 are mainly found in Madagascar while the remaining three are in mainland Africa (Embaye,

2000). There are two indigenous woody bamboo species in Ethiopia: the African Alpine

Bamboo or highland bamboo (Yushane alpina K. Shumann Lin; synonym: Arundinaria alpina K. Schumann) and the monotypic genus lowland bamboo (Oxytenanthera

abyssinica A. Richard) Munro. These species occur in some other African countries, but nowhere other than the continent of Africa (Embaye, 2000; Ensermu et al., 2000). They

are indigenous to Ethiopia and endemic to Africa, confined to the sub-Saharan region

(Embaye, 2000). Ethiopia contributes to the leading coverage constituting more than 1.44 million hectares (Zhao et al., 2018). This constitutes about 67% of the total area of bamboo on the continent and 7% of the world (Embaye, 2000). The lowland bamboo (O. abyssinica ) in Ethiopia accounts for 85% of the total national coverage and the rest 15% is

covered by highland bamboo (A. alpina ) (Embaye, 2000; Embaye et al., 2003; FAO and

INBAR, 2005). The lowland bamboo covers a range of elevation between 540 to 1,750 m and highland bamboo at a higher elevation above 2,480 m (Zhao et al., 2018).

The major lowland bamboo (O. abyssinica) growing regions in Ethiopia are Benishangul -

Gumuz, Oromia, Gambella, Southern Nations Nationalities and Peoples (SNNPs),

Amhara and Tigray Regions. Benishangul - Gumuz Region (BGR) has 440,000 hectares of lowland bamboo (O. abyssinica ) which at present is mainly used for subsistence uses. The major African Alpine Bamboo (Y. alpina) growing regions in Ethiopia are Amhara, Oromia

13 and Southern Nations Nationalities and Peoples (SNNPs) and BGR (Embaye et al., 2003;

INBAR, 2010; Zhao et al., 2018).

Bamboos have limited diversity in Pakistan and all bamboo area is reported as private

(Lobovikov et al., 2007). Three species ( Arundinaria falcate, Bambusa bambos and

Dendrocalamus strictus ) grow naturally in Pakistan. The first one ( A. falcate ) grows in the

NW Himalayas at 1,200-2,000 m. It occurs in the undergrowth in forests of oak, firs and

mixed trees, usually on northern slopes or in ravines. It is part of a wider gene pool through

the Himalayas. It is used for making baskets, mats and pipes. The second species ( B.

bambos ) is extensively used for construction. The third species ( D. strictus ) is found in

Punjab and Kashmir. It is found also in mixed vegetation on Marghalla hills surrounding

Islamabad. It is used for construction and a variety of purposes. This forms part of a gene pool extending across Hindustan and usually growing below 1,200 m (FAO, 2006).

According to global forest resources assessment and INBAR (2005), Pakistan has introduced twenty-five species of bamboos. Twenty-one species were from Bangladesh and four species from Thiland and China. Bamboo plantations have been raised on good agricultural lands in Sargodha, Jhang, Khoshab and Mandibhaudin districts of Punjab province. Most of these plantations are on 0.5 acres of lands. In Chunian sub division of

Kasur district, smallholder farmers have also successfully established small bamboo groves of 4 - 10 acres area. Generally, in Pakistan the resources are shrinking and the plantation area increases or decreases with the market demand in the domestic as well as in the Middle East markets (FAO, 2006; Shah et al., 2013).

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2.4. Assessment of Phylogenetics and Genetic Diversity Study

Phylogenetics is the study of evolutionary relationships among biological entity - often species, individuals or genes (may be referred as taxa) and phylogeny is the history of descent of a group of taxa such as species from their common ancestors including the order of branching and sometimes the times of divergence (Patwardhan et al., 2014). In the

genealogy of genes it might have explanation; derived from a common ancestral gene and

in molecular phylogeny, the relationships among organisms or genes are studied by

comparing homologues DNA or protein sequences. Dissimilarities among the sequences

indicate genetic divergence because of molecular evolution during the course of time

(Vandamme, 2003). Morphological characteristics of an organism in classical phylogenetics and nucleotide sequences of DNA, RNA and amino acids of a protein of

molecular approaches are major sources of information (Vandamme, 2003; Page and

Holmes, 2009; Patwardhan et al., 2014).

Determining phylogenetic relationship between different organisms is a difficult task as

the living world experiences incredible complexity with respect to its species material. This

diversity is not only reflected in phenotypic characters but also in ultra-structural, biochemical and molecular features. Phenotypically similar organisms may have distinct biochemical and molecular features. To understand and express biological terms, has to

know the organism’s evolutionary history since it is the result of an evolutionary process

(Patwardhan et al., 2014).

15

Molecular genetics research and assessment of genetic diversity and population structure is a prerequisite to promote genetic, evolutionary, functional studies of plants to have a comprehensive understanding of the biology and other key characteristics that enable to properly exploit plant resources in general and bamboo in particular (Das et al., 2008; Sui

et al., 2009; Peng et al., 2013). Genetic diversity and population structure within different populations of a particular species is the main building block for understanding

evolutionary and speciation aspects of that species. In addition, genetic diversity is the basis of an organism’s ability to adapt to changes in its environment, crucial for the

effective conservation, management, and efficient utilization of plant genetic resources and can be affected by many factors (Amos and Harwood, 1998). Geographical (e.g. landscape, latitude, longitude and altitude) and environmental (e.g. temperature and precipitation) factors affect the genetic diversity and population structure of a species and the individuals among populations (Wellenreuther et al., 2011; Pauls et al., 2013).

Genetic markers are important developments in the field of plant breeding and conservation

(Kebriyaee et al., 2012). Genetic marker is a morphological trait or gene or DNA sequence with a known chromosome location controlling a particular gene or trait. Genetic markers are closely related with the target gene and they act as sign or flags ( Collard et al., 2005) .

Genetic markers are broadly grouped into two categories: classical markers and

DNA/molecular markers. Morphological, cytological and biochemical markers are types

of classical markers. For the advancement and widely used molecular marker, one of the breakthroughs in biological sciences in general and molecular research in particular, is the

16 invention of Polymerase Chain Reaction (PCR) that amplifies DNA in vitro (Mullis and

Faloona, 1987). Since then, molecular marker techniques were grouped into non-PCR based and PCR-based, depending on the requirement of PCR or not to produce different

DNA fragments. Molecular markers are fragments or nucleotide sequences that can be investigated through the polymorphism present between the fragment and nucleotide sequences of different individuals. Insertion, deletion, point mutations duplication and translocation are basis of these polymorphisms; however, they do not necessarily affect the activity of genes.

An ideal DNA marker should be co-dominant, evenly distributed throughout genome, highly reproducible and having ability to detect higher level of polymorphism (Mondini et

al., 2009). Some examples of DNA markers that used for phylogenetics and genetic

diversity study are restriction fragment length polymorphism (RFLP), amplified fragment

length polymorphism (AFLP), simple sequence repeats (SSRs), inter simple sequence repeats (ISSRs), and single-nucleotide polymorphisms (SNPs) (Jiang, 2013).

Among molecular techniques used for phylogenetics and genetic diversity study, cpDNA genes are more common ( Qiang et al., 2005; Triplett et al., 2010; Goh et al., 2010;

Chokthaweepanich, 2014; Kelchner and BPG, 2013). ISSR markers are also used for phylogenetics and genetic diversity study of some bamboos (Wang et al., 2009; Mukherjee et al., 2010; Desai et al., 20015; Goyal and Sen, 2015).

17

2.4.1. Chloroplast Genes Based Phylogenetics and Genetic Diversity Study

Most molecular phylogenetic and genetic diversity studies on bamboos have utilized nuclear and/or plastid DNA sequences. Single-locus DNA regions were employed by the earlier phylogenetic studies, e.g., those using the cpDNA rpl 16 intron for the

Bambusoideae group in Poaceae (Zhang and Clark, 2000), for Chusquea (Kelchner and

Clark, 1997), and those using the nrITS region for Bambusa (Sun et al., 2005) and for

Alpine woody bamboos (Guo et al., 2001; Zhang et al., 2019). More recently, investigations have utilized combined DNA datasets from multiple DNA regions. This includes potentially more informative characters for resolving phylogenetic relationships at lower taxonomic levels, because different DNA regions evolve at different rates and could be helpful in resolving different parts of the phylogeny. A variety of studies have also revealed that multi-gene analysis provides better resolving power in phylogenetic studies of woody bamboos (Yang et al., 2007; Yang et al., 2008; Fisher et al., 2009;

Sungkaew et al., 2009; Yang et al., 2010; Triplett and Clark, 2010; Zeng et al., 2010).

Chloroplast or plastid is a cellular organelle resulting from endosymbiosis between independent living cyanobacteria and a non-photosynthetic host ~1.5 billion years ago

(Dyall et al., 2004). Each has its own genome that is usually non-recombinant and uniparentally inherited (Birky, 1995). Chloroplast genome of most higher plant have conserved quadripartite structure, consisting two copies of a large inverted repeat (IR) and two sections of unique DNA, which are referred to as the ‘‘large single copy regions

(LSC)’’ and ‘‘small single copy regions (SSC)’’ (Jansen et al., 2005).

18

Chloroplast DNA sequence and its characteristic for phyllogenetic and population genetics study is well known and strongly preferable due to its relative small size (compared to mitochondria and nuclear genome (Wagner, 1992)) and conserved region property (Kim et al., 1999; Chokthaweepanich, 2014; Attigala, 2015). In its evolution, it is assumed to be

conserved in terms of nucleotide substitution with very few rearrangements that allow the

molecule to be used to solve phylogenetic relations and taxonomic annomalies, especially

at deep levels of evolution (Kim et al., 1999).

The focus of plant molecular systematics has shifted towards to more rapid development of cpDNA loci. Simple genetics property, high copy within typical genomic DNA and structural stability makes cpDNA preferable for evolutionary and population genetics studies in many plants since it has protein-coding genes ( matK , ndhF , etc), introns ( trnL ,

rpll6 , rps16 , etc) and intergenic spacer (intergenic spacers between rbcL and atpB , trnT and trnL , trnL and trnF ) regions (Scarcelli et al., 2011; Daniell et al., 2016). As the evolutionary rates of cpDNA with nucleotide substitutions and structural changes are highly conserved (Soltis et al., 2004), both coding and non-coding cpDNA regions are used

to elucidate genetic diversity and population structure, the evolutionary relationships at the

generic and higher taxonomic levels (Shaw et al., 2007; Shaw et al., 2014).

In most angiosperms, matK gene is about 1,515 bp long within the trnK intron, and

functionally may be involved in splicing group II introns (Hilu et al., 1999). This gene's

effective application in plant systems has already been documented on phylogenetics and evolution of woody bamboo, phylogeny of legumes, Saxifragaceae, etc (Johnson and

19

Soltis, 1994, Wojciechowski et al., 2004, Chokthaweepanich, 2014). MatK is known to have relatively high rates of substitution compared to other chloroplast genes (Johnson and

Soltis, 1994). This gene exhibits a relatively high proportion of transversions and the 3' region of its open reading frame (ORF) has been shown to be extremely useful in resolving sub familial and to a certain degree tribal relationship in Poaceae.

The NADH dehydrogenase subunit F ( ndhF ) 3' end gene is ~1,140 bp long cpDNA coding region (Chokthaweepanich, 2014) and in most angiosperms, the ndh proteins associate the

NADH dehydrogenase like complex with nuclear-encoded subunits. This protein complex links with photosystem I for becoming a super-complex that mediates cyclic electron transport, produces ATP to adjust the ATP/NADPH proportion and facilitates chlororespiration when cyclic electron transport pauses during the night (Lin et al.,

2015).

The rps16 gene is a non - coding region of ~860 bp long cpDNA encoding the ribosomal protein S16 and is present in the chloroplast genome of most higher plants (Oxelman et al.,

1997; Chokthaweepanich, 2014).

20

Figure 2.1-3: Schematic gene map representation of some woody bamboo chloroplast genomes ( Zhang et al., 2011; Wu et al., 2015). Inner thick arcs represent the inverted repeat regions (IRA; IRB), large and small single copy (LSC; SSC) region. Genes inside and outside of the circle are transcribed clockwise and counterclockwise and colored according to their functional groups. *: genes used for the study.

Some of these cpDNA markers have been used on crops and trees of Ethiopian origin. To cite few, Coffea spp. (Tesfaye et al., 2007); Guizotia abyssinica (Geleta et al., 2010);

Ensete and Musa species (Bekele and Shigeta, 2011); Cordia Africana (Derero et. al.,

2011); Lobelia (Kebede et al., 2007; Geleta and Bryngelsson, 2012).

21

2.4.2. ISSR Based Phylogenetics, Genetic Diversity and Population Structure Study

An ISSR primer is typically 16 - 25 nucleotides in length and comprises mainly, or solely, of repeated DNA motifs (2 - 5 bp each) intended to be complementary to microsatellite regions in the genome. Depending on the implimentation, there are 3 forms of ISSR primers: (1) unanchored (primer consists only of a repeated motif, e.g. 5'-(AC) 8-3'), (2) 5'- anchored (primer consists of a repeated motif with one or several non-motif nucleotides at the 5'-end, e.g. 5'-GA(AC) 8-3'), and (3) 3'-anchored (primer consists of a repeated motif

with one or several non-motif nucleotides at the 3'-end, e.g. 5'-(AC) 8 AG-3') (Ng and Tan,

2015).

ISSR primers are used to study the phylogenetics and genetic diversity of different species of plants either in combination with other markers or solely. But the use of ISSR markers in bamboo in general and in O. abyssinica in particular is limited or none. The use of SSR

markers is limited by their lack of availability in bamboo; nevertheless, they have been

successfully applied to Phyllostachys (Lai and Hsiao 1997). Phylogenetics study of 22 taxa of bamboos using 12 ISSR primers (Mukherjee et al., 2015) and phylogenetics study of 29

species of bamboo using 16 ISSR primers (Goyal and Sen, 2015) are among the studies

used ISSR primers for phylogenetics study in bamboo.

These markers have been in use to study various crops and cereals of Ethiopian origin but few number of researches on trees and forest plants; to mention few, Eragrostis tef (Assefa et al., 2003); Wheat (Hailu et al., 2005); Hagenia abyssinica (Feyissa et al., 2007); Coffea

(Aga et al., 2005; Tesfaye et al., 2014); Rice (Girma et al., 2010); Enset ( Tobiaw and

22

Bekele, 2011; Getachew et al., 2014 ); Sesame (Admas et al., 2013; Abate et al., 2015;

Woldesenbet et al., 2015); Anchote (Bekele et al., 2014); White lupine (Oumer et al.,

2015); Black cumin (Birhanu et al., 2015); Sorghum (Teshome and Feyissa, 2013).

2.5. Phylogenetic Tree Construction Methods

The phylogenetic tree can be constructed by distance or character-based methods. Distance method transforms the sequence data into pair wise distances and then uses the matrix during tree building by ignoring characters. ME (minimum evolution) (Rzhetsky & Nei,

1993), NJ (neighbor joining) (Saitou & Nei, 1987), UPGMA (unweighted paired group method with arithmetic mean) (Murtagh, 1984) and FM (Fitch-Margoliash) (Fitch &

Margoliash, 1967) are among most commonly used distance-based methods. Character based method uses the aligned sequences directly during tree inference and optimizes the distribution of the actual data pattern for each character. Maximum Parsimony (MP)

(Sober, 1983) and Maximum Likelihood (ML) methods (Felsenstein, 1981) are among the most used character-based methods (Roy et al., 2014).

Computational speed, factual consistency of phylogenetic trees, consistency of evaluated topology, likelihood of getting the right topology, unwavering quality of assessed branch length, and so forth are among those criteria's relying upon which can think about various set up tree-building techniques (Roy et al., 2014). Based on computational speed and other parameters, NJ strategy from distance based is the prevalent one from other tree-building strategies which are at present being used. This method can handle a large number of sequences with bootstrap tests with ease whereas MP and ML from character based and

23

ME from distance-based methods examine all possible topologies searching for the MP,

ML and ME trees. In the case of ME, simplified advanced algorithms have been developed

that are efficient in time scales to obtain the correct tree and for MP methods, when the

number of sequences is relatively high, the branch and bound method is often used (Roy et

al., 2014; Binet et al., 2016).

During the estimation of distance through substitution, NJ and ME strategies are discovered

consistent for estimating trees but MP is often inconsistent (Roy et al., 2014; Binet et al.,

2016). Alternatively, from character-based methods ML methods have the added benefit

of being more flexible in the choice of the evolutionary model. But this method is lengthy

and time consuming (Roy et al., 2014; Binet et al., 2016). The algorithms used to create phylogenetic trees with phylogenetic characters are generally more complex than distance- based methods (Scott & Gras, 2012).

24

CHAPTER THREE

3. Phylogenetic Relationships among the Indigenous and Introduced

Bamboo Species using cpDNA Genes Sequences

3.1. Materials and Methods

3.1.1. Plant Materials and Sample Collections

Young fresh leaves of three individual plants from 31 species of woody bamboo (two

Ethiopian indigenous bamboo species, twenty seven introduced woody bamboo species from central Ethiopia environment and forest research center (CE-EFRC) and two from

Pakistan woody bamboo species) were collected for the study (Table 3-3). The leaves were immersed in 15ml falcon tube containing 2% CTAB solution.

3.1.2. DNA Extraction and Primer Screening

Three independent leaf materials from each species were used for DNA isolation. DNA was isolated separately using a modified CTAB DNA isolation method (Hyder et al., 2007) at the Biochemistry, Molecular Biology and Biotechnology (BMBB) laboratory,

Department of Biosciences, COMSATS University Islamabad (CUI), Pakistan. Test gel electrophoresis in 1% agarose and nanodrop (Implen Nanophotometer 190-1100nm spectrophotometer) of each sample was used to measure DNA quantity and quality. Those with high DNA quantity and quality were used for PCR amplification. Among ten primers selected from Chokthaweepanich (2014) and Attigala (2015) and designed via Primer3

(http://bioinfo.ut.ee/primer3-0.4.0/ ), three chloroplast sequences with coding ( matK and ndhF ) and non-coding ( rps16 intron) were PCR amplified (Table 3-1).

25

Table 3-1: cpDNA primer sequences, their approximate amplified size and PCR profile. Amplification PCR Profile Primer Amplified Primer Sets pattern (All end with name size (bp) 4ºC hold) matK F: CGT TCT GAC CAT ATT GCA CTA TG ~1,350 Excellent 96 °C, 3 min.; R: AAC TAG TCG GAT GGA GTA G 35X (96 °C, 30 ndhF F: GTC TCA ATT GGG TTA TAT GAT G ~1,140 Excellent sec., 53, 30sec., (3'end) R: CCC CCT AYA TAT TTG ATA CCT TCT CC 72 °C 1 min.); rps 16 F:AAA CGA TGT GGT ARA AAG CAA C ~860 Excellent 72 °C, 20 min. R:AAC ATC WAT TGC AAS GAT TCG ATA rpl16 F: GCTATGCTTAGTGTGTGACTCGTTG ~ 1,100 R: CGTACCCATATTTTTCCACCACGAC trnD- F: ACCAATTGAACTACAATCCC ~ 1,100 trnT R: CCCTTTTAACTCAGTGGTA trnT- F: CATTACAAATGCGATGCTCT ~ 880 trnL R: TCTACCGATTTCGCCATATC matKO ~ 1,754 F: CGTCTACCCACTTCTCTTTCAGG R: GGGTTCACCAGGTCATTGATAC psbA ~610 F: GGAAGGAAAGCCAGAAATACCC R: ACAATCCAC TGCCTTGATCC KUN ~1,215 F: CAGAACAACCGTACGTGAGC R: TTCCAGGAGAGATCCTGAGC bad amplificationpattern. GPA1 ~1,155 F: GCTCAAGGGTTACAACTGAAGTCC R: CGCACCTCCAGATCATAAGC Rejected due to andnon reproducible

3.1.3. PCR Product Profiling, Sequencing and Alignment

PCR reaction (50µl per reaction) and amplification contained 7.50µlof 50 - 100ng/µl template DNA, 5.0µl Taq buffer (100mM Tris-HCl, 500mM KCl, 15mM MgCl 2, pH 8.5

(25 oC), 5.0µl dNTPs mix (2.5mM each), 2.5µl Taq DNA Polymerase (5U/µl) (WizPure™

Taq DNA Polymerase), 1.25µl 25pM of each primer and 28.75µl of PCR grade H 2O. The thermal profile for all primer sets included pre-PCR denaturation at 96°C for 3 min. followed by 35 cycles of denaturing at 96°C for 30 seconds, annealing at 53°C for 30 seconds, extension at 72°C for 1 min. a final extension at72°C for 20 min. and hold at 4°C.

3.0µl PCR products were analyzed using standard 1% agarose gel electrophoresis and purified and paired-end sequenced at commercial sequencing facility of Macrogen, Inc.

(Seoul, Korea).

26

The sequence of both strands of every fragment amplified from each sample was assembled separately using DNA Dragon version 1.6.0 and each district was represented by a single sequence with the one very identical and informative among the triplicate samples. The assembled sample was submitted to the GenBank and used for sequence analysis. BLAST searches for each target sequence were used to confirm probable homology (Query cover,

Identity percentage, E-value and Direction of the strand).

Sequences of three genes from thirty one taxa together with nine reference sequences retrived from NCBI were arranged in FASTA format and aligned in MAFFT (multiple sequence alignment software version 7) (Katoh and Standley 2013) and realigned again using MEGA version 7.0 to increase the quality of final alignment product. Sequence information for submission to NCBI was prepared by bankit

(https://www.ncbi.nlm.nih.gov/WebSub/ ) and Sequin v5.51. An accurate and complete

GenBank record or accession number is described in Table 3-2.

3.1.4. Phylogenetics Analyses

The three markers ( matK, ndhF and rps16 ) were analyzed separately and then combined into a single data set. The sequence alignments with MUSCLE (multiple sequence comparison by log-expectation) were used to identify the best nucleotide substitution model and construct MP and ML tree using MEGA 7.0 (Tamura et al., 2013).

To construct MP tree, bootstrap analysis with 1000 replicates was conducted to estimate nodal support. The percentage of replicate trees in which the associated taxa clustered

27 together in the bootstrap test greater than 50% was placed on the branches (Felsenstein,

1985) (Felsenstein 1985). The MP tree was obtained using the Subtree-Pruning-Regrafting

(SPR) algorithm (Nei & Kumar, 2000) with search level 1 in which the initial trees were obtained by the random addition of sequences (10 replicates). The tree is drawn to scale, with branch lengths calculated using the average pathway method and are in the units of the number of changes over the whole sequence. The analysis involved 40 nucleotide sequences. All positions containing gaps and missing data were eliminated.

In the case of ML tree construction method, initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach, and then selecting the topology with superior log likelihood value. The analysis involved

40 nucleotide sequences. All positions containing gaps and missing data were eliminated.

Evolutionary analyses were conducted in MEGA7 (Kumar et al., 2016).

Neighbor-joining (NJ) tree analyses with each separate and combined cpDNA genes were conducted using the Kimura’s two-parameter distance correction mode to construct a phylogenetic tree. The evolutionary distances were computed using the Maximum

Composite Likelihood method (Tamura & Nei, 1993) and are in the units of the number of base substitutions per site. The analysis involved 31 samples of target sequences plus 9 references from NCBI nucleotide sequences. All positions containing gaps and missing data were eliminated. Evolutionary analyses were conducted in MEGA7 (Kumar et al.,

2016).

28

3.2. Results

3.2.1. Chloroplast DNA Sequence Character and Sequence Divergence

3.2.1.1.GC and AC content analysis

GC and AT content of each and aggregate cpDNA genes were analyzed (table 3-2). Highest

AT content (67.4) in G. ampelxifolia and least (66.2) in D. diannanesis was observed by the aggregate genes while the GC content was highest (34.2) in D. diannanesis and the least was observed in G. ampelxifolia (32.6). Average GC and AT content and total sequence was observed (66.49, 33.51 and 3612.58) in the aggregate cpDNA genes respectively.

Highest AT content using matK gene was observed in G. ampelxifolia (67.7) and the least by D. diannanesis (65.8). Highest AT content (67.0) in D. brandisii and least (66.2) in G. atter, B. vulgaris (Green), P. pubescens and A. alpine (Eth_HB) was observed by ndhF gene. Wheras the highest AT content using rps16 gene was observed in G. ampelxifolia

(66.3) and the least by B. vulgaris (Green), P. pubescens, B. multiplex, D. membranaceus

Cx Grandis, G. angustifolia and B. chungii (Pks_WB) (65.7). Species that has highest AT

content percentage will have least GC content and vise versa.

Ethiopian lowland bamboo observed to have (66.3, 33.7 and 3661) GC and AT content and

total sequence and highland bamboo observed (66.5, 33.5 and 3573) GC and AT content

and total sequence. Result of GC and AT content on Ethiopian bamboos were not far from

the average but total sequence was observed higher in lowland bamboo.

