Sandip M. Kale

Prioritization of candidate genes in “ QTL-hotspot ” region for drought tolerance in chickpea ( Cicer arietinum L.)

A combination of two approaches, namely QTL analysis and gene enrichment analysis were used to identify candidate genes in the “QTL-hotspot” region for drought tolerance present on the Ca4 pseudomolecule in chickpea. In the first approach, a high-density bin map was developed using 53,223 single nucleotide polymorphisms (SNPs) identified in the recombinant inbred line (RIL) population of ICC 4958 (drought tolerant) and ICC 1882 (drought sensitive) cross. QTL analysis using recombination bins as markers along with the phenotyping data for 17 drought tolerance related traits obtained over 1–5 seasons and 1–5 locations split the “QTL-hotspot” region into two subregions namely “QTL-hotspot_a” (15 genes) and “QTL-hotspot_b” (11 genes). In the second approach, gene enrichment analysis using significant marker trait associations based on SNPs from the Ca4 pseudomolecule with the above mentioned phenotyping data, and the candidate genes from the refined “QTL-hotspot” region showed enrichment for 23 genes. Twelve genes were found common in both approaches. Functional validation using quantitative real-time PCR (qRT-PCR) indicated four promising candidate genes having functional implications on the effect of “QTL-hotspot” for drought tolerance in chickpea.

Phylogenomic analysis of UDP glycosyltransferase 1 multigene family in Linum usitatissimum identified genes with varied expression patterns

BackgroundThe glycosylation process, catalyzed by ubiquitous glycosyltransferase (GT) family enzymes, is a prevalent modification of plant secondary metabolites that regulates various functions such as hormone homeostasis, detoxification of xenobiotics and biosynthesis and storage of secondary metabolites. Flax (Linum usitatissimum L.) is a commercially grown oilseed crop, important because of its essential fatty acids and health promoting lignans. Identification and characterization of UDP glycosyltransferase (UGT) genes from flax could provide valuable basic information about this important gene family and help to explain the seed specific glycosylated metabolite accumulation and other processes in plants. Plant genome sequencing projects are useful to discover complexity within this gene family and also pave way for the development of functional genomics approaches.ResultsTaking advantage of the newly assembled draft genome sequence of flax, we identified 137 UDP glycosyltransferase (UGT) genes from flax using a conserved signature motif. Phylogenetic analysis of these protein sequences clustered them into 14 major groups (A-N). Expression patterns of these genes were investigated using publicly available expressed sequence tag (EST), microarray data and reverse transcription quantitative real time PCR (RT-qPCR). Seventy-three per cent of these genes (100 out of 137) showed expression evidence in 15 tissues examined and indicated varied expression profiles. The RT-qPCR results of 10 selected genes were also coherent with the digital expression analysis. Interestingly, five duplicated UGT genes were identified, which showed differential expression in various tissues. Of the seven intron loss/gain positions detected, two intron positions were conserved among most of the UGTs, although a clear relationship about the evolution of these genes could not be established. Comparison of the flax UGTs with orthologs from four other sequenced dicot genomes indicated that seven UGTs were flax diverged.ConclusionsFlax has a large number of UGT genes including few flax diverged ones. Phylogenetic analysis and expression profiles of these genes identified tissue and condition specific repertoire of UGT genes from this crop. This study would facilitate precise selection of candidate genes and their further characterization of substrate specificities and in planta functions.

Development and Evaluation of a High Density Genotyping 'Axiom_Arachis' Array with 58 K SNPs for Accelerating Genetics and Breeding in Groundnut.

Single nucleotide polymorphisms (SNPs) are the most abundant DNA sequence variation in the genomes which can be used to associate genotypic variation to the phenotype. Therefore, availability of a high-density SNP array with uniform genome coverage can advance genetic studies and breeding applications. Here we report the development of a high-density SNP array ‘Axiom_Arachis’ with 58 K SNPs and its utility in groundnut genetic diversity study. In this context, from a total of 163,782 SNPs derived from DNA resequencing and RNA-sequencing of 41 groundnut accessions and wild diploid ancestors, a total of 58,233 unique and informative SNPs were selected for developing the array. In addition to cultivated groundnuts (Arachis hypogaea), fair representation was kept for other diploids (A. duranensis, A. stenosperma, A. cardenasii, A. magna and A. batizocoi). Genotyping of the groundnut ‘Reference Set’ containing 300 genotypes identified 44,424 polymorphic SNPs and genetic diversity analysis provided in-depth insights into the genetic architecture of this material. The availability of the high-density SNP array ‘Axiom_Arachis’ with 58 K SNPs will accelerate the process of high resolution trait genetics and molecular breeding in cultivated groundnut.

Next‐generation sequencing for identification of candidate genes for Fusarium wilt and sterility mosaic disease in pigeonpea (Cajanus cajan)

Summary To map resistance genes for Fusarium wilt (FW) and sterility mosaic disease (SMD) in pigeonpea, sequencing‐based bulked segregant analysis (Seq‐BSA) was used. Resistant (R) and susceptible (S) bulks from the extreme recombinant inbred lines of ICPL 20096 × ICPL 332 were sequenced. Subsequently, SNP index was calculated between R‐ and S‐bulks with the help of draft genome sequence and reference‐guided assembly of ICPL 20096 (resistant parent). Seq‐BSA has provided seven candidate SNPs for FW and SMD resistance in pigeonpea. In parallel, four additional genotypes were re‐sequenced and their combined analysis with R‐ and S‐bulks has provided a total of 8362 nonsynonymous (ns) SNPs. Of 8362 nsSNPs, 60 were found within the 2‐Mb flanking regions of seven candidate SNPs identified through Seq‐BSA. Haplotype analysis narrowed down to eight nsSNPs in seven genes. These eight nsSNPs were further validated by re‐sequencing 11 genotypes that are resistant and susceptible to FW and SMD. This analysis revealed association of four candidate nsSNPs in four genes with FW resistance and four candidate nsSNPs in three genes with SMD resistance. Further, In silico protein analysis and expression profiling identified two most promising candidate genes namely C.cajan_01839 for SMD resistance and C.cajan_03203 for FW resistance. Identified candidate genomic regions/SNPs will be useful for genomics‐assisted breeