Scientia Horticulturae 198 (2016) 462–472

Contents lists available at ScienceDirect

Scientia Horticulturae

journal homepage: www.elsevier.com/locate/scihorti

Parallel consideration of SSRs and differentially expressed genes

under abiotic stress for targeted development of functional markers

in almond and related Prunus species

a,1 a,1 a,1 a,1

Arghavan Alisoltani , Shekoufeh Ebrahimi , Sahar Azarian , Mahsa Hematyar ,

a,b,∗ c d e

Behrouz Shiran , Hassan Jahanbazi , Hossein Fallahi , Sadegh Mousavi-Fard , a

Fariba Rafiei

a

Department of Plant Breeding and Biotechnology, Faculty of Agriculture, Shahrekord University, Shahrekord, P.O. Box 115, Iran

b

Institute of Biotechnology, Shahrekord University, Shahrekord, P.O. Box 115, Iran

c

Agriculture and Natural Resources Research Center of Chaharmahal and Bakhtiari Province, Iran

d

Department of Biology, School of Sciences, Razi University, Bagh-e-Abrisham Kermanshah, Iran

e

Department of Horticultural Science, Faculty of Agriculture, Lorestan University, Khorramabad, P.O. Box 465, Iran

a r t i c l e i n f o a b s t r a c t

Article history: RNA-Seq approach is widely used to study plant transcriptome responses to different environmental

Received 14 June 2015

stresses. RNA-Seq datasets have also become valuable resources to develop SSR markers and other types

Received in revised form 8 October 2015

of markers in plant species. However, there are challenges such as the validation of SSR polymorphisms,

Accepted 9 October 2015

and translation of these information into a functional approach for plant breeding programs. In our recent

Available online 24 November 2015

work, the first de novo transcriptome assembly of almond have been reported in response to freezing

stress, and thousands of differential expression (DE) genes have been identified. Here, for the first time,

Keywords:

we have suggested a parallel consideration of genes with DE under frost stress and SSR markers to find

Almond

Calmodulin functional markers in almond (Prunus dulcis Mill.) and other related Prunus species. The term “RNA-Seq

SSR” was used in the current study, replacing the previous term “EST-SSR” (expressed sequence tagged),

Differential expression

Frost stress for the distinction between traditional EST sequencing and the new RNA-Seq methods. Eleven RNA-Seq

Genetic diversity SSR markers were identified as polymorphic markers. Some of SSR loci were found on genes which are

RNA-Seq SSR responsive in cold and other abiotic stresses, including calmodulin, trihelix transcription factor GT-1-like

and delta-(8)-fatty-acid desaturase. Furthermore, these markers revealed high polymorphism in popu-

lation of Prunus arabica, Prunus scoparia and Prunus haussknechtii. Our overall results suggest potential

application of DE genes carrying SSR sequences as functional markers. The developed workflow and the

new findings presented here are likely to open new opportunity for future genetic diversity, associa-

tion studies and breeding projects of almond and other plants grown under environmental stresses. This

workflow can also be applied to targeted validation and development of SNP and/or indel markers.

© 2015 Elsevier B.V. All rights reserved.

1. Introduction (Prunus armeniaca), cherry (Prunus avium) and almond (Prunus

dulcis Mill.). Spring frost is regarded as one of the main stress

The genus Prunus belongs to Rosaceae family and contains factors, leading to significant decrease in crop productivity of

several economically important species such as peach (Prunus per- almond and other fruit trees in Prunus genus (Mousavi et al.,

sica), Plum (Prunus cerasus), Chinese plum (Prunus mume), apricot 2014a; Salazar-Gutiérrez et al., 2014). Introducing new cultivars

resistant to abiotic stresses are important to increase food produc-

tion. Acquired plant tolerance to abiotic stresses can be achieved

both by genetic engineering strategies and by conventional plant

Abbreviations: DE, differential expression; EST, expressed sequence tag; MAS, breeding combined with the use of molecular markers in marker-

marker assisted selection; RNA-Seq, RNA sequencing; SSR, simple sequence repeat. assisted selection (MAS) (Hajmansoor et al., 2013; Mousavi et al.,

∗

Corresponding author at: Department of Plant Breeding and Biotechnology,

2014a; Roychoudhury et al., 2011). Among molecular markers, sim-

Faculty of Agriculture, Shahrekord University, Shahrekord, P.O. Box 115, Iran.

ple sequence repeats (SSRs) or microsatellites are the marker of

Fax: +98 38 32324428.

choice because they are co-dominant, more polymorphic and sta-

E-mail addresses: [email protected], [email protected] (B. Shiran).

1

These authors contributed equally to this work.

http://dx.doi.org/10.1016/j.scienta.2015.10.020

0304-4238/© 2015 Elsevier B.V. All rights reserved.

A. Alisoltani et al. / Scientia Horticulturae 198 (2016) 462–472 463

ble. They are also much easier to assay compared with other types overcome these obstacles, Iiorizzo and colleagues offered compu-

of molecular markers (Hajmansoor et al., 2013; Shiran et al., 2007). tational identifications of polymorphic SSR markers prior to actual

SRRs are tandem repeats of 1–6 nucleotide motifs in nucleic laboratory verifications (Iorizzo et al., 2011). Zalapa et al. (2012)

acid sequences, which are located on non-coding as well as cod- also suggested ways to reduce the cost for validating and screening

ing regions of the plant genomes. EST-SSR is a type of SSR markers a growing number of SSRs.

