DOCSLIB.ORG

Genetic Effects on Microsatellite Diversity in Wild Emmer Wheat (Triticum Dicoccoides) at the Yehudiyya Microsite, Israel

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Genetic Effects on Microsatellite Diversity in Wild Emmer Wheat (Triticum Dicoccoides) at the Yehudiyya Microsite, Israel Heredity (2003) 90, 150–156 & 2003 Nature Publishing Group All rights reserved 0018-067X/03 $25.00 www.nature.com/hdy Genetic effects on microsatellite diversity in wild emmer wheat (Triticum dicoccoides) at the Yehudiyya microsite, Israel Y-C Li1,3, T Fahima1,MSRo¨der2, VM Kirzhner1, A Beiles1, AB Korol1 and E Nevo1 1Institute of Evolution, University of Haifa, Mount Carmel, Haifa 31905, Israel; 2Institute for Plant Genetics and Crop Plant Research, Corrensstrasse 3, 06466 Gatersleben, Germany This study investigated allele size constraints and clustering, diversity. Genome B appeared to have a larger average and genetic effects on microsatellite (simple sequence repeat number (ARN), but lower variance in repeat number 2 repeat, SSR) diversity at 28 loci comprising seven types of (sARN), and smaller number of alleles per locus than genome tandem repeated dinucleotide motifs in a natural population A. SSRs with compound motifs showed larger ARN than of wild emmer wheat, Triticum dicoccoides, from a shade vs those with perfect motifs. The effects of replication slippage sun microsite in Yehudiyya, northeast of the Sea of Galilee, and recombinational effects (eg, unequal crossing over) on Israel. It was found that allele distribution at SSR loci is SSR diversity varied with SSR motifs. Ecological stresses clustered and constrained with lower or higher boundary. (sun vs shade) may affect mutational mechanisms, influen- This may imply that SSR have functional significance and cing the level of SSR diversity by both processes. natural constraints. Genetic factors, involving genome, Heredity (2003) 90, 150–156. doi:10.1038/sj.hdy.6800190 chromosome, motif, and locus significantly affected SSR Keywords: SSR variation; allelic cluster; genome effect; mutational mechanism; Triticum dicoccoides; wheat’s progenitor Introduction than expected by chance) in allele size distributions among various allele series of the same locus suggests Microsatellites, or simple sequence repeats (SSR), are the existence of evolutionary constraints on that locus ubiquitously interspersed in eukaryotic genomes (Tautz (Lehmann et al, 1996). Two alternative forces for such and Renz, 1984; Kashi et al, 1997; Kashi and Soller, 1999; nonrandom distribution of allele-size frequency have Li et al, 2002a). SSRs are among the fastest-evolving DNA been proposed: biased mutation and/or selection sequences with high mutation rates, 10À2–10À3 per locus acting on allele size (Garza et al, 1995; Dermitzakis et al, per gamete per generation (Weber and Wong, 1993), 1998). which leads to their high polymorphism in terms of The present study demonstrated constraints and repeat number. It has been suggested that replication clustering of allele size distribution in a natural popula- slippage, sister-chromatid exchanges, unequal crossing tion of wild emmer wheat, Triticum dicoccoides, and over, and gene conversion may cause SSR diversity correlation between SSR diversity and repeat length, (Tautz and Renz, 1984). Among these mutational locus chromosomal location, and genetic effects on mechanisms, replication slippage seems to play a major dinucleotide SSR diversity in a natural population of role in producing new alleles at SSR loci (Levinson and wild emmer wheat from two neighboring (a few meters Gutman, 1987; Wolff et al, 1991; Innan et al, 1997; Stephan apart) and contrasting microclimatic niches, sun, and and Kim, 1998). However, these suggestions need more shade. The microclimatic effect on SSR divergence and critical analysis across species and populations. diversity are described in a