Identification and Characterization of SNPs in released, landrace and wild accessions of Mungbean (Vigna radiata (L.) Wilczek) using whole genome re-sequencing

doi:10.21203/rs.2.13417/v1

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Identification and Characterization of SNPs in released, landrace and wild accessions of Mungbean (Vigna radiata (L.) Wilczek) using whole genome re-sequencing

https://doi.org/10.21203/rs.2.13417/v1

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Mungbean [Vigna radiata (L.) R. Wilczek var. radiata] is vital grain legume having nutritional and socio-economic importance, especially in the developing countries. We performed whole genome re-sequencing of three accessions representing the wild progenitor species, released and landrace of mungbean to identify SNPs with relevance to genetic relationships analyses. Approximately 9.3 million raw reads were obtained by using Ion Torrent PGM™ platform and more than 92% of the reads were mapped to the reference mungbean genome. We identified a total of 233,799 single nucleotide polymorphisms in relation to the reference genome (SNPs: 103,341 in wild, 93,078 in released and 37,380 in landrace accessions) and 9,544 insertions and deletions (InDels: 4,742 in wild, 3,608 in released and 1,194 in landrace accessions) in the coding and non-coding regions. In all accessions, genomic variants were unevenly distributed within and across the mungbean chromosomes. Among these 5,339; 4,739 and 1,795 SNPs were non-synonymous in 815, 790 and 317 genes of wild, released and landrace accessions, respectively. These polymorphisms might contribute to the variation in important pathways of genes for abiotic and biotic stress tolerance and important agronomic traits such as seed dormancy, flowering time and seed size in mungbean. Among the randomly selected SNPs, a selected subset was validated using Sanger sequencing technique. The genomic variations among mungbean wild, released and landrace accessions constitute a powerful tool to support genetic research and molecular breeding of mungbean.

Epigenetics & Genomics

Domestication

insertion/deletion

mungbean

single nucleotide polymorphism

whole genome re-sequencing

Mungbean is a diploid (2n=22), self-pollinated and fast-growing (<60 days) legume belonging to the subfamily Papilionoid of the family Fabaceae (Van et al. 2013). It is distributed mainly in Asia, Australia, West Indies, South and North America and tropical and subtropical Africa (Gowda et al. 2015). Archaeological evidence and morphological diversity studies suggested that mungbean was domesticated in the Indian subcontinent about 3500 years ago and later spread to other Asian and African countries amid the initial domestication process (Vishnu-Mittre 1974; Fuller and Harvey 2006; Lambrides and Godwin 2007). Vigna radiata var. sublobata (Roxb. Verdcourt) is presumed to be the originator of mungbean and is widely distributed in the tropics of the Indian subcontinent, northern Australia to western Africa and Papua New Guinea (Smartt 1990; Tomooka et al. 2002). Among legumes, mungbean is an excellent and easily digestible source of protein for predominantly vegetarian populations in India. The raw and mature seeds are rich in nutrients including carbohydrates, protein, fiber, minerals, antioxidants like flavonoids (Quercetin-3-O-glucoside) and phenolics (Guo et al. 2012). In addition, mungbean roots ﬁx atmospheric nitrogen via symbiotic relationship with nitrogen-ﬁxing rhizobia (Chankaew et al. 2011; Allito et al. 2015). Thus this crop is valuable both economically as well as nutritionally and supports sustainable agriculture (Graham et al. 2003; Bangar et al 2018). However, despite being a valuable crop, overall production of mungbean is hampered by several factors such as narrow genetic base, biotic and abiotic stresses (Singh et al. 2015).

Molecular marker development is critical for crop improvement programs (Bangar et al. 2018). Among the molecular markers, SSR (simple sequence repeats) has been used mostly for assessing genetic diversity in mungbean (Chen et al. 2015; Kaur et al 2016). However, availability of only a limited number of polymorphic SSR makers in mungbean has hindered its use in marker assisted breeding programs (Gwag et al. 2010; Shrivastava et al. 2014). Attempts were also made to use SSR markers from other closely related legumes like moth bean, adzuki bean, cowpea and rice bean in diversity analyses (Jingade et al. 2014; Shivakumar et al. 2017) which was not sufficient to meet the basic requirements in terms of polymorphisms. SNPs (single nucleotide polymorphisms) representing single nucleotide changes at a specific locus are considered as the most abundant and ultimate form of genetic variation (Mammadov et al. 2012). Among the genomic variations, SNPs including InDels (insertions and deletions) have gained importance due to their wide genomic distribution with chromosome-specific positions, co-dominant inheritance, amenability to automated genotyping and high reproducibility (Ganal et al. 2009; Mammadov et al. 2012; Huq et al. 2016). The high density of SNPs has resulted in the increased use of SNPs as the markers for various applications such as accurate variety identification, diversity analysis, marker-assisted and genomic selection, association and QTL analysis and seed purity testing (Van et al. 2013; Kang et al. 2014; Huq et al. 2016).