29

Table 3-2: GC and AT content of each and aggregate cpDNA genes. matK (~ 1,350 bp) ndhF (~ 1,140 bp) rps16 (~ 860 bp) Aggregate genes Name of the species Percentage Total Percentage Total Percentage Total Percentage Total AT GC Sequence AT GC Sequence AT GC Sequence AT GC Sequence G. sumatra (Black) 66.4 33.6 1766.0 66.5 33.5 1046.0 65.8 34.2 860.0 66.5 33.5 3601.0 D. latiflorus 66.2 33.8 1766.0 66.7 33.3 1044.0 65.8 34.2 860.0 66.4 33.6 3664.0 G. ampelxifolia 67.7 32.3 1773.0 66.9 33.1 1044.0 66.3 33.7 860.0 67.4 32.6 3616.0 G. apus 66.2 33.8 1766.0 66.6 33.4 1044.0 66.0 34.0 860.0 66.4 33.6 3675.0 P. dulcis 66.2 33.8 1766.0 66.6 33.4 1044.0 66.0 34.0 860.0 66.5 33.5 3667.0 G. atter 66.4 33.6 1766.0 66.2 33.8 1044.0 65.8 34.2 843.0 66.3 33.7 3662.0 D. barbatus 66.1 33.9 1766.0 66.6 33.4 1044.0 65.9 34.1 860.0 66.3 33.7 3671.0 B. polymorpha 66.4 33.6 1766.0 66.6 33.4 1044.0 65.9 34.1 860.0 66.5 33.5 3655.0 D. diannanesis 65.8 34.2 1765.0 66.8 33.2 1044.0 65.8 34.2 860.0 66.2 33.8 3661.0 D. fuminesis 66.1 33.9 1766.0 66.7 33.3 1044.0 65.9 34.1 860.0 66.4 33.6 3622.0 D. asper 66.1 33.9 1766.0 66.6 33.4 1044.0 65.8 34.2 860.0 66.4 33.6 3652.0 B. vulgaris (Green) 66.5 33.5 1766.0 66.2 33.8 1044.0 65.7 34.3 860.0 66.4 33.6 3651.0 P. pubescens 66.5 33.5 1775.0 66.2 33.8 1044.0 65.7 34.3 843.0 66.4 33.6 3600.0 G. sumatra (Green) 66.5 33.5 1766.0 66.5 33.5 1044.0 65.8 34.2 860.0 66.6 33.4 3628.0 B. oldhamii 66.5 33.5 1766.0 66.6 33.4 1044.0 65.8 34.2 860.0 66.5 33.5 3652.0 D. gigantus 66.3 33.7 1766.0 66.6 33.4 1044.0 65.9 34.1 860.0 66.5 33.5 3607.0 B. multiplex 66.3 33.7 1763.0 66.4 33.6 1044.0 65.7 34.3 860.0 66.6 33.4 3538.0 D. hamilitonis 66.2 33.8 1766.0 66.6 33.4 1044.0 65.9 34.1 860.0 66.4 33.6 3581.0 A. alpine (Eth_HB) 66.5 33.5 1775.0 66.2 33.8 1044.0 65.8 34.2 843.0 66.5 33.5 3573.0 D. sinicus 66.2 33.8 1766.0 66.8 33.2 1044.0 65.9 34.1 860.0 66.5 33.5 3544.0 D. membranaceus Cx Grandis 66.2 33.8 1766.0 66.7 33.3 1044.0 65.7 34.3 860.0 66.5 33.5 3583.0 D. laosenesis 66.5 33.5 1766.0 66.5 33.5 1044.0 65.8 34.2 860.0 66.5 33.5 3569.0 B. vulgaris (Yellow) 66.5 33.5 1766.0 66.5 33.5 1042.0 65.8 34.2 860.0 66.5 33.5 3573.0 B. tulda 66.3 33.7 1766.0 66.7 33.3 1044.0 65.9 34.1 861.0 66.5 33.5 3635.0 D. brandisii 66.4 33.6 1766.0 67.0 33.0 1044.0 66.1 33.9 861.0 66.7 33.3 3621.0 G. angustifolia 66.6 33.4 1770.0 66.7 33.3 1044.0 65.7 34.3 860.0 66.5 33.5 3661.0 B. longinternode 66.6 33.4 1764.0 66.8 33.2 1044.0 65.9 34.1 860.0 66.6 33.4 3622.0 B. lapidea 66.4 33.6 1766.0 66.8 33.2 1044.0 65.9 34.1 861.0 66.6 33.4 3586.0 O. abyssinica (Eth_LB) 66.5 33.5 1766.0 66.8 33.2 1044.0 65.8 34.2 859.0 66.5 33.5 3661.0 P. nigra (Pks_BB) 66.2 33.8 1775.0 66.5 33.5 1001.0 65.8 34.2 860.0 66.3 33.7 3629.0 B. chungii (Pks_WB) 66.1 33.9 1766.0 66.9 33.1 985.0 65.7 34.3 861.0 66.3 33.7 3609.0 Average 66.4 33.6 1767.0 66.6 33. 4 1040.7 65.9 34.1 858.5 66.49 33.51 3612.58

30

3.2.2. Phylogenetic Inference and Relationship

3.2.2.1.Maximum Parsimony Method Phylogenetics Tree Construction

The evolutionary history was inferred using the Maximum Parsimony method. Tree #1 out of 8 most parsimonious trees (length = 144) is shown (figure 3-1). The consistency index is (0.674), the retention index is (0.854), and the composite index is 0.682 (0.576) for all sites and parsimony-informative sites (in parentheses). Ethiopian lowland bamboo ( O. abyssinica ) clustered with B. lapidea and B. longinternode with tree suppor of 80%.

Highland bamboo ( A. alpina ) observed to cluster with P. pubescence and P. edulis (known as Chinese moso bamboo) with 56% support and with G. atter 99% support.

71 B. vulgaris (Green) B. multiplex B. emeiensis (NC 015830.1) 84 B. oldhamii (NC 012927.1) B. multiplex (NC 024668.1) G. angustifolia G. sumatra (Green) D. laosenesis B. arnhemica (NC 026958.1) B. vulgaris var. striata (Yellow) 62 B. oldhamii G. sumatra (Black) B. bambos BI-1 (NC 026957.1) O. abyssinica 80 B. longinternode 81 B. lapidea B. polymorpha G. ampelxifolia 100 G. angustifolia (NC 029749.1) D. latiflorus D. diannanesis D. barbatus 51 D. brandisii P. dulcis D. sinicus D. gigantus D. membranaceus D. latiflorus (NC 013088.1) D. hamilitonis Neohouzeaua sp. (NC 026963.1) G. apus D. fuminesis 77 D. asper B. tulda A. alpina 56 P. pubescens 99 P. edulis (NC 015817.1) 76 G. atter P. nigra-(Pks-02) 99 B. chungii-(Pks-01) Figure 3-1: MP revealed genomic relationships among 31 taxa of Bambusoideae along with reference sequences (with accession numbers starting from “NC”) from NCBI using matK, ndhF and rps16 genes of cpDNA. The indigenous bamboo species are written in red font color and pointed with arrow. 31

3.2.2.2.Maximum Likelihood Method Phylogenetics Tree Construction

The evolutionary history was inferred by using the Maximum Likelihood method based on the Tamura-Nei model (Tamura and Nei 1993). The tree with the highest log likelihood (-

3448.22) is shown (figure 3-2). The percentage of trees greater than 50% in which the associated taxa clustered together is shown next to the branches. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. Except the percentage difference on tree support, ML method also provides similar result for Ethiopian bamboos.

61 B. vulgaris (Green) B. multiplex 78 B. multiplex (NC 024668.1) B. emeiensis (NC 015830.1) B. oldhamii (NC 012927.1) B. bambos BI-1 (NC 026957.1) O. abyssinica 64 B. lapidea 76 B. longinternode B. polymorpha D. laosenesis G. sumatra (Green) G. sumatra (Black) B. oldhamii B. vulgaris var, striata (Yellow) B. arnhemica (NC 026958.1) G. angustifolia B. tulda 100 G. ampelxifolia 63 G. angustifolia (NC 029749.1) D. brandisii D. barbatus D. diannanesis 68 D. fuminesis D. asper D. gigantus D. membranaceus D. sinicus P. dulcis D. latiflorus G. apus Neohouzeaua sp. (NC 026963.1) D. hamilitonis D. latiflorus (NC 013088.1) B. chungii-(Pks-02) P. nigra-(Pks-01) 99 G. atter 81 A. alpina 99 P. pubescens 61 P. edulis (NC 015817.1)

0.002 Figure 3-2: ML revealed genomic relationships among 31 taxa of Bambusoideae along with reference sequences using matK , ndhF and rps16 genes of cpDNA. The indigenous bamboo species are written in red font color and pointed with arrow.

32

3.2.2.3.Neighbor-Joining Method Phylogenetics Tree Construction

The evolutionary history was inferred using the Neighbor-Joining method (Saitou & Nei,

1987). Each cpDNA genes were analyzed to see their effectiveness in phylogenetics study of 31 taxa of woody bamboos (figure 3-3 to figure 3-5). According to independent cpDNA genes, matK (figure 3-3) and rps16 (figure 3-5A) genes showed better phylogenetic tree as

of the aggregate genes (figure 3-5B) than ndhF (figure 3-4A). Coding cpDNA genes ( ndhF together with matK ) mixed different taxa in different positions but non-coding region rps16 alone shows a better result than the coding and similar phylogenetic tree with the cumulative cpDNA genes.

For the cumulative cpDNA genes, the optimal tree with the sum of branch length = 0.079 is shown (Figure 3-5B). The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) are shown next to the branches

(Felsenstein, 1985). The tree is drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree.

Again, like the result of MP and ML, NJ also shows Ethiopian lowland bamboo ( O. abyssinica ) clustered with B. lapidea and B. longinternode with tree suppor of 66%.

Highland bamboo ( A. alpina ) observed to cluster with P. pubescence and P. edulis with

74% support and with G. atter 99% support.

33

B.vulgaris-(Green) 68 B. multiplex 77 B. multiplex (NC 024668.1) B. oldhamii (NC 012927.1) B. emeiensis (NC 015830.1) O. abyssinica B. longinternode 66 73 B. lapidea B. polymorpha B. bambos BI-1 (NC 026957.1) D. laosenesis G. sumatra-(Green) G. sumatra (Black) B. oldhamii B. vulgaris-striata-(Yellow) G. angustifolia B. arnhemica (NC 026958.1) B. tulda D. barbatus D. gigantus D. diannanesis 68 D. fuminesis D. asper Neohouzeaua sp. (NC 026963.1) G. apus P. dulcis D. hamilitonis D. latiflorus D. membranaceus D. sinicus D. latiflorus (NC 013088.1) B. chungii-(Pks-02) P. nigra-(Pks-01) 99 G. atter 67 A. alpina 99 P. pubescens 74 82 P. edulis (NC 015817.1) D. brandisii G. ampelxifolia 100 G. angustifolia (NC 029749.1)

0.002 Figure 3-3: NJ revealed genomic relationships among 31 taxa of Bambusoideae along with reference sequences using matK gene of cpDNA. The indigenous bamboo species are written in red font color and pointed with arrow.

34

B. tulda 100 G. ampelxifolia Neohouzeaua sp. (NC 026963.1) 99 G. angustifolia (NC 029749.1) D. hamilitonis 70 D. brandisii D. gigantus 33 G. angustifolia D. asper O. abyssinica D. fuminesis B. longinternode 3199 D. barbatus 79 B. lapidea P. dulcis D. laosenesis G. apus G. sumatra-(Green) D. latiflorus 37 B. oldhamii D. membranaceus 16 G. sumatra (Black) D. diannanesis 30 B. vulgaris-striata-(Yellow) D. latiflorus (NC 013088.1) B. arnhemica (NC 026958.1) D. sinicus B. polymorpha B. polymorpha B. bambos BI-1 (NC 026957.1) B. emeiensis (NC 015830.1) B. bambos BI-1 (NC 026957.1) 9052 B.vulgaris-(Green) B.vulgaris-(Green) 72 B. emeiensis (NC 015830.1) B. oldhamii (NC 012927.1) 42 B. multiplex 100 P. nigra-(Pks-01) 40 B. chungii-(Pks-02) 54 B. multiplex (NC 024668.1) B. multiplex B. tulda B. oldhamii (NC 012927.1) D. barbatus B. multiplex (NC 024668.1) 62 D. fuminesis 62 B. lapidea D. asper 94 O. abyssinica D. gigantus 51 B. longinternode Neohouzeaua sp. (NC 026963.1) 98 B. oldhamii D. hamilitonis D. sinicus G. sumatra (Black) 40 G. sumatra-(Green) G. apus D. laosenesis P. dulcis B. vulgaris-striata-(Yellow) D. latiflorus B. arnhemica (NC 026958.1) D. membranaceus G. angustifolia 64 D. diannanesis G. ampelxifolia D. latiflorus (NC 013088.1) 100 74 D. brandisii P. nigra-(Pks-01) 100 B. chungii-(Pks-02) 76 G. angustifolia (NC 029749.1) G. atter A. alpina G. atter P. pubescens 100 P. pubescens 96 P. edulis (NC 015817.1) 68 P. edulis (NC 015817.1) A. alpina 96 A B 0.05 0.0100 Figure 3-4: NJ revealed genomic relationships among 31 taxa of Bambusoideae along with reference sequences using (A) ndhF and (B) ndhF plus matK genes of cpDNA. The indigenous bamboo species are written in red font color and pointed with arrow.

35

B. tulda 74 B. lapidea Neohouzeaua sp. (NC 026963.1) 66 B. longinternode D. sinicus O. abyssinica D. hamilitonis B. bambos BI-1 (NC 026957.1) D. gigantus B. polymorpha D. fuminesis B. emeiensis (NC 015830.1) D. barbatus B. oldhamii (NC 012927.1) D. membranaceus 77 B. multiplex (NC 024668.1) D. latiflorus 72 B. vulgaris (Green) D. diannanesis 59 B. multiplex D. asper D. laosenesis D. latiflorus (NC 013088.1) G. sumatra (Green) G. apus G. sumatra (Black) 64 P. dulcis B. oldhamii B. longinternode B. vulgaris var. striata (Yellow) B. lapidea B. arnhemica (NC 026958.1) O. abyssinica G. angustifolia P. nigra-(Pks-01) B. tulda B. arnhemica (NC 026958.1) D. barbatus B. chungii-(Pks-02) D. gigantus B. vulgaris-striata-(Yellow) D. diannanesis D. laosenesis 62 D. fuminesis B. oldhamii D. asper G. sumatra-(Green) D. membranaceus G. sumatra (Black) Neohouzeaua sp. (NC 026963.1) B. polymorpha D. hamilitonis 63 B.bambos BI-1 (NC 026957.1) P. dulcis B. emeiensis (NC 015830.1) D. latiflorus B.vulgaris-(Green) G. apus B. multiplex 99 D. latiflorus (NC 013088.1) B. multiplex (NC 024668.1) D. sinicus B. oldhamii (NC 012927.1) D. brandisii G. angustifolia G. ampelxifolia G. ampelxifolia 60 100 G. angustifolia (NC 029749.1) D. brandisii 100 99 G. atter 75 G. angustifolia (NC 029749.1) A. alpina A. alpina 66 74 P. pubescens G. atter P. edulis (NC 015817.1) P. pubescens 82 65 99 P. nigra-(Pks-01) P. edulis (NC 015817.1) B. chungii-(Pks-02)

0.002 0.002 Figure 3-5: NJ revealed genomic relationships among 31 taxa of Bambusoideae along with reference sequences using (A) rps16 and (B) cumulative of matK , ndhF and rps16 genes of cpDNA. NB: - The indigenous bamboo species are written in red font color and pointed with arrow.

36

O.abyssinica-(BGK-Yass) 50 O.abyssinica-(BGK-Kema) O.abyssinica-(BGA-Kurm) 56 B. lapidea O.abyssinica-(ORWW-Gimb) B. longinternode O.abyssinica-(SNNPs-Kont) O.abyssinica-(ORBB-DabuH) Oxytenathera 59 O.abyssinica-(BGM-Dang) 56 O.abyssinica-(BGM-Mand) O.abyssinica-(BGM-Pawe) O. abyssinica O.abyssinica-(BGA-Asso) O.abyssinica-(BGM-Guba) O.abyssinica-(BGA-Bamb) B. polymorpha Bambuseae B. bambos BI-1 (NC 026957.1) B. oldhamii (NC 012927.1) B. emeiensis (NC 015830.1) 80 B. multiplex (NC 024668.1) Bambusa B. vulgaris (Green) 68 57 B. multiplex G. angustifolia D. laosenesis (I) G. sumatra (Green) B. vulgaris (Yellow) B. oldhamii Bambusa B. arnhemica (NC 026958.1) G. sumatra (Black) O. abyssinica-(GAM-Abol) D. latiflorus (NC 013088.1) D. dianxiensis D. sinicus Neohouzeaua sp. (NC 026963.1) G. apus D. hamilitonis D. membranaceus Dendrocalamus D. latiflorus D. fuminesis Bambuseae 62 D. asper P. dulcis D. gigantus D. barbatus D. brandisii G. angustifolia (NC 029749.1) 64 Guadua 100 G. ampelxifolia B. tulda B. chungii-(Pks-02) P. nigra-(Pks-01) 99 77 A. alpina 65 P. edulis (NC 015817.1) Phyllostachys (II) 87 P. pubescens 99 G. atter

0.002 Figure 3-6: NJ revealed genomic relationships among 31 taxa of Bambusoideae along with reference sequences and Ethiopian lowland bamboo ( O. abyssinica ) using matK , ndhF and rps16 genes of cpDNA (I) - Bambusoideae (tropical woody bamboo) and (II) - Arundinareae (temperate woody bamboo). 37

Table 3-3: List of bamboo species and an accurate and complete GenBank record and/or accession numbers at NCBI Origin Accession Numbers of Genes S. Source of Coding Region Intron No. Species Name Genus Subtribe Tribe Origin matK ndhF rps16 1. Gigantochloa_sumatra_(Black) Unclassified Unclassified Introduced 2. Dendrocalamus_latiflorus Dendrocalamus Bambusinae Bambuseae Introduced MT476656 MH72 7666 MT123879 3. Guadua_amplexifolia Phyllostachys Arundinariinae Arundinarieae Introduced 4. Gigantochloa_apus Gigantochloa Bambusinae Bambuseae Introduced MT47665 7 MH727667 MT123876 5. Phyllostachus_dulcis Phyllostachys Arundinariinae Arundinarieae Introduced 6. Gigantochloa_atter Gigantochloa Bambusinae Bambuseae Introduced MT47665 8 MH727668 MT123877 7. Dendrocalamus_barbatus Dendrocalamus Bambusinae Bambuseae Introduced MT476659 MH727669 MT123875 8. Bambusa_polymorpha Bambusa Bambusinae Bambuseae Introd uced MT476660 MH727670 MT123878 9. Dendrocalamus_dianxiensis Unclassified Unclassified Introduced 10. Dendrocalamus_fuminesis Dendrocalamus Bambusinae Bambuseae Introduced 11. Dendrocalamus_asper Dendrocalamus Bambusinae Bambuseae Introduced MT476661 MH7 27671 MT123880 12. Bambusa_vulgaris _(Green) Bambusa Bambusinae Bambuseae Introduced MT476662 MH727672 MT123881 13. Phyllostachus_pubescens Phyllostachys Arundinariinae Arundinarieae Introduced 14. Gigantochloa_sumatra_(Green) Unclassified Unclassified Introduced 15. Bambusa_oldhamii Bambusa Bambusinae Bambuseae Introduced MT4766 63 MH727673 MT123882 16. Dendrocalamus_gigantus Dendrocalamus Bambusinae Bambuseae Introduced 17. Bambusa_multiplex Bambusa Bambusinae Bambuseae Introduced MH727674 MT123883 18. Dendro calamus_hamilitonis Dendrocalamus Bambusinae Bambuseae Introduced 19. Arundinaria_alpina Oldeania Arundinariinae Arundinarieae Ethiopia MT476664 MH727675 MT123884 20. Dendrocalamus_sinicus Dendrocalamus Bambusinae Bambuseae Introduced MT476665 MH727676 MT12 3885 21. Dendrocalamus_membranaceus_Cx_Grandis Dendrocalamus Bambusinae Bambuseae Introduced MT476666 MH727677 MT123886 22. Dendrocalamus_laosenesis Unclassified Unclassified Introduced 23. Bambusa vulgaris var. striata (Yellow) Bambusa Bambusinae Bambuseae Introduced MT476667 MH727678 MT123887 24. Bambusa_tulda Bambusa Bambusinae Bambuseae Introduced MT476668 MH727679 MT123888 25. Dendrocalamus_brandisii Dendrocalamus Bambusinae Bambuseae Introduced MT476669 MH727680 MT123889 26. Guadua_angustifolia Guadua Guaduin ae Bambuseae Introduced MH727681 MT123891 27. Bambusa_longinternode Unclassified Unclassified Introduced 28. Bambusa_lapidea Bambusa Bambusinae Bambuseae Introduced MT476670 MH727682 MT123890 29. Oxytenanthera_abyssinica Oxytenanthera Bambusinae Bambuseae Ethiopia MT476671 MH727683 MT123892 30. Phyllostachys_nigra (black bamboo) Phyllostachys Arundinariinae Arundinarieae Pakistan MT476672 MH727684 MT123894 31. Bambusa_chungii (white bamboo) Bambusa Bambusinae Bambuseae Pakistan MT476673 MH727685 MT123893

38

3.3. Discussion

The taxonomy of bamboo has puzzled researchers because of bamboo reproductive characteristics. Some of the same accessions may have different names, while some different accessions may have the same name (Zhao et al., 2015). Bamboos have long been a problematic plant group to examine with molecular phylogenetic techniques. Rare heterogeneity among lineages, lack of sequence variation in certain genera and subtribes, and short internodes deep within the topology have prevented consistent and well supported resolution of branching order among and within major bamboo clades (Kelchner and BPG, 2013). With the fast development of molecular biology, the molecular marker of bamboo was developed and used for bamboo genetic diversity and phylogenetic analysis which was helpful for its taxonomy.

Many plant phylogenetic studies are based on cpDNA. In plants, cpDNA is smallest as compared to mitochondria and nuclear genome. It is assumed to be conserved in its evolution in terms of nucleotide substitution with very little rearrangements that permit the molecule to be used in resolving phylogenetic relationships especially at deep levels of evolution. Simple genetics property, a high copy within typical genomic DNA, and structural stability make cpDNA preferable for evolutionary studies in many plants (Small et al., 2004). The chloroplast genome can be divided into three functional categories including (1) protein-coding genes, (2) introns, and (3) intergenic spacers; the latter two do not encode proteins and are referred to as non-coding regions. According to the Nicotiana

chloroplast map, approximately 43% of the large single-copy (LSC) and small single-copy

39

(SSC) are noncoding. Fifteen introns make up approximately 10.6% of the single-copy chloroplast DNA, while 92 intergenic spacers comprise 32.3% (Shaw et al., 2007).

This study provides the first information about cpDNA based phylogenetics study of introduced bamboo species over the indigenous Ethiopian bamboos. The molecular topologies recovered in this study provide a number of valuable insights into bamboo evolution and the phylogenetic similarities to Ethiopian and Pakistani woody bamboos.

Among these, several observations can be noted regarding the closest relatives of temperate woody bamboos and tropical woody bamboos (Mukherjee et al., 2010; Kelchner and BPG,

2013; Wu et al., 2015).

Mostly Ethiopian lowland bamboo ( O. abyssinica ) was clustered with Bambusa and

highland bamboo ( A. alpine) was clustered with Phyllostachys and Pakistani woody bamboos P. nigra and B. chungii with Phyllostachys . Clustering of Ethiopian lowland bamboo ( O. abyssinica ) with Bambusa , highland bamboo ( A. alpine) with Phyllostachys and Pakistani woody bamboos P. nigra with Phyllostachys was as of expected and similar to the work of others that temperate woody bamboos clustered with temperate woody bamboos and evolved prior than tropical woody bamboo (Sungkaew et al., 2009;

Bouchenak-Khelladi et al., 2010; Mukherjee et al., 2010; Triplett and Clark, 2010;

Kelchner and BPG, 2013). Kelchner and BPG (2013) using five plastid DNA regions (one gene (ndhF), two group II introns (rpl16 intron, rps16 intron), and two intergenic spacers

(trnD–trnT, trnT–trnL)) have found that O. abyssinica was clustered with B. vulgaris in paleotropical woody bamboo group. But clustering of B. chungii in a genus of Bambusa

40

(tropical woody bamboo) with Phyllostachys and Guadua (both of them are grouped under

temperate woody bamboo) is uncommon and might be sampling error and needs further

detail assessment.

The three cpDNA genes ( matK , ndhF , and rps16 ) were analyzed separately and then

combined into a single data to construct an optimal NJ tree (Figure 4-4 A-D). The matK

and rps16 genes of the cpDNA showed the result similar with the result of the aggregate

cpDNA genes.

Except difference on percentage of tree support, both tree construction methods showed

that, Ethiopian lowland bamboo ( O. abyssinica ) clustered with B. lapidea and B. longinternode with tree support of 80% in MP, 76% in ML and 73% in NJ. Highland bamboo ( A. alpina ) observed to cluster with P. pubescence and P. edulis (known as

Chinese moso bamboo) with 56% support in MP, 61% in ML and 74 % in NJ methods.