developed from expressed sequence tags (EST) libraries (Zalapa In addition to aforementioned solutions, we suggest that the

et al., 2012). The polymorphism derived from EST-SSR may affect purposeful selection of SSR markers has the potential to yield many

protein structure and function, which make them important for benefits beyond the random validation of SSRs. Since SSR sequences

association, phylogenetic and evolutionary studies, quantitative on coding regions may alter protein structure and function leading

trait loci (QTL) analysis, MAS as well as many other applications. SSR to phenotypic variations, it can help to identify candidate func-

and EST-SSR markers have been applied in almond for generating tional genes and to increase the efficiency of MAS. To the best of

linkage maps (Joobeur et al., 2000), phylogenetic analysis (Xu et al., our knowledge, there is no study on the parallel consideration of DE

2004), QTL mapping (Sánchez-Pérez et al., 2007), assessing the genes under stress and SSRs. Polymorphic SSRs on stress responsive

genetic diversity (Rahemi et al., 2012; Shiran et al., 2007; Szikriszt genes can be important, and may be further translated to functional

et al., 2011) and gene flow (Delplancke et al., 2012). EST-SSR mark- markers in breeding programs. Recently, we have conducted the

ers have been also important to estimate the cross transferability holistic overview of gene expression in almond under frost stress,

rate among Prunus species (Wang et al., 2012; Zhang et al., 2014). and a huge number of DE genes (Mousavi et al., 2014).

However, development of SSR markers in almond and many In the current study, we have presented a pipeline for detec-

other related species has been limited due to the lack of avail- tion and comparison of RNA-Seq SSRs under frost stress aimed

able genomic information and EST libraries (Mousavi et al., 2014a; to develop informative markers. In addition to developing huge

Zhang et al., 2014). Preparing and sequencing of the traditional EST number of SSR markers in almond, we proved the potential use

libraries is a difficult, time-consuming and costly process. Whereas, of DE genes harboring SSR loci in analysis of genetic diversity in

next generation sequencing (NGS) technology allows efficient iden- almond and related Prunus species. It is found that some of these

tification of a large number of sequences at a fraction of the cost polymorphic markers are related to cold and other abiotic stress

and efforts offered by traditional approaches. High-throughput responses such as calmodulin and trihelix transcription factor GT-1.

RNA sequencing (RNA-Seq) is one of the NGS techniques, which These findings suggest the potential use of these markers in genetic

is rapidly emerging as a major quantitative transcriptome profil- diversity, association studies and MAS breeding.

ing approach (Wang et al., 2009). Large numbers of RNA-Seq data

have been produced in Prunus species (approximately 100 datasets)

2. Material and methods

as well as other genus in Rosaceae family (about 300 datasets) as

recorded in NCBI-SRA (sequence read archive) database. Because

2.1. Data collection and SSR analysis

of the high value of transferability (Wang et al., 2012; Zhang et al.,

2014), RNA-Seq SSR markers can be used to explore the genetic

The workflow of this study is presented in Fig. 1. RNA-Seq

diversity, comparative genomics, evolution and functional studies

data were obtained from our previous study on almond (P. dul-

across almond and other Rosaceae species.

cis Mill.) under frost stress (Mousavi et al., 2014a). Briefly, the

Recently, the holistic overview of almond transcriptome has

quality and trimming of datasets were conducted using FastQC

been performed under frost stress condition, and more than 40,000

(Andrews, 2012) and FastX-toolkit (Gordon, 2011), respectively.

contigs have been de novo assembled (Mousavi et al., 2014a). Frost

Four paired-end sequencing libraries of almond were assembled

injury is regarded as one the major limiting factor in the production

using Trinity v1.3 (Grabherr et al., 2011), including ovary and anther

of almond (Khanizadehi et al., 1989; Kodad et al., 2010; Rodrigo,

tissues under normal and frost stress conditions. Annotation of de

2000). Almond is an early fruit tree, and it is usually exposed to

−5

novo transcripts was performed using BLASTX (with E-value <10 ).

late-spring frost, which could result in reduction or even abolishing

Transcript quantification for RNA-Seq reads and DE analysis were

the yield (Kodad et al., 2010; Samani et al., 2005). Frost stress could

performed with RSEM (Li and Dewey, 2011) and EBSeq (Leng et al.,

damage trees from the early blooming stage to anthesis (Imani et al.,

2013), respectively.

2012; Proebsting and Mills, 1978). Almond buds are more resistant

In de novo sequencing projects transcriptome coverage effi-

during winter, while reproductive tissues (anther and ovary) are

ciency has been evaluated by comparing the number of genes

less resistant to frost during blooming stage (Imani et al., 2012;

and/or protein-coding transcripts to the nearest transcriptome

Imani and Mahamadkhani, 2011; Mousavi et al., 2014a). Enhance-

available (De Carvalho et al., 2013; Verde et al., 2013). The num-

ment of cold tolerance is a complex trait involving the activation

ber of protein coding transcripts in almond (about 30,000) was

of thousands of genes in plants. As an example, the high through-

the same as predicted protein coding transcripts in peach (28,689)

put analysis of gene expression in almond under frost stress led to

(Verde et al., 2013). Moreover, quality validation of de novo con-

detection of more than 7000 DE genes (Mousavi et al., 2014a). Gene

tigs was evaluated by mapping reads to the P. persica v1.0 genome

ontology analysis of plant DE genes under cold stress using RNA-seq

(Verde et al., 2013). Almost 80% of the reads could be properly

methods revealed the importance of signaling, regulation, carbo-

mapped to the peach reference genome. This could show high accu-

hydrate and other biological pathways (Lei et al., 2014; Mousavi

racy of our contigs assembly and could reflect the presence of high

et al., 2014a; Shen et al., 2014; Wang et al., 2015). Therefore, these

similarity between almond and peach genomes (Mousavi et al.,

data are valuable resources for development of SSR markers for

2014a).

tolerance to cold stress.

De novo contigs for each untreated and frost treated samples

Despite discovery of enormous amounts of SSR loci in the recent

were analyzed for SSR motifs using SSR locator (Maia et al., 2008).