Presence of a narrow genetic base has necessitated the use of wild relatives for crop improvement programs (Zhang et al. 2017; Muñoz et al. 2017). Further, the rapid development of the next-generation sequencing (NGS) technologies has enabled genome wide discovery of SNPs for characterization of genetic differences among varieties (Lam et al. 2010; Zhang et al. 2014; Wei et al. 2016; Valliyodan et al. 2016). Whole-genome sequencing has facilitated generation of genome-wide markers in several legumes such as lotus, soybean, pigeon pea, etc (Sato et al. 2008; Schmutz et al. 2010; Varshney et al. 2012, 2013). In mungbean, Isemura et al. (2012) reported 38 domestication related traits and 105 QTLs by genetic linkage mapping between mungbean and its wild relative species. Genome wide comparisons of variations between two mungbean cultivars Sunhwanokdu and Gyeonggijaerae 5 were also reported (Van et al. 2013). Further in a landmark study, Kang et al. (2014) explained the domestication and evolution process of Vigna with the completion of whole genome sequencing of cultivated (V. radiata var. radiata VC1973A), wild relative (V. radiata var. sublobata) and tetraploid relative (V. reflexo-pilosa var. glabra) of mungbean accessions. Schafleitner et al. (2016) reported bruchid resistance QTL on chromosome 5 from the populations derived from the wild mungbean TC1966 and cultivated variety V2802. The rapid development of NGS technologies along with the accessibility of complete mungbean genome facilitates an opportunity for the advance mungbean genomic research.

In this study, we sequenced whole genomes of a wild accession (Vigna radiata var. sublobata), a released variety (SML-668) and a landrace (MCV-1) of mungbean using Ion Torrent Personal Genome Machine™ (PGM^TM) platform. We analysed the genetic divergence of the wild accession and the domesticates after comparing the patterns of genetic variation among all accessions. The SNP polymorphisms observed in this study will enable the researchers to utilize genome-assisted breeding programs for utilization of genetic variations in wild and landraces in mungbean improvement.

Sample preparation

The materials used in this study were maintained at the National Bureau of Plant Genetic Resources (NBPGR), Pusa, New Delhi. Genomic DNA was isolated from the fresh, young leaf material of the released variety SML-668, wild Vigna radiata var. sublobata and landrace MCV-1 using Qiagen DNeasy Plant Mini Kit (Cat no. 69106). The quantity, as well as quality of isolated DNA, were analyzed with the Bioanalyzer 2100 (Agilent Technologies, Singapore) and Qubit 2.0 Fluorometer (Invitrogen Corporation) using the Qubit dsDNA BR Assay (Molecular probe, Life Technologies, Invitrogen Division).

Library preparation and sequencing

The DNA libraries were prepared by the Ion Shear Plus reagent kit (Life Technologies, USA) for each sample according to the user guide (Cat. no.4471248, Revision C.0) with minor modifications (shearing time 90 seconds). Firstly emulsion PCR of prepared libraries was performed by using the Ion OneTouch 2 (OT2) followed by the clonal amplification of DNA [according to Ion PGM™ Template OT2 400 Kit Cat. no. 4479878, Revision 3.0]. The prepared sample library was loaded on the Ion Torrent PGM machine (Life Technologies) using Ion PGM Sequencing 318v2 chip.

Sequence read mapping

CLC Genomics Workbench (version 8.0.1) was used for the sequence mapping. The following criteria were used for trimming the raw sequence: adaptor sequences, short reads (<101 bp), low-quality sequences (Phred quality score Q>29), and ambiguous nucleotides (N>2) were removed. The resultant high quality, filtered reads were mapped onto the mungbean reference genome using default parameters. The recent version of mungbean [Vigna radiata var. radiata (assembly Vradiata_ver6), RefSeq assembly accession: GCF_000741045.1] retrieved from NCBI was used as a reference (http://www.ncbi.nlm.nih.gov). For further analysis, the mapping output was changed to BAM format.