A novel result of the present study is, from the overall cpDNA genes based dendrogram

result of 31 taxa and thirteen Ethiopian lowland bamboo populations (figure 3-6). Ethiopian

lowland bamboo ( O. abyssinica ) collected from Gambella region associated differently

than other lowland bamboo ( O. abyssinica ) samples and mostly it is associating with

Bambusa and Gigantochloa . Even it showed morphological variation from others (personal

observation). The leaves were broad and dark green, the culm looks taller and wider in

diameter. This implies samples collected from Gambella region are different from others

and might tell us there might be additional bamboo species in the country or introduced a

long time ago even though there is no evidence. 41

CHAPTER FOUR

4. Genetic Diversity, Population Structure and Gene Flow Analysis of

Ethiopian Lowland Bamboo [Bambusinea: Oxytenanthera abyssinica (A.

Rich.) Munro] Using cpDNA Genes Sequences

4.1. Materials and Methods

Three to five young fresh leaves were immersed in 15ml falcon tube containing 2% CTAB

solution. CTAB solution immersed young fresh leaves of three individual plants of

Ethiopian lowland bamboo ( O. abyssinica ) from thirteen potential bamboo growing areas

across the country were collected for the study. GPS data and altitudinal information for

each sample were also collected and presented in table 4-1. Maps showing sample coverage

and collection sites are described in figure 4-1.

Table 4-1: Samples information along with their GPS location Specific collection GPS Reading Altitude Region Zone District site X Y m.a.s.l Guba Yarenja 11 o 16 ' 13.1 " 035 o 22 ' 15.4 " 824 Dangur Misreta 11 o 18 ' 50.3 " 036 14 ' 10.6 " 1240 Metekel Mandura Et sitsa 11 o 09 ' 14.5 " 036 o 19 ' 50.3 " 1039 Pawe/Almu Mender 30 11 o 18 ' 32.5 " 036 o 24 ' 40.2 " 1118 Benishangul- Bambasi Ambesa Chaka 09 o 53 '55.0 " 034 o 40 ' 01.8 " 1518 Gumuz Assosa Assosa Tsetse Adurnunu 10 o 09 ' 29.9 " 034 o 31 ' 37.1 " 1507 Kurmuk HorAz ab 10 o 32 ' 33.7 " 034 o 28 ' 57.9 " 1275 Kemash Kemash 09 o 29 ' 31.4 " 035 o 52 ' 35.2 " 1234 Kemash Yasso Dangacho 09 o 52 ' 27.5 " 036 o 05 ' 32.6 " 1176 West Wollega Gimbi Aba Sena Forest 09 o 01' 32.2" 035 o 59' 54.1" 1407 Oromia BunoBedele DabuHena Did hessa Valley 08 o 40 ' 21.1 " 036 o 23 ' 32.9 " 1399 Gambella Gambella Abol Penkwe 08 o 14 ' 13.1 " 034 o 31 ' 06.2 " 435 SNNPs Konta Konta Koyshe 06 o 43 ' 35.6 " 036 o 34 ' 26.8 " 958

42

A B

C

Figure 4-1: (A) Bamboo cover map of Ethiopia (Zhao et al., 2018), (B) Map of Ethiopia with sample collection area and (C) Map of the sample collection area

43

4.1.1. DNA Extraction and PCR amplification

Three independent leaf materials from thirteen populations were used for DNA isolation.

DNA was isolated separately using a modified CTAB DNA isolation method (Hyder et al.,

2007) at BMBB laboratory, Department of Biosciences, CUI, Pakistan. Test gel electrophoresis in 1% agarose and nanodrop (Implen Nanophotometer 190-1100nm spectrophotometer) of each sample was used to measure DNA quantity and quality. Those with high DNA quantity and quality were used for PCR amplification. Among 10 primers that amplify 10 specific cpDNA regions selected from Chokthaweepanich (2014) and

Attigala (2015) and designed via Primer3 ( http://bioinfo.ut.ee/primer3-0.4.0/ ) primer

designing program, three chloroplast sequences with coding ( matK and ndhF ) and non-

coding ( rps16 intron) were used (Table 3-1).

4.1.2. PCR product profiling, sequencing, and alignment

PCR reaction (50µl per reaction) and amplification contained 7.50µl of 50 - 100ng/µl

template DNA, 5.0µl of Taq buffer (100mM Tris-HCl, 500mM KCl, 15mM MgCl 2, pH

8.5 (25 0C), 5.0µl of dNTPs mix (2.5mM each), 2.5µl of Taq DNA Polymerase (5U/µl)

(WizPure™ Taq DNA Polymerase), 1.25µl of 25pM of each primer (Table 2) and 28.75µl

of PCR grade H 2O. Profile of PCR for all primer sets included pre-PCR denaturation at 96

°C for 3 minutes followed by 35 cycles of denaturing at 96 °C for 30 seconds, annealing at

53 °C for 30 seconds, extension at 72 °C for 1 minute, a final extension at 72 °C for 20

minutes and hold at 4 °C. 3.0µl PCR products were analyzed using a standard 1% agarose

gel electrophoresis and purified and paired-end sequenced at Macrogen, Inc. Seoul, Korea.

44

The sequence of both strands of every fragment amplified from each sample was assembled separately using DNA Dragon version 1.6.0 and each sampling district was represented by a single sequence with the one very identical and informative among the triplicate samples.

The assembled sample was submitted to the GenBank and used for sequence analysis.

BLAST searches for each target sequence were used to confirm probable homology (Query cover, Identity percentage, E-value and Direction of the strand).

Sequences of three markers from thirteen O. abyssinica cpDNA were arranged in FASTA

format and aligned in MAFFT (multiple sequence alignment software version 7) (Katoh &

Standley, 2013) and realigned again using MUSCLE of MEGA version 7.0 (Kumar et al.,

2016) to increase the quality of final alignment product. Sequence information for

submission to NCBI was prepared by Sequin v5.51. An accurate and complete GenBank

record or accession number is reported in Table 4-3.

4.1.3. Evolutionary tree construction and network analysis

The three markers ( matK , ndhF and rps16 ) were analyzed separately and then combined

into a single data set. The sequence alignments with MUSCLE were used to identify the best nucleotide substitution model and construct the MP tree (Figure 4-2) and NJ tree

(Figure 4-3) using MEGA version 7.0 (Tamura et al., 2013). The MP tree was acquired using the search level 1 Subtree-Pruning-Regrafting (SPR) algorithm (Nei & Kumar, 2000)

(Nei and Kumar 2000) in which the initial trees were obtained by adding sequences in random (10 replicates). The tree is drawn to scale, with branch lengths calculated using the average pathway technique and in the number of change units throughout the sequence.

45

Bootstrap analysis with a thousand replicates was used to estimate nodal support. On the other hand, NJ tree (Figure 3) analysis was conducted using the Kimura’s two-parameter distance correction mode to build a phylogenetic tree.

The evolutionary distances were calculated based on MCL method (Tamura & Nei, 1993)

(Tamura and Nei 1993) and are in the units of the number of base substitutions per site.

Gamma distribution (shape parameter = 1) was used for the rate variation among sites.

Thirteen nucleotide sequences were involved in the analysis. For each sequence pair, all ambiguous positions have been removed and for the final dataset, there were a total of

3,694 positions.

DnaSP version 6.10.01 was used to generate haplotype files (with and without the use of the indels). The generated sequence files saved as Roehl format and network analyses were performed via Network version 5.0.1.1 (http://www.fluxus-engineering.com/sharenet.htm ).

4.1.4. Measuring nucleotide diversity, InDel polymorphism, and gene low and

genetic differentiation

DnaSP version 6.10.01 were used to calculate and analyze (1) nucleotide diversity including an average number of nucleotides difference (k), nucleotides diversity (π), population mutation rates per 100 sites (θw) for total sequence (coding + non-coding regions together) and coding and non-coding regions separately, (2) InDel polymorphism including number of sites with fixed gaps, total number of (InDel and non-InDel) sites, average InDel length, InDel diversity k(i) and InDel diversity per sites π(i), and (3) gene

46 flow and genetic differentiation including Gene flow via genetic differences among population (Gamma St) and average level of gene flow (Fst) and genetic differentiation via nucleotide sequence-based statistics (Ks) and average number of nucleotide differences between population 1 and population 2 (Kxy).

4.2. Results

There were 13 nucleotide sequences involved in the analysis of the current study. For each pair of sequences, each ambiguous position was removed and in the last dataset, there was an aggregate of 3,694 positions. Evolutionary history using MP and NJ together with nucleotide diversity analysis, DNA divergence between populations, InDel polymorphism and gene flow and genetic differentiation analysis on Ethiopian lowland bamboo ( O.

abyssinica ) were investigated to analyze on this part which is the first to study the plants

genetic diversity, population structure and gene flow using coding (matK and ndhF ) and

non-coding ( rps16 ) regions of cpDNA genes. Accession number for matk , ndhF and rps16

obtained from NCBI presented on table 4-2.

Table 4-2: An accurate and complete GenBank record (accession numbers at NCBI). Sample Coding Region Intron No. Collection Area Name matK ndhF rps16 1. BG_Asso_Bambasi Bambasi MH445413 MH445426 MH445439 2. BG_Asso_Assosa Assosa MH445414 MH445427 MH445440 3. BG_Asso_K urmuk Kurmuk MH445415 MH445428 MH445441 4. BG_Metk_Guba Guba MH445416 MH445429 MH445442 5. BG_Metk_Dangur Dangur MH445417 MH445430 MH445443 6. BG_Metk_Mandura Mandura MH445418 MH445431 MH445444 7. BG_Metk_Pawe/Almu Pawe MH445419 MH445432 MH445445 8. BG_Kem_Kema sh Kemash MH445420 MH445433 MH445446 9. BG_Kem_Yasso Yasso MH445421 MH445434 MH445447 10. OR_W/Wollg_Gimbi Gimbi MH445422 MH445435 MH445448 11. OR_B/Bed_Dabu Hena Dedhesa MH445423 MH445436 MH445449 12. GM_Gamb_Abol Abol MH445424 MH445437 MH445450 13. SNNPs_Kon_Kont a Koyshe MH445425 MH445438 MH445451 47

4.2.1. Chloroplast DNA sequence character and sequence divergence

GC and AT content of each and aggregate cpDNA genes were analyzed (table 4-4). Highest AT content (66.6) in Bambasi, Kurmuk and

Pawe populations and least (66.4) in Dangur, Abol and Dabu Hena populations was observed by the aggregate genes while the GC content was highest (33.6) in Dangur, Abol and Dabu Hena populations and the least (33.4) was observed in Bambasi, Kurmuk and

Pawe populations. Average GC and AT content and total sequence was observed (66.5, 33.5 and 3658.6) in the aggregate cpDNA genes respectively. Since the comparison was between different populations of a single species ( O. abyssinica ), there was no significant difference on GC and AT content observed and the result of each samples were close to the average.

Table 4-3: GC and AT content of each and aggregate cpDNA genes. matK (~ 1,350 bp) ndhF (~ 1,140 bp) rps16 (~ 860 bp) Aggregate genes Name of the species Percentage Total Percentage Total Percentage Total Percentage Total AT GC Sequence AT GC Sequence AT GC Sequence AT GC Sequence O. abyssinica -(BGA-Asso) 66.4 33.6 1778.0 66.8 33.2 1057.0 65.9 34.1 848.0 66.5 33.5 3670.0 O. abyssinica -(BAB-Bamb) 66.4 33.6 1778.0 66.7 33.3 1057.0 66.0 34.0 853.0 66.6 33.4 3666.0 O. abyssinica -(BGA-Kurm) 66.4 33.6 1778.0 66.8 33.2 1057.0 66.2 33.8 852.0 66.6 33.4 3669.0 O. abyssinica -(BKK-Kema) 66.4 33.6 1778.0 66.6 33.4 1057.0 66.2 33.8 852.0 66.5 33.5 3662.0 O. abyssinica -(BGK-Yass) 66.4 33.6 1778.0 66.6 33.4 1057.0 66.2 33.8 852.0 66.5 33.5 3656.0 O. abyssinica -(BGM-Dang) 66.4 33.6 1779.0 66.4 33.6 1057.0 66.1 33.9 852.0 66.4 33.6 3680.0 O. abyssinica -(BGM-Guba) 66.4 33.6 1778.0 66.7 33.3 1056.0 66.2 33.8 852.0 66.5 33.5 3634.0 O. abyssinica -(BGM-Mand) 66.4 33.6 1779.0 66.6 33.4 1056.0 66.2 33.8 852.0 66.5 33.5 3635.0 O. abyssinica -(BGM-Pawe) 66.4 33.6 1779.0 66.4 33.6 1057.0 66.1 33.9 852.0 66.6 33.4 3648.0 O. abyssinica -(GAM-Abol) 66.4 33.6 1778.0 66.5 33.5 1058.0 66.0 34.0 852.0 66.4 33.6 3671.0 O. abyssinica -(ORWW-Gimb) 66.3 33.7 1779.0 66.8 33.2 1057.0 66.2 33.8 852.0 66.5 33.5 3648.0 O. abyssinica -(ORBB-DabuH) 66.4 33.6 1779.0 66.4 33.6 1057.0 66.1 33.9 852.0 66.4 33.6 3650.0 O. abyssini ca -(SNNPs-Koys) 66.5 33.5 1778.0 66.4 33.6 1057.0 66.1 33.9 853.0 66.5 33.5 3673.0 Average 66.4 33.6 1778.4 66.6 33.4 1056.9 66.1 33.9 851.8 66.5 33.5 3658.6

48

4.2.2. Phylogenetic inference and relationship

4.2.2.1.Maximum parsimony method evolutionary history analysis The evolutionary history of bamboos was inferred using the MP method. The analysis showed consistency index (0.800), composite index 0.824 (0.706) and retention index

(0.882) for all sites and parsimony-informative sites (in parentheses) (Figure 4-2). The percentage of replicate trees in the bootstrap test (Felsenstein, 1985) (Felsenstein 1985) grouped together by the associated taxa 1000 replicates is shown next to the branches.

Distant populations (SNNPs + Gambella) showed distinctly different from other populations but others showed intermixing up between populations.

Abol Koyshe 95 Mandura 55 Guba 96 Bambasi Assoaa Kurmuk 38 Gimbi 53 Yasso 57 20 85 Kemash 62 Dangur Dabu Hena 77 Pawe

2.5 Figure 4-2: The Maximum Parsimony tree of O. abyssinica obtained based on pair-wise distance from the combined data of matK, ndhF and rps16.

4.2.2.2.Neighbor-Joining method evolutionary history analysis The evolutionary history of bamboos was inferred based on the Neighbor-Joining method

(Saitou & Nei, 1987) (Saitou and Nei 1987). NJ showed the optimal tree with the total

length of the branch = 0.012 (Figure 4-3). Except samples collected from Oromia region

that showed mixing with other groups, other populations form their own group which

secured the distinctness of their population and effectiveness of genes used for sequencing.

49

46 Assosa Assosa Zone Bambasi 54 Kurmuk Assosa Zone

67 Yasso 43 Kemash Zone 63 Kemash

55 Gimbi West Wollega

Guba

59 Mandura Metekel Zone

32 Pawe

Dangur Metekel Zone

79 Dabu Hena Buno Bedelle

Koyshe SNNPs Distant Population 45 Abol Gambella

0.0019 Scale Figure 4-3: The neighbor joining tree of O. abyssinica obtained based on pair-wise distance from the combined data of matK, ndhF and rps16.

The three cpDNA genes ( matK , ndhF 3', and rps16 ) were analyzed separately and then

combined into a single data to construct an optimal NJ tree (Figure 4-4 A-D). The sum of branch length (A) = 0.003, (B) = 0.011, (C) = 0.007 and (D) = 0.006 was obtained. There

was a total of (A) = 1,771, (B) = 1,001, (C) = 834 and (D) = 2,773 positions in the final

dataset. The ndhF 3' end of the cpDNA gene alone showed the result similar with all primers merged together. Three major clusters and three sub-clusters with five clades

(Assosa Zone, Kemash Zone, Metekel Zone, the distant and the intermixed Oromia region

samples) were formed in the final NJ analysis. In all condition’s samples collected from

Kemash Zone is not separated and always clustered together with great nodal support and

this population shows lastly evolved.

50

Koyshe 86 Guba 65 Dabu Hena 17 Mandura Dangur Gimbi 9 Mandura Assosa Bambasi 22 Kemash Guba B 64 Yasso A 94 Kurmuk Kurmuk Kemash 39 Bambasi 59 Yasso Dangur Gimbi Pawe 65 Assosa Dabu Hena Pawe Abol Abol Koyshe

0.000100 0.00050

48 Gimbi 44 Dabu Hena Kemash 52 Yasso Dangur Pawe C Kurmuk Bambasi Assosa Mandura Guba Koyshe Abol 0.00050 Figure 4-4: The NJ tree obtained based on pair-wise distance from each genes A. matK , B. ndhF , and C. rps16 gene.

4.2.3. Network Analysis

Total number of mutations disregarding the torso (130, 27), estimated number of mutations

of shortest tree within the torso (73, 0), estimated number of mutations of shortest tree

(203, 27), total number of taxa (13, 13) and total number of haplotypes (13, 11) were

observed on gaps or missing data considered and not considered network analysis. Number

values before parenthesis are for gaps or missing data considered and after parenthesis for

gaps or missing data not considered. Haplotype 8 (Kurmuk sample of Assosa Zone) from

gaps or missing data considered (Figure 4A) and haplotype 2 (Bambasi sample of Assosa

Zone) from gaps or missing data not-considered (Figure 4B) has descendants around them,

51 many of which differ from them by nucleotide change (at sites shown by numbers), some are more distantly related. Both forms approve that; Assosa Zone is the root of O.

abyssinica and others have diverged from this Zone. The distant populations H_3 (Abol

sample of Gambella Region) and H_11 (Koyshe sample of SNNPs Region) from gaps or

missing data not-considered and H_3 (Abol sample of Gambella Region) and H_13

(Koyshe sample of SNNPs Region) from gaps or missing data considered showed distant

from the root.

A B

Figure 4-5: Haplotype network of the combined cpDNA region obtained based on (A) gaps/missing data considered and (B) gaps/missing data not-considered. Note 1: Haplotypes for figure 5A; H_1 [Assosa], H_2 [Bambasi], H_3 [Abol], H_4 [Kemash], H_5 [Yasso], H_6 [Dangur], H_7 [Pawe], H_8 [Kurmuk], H_9 [Guba], H_10 [Guba], H_11 [Mandura], H_12 [Dabu Hena] and H_13 [Gimbi]. Note 2: Haplotypes for figure 5B; H_1 [Assosa], H_2 [Bambasi], H_3 [Abol], H_4 [Kemash + Yasso], H_5 [Dangur + Dabu Hena], H_6 [Pawe], H_7 [Kurmuk], H_8 [Guba], H_9 [Mandura], H_10 [Gimbi] and H_11 [Koyshe].

52

4.2.4. Nucleotide Diversity Analysis

Metekel Zone found extremely higher k (23.167), π (0.00633 ± 0.00046) and θw (22.33333 ± 0.00099). Distant populations (11.000,

0.00300 ± 0.00150, 11.00000 ± 0.00222) followed by Oromia, Assosa Zone, and Kemash Zone were found to be lower in k, π, and θw

(Table 4-4). This implicates that gene differentiation in Metekel Zone and the distant populations is higher and that makes them a diverse population as compared to others.

Table 4-4: Nucleotide diversity analysis on Ethiopian lowland bamboo populations in different Zones. Analysis in Pair wise Comparisons Total Coding Region Non - Coding Region Pupulation k Π θw k Π θw k π θw Assosa Zone 4.333 0.00118 ± 0.00026 4.33333 ± 0.00063 2.000 0.00071 ± 0.00025 2.00000 ± 0.00053 1.333 0.00159 ± 0.00075 1.33333 ± 0.00132 Metekel Zone 23.167 0.00633 ± 0.00046 22.33333 ± 0.00099 10.667 0.00380 ± 0.00049 10.12121 ± 0.0 0096 1.333 0.00156 ± 0.00034 1.09091 ± 0.00102 Kemash Zone 2.000 0.00055 ± 0.00027 2.00000 ± 0.00047 0.000 0.00000 ± 0.00000 0.00000 ± 0.00000 0.000 0.00000 ± 0.00000 0.00000 ± 0.00000 Oromia 8.000 0.00219 ± 0.00110 8.00000 ± 0.00165 6.000 0.00214 ± 0.0 0107 6.00000 ± 0.00163 2.000 0.00232 ± 0.00116 2.00000 ± 0.00201 Distant Pop. 11.000 0.00300 ± 0.00150 11.00000 ± 0.00222 8.000 0.00283 ± 0.00142 8.00000 ± 0.00213 2.000 0.00233 ± 0.00117 2.00000 ± 0.00202 Note: k denotes average number of nucleotide differences, π (Pi) - pair-wise average nucleotide diversity per 100 sites along with standard deviation and θw (Theta-w) signifies Watterson estimator for population mutation rates per 100 sites with its standard deviation

53

4.2.5. InDel Polymorphism Analysis

Average InDel length was higher on Kemash (15.333) and Metekel Zones (12.214) and the

lower value was observed on Assosa (7.143), distant and Oromia populations (Figure 4-6).

Whereas the total number of InDel and non-InDel sites analyzed were higher for

populations of Metekel (3,692), distant population (3,679) and Assosa Zone (3,678) but

populations from West Wellega and Buno Bedele Zones of Oromia Region and Kemash

Zone populations show relatively smaller value (Table 4-5). Higher frequency of InDel

makes Metekel, the distant population and Assosa Zone populations more diverse than

Oromia (3,654) and Kemash Zone (3,668) populations. From this, we can conclude InDel

plays a significant role in genetic differentiation and population structure of Ethiopian

lowland bamboo ( O. abyssinica ) populations.

Table 4-5: InDel polymorphism of Ethiopian lowland bamboo ( O. abyssinica ). Total Total Total Total number Number of number of number of Average number of (InDel and Collection Site sites with InDel non-InDel InDel k(i) π(i) of InDel non-InDel) fixed gaps sites sites length sites sites analysed analysed analysed Assosa Zone 16 18 3660 18 3678 7.143 4.667 0.00127 Kemash Zone 26 16 3652 16 3668 15.333 3 0.00082 Metekel Zo ne 2 75 3617 75 3692 12.214 6 0.00163 Oromia 40 8 3646 8 3654 4 2 0.00055 Distant Pop. 15 12 3667 12 3679 4.5 4 0.00109 Note: k(i) denotes InDel diversity, π(i) - InDel diversity per sites

54

InDel polymorphism of Ethiopian lowland bamboo (O. abyssinica) Frequency and Percentage

A B C 15, 15.2% 16, 16.2% 12, 9.3% 18, 14.0% 8, 6.2% 3667, 20.1% 3660, 20.1% Category 16, 12.4% Assosa Zone 26, 26.3% 3646, 20.0% 3652, 20.0% Kemash Zone 40, 40.4% Metekel Zone Oromia 2, 2.0% 75, 58.1% 3617, 19.8% Out Group D E F 12, 9.3% 18, 14.0% 3679, 20.0% 3678, 20.0% 4.500, 10.4% 7.143, 16.5% 8, 6.2% 4.000, 9.3% 16, 12.4%

3654, 19.9% 3668, 20.0% 12.214, 28.3% 15.333, 35.5%

75, 58.1% 3692, 20.1%

G H Where 4.667, 23.7% A = Number of sites with fixed gaps 4.000, 20.3% 0.00109, 20.3% 0.00127, 23.7% B = Total number of InDel sites C = Total number of InDel sites analysed 2.000, 10.2% 0.00055, 10.3% D = Total number of non-InDel sites analysed E = Total number of (InDel and non-InDel) sites analysed 3.000, 15.3% 0.00082, 15.3% F = Average InDel length G = InDel diversity, k(i) 6.000, 30.5% 0.00163, 30.4% H = InDel diversity per sites, π(i)

Figure 4-6: Frequency and percentage of InDel polymorphism of Ethiopian lowland bamboo ( O. abyssinica ).

4.2.6. Analysis of DNA Divergence

DNA divergence between populations was higher between populations of Metekel,

Oromia, Kemash and Assosa Zone Vs distant populations in chronological order (Figure

4-7). The k was higher between Metekel Zone Vs distant population (9.5), followed by

Oromia Vs distant population (8.667) and Kemash Zone Vs the distant population (8.467).

The least k was found between populations of Assosa Vs Kemash Zone and between

Assosa Zone Vs Oromia. The π(t) was higher between Metekel Zone Vs distant population

(0.00261), followed by Oromia Vs distant population (0.00238) and Kemash Zone Vs the

distant population (0.00234). The least π(t) was found between populations of Assosa Zone

Vs Kemash Zone and between Assosa Zone Vs Oromia.

55

The MP in P1, but monomorphic in P2 was higher between Metekel Zone Vs distant population (10), followed by Oromia Vs distant population (7) and Metekel Zone Vs

Oromia (5). The MP in P1, but monomorphic in P2 was found zero between populations

of Kemash Vs Metekel Zone and between Kemash Zone Vs Oromia. The MP in P2, but

monomorphic in P1 was higher between Assosa Zone Vs Metekel Zone (11) and between

Kemash Zone Vs Metekel Zone (11) followed by Kemash Zone Vs the distant population

(10). The least MP in P2, but monomorphic in P1 was found between populations of

Metekel Zone Vs Oromia followed by between Assosa Zone Vs Kemash Zone. The π between populations was higher between Kemash Zone (11.5), followed by Metekel Zone

(9.5) and Assosa Zone (9.333) Vs distant population. The least π between populations was

found between populations of Assosa Zone Vs Kemash Zone and between Assosa Zone

Vs Oromia.