NGS studies, about 1% of all reported SSRs were validated, and

Mono-nucleotide repeats were excluded due to the abundance of

nearly half of these SSRs were characterized as polymorphic mark-

poly A/T repeats mostly resulting from poly A tails and/or sequenc-

ers (Zalapa et al., 2012). Another challenge is to find the functional

ing artifacts. The sequences were searched with SSR Locator for SSR

consequences of EST-SSRs and to translate the knowledge into

motifs ranging from 2 to 6 nucleotides (nt) in length. The repeat

applicable form for plant improvement. Thus, the question remains

numbers of motifs were set as follows: ≥10 for di-nt, ≥7 for tri-nt,

as to what is the way to develop informative and functional mark-

≥5 for tetr-nt, ≥4 for penta- and hexa-nt.

ers out of huge amounts of obtained SSRs with the lowest price? To

464 A. Alisoltani et al. / Scientia Horticulturae 198 (2016) 462–472

2.2. Statistical analysis of SSRs

Statistical analysis of SSR motifs between samples was per-

formed using a web tool, IDEG6 (Romualdi et al., 2003). The

Chi-squared 2 × 2, Audic and Claverie (Audic and Claverie, 1997),

and Fisher exact test were all conducted for comparison of nor-

mal and stress treated libraries in each tissue. However, R of Stekel

and Falciani (Stekel et al., 2000), Greller and Tobin (Greller and

Tobin, 1999) and General Chi-squared tests were all conducted for

comparison of total libraries (with p-value less than 0.05).

2.3. Ontology analysis of contigs harboring SSRs

The gene ontology analysis of the contigs harboring SSR loci

was conducted using AgriGO (http://bioinfo.cau.edu.cn/agriGO).

Fisher’s exact test was applied to compare the list of contigs har-

boring SSR sequences with peach genome (p-value < 0.05).

2.4. Selection of SSR markers and primer design

Among total contigs with SSR, twenty contigs with DE under

frost were selected (Table 1). Primer design for these 20 contigs

were conducted using primer3 script. The parameters for primer

design were set as follows: PCR product size 150–300 bp, primer

◦

length 18–25 bp, optimum annealing temperature 58–63 C, and

GC content of 30–50%.

Fig. 1. Workflow for development of functional SSR markers by parallel analysis of

2.5. Plant material, sampling and study site gene expression and SSRs. Differential expressed genes with SSRs have potential to

use as functional markers.

Twenty almond varieties along with 11 different related species

were obtained to confirm the polymorphism of RNA-Seq-SSR ◦

primer), extension at 72 C for 30 s and a final extension for 5 min

primers. The complete list of the samples is presented in Table 2. ◦

at 72 C. The PCR products were resolved on non-denaturing 8%

Besides, 60 samples were collected from each of Prunus arabica,

poly-Acrylamide gels in Tris borate/EDTA buffer until the loading

Prunus haussknechtii and Prunus scoparia for assessing the genetic

dye had migrated 10 cm. The products were then stained by ethid-

diversity of these species. The interval between samples was aver-

ium bromide and visualized under UV light. One sample was used

aged about 100 m to avoid close relatives. The geographical position

as a reference lane across all gels.

of the studied site was Karebas, Chaharmahal va Bakhtiari, Iran

◦  ◦  ◦  ◦ 

located between 31 33 –31 36 N and 51 10 –51 12 E, as illus-

trated in Fig. 2. Under laws and regulations controlling researches 2.7. Data scoring and genetic diversity analysis

undertaken in the field of agriculture in Iran, there is no obliga-

tion for the researchers to acquire permission from any academic All gels were manually scored with at least two individuals.

or official institution for using natural — considered to be national A numerical code was assigned to the total number of alleles

properties — resources and sites of the kind that have been used in each SSR locus. Thus a two-column matrix was obtained in

in our study. This, however, is subject to exceptions with regard which homozygous and heterozygous individuals showed one and

to enclosed regions. Therefore, the ethics underlying our sampling two bands in each SSR locus, respectively. It would be perfect if

from the region is underwritten by the freedom of intellectuals microsatellite data produced two bands. But often there are other

and researchers to undertake research freely in natural sites such bands in addition to the main bands known as stutter bands,

as Karebas, which is not classified as enclosed region. All voucher which usually differ from the real bands. Stutter bands usually

specimens are deposited in the Herbarium of the Agriculture and have lower intensity than the main alleles which make them dis-

Natural Resources Research Centre, Shahrekord (Table S1). tinguishable from real bands (Kohlstrom, 2008). Besides, in some

cases we had to use lower stringency condition of PCR for obtaining

2.6. DNA extraction, PCR amplification and separation of SSR sharper expected band. Therefore, non-specific bands appeared in

markers some gels. Anyhow, to prepare the accurate scoring, only correct-

sized PCR products have been considered, and we have tried to

Total genomic DNA was extracted from leaf tissue (500 mg) by ignore stutter and non-specific bands during the scoring proce-

CTAB DNA isolation method described earlier (Khanuja et al., 1999). dure. Although, stutter bands are generally considered undesirable

Genomic DNA quality and quantity were assessed on 1.2% Agarose (especially those with equivalent intensity as the main bands), they

gel, stained with ethidium bromide and the UV spectrophotometer. are good indicators of the presence of SSRs.