Identification and analysis of SNPs, InDels and structural variants

SNPs and InDels were identified from the mapping output files using the ‘Fixed Ploidy Variant Detection’ tool of the CLC Genomics Workbench. The following criteria were used for identification of SNP and InDels: Ploidy of sample 2, required variant probability ≥ 90%, average quality of the SNP base >29, minimum coverage 10, and minimum frequency 20%. Default values were used for all filters such as general filters, noise, quality, direction, and position. Pyro-variants from the raw data were removed using the technology-specific filters. To remove false positive SNPs from the data, SNPs showing homopolymer and 100% non-reference allele in output were filtered out. Further variant call format (VCF) files of SNPs and InDels of each accession were generated. Structural Variants tool of CLC Genomics Workbench was used to identify large and complex structural variants such as insertions, deletions, inversions, translocations and tandem duplications in read mapping using default parameters. Further, SAMtools (v0.1.16) software was used to measure genome coverage (Li et al. 2009).

Structural and functional annotations of SNPs and InDels

Genetic variant annotation and effect prediction toolbox SnpEff 4.3k (http://snpeff.sourceforge.net/) was used to annotate and classify the genomic variants (SNPs and InDels) using the VCF files as input (Cingolani et al.2012). For this, SnpEff Vigna radiata database was created using the V. radiata_ver6 genome annotation file (gff) and genome sequence. Using this database, both HTML and text files were obtained as an output for all the accessions. Genomic variants were annotated based on their impact (high, moderate, low and modifier) and functional class (synonymous and non-synonymous substitutions) in the output. The variants were also located based on their genomic regions such as downstream, upstream, exon, intron, intragenic and intergenic region, transcript, 3’and 5’un-translated regions (UTRs). The detected synonymous and non-synonymous SNPs and InDels of all accessions were visualized on the nuclear chromosomes using Circos Visualization tool (version 0.69) (Krzywinski et al. 2009). Further SNP variant containing genes were BLAST (cut-off value 1e-5) searched against NR database and Blast2Go was used for functional analysis of variants. Gene ontology (GO) category was assigned to each variant according to the biological process (BP), cellular component (CC) and molecular function (MF) and the results were visualized by WEGO 2.0 (Web Gene Ontology Annotations Plot) (Ye et al. 2006). Finally, high and moderate effects genomic variants were mapped to the KOBAS 3.0 version database for biological pathways analysis. The conserved domains in the proteins were predicted against the Pfam database (release 27.0) at the BLAST threshold 1e−5 (Wu et al. 2006).

SNPs Validation

Two SNPs per chromosome were selected randomly for the experimental validation of identified SNPs between the varieties. Primer pairs were designed from the 250 bp flanking sequences of the selected SNPs using Primer 3 (http://bioinfo.ut.ee/primer3-0.4.0/). Polymerase chain reaction (PCR) amplification was done in a thermal cycler (Eppendorf) with 25 µl reaction mixture under temperature conditions of 94°C for 6 min, followed by 35 PCR cycles inclusive of denaturation for 1 min at 94°C, primer annealing for 1 min at 54°C and primer elongation at 72°C for 1 min, followed by a step of extension at 72°C for 10 min. Only those amplified PCR products which are single and clear distinct band on an agarose gel were purified and sequenced by the Sanger sequencing method. The high-quality sequences of the accessions were aligned with the reference genome and analyzed for SNP variation by Jalview software version 2.10.1 (Waterhouse et al. 2009).

Whole genome sequencing and mapping

Whole genome sequencing was performed with Ion Torrent PGM™ sequencer using 318 v2 chip followed by a quality check of sequences with NGS core tools in CLC Genomics Workbench. A total of 3.3 million, 3.4 million and 2.6 million raw reads were obtained from the wild accession, released variety, and landrace, respectively. After removing low-quality reads, high quality trimmed reads were mapped to the reference genome (Vigna radiata var. radiata) individually. Approximately 91-92% reads of all accessions were mapped with 52-60 % coverage on the reference genome. Data of high quality trimmed reads, mapped alignments and GC% of all three re-sequenced accessions are presented in Table 1.