complementary paper (Li The distribution of allele sizes in SSR loci, seems to be et al, 2002b). nonrandom. For instance, alleles with long repeats were found to be more mutable than a bulk of the Ccon70 with short repeats (Crozier et al, 1999). Likewise, bimodal Materials and methods distribution of allele size was revealed at many SSR loci Wild emmer wheat, Triticum dicoccoides (Nevo et al, 2002) in some species including human (Rubinsztein et al, is the tetraploid and predominantly self-pollinated 1995), Mimulus guttatus (Awadalla and Ritland, 1997), progenitor of cultivated wheat (Zohary, 1970). This Arabidopsis (Innan et al, 1997), and the fish Sparus aurata tetraploid species contains two genomes and 28 chromo- (Dermitzakis et al, 1998). The excessive similarity (more somes (2n ¼ 4x ¼ 28, genome AABB). The plant materials used in this analysis are described in detail in Li et al (2002b). Correspondence: E Nevo, Institute of Evolution, University of Haifa, Mt Carmel, Haifa 31905, Israel. E-mail: [email protected] A total of 28 dinucleotide SSR DNA markers (one for 3Current address: Department of Plant Sciences, The University of each chromosomal arm) were chosen for the analysis. Arizona, Tucson, AZ 857-19, USA. The SSR primers used in this study were described by Genetic effects on SSR diversity in wild emmer Y-C Li et al 151 Table 1 SSR motif and chromosomal locations Plaschke et al (1995) and Ro¨der et al (1995, 1998). Table 1 presents the repetitive motif, locus location, and distance Marker Motif Chromosomal from the centromere (D) in bread wheat, T. aestivum. The procedure used to detect SSR polymorphism followed Locationa Distanceb Plaschke et al (1995) and Fahima et al (1998). Fragment sizes were calculated using the Fragment Manager c GWM18 (CA)nGA(TA)k 1BS 5.7 (Pharmacia) computer program by comparing with GWM60 (CA)n 7AS 52.3 internal size standards, which were added to each lane GWM95 (AC)n 2AS 10.8 in the loading buffer. GWM99 (AC)n 1AL 95.3 GWM120 (CT)n(CA)k 2BL 23.7 Analysis of variance (ANOVA) was used to analyze GWM124 (CT)n(GT)k 1BL 82.2 genetic effects on SSR diversity. Multiple regression was GWM136 (CT)n 1AS 38.8 used to measure indirectly contributions of mutational GWM162 (CA)nAA(CA)k 3AL 91.0 mechanisms to SSR diversity in different repeat motifs. GWM169 (GA)n 6AL 49.6 The statistical analyses were performed using the GWM186 (GA)n 5AL 38.4 STATISTICA program (Statsoft, 1996). GWM218 (CT)n 3AS 30.4 GWM219 (GA)n 6BL 40.5 GWM251 (CA)n 4BL 28.9 Results GWM294 (GA)nTA(GA)k 2AL 16.1 GWM332 (GA)n 7AL 53.0 GWM340 (GA)n 3BL 131.4 SSR allele distribution with size clusters and constraints GWM361 (GA)n 6BS 11.4 The distribution of alleles at locus GWM99 showed two GWM368 (AT)n 4BS 8.7 clusters, one with small repeat numbers (7,8), the other GWM389 (CT)n(GT)k 3BS 118.4 with larger repeat numbers (21–24), with a considerable GWM408 (CA) (TA)(CA) (TA) 5BL 73.8 n k m gap of 12 repeats of (AC) between them (Figure 1). GWM415 (GA)n 5AS 25.4 GWM429 (CT)n 2BS 29.0 Similar patterns were observed at loci GWM60, GWM459 (GA)n 6AS 62.5 GWM537, and GWM577 (Figure 1). The allele-size GWM537 (CA)n(TA)k 7BS 43.6 distribution seems to have a low boundary at locus GWM540 (CT)n(CC)(CT)k 5BS 9.3 GWM577 and upper limits at locus GWM537 (Figure 1). GWM577 (CA)n(TA)k 7BL 105.0 At loci GWM415 and GWM601, alleles were limited to GWM601 (CT) 4AS 8.1 n repeat numbers 19 and 17, respectively. Allele sizes at GWM637 (CA)n 4AL 40.1 GWM95, GWM120, and GWM332a varied in the ranges aA, B: genome A and B; S, L: short and long arm. bDistance from the of 15–20, 31–36, and 17–18 repeats, respectively. These centromere (D, in cM), which was estimated according to the map of results suggest that some constraints may exist on repeat Ro¨der et al (1998), the distance of GWM 218 also referred to the map number at SSR loci. The last assumption is especially of Peng et al (2000). cm, n, and k symbolize repeat number. supported by allele distribution at GWM537 (Figure 1). Figure 1 Allele distributions with clusters and constraint at loci GWM60, GWM99, GWM537, and GWM577. Heredity Genetic effects on SSR diversity in wild emmer Y-C Li et al 152 Genetic effect on SSR variation then microsatellite loci, located farther from the centro- Analysis of variance (ANOVA) was used to test the meres should have larger diversity, because recombina- effects of genetic factors (genome, chromosome, and tion is suppressed around the centromeres (Gill et al, motif) (Table 2). The results suggested that genome (A vs 1996). In other words, the ARN and locus distance from B) significantly (Po0.05) affected the average repeat the centromere (D) may affect the genetic diversity at SSR number (ARN), with genome B showing larger ARN loci, allele number (NA) and variance in repeat number (30.2) than genome A (25.1). Genome A showed larger (s2), serving as indirect evidence in favor of one of the variance in repeat number (s2 ¼ 27.8) than genome B explanatory models. Forward stepwise regression was (s2 ¼ 19.0). The SSR ARN on chromosome 1 (including used to estimate contributions of ARN, D, and micro- 2 both 1A and 1B) were significantly (F(6,40) ¼ 3.85, Po0.01) niches to the A and s of different motifs (Table 3). The larger (ARN ¼ 42.5) than those of other chromosomes results indicated that ARN were the most important (ranged from 22 to 31). Microsatellites on chromosome 7 factor for (GA)n loci. Mutational mechanisms (repre- showed the highest variance (s2 ¼ 53.5) in repeat number sented indirectly by ARN, D, and D  ARN) could 2 2 (F(6,40) ¼ 2.72, Po0.05) compared with those on other significantly affect s at (GA)n loci (R ¼ 0.827, chromosomes. Compound SSRs, such as (CA)n(TA)k, Po0.00005). Niche could also alone (r ¼ 0.466, Po0.05) (CT)n(GT)k, and (CT)n(CA)k, appeared to have signifi- or through interaction niche  ARN (r ¼À0.538, Po0.05) 2 cantly (F(6,47) ¼ 2.88, Po0.01) larger ARN (433) than affect the s of (GA)n loci.
Load more

Recommended publications
  • 13 Genomics and Bioinformatics
    Enderle / Introduction to Biomedical Engineering 2nd ed. Final Proof 5.2.2005 11:58am page 799 13 GENOMICS AND BIOINFORMATICS Spencer Muse, PhD Chapter Contents 13.1 Introduction 13.1.1 The Central Dogma: DNA to RNA to Protein 13.2 Core Laboratory Technologies 13.2.1 Gene Sequencing 13.2.2 Whole Genome Sequencing 13.2.3 Gene Expression 13.2.4 Polymorphisms 13.3 Core Bioinformatics Technologies 13.3.1 Genomics Databases 13.3.2 Sequence Alignment 13.3.3 Database Searching 13.3.4 Hidden Markov Models 13.3.5 Gene Prediction 13.3.6 Functional Annotation 13.3.7 Identifying Differentially Expressed Genes 13.3.8 Clustering Genes with Shared Expression Patterns 13.4 Conclusion Exercises Suggested Reading At the conclusion of this chapter, the reader will be able to: & Discuss the basic principles of molecular biology regarding genome science. & Describe the major types of data involved in genome projects, including technologies for collecting them. 799 Enderle / Introduction to Biomedical Engineering 2nd ed. Final Proof 5.2.2005 11:58am page 800 800 CHAPTER 13 GENOMICS AND BIOINFORMATICS & Describe practical applications and uses of genomic data. & Understand the major topics in the field of bioinformatics and DNA sequence analysis. & Use key bioinformatics databases and web resources. 13.1 INTRODUCTION In April 2003, sequencing of all three billion nucleotides in the human genome was declared complete. This landmark of modern science brought with it high hopes for the understanding and treatment of human genetic disorders. There is plenty of evidence to suggest that the hopes will become reality—1631 human genetic diseases are now associated with known DNA sequences, compared to the less than 100 that were known at the initiation of the Human Genome Project (HGP) in 1990.