Polymerase Chain Reaction (PCR) was performed by an Eppen- Polymorphism information content (PIC) was calculated using

dorf Mastercycler ep Gradient S thermal cycler. PCR amplifications Power marker 3.25 (Liu and Muse, 2005) to determine the discrim-

were carried out in a 20 ␮L reaction mixture containing 100 ng of ination power of the SSR markers. The genetic distance coefficient

genomic DNA, 2 units of Taq DNA polymerase, 250 ␮M of each dNTP, of SSR markers was measured among all possible pairs of culti-

0.5 ␮M of each primer, 2 mM MgCl2 and 1× PCR buffer. The ther- vars/genotypes based on Rogers’ coefficient (Rogers, 1972). Cluster

◦

mocycler protocol was set with an initial denaturation step at 94 C analyses were obtained using NTSYSpc version 2.21j software

for 3 min, followed by 35 amplification cycles of denaturation at package (Rohlf, 2009), based on genetic distance matrices with

◦

94 C for 30 s, annealing for 30 s (temperatures specified for each the unweighted pair group method using arithmetic averages

A. Alisoltani et al. / Scientia Horticulturae 198 (2016) 462–472 465

Fig. 2. The geographical position of the collected populations of P. arabica, P. haussknechtii and P. scoparia: Karebas, Chaharmahal va Bakhtiari, Iran.

466 A. Alisoltani et al. / Scientia Horticulturae 198 (2016) 462–472 5 5

7 7 7 7 7 7 7 7 7 7 8 7 7

7 7 7

12 10

SSR (AAC) (TTC) (AAG) (ACA) (CAG) (GAT) (AAG) (ATGG) (AC) (CTC) (TCA) (AAT) (CAT) (TTTG) (AGG) (GCC) (AGA) (CCT) (TC) (CCG)

size

Product 260 268 187 225 216 227 246 158 291 285 280 160 284 211 243 281 143 150 106 211

sequences

AAACAATAACCAGCCGATGC CCTTGAAGTGAAGGCTGAGG AGATCTGGTGGTGGGATCTG CAACCAAAGCCCATCAAAAT Primer AACAAACCCCATGAGCAAAG AGGGTGATTAGGGCCAGAGT CCCCTTCCTCGTCACATTTA TCTTCGTCTTGTGTCTAGGGC GGGCTTCAAATTGACCATGT TTAACTTCATGGTCCTCGCC ATCTGGGCAGCGATAACAAC TGGCTCTTCCACCTTCAACT GAGAGGGTTTCGACATTGGA CGACACACCAGCAGAGAGAC GCTCAAAACCCTAACCCTCC GTGGATCAACAGCGAGACAA GCGCCAACAAATTAAACCAC TAGTTGGTGAGCTCGGTGTG ACCCCTAGTGCTTGGTCCTT GGGTTTGATTATTATGTTGGGC CATCCGAGGAAGAATTGGAA ACCAGCAGAGCCAGCAGTAT CCAGAAGGGTGTTGTCACCT CCCCTTCCACTATGCTCAAA AGCTAGCGACGCGTAATCAT CCCACAAACTCACACCCTCT GGCCGTCCTCTTTCTTCTCT AAGGCTCAAAGCAATGGATG CCTCCTTGGGTAGATGGGTT TCTTTCTTTCATTGCCCACC CACCCTCAGCCCATTACTGT AATCGTAACGCCACCAGAAC TTTGCTTCCACACACGAAAG TAACCGGAAAAGTAGTGCGG TCCATTTTTCCACCACCATT AGGATTTGGTGACGGTGAAG

2-like TGTAATCTTCATCCTCCGCC

kinase

clpX-like

homolog

1 CTTGGCCCAATCAGAGACAT

A2 subunit

1-like

BSL3

1-like

isoform

kinase

shkC

ATP-binding

GT-1-like TTTCAACACCCAGTCACCAA

serine/threonine-protein

phosphatase 11

receptor kinase ribonucleoprotein

L18a-2

factor

protease

desaturase-like

4

galactosyltransferase

Clp synthase protein

nuclear

protein

receptor-like

protein

LRR

embryogenesis transcription

OBERON

name specificity

ribosomal

protein CTCAACAATGGCTTCAACGA

Gene 3-ketoacyl-CoA ARGOS-like Galactomannan Somatic Protein Calmodulin-like 60S Probable Dual Serine/threonine-protein ATP-dependent hexokinase-3-like Uncharacterized size.

product

and

008234736.1|007215798.1| delta(8)-fatty-acid 007215474.1| Uncharacterized 008240933.1| Heterogeneous B2 008244485.1| 008239489.1| 007199420.1| 007212118.1| 008227081.1| 008231814.1| 008234312.1| 008228105.1| 008223805.1| Trihelix 007202712.1| 007202637.1|008233234.1| Uncharacterized 008240233.1| 007201966.1| 007202216.1| Uncharacterized

sequence

hit

primer

First

of

ID gi|645275222|ref|XM gi|595808541|ref|XM gi|645219866|ref|XM gi|595791466|ref|XM gi|645250955|ref|XM gi|645266071|ref|XM gi|595875424|ref|XM gi|645237647|ref|XM gi|595803546|ref|XM gi|645218321|ref|XM gi|645253343|ref|XM gi|645217544|ref|XM annotation,

gene

F R

FR gi|645267613|ref|XM FR gi|595936426|ref|XM

with

F R

FR gi|595941224|ref|XM FR gi|595807968|ref|XM FR gi|595805315|ref|XM F R FR gi|645230639|ref|XM

F R F R

F R

F R

SSR SSR

F R

FR gi|700284246|gb|KM214674.1|

SSR SSR SSR SSR

FR gi|645254259|ref|XM

F R F R

SSR SSR F R

SSR SSR SSR SSR SSR SSR SSR SSR

SSR SSR 4 4 F R

SSR SSR SSR SSR

SSR SSR

SSR SSR

SSR SSR

SSR SSR primers

SSR SSR

SSR SSR SSR SSR SSR SSR

name

SSR SSR

SSR 1

of

Primer PdSLD1 PdPER PdCALM PdARGOS PdGMGT1 PdUnchar1 PdHNRnpA2 PdB2protein PdTrTFGT1 PdKCS11 PdSERK11 PdUnchar2 PdOBERON PdRPL18AB PdshkC PdBSL3 PdUnchar3 PdclpX PdHEX3 PdUnchar4 PdHEX3 PdGMGT1 PdSERK11 PdUnchar2 PdclpX PdOBERON PdRPL18AB PdHNRnpA2 PdARGOS PdUnchar3 PdUnchar1 PdCALM PdSLD1 PdB2protein PdKCS11 PdTrTFGT1 PdBSL3 PdUnchar4 PdshkC PdPER Table List

A. Alisoltani et al. / Scientia Horticulturae 198 (2016) 462–472 467

Table 2

List of almond genotypes/cultivars and related Prunus species. The details for each sample are presented including name of species, name of cultivar/genotype, origin and

source.