Identification, characterization and chromosomal distribution of genomic variants

SNPs and InDels were identified in all accessions against the reference genome individually. We identified 103,341 SNPs (1 variant every 3,230 bases) in wild accession, 93,078 SNPs (1 variant every 3,585 bases) in released variety and 37,380 SNPs (1 variant every 8,927 bases) in landrace in comparison with the reference genome. The number of transitions (Ts) and transversion (Tv) identified in wild accession were 66.46% and 33.54% respectively with Ts/Tv ratio of 1.98. Similarly, the released variety has 66.83% transition and 33.17% transversion with Ts/Tv ratio 2.01 and landrace had 66.20% transitions and 33.80% transversion with Ts/Tv ratio 1.95. Thus, the overall frequency of transitions was found to be higher than transversion in all the accessions (Supplementary Fig. S1). Transition frequency of A/G was more than C/T, while T/C was higher as compared to G/A among the accessions. However, the transversion frequency of A/T and C/G was higher as compared to T/A and G/C. Likewise, on individual comparison to the reference genome, 4,742 InDels (2,594 insertions and 2,148 deletions), 3,608 InDels (2,019 insertions and 1,589 deletions) and 1,194 InDels (693 insertions and 501 deletions) were identified in wild, released, and landrace accession, respectively. The length of insertion and deletions were 1-29 bp in wild accession, 1-36 bp in released variety and 1-24 bp in landrace (Supplementary Fig. S2). Most of the InDels were found to be less than 5 bp in length. Among the InDels detected, single base InDel was found at a higher rate (68.9%, 71.8%, and 75.3%) in all three accessions of Vigna. The longest deletion of 36 bp was found in released variety and the longest insertion of 26 bp was found in wild accession. InDels which are greater than 1kb in length were considered as structural variations. Wild accession harbors a maximum number of structural variations (5,043) followed by released variety (3,686) and landrace (3,533). Complex structural variations such as tandem duplication, replacement, cross-mapped breakpoints identified are presented in Supplementary Table S1. Among these, maximum and minimum numbers of genomic variations were found in wild accession and landrace, respectively.

For analyzing the chromosomal distribution of genomic variations, the latest version of mungbean genome was used as a reference. The SNPs and InDels detected from each accession are shown in the Vigna radiata chromosomes using Circos Visualization tool with 100kb sliding window size (Fig. 1). Maximum and minimum number of genomic variations was found on chromosome 8 and chromosome 3, respectively (Table 2). However, among all the accessions the highest density of SNPs was found in chromosome 1 (44.9/100kb) and lowest in chromosome 3 (19.6/100kb). Distribution of SNPs and InDels showed a positive correlation with the length of chromosomes in all the accessions. However, it was observed that SNPs and InDels distribution was not uniform within and across the chromosomes, as regions without SNPs/InDels were also noticed. Further to identify SNP hotspots, criteria of ≥400 SNPs per 100 kb were considered for all the accessions. In the wild accession, five hotspots were identified in chromosomes 1, 2, 9 and 10, while in the landrace and released variety only two hotspots were found on chromosome 9.

The selected SNPs were validated by their gel amplification in all the accessions. Table 3 lists the primer descriptions used for the verification of the selected SNPs along with their chromosomal reference positions and genomic locations. The results of in silico discovery of 16 SNPs out of selected 22 SNPs in mungbean were verified by the Sanger sequencing method followed by aligning the accession sequences using Jalview software (Fig. 2).

Structural and functional annotations of genomic variants

Vigna radiata annotated reference genome was used to evaluate the impact and possible effects of the SNPs and InDels identified in all accessions using the SnpEff software. SNPs and InDels were classified on the basis of their impacts on gene expression into four classes i.e. high effect (modify splice sites, frame-shift, start lost and stop gained/lost), moderate effect (causes non-synonymous substitutions), modifier (intergenic, intragenic, intron, upstream, downstream and UTR variants) and low effect (causes synonymous substitutions and start gained). In all accessions, a major proportion of SNPs were modifier (95-96%), followed by moderate (2.2-2.6 %), low impact (1.5-1.9%) and smallest subset of high effect SNPs (0.17- 0.23%). Similarly, InDels showed around 97% modifier genomic variants in the three accessions. InDels belonging to high impact variants ranged from 1.9 to 2.3% according to genotypes. Approximately 0.15-0.26% and 0.30-0.67% genomic variants are of low and moderate type effect respectively. Impacts of genomic variants are shown in Supplementary Table S2.