    [Show full text]
  • Genomics and Its Impact on Science and Society: the Human Genome Project and Beyond
    DOE/SC-0083 Genomics and Its Impact on Science and Society The Human Genome Project and Beyond U.S. Department of Energy Genome Research Programs: genomics.energy.gov A Primer ells are the fundamental working units of every living system. All the instructions Cneeded to direct their activities are contained within the chemical DNA (deoxyribonucleic acid). DNA from all organisms is made up of the same chemical and physical components. The DNA sequence is the particular side-by-side arrangement of bases along the DNA strand (e.g., ATTCCGGA). This order spells out the exact instruc- tions required to create a particular organism with protein complex its own unique traits. The genome is an organism’s complete set of DNA. Genomes vary widely in size: The smallest known genome for a free-living organism (a bac- terium) contains about 600,000 DNA base pairs, while human and mouse genomes have some From Genes to Proteins 3 billion (see p. 3). Except for mature red blood cells, all human cells contain a complete genome. Although genes get a lot of attention, the proteins DNA in each human cell is packaged into 46 chro- perform most life functions and even comprise the mosomes arranged into 23 pairs. Each chromosome is majority of cellular structures. Proteins are large, complex a physically separate molecule of DNA that ranges in molecules made up of chains of small chemical com- length from about 50 million to 250 million base pairs. pounds called amino acids. Chemical properties that A few types of major chromosomal abnormalities, distinguish the 20 different amino acids cause the including missing or extra copies or gross breaks and protein chains to fold up into specific three-dimensional rejoinings (translocations), can be detected by micro- structures that define their particular functions in the cell.
    [Show full text]
  • Gene Prediction and Genome Annotation
    A Crash Course in Gene and Genome Annotation Lieven Sterck, Bioinformatics & Systems Biology VIB-UGent [email protected] ProCoGen Dissemination Workshop, Riga, 5 nov 2013 “Conifer sequencing: basic concepts in conifer genomics” “This Project is financially supported by the European Commission under the 7th Framework Programme” Genome annotation: finding the biological relevant features on a raw genomic sequence (in a high throughput manner) ProCoGen Dissemination Workshop, Riga, 5 nov 2013 Thx to: BSB - annotation team • Lieven Sterck (Ectocarpus, higher plants, conifers, … ) • Yao-cheng Lin (Fungi, conifers, …) • Stephane Rombauts (green alga, mites, …) • Bram Verhelst (green algae) • Pierre Rouzé • Yves Van de Peer ProCoGen Dissemination Workshop, Riga, 5 nov 2013 Annotation experience • Plant genomes : A.thaliana & relatives (e.g. A.lyrata), Poplar, Physcomitrella patens, Medicago, Tomato, Vitis, Apple, Eucalyptus, Zostera, Spruce, Oak, Orchids … • Fungal genomes: Laccaria bicolor, Melampsora laricis- populina, Heterobasidion, other basidiomycetes, Glomus intraradices, Pichia pastoris, Geotrichum Candidum, Candida ... • Algal genomes: Ostreococcus spp, Micromonas, Bathycoccus, Phaeodactylum (and other diatoms), E.hux, Ectocarpus, Amoebophrya … • Animal genomes: Tetranychus urticae, Brevipalpus spp (mites), ... ProCoGen Dissemination Workshop, Riga, 5 nov 2013 Why genome annotation? • Raw sequence data is not useful for most biologists • To be meaningful to them it has to be converted into biological significant knowledge
    [Show full text]
  • Biology Dictionary English - Khmer
    vcnanuRkm CIvviTüa Gg;eKøs-Exµr Biology Dictionary English - Khmer saklviTüal½yPUminÞPñMeBj ed)a:tWm:g; CIvviTüa e)aHBum<elIkTI 3 ¬EksMrYl¦ 2003 Preface to the Third Edition (Revised) This dictionary is the work of many teachers and some students in the Biology department of The Royal University of Phnom Penh. It has developed over the last three years in response to the need of Biology students to learn Biology from English text books. We have also tried to anticipate the future needs of Biology students and teachers in Cambodia. If they want to join the global scientific community; read scientific journals, listen to international media, attend international conferences or study outside Cambodia, then they will probably need to communicate in English. Therefore, the main aim of this book is to help Cambodian students and teachers at the university level to understand Biology in English. All languages evolve. In the past the main influence on Khmer language was French. Nowadays, it is increasingly English. Some technical terms have already been absorbed from French and have become Khmer. Nowadays new technical terms are usually created in English and are used around the world. Language is also created by those who use it and only exists when it is used. Therefore, common usage has also influenced our translation. We have tried to respond to these various influences when preparing this dictionary, so that it represents many different opinions - old and new, Francophile, Anglophile and Khmer. But there will always be some disagreement about the translation of some terms. This is normal and occurs in all languages.