56

Any population compared to the distant population found larger DNA divergence than others. This tells us DNA of the distant population is distinctly different from other populations. DNA divergence between Assosa Vs Kemash Zone, Assosa Vs Oromia, and Kemash Zone

Vs Oromia found to be smaller. Those three areas (Assosa Zone, Kemash Zone, and West Wellega and Buno Bedele Zones of Oromia

Region) are very close each other and there might be seed and/or seedling transfer between populations that make them close and related each other on their genetic makeup.

12 10 8 6 4 2 0 Assosa Assosa Assosa Assosa Kemash Kemash Kemash Metekel Metekel Oromia Zone vs Zone vs Zone vs Zone vs Zone vs Zone vs Zone vs Zone vs Zone vs vs Kemash Metekel Oromia Distant Metekel Oromia Distant Oromia Distant Distant Zone Zone Pop. Zone Pop. Pop. Pop. k 3 5.524 4.6 7.4 6.333 5.333 8.467 6.467 9.5 8.667 π(t) 0.00082 0.00153 0.00127 0.00202 0.00175 0.00146 0.00234 0.00179 0.00261 0.00238 MP in P1, but Monomorphic in P2 43340015107 MP in P2, but Monomorphic in P1 1 11 7 10 11 8 10 2 9 9 π between populations 3.5 5.75 5 9.333 6.75 6 11.5 6 9.5 8.5 Dx 0.00096 0.00159 0.00138 0.00255 0.00187 0.00165 0.00263 0.00166 0.00316 0.00233

Figure 4-7: DNA divergence between different Zones of Ethiopian lowland bamboo populations. Note: k denotes average number of nucleotide differences, π(t) - nucleotide diversity, MP - mutations polymorphic, P1 - population 1, P2 - population 2, π - average number of nucleotide differences, Dx - average number of nucleotide substitution per site between populations. 57

4.2.7. Gene Flow and Genetic Differentiation

Extremely higher frequency of genetic differentiation was found between Metekel Zone

Vs the distant population (51.63) and between Assosa Zone Vs Metekel Zone (51.50).

Least frequency was observed between Kemash Zone Vs Oromia (19.25) and between

Assosa Zone Vs Oromia (23.00). Higher frequency of gene flow was found between

Assosa Zone Vs Oromia (0.61) and between Kemash Zone Vs Oromia (0.50) and minimum frequency of gene flow was observed between Metekel Zone Vs the distant population

(0.02) and between Oromia Vs the distant populations (Table 4-6). This implicates that gene flow to Metekel Zone and the distant populations is rare and that makes diverse population as compared to others.

Table 4-6: Effects of gene flow and genetic differentiation on Ethiopian lowland bamboo. Genetic differentiation Gene flow Population comparison Ks Kxy Gamma St Fst Assosa Zone Vs Kemash Zone 16.60000 36.00000 0.56109 0.53241 Assosa Zone Vs Metekel Zone 36.52381 51.50000 0.32779 0.34142 Assosa Zone Vs Oromia 15.80000 23.00000 0.61075 0.60581 Assosa Zone Vs Distant Pop. 18.60000 40.16667 0.34696 0.15942 Kemash Zone Vs Metekel Zone 40.77778 40.50000 0.20076 0.13374 Kemash Zone Vs Oromia 17.00000 19.25000 0.60204 0.50318 Kemash Zone Vs Distant Pop. 20.50000 38.75000 0.58163 0.47097 Metekel Zone Vs Oromia 40.11111 34.87500 0.28104 0.27199 Metekel Zone Vs Distant Pop. 42.44444 51.62500 0.14885 0.02270 Oromia Vs Distant Pop. 19.50000 39.25000 0.38739 0.11688 Note: Ks denotes nucleotide sequence-based statistics, Kxy - average number of nucleotide differences between population 1 and population 2, GammaSt - genetic differences among population and Fst - average level of gene flow

58

4.3. Discussion

Assessing the genetic diversity and population structure of any plant’s germplasm is a prerequisite for effective and successful improvement, conservation and management strategies of that plant (Sui et al., 2009). Furthermore, genetic diversity, population

structure, and gene flow analysis within different populations of a species are the main building blocks for understanding the evolutionary and speciation aspect of that species.

Oxytenanthera abyssinica is widely distributed in Ethiopia except for the eastern and southeastern parts of the country.

Genetic diversity is the basis for the ability of an organism to adapt to environmental changes and can be influenced by many factors (Amos and Harwood, 1998). Geographical factors (e.g. landscape, latitude, longitude, and altitude) and environmental factors (e.g. temperature and precipitation) influence the genetic diversity and population structure of a species and the individuals among populations (Wellenreuther et al., 2011; Pauls et al.,

2013). Biological factors such as mutation, genetic drift, mating system, pollination mode, gene flow, and selection also influence the diversity of plant species and population (Schaal et al., 1998).

Several studies applied on the genetic diversity of different bamboo species using phenotypic and different types molecular marker (GPWG, 2001; Nayak et al., 2003; Sun et al., 2006; Gami el al. , 2015). But studying the genetic diversity and population structure of O. abyssinica using either of phenotypic and molecular marker or both has not been done yet.

59

The k, π, and θw for the total sequence (coding + non-coding regions together) and coding and non-coding regions separately were used to calculate nucleotide diversity. The number of sites with fixed gaps, the total number of InDel and non-InDel sites, average InDel length, ki and π(i) were used to calculate InDel polymorphism. The k, π, and mutations polymorphic in population 1, but monomorphic in population 2 and vice-versa, the average number of nucleotide differences between populations, Dx for total sequence were used to calculate DNA divergence. Gamma St and Fs and Ks and Kxy were used to calculate gene flow and genetic differentiation.

The effectiveness of cpDNA regions for phylogenetics and genetic diversity studies are well approved and tested in many plants including prayer plant (Marantaceae) (Prince et al., 2006), palm (Chamaedoreeae) (Cuenca et al., 2008), 12 genera of angiosperms (Dong et al., 2012), paleotropical woody bamboos (Poaceae: Bambusoideae: Bambuseae)

(Chokthaweepanich, 2014), temperate woody bamboos (Attigala et al., 2015). As the

evolutionary rates of cpDNA are highly conserved with structural changes and nucleotides

substitution (Soltis et al., 2004), cpDNA regions that are coding ( matK and ndhF 3’ end) and non-coding ( rps16 ) genes were used to examine genetic diversities, population structure and gene flow analysis of O. abyssinica.

The NJ result retrieved three major clusters and three sub-clusters with five clades (Assosa

Zone, Kemash Zone, Metekel Zone, the distant population and the intermixed Oromia region samples) with their phylogeographic location. But MP result shows the mixing up

60 of some populations with others although major groups are almost similar to NJ. This approves that; phylogeography has a great impact on gene flow and genetic differentiation

(Avise, 2000). Generally, algorithms used to create phylogenetic trees with phylogenetic characteristics are more complex than methods based on distance (Scott & Gras, 2012). In this study, we found a mixing up of some populations with others in the MP method. But major groups are almost similar to NJ evolutionary tree construction method.

DnaSP can estimate multiple measurements of DNA sequence variations within and between populations in non-coding, synonymous or non-synonymous sites, or in different types of codon positions, as well as associating parameters of disequilibrium, recombination, gene flow and gene conversion (Rozas, Ferrer-Mata et al. 2017). Mainly mutations within the DNA are the source of variations. InDels are the main variation sources found within the genomes of various species of plants, including Arabidopsis (Hu

et al., 2011), rice (Lü et al., 2015), tomato (Yang et al., 2014) and chickpea (Das et al.,

2015). InDels usually occur by reason of certain cellular mechanisms, including

transposable elements movement, replication slippage and crossing-over imbalanced

within genomes (Moghaddam et al., 2014). InDels are essential phenomena that can have

a harmful or advantageous effect on specific genomes loci (Pearson et al., 2005; Garcia-

Diaz et al., 2006). Examination of DNA differences among closely related species or

among polymorphic DNA variations of a species will provide insight into mutations nature and evolution process (Britten et al., 2003). InDel analysis on O. abyssinica also shows

that; gene flow between distant populations found rare and genetic diferentioan becomes

higher.

61

Network analysis also shows that, haplotype 8 (Kurmuk sample of Assosa Zone) from gaps

or missing data considered and haplotype 2 (Bambasi sample of Assosa Zone) from gaps

or missing data not-considered has descendants around them, many of which differ from

them by nucleotide change (at sites shown by numbers), some are more distantly related.

Both the gaps and/or missing data considered and not-considered forms approve that,

Assosa Zone is the root of O. abyssinica and others diverge from this Zone. Amharic

Ambesa Chacka (meaning lion’s forest , because of high abundance of lions in the forest)

was one of sample collection site from Assosa Zone of Bambasi district. Years ago, the

area was known for its wide and dense lowland bamboo coverage. But now due to human’s

effect on the forest and/or deforestation, even small wild animals were out of our sight

during sample collection period for four days stay in a specified area.

Populations of O. abyssinica collected in Ethiopia showed clear diversity based on their geographic location. This might be due to the plant is indigenous to the country (Embaye,

2000) and largely abundant with broad geographical coverage for a long time, cross- pollination nature of the flower, and the distance between sample collections sites especially Zones was far and distant. Sample collection sites that have relatively closer distance like Assosa, Kemash, and Oromia, showed smaller nucleotide diversity (Table 4-

4), InDel (Table 4-5 and Figure 4-6), genetic differentiation (Table 4-6) and DNA divergence (Figure 4-7) but higher gene flow between populations (Table 4). These three sites are neighbor to each other. Assosa and Kemash Zones are under the administrative system of BGR and neighbor to each other with relative closer distance as compared to other sampling sites. Samples from Oromia are also neighbor to Kemash Zone. Thus, both

62 geographic range and distribution of populations influence patterns of genetic diversity, differentiation and gene flow of Ethiopian lowland bamboo (O. abyssinica ). Indeed, cross- pollination may have contributed to increasing the heterogeneity of bamboo seedlings

(John and Nadguada, 1999). This result is more in line with the study on African tropical

forest refugia using chloroplast and nuclear DNA phylogeography (Lowe et al., 2010),

classification of the Chloridoideae (Poaceae) based on multi-gene phylogenetic trees

(Peterson et al., 2010), Chinese Cherry revealed by chloroplast DNA trnQ-rps16 intergenic

spacer (Chen et al., 2013), natural populations of Oxalis laciniata from Patagonia

Argentina using ISSR and cpDNA based markers (López & Bonasora, 2017), wild soybean evaluated by chloroplast and nuclear gene sequences from 44 Chinese, four Japanese and five Korean populations (Wang et al., 2017) and endangered basal angiosperm Brasenia schreberi (Cabombaceae) in China using microsatellites (Li et al., 2018).

Based on the results retrieved, Metekel Zone showed the highest diversity among other populations and thus government sectors and other stakeholders are recommended to focus on conservation of lowland bamboo of Metekel Zone and carry out further study on O. abyssinica. The current study was performed only by few chloroplast coding and non- coding genes thus; additional coding, non-coding and spacer chloroplast and nuclear genes on Ethiopian lowland bamboo ( O. abyssinica ) might give additional information on the population genetic diversity, structure and gene flow.

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CHAPTER FIVE

5. Genetic Relationship among Indigenous and Introduced Bamboo Species and ISSR Markers Efficiency Analysis

5.1. Materials and Methods

5.1.1. Plant Material Collection and Sampling Strategy

The same plant materials (Table 3-2) used for the study of phylogenetic relationships among the indigenous and introduced bamboo species using cpDNA genes were also used here for phylogenetics study of introduced bamboo species over the indigenous Ethiopian bamboo species using ISSR markers. But leaf samples used for DNA extraction were silicagel dried. Five to seven young fresh leaves were stored in a zip lock plastic bag with appropriate silica gel. A single woody bamboo species was represented by three individuals for all the 31 species.

5.1.2. DNA Extraction and Primer Screening

Silicagel dried leaves were crashed by a mixer and miller (Retsch Mixer Mill MM 400).

Genomic DNA was isolated separately using a modified 2% CTAB DNA isolation method at Plant Molecular Biology Laboratory (PMBL) and Plant Genetics Research Laboratory

(PGRL) of AAU. Test gel electrophoresis in 1% agarose and nanodrop (Thermo

SCIENTIFIC NANODROP 2000 Spectrophotometer) of each sample was measured and those with high DNA quality used for PCR amplification after normalization of each sample to a concentration of 100ng. Gel documentation was taken by BIORAD Gel Doc TM

EZ System Imager.

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Fifteen ISSR primers were chosen out of 38 ISSR primers designed from University of

British Colombia (UBC) and previous work on the literature. Among fifteen primers, ten were di-nucleotide, one was tri-nucleotide, two were tetra-nucleotide, one was penta- nucleotide, and two were 5` anchored primers. Primers were further categorized into 3` anchored, 5` anchored, and un-anchored based on anchorage property (table 5-2).

Table 5-1: ISSR primers used for PCR amplification Primer Primers Nucleotide Repeat Anchorage Optimized No. name or selected Tm Sequence motifs property Ta Code for PCR

1 (AG) 8T UBC807 Dinucleotide 3’ -anchored

2 (AG) 8C UBC808 '' ''

3 (GA) 8T UBC810 '' '' √ 42

4 (GA) 8A UBC812 '' '' √ 42

5 (CT) 8T UBC813 '' ''

6 (CT) 8G UBC815 '' '' √ 42

7 (TC) 8C UBC823 '' ''

8 (TC) 8G UBC824 '' '' √ 43

9 (AC) 8T UBC825 '' ''

10 (AG) 8YT UBC834 '' '' √ 43

11 (AG) 8YC UBC835 '' '' √ 45

12 (GA) 8YT UBC840 '' '' √ 42

13 (GA) 8YC UBC841 '' '' √ 43

14 (GA) 8YG UBC842 '' ''

15 (CT) 8RC UBC844 '' '' √ 43

16 (CT) 8RG UBC845 '' ''

17 (CA) 8RG UBC848 '' ''

18 (GT) 8YG UBC851 '' ''

19 (TC) 8RT UBC853 '' ''

20 (TC) 8RG UBC854 '' ''

21 (AC) 8YG UBC857 '' ''

22 (ACC) 6 UBC861 Tri Unanchored

23 (AGC) 6 UBC862 '' ''

24 (AGT) 6 UBC863 '' ''

25 (ATG) 6 UBC864 '' '' √ 39

26 (GATA) 4 UBC872 Tetra “

27 (GACA) 4 UBC873 '' '' √ 42

28 (CCCT) 4 UBC874 '' ''

29 (CTAG) 4 UBC875 '' ''

30 (GATA)2(GACA) 2 UBC876 '' '' √ 39 65

31 (CTTCA) 3 UBC879 Penta ''

32 (GGAGA) 3 UBC880 '' '' √ 45

33 (GGGTG) 3 UBC881 '' ''

34 BDB(CA) 7 UBC888 5’-anchored 5’-anchored √ 47

35 DBD(AC) 7 UBC889 '' '' √ 45

36 (AGG) 6 ISSR_1 Tri Unanchored

37 (GACAC) 4 ISS R_2 Penta ''

38 (ACTG) 4 ISSR_3 Tetra '' Y = C or T ‰ (PYramidine), R = A or G ‰ (PuRine), B = C, G, or T ‰ (not A), D = A, G, or T ‰ (not C)

5.1.3. ISSR-PCR Amplification and Gel Electrophoresis

Each DNA amplification reaction was performed in a final volume of 10µl containing 5.5

µl 2x Taq plus Master Mix (containing Taq DNA polymerase, dNTPs, MgCl 2, PCR buffer,

PCR reaction enhancer, stabilizer and a blue tracer dye), 3.5 µl ddH 2O, 0.5 µl ISSR primer and 0.5 µl normalized genomic DNA. The blue dye and a stabilizer of 2x Taq plus Master

Mix help to directly load the final products onto a gel for analysis. The thermal profile included pre-PCR denaturation at 94 °C for 4 minutes followed by 35 cycles of denaturing at 94 °C for 30 seconds, annealing (39 - 47 °C) for 30 seconds (Table 5-1), extension at

72°C for 1 minute and a final extension at 72 °C for 10 minutes. The PCR products were stored at 4 °C until loading on gel electrophoresis. About 5 µl of ISSR-amplification product of each sample DNA was loaded on and were resolved in 1.67% agarose gels in

0.5x TBE buffer at 100 V constant for 1:30 - 2h. The agarose solution was stained with 3.0

µl Ethidium Bromide (EtBr) after the boiling of the powder and 0.5% TBE buffer. The

ISSR profiles were visualized and photographed under BIORAD Gel Doc TM EZ System

Imager that connected to PC with Image Lab software, and stored for later data scoring. To

estimate the molecular sizes of the resolved fragment, 100 bp DNA markers were used.

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5.1.4. Scoring and Data Analysis

Bands were scored manually. According to the weight of the DNA ladder (100 bp), the same weight bands were marked as a line. The bands that were clearly visible and repeatable on the electrophoresis map were marked as “1”, the absence of a band at the same site was marked as “0” and “?” for the ambiguous bands that were not clearly shown were scored as a missing data. Intensity variations among fragments having approximately the same molecular size were not considered although in some cases intensity differences of the bands were observed. A binary data matrix was compiled with individuals in the column and the ISSR markers in the row for each primer set and vise-versa according to the requirements of the software’s. Each amplified fragment was named by the code of the primers across the row and/or column followed by the Arabic numbers starting from the fragment having high molecular weight to the fragments with low molecular weight. Both the total number of bands amplified by each primer and the number of polymorphic bands were calculated. On the basis of the recorded band profiles, different software was employed for the analysis of the data.

POPGENE version1.32 (Yeh et al., 1999) and GenAlEx version 6.5 (Peakall and Smouse,

2012) were used to calculate number of polymorphic loci, percent polymorphism, gene diversity and Shannon diversity index. Shannon diversity index (H) was calculated asH = -

n ∑i=1 Pi ln 2 Pi where pi is the frequency of a given band for each population (Lewontin,

1972). Shannon’s index of diversity was used to measure the total diversity (Hsp) for the species as well as the mean diversity per population (Hpop). The proportion of diversity

within and between populations was then calculated as and 1 − respectively. 67

Genetic similarity matrix among each taxa was calculated in all pair-wise comparisons following Jaccard’s similarity coefficients. NTSys version 2.02 (Rohlf, 2000) software was used to calculate Jaccard’s similarity coefficient which is calculated as: - S = + + Where, “a” is the total number of bands shared between individuals i and j, “b” is the total number of bands present in individual i but not in individual j and “c” is the total number of bands present in individual j but not in individual i.

NTSYS was also used to generate the unweighted pair group method with arithmetic mean

(UPGMA) phenogram to analyze a sequential, agglomerative, hierarchical, and nested

(SAHN) cluster analysis using the similarity matrix and compare the individual genotypes.

The neighbor joining (NJ) method (Saitou and Nei 1987; Studier and Keppler, 1988) was

used to compare individual genotypes and evaluate patterns of genotype clustering using

Free Tree 0.9.1.50 Software (Pavlicek et al., 1999). The major difference between the two

algorithms is that UPGMA assumes equal rates of evolution (molecular clock assumption)

along all branches, whereas neighbor joining assume variations in the rate of change

(Saitou and Nei1987; Studier and Keppler, 1988; Nei and Kumar, 2000; Lan and Reeves,

2002).

Patterns of genetic variation among individual samples were also further examined with

three dimensions with the help of principal coordinate analysis (PCO) on the basis of

Jaccard’s coefficients of similarities (Jaccard’s, 1908), which was calculated using PAST

software version1.18 (Hammer et al., 2001). The first three axis were later used to construct

68 the scatter plot with STATISTICA version 12.0 software’s (Hammer et al., 2001; Statistica soft, Inc., 2010) and XLSTAT 2014.5.03 softwares.

GenAlEx 6.502 (genetic analysis in excel) was also used to calculate pairwise population matrix of Nei unbiased genetic distance and genetic identity, PCoA, genetic diversity for each population as number of polymorphic loci, percent polymorphism, gene diversity and

Shannon–Weaver diversity index (H).

The iMEC (marker efficiency calculator) created by a group of researchers Amiryousefi et al. (2018) is coded in R and is available online at https://irscope.shinyapps.io/iMEC/ was used to detect the polymorphism information content (PIC), marker index (MI), expected heterozygosity (H) and discriminating power (D).

69

5.2. Results

5.2.1. ISSR Marker Banding Patterns

The pattern of DNA amplification obtained was clear and reproducible banding patterns based on the results from gel pictures taken for

each primer. The size of the band generated ranged from 100 to 1,900 bp (Table 5-2). The number of bands produced by each primer

varied from 17 bands for UBC-873 to 37 for UBC-841.

2 -

2 - D. sinicus-1 D. Ladder gigantus-1 D. gigantus-2 D. gigantus-3 D. multiple-1 B. multiple-2 B. multiple-3 B. hamilitonii-1 D. hamilitonii-2 D. hamilitonii-3 D. sinicus D. A. alpine-1 A. alpine-2 A. alpine-3 A. Ladder G. Sumatra-1 G. Sumatra-2 G. Sumatra-3 G. ampelxifolia-1 G. ampelxifolia-2 G. ampelxifolia-3 G. apus-1 G. apus-2 G. apus-3 D. latiflorus-1 D. latiflorus-2 D. latiflorus-3 P. dulcis-1 P. dulcis Ladder G. sumatra-1 D. asper-1 B. vulgaris-1 P. pubescens-1 B. oldhamii-1 D. gigantus-1 B. multiplex-1 D. hamilitonii-1 A. alpine-1 D. sinicus-1 D. membranaceus -1 B. vulgaris var. striata-1 B. tulda-1 D. brandisii-1

UBC -835 UBC -873 UBC -841

Figure 5-1: A representative of ISSR electrophoresis profile of 31 species of bamboo using ISSR A) UBC-835, B) UBC-873 and C) UBC-841 (single sample representative for fourteen bamboo species). 70

5.2.2. Level of polymorphism in ISSR primers

5.2.2.1.ISSR primers on genetic polymorphism

Highest number of scorable bands (NSB) was observed by primers UBC-841 (37), UBC-

835 (34), and UBC-834 (32) and least NSB was observed by primers UBC-873 (17) and

UBC-824 (19). The number of polymorphic loci (NPL) ranged from 37 (UBC-841) to 12

(UBC-873). Percentage of polymorphic loci (PPL) was 100% for majority of the primers and least PPL was observed by primers UBC-873 (70.59%) and average PPL for all primers was 95.6% respectively.

Based on the repeat motifs and anchorage property of primers, di-nucleotide repeat motifs showed higher PPL (98.83) than tri (88.89), tetra (86.36) and penta-nucleotide (82.61) repeat motifs. 3` anchored primers showed higher PPL (98.83) than 5` anchored (96.08).

Anchored primers show higher PPL (98.38) than unanchored ISSR primers (93.62).

The lowest heterozygosity value (0.0882) was from primer UBC-888 and the highest

(0.3686) was observed with primer UBC-834. Again di-nucleotide repeats show higher hetrozigosity (0.3667) than others. Similarly, the maximum and minimum Shanon’s information index was 0.5455 by UBC-834 and 0.1639 by UBC-888. Estimate of gene flow (Nm) was not observed for majority of primers except UBC-835 (0.0081) and UBC-

844 (0.0011) (Table 5-2).