Structural annotation showed that SNPs were abundant in the intergenic region (38.36-41.78%) followed by downstream region (19.93-20.95%) and upstream region (17.18-19.68%) in all the accessions. In the structural component of the gene, a significant number of SNPs were found in intron region (5.25-5.93%) followed by exon region (4.84-5.06%) and minimum SNPs were observed in 3’UTR (0.13-0.26%) and 5’UTR (0.06-0.12%) in all the accessions (Fig. 3). Likewise, maximum numbers of InDels were found in the intergenic region (34.22-38.89%) followed by downstream (20.45-22.37%) and upstream (19.02-21.09%) regions. Genic regions contained a significant number of InDels in introns (6.48-8.47%) and exons (2.87-3.57%) and a minimum number in 3’UTRs (0.13-0.36%) and 5’UTRs (0.07-0.17%) in the accessions (Fig. 4). It was observed that the majority of genomic variations were located in non-coding regions and low diversity was present in coding regions. Further, SNP variants were functionally evaluated in terms of mis-sense, nonsense and silent SNPs. Among the protein coding regions, wild accession showed 3,191 synonymous SNPs in 570 genes and 5,339 non-synonymous SNPs in 815 genes. The non-synonymous SNPs included mis-sense substitution in 4,991 (77.44%) SNPs in 620 genes and 348 (5.4%) nonsense SNPs showed substitution by premature stop codon introduction in 195 genes. The released variety showed 2,882 synonymous SNPs in 528 genes and 4,739 non-synonymous SNPs in 790 genes. The non-synonymous SNPs included 4,442 (77.31%) mis-sense SNPs in 610 genes and 297 (5.17%) nonsense SNPs in 180 genes. Similarly, the landrace showed 1,105 synonymous SNPs in 228 genes and 1,795 non-synonymous SNPs in 317 genes. The non-synonymous SNPs in the landrace included 1,701 (78.49%) mis-sense SNPs in 256 genes and 94 (4.3%) nonsense SNPs in 61 genes. The remaining fraction of SNPs i.e. 17.16%, 17.51% and 17.16% in wild, released, and landrace respectively were silent SNPs. The ratio of non-synonymous (mis-sense) to synonymous SNPs was 1.56, 1.54 and 1.53 for wild accession, released variety and landrace respectively.

We further analysed variants which cause a change in the amino acid in the coding part of gene thereby play an important role in the functional variations. For this, we mapped the high and moderate effect genomic variants to KOBAS database and all variants were mapped to 178 unique KEGG pathways. Functional annotation of high and moderate effect SNPs gene revealed their maximum correspondence to signal transduction (average of 15.58%) followed by carbohydrate metabolism (an average of 9.74%), global and overview maps (average of 8.08%) with minimal correspondence to membrane transport pathways (an average of 0.5%) (Supplementary Fig. S3). Further, GO analysis depicted a significant representation of GO terms in the genes associated with biological processes (cellular process, 54.05%), followed by cellular components (cell, 27.02%), and molecular functions (catalytic activity, 18.91%) (Fig. 5).

Comparative genomic variations in the wild, released and landrace accessions

We observed that wild-speciﬁc SNP alleles (39.15%) were more abundant than the released variety of speciﬁc alleles (33.11%) and landrace speciﬁc alleles (8.89%). On comparison of the wild accession with landrace, we found 6,072 unique SNPs in 340 loci in wild accession and 749 unique SNPs in 74 loci in landrace in addition to 134 common loci in the protein coding regions of the wild accession and the landrace (Supplementary Table S3). Likewise, by comparison of wild accession with released variety, we found 4,007 unique SNPs in 245 loci in wild accession and 3,635 unique SNPs in 237 loci in released variety in addition to 229 common loci in protein coding regions of wild accession and released variety (Supplementary Table S4). Further, between released and landrace varieties, we found 4,696 unique SNPs in 317 loci in released variety and 534 unique SNPs in 59 loci in landrace in addition to 149 common loci in both released and landrace varieties (Supplementary Table S5).

We observed multiple variations in the high and moderate effect SNPs associated with the disease resistance pathways, receptor-like protein kinases and agronomic traits in all the accessions. Further, we found 568 SNPs in 46 protein kinase loci in wild accession, 161 SNPs in 14 loci in landrace and 575 SNPs in 32 protein kinase loci in released variety. Similarly, 764 SNPs were found in 19 disease resistance loci in wild accession, 440 SNPs in 12 loci in landrace and 931 SNPs in 28 loci in released variety. SNPs associated with agronomic characteristics such as seed size, seed color, seed dormancy and flowering timing among the wild, landrace and released accessions were compared (Supplementary Table S6). A total of 169 SNPs in wild accession and 63 SNPs in released variety were in the callose synthase gene, 29 SNPs were detected in the pentatricopeptide repeat. In addition, genes with an important role in regulating plant growth and flower development such as FAR1 related 5-like, F-box, and agamous-like MADS-box protein were observed to have SNPs in all accessions analysed. In this study, we found unique loci for agamous-like MADS-box protein (NC_028358.1, LOC106760530) in the wild accession only. However high impact SNPs was found lowest in number but they had a direct effect on the functionality of important genes related to the signaling pathways, growth and developmental traits of plants either by premature stop/start codon and or by changing gene splicing sites. We found a total of 347 SNPs in 203 loci in wild accession, 290 SNPs in 179 loci in released variety and 101 SNPs in 64 loci in landrace. By Pfam domain analysis of non-synonymous SNPs, 68.92%, 70.39%, and 79.76% transposon domains were found in released variety, wild accession, and landrace, respectively (Supplementary Table S7). The proportion of long terminal repeats (LTR) (class I transposon) was highest (~ 20%) while MuDr family transposase (class II transposon) proportion was lowest (~0.5%) in released variety and landrace accessions.