Species name Cultivar/genotype name Characteristics Origin Source

Prunus dulcis H Genotype Iran SPII, Karj- Iran

Prunus dulcis M3 Genotype Iran SPII, Karj- Iran

Prunus dulcis G Genotype Iran SPII, Karj- Iran

Prunus dulcis Sh12 Genotype Iran SPII, Karj- Iran

Prunus dulcis Rabie Cultivar Iran SPII, Karj- Iran

Prunus dulcis NeplusUltera Cultivar USA SPII, Karj- Iran

Prunus dulcis Mamaei Cultivar Iran SPII, Karj- Iran

Prunus dulcis Sefid Cultivar Iran SPII, Karj- Iran

Prunus dulcis Shekoofe Cultivar Iran SPII, Karj- Iran

Prunus dulcis Sahand Cultivar Iran SPII, Karj- Iran

Prunus dulcis Azar Cultivar Iran SPII, Karj- Iran

Prunus dulcis Lauranne Cultivar Italy SPII, Karj- Iran

Prunus dulcis Texas Cultivar USA SPII, Karj- Iran

Prunus dulcis Perlis Cultivar Malaysia SPII, Karj- Iran

Prunus dulcis Genco Cultivar Italy SPII, Karj- Iran

Prunus dulcis Nonpareil Cultivar USA SPII, Karj- Iran

Prunus dulcis Tuono Cultivar Italy SPII, Karj- Iran

Prunus dulcis Primorskyi Cultivar Russia SPII, Karj- Iran

Prunus dulcis Thompson Cultivar USA SPII, Karj- Iran

Prunus scoparia – Wild Iran Natural resources

Prunus arabica – Wild Iran Natural resources

Prunus elaeagnifolia – Wild Iran Natural resources

Prunus communis – Wild Iran Natural resources

Prunus haussknechtii – Wild Iran Natural resources

Prunus bucharica – Wild Pakistan Gradziel

Prunus lycioides – Wild Iran Natural resources

Prunus webbii – Wild Mediterranean Gradziel

Prunus glauca – Wild Mediterranean Gradziel

Prunus kuramica – Wild Afghanistan Gradziel

Prunus persica – Cultivar China SPII, Karj, Iran

Fig. 3. Distribution of SSR motifs including type of SSR motifs, di- and trinucleotide motifs and types of amino acid (corresponding to trinucleotid motifs) in anther and ovary

tissues of almond. A is types of SSR motifs; B, C and D are types of dinucleotides, trinucleotides and amino acids, respectively. All of presented motifs are significantly (p < 0.05)

different between freezing treated and untreated tissues. HCO, HSO, HCA and HSA are assigned for untreated ovary tissue, frost treated ovary tissue, untreated anther tissue

and frost treated anther tissue, respectively.

468 A. Alisoltani et al. / Scientia Horticulturae 198 (2016) 462–472

Table 3

(Table S3). Sequence-specific DNA binding, protein kinase activ-

The number of total contigs and contigs harboring SSRs in anther and ovary tissues

ity, transcription factor (TF) activity, transcription regulator activity

under frost stress and normal conditions.

and transferase activity were the most significant functional classes

Tissue Condition Num. of contigs Num. of contigs harboting

among the whole molecular function ontologies. In the case of

SSRs

cellular components, cell part (18%), intracellular (10%) and mem-

Anther Frost stress 44477 1988 brane (9%) contributed to the highest proportion of terms followed

Untreated 41283 1489

by organelle (6%) and nucleus (5%) (Table S3).

Ovary Frost stress 38920 1956

Untreated 48562 1996

3.3. Polymorphism of SSR markers across almond

(UPGMA). The relationships between individuals were presented cultivars/genotypes and related Prunus species

in the form of dendrograms.

Out of 20 contigs harboring SSR markers, eleven RNA-Seq SSR

3. Results markers were shown clear polymorphic pattern across almond

cultivars/genotypes and/or related Prunus species (some exam-

3.1. Distribution of SSRs on sequences of de novo contigs in ples are illustrated in Fig. S1). These markers were annotated as

almond protein coding genes, including delta(8)-fatty-acid desaturase-like

isoform 1 (PdSLD1 SSR), B2 protein like (PdB2protein SSR), trihelix

The list of contigs obtained from de novo assembly of RNA- transcription factor GT-1-like (PdTrTFGT1 SSR), ARGOS-like pro-

Seq data is presented in Table 3. Four samples were analyzed by tein (PdARGOS SSR), galactomannan galactosyltransferase 1-like

SSR locator; 85,760 contigs belonged to anther and 87,482 contigs (PdGMGT1 SSR), protein OBERON 4 (PdOBERON4 SSR), calmodulin-

belonged to ovary tissues. As presented in Table 3, 1988 and 1489 like (PdCALM SSR), probable LRR receptor-like serine/threonine-

SSR loci were found on the contigs derived from anther tissues protein kinase (PdPER SSR) and dual specificity protein kinase

under freezing and normal conditions, respectively. In contrast, shkC (PdshkC SSR) as well as two uncharacterized proteins (PdUn-