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Table 5-2: Polymorphism of the fifteen ISSR primers on the phylogenetics study Individual primers Molecular size Primers range in bp NSB NPL PPL (%) H ± SD I ± SD Nm UBC -810 25 25 100 0.3801 ± 0.1315 0.5579 ± 0.1595 0.0000 1,400 -100 UBC -812 28 28 100 0.3996 ± 0.0989 0.5843 ± 0.1128 0.0000 1,400 -100 UBC -815 28 28 100 0.3861 ± 0.1052 0.5692 ± 0.1180 0.0000 1,400 -200 UBC -824 19 17 89.47 0.3389 ± 0.1626 0.5005 ± 0.2 186 0.0000 1,900 -200 UBC -834 32 32 100 0.3246 ± 0.1325 0.4943 ± 0.1630 0.0000 1,700 -100 UBC -835 34 34 100 0.4210 ± 0.0840 0.6089 ± 0.0916 0.0081 1,600 -100 UBC -840 30 29 96.67 0.3292 ± 0.2044 0.4955 ± 0.1873 0.0000 1,500 -100 UBC -841 37 37 100 0.3671 ± 0.1234 0.5449 ± 0.1470 0.0000 1,500 -100 UBC -844 24 24 100 0.2996 ± 0.1444 0.4624 ± 0.1793 0.0011 1,600 -100 UBC -864 27 24 88.89 0.3155 ± 0 .1484 0.4779 ± 0.1974 0.0000 1,400 -200 UBC -873 17 12 70.59 0.2354 ± 0.2008 0.3548 ± 0.2803 0.0000 950 -150 UBC -876 27 26 96.30 0.3390 ± 0.1426 0.5083 ± 0.1793 0.0000 1,300 -200 UBC -880 23 19 82.61 0.3323 ± 0.1499 0.5008 ± 0.1813 0.0000 1,100 -200 UBC -888 26 24 92.31 0.3223 ± 0.1744 0.4791 ± 0.2285 0.0000 1,200 -200 UBC -889 25 25 100 0.3892 ± 0.0925 0.5738 ± 0.1039 0.0000 1,000 -100 Average 26.8 25.86 95.62 All primers 402 391 97.26 0.3482 ± 0.1412 0.5186 ± 0.1777 0.0007 Based on repeat motif Di -nucleotides 257 254 98.83 0.3499 ± 0.1344 0.5225 ± 0.1661 0.0011 Tri -nucleotides 27 24 88.89 0.3155 ± 0.1484 0.4779 ± 0.1974 0.0000 Tetra -nucleotides 44 38 86.36 0.2990 ± 0.1729 0.4490 ± 0.2332 0.0000 Penta - nucleotides 23 19 82.61 0.3323 ± 0.1499 0.5008 ± 0.1813 0.0000 Based on anchorage property 3’ anchored 257 254 98.83 0.3499 ± 0.1344 0.5225 ± 0.1661 0.0011 5’ anchored 51 49 96.08 0.3551 ± 0.1430 0.5255 ± 0.1832 0.0000 3’ + 5’ anchored 308 303 98.38 0.3500 ± 0.1372 0.5219 ± 0.1707 0.0009 Un anchored 94 88 93.62 0.3422 ± 0.1544 0.5076 ± 0.1997 0.0000 NSB - number of scorable bands, NPL - number of polymorphic loci, PP - percent polymorphism, H - genetic diversity, I - Shanon’s information index and Nm - estimate of gene flow Remark : all di-nucleotides are 3’ anchored

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5.2.2.2. Calculating Markers Efficiency

The polymorphism information content (PIC), marker index (MI), expected heterozygosity

(H) and discriminating power (D) was inferred via iMEC

(https://irscope.shinyapps.io/iMEC/ ) online. The highest H, PIC and D were observed by anchored primers in general and 3’ anchored and di-nucleotide repeats (UBC-834 and

UBC-835) in specific. The H, PIC, MI and D values for anchored primers 0.460436,

0.373484, 0.460436 and 0.796385 values were recorded, 3’ anchored and also di- nucleotide repeats 0.478717, 0.365212, 0.478717 and 0.871969 values were recorded,

UBC-834 0.4964, 0.3566, 0.4964 and 0.9324 and UBC-810 0.4928, 0.3584, 0.4928 and

0.8065 values were recorded. The least H, PIC and D were observed by tri-nucleotides and

5’ anchored primers. Again di-nucleotide and anchored primers show higher D values than other repeat motif types and unanchored primers (table 5-3).

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Table 5-3: Polymorphism statistics calculated with iMEC for different types of primers for the 31 taxa of woody bamboos based on fifteen ISSR primers data set. ISSR Primer/Marker H PIC MI D UBC -810 0.4928 0.3584 0.4928 0.8065 UBC -812 0.485 9 0.3618 0.485 9 0.8271 UBC -815 0.4739 0.3675 0.47 40 0.8511 UBC -824 0.472 2 0.368 4 0.472 2 0.8542 UBC -834 0.4964 0.3566 0. 4964 0.9324 UBC -835 0.4723 0.3683 0.4723 0.930 5 UBC -840 0.4745 0.367 3 0.4745 0.8502 UBC -841 0.4723 0.3683 0.4723 0.882 7 UBC -844 0.468 2 0.370 3 0.468 2 0.9129 Di-nucleotides also 3' anchored 0.4787 0.3652 0.4787 0.8720 UBC -864 0.388 4 0.4044 0.388 4 0.705 9 Tri-nucleotide 0.3884 0.4044 0.3884 0.7059 UBC -873 0.384 9 0.405 8 0.384 9 0.6080 UBC -876 0.4705 0.3726 0.4705 0.8539 Tetra-nucleotides 0.4277 0.3892 0.4277 0.7340 UBC -880 0.416 2 0.393 3 0.4162 0.3498 Penta-nucleotide 0.4162 0.3933 0.4162 0.3498 UBC -888 0.468 2 0.370 3 0.468 2 0.674 4 UBC -889 0.416 2 0.393 3 0.416 2 0.7672 5' anchored 0.4422 0.3818 0.4422 0.7208 Overall average 0.456848 0.375099 0.456848 0.787134 Summary based on primers repeat motifs Di-nucleotides 0.478717 0.365212 0.478717 0.871969 Tri-nucleotides 0.388379 0.404425 0.388379 0.705887 Tetra-nucleotides 0.427713 0.389195 0.427713 0.730983 Penta- nucleotides 0.416156 0.393251 0.416156 0.349838 Summary based on primers anchorage property 3' anchored 0.478717 0.365212 0.478717 0.871969 5' anchored 0.442155 0.381756 0.442155 0.720802 3' + 5' anchored 0.460436 0.373484 0.460436 0.796385 Unanchored 0.410749 0.395624 0.410749 0.595569 Note : D = discriminating power; E = effective multiplex ratio; H = expected heterozygosity; Hav = mean heterozygosity; MI = marker index; PIC = polymorphism information content; R = resolving power

5.2.2.3.Band Pattern and Heterozygosity

Highest numbers of band patterns were observed in B. longinternode (248) followed by B.

vulgaris (Green), and G. sumatra (Green) (246) each. Numbers of private bands were

observed in B. chungii (Pakistani white bamboo) (9), others did not have such kind of bands. Majority of the bands were obtained from number of different bands with a

74

frequency ≥5% (NDBF ≥ 5%). Mean of expected heterozygosity (He ) and mean of

unbiased expected heterozygosity (uHe) along with standard errors showed higher values

in B. longinternode (0.17 ± 0.01, 0.20 ± 0.01 ) but for the majority of the taxas He and uHe

values found to be zero (table 5-4).

Table 5-4: Band patterns observed across 31 taxa of bamboos

NDBF NLCB NLCB Mean He ± Mean uHe Population NDB ≥ 5% NPB (≤25%) (≤50%) SE ± SE Gigantochloa sumatra (Black) 153 153 0 5 58 0.00 ± 0.00 0.00 ± 0.00 Dendrocalamus latiflorus 242 242 0 13 87 0.15 ± 0.01 0.18 ± 0.01 Guadua amp lexifolia 167 167 0 7 36 0.00 ± 0.00 0.00 ± 0.00 Gigantochloa apus 239 239 0 29 86 0.16 ± 0.01 0.19 ± 0.01 Phyllostachys dulcis 142 142 0 24 59 0.00 ± 0.00 0.00 ± 0.00 Gigantochloa atter 174 174 0 9 64 0.00 ± 0.00 0.00 ± 0.00 Dendrocalamus barbatus 227 227 0 15 88 0.12 ± 0.01 0.15 ± 0.01 Bambusa pol ymorpha 153 153 0 8 48 0.00 ± 0.00 0.00 ± 0.00 Dendrocalamus diannanesis 232 232 0 15 85 0.13 ± 0.01 0.16 ± 0.01 Dendrocalamus fuminesis 173 173 0 9 58 0.00 ± 0.00 0.00 ± 0.00 Dendrocalamus asper 168 168 0 7 37 0.00 ± 0.00 0.00 ± 0.00 Bambusa vulgaris (Green) 246 246 0 14 82 0.16 ± 0.01 0.19 ± 0.01 Phyllostachys pubescens 160 160 0 7 51 0.00 ± 0.00 0.00 ± 0.00 Gigantochloa sumatra (Green) 246 246 0 13 83 0.15 ± 0.01 0.18 ± 0.01 Bambusa oldhamii 172 172 0 6 36 0.00 ± 0.00 0.00 ± 0.00 Dendrocalamus gi gantus 165 165 0 6 35 0.00 ± 0.00 0.00 ± 0.00 Bambusa multiplex 191 191 0 10 49 0.06 ± 0.01 0.07 ± 0.01 Dendrocalamus hamilitonis 159 159 0 4 30 0.00 ± 0.00 0.00 ± 0.00 Arundinaria alpine (Eth. 2) 221 221 0 8 63 0.14 ± 0.01 0.17 ± 0.01 Dendrocalamus si nicus 134 134 0 4 36 0.00 ± 0.00 0.00 ± 0.00 Dendrocalamus membranaceus 164 164 0 17 63 0.00 ± 0.00 0.00 ± 0.00 Dendrocalamus laosenesis 242 242 0 19 102 0.15 ± 0.01 0.18 ± 0.01 Bambusa vulgaris var. striata 164 164 0 2 58 0.00 ± 0.00 0.00 ± 0.00 Dend rocalamus tulda 238 238 0 7 92 0.15 ± 0.01 0.18 ± 0.01 Dendrocalamus brandisii 157 157 0 5 53 0.00 ± 0.00 0.00 ± 0.00 Guadua angustifolia 172 172 0 9 43 0.00 ± 0.00 0.00 ± 0.00 Bambusa longinternode 248 248 0 15 88 0.17 ± 0.01 0.20 ± 0.01 Bambusa lapid ea 151 151 0 6 50 0.00 ± 0.00 0.00 ± 0.00 Oxytenanthera abyssinica (Eth.1) 236 236 0 16 85 0.16 ± 0.01 0.19 ± 0.01 Phyllostachys nigra (Pks. 1) 162 162 0 11 40 0.00 ± 0.00 0.00 ± 0.00 Bambusa chungii (Pks. 2) 154 154 9 19 66 0.00 ± 0.00 0.00 ± 0.00 Note: NDB = No. of different bands, NDBF ≥5% = No. of different bands with a frequency ≥5%, NPB = No. of bands unique to a single population, NLCB (≤25%) = No. of locally common bands (Freq. ≥5%) found in 25% or fewer populations, NLCB(≤ 50%) = No. of locally common bands (Freq. ≥ 5%) found in 50% or fewer populations, He = Expected heterozygosity = 2 * p * q, uHe = Unbiased expected heterozygosity = (2N / (2N-1)) * He Where for Diploid Binary data and assuming Hardy-Weinberg Equilibrium, q = (1 - Band Freq.)^0.5 and p = 1 - q. 75

Band patterns across populations

300 0.200 NDB 250 0.150 200 NDB ≥ 5% 150 0.100 NPB

Number 100 0.050 NLCB (≤ 25%) 50 NLCB (≤ 50%)

0 0.000 Heterozygosity Mean He D. lati D. D. sini D. B. lapi B. A. A. alpi P. nigr P. P. dulc P. D. tuld D. B. vulg B. B. poly B. D. laos D. G. atte G. B. oldh B. B. long B. D. giga D. D. dian D. B. mult B. D. fumi D. D. aspe D. D. barb D. D. bran D. B. chun B. P. pube P. G. apus G. O. O. abyy D. hami D. G. ampl G. G. angu G. D. memb D. B. vulg (S) vulg B. G. suma (B) suma G. Populations(G) suma G.

5.2.3. Nei’s Genetic Distance and Similarity

Nei’s genetic similarity between each pair of species ranged from 0.5124 to 0.9006. The

highest value was recorded between G. angustifolia and G. amplexifolia , while the lowest

value was observed between A. alpina and D. latiflorus. The highest genetic similarity for

Ethiopian woody bamboos O. abyssinica was found between D. membranaceus (0.64), B.

lapidea (0.63) and B. longinternode (0.62) and for A. alpine was found between G.

amplexifolia (0.602), B. vulgaris (Green) (0.58), and B. oldhamii (0.56) . The least genetic

similarity for O. abyssinica was found between G. apus (0.55), D. diannanesis (0.56) and

for A. alpine was found between D. latiflorus (0.51) and G. sumatra (Black) and D.

diannanesis (0.52).

5.2.4. Cluster Analysis

Intra taxa cluster analyses of UPGMA were computed for all woody bamboo species. The

UPGMA dendrogram resulting from a SAHN clustering analysis on the basis of Jaccard’s

coefficients of similarity was constructed. The Jaccard’s coefficient of similarity was

obtained after pair-wise comparisons performed using binary character matrices (of the

presence and absence) that were produced from amplified fragments.

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Dendrogram from the total primer was split into two clusters; the main cluster was divided into two sub-clusters. All the 31 taxas were split in different sub-clusters. Specifically, result of the total primer shows that, Ethiopian woody bamboos ( O. abyssinica clustered with tribe Bambusa (paleotropical woody bamboos) and A. alpina clustered with Guadua

(neotropical woody bamboos)). Pakistani woody bamboos P. nigra clustered with tribe

Phyllostachys (temperate woody bamboos) and B.chungii clustered with tribe Bambusa

(paleotropical woody bamboos). Primers were categorized in to their repeat motifs and anchorage property to observe their efficiency in constructing the woody bamboos.

Anchored primers which are the combination of di-nucleotide primers which are also 3’ anchored and 5’ anchored primers showed almost similar clustering with the whole primers whereas unanchored primers clustered O. abyssinica in to the tribe Phyllostachys . In terms of repeat motifs, di-nucleotides cluster the 31 bamboo taxas similar to the whole combinations of primers but other repeat motifs cluster the Ethiopian bamboos differently as of the total primers.

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G-sumatra-black G-sumatra-green G-apus G-atter D-latiflorus D-barbatus D-diannanesis D-fuminesis D-asper D-gigantus D-hamilitonis D-sinicus D-membranaceus D-laosenesis D-tulda D-brandisii B-polymorpha B-vulgaris-gree B-vulgaris-stri B-longinternode B-lapidea B-chungii-Pks B-oldhamii A B-multiplex O-abyssinica-Et G-amplexifolia G-angustifolia P-dulcis P-nigra-Pks P-pubescens A-alpina-Eth 0.29 0.41 0.54 0.66 0.78 Coefficient

G-sumatra-black G-sumatra-black G-sumatra-green G-sumatra-green G-apus G-apus G-atter G-atter D-latiflorus P-dulcis D-barbatus P-pubescens D-diannanesis P-nigra-Pks D-fuminesis D-latiflorus D-asper D-barbatus D-gigantus D-diannanesis D-hamilitonis D-fuminesis D-sinicus D-asper D-membranaceus D-gigantus D-laosenesis D-hamilitonis D-tulda D-sinicus D-brandisii D-membranaceus B-polymorpha D-laosenesis B-vulgaris-gree D-tulda B-vulgaris-stri D-brandisii B-longinternode C O-abyssinica-Et B-lapidea B-polymorpha B-chungii-Pks B-longinternode B-oldhamii B-lapidea B-multiplex B-chungii-Pks O-abyssinica-Et B-vulgaris-stri G-amplexifolia B-vulgaris-gree G-angustifolia B-oldhamii P-dulcis B-multiplex B P-nigra-Pks G-ampelxifolia P-pubescens G-angustifolia A-alpina-Eth A-alpina-Eth 0.29 0.41 0.54 0.66 0.78 0.22 0.38 0.54 0.70 0.86 Coefficient Coefficient

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G-sumatra-black G-sumatra-black G-apus G-atter P-dulcis D-latiflorus P-pubescens D-asper P-nigra-Pks D-diannanesis G-atter D-fuminesis O-abyssinica-Et D-gigantus D-latiflorus D-sinicus D-barbatus D-membranaceus D-sinicus D-tulda D-diannanesis D-brandisii D-fuminesis D-hamilitonis D-asper D-laosenesis D-hamilitonis D-barbatus D D-brandisii G-apus D-membranaceus G-sumatra-green D-tulda P-dulcis D-laosenesis P-pubescens D-gigantus B-oldhamii G-ampelxifolia B-chungii-Pks G-angustifolia B-longinternode A-alpina-Eth B-multiplex B-polymorpha B-vulgaris-stri B-multiplex P-nigra-Pks B-vulgaris-gree E A-alpina-Eth B-lapidea B-polymorpha B-oldhamii B-vulgaris-gree B-chungii-Pks B-lapidea G-sumatra-green G-ampelxifolia B-vulgaris-stri G-angustifolia B-longinternode O-abyssinica-Et 0.45 0.59 0.72 0.86 1.00 0.12 0.34 0.56 0.78 1.00 Coefficient Coefficient G-sumatra-black G-sumatra-black G-sumatra-green G-apus G-apus G-atter G-atter G-sumatra-green D-latiflorus P-dulcis D-barbatus P-pubescens D-diannanesis P-nigra-Pks D-fuminesis O-abyssinica-Et D-asper D-latiflorus D-gigantus D-hamilitonis D-hamilitonis D-asper D-sinicus D-diannanesis D-membranaceus D-fuminesis D-laosenesis D-barbatus D-tulda D-gigantus D-brandisii D-laosenesis B-polymorpha D-sinicus B-vulgaris-gree D-membranaceus B-vulgaris-stri D-tulda B-longinternode D-brandisii B-lapidea B-polymorpha B-chungii-Pks B-oldhamii B-oldhamii B-vulgaris-gree B-multiplex B-vulgaris-stri O-abyssinica-Et B-lapidea G-amplexifolia B-multiplex F G-angustifolia B-longinternode P-dulcis G B-chungii-Pks P-nigra-Pks G-ampelxifolia P-pubescens G-angustifolia A-alpina-Eth A-alpina-Eth 0.29 0.41 0.54 0.66 0.78 0.39 0.53 0.67 0.82 0.96 Coefficient Coefficient

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G-sumatra-black G-sumatra-black G-sumatra-green G-apus G-apus G-sumatra-green G-atter G-atter D-latiflorus P-dulcis D-barbatus P-pubescens D-diannanesis P-nigra-Pks D-fuminesis O-abyssinica-Et D-asper B-polymorpha D-gigantus B-vulgaris-gree D-hamilitonis B-lapidea D-sinicus B-multiplex D-membranaceus B-longinternode D-laosenesis B-vulgaris-stri D-tulda B-chungii-Pks D-brandisii B-oldhamii B-polymorpha D-latiflorus B-vulgaris-gree D-barbatus B-vulgaris-stri D-asper B-longinternode D-gigantus H B-lapidea I D-diannanesis B-chungii-Pks D-fuminesis B-oldhamii D-brandisii B-multiplex D-tulda O-abyssinica-Et D-hamilitonis G-amplexifolia D-laosenesis G-angustifolia D-sinicus P-dulcis D-membranaceus P-nigra-Pks G-ampelxifolia P-pubescens G-angustifolia A-alpina-Eth A-alpina-Eth 0.29 0.41 0.54 0.66 0.78 0.35 0.50 0.64 0.79 0.93 Coefficient Coefficient Figure 5-2: UPGMA dendrogram depicting clustering patterns for 31 taxa of bamboo based on Jaccard’s similarity coefficient. A. Aggregate of total primers, B. Di-nucleotide also 3’ anchored, C. Tri-nucleotide, D. Tetra-nucleotide, E. Penta-nucleotide, F. 3’ anchored, G. 5’ anchored, H. 3’ and 5’ anchored and I. Unanchored ISSR primers.

5.2.5. Principal Coordinate (PCoA) Analysis

The data obtained from 15 ISSR primers were used in PCoA analysis using Jaccard’s

coefficients of similarity for grouping of individuals and clustering of O. abyssinica using

three coordinates (Figure 5-3A). The first three coordinates of the PCO having Eigen

values of 10.57, 6.96 and 4.76 with variance of 16.85%, 11.09% and 7.59% were used to

construct the three-dimensional (3D) graphs. In STATISTICA, majority of the taxa were

grouped together and that was difficult to differentiate one another. But XLSTAT

categorized in to three groups (Figure 5-3B). Majority of the Dendrocalamus were

categorized in group III (+/-) and majority of Bambusa together with Oxytenanthera were

clustered in group II (in the same sign (-/-) respectively. Gigantochloa , Guadua ,

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Phyllostachys and Arundinaria both of them expected among the temperate woody bamboos were clustered together at the opposite sign (+/-) in group IV.

G.ampelxifolia-1G.ampelxifolia-2G.ampelxifolia-3G.angustifolia-1G.angustifolia-2G.angustifolia-3

P.nigra-(Pks-01)-1P.nigra-(Pks-01)-2P.nigra-(Pks-01)-3 P.pubescens-1P.pubescens-2P.pubescens-3P.dulcis-1P.dulcis-2P.dulcis-3A.alpina-1A.alpina-2A.alpina-3 O.abyssinica-1O.abyssinica-2O.abyssinica-3 D.latiflorus-1D.latiflorus-2D.latiflorus-3D.membranaceus-1D.membranaceus-2D.membranaceus-3D.barbatus-1D.barbatus-2D.barbatus-3D.sinicus-3D.sinicus-1D.sinicus-2D.laosenesis-1D.laosenesis-2D.laosenesis-3D.gigantus-1D.gigantus-2D.gigantus-3D.fuminesis-1D.fuminesis-2D.fuminesis-3D.asper-1D.asper-2D.asper-3 D.diannanesis-3D.diannanesis-1D.diannanesis-2D.hamilitonis-1D.hamilitonis-2D.hamilitonis-3 G.apus-1G.apus-2G.apus-3 D.tulda-1D.tulda-2D.tulda-3 G.sumatra-(Black)-1G.sumatra-(Black)-3G.sumatra-(Black)-2G.atter-2G.atter-3G.atter-1 D.brandisii-1D.brandisii-2D.brandisii-3 G.sumatra-(Green)-1G.sumatra-(Green)-2G.sumatra-(Green)-3

B.multiplex-1B.multiplex-2B.multiplex-3 B.vulgaris-var.striata-1B.vulgaris-var.striata-2B.vulgaris-var.striata-3B.longinternode-1B.longinternode-2B.longinternode-3B.vulgaris-(Green)-3B.vulgaris-(Green)-1B.vulgaris-(Green)-2 B.chungii-(Pks-02)-1B.chungii-(Pks-02)-2B.chungii-(Pks-02)-3B.polymorpha-1B.polymorpha-2B.polymorpha-3B.lapidea-1B.lapidea-2B.lapidea-3B.oldhamii-1B.oldhamii-2B.oldhamii-3

A

81

Observations (axes F1 and F2: 28.60 %) 15

A. alpina G. apus P. pubescens P. nigra (Pks-01) 10 P. dulcisG. atter

G. sumatra (Green) G. ampelxifolia G. angustifolia

5

F2 (11.88F2%) 0 D.D. latiflorus barbatus D. diannanesisD. fuminesis D. sinicusD. membranaceusD.D. laosenesis asperD. gigantus D. tulda D. hamilitonis D. brandisii

-5 B. multiplex

O. abyssinica B. B.vulgaris oldhamii var. striata B. B.PolymorphalapideaB. longinternode chungiiB. vulgaris(Yellow) (Pks-02) (Green) B -10 -20 -15 -10 -5 0 5 10 15 F1 (16.72 %)

Figure 5-3: Three-dimensional representation of principal coordinate analysis of genetic relationships among 31 species of bamboo inferred from similarity matrix using (A) the Jaccard’s index using STATISTICA and (B) Pearson PCA method using XLSTAT.

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5.3. Discussion Though molecular data sets can provide useful information on various aspects of taxonomy, there is limited information available on phylogenetics study, genetic diversity and/or population structure of bamboos in general and Ethiopian bamboos in particular

Mukherjee et al., 2010. Molecular techniques based on PCR such as RAPD (Friar and

Kochert 1991, 1994), ISSR (Mukherjee et al., 2010; Goyal and Sen 2015), AFLP (Loh et al., 2000), SSR (Sharma et al., 2009; Adem et al., 2019), EST-SSR (Barkley et al., 2005) and cpDNA genes (Triplett and Clark, 2010) are being used for phylogenetic studies in tropical and temperate woody bamboos. RAPD was utilized to authenticate intrageneric classification and to assess genetic relationships among species of Phyllostachys,

Dendrocalamus, and Bambusa (Gielis 1997; Ding 1998; Nayak et al., 2003; Das et al.,

2007; Sun et al., 2006; Hsiao and Rieseberg 1994; Bhattacharya et al., 2006). Similarly,

Mukherjee et al. (2010) used the ISSR and EST-based primers for the genetic relationships among 22 taxa of bamboos and Goyal and Sen (2015) used RAPD and ISSR primers for the phylogenetic relationships among 29 accessions of bamboos encountered in North

Bengal, India.

So far, there is no report on the extents of phylogenetics study and molecular diversity in general and ISSR based marker system in particular for introduced bamboo species in

Ethiopia. Hence, as the first step in the development of genomic tools and resources that could contribute to the development of strategies for selective use of introduced bamboo species, effective conservation and sustainable utilization of the introduced bamboo for ecological and economic gains by better understanding the genetic diversity profile at the species and population level, we examined and assessed 31 taxa of bamboos using fifteen 83

ISSR markers. These molecular markers have been successfully utilized for assessing the phylogenetics and genetic similarity and revealed a remarkable molecular discrimination between the 31 woody bamboos.

The fifteen ISSR primers used for this study have retrieved a total of 402 scorable bands.

The maximum number of scorable bands (37) was scored by primer (GA) 8YC - UBC-841

and the minimum by primer (GACA)4 - UBC-873 (17) and average PPL for all primers

was 95.6%. Mukherjee et al. (2010) has found the maximum of 19 and minimum of 8 bands by ISSR primers (GACA) 4G and T(GACA) 4 with a total of 152 scorable bands from

12 ISSR primers. Goyal and Sen (2015) reported the maximum 33 and minimum of 22 bands by ISSR primers (TC) 8G - UBC824 and (TC) 8A - UBC822 with a total of 244 scorable bands from 9 ISSR primers and average PPL for all primers was 100%.