Whole genome re-sequencing is currently the most convenient approach for the genome-wide SNP identification and trait discovery in various crop plants including mungbean (Lam et al. 2010; Jain et al. 2014; Jiao et al. 2016). Genomic variations such as SNPs are linked to the majority of important traits used for numerous applications such as in genetic mapping, quantitative trait locus (QTL) analysis and genotypic diversification and evolutionary studies of plant species (Jain et al. 2014; Clevenger et al. 2015). In the present study, genomic variants were identified and compared between wild accession (Vigna radiata var. sublobata), and released variety (SML-668) as well as landrace (MCV-1) of mungbean by using NGS platform. In our data, 92% of the reads were mapped onto the reference genome indicating good quality of the data generated in this experiment. We observed high genetic variation in wild accession among all the accessions analysed indicating that these could be used as a source of new allelic variations in the mungbean germplasm improvement programs. Among the observed SNPs, a large proportion of the SNPs were detected in both wild and released mungbean variety, suggesting that most of the polymorphism observed in the modern released variety of mungbean came from their wild progenitors (Fig. 6). Also, the non-synonymous to synonymous ratio indicated a high substitution rates in mungbean wild, released and landrace accessions compared to the reports in other plants such as rice (1.2) and soybean (1.47) (Kenneth et al. 2009; Valliyodan et al. 2016). The results of the present study indicate the need to further analyze the diversity in mungbean genome so that more useful genomic variations can be discovered for use in marker assisted breeding in this important pulse crop.

Analysis for chromosomal level distribution of the variants revealed that SNP variations were dispersed unevenly across the chromosomes but positively correlate with the length of chromosomes. It was observed that high and low-density regions of genomic variants are present in the chromosomes. Such uneven dispersal of variants has also been identified in other plant species such as in tomato, rice, mei, and chickpea (Corrado et al. 2013; Jain et al. 2014; Zhang et al. 2017; Kujur et al. 2015). The high-density or hotspot regions were proposed to be the result of high rate of mutation in the genes residing in those regions (Lercher and Hurst 2002). In this study, high density regions of SNPs were found on chromosomes 1, 2, 9 and 10 in wild accession. These chromosomal regions have been reported to harbor QTLs related to important agronomic traits such as seed dormancy, seed size, pod dehiscence, growth habit and flowering time that might have been used in the domestication of modern mungbean cultivars (Isemura et al. 2012; Li et al. 2014). On the other hand, the low-density regions represent a reduction in the genetic diversity. Therefore, knowledge of genomic variants residing in the high and low variant density regions provides a better breeding approach for crop improvement (Jain et al. 2014). We observed that SNPs identified exhibited transition bias as the numbers of transition were higher than transversion, which is comparable with the previous studies (Jain et al. 2014; Zhang et al. 2014). This might be related to the high methylation frequency of C to T changes. Structural annotation of all SNPs and InDels indicated that these were present in only 5% of the coding region and the rest were located in intergenic and non-coding regions of mungbean genome. Similar results have also been reported in other species, such as in melon, strawberry, soybean, and tomato (Natarajan et al. 2016; Corrado et al. 2013; Hawkins et al. 2016). One possible explanation for the low occurrence of such variants could be that the non-synonymous SNPs in coding regions can lead to a functional change of gene expression and might affect plant growth and development thus resulting in positive or negative effects of selection process during the course of evolution. It had reported that InDels of shorter length cause a more deleterious effect on gene expression than longer InDels in all crops (Choi et al. 2012). Further, transposon elements (TE) have played a key role in the course of plant evolution, genome expansion, and gene regulation by causing various kinds of genetic variations (Lisch 2013). We observed more transposon elements in wild relatives than released variety. Similar findings of the transposon elements have been reported in other studies (Wang et al. 2013; Kang et al. 2014) which also substantiate the present conclusions.