1956 and 1996 SSR loci were located on the contigs of ovary tissues char1 SSR and PdUnchar4 SSR). Most of these SSR markers were

under freezing and normal conditions, respectively (Table 3). tri-nt, and recorded as down-expressed genes in ovary tissues

We observed significant variation within SSR motifs among (except for PdGMGT1 SSR and PdOBERON 4 SSR as overexpressed).

all samples (Fig. 3). Altogether, di-nt and tri-nt were recorded as However, some of these genes were mostly over-expressed in

the most frequent motifs compared to other types of SSR mark- anther tissue, including PdSLD1 SSR, PdUnchar1 SSR, PdGMGT1 SSR,

ers in both anther and ovary tissues (Fig. 3A and Table S2). Di-nt PdOBERON 4 SSR and PdPER SSR (Table S4).

was accounted for about 56.99% and 55.73% of all detected SSRs Presence of bands with the expected size were considered to

in anther and ovary tissues, respectively. However, trinucleotides assess transferability rates in almond and related Prunus species.

were accounted for about 20.81% and 20.69% of SSRs in anther and All of the 11 mentioned markers showed high amounts of trans-

ovary tissues, respectively. The remaining proportion of SSR motifs ferability (about 100%) across almond wild species as well as P.

was devoted to the other types of SSRs (tetra– to hexa-nt). persica. Summary statistics on genetic diversity and polymorphism

The patterns of di- and tri-nt motifs were compared between were calculated across both almond cultivars and related Prunus

freezing and normal conditions for both anther and ovary tissues species. The polymorphic information content (PIC) values ranged

(Fig. 3B and C). Among di- and tri-nt motifs, AG/CT, GA/TC, AAG/CTT, from 0 to 0.72 (PdOBERON 4 SSR), with an average of 0.42 across

AGA/TCT and GAA/TTC were recorded as the most abundant SSR almond cultivars/genotypes, meanwhile, it ranged from 0 to 0.74

markers (Fig. 3B and C). SSRs represented both consistent and (PdUnchar4 SSR) with an average of 0.42 across almond related wild

mixed altered patterns in ovary and anther tissues under frost stress species and P. persica (Tables S5 and S6). Mean of other statistics on

conditions. Two di-nt—AG/CT and GA/TC—were identified as com- diversity are presented in Table 4, including major allele frequency,

monly increased motifs under freezing, while no stable alternation allele number, gene diversity and heterozygosity. The highest rates

was observed for other types of di-nt in either of tissues (Fig. 3B). of heterozygosity were recorded for PdSLD1 SSR, PdTrTFGT1 SSR and

In the case of tri-nt, frequency of some of the tri-nt was increased PdCALM SSR, whereas PdCALM SSR, PdUnchar4 SSR and PdOBERON

during freezing stress, including ACC/GGT, AGC/GCT, ATA/TAT, 4 SSR showed the highest amounts of gene diversity in the total of

ATG/CAT and CTC/GAG. Whereas, some of the tri-nt motifs (such as the almond cultivars/genotypes as well as related species (Tables

GAA/TTC) were significantly decreased in both reproductive tissues S5 and S6).

under freezing stress (Fig. 3C).

SSRs also lead to differences in amino acid contents of frost

treated and untreated tissues. Within different amino acids cor- 3.4. Cluster analysis of almond genotypes and related species

responding to triplet motifs, Ala, Gly, Phe, Ile, Cys and Tyr were

significantly over-represented under freezing, while frequency of All 19 almond cultivars/genotypes were clustered according to

Val was significantly decreased under freezing stress in both anther their allelic data produced from the 11 RNA-Seq SSR markers. All

and ovary tissues (Fig. 3D and Table S2). cultivars were successfully distinguished from each other (Fig. 4).

Cluster analysis based on Rogers’ coefficient separated the almond

into two groups mostly according to their origin, hybridization

3.2. De novo assembled contigs with SSR markers are contribute

and/or common ancestry. Most of the cultivars/genotypes origi-

in different biological processes

nated from Iran along with Tuono, Nonpareil and Neplus Ultera

were clustered in group I. But the cultivars with non-Iranian ances-

De novo assembled contigs, harboring SSR markers, were clas-

try were mostly clustered in the second group (II), which includes

sified into different biological processes and molecular functions

Laurance, Texas, Perlis, Genco, Primorskyi and Thompson (Fig. 4).

as well as cellular component categories. Contigs harboring SSR

Cluster analysis was also conducted based on similarity matrix for

sequences were largely involved in regulation processes (approx-

almond related species. Unlike almond cultivars, almond and other

imately, 25% of total significant terms) such as regulation of

11 related species were scattered in no meaningful and distinct

biological process, cellular process, metabolic process, macro-

groups (Fig. S2).

molecule metabolic process, biosynthetic process and transcription

A. Alisoltani et al. / Scientia Horticulturae 198 (2016) 462–472 469

Table 4

Summary statistics on genetic variation in almond cultivars/genotypes and relative species as well as three populations of P. arabica, P. haussknechtii and P. scoparia.

Name of populations Sample size Major allele frequency Allele no Gene diversity Heterozygosity PIC

Almond cultivars/genotypes 19.00 0.64 3.36 0.46 0.40 0.43

Almond relative species 12.00 0.59 3.09 0.50 0.38 0.45

P. arabica 60.00 0.48 3.20 0.59 0.29 0.51

P. haussknechtii 60.00 0.38 3.80 0.69 0.23 0.62

P. scoparia 60.00 0.36 7.20 0.78 0.38 0.75

Fig. 4. Dendrogram based on the Rogers’ coefficient for 19 Iranian and non-Iranian almond genotypes/cultivars. Cluster analysis separated the almond into two groups mostly

according to their origin, hybridization and common ancestry.