Nei’s genetic similarity between each pair of species ranged from 0.5124 to 0.9006. The highest value was recorded between G. angustifolia and G. amplexifolia , while the lowest

value was found between A. alpina and D. latiflorus. The highest genetic similarity for

Ethiopian woody bamboos O. abyssinica was found between D. membranaceus (0.64), B. lapidea (0.63) and B. longinternode (0.62) and for A. alpine was found between G.

amplexifolia (0.602), B. vulgaris (Green) (0.58), and B. oldhamii (0.56) . The least genetic

similarity for O. abyssinica was found between G. apus (0.55), D. diannanesis (0.56) and

for A. alpine was found between D. latiflorus (0.51) and G. sumatra (Black) and D.

diannanesis (0.52). Nei’s genetic similarity between each pair of species ranged between

0.613 and 0.960 for the phylogenetic relationships among 29 accessions of bamboos

84 encountered in North Bengal (Goyal and Sen, 2015) and Mukherjee et al. (2010) reported between the range of 0.12 and 0.741. Loh et al. (2000), using AFLP to study the genetic

diversity of 15 bamboo species belonging to Bambusa , Dendrocalamus , Gigantochloa , and

Phylostachys in the subtribe Bambusinae, found that D. giganteus had the least genetic similarity to any of the other species.

The dendrogram constructed based on the data from the ISSR random primers showed that most of the Bambusa , Dendrocalamus , Gigantochloa , Phyllostachys and Guadua species clustered together. But A. alpina (Ethiopian highland bamboo or type of temperate woody bamboo) a genus of Oldeania forms a cluster with a genus Guadua (temperate woody bamboo) and O. abyssinica (Ethiopian lowland bamboo or tropical woody bamboo) clustered with Bambusa (tropical woody bamboo). Even though SNPs study clustered A. alpina with the genus Phyllostachys and ISSR study clustered with Guadua , both the

Phyllostachys and Guadua are among temperate woody bambos.

Though the present investigation throws some information on the classification and phylogeny of the introduced bamboos based on analysis of ISSR markers, there is a need for further critical work involving molecular markers giving greater genome coverage.

Furthermore, more studies are required to improve our understanding of genetic diversity in bamboo at the population level.

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CHAPTER SIX

6. Genetic Diversity and Population Structure Analysis of Ethiopian Lowland Bamboo [Bambusinea: Oxytenanthera abyssinica (A. Rich.) Munro] Using ISSR Marker

6.1. Materials and Methods

6.1.1. Plant Material Collection and Sampling Strategy

Five to seven young fresh leaves of thirteen individual plants (10 individual plants representing a single population and three were used as a reserve) from thirteen Ethiopian lowland bamboo growing areas across the country were collected. Since the plant is gregarious in seed formation, somatic clonal propagation, and clump formation, samples were taken to the minimum of 25m diameter distance in all directions randomly. GPS data and altitudinal information for each samples presented in table 4-1. Maps showing sample coverage and collection sites are described in figure 4-1.

6.1.2. DNA Extraction and Primer Screening

Five to seven young fresh leaves were preserved in the zip-lock plastic bag with appropriate silica gel. Each population was represented by ten individuals. Silica gel dried leaves were crashed by a mixer and miller (Retsch Mixer Mill MM 400). Genomic DNA was isolated separately using a modified 2% CTAB DNA isolation method at Plant Molecular Biology

Laboratory (PMBL) and Plant Genetics Research Laboratory (PGRL) of AAU. Test gel electrophoresis in 1% agarose and nanodrop (Thermo SCIENTIFIC NANODROP 2000

Spectrophotometer) of each sample was measured and those with high DNA quality used

86 for PCR amplification after normalization of each sample to a concentration of 100 ng. Gel documentation was taken by BIORAD Gel Doc TM EZ System Imager.

Nineteen ISSR primers were chosen out of 38 ISSR primers designed from the University of British Colombia (UBC) and previous work on the literature. Among nineteen primers; ten were di-nucleotide, two were tri-nucleotide, two were tetra-nucleotide, three were penta-nucleotide, and two were 5` anchored primers. Primers were further categorized into

3` anchored, 5` anchored, and un-anchored based on anchorage property (table 6-1).

Table 6-1: ISSR primers used for PCR analysis for the study of Ethiopian lowland bamboo Nucleotide Primer name Repeat Anchorage Selected Optimized No. Sequence or Code motifs property for PCR Ta

1 (AG) 8T UBC807 Dinucleotide 3’ -anchored

2 (AG) 8C UBC808 '' '' 3 (GA) 8T UBC810 '' '' √ 42 4 (GA) 8A UBC812 '' '' √ 42

5 (CT) 8T UBC813 '' '' 6 (CT) 8G UBC815 '' '' √ 42

7 (TC) 8C UBC823 '' '' 8 (TC) 8G UBC824 '' '' √ 43

9 (AC) 8T UBC825 '' '' 10 (AG) 8YT UBC834 '' '' √ 43 11 (AG) 8YC UBC835 '' '' √ 45 12 (GA) 8YT UBC840 '' '' √ 42 13 (GA) 8YC UBC841 '' '' √ 43

14 (GA) 8YG UBC842 '' '' 15 (CT) 8RC UBC844 '' '' √ 43

16 (CT) 8RG UBC845 '' '' 17 (CA) 8RG UBC848 '' '' √ 47

18 (GT) 8YG UBC851 '' ''

19 (TC) 8RT UBC853 '' ''

20 (TC) 8RG UBC854 '' ''

21 (AC) 8YG UBC857 '' '' 22 (A CC) 6 UBC861 Tri Unanchored √ 55

23 (AGC) 6 UBC862 '' ''

24 (AGT) 6 UBC863 '' '' 25 (ATG) 6 UBC864 '' '' √ 39

26 (GATA) 4 UBC872 Tetra “ 27 (GACA) 4 UBC873 '' '' √ 42

28 (CCCT) 4 UBC874 '' '' 87

29 (CTAG) 4 UBC875 '' '' 30 (GATA) 2(GACA) 2 UBC876 '' '' √ 39

31 (CTTCA) 3 UBC879 Penta '' 32 (GGAGA) 3 UBC880 '' '' √ 45 33 (GGGTG) 3 UBC881 '' '' √ 47 34 BDB(CA) 7 UBC888 5’ -anchored 5’ -anchored √ 47 35 DBD(AC) 7 UBC889 '' '' √ 45

36 (AGG) 6 ISSR_1 Tri Unanchored 37 (GACAC) 4 ISSR_2 Penta '' √ 55

38 (AC TG) 4 ISSR_3 Tetra '' Y = C or T (PYramidine); R = A or G ‰ (PuRine); B = C, G, or T ‰ (not A); D = A, G, or T ‰ (not C)

6.1.3. ISSR-PCR Amplification and Gel Electrophoresis

Each DNA amplification reaction was performed in a final volume of 10µl containing 5.5

µl 2x Taq plus Master Mix (containing Taq DNA polymerase, dNTPs, MgCl 2, PCR buffer,

PCR reaction enhancer, stabilizer and a blue tracer dye), 3.5 µl ddH 2O, 0.5 µl ISSR primer and 0.5 µl normalized genomic DNA. The blue dye and a stabilizer of 2x Taq plus Master

Mix help to directly load the final products onto a gel for analysis. The thermal profile included pre-PCR denaturation at 94 °C for 4 minutes followed by 35 cycles of denaturing at 94 °C for 30 seconds, annealing (39 - 55 °C) for 30 seconds (Table 6-2), extension at

72°C for 1 minute and a final extension at 72 °C for 10 minutes. The PCR products were stored at 4 °C until loading on gel electrophoresis. Five mocroliter of ISSR-amplification product of each sample DNA was loaded and were resolved in 1.67% agarose gels in 0.5x

TBE buffer at constant 100 V for 1:30 - 2h. The agarose solution was stained with 3.0 µl

Ethidium Bromide after the boiling of the powder and 0.5% TBE buffer. The ISSR profiles were visualized and photographed under BIORAD Gel Doc TM EZ System Imager connected to PC with Image Lab software, and stored for later data scoring. To estimate the molecular sizes of the resolved fragment, a 100bp DNA marker was used.

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6.1.4. Scoring and Data Analysis

Bands were scored manually. According to the weight of the DNA ladder (100 bp), the same weight bands were marked as a line. The bands that were clearly visible and repeatable on the electrophoresis map were marked as "1" , the absence of a band at the

same site was marked as "0" and "?" for the ambiguous bands that were not clearly shown were scored as a missing data. Intensity variations among fragments having approximately the same molecular size were not considered although in some cases intensity differences of the bands were observed.

A binary data matrix was compiled with individuals in the column and the ISSR markers in the row for each primer set and vice-versa according to the requirements of the software.

Each amplified fragments was named by the code of the primers across the row and/or column followed by the Arabic numbers starting from the fragment having high molecular weight to the fragments with low molecular weight. Both the total number of bands amplified by each primer and the number of polymorphic bands were calculated. On the basis of the recorded band profiles, different software was employed for the analysis of the data.

POPGENE version1.32 (Yeh et al., 1999) and GenAlEx version 6.5 (genetic analysis in excel) (Peakall and Smouse 2012) were used to calculate genetic diversity for each population as the number of polymorphic loci, percent polymorphism, gene diversity, and

Shannon diversity index. GenAlEx6.502 was also used to calculate band patterns on its frequency and polymorphism. Shannon diversity index (H) was calculated as H = -

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n ∑i=1 Pi ln 2 Pi where pi is the frequency of a given band for each population (Lewontin,

1972). Shannon’s index of diversity was used to measure the total diversity (Hsp) for the species as well as the mean diversity per population (Hpop). The proportion of diversity

within and between populations was then calculated as and 1 − respectively.

Analysis of molecular variance (AMOVA) was used to calculate the F-statistics that used

to estimate the proportion of genetic variability found among populations (FST ), among populations within groups (FSC ) and among groups (FCT ) using Areliquin version 3.01

(Excoffier et al., 2006) and GenAlEx6.503 (Peakall and Smouse, 2012). The genetic similarity matrix among the hundred and thirty individual samples of O. abyssinica was calculated in all pair-wise comparisons following Jaccard’s similarity coefficients.

NTSYS- pc version 2.02 (Rohlf, 2000) and Free Tree 0.9.1.50 (Pavlicek et al., 1999) software was used to calculate Jaccard’s similarity coefficient which is calculated as:- S = + + Where, “a” is the total number of bands shared between individuals i and j, “b” is the total number of bands present in individual i but not in individual j and “c” is the total number of bands present in individual j but not in individual i.

NTSYS was also used to generate the unweighted pair group method with arithmetic mean

(UPGMA) phenogram to analyze a sequential, agglomerative, hierarchical, and nested

(SAHN) cluster analysis using the similarity matrix and compare the individual genotypes.

The neighbor-joining (NJ) method (Saitou and Nei 1987; Studier and Keppler, 1988) was

used to compare individual genotypes and evaluate patterns of genotype clustering using

Free Tree 0.9.1.50 Software (Pavlicek et al., 1999). The major difference between the two 90 algorithms is that UPGMA assumes equal rates of evolution (molecular clock assumption) along all branches, whereas neighbor-joining assumes variations in the rate of change

(Saitou and Nei, 1987; Studier and Keppler, 1988; Nei and Kumar, 2000; Lan and Reeves,

2002).

Patterns of genetic variation among individual samples were also further examined with three dimensions with the help of principal coordinate analysis (PCO) on the basis of

Jaccard’s coefficients of similarities (Jaccard’s, 1908), which was calculated using PAST software version1.18 (Hammer et al., 2001). The first three axis were later used to construct the scatter plot with STATISTICA version 12.0 (Statistica soft, Inc., 2010) and XLSTAT

2014.5.03 software.

The polymorphism information content (PIC), marker index (MI), expected heterozygosity

(H) and discriminating power (D) were detected by the web application iMEC (marker efficiency calculator) created by a group of researchers Amiryousefi et al. (2018) at https://irscope.shinyapps.io/iMEC/ .

A Bayesian model-based clustering algorithm in STRUCTURE ver. 2.3.4 (Pritchard et al.,

2000; Falush et al., 2003) was applied to infer the pattern of population structure and detection of admixture. To determine the most likely number of populations (K), a burn-in period of 50,000 was used in each run, and data were collected over 500,000 Markov Chain

Monte Carlo (MCMC) replications for K = 1 to K = 13 using 20 iterations for each K. The test takes more than 300 h for analysis in PC having 8GB RAM and core i7 processor. The

91 optimum K value was predicted following the simulation method of Evanno et al. (2005)

using the web-based STRUCTURE HARVESTER ver. 0.6.94 (Earl, 2012). Bar plot for

the optimum K was determined using Clumpak (Cluster Markov Packager Across K) beta

version (Kopelman, 2015).

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6.2. Results

6.2.1. ISSR Marker Banding Patterns

Fragment patterns generated by the nineteen ISSR primers; (ten were di-nucleotide, two were tri-nucleotide, two were tetra-nucleotide, three were penta-nucleotide, and two were

5` anchored) were analyzed among hundred and thirty individuals of O. abyssinica representing thirteen populations. The pattern of DNA amplification obtained was clear and reproducible banding patterns based on the results from gel pictures taken for each primer (Figure 6-1). The size of the band generated ranged from 100 to 1,700 bp (Table 6-

2). The number of bands produced by each primer varied from 13 bands for UBC-844 to

24 for UBC-815. Three hundred forty eight bands were scored in which two hundred ninety four fragments showed polymorphisms.

Based on the repeat motifs property of primers, di-nucleotide repeat motifs with 10 primers produced 185 scorable bands, tri-nucleotides 32, tetra-nucleotides 39 and penta-

nucleotides produced 56 scorable bands. Based on the anchorage property of primers,

anchored primers produced 221 bands and unanchored primers produced 127 bands. 3’

anchored di-nucleotide primeres produced 185 bands, whereas 5’ anchored primers produced 56 bands (Table 6-2).

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Ladder SNK05 SNK06 SNK07 SNK08 SNK09 SNK10 BMM01 BMM02 BMM03 BMM04 BMM05 BMM06 BMM07 BMM08 GMA01 GMA02 GMA03 GMA04 GMA05 GMA06 GMA07 GMA08 GMA09 GMA10 SNK01 SNK02 SNK03 SNK04 Ladder Ladder Ladder Ladder Ladder BMP-01 BMP-02 BMP-03 BMP-04 BMP-05 BMP-06 BMP-07 BMP-08 BMP-09 BMP-10 BKK-01 BKK-02 BKK-03

Figure 6-1: A representative of ISSR electrophoresis profile of 13 populations of O. abyssinica using ISSR markers A) UBC-834, B) UBC-845 and C) UBC-888.

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6.2.2. Level of Polymorphism of Ethiopian Lowland Bamboo

6.2.2.1.ISSR Primers on Genetic Polymorphism of Ethiopian Lowland Bamboo

The highest number of scorable bands (NSB) was revealed by primers UBC-815 (24),

UBC-835 (23), UBC-834 (22) and UBC-888 (22) and least NSB was exhibited by primers

UBC-844 (13) and UBC-889 (14). The number of polymorphic loci (NPL) ranged from 24

(UBC-815) to 9 (UBC-889). Percentage of polymorphic loci (PPL) was 100% for primers

UBC-812, UBC-815 and UBC-834 and least PPL was shown by primers UBC-888

(54.55%) and UBC-889 (64.29%) and average PPL for all primers was 84.48% respectively. Based on the repeat motifs and anchorage property of primers, di-nucleotide repeat motifs showed higher PPL (94.05) than tri (78.12 ), tetra (74.36 ) and penta-

nucleotide (80.36) repeat motifs. 3` anchored primers showed higher PPL (94.05) than 5`

anchored (58.33). Anchored primers showed higher PPL (88.24) than unanchored ISSR primers (77.95).

The lowest heterozygosity (H) value (0.1451 ± 0.1633) was observed from primer UBC-

848 and the highest (0.3747 ± 0.1784) was primer UBC-812. Again di-nucleotide repeats showed higher heterozygosity (0.2894 ± 0.1780) than others. Similarly, the maximum and minimum Shanon’s information index (I) was 0.5506 ± 0.1389 by UBC-834 and 0.5428 ±

0.2197 by UBC-812. The highest estimate of gene flow (Nm) was shown by UBC-888

(3.2746) and least Nm was shown by UBC-861 (0.3456). The average Nm for overall primers was 1.5474. Tetra-nucleotide ( 2.4322) and 5’ anchored (2.4821) primers showed the highest Nm values (Table 6-2).

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Table 6-2: Polymorphism of the nineteen ISSR primers on 13 populations of O. abyssinica along with molecular size ranges in bp. Individual primers Molecular size Primers NSB NPL PPL (%) H ± SD I ± SD Nm range in bp UBC -810 18 16 88.89 0.2130 ± 0.2037 0.3322 ± 0.2632 2.1307 1,400 -100 UBC -812 19 19 100 0.3747 ± 0.1784 0.5428 ± 0.2197 2.9205 1,300 -300 UBC -815 24 24 100 0.3318 ± 0.1638 0.4973 ± 0.1992 2.2082 1,400 -200 UBC -824 16 15 93.75 0.3149 ± 0.1563 0.4749 ± 0.2082 1.5946 1,600 -300 UBC -834 22 22 100 0.3712 ± 0.1173 0.5506 ± 0.1389 1.4004 1,700 -200 UBC -835 23 22 95.65 0.2776 ± 0 .1623 0.4307 ± 0.2046 1.1409 1,600 -100 UBC -840 16 15 93.75 0.2826 ± 0.2044 0.4242 ± 0.2629 2.9005 1,500 -150 UBC -841 16 14 87.50 0.3050 ± 0.2012 0.4500 ± 0.2665 2.5796 1,100 -100 UBC -844 13 12 92.31 0.2314 ± 0.1714 0.3678 ± 0.2243 1.2566 950 -350 UBC -848 18 15 83.33 0.1451 ± 0.1633 0.2546 ± 0.2047 0.3496 950 -150 UBC -861 14 12 85.71 0. 2530 ± 0.1835 0.3905 ± 0.2437 0.3456 1,300 -300 UBC -864 18 13 72.22 0.2775 ± 0.1983 0.4087 ± 0.2832 1.8663 1,400 -400 UBC -873 21 16 76.19 0.2603 ± 0.2106 0.3857 ± 0.2884 2.5901 900 -200 UBC -876 18 13 72.22 0.2520 ± 0.2214 0.3711 ± 0.3012 2.2620 1,100 -300 UBC -880 21 19 90.48 0.3311 ± 0.1962 0.4844 ± 0.2537 1.1703 1,100 -200 UBC -881 19 13 68.42 0.1913 ± 0.2157 0.2899 ± 0.2912 1.9785 1,100 -200 UBC -888 22 12 54.55 0.1542 ± 0.2121 0.2316 ± 0.2911 3.2746 950 -300 UBC -889 14 9 64.29 0.2619 ± 0.2297 0.3778 ± 0.31 97 2.0015 900 -200 (GACAC)4 16 13 81.25 0.2594 ± 0.2081 0.3892 ± 0.2775 0.8541 1,200 -300 Average 18.31579 15.58 84.48 0.2702 ± 0.1945 0.4061 ±0.2595 1.5474 All primers 348 294 Based on repeat motif Di -nucleotides 185 174 94.05 0.2894 ± 0.1780 0. 4389 ± 0.2288 1.6598 Tri -nucleotides 32 25 78.12 0.2668 ± 0.1893 0.4007 ± 0.2626 0.8552 Tetra -nucleotides 39 29 74.36 0.2565 ± 0.2128 0.3789 ± 0.2906 2.4322 Penta - nucleotides 56 45 80.36 0.2632 ± 0.2112 0.3912 ± 0.2811 1.1952 Based on anchorage property 3’ anchored 185 174 94.05 0.2894 ± 0.1780 0.4389 ± 0.2288 1.6598 5’ anchored 36 21 58.33 0.1961 ± 0.2223 0.2884 ± 0.3067 2.4821 3’ + 5’ anchored 221 195 88.24 0.2742 ± 0.1885 0.4144 ± 0.2487 1.7315 Un anchored 127 99 77.95 0.2620 ± 0.2048 0. 3898 ± 0.2775 1.3081 NSB - number of scorable bands, NPL - number of polymorphic loci, PP - percent polymorphism, H - genetic diversity, I - Shanon’s information index and Nm - estimate of gene flow. ( Remark) : all di-nucleotides are 3’ anchored 96

6.2.2.2.Calculating Markers Efficiency

Online marker efficiency calculator (iMEC) ( https://irscope.shinyapps.io/iMEC/ ) were used to calculate the polymorphism information content (PIC), marker index (MI), expected heterozygosity (H) and discriminating power (D). The highest H, PIC and D were shown by anchored primers in general and 3’ anchored and di-nucleotide repeats, specifically (UBC-834 and UBC-835). The H, PIC, MI and D values for anchored primers were 0.503661, 0.470489, 0.503661 and 0.455827. 3’ anchored and also di-nucleotide repeats were 0.520932, 0.459651, 0.520932 and 0.698063. UBC-834 were 0.732223,

0.507292, 0.732223 and 0.438911 and UBC-835 were 0.686454, 0.508061, 0.686454and

0.323554. The least H, PIC and D were observed by tri-nucleotides and 5’ anchored primers. Again di-nucleotide and anchored primers showed higher D values than other repeat motif types and unanchored primers (Table 6-3).

Table 6-3: Polymorphism statistics calculated with iMEC for different types of primers for the lowland bamboo ( O. abyssinica ) based on nineteen ISSR primers data set. ISSR Primer/Marker H PIC MI D UBC -810 0.465799 0.447393 0.465799 0.863768 UBC -812 0.499475 0.43114 0.4994 75 0.766033 UBC -815 0.515089 0.46009 0.515089 0.844063 UBC -824 0.482959 0.439253 0.482959 0.833903 UBC -834 0.732223 0.507292 0.732223 0.920051 UBC -835 0.686454 0.508061 0.686454 0.896514 UBC -840 0.485022 0.438254 0.485022 0.829166 UBC -841 0.499998 0. 430879 0.499998 0.751081 UBC -844 0.436556 0.460587 0.436556 0.323554 UBC -848 0.40574 0.473565 0.40574 0.438911 Di-nucleotides + 3' anchored 0.520932 0.459651 0.520932 0.746704 UBC -861 0.477973 0.441648 0.477973 0.357648 UBC -864 0.483738 0.438876 0.483 738 0.651802 Tri-nucleotides + Unanchored 0.480856 0.440262 0.480856 0.504725 UBC -873 0.495109 0.433311 0.495109 0.698195 UBC -876 0.537861 0.460926 0.537861 0.696486 Tetra-nucleotides + Unanchored 0.516485 0.447119 0.516485 0.697341 UBC -880 0.499527 0.431114 0.499527 0.269529 97

UBC -881 0.494796 0.433466 0.494796 0.253031 (GACAC)4 0.499963 0.430896 0.499963 0.745775 Penta-nucleotides + Unanchored 0.498095 0.431825 0.498095 0.422778 UBC -888 0.482824 0.474689 0.482824 0.157652 UBC -889 0.489958 0.487964 0.489958 0.73447 5' anchored 0.486391 0.481327 0.486391 0.446061 Overall 0.509003 0.454179 0.509003 0.633244 Summary based on primers repeat motifs Di-nucleotides 0.520932 0.459651 0.520932 0.746704 Tri-nucleotides 0.480856 0.440262 0.480856 0.504725 Tetra-nucleotides 0.516485 0.447119 0.516485 0.697341 Penta- nucleotides 0.498095 0.431825 0.498095 0.422778 Summary based on primers anchorage property 3' anchored 0.520932 0.459651 0.520932 0.746704 5' anchored 0.486391 0.481327 0.486391 0.446061 3' + 5' anchored 0.503661 0.470489 0.503661 0.596383 Unanchored 0.49885 0.437525 0.49885 0.592655 Note : D = discriminating power; E = effective multiplex ratio; H = expected heterozygosity; Hav = mean heterozygosity; MI = marker index; PIC = polymorphism information content; R = resolving power

6.2.2.3.Band Pattern and Heterozygosity

The highest number of band patterns were observed in Koyshe population (227) followed by Guba, and Pawe populations (219) each. Extremely highest number of private bands were observed in Gambella populations (69), 6 in Koyshe and 1 in Pawe population. There were no private bands on the other populations. The majority of the bands were obtained from the number of different bands with a frequency of ≥5% (NDBF ≥ 5%). Mean of expected heterozygosity (He ) and mean of unbiased expected heterozygosity (uHe) along with standard errors showed higher values in Guba (0.219 ± 0.013, 0.231 ± 0.013) and

Dabu Hena populations (0.218 ± 0.013, 0.229 ± 0.014).