A significant number of high and moderate eﬀect SNPs were identiﬁed in the genes related to plant development, signal transduction, ﬂowering, and carbohydrate metabolism. The SNPs in the gene loci, protein kinases loci, leucine-rich receptors, serine/threonine protein kinases and cysteine-rich protein kinases were present in higher frequencies in wild accession than the released variety which is comparable to the earlier studies (Li et al. 2014; Zhang et al 2017). KEGG pathway analysis of the genomic variants showed enrichment of variants in genes required for carbohydrate metabolism and signal transduction pathways in mungbean (Hudson et al. 1999; de Folter et al. 2005; Jung et al. 2012). Since both these pathways are known for their role in plant abiotic stress tolerance, understanding implications of these genomic variations are likely to provide in depth information about the positive selection for abiotic stress tolerance during the domestication and selection of mungbean (Brozynska et al. 2016; Pandey et al. 2016).

Overall, in this study, a substantial number of genomic variations i.e. SNPs and InDels were detected using Ion torrent PGM^TM platform. Most of the modern mungbean released varieties are suffering from the high degree of homogeneity (Lakhanpaul et al. 2000). These identified genomic variations provided significant information on functional and structural diversity among wild, released and landrace accession of mungbean accessions. Further, this study brings into focus the significance of wild species diversity in mungbean breeding programs. The integrated analysis of high effect and non-synonymous genomic variations with QTLs could be used to discover and clone genes related to the important agronomic traits. In addition, medium- or low-density SNP arrays could be constructed with a set of SNPs having high agronomic values for specific germplasm screening and molecular breeding programs. Thus the genomic variations (SNPs and InDels) generated in this study will add beneficial genomic resources that can be efficiently exploited for future mungbean improvement programs.

Acknowledgements

The authors thank the Indian Council of Agricultural Research and Director New Delhi, National Bureau of Plant Genetic Resources for the facilities provided for the study. The first author, PB acknowledges the fellowship from The Department of Biotechnology, Government of India for the Ph. D program. The funding for the wet laboratory analyses from CRP on Genomics project of the Indian Council of Agricultural Research is gratefully acknowledged.

Conflict of Interests

Authors declare no conflict of interest.

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Table 1 Summary of re-sequenced accessions (Wild accession, Released variety and Landrace) on to the reference genome Vigna radiata

*Vigna* accessions	Wild	Released	Landrace
High quality reads	2,551,540	2,683,047	1,697,559
Mapped reads	2,326,880 (91.20%)	2,473,655 (92.20%)	1,560,852 (91.95%)
Average length	252.89	258.79	251.49
GC (%)	34.20	35.49	34.73
Genome coverage (%)	54.83%	59.85%	46.85%

Table 2 Distribution of SNPs, InDels and Structural variations in each chromosome of Vigna accessions

Chromosomes	SNPs			InDels			Structural variations
Chromosomes	Wild	Landrace	Released	Wild	Landrace	Released	Wild	Landrace	Released
Plastid	1	0	0	1	1	1	21	1	24
Mitochondria	1	51	2	15	7	10	1	1	1
Chromosome 1	14,663	5,134	12,601	650	170	472	836	448	525
Chromosome 2	8,251	3,134	8,102	370	93	354	172	134	284
Chromosome 3	1,450	454	1,161	82	13	52	117	203	179
Chromosome 4	5,771	1,651	5,030	237	58	212	368	196	247
Chromosome 5	8,385	2,911	7,314	370	80	301	243	320	302
Chromosome 6	14,265	5,229	12,767	592	129	441	859	410	471
Chromosome 7	15,342	5,138	14,072	713	168	514	439	555	599
Chromosome 8	16,951	6,785	15,729	767	227	541	1171	526	374
Chromosome 9	7,860	3,325	7,518	435	131	325	525	231	297
Chromosome 10	5,761	2,005	4,919	289	60	224	158	267	164
Chromosome 11	4,640	1,563	3,863	221	57	161	133	241	219
Total	1,03,341	37,380	93,078	4,742	1,194	3,608	5043	3533	3686
Average	9394.6	3398.1	8461.6	431.1	108.5	328	458.4	321.2	335.1

Note: SNP single nucleotide polymorphism, InDels insertion and deletion

Table 3 List of primers used for the validation of selected SNPs in the mungbean accessions