3.5. Genetic diversity of P. arabica, P. haussknechtii and P. some genes were predicted as functional markers using RNA-Seq

scoparia data of almond under frost stress. These markers were then vali-

dated and applied to evaluate genetic diversity of different almond

The 11 above mentioned SSR markers were also evaluated to cultivars/genotypes as well as almond related species.

assess the genetic diversity of three populations of P. arabica, P. Results revealed that di- and tri-nt motifs are the most common

haussknechtii and P. scoparia. Among total 11 loci 9, 9 and 5 loci SSRs in almond, respectively. Although this is similar to previous

were polymorph in P. arabica, P. haussknechtii and P. scoparia, reports in almond and other Prunus species as well as many tree

respectively (Some examples are illustrated in Figs S3 and S4). genera (Ranade et al., 2014), it is quite different from the SSR dis-

The maximum PIC values were recorded for PdSLD1 SSR in P. ara- tribution in some plant species, such as Medicago truncatula (Mun

bica (0.74) and P. scoparia (0.74), as well as PdB2protein SSR in P. et al., 2006), tung tree (Xu et al., 2012), Paspalum dilatatum Poir

haussknechtii (0.74) (Tables S7–S9). The average value of PIC, major (Giordano et al., 2014) and wheat (Asadi and Monfared, 2014). In

allele frequency, allele number, gene diversity and heterozygosity these species the proportion of tri-nt motifs have been character-

for each of three species are presented in Table 4. Taken together, ized higher than di-nt motifs (specially in the protein coding regions

PdSLD1 SSR, PdB2protein SSR, PdCALM SSR and PdTrTFGT1 SSR are (CDS)). In addition to genetic background, the frequency of SSRs can

among the SSR markers with the highest gene diversity and het- be affected by criteria and tools used in SSR scanning and also the

erozygosity (Tables S7–S9). size of the applied library or dataset.

AG/CT motifs, as the most abundant di-nt, were recorded as

increased SSRs in frost treated libraries compare to untreated ones

4. Discussion in both anther and ovary tissues. Recently, comparative analysis

of EST-SSRs revealed higher proportion of AG/CT motifs in both

RNA-Seq is a newly developed approach to profile mRNAs using angiosperm and gymnosperm species (Ranade et al., 2014). In addi-

deep-sequencing technologies. It is widely being applied for SSR tion, higher frequency of AAG/CTT in our study was in accordance

marker discovery and genetic diversity assessments. However, the with previous reports in Prunus (Li et al., 2010; Wang et al., 2012),

main challenges in development of SSR markers are selection and Eucalyptus (Yan et al., 2012), Citrus (Palmieri et al., 2007) as well as

validation of huge number of predicted SSR loci in recent NGS data. many other angiosperms (Ranade et al., 2014). However, to the best

In the current research, simple pipeline was introduced for targeted of our knowledge there is no report on the changes of SSRs under

rather than random selection of SSR loci aim to develop functional adverse environmental conditions. Our recent study revealed the

markers. By parallel consideration of gene expression and SSR loci,

470 A. Alisoltani et al. / Scientia Horticulturae 198 (2016) 462–472

alternation of SSRs in different human cancers, and highlighted the affect phenotype. Furthermore, other types of DE genes harboring

impact of RNA-Seq SSRs as well as small RNA-Seq SSRs in human polymorphic SSR markers in our study were considered as stress

disease discovery and therapy (Alisoltani et al., 2015a). Changes in related genes in previous researches. An example is fatty acid desat-

the expression level of genes containing SSR sequences might inter- urases (e.g. PdSLD-SSR) which can modify the membrane fluidity by

pret the observed alternations of SSR frequencies under frost stress changes in unsaturated fatty acid levels (Upchurch, 2008). Mem-

in this study. SSR loci might also undergo quantitative and qualita- brane fluidity is important for sensing the stress agent and also

tive variations due to mutations that add or subtract repeat units acclimation of plants to environmental stresses in particular cold

(Kashi and King, 2006). Regardless of the mechanisms by which stress (Sung et al., 2003; Swan and Watson, 1997; Upchurch, 2008).

SSR sequence altered under stress, the DE genes harboring altered Localization of numerous genes with SSR motifs in membrane (9%)

motifs (polymorphic across individuals) could confer stress toler- might imply the importance of these genes by changing membrane

ance and have high potential to be used in the marker-assisted fluidity under frost stress.

breeding programs. We found that genes with SSR loci are mostly All of the 11 markers have shown 100% transferability across

contributed in regulation of biological and cellular processes, which almond related species. It has been demonstrated that SSR mark-

may indicate that SSRs have been non-randomly distributed in ers in coding regions represent a higher rate of transferability across

almond genome. Numerous reports have previously demonstrated species and also genus compared to genomic SSRs (Varshney et al.,

the non-random distribution of SSR motifs in genomes of various 2005). Hence, these markers are suitable for application in cross-

species such as Arabidopsis thaliana (Mortimer et al., 2005), Daphnia species phylogenetic researches. High rate of transferability have

pulex (Mayer et al., 2010) and Citrus (Biswas et al., 2012, 2014). been observed in Prunus (Mnejja et al., 2010) and other Rosacea

Changes in gene expression are often considered as the pri- (Gasic et al., 2009; Wang et al., 2012) species as well as other plant

mary layers in response to abiotic stresses. For instance, alternation species such as cereals (Kuleung et al., 2004; Tang et al., 2006), Bras-

of gene expression is initiated within 30 min after exposure of sica (An et al., 2011), leguminous (Mishra et al., 2012). Despite the

Arabidopsis plants to low temperatures (Le et al., 2015). Hence high transferability rate of these markers across almond species, no

genes with differential expression might be involved in the stress meaningful and distinct groups were identified in dendrogram of

tolerance of the plants. In our study, 11 DE genes harboring almond related species compared to almond cultivars/genotypes.