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Table 6-4: Band patterns observed across Ethiopian lowland bamboo populations using nineteen ISSR bands Region – Zone NDBF NLCB NLCB Mean uHe ± Population NDB NPB Mean He ± SE ≥ 5% (≤25%) (≤50%) SE Gambella-Gambella Abol 215 215 66 24 35 0.198 ± 0.013 0.208 ± 0.013 SNNPs-Konta Special Wereda Koyshe 227 227 6 16 28 0.210 ± 0.013 0.221 ± 0.014 Mandura 195 195 0 6 13 0.184 ± 0.012 0.194 ± 0.013 Dangur 211 211 0 2 14 0.213 ± 0.013 0.225 ± 0.014 Benishangul Gumuz-Metekel Zone Guba 219 219 0 6 19 0.219 ± 0.013 0.231 ± 0.013 Pawe 219 219 1 10 21 0.208 ± 0.013 0.219 ± 0.013 Kemash 210 210 0 2 10 0.213 ± 0.013 0.224 ± 0.014 Benishangul Gumuz-Kemash Zone Yasso 212 212 0 3 11 0.193 ± 0.013 0.204 ± 0.013 Benishangul Gumuz-Assosa Zone Assosa 205 205 0 2 13 0.204 ± 0.013 0.215 ± 0.014 Bambasi 210 210 0 4 17 0.205 ± 0.013 0.216 ± 0.013 Kurmuk 200 200 0 2 10 0.196 ± 0.013 0.207 ± 0.013 Oromia-West Wellega Zone Gimbi 210 210 0 2 11 0.203 ± 0.013 0.214 ± 0.014 Oromia-Buno Bedele Zone Dabu Hena 214 214 0 5 16 0.218 ± 0.013 0.229 ± 0.014 Note: NDB = No. of different bands, NDBF ≥5% = No. of different bands with a frequency ≥5%, NPB = No. of bands unique to a single population, NLCB (≤25%) = No. of locally common bands (Freq. ≥5%) found in 25% or fewer populations, NLCB(≤ 50%) = No. of locally common bands (Freq. ≥ 5%) found in 50% or fewer populations, He = Expected heterozygosity = 2 * p * q, uHe = Unbiased expected heterozygosity = (2N/(2N-1)) * He Where for Diploid Binary data and assuming Hardy-Weinberg Equilibrium, q = (1 - Band Freq.)^0.5 and p = 1 - q. Band patterns across populations

250 0.250 200 0.200 150 0.150 NDB 100 0.100 NDB ≥ 5% Number 50 0.050 0 0.000 NPB Heterozygosity

BGM-… NLCB (≤ 25%) SNNPs-…

BGK-Yasso NLCB (≤ 50%) BGM-Guba BGM-Pawe ORBB-Dabu… BGA-Assosa GGAM-Abol BGK-Kemash BGA-Kurmuk BGM-Dangur BGA-Bambasi ORWW-Gimbi Populations Mean He

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6.2.3. Genetic Polymorphism and Shanon’s Information Index

Among the thirteen populations, Guba population has the highest percent polymorphism

(47.13%) followed by Dabu Hena or Didhesa valley (45.40%) and Bambasi (44.83%).

While populations from Mandura (40.52%), Gambella and Yasso (41.09%) were observed

to have the least percent polymorphism (Table 6-5).

The nineteen different ISSR markers were analyzed for a total of 130 individuals

representing 13 different populations of O. abyssinica and generating a high level of genetic polymorphism. High genetic variation at species level was observed in the present investigation with the recording of the percentage of the polymorphic loci (PPL) at 84.48%.

The values for Nei`s genetic diversity (H), Shannon diversity index (I), observed number of alleles (Na) and effective number of alleles (Ne) along with standard deviation (SD) at species level were also recorded at 0.2702 ± 0.1945, 0.4061 ± 0.2595, 1.8448 ± 0.3626, and 1.4744 ± 0.3960, respectively, showing a relatively high level of genetic diversity

(Table 6-5). However, the genetic differentiation at the population level was relatively low as compared to genetic variation evidenced at the species level. This was proved by

relatively moderate PPL recorded in the range of 40.52% to 47.13% averaging at 43.41%.

The H values showed the highest for Guba (0.2193 ± 0.2383) followed by Dabu Hena or

Didhesa valley population (0.2165 ± 0.2407). Mandura, Abol and Yasso populations were

observed to be the least diverse with gene diversity value of 0.1842 ± 0.2285, 0.1978 ±

0.2390 and 0.1922 ± 0.2342 respectively. The same diversity patterns were also observed

for I, Na and Ne, whereby Guba, Dabu Hena and Bambasi populations showed the highest

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and Mandura, Yasso and Abol populations showed the least. In general, Metekel Zone of

BGR with mean value shows the highest NPL, PPL, H, I, Na and Ne eventhough Buno

Bedelle Zone of Oromia Region has greatest value by single population.

Polymorphism within the population was under 50% for all populations. Additionally, for

the present study of Ethiopian lowland bamboo ( O. abyssinica ) using nineteen ISSR primers, the total genetic diversity (Ht) was 0.2708 ± 0.0379, the genetic diversity within populations (Hs) was 0.2047 ± 0.0327, the coefficient of gene differentiation (Gst) was =

0.2442 and estimate of gene flow among populations (Nm) was = 1.5474) (Table 6-5).

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Table 6-5: Genetic diversity within populations and genetic differentiation parameters of thirteen populations of O. abyssinica.

Region-Zone Code-Population NPL PPL (%) (H ± SD) (I ± SD) Na Ne Gambella-Gambella GGAM -Abol 143 41.09 0.1978 ± 0.2390 0.2767 ± 0.3336 1.4109 ± 0.4927 1.3857 ± 0.4686 SNNPs-Konta Special Wereda SNNPs -Koyshe 153 43.97 0.2102 ± 0.2408 0.2942 ± 0.3359 1.4397 ± 0.4971 1.4097 ± 0.4730 B-Gumuz-Metekel Zone BGM -Mandura 141 40.52 0.1842 ± 0.2285 0.2611 ± 0.3214 1.4052 ± 0.4916 1.3484 ± 0.4408 BGM -Dangur 155 44.54 0.2112 ± 0.2400 0.2962 ± 0.3349 1.4454 ± 0.4977 1.4102 ± 0.3349 BGM -Guba 164 47.13 0.2193 ± 0.2383 0.3088 ± 0.3330 1.4713 ± 0.4999 1.4 224 ± 0.4661 BGM -Pawe 155 44.54 0.2078 ± 0.2366 0.2927 ± 0.3310 1.4454 ± 0.4977 1.3996 ± 0.4622 Zone Mean 153.75 44.1825 0.2056 ± 0.2358 0.2897 ± 0.3301 1.4418 ± 0.4967 1.3952 ± 0.4260 B-Gumuz-Kemash Zone BGK -Kemash 155 44.54 0.2129 ± 0.2411 0.2981 ± 0.3363 1.4454 ± 0.4977 1.4150 ± 0.4735 BGK -Yasso 143 41.09 0.1922 ± 0.2342 0.2705 ± 0.3281 1.4109 ± 0.4927 1.3690 ± 0.4543 Zone Mean 149 42.815 0.2025 ± 0.2376 0.2843 ± 0.3322 1.4282 ± 0.4952 1.3920 ± 0.4639 B-Gumuz-Assosa Zone BGA -Assosa 147 42.24 0.2040 ± 0.2407 0.2851 ± 0.3356 1.4224 ± 0.4947 1.3987 ± 0.4730 BGA -Bambasi 156 44.83 0.2056 ± 0.2353 0.2902 ± 0.3292 1.4483 ± 0.4980 1.3937 ± 0.4583 BGA -Kurmuk 146 41.95 0.1962 ± 0.2353 0.2761 ± 0.3293 1.4195 ± 0.4942 1.3773 ± 0.4571 Zone Mean 149.67 43.01 0.2019 ± 0.2371 0.2838 ± 0.3314 1.4301 ± 0.4956 1.3899 ± 0.4628 Oromia-West Wellega ORWW -Gimbi 148 42.53 0.2023 ± 0.2399 0.2842 ± 0.3344 1.4253 ± 0.4951 1.3961 ± 0.4717 Oromia-Buno-Bedelle ORBB -Dabu Hena 158 45.40 0.2165 ± 0.2407 0.3035 ± 0.3360 1.4540 ± 0.4986 1.4207 ± 0.4721 Mean of Populations 151.077 43.4131 0.2046 ± 0.2377 0.2875 ± 0.3322 1.4341 ± 0.4960 1.3959 ± 0.4543 Overall for species 294 84.48 0.2702 ± 0.1945 0.4061 ± 0.2595 1.8448 ± 0.3626 1.4744 ± 0.3960 Summary of Genic Ht 0.2708 ± 0.0379 Variation Statistics for Hs 0.2047 ± 0.0327 All Loci Total and Gst 0.2442 (Mean ± SD) Nm 1.5474 NPL - Number of polymorphic loci, PPL - percentage of polymorphic loci, H - Nei’s gene diversity, I - Shannon’s information index, na - observed number of alleles, ne - effective number of alleles, t - total genetic diversity, s - genetic diversity within populations, Gst - the coefficient of gene differentiation and Nm- estimateof gene flow among populations.

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6.2.4. Analysis of Molecular Variance

Analysis of molecular variance (AMOVA) was carried out in two phases; one was done

for the entire populations (i.e., using the thirteen populations as it is without grouping)

overall loci by considering them as one geographic region and the other one was done using

the populations grouped in to seven based on administrative Zones. The analysis was

carried out by computation of the distance between ‘haplotypes’, each individual’s data pattern as one ‘haplotype’ and computing variance components for each level (Exocoffer

et al., 1992).

Partitioning of genetic diversity by AMOVA (Table 6-4) using grouped populations

revealed that out of the total genetic diversity, most of the ISSR diversity was distributed

within the populations (61.05%), with the remaining diversity being distributed among

groups (31.80%) and among populations within groups (7.15%) with F ST = 0.38949, F SC =

0.10486 and F CT = 0.31797. Similarly, partitioning of genetic diversity by analysis of molecular variance without grouping populations revealed that out of the total genetic diversity, most of the ISSR diversity is due to differences between individual plants within the populations (63.65%), while the remaining is due to differences among populations

(36.35%) with F ST value of 0.36354. In both cases, the results of an analysis of molecular

variance revealed the same patterns of genetic diversity and support the larger genetic

diversity found within the populations rather than among the populations and are similar

to Shannon’s diversity index.

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Table 6-6: Analysis of molecular variance (AMOVA) for thirteen populations of O. abyssinica with seven administrative Zonal groups and without grouping. Source of Sum of Variance Percentage d.f. variation squares components of variation Among 6 2124.524 16.38900 Va 31.80 Groups With Among Populations seven 6 409.983 3.68630 Vb 7.15 within Groups Zonal Within grouping 117 3681.700 31.46752 Vc 61.05 Populations Total 129 6216.208 51.54282 Fixation Indices: FSC = 0.10486 FST = 0.38949 FCT = 0.31797 Among 12 2534.508 17.97415 Va 36.35 Populations Without Within grouping 117 3681.700 31.46752 Vb 63.65 Populations Total 129 6216.208 49.44167 Fixation Index FST = 0.36354

6.2.5. Cluster Analysis

Intra geographical cluster analysis of UPGMA and NJ were computed for all individuals

and populations of O. abyssinica . The UPGMA dendrogram resulting from a SAHN

clustering analysis and NJ analysis on the basis of Jaccard’s coefficients of similarity was

constructed. The Jaccard’s coefficient of similarity was obtained after pair-wise

comparisons performed using binary character matrices (of the presence and absence) that

were produced from amplified fragments. Even though both UPGMA and NJ clustering of

the overall analysis, all the individuals clustered according to their respective origin of the

populations in the Region and Zones, NJ showed much better than UPGMA (Figure 6-4).

Most primer combinations in terms of nucleotide repeats and anchorage property showed

almost similar clusters like the overall assessment exception of tri and penta-nuvleotide

repeats. Tri-nucleotide repeat ISSR primer mixes Kurumk samples of BGR with Oromia 104

Region of which they are distant to each other. Unanchored primers make Assosa samples

diverged from Bambasi and Kurmuk populations while all the rest combinations except penta-nucleotide primers showed Assosa and Kurmuk samples have diverged from

Bambasi populations. 5’ anchored primers, on the other hand, mixed Kemash Zones of

BGR samples with Oromia Region sample in addition to the drawbacks like unanchored primers. The poorest tree topology was observed by penta-nucleotide primers that mixed

Assosa, Pawe and Yasso populations in the same cluster while they were geographically

very distant and even in three separate administrative zones of BGR (Figure 6-4A - G).

Generally, di-nucleotide with 3’ anchored primers and anchored primers showed better

clustering results (Figure 6-3A). Moreover, the UPGMA and NJ clustering methods of

hundred and thirty individuals of lowland bamboo ( O. abyssinica ) for the overall nineteen

ISSR primers, (ten di-nucleotide also they are 3’anchored, two tri-nucleotide, two tetra- nucleotide, three penta-nucleotide, and two 5` anchored primers) produces exactly the same tree topology according to their geographic distance and location.

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GGAM-Abol SNNPs-Konta BGM-Mandura BGM-Pawe BGM-Dangur BGM-Guba

BGK-Kemash BGK-Yasso ORWW-Gimbi ORBB-Dabu-Hena BGA-Assosa BGA-Bambasi BGA-Kurmuk 0.36 0.45 0.55 0.65 0.74 Coefficient Figure 6-2: UPGMA based dendrogram for thirteen O. abyssinica populations based on Jaccard’s similarity coefficient using ninteen ISSR primers.

Figure 6-3: NJ analysis of 130 individuals based on Jaccard’s similarity coefficient.

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GGAM-Abol GGAM-Abol SNNPs-Konta SNNPs-Konta BGK-Kemash BGM-Mandura ORWW-Gimbi BGM-Dangur ORBB-Dabu-Hena BGM-Guba BGK-Yasso BGM-Pawe BGM-Mandura BGK-Kemash BGM-Dangur BGK-Yasso BGM-Guba BGA-Assosa BGM-Pawe BGA-Bambasi BGA-Assosa BGA-Kurmuk A BGA-Kurmuk B ORWW-Gimbi BGA-Bambasi ORBB-Dabu 0.22 0.32 0.42 0.51 0.61 0.41 0.49 0.58 0.66 0.75 Coefficient Coefficient GGAM-Abol GGAM-Abol SNNPs-Konta SNNPs-Konta BGM-Dangur BGM-Mandura BGM-Guba BGM-Pawe BGM-Mandura BGK-Yasso BGM-Pawe BGA-Assosa BGK-Kemash BGK-Kemash BGK-Yasso BGM-Dangur ORBB-Dabu-Hena ORWW-Gimbi ORWW-Gimbi ORBB-Dabu-Hena BGA-Assosa BGA-Bambasi C BGA-Kurmuk D BGA-Kurmuk BGA-Bambasi BGM-Guba 0.40 0.51 0.61 0.72 0.82 0.30 0.42 0.54 0.66 0.78 Coefficient Coefficient GGAM-Abol GGAM-Abol SNNPs-Konta SNNPs-Konta BGM-Dangur BGK-Kemash BGA-Assosa ORWW-Gimbi BGA-Bambasi ORBB-Dabu-Hena BGM-Pawe BGK-Yasso BGA-Kurmuk BGM-Mandura BGM-Guba BGM-Dangur BGM-Mandura BGM-Guba BGK-Kemash BGM-Pawe ORWW-Gimbi BGA-Assosa E BGK-Yasso F BGA-Kurmuk ORBB-Dabu-Hena BGA-Bambasi 0.61 0.67 0.73 0.79 0.85 0.29 0.38 0.47 0.56 0.65 Coefficient Coefficient GGAM-Abol SNNPs-Konta BGM-Mandura BGM-Pawe BGM-Dangur BGM-Guba BGK-Kemash BGK-Yasso ORWW-Gimbi ORBB-Dabu-Hena BGA-Assosa G BGA-Bambasi BGA-Kurmuk 0.36 0.45 0.55 0.65 0.74 Coefficient Figure 6-4: UPGMA dendrogram depicting clustering patterns for thirteen populations of O. abyssinica based on Jaccard’s similarity coefficient. A. Di-nucleotide also 3’ anchored, B. Tri-nucleotide, C. Tetra- nucleotide, D. Penta-nucleotide, E.5’ anchored, F. 3’ and 5’ anchored and G. Unanchored ISSR primers.

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6.2.6. Principal Coordinate (PCoA) Analysis

The data obtained from nineteen ISSR primers were used in PCoA analysis using Jaccard’s coefficients of similarity for grouping of individuals and clustering of O. abyssinica using three coordinates (Figure 6-5A-B). The analysis was carried out using STATISTICA version 12.0 and XLSTAT 2014.5.03 softwares. The first three coordinates of the PCO having Eigen values of 11.79, 6.89 and 6.12 with the variance of 27.68%, 16.19% and

14.33% were used to construct the three-dimensional (3D) graphs. All the 13 populations were observed to form separate clusters (Figure 6-5A). However, XLSTAT categorized into four groups (Figure 6-6B). Group I and group II both in the same sign (+/+ and -/-) were among the samples clustered together and opposite signs (either +/- or -/+) were the samples most diverse and distant.

Group 5

BGM-Mandura-10BGM-Mandura-9BGM-Mandura-6BGM-Pawe-1 BGM-Mandura-3BGM-Mandura-4BGM-Mandura-1BGM-Mandura-5BGM-Mandura-8BGM-Pawe-5BGM-Pawe-3BGM-Pawe-4BGM-Pawe-2BGM-Pawe-9BGM-Pawe-8 BGM-Mandura-2BGM-Mandura-7BGM-Pawe-6BGM-Pawe-7BGM-Pawe-10BGM-Guba-5BGM-Guba-8 BGM-Guba-10BGM-Guba-6BGM-Guba-9BGM-Guba-7 Group 1 BGM-Guba-2BGM-Guba-1BGM-Guba-4BGM-Guba-3 GGAM-Abol-10GGAM-Abol-6GGAM-Abol-7GGAM-Abol-8GGAM-Abol-9 BGM-Dangur-8BGM-Dangur-5BGM-Dangur-6 GGAM-Abol-5GGAM-Abol-4GGAM-Abol-2GGAM-Abol-1GGAM-Abol-3 BGM-Dangur-10BGM-Dangur-9BGM-Dangur-2BGM-Dangur-4BGM-Dangur-3BGM-Dangur-1BGM-Dangur-7 SNNPs-Koyshe-3SNNPs-Koyshe-1SNNPs-Koyshe-4SNNPs-Koyshe-10SNNPs-Koyshe-5SNNPs-Koyshe-2 SNNPs-Koyshe-8SNNPs-Koyshe-9SNNPs-Koyshe-6SNNPs-Koyshe-7 Group 2 Group 4 BGA-Assosa-6BGA-Assosa-4 BGA-Kurmuk-10BGA-Bambasi-2BGA-Bambasi-10BGA-Bambasi-6BGA-Bambasi-1BGA-Bambasi-7BGA-Kurmuk-9BGA-Bambasi-5BGA-Kurmuk-8BGA-Assosa-1BGA-Assosa-7BGA-Bambasi-4BGA-Bambasi-8BGA-Assosa-5BGA-Assosa-10BGA-Assosa-2BGA-Bambasi-9BGA-Assosa-8BGA-Assosa-3BGA-Assosa-9 BGA-Kurmuk-1BGA-Kurmuk-2BGA-Kurmuk-4BGA-Kurmuk-3BGA-Kurmuk-5BGA-Kurmuk-7BGA-Kurmuk-6BGA-Bambasi-3

ORWW-Gimbi-5ORWW-Gimbi-8ORWW-Gimbi-7ORWW-Gimbi-6BGK-Kemash-1BGK-Kemash-7BGK-Kemash-6 ORWW-Gimbi-10ORWW-Gimbi-9 BGK-Kemash-3BGK-Kemash-4BGK-Kemash-8BGK-Kemash-5BGK-Kemash-10BGK-Kemash-2BGK-Yasso-8BGK-Yasso-7 ORBB-Dabu-Hena-1ORWW-Gimbi-3ORWW-Gimbi-4ORWW-Gimbi-2BGK-Kemash-9BGK-Yasso-10BGK-Yasso-1BGK-Yasso-4BGK-Yasso-6BGK-Yasso-9BGK-Yasso-3BGK-Yasso-5BGK-Yasso-2 ORBB-Dabu-Hena-8ORBB-Dabu-Hena-10ORBB-Dabu-Hena-7ORBB-Dabu-Hena-9ORBB-Dabu-Hena-6ORBB-Dabu-Hena-3ORBB-Dabu-Hena-5ORBB-Dabu-Hena-4ORBB-Dabu-Hena-2ORWW-Gimbi-1 Group 3

A

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Biplot (axes F1 and F3: 66.67 %)

2 ORBB-Dabu-Hena- ORBB-Dabu-Hena-ORBB-Dabu-Hena-ORBB-Dabu-Hena-ORBB-Dabu-Hena-ORBB-Dabu-Hena-ORBB-Dabu-Hena-ORBB-Dabu-Hena- ORBB-Dabu-Hena-ORBB-Dabu-Hena-9 3452106781 1.5 ORWW-Gimbi-1ORWW-Gimbi-4ORWW-Gimbi-3 ORWW-Gimbi-2ORWW-Gimbi-9ORWW-Gimbi-10 Y I BGK-Yasso-2BGK-Yasso-5BGK-Yasso-3BGK-Yasso-10BGK-Yasso-6BGK-Yasso-4BGK-Yasso-1BGK-Kemash-8BGK-Yasso-9BGK-Kemash-9BGK-Kemash-4ORWW-Gimbi-6BGK-Kemash-3ORWW-Gimbi-7ORWW-Gimbi-8ORWW-Gimbi-5 IV BGK-Kemash-10BGK-Yasso-7BGK-Yasso-8BGK-Kemash-5BGK-Kemash-2BGK-Kemash-7BGK-Kemash-1 I. ORDH-Buno I. GGAM -Abol BGK-Kemash-6 Bedele 1 II. ORWW-Gimbi III. BGK -Kemash GGAM-Abol-1GGAM-Abol-10 0.5 GGAM-Abol-2GGAM-Abol-3GGAM-Abol-8GGAM-Abol-4GGAM-Abol-5GGAM-Abol-6GGAM-Abol-7GGAM-Abol-9

BGA-Kurmuk-9BGA-Kurmuk-1 BGA-Kurmuk-3BGA-Kurmuk-5BGA-Kurmuk-2BGA-Kurmuk-4BGA-Kurmuk-7BGA-Kurmuk-6 X SNNPs-Koyshe-8SNNPs-Koyshe-9 0 BGA-Bambasi-3BGA-Bambasi-4BGA-Bambasi-7BGA-Bambasi-5BGA-Bambasi-6BGA-Assosa-10BGA-Bambasi-1BGA-Kurmuk-8BGA-Assosa-5BGA-Assosa-2BGA-Kurmuk-10BGA-Assosa-1BGA-Assosa-7 SNNPs-Koyshe-7 BGA-Assosa-9BGA-Bambasi-8BGA-Bambasi-9BGA-Bambasi-2BGA-Assosa-8BGA-Assosa-4BGA-Assosa-3BGA-Assosa-6 SNNPs-Koyshe-10SNNPs-Koyshe-6SNNPs-Koyshe-5SNNPs-Koyshe-2SNNPs-Koyshe-4SNNPs-Koyshe-3SNNPs-Koyshe-1 BGA-Bambasi-10 BGM-Dangur-9 F3(33.33 %) BGM-Dangur-1BGM-Dangur-3BGM-Dangur-4BGM-Dangur-2BGM-Dangur-10 III II BGM-Dangur-7BGM-Dangur-6BGM-Dangur-5BGM-Dangur-8 -0.5 I. BGA-Assosa I. SNNPs-Koyshe II. VGA-Bambasi II. BGM-Dangur III. BGA- BGM-Guba-1BGM-Guba-2 III. BGM-Guba -1 BGM-Guba-3BGM-Guba-4 BGM-Mandura-7IV. BGM- Kurmuk BGM-Mandura-5BGM-Mandura-4BGM-Mandura-1BGM-Mandura-2BGM-Mandura-3 BGM-Guba-10BGM-Pawe-6BGM-Mandura-9BGM-Mandura-10BGM-Mandura-8Mandura BGM-Guba-7BGM-Guba-9BGM-Guba-6BGM-Pawe-10BGM-Pawe-7BGM-Pawe-5BGM-Mandura-6 B BGM-Guba-8BGM-Guba-5BGM-Pawe-8BGM-Pawe-3BGM-Pawe-9BGM-Pawe-2BGM-Pawe-4 -1.5 BGM-Pawe-1 Z

-2 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 F1 (33.33 %)

Figure 6-5: Three-dimensional representation of principal coordinate analysis of genetic relationships among 130 individuals of 13 populations of Ethiopian lowland bamboo ( O. abyssinica ) inferred from similarity matrix using (A) the Jaccard’s index at STATISTICA and (B) Pearson PCA method using XLSTAT.

6.2.7. Admixture Analysis

The Bayesian approach-based assignment of the 130 individual plants to different populations and determination of their population structure using STRUCTURE outputs

Evanno et al. (2005), predicted K = 2 for 13 populations for whole samples to be the most likely number of clusters (Figure 6-6).

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K = 1 A B K = 2

K = 3

K = 4

K = 5

K = 6

K = 7

K = 8 C D

K = 9

K = 10

K = 11

K = 12

K = 13

GGAM-Abol SNNPs-Koys BGM-Mand BGM-Dang BGM-Guba BGM-Pawe BGK-Kema BGK-Yass BGA-Asso BGA-Bamb BGA-Kurm ORWW-Gimb ORBB-DabuH Figure 6-6: STRUCTURE harvester and CLUMPAK Delta K value estimated using Evano et al. (2005) method and Bayesian model-based estimation of population structure for 130 Ethiopian lowland bamboos ( O. abyssinica ) based on ISSR markers in thirteen pre-determined populations. (A), ΔK = mean(|L”(K)|)/sd(L(K)). ΔK = 11 indicates the maximum K value; (B), rate of change of the likelihood distribution (mean); (C), mean of estimated Ln probability; (D), absolute value of the 2 nd order rate of change of the likelihood distribution (mean). 110

6.3. Discussion

6.3.1. ISSR Markers for the Genetic Polymorphism in Ethiopian Lowland Bamboo

(O. abyssinica ) Populations

Assessment of genetic diversity is crucial for any improvement program of plants and for the conservation of genetic resources in the organism’s natural habitats (Choudhary et al.,

2013). A number of molecular markers have been widely used to study diversity in many plants (Karp et al., 1996). Given the proliferation of molecular markers, a comparison between the markers seems highly inevitable on the basis of study objectives and the nature of the markers. Of many desired qualities of molecular markers, automation (PCR-based), polymorphisms and reproducibility are the highly demanded features of the molecular techniques to be used in inter and intraregional diversity analysis. ISSR markers are thus one of the molecular markers that have these characteristics (Zietkiewicz et al., 1994; Wolf and Liston, 1998).