SNP ID	Chromosome	Reference position	Reference	*V. sublobata*	MCV-1	SML-668	Variant Type	Forward (F) primer (5’-3’)	Reverse (R) primer (5’-3’)	Product size	T_m (F)	T_m (R)	GC% (F)	GC% (R)
1	NC_028351.1	4139677	C	T	A	-	Upstream gene	TACGAAAAGGAGGGCATATG	AATTTATGCTGGCTCCAAGA	179	54.92	54.98	45	40
2	NC_028351.1	22089531	T	C	G	C	Intergenic	ACTGTTGTTGAGGCCTAGCT	ACCCAGTTTCAACCCAGGAA	167	58.94	59.07	50	50
3	NC_028352.1	111585	A	T	G	G/T	Missense	TACCGGTACAGCTGAGAATA	TGCGATATTCAAGTCTGGAG	190	55.09	54.98	45	45
4	NC_028352.1	20606865	A	C	T	C/T	Intergenic	CATCCAACAACTAGCCTAGG	TAGTACACACCGAGAGATGT	227	55.23	55.04	50	45
5	NC_028353.1	7339845	G	T	C	C/T	Missense	AACCTCCTCTGAATGACAAC	TCATTCAAACTCGCTACCAT	190	54.98	54.77	45	40
6	NC_028353.1	12661878	G	A	T	T	Intergenic	ATTTTCCCAACTTAGAGGCC	TGGAGTGGTGATTTTGAGAG	153	55.29	54.98	45	45
7	NC_028354.1	1017819	T	A	C	A	Intergenic	TCGGATGACAGAGTTAGACT	TAAGCCCTTCCAAGAGTTTC	215	55.03	54.96	45	45
8	NC_028354.1	13487393	T	A	C	C	Upstream gene	GACAGTTGACAGAGAAACCT	AAACCTCGTACTTTGACCTC	173	54.94	55.03	45	45
9	NC_028355.1	5770737	T	C	A	A/C	Intergenic	ATGTCAACCAAATCCAAACG	GAAGTCTTCTGTCACGACC	198	54.77	55.31	40	52.6
10	NC_028355.1	31958930	C	A	T	T	Intergenic	GTGCTTGTTTCAACCCATAC	ACTTTTGCTCCTGTGACTAG	220	55.17	55.01	45	45
11	NC_028356.1	23575348	A	C	T	-	Upstream gene	AAGTCATACGCCTCATCATC	TCTCTTCATTCAGACAAGGC	211	55.04	55.08	45	45
12	NC_028356.1	29215660	T	C	G	-	Intergenic	AATCTCGCCTTGAAGTTCAT	GCAGGACTTAAAGCTTGTTG	193	55.05	55.19	40	45
13	NC_028357.1	9767300	A	C	T	C/T	Upstream gene	CTGTTGCTTTTGTGTCTCAG	TCATCAAGCTTGTTCCTGAA	187	55.14	54.88	45	40
14	NC_028357.1	19212708	T	C	G	C	Intergenic	TGCGTGATTGAAGATGTAGA	ATCTTCCACCATACCAATCG	174	54.52	54.91	45	40
15	NC_028358.1	19533745	A	C	G	A/T	Upstream gene	GCAACCAAAAGTCACAACAA	TGTTTCTGTGTTGTTCTTGC	178	55.51	54.96	40	40
16	NC_028358.1	29706229	G	A	T	A	Synonymous	GGCACCACGTATTATAGTGT	TAGAGCAAGAACCCAACTTC	206	54.97	54.99	45	45
17	NC_028359.1	16146976	A	G	T	G	Intergenic	CCAGTAGCAGTACAATGTCA	TCTTTCTGATGCATCTCTGT	179	54.81	54.07	45	40
18	NC_028359.1	17596728	C	A	G	G	Intergenic	GGCATATGAAGTCTTGGTCA	CGAATTGAAAGTGAAGCCTC	207	55.13	55.01	45	45
19	NC_028360.1	12538607	A	G	T	-	Upstream gene	CGGATCTCCTTAGGAAGTTG	CAGAAGACGAGGCTTATGAA	190	54.97	54.91	50	45
20	NC_028360.1	2851951	A	-	T	T	Intergenic	GGCCTAATAAGCATCCTGTT	TTTTCTGCACCTAGAACTCC	167	55.17	54.99	45	45
21	NC_028361.1	12573184	T	C	A	-	Intergenic	ATTGGCAATTCAAACGATGC	AGAAGCGTTGTTCATATGGT	188	55.88	55.06	40	40
22	NC_028361.1	13099471	T	G	G	A	Intergenic	ATGATAGGAGGAGAGTGACC	GTTGAAGTCGATGAAGCTTG	201	55.12	55.04	50	45

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Identification and Characterization of SNPs in released, landrace and wild accessions of Mungbean (Vigna radiata (L.) Wilczek) using whole genome re-sequencing

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