SSRs exhibited distinct polymorphisms across almond culti- This might be due to the low number of polymorphic markers

vars/genotypes and related species. PdSLD1 SSR, PdB2protein SSR, used in this study and/or mixed common ancestry of these species.

PdCALM SSR, PdTrTFGT1 SSR, PdUnchar4 SSR and PdOBERON 4 SSR The separation of almond cultivars/genotypes, however, was per-

were recorded as the RNA-Seq SSRs with the highest gene diver- formed using 11 RNA-Seq SSRs, highlighting the efficiency of these

sity and heterozygosity. Both calmodulin and trihelix transcription markers to study intra species diversity. Similar to the obtained

factor GT-1 are related to stress tolerance in plants. Calmodulin pro- results in almond cultivars and species, PdSLD1 SSR, PdCALM SSR

tein family is a ubiquitous and highly conserved calcium-binding and PdTrTFGT1 SSR have the highest gene diversity and heterozy-

regulatory proteins in eukaryotes (Das et al., 2014). Many of the gosity in P. arabica, P. haussknechtii and P. scoparia populations. This

calmodulin and calmodulin-like proteins play important roles in can confirm the high potential application of these three markers

mediating stress-signaling pathways, and assist plants to cope with in genetic diversity and evolution studies as well as plant improve-

both biotic and abiotic stresses (Das et al., 2014; Magnan et al., ment projects.

2008; Perochon et al., 2011). The obvious polymorphism of calmod- In conclusion, parallel consideration of SSRs and DE genes under

ulin was characterized across H, M3, G and Sh12 genotypes (Fig. frost stress leads to detection of some functional markers with

S1B). The differences in frost injury rate of these four genotypes potential application for enhancement of frost tolerance in almond

were previously reported, in which H and G were regarded as more and related Prunus species. The exponential growth in the number

tolerant genotypes compared to M3 and Sh12 genotypes (Alisoltani of RNA-Seq studies provides valuable resources of data for devel-

et al., 2015b; Mousavi et al., 2014b). In these studies, as a phe- opment of functional markers in plants. Despite the detection of

notypic marker of frost injury in each genotype, the number of huge numbers of SSR markers in plants through RNA-Seq tech-

normal and brownish pistils was counted after different freezing niques, a few number of them were randomly validated in the lab.

treatments in early and late blooming genotypes of Almond. Frost To cope with the large amounts of detected SSRs, we suggest a

injury depends on the intensity and duration of cold temperature, targeted selection scheme for SSRs, instead of random selection

and it has been reported from 0 to about 65% in G, H, Sh12 and of these markers. On the one hand, SSR markers are versatile and

M3 genotypes (Alisoltani et al., 2015b). High genetic diversity has important markers in plant breeding. On the other hand, changes

also been detected among other genotypes and varieties of almond in gene expression are critical for plant tolerance to environmental

for cold resistance (Imani et al., 2012; Imani and Mahamadkhani, stresses. Here, for the first time, we have integrated these two topics

2011). As different almond germplasms are available in both SPII, to develop functional markers for cold tolerance in almond. Some

Karaj, Iran and also in the world (Küden, 1997), these findings might of the detected DE genes harboring polymorphic SSRs directly or

offer the potential application of calmodulin in MAS breeding for indirectly play important role in response to cold and other abiotic

tolerance to frost stress. stresses. This suggests that these markers have potential to be used

In addition to the calmodulin gene, trihelix transcription fac- in MAS breeding projects, such as calmodulin, trihelix transcription

tors have been reported in improvement of plant tolerance to factor GT-1like and delta (8)-fatty-acid desaturase. In general, the

abiotic stresses (Kaplan-Levy et al., 2012; Wang et al., 2014; Xie applied pipeline in this study can open a new avenue for devel-

et al., 2009). Transcriptional regulation of gene expression, which opment of informative markers in breeding program of different

is controlled by various TFs, plays critical role in plant responses plants. The pipeline can also be applied to the development of func-

to environmental stresses. The introduced RNA-Seq SSRs in the tional markers based on other types of genomic variations (SNPs

present study were mostly classified to DNA binding, transcription and Indels).

factor activity and transcription regulator activity. This can suggest

that these genes with SSRs are valuable resources to find functional

markers. Besides, variations of SSRs in coding regions can change Author contribution statement

the amino acid sequence. Therefore, more study on the impact of

SSR variations on protein stability and structure is required to find A.A., B.Sh. and H.J. designed the analysis/experiment. A.A., B.Sh.

the function as well as binding features of TFs, which consequently and H.F. conducted the RNA-Seq SSR and statistical analysis. A.A.,

A. Alisoltani et al. / Scientia Horticulturae 198 (2016) 462–472 471

B.Sh., S.A., S.E., M.H., H.J., F.R. and S.M. contributed in sampling and Hajmansoor, S., Bihamta, M.R., Alisoltani, A., 2013. Genetic diversity among and

within Iranian and non-Iranian barely (Hordeum vulgare L.) genotypes using

collection of materials. SA, SE, AA, MH and SM performed experi-

SSR and storage proteins markers. Biochem. Syst. Ecol. 46, 7–17.

mental analysis and data confirmations. A.A., B.Sh. and H.F. wrote

Imani, A., Ezaddost, M., Asgari, F., Masoumi, S., Raeisi, I., 2012. Evaluation the

the paper. All authors discussed the results and commented on the resistance of almond to frost in controlled and field conditions. Int. J. Nuts

Related Sci. 3, 29–36.

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Imani, A., Mahamadkhani, Y., 2011. Characteristics of almond selections in relation

to late frost spring. Int. J. Nuts Related Sci. 2, 31–34.

Iorizzo, M., Senalik, D.A., Grzebelus, D., Bowman, M., Cavagnaro, P.F., Matvienko,

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