Molecular marker techniques such as RAPD, RFLP, ISSR, AFLP, SSR, EST-SSR, and

SRAP have been routinely used for characterization of bamboo germplasm (Tian et al.,

2012; Yang et al., 2012; Ma et al., 2013; Nag et al., 2013; Nilkanta et al., 2017). ISSR

markers are widely used for population genetic analysis of different plants generating more reliable and reproducible bands than RAPD ( Nagaoka and Ogihara, 1997; Zhang and Dai,

2010) . They are technically simpler, quick and cost effective ( Tesfaye et al., 2014) as compared to RFLP, SSR, and AFLP markers as no previous sequence information is required for generating DNA amplification products ( Mukherjee et al., 2010; Tian et al.

2012 ). ISSR markers are observed to be highly variable within the species and reveal many

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more polymorphisms since they use longer primers that allow more stringent annealing

temperatures (Hillis et al., 1996). In this study, also the ISSR markers observed to be an

appropriate molecular marker for generating the detailed intraspecific genetic diversity

data to evaluate the extent and distribution of genetic diversity within and among O.

abyssinica .

So far, there is no report on the extents of molecular diversity in general and ISSR based

marker system in particular for Ethiopian lowland bamboo. Hence, as the first step in the

development of genomic tools and resources that could contribute to the development of

strategies for effective conservation and sustainable utilization of this bamboo for

ecological and economic gains by better understanding the genetic diversity profile at the

species and population level, we examined and assessed thirteen O. abyssinica populations by nineteen ISSR markers. These molecular markers have been successfully utilized for assessing the genetic diversity and revealed a remarkable molecular discrimination among the thirteen Ethiopian lowland bamboo populations.

Out of the total 348 scorable bands produced with a total of nineteen primers; ten di- nucleotide, two tri-nucleotide, two tetra-nucleotide, three penta-nucleotide, and two 5` anchored primers,294 bands were polymorphic. In terms of number of polymorphic fragments detected and percentage of polymorphic loci per class of primer, di-nucleotides with 3’ anchored were found to be superior. While the tri-nucleotide primers generated 32 bands, tetra-nucleotide generated 39 bands and the penta-nucleotide primers generated 56 bands, of which 25, 29 and 45 were polymorphic loci respectively. Based on the anchorage

112 property of the primers, 5’ anchored primers showed the least polymorphism with 36, 21

and 58.33value of NSB, NPL and PPL respectively. Generally, anchored primers with NSB

(221), NPL (195) and PPL (88.24) showed better NSB, NPL and PPL than unanchored primers (127, 99 and 77.95) respectively. This work like the works of Ng & Tan (2015) and Tarinejad et al. (2015) confirms that anchored primers in general and 3` anchored and

di-nucleotides ISSR primers in specifically shows better polymorphism than unanchored

and other repeats motifs of ISSR markers for the study of O. abyssinica populations

collected throughout Ethiopia. In terms of bands specificity, the highest in Gambella and

moderate numbers of private bands observed in Koyshe populations makes this population

isolated and different from other O. abyssinica populations collected in Ethiopia.

The choice of molecular markers largely depends on the level of polymorphism to be detected and their genomic coverage, rather than on the technology used to generate the markers. Estimates of marker based selection depend on the linkage of the genomic region and the marker itself. Because highly informative markers can reduce the amount of genotyping required for inference of ancestry, it is desirable to measure the extent to which specific markers contribute to this inference (Rosenberg et al., 2003). Several approaches

have been previously developed for measuring polymorphism information, but a user

friendly platform to calculate this information is missing or otherwise inaccessible (Nagy

et al., 2012). The iMEC (marker efficiency calculator) created by a group of researchers

(Amiryousefi et al., 2018) is coded in R and is available as a web application at https://irscope.shinyapps.io/iMEC/ that helps to detect markers for lots of genetics researches. For the present study, the highest PIC, MI, H and D were observed by anchored

113 primers in general and 3’ anchored and di-nucleotide repeats (UBC-812, UBC-815, UBC-

834 and UBC-835) in specific. The least H, PIC and D were observed by penta-nucleotides

and tri-nucleotides as well as 5’ anchored primers (table 6-4).

Again, anchored and di-nucleotide repeat primers showed more polymorphism and discriminating power than unanchored primers like the studies by Tarinejad et al. (2015) and Ng & Tan (2015). It is noteworthy that di-nucleotide repeats, anchored either at 3’ or

5’ end, usually reveal high polymorphism and the primers anchored at 3’ end give clearer banding pattern compared to those anchored at 5’ end (Joshi et al., 2000; Pradeep Reddy

et al., 2002; Tarinejad et al., 2015).

6.3.2. Genetic Differentiation and Population Structure

The high number of alleles and high polymorphism are very important for the correct

estimation of the genetic diversity of germplasm. The degree of polymorphism showed the

extent of diversity and effectiveness of the markers (Pfeifer et al., 2011) and consequently, polymorphic information is related to expected heterozygosity and is usually determined from allele frequency. In the present study, the largest NPL (164 and 158), highest PPL

(47.13% and 45.40), the highest H (0.2193 ± 0.2383 and 0.2165 ± 0.2407) and I (0.3088 ±

0.3330 and 0.3035 ± 0.3360) were found in populations of Guba and Dabu Hena

Populations. The least values of NPL, PPL, H and I were showed by populations of Yasso,

Abol and Kurmuk. This might be due to clonal propagation of the plant in those areas.

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The overall NPL (294), PPL (84.48%), H ± SD (0.2702 ± 0.1945), I ± SD (0.4061 ±

0.2595), na (1.8448 ± 0.3626) and Ne (1.4744 ± 0.3960) were recorded in the current study

of O. abyssinica populations based on nineteen ISSR markers. Compared to other bamboo species, the Ethiopian lowland bamboo ( O. abyssinica ) populations showed higher genetic diversity with H = 0.2702 ± 0.1945 and I = 0.4061 ± 0.2595. The H = 0.0418 ± 0.0456 and

I = 0.0624 ± 0.0651 were recorded in giant bamboo (Dendrocalamus giganteus ) China population with low genetic diversity and high genetic differentiation (Tian et al., 2012).

The H (0.175 ± 0.152) and I (0.291 ± 0.209) were observed in Dendrocalamus hamiltonii northeast Himalayas with low genetic diversity and a moderate level of genetic differentiation (Meena et al., 2019). High genetic variation at the species level with H =

0.1939 and I = 0.3218 values were recorded in Melocanna baccifera (Roxb.) Kurz: bamboo

of Manipur, North-East India (Nilkanta et al., 2017). High level of genetic diversity with

H = 0.219 and I = 0.349 was also found for Dendrocalamus membranaceus a declining bamboo species in Yunnan, China, as based on ISSR analysis (Yang et al., 2012).

Therefore, this tells us there is high genetic diversity and differentiation in O. abyssinica populations collected throughout Ethiopia. Metekel Zone of BGR samples could be considered to possess the highest genetic variation and Gambella and SNNPs populations possess lower genetic variation as compared to other populations indicating that the populations were subjected to genetic isolation.

Additionally, for the present study on O. abyssinica the total genetic diversity (t = 0.2708

± 0.0379), genetic diversity within populations (s = 0.2047 ± 0.0327), the relative magnitude of genetic differentiation among populations (st = 0.2442) and estimate of

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gene flow among populations (m = 1.5474) was recorded. The Ht = 0.1961, Hs = 0.1639,

Gst = 0.1942 and Nm = 2.5455 with high genetic diversity was also recorded in Melocanna baccifera (Roxb.) Kurz: a commercially important bamboo of Manipur, North-East India using seven ISSR markers (Nilkanta et al., 2017). The Ht = 0.167, Hs = 0.138, Gst = 0.247 and Nm = 1.52 with a low level of genetic diversity were also recorded in D. hamiltonii using seventeen SSR markers in the northeastern region of India ( Meena et al., 2019).

6.3.3. Levels of Genetic Diversity among and Within Populations

Most bamboo populations are established through vegetative propagations. Sometimes a population might be of a single rhizome clonally extended to a vast area. Hence, all individuals of a population might have similar or nearly similar genetic makeup (Stern,

2004). The genetic similarity might result in total loss of the population if a certain disease or pest arises. Flowering creates the opportunity of gene mix up in the next generation since seeds can have more genetic variability. Bamboo is an out-crossing wind-pollinated plant where there is high gene random mix up although flowering is an extremely rare event or one in life. As bamboos are mostly multiplied clonally, a single plant can form huge populations over time (Miyazaki et al , 2009). This may follow a deficit of genetic variation within a population (Wong, 2004).

Partitioning of genetic diversity by analysis of molecular variance (AMOVA) using grouped populations revealed that out of the total genetic diversity, most of the ISSR diversity was distributed within populations (61.05%), the remaining diversity being distributed among groups (31.80%) and among populations within groups (7.15%).

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Similarly partitioning of genetic diversity by AMOVA without grouping populations

revealed that out of the total genetic diversity, most of the ISSR diversity is due to

differences between individual plants within the populations (63.65%), while the

remaining is due to differences among populations (36.35 %).

Our results are in agreement with several works on bamboo including, the findings of

Meena et al. (2019) on 19 populations of D. hamiltonii using seventeen SSR markers with

an AMOVA result of 16.53 % among populations and 83.47 % within populations

assuming no hierarchical grouping and 6.28% among groups, 12.45% among populations

within the group and 81.26% within populations in four hierarchical groups. Similarly,

Nilkanta et al. (2017) using five ISSR markers on M. baccifera (Roxb.) Kurz: bamboo of

Manipur, North-East India has found an AMOVA of 22% among populations and 78% within populations. Yang et al. (2012) on D. membranaceus using ten ISSR markers have also found the AMOVA result of 78.95% within the population and 21.05% among populations. Again Attigala et al., (2017) on the study of g enetic diversity and population structure of the threatened temperate woody bamboo Kuruna debilis (Poaceae:

Bambusoideae: Arundinarieae) from Sri Lanka based on microsatellite analysis has found an AMOVA result of 8.35% among groups, 7.52% among populations within groups and

84.13% within populations using twelve microsatellite loci. But compared to the above work on different bamboo species, the within population percentage with 61.05% for O.

abyssinica was found to be low. Similarly, recent study on genetic diversity analysis of

Ethiopian highland bamboo ( A. alpina ) based on 16 SSR primers by Muhamed et al.,

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(2019) also showed that AMOVA result within individuals (53 %) was higher than among

individuals (45%) and among populations (2%).

On the other hand, FSC = 0.10486, F ST = 0.38949 and F CT = 0.31797 with seven groups and

FST = 0.36354 without grouping was recorded from O. abyssinica . FSC = 0.132, F ST = 0.187

and F CT = 0.062 with four groups and F ST = 0.165 without grouping was recorded in D. hamiltonii (Meena et al., 2019). Higher population divergence or differentiation is observed for D. hamiltonii (FST = 0.165) and significant genetic differentiation with FST =

0.36354 was recorded in Ethiopian lowland bamboo ( O. abyssinica) populations.

For the interpretation of FST , it has been suggested that a value lying below 0.05 indicates

little genetic differentiation; a value between 0.05 and 0.15, moderate differentiation; a

value between 0.15 and 0.25, great differentiation and values above 0.25, very great or

significant genetic differentiation (Wright, 1984; De Vicente et al., 2004). However, for

interpretation through comparisons with earlier findings, another widely used measure of

genetic differentiation such as GST was also considered along with FST . The measure of genetic differentiation (G ST = 0.2442) recorded in O. abyssinica was comparable to those of another bamboo species such as D. hamiltonii (G ST = 0.247) Meena et al., (2019), D. membranaceus (G ST = 0.252) Yang et al., (2012) and M. baccifera (G ST = 0.194) Nilkanta

et al., (2017).

Many factors can determine the genetic structure and differentiation of plant populations,

including reproductive biology, natural selection, genetic isolation or genetic drift,

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geographic distribution range and gene flow (Loveless and Hamrick, 1984; Hogbin and

Peakall, 1999; Schall et al., 1998). Many ISSR, RAPD, and sequence-tagged microsatellite sites (STMS) based genetic analyses showed that long-lived, out-crossing taxa retained most of their genetic variability within populations (Nybom, 2004; Nilkanta et al., 2017;

Meena et al., 2019). The woody bamboos have a long vegetative phase of 20 - 150 years

and are typical long-lived species of the grass family (Ma et al., 2013). As one of those

critical influences, the out-crossing of a plant species tends to explain 10 to 20% of the

genetic variation among populations, whereas the selfing of a species leads, on average, to

50% variation between populations (Miyazaki et al., 2009). Oxytenanthera abyssinica can

reproduce via seed in the wild, although this phenomenon is rare, and the rate of seed set is low (Embaye, 2000; Ensermu et al., 2000; Zhao et al., 2018). Furthermore, studies on

the floral biology have indicated that O. abyssinica is likely anemophilous and prone to be an out-crosser (Zhao et al., 2018), which also was supported by the genetic differentiation

(GST = 0.2442) that was similar to the average of out-crossing species (GST = 0.22) (Nybom,

2004).

6.3.4. Patterns of relationship and admixture analysis

Even though both UPGMA and NJ clustering of the overall analysis, all the individuals

clustered according to their respective origin of the populations in the Region and Zones,

NJ shows much better than UPGMA (Figure 6-5). This shows that the power of NJ to

construct a phylogenetic tree is superior from other tree-building methods that are currently

in use (Roy et al., 2014).

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Dendrogram cluster generated by penta-nucleotides were relatively poor and intermixed

some population. The reason that penta-nucleotides reveal the poorest information might be the availability of SSRs in small numbers as compared to other repeat motifs (Zhao et

al., 2015). Number of SSRs by the study Zhao et al., (2015) on the genus Phyllostachys was 581 for di-nucleotide, 442 for tri-nucleotides, 35 for tetra-nucleotides, 22 for penta- nucleotides and 9 for hexa-nucleotides.

Admixture results via STRUCTURE and web-based data retrieval from structure harvester and CLUMPAK with all samples showed delta K (K = 2) value. The K value 2 might tell us the Gamblella populations might in a single group and others in another group. Based on this value, Clumpak result (bar plot) showed little admixtures and hence there is geographic origin based structuring of populations (Figure 6-6). Again, this might tell us there might be additional bamboo species in the country.

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7. Conclusion and Recommendation

7.1. Conclusion

In this study, we provide the first assessment of the phylogenetic relationships of the indigenous and introduced bamboo species and the first wide assessment of genetic diversity, population structure, and gene flow analysis of O. abyssinica using cpDNA genes and ISSR primers. This is important for understanding the plant's genetic diversity and structure for its conservation and management and to study the phylogenetic relationships of indigenous and introduced bamboo species.

The result on the phylogenetic relationships of the indigenous and introduced bamboo species study using cpDNA genes showed, mostly Ethiopian lowland bamboo ( O. abyssinica ) was clustered with Bambusa whereas, highland bamboo ( A. alpine) was clustered with Phyllostachys and Pakistani woody bamboos P. nigra and B. chungii was clustered with Phyllostachys . Clustering of Ethiopian lowland bamboo ( O. abyssinica ) with Bambuseae, highland bamboo (A. alpine) with Phyllostachys and Pakistani woody bamboos P. nigra with Phyllostachys was as of expected and similar to the work of others that temperate woody bamboos clustered with temperate woody bamboos and evolved prior than tropical woody bamboos. But clustering of B. chungii which is a genus of

Bambusa (tropical woody bamboo) with Phyllostachys and Guadua (both of them are grouped under temperate woody bamboo) is uncommon and might be sampling error or selected cpDNA genes might not enough to characterize.

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The dendrogram constructed based on the data from the ISSR random primers showed, O.

abyssinica (Ethiopian lowland bamboo or type of tropical woody bamboo) clustered with

Bambusa (tropical woody bamboo) and most of the Bambusa , Dendrocalamus ,

Gigantochloa , Phyllostachys and Guadua species clustered together. But A. alpina

(Ethiopian highland bamboo or type of temperate woody bamboo) a genus of Oldeania formed a cluster with a genus Phyllostachys and Guadua species. Even though SNPs study clustered A. alpina with the genus Phyllostachys and ISSR study clustered with

Phyllostachys and Guadua , both Phyllostachys and Guadua are among temperate woody bamboos.

Genetic diversity and population structure analysis using cpDNA genes and ISSR markers in Ethiopian lowland bamboo populations revealed a strong geographic region of origin and Metekel Zone showed the most diverse while Assosa Zone is the root of O. abyssinica.

Overall, this study could offer baseline information that promotes further studies to exploit the phylogenetics of indigenous and introduced bamboo species as well as the genetic diversity of Ethiopian lowland bamboo ( O. abyssinica ) populations and to study more on

genetics and biology of Ethiopian lowland bamboo ( O. abyssinica ).

7.2. Recommendation

This study addressed the knowledge gap that existed in the phylogenetics relationships of indigenous and introduced bamboo species as well as the genetic diversity of Ethiopian lowland bamboo ( O. abyssinica ) growing in Ethiopia. Though the present investigation

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gives some information on the phylogeny of the indigenous vs introduced bamboos and

genetic diversity of Ethiopian lowland bamboo ( O. abyssinica ) based on analysis of

cpDNA genes and ISSR markers, there is a need for further critical work involving

molecular markers giving greater genome coverage to improve our understanding of phylogenetics and genetic diversity in bamboo at the country and population level.

However, the following issues are recommended and should be addressed in future

research.

1. cpDNA genes based phylogenetics study shows, mostly Ethiopian lowland bamboo

(O. abyssinica ) was clustered with Bambusa whereas, highland bamboo ( A. alpine)

was clustered with Phyllostachys . Pakistani woody bamboos P. nigra and B.

chungii was clustered with Phyllostachys . Clustering of Ethiopian lowland bamboo

(O. abyssinica ) with Bambusa , highland bamboo ( A. alpine) with Phyllostachys

and Pakistani woody bamboos P. nigra with Phyllostachys was as of expected and

similar to the work of others that temperate woody bamboos clustered with

temperate woody bamboos and evolved prior to tropical woody bamboo. But

clustering of B. chungii which is a genus of Bambusa (tropical woody bamboo)

with Phyllostachys and Guadua (both of them are grouped under temperate woody

bamboo) is uncommon and might be sampling error or selected cpDNA genes

might not enough to characterize; so, needs further detail assessment.

2. cpDNA genes based phylogenetics study shows, P. pubescens from the introduced

species and P. edulis (Chinese moso bamboo, most economical and widely used in

China) from reference sequence were clustered together with A. alpina and ISSR

markers based phylogenetics study shows, G. angustifolia and G. amplexifolia

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(both are temperate woody bamboos) were clustered together with A. alpina; so, it

is recommended to grow those species where A. alpina is planted or growing.

3. A novel result of this phylogenetics study is, from the overall cpDNA genes based

dendrogram result of 31 taxa and thirteen Ethiopian lowland bamboo populations.

Ethiopian lowland bamboo ( O. abyssinica ) collected from Gambella region

associated differently from other lowland bamboo ( O. abyssinica ) samples and

mostly it is associating with Bambusa and Gigantochloa . This implies samples

collected from Gambella region are different from other lowland bamboo

populations and might tell us there might be additional bamboo species in the

country or introduced a long time ago even though there is no evidence but needs

further detail study on the population.

4. As Metekel Zone populations have the highest genetic differentiation, more

conservation attention deserves for this population.

5. The employed three cpDNA genes and 19 ISSR markers were able to capture the

genetic variability of lowland bamboo populations and three cpDNA genes and 15

ISSR markers were able to demonstrate the phylogenetics relationships of

indigenous and introduced bamboo species. Repeating the phylogenetics and

genetic diversity research with a greater number of ISSRs, SSRs, SNPs, cpDNA

primers, genes and complete chloroplast that are capable of capturing the entire

genetic variability is very important so as to elucidate the actual phylogenetics

relationships of indigenous and introduced bamboo species as well as genetic

variability of Ethiopian lowland bamboo populations.

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6. There is a long history of species being moved around the world by humans. Over

the past three centuries, human-mediated species dissemination has increased with

increasing global traffic (Meyerson and Mooney, 2007; Richardson, 2007 ). Some

introduced species can provide substantial benefits and naturalize (consistently

reproduce) in their new ranges and some naturalized species can have undesirable

consequences or invade (spread from introduction sites) (Canavan et al., 2016).

Finding and introducing the scientifically approved invasive, economically

important and environmentally friendly bamboo species to the degraded and

deforestation lands might be necessary and good for the country but introducing the

opposite is sure to have great consequence to the country for a long term.

7. Ethiopia has only two indigenous bamboo species namely O. abyssinica and A.

alpina . These two species are restricted in limited agro ecological regions, i.e. in

lowland areas from 500-1800 m.a.s.l and in highland areas of altitude 2400-3500

m.a.s.l. Thus, those species that are not close to the Ethiopian indigenous species

doesn’t mean they will not have a potential to grow in the country rather they may

grow in mid altitudes.

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9. APPENDICES Appendix 1: SNPs based AMOVA result using GenAlex AMOVA using the average number of pairwise differences between populations (PiXY), the average number of pairwise differences within the population (PiX) and corrected average pairwise difference (PiXY-(PiX+PiY)/2) was also calculated. PiXY was higher between populations of Abol of Gambella Region and Koyshe of SNNPs Region (208.9) and between Abol and Yasso of B-Gumuz Region populations (204.6). The least PiXY was observed between populations of Assosa and Bambasi (56.29) and between Gimbi and Dabu Hena (57.28). The distance between thess sampling sites was relatively closer as compared to other sampling sites. Whereas PiX was higher in Bambasi (75.4) and Guba (70) populations and least in Koyshe (43.2) and Abol (45.089) populations. PiXY- (PiX+PiY)/2 results get almost similar values with PiXY. Generally, a population from Gambella and SNNPs Regions has high values of PiXY and PiXY-(PiX+PiY)/2.

Abol Koyshe Mandura Dangur Guba Pawe Kemash Yasso Assosa Bambasi Kurmuk Gimbi Dabu Hena

Abol 45.089 208.9 193.3 196.3 194.6 198.8 202.2 204.6 199.9 192.6 194.4 198.9 197.6 Koyshe 164.74 43.2 100.3 94.52 102.1 101.6 95.75 92.81 99.68 108.3 101.7 95.92 104.9 Mandura 138.83 46.71 63.93 82.03 88.28 79.63 95.55 94.96 94.88 99.52 94.82 95.17 98.63 Dangur 140.82 39.94 17.09 65.96 83.73 85.24 82.73 81.8 88.44 94.66 90.32 82.06 90.7 Guba 137.1 45.45 21.31 15.75 70 76.58 94.92 95.25 87.52 92.92 87.08 96.03 99.31 Pawe 144.64 48.41 16.05 20.65 9.969 63.22 92.83 92.92 88.9 97.74 89.18 97.1 101.2 Kemash 151.92 46.41 35.84 22.01 32.18 33.47 55.49 67.62 84.08 93.5 83.73 65.58 73.01 Yasso 157.99 47.14 38.93 24.76 36.18 37 .24 4.479 48.13 81.52 92.28 81.86 67.86 74.7 Assosa 148.35 49.09 33.92 26.47 23.53 28.3 27.35 28.46 57.98 56.29 60.84 90.24 94 Bambasi 132.35 49.03 29.85 23.98 20.22 28.43 28.06 30.51 0.931 75.4 67.22 96.62 100 Kurmuk 144.3 52.56 35.28 29.76 24.5 29.99 28.41 30.22 4.273 1.942 55.16 86.98 92.34 Gimbi 151.11 49.05 37.94 23.82 35.76 40.22 12.57 18.53 35.98 33.65 34.14 50.53 57.28 Dabu Hena 146.48 54.75 38.13 29.19 35.78 41.04 16.73 22.1 36.48 33.81 36.23 3.48 57.07 Above diagonal : Average number of pairwise differences between populations (PiXY) Diagonal elements : Average number of pairwise differences within population (PiX) Below diagonal : Corrected average pairwise difference (PiXY-(PiX+PiY)/2)

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Appendix 2: Some of Ethiopian lowland bamboo ( O. abyssinica ) sample collection sites.

BGR -Bambasi BGR -Assosa

BGR -Kurmuk ORM -Gimbi -Aba Sena

BGR -Gu ba GAM -Abol BGR -Mambuk

BGR -Yasso BGR -Kemash ORM -Didhesa

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Appendix 3: DNA Dragon sequence alignment and nucleotide peaks for one of cpDNA gene ndhF .

Appendix 4: MAFFT alignment.

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Appendix 5: MEGA realignment.

Appendix 6: Sequence submission to NCBI via Sequin.

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