    [Show full text]
  • Small Variants Frequently Asked Questions (FAQ) Updated September 2011
    Small Variants Frequently Asked Questions (FAQ) Updated September 2011 Summary Information for each Genome .......................................................................................................... 3 How does Complete Genomics map reads and call variations? ........................................................................... 3 How do I assess the quality of a genome produced by Complete Genomics?................................................ 4 What is the difference between “Gross mapping yield” and “Both arms mapped yield” in the summary file? ............................................................................................................................................................................. 5 What are the definitions for Fully Called, Partially Called, Half-Called and No-Called?............................ 5 In the summary-[ASM-ID].tsv file, how is the number of homozygous SNPs calculated? ......................... 5 In the summary-[ASM-ID].tsv file, how is the number of heterozygous SNPs calculated? ....................... 5 In the summary-[ASM-ID].tsv file, how is the total number of SNPs calculated? .......................................... 5 In the summary-[ASM-ID].tsv file, what regions of the genome are included in the “exome”? .............. 6 In the summary-[ASM-ID].tsv file, how is the number of SNPs in the exome calculated? ......................... 6 In the summary-[ASM-ID].tsv file, how are variations in potentially redundant regions of the genome counted? .....................................................................................................................................................................
    [Show full text]
  • Capture of a Recombination Activating Sequence from Mammalian Cells
    Gene Therapy (1999) 6, 1819–1825 1999 Stockton Press All rights reserved 0969-7128/99 $15.00 http://www.stockton-press.co.uk/gt Capture of a recombination activating sequence from mammalian cells P Olson and R Dornburg The Dorrance H Hamilton Laboratories, Center for Human Virology, Division of Infectious Diseases, Jefferson Medical College, Thomas Jefferson University, Jefferson Alumni Hall, 1020 Locust Street, Rm 329, Philadelphia, PA 19107, USA We have developed a genetic trap for identifying revealed a putative recombination signal (CCCACCC). sequences that promote homologous DNA recombination. When this heptamer or an abbreviated form (CCCACC) The trap employs a retroviral vector that normally disables were reinserted into the vector, they stimulated vector itself after one round of replication. Insertion of defined repair and other DNA rearrangements. Mutant forms of DNA sequences into the vector induced the repair of a 300 these oligomers (eg CCCAACC or CCWACWS) did not. base pair deletion, which restored its ability to replicate. Our data suggest that the recombination events occurred Tests of random sequence libraries made in the vector within 48 h after transfection. Keywords: recombination; retroviral vector; vector stability; gene conversion; gene therapy Introduction scripts are still made from the intact left LTR, but reverse transcription copies the deletion to both LTRs, disabling Recognition of cis-acting DNA signals occupies a central the daughter provirus.15–17 We found that the SIN vectors role in both site-specific and general recombination path- that could escape this programmed disablement did so 1–6 ways. Signals in site-specific pathways define the by recombinationally repairing the U3-deleted LTR.
    [Show full text]
  • Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine
    biomolecules Review Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine Ryuji Hamamoto 1,2,*, Masaaki Komatsu 1,2, Ken Takasawa 1,2 , Ken Asada 1,2 and Syuzo Kaneko 1 1 Division of Molecular Modification and Cancer Biology, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan; [email protected] (M.K.); [email protected] (K.T.); [email protected] (K.A.); [email protected] (S.K.) 2 Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan * Correspondence: [email protected]; Tel.: +81-3-3547-5271 Received: 1 December 2019; Accepted: 27 December 2019; Published: 30 December 2019 Abstract: To clarify the mechanisms of diseases, such as cancer, studies analyzing genetic mutations have been actively conducted for a long time, and a large number of achievements have already been reported. Indeed, genomic medicine is considered the core discipline of precision medicine, and currently, the clinical application of cutting-edge genomic medicine aimed at improving the prevention, diagnosis and treatment of a wide range of diseases is promoted. However, although the Human Genome Project was completed in 2003 and large-scale genetic analyses have since been accomplished worldwide with the development of next-generation sequencing (NGS), explaining the mechanism of disease onset only using genetic variation has been recognized as difficult. Meanwhile, the importance of epigenetics, which describes inheritance by mechanisms other than the genomic DNA sequence, has recently attracted attention, and, in particular, many studies have reported the involvement of epigenetic deregulation in human cancer.
    [Show full text]
  • The Economic Impact and Functional Applications of Human Genetics and Genomics
    The Economic Impact and Functional Applications of Human Genetics and Genomics Commissioned by the American Society of Human Genetics Produced by TEConomy Partners, LLC. Report Authors: Simon Tripp and Martin Grueber May 2021 TEConomy Partners, LLC (TEConomy) endeavors at all times to produce work of the highest quality, consistent with our contract commitments. However, because of the research and/or experimental nature of this work, the client undertakes the sole responsibility for the consequence of any use or misuse of, or inability to use, any information or result obtained from TEConomy, and TEConomy, its partners, or employees have no legal liability for the accuracy, adequacy, or efficacy thereof. Acknowledgements ASHG and the project authors wish to thank the following organizations for their generous support of this study. Invitae Corporation, San Francisco, CA Regeneron Pharmaceuticals, Inc., Tarrytown, NY The project authors express their sincere appreciation to the following indi- viduals who provided their advice and input to this project. ASHG Government and Public Advocacy Committee Lynn B. Jorde, PhD ASHG Government and Public Advocacy Committee (GPAC) Chair, President (2011) Professor and Chair of Human Genetics George and Dolores Eccles Institute of Human Genetics University of Utah School of Medicine Katrina Goddard, PhD ASHG GPAC Incoming Chair, Board of Directors (2018-2020) Distinguished Investigator, Associate Director, Science Programs Kaiser Permanente Northwest Melinda Aldrich, PhD, MPH Associate Professor, Department of Medicine, Division of Genetic Medicine Vanderbilt University Medical Center Wendy Chung, MD, PhD Professor of Pediatrics in Medicine and Director, Clinical Cancer Genetics Columbia University Mira Irons, MD Chief Health and Science Officer American Medical Association Peng Jin, PhD Professor and Chair, Department of Human Genetics Emory University Allison McCague, PhD Science Policy Analyst, Policy and Program Analysis Branch National Human Genome Research Institute Rebecca Meyer-Schuman, MS Human Genetics Ph.D.
    [Show full text]
  • Conversion Between 100-Million-Year-Old Duplicated Genes Contributes to Rice Subspecies Divergence
    Wei et al. BMC Genomics (2021) 22:460 https://doi.org/10.1186/s12864-021-07776-y RESEARCH Open Access Conversion between 100-million-year-old duplicated genes contributes to rice subspecies divergence Chendan Wei1†, Zhenyi Wang1†, Jianyu Wang1†, Jia Teng1, Shaoqi Shen1, Qimeng Xiao1, Shoutong Bao1, Yishan Feng1, Yan Zhang1, Yuxian Li1, Sangrong Sun1, Yuanshuai Yue1, Chunyang Wu1, Yanli Wang1, Tianning Zhou1, Wenbo Xu1, Jigao Yu2,3, Li Wang1* and Jinpeng Wang1,2,3* Abstract Background: Duplicated gene pairs produced by ancient polyploidy maintain high sequence similarity over a long period of time and may result from illegitimate recombination between homeologous chromosomes. The genomes of Asian cultivated rice Oryza sativa ssp. indica (XI) and Oryza sativa ssp. japonica (GJ) have recently been updated, providing new opportunities for investigating ongoing gene conversion events and their impact on genome evolution. Results: Using comparative genomics and phylogenetic analyses, we evaluated gene conversion rates between duplicated genes produced by polyploidization 100 million years ago (mya) in GJ and XI. At least 5.19–5.77% of genes duplicated across the three rice genomes were affected by whole-gene conversion after the divergence of GJ and XI at ~ 0.4 mya, with more (7.77–9.53%) showing conversion of only portions of genes. Independently converted duplicates surviving in the genomes of different subspecies often use the same donor genes. The ongoing gene conversion frequency was higher near chromosome termini, with a single pair of homoeologous chromosomes, 11 and 12, in each rice genome being most affected. Notably, ongoing gene conversion has maintained similarity between very ancient duplicates, provided opportunities for further gene conversion, and accelerated rice divergence.
    [Show full text]
  • Molecular Biology and Applied Genetics
    MOLECULAR BIOLOGY AND APPLIED GENETICS FOR Medical Laboratory Technology Students Upgraded Lecture Note Series Mohammed Awole Adem Jimma University MOLECULAR BIOLOGY AND APPLIED GENETICS For Medical Laboratory Technician Students Lecture Note Series Mohammed Awole Adem Upgraded - 2006 In collaboration with The Carter Center (EPHTI) and The Federal Democratic Republic of Ethiopia Ministry of Education and Ministry of Health Jimma University PREFACE The problem faced today in the learning and teaching of Applied Genetics and Molecular Biology for laboratory technologists in universities, colleges andhealth institutions primarily from the unavailability of textbooks that focus on the needs of Ethiopian students. This lecture note has been prepared with the primary aim of alleviating the problems encountered in the teaching of Medical Applied Genetics and Molecular Biology course and in minimizing discrepancies prevailing among the different teaching and training health institutions. It can also be used in teaching any introductory course on medical Applied Genetics and Molecular Biology and as a reference material. This lecture note is specifically designed for medical laboratory technologists, and includes only those areas of molecular cell biology and Applied Genetics relevant to degree-level understanding of modern laboratory technology. Since genetics is prerequisite course to molecular biology, the lecture note starts with Genetics i followed by Molecular Biology. It provides students with molecular background to enable them to understand and critically analyze recent advances in laboratory sciences. Finally, it contains a glossary, which summarizes important terminologies used in the text. Each chapter begins by specific learning objectives and at the end of each chapter review questions are also included.
    [Show full text]
  • A Long Polymorphic GT Microsatellite Within a Gene Promoter Mediates Non-Imprinted Allele-Specific DNA Methylation of a Cpg Island in a Goldfish Inter-Strain Hybrid
    International Journal of Molecular Sciences Article A Long Polymorphic GT Microsatellite within a Gene Promoter Mediates Non-Imprinted Allele-Specific DNA Methylation of a CpG Island in a Goldfish Inter-Strain Hybrid 1,2, , 2, 2 Jianbo Zheng * y , Haomang Xu y and Huiwen Cao 1 Zhejiang Institute of Freshwater Fisheries, Huzhou 313001, China 2 College of Life Sciences, Zhejiang University, Hangzhou 310058, China * Correspondence: [email protected]; Tel.: +86-572-204-5681 These authors equally contributed to this work. y Received: 26 June 2019; Accepted: 6 August 2019; Published: 12 August 2019 Abstract: It is now widely accepted that allele-specific DNA methylation (ASM) commonly occurs at non-imprinted loci. Most of the non-imprinted ASM regions observed both within and outside of the CpG island show a strong correlation with DNA polymorphisms. However, what polymorphic cis-acting elements mediate non-imprinted ASM of the CpG island remains unclear. In this study, we investigated the impact of polymorphic GT microsatellites within the gene promoter on non-imprinted ASM of the local CpG island in goldfish. We generated various goldfish heterozygotes, in which the length of GT microsatellites or some non-repetitive sequences in the promoter of no tail alleles was different. By examining the methylation status of the downstream CpG island in these heterozygotes, we found that polymorphisms of a long GT microsatellite can lead to the ASM of the downstream CpG island during oogenesis and embryogenesis, polymorphisms of short GT microsatellites and non-repetitive sequences in the promoter exhibited no significant effect on the methylation of the CpG island.
    [Show full text]
  • Mathematical Challenges from Genomics and Molecular Biology Richard M
    Mathematical Challenges from Genomics and Molecular Biology Richard M. Karp fundamental goal of biology is to un- algorithms and the role of combinatorics, opti- derstand how living cells function. This mization, probability, statistics, pattern recognition, understanding is the foundation for all and machine learning. higher levels of explanation, including We begin by presenting the minimal information Aphysiology, anatomy, behavior, ecology, about genes, genomes, and proteins required to and the study of populations. The field of molec- understand some of the key problems in genomics. ular biology analyzes the functioning of cells and Next we describe some of the fundamental goals of the processes of inheritance principally in terms of the molecular life sciences and the role of genomics interactions among three crucially important classes in attaining these goals. We then give a series of of macromolecules: DNA, RNA, and proteins. brief vignettes illustrating algorithmic and mathe- Proteins are the molecules that enable and execute matical questions arising in a number of specific most of the processes within a cell. DNA is the car- areas: sequence comparison, sequence assembly, rier of hereditary information in the form of genes gene finding, phylogeny construction, genome re- and directs the production of proteins. RNA is a key arrangement, associations between polymorphisms intermediary between DNA and proteins. and disease, classification and clustering of gene Molecular biology and genetics are undergoing expression data, and the logic of transcriptional revolutionary changes. These changes are guided by control. An annotated bibliography provides point- a view of a cell as a collection of interrelated sub- ers to more detailed information.
    [Show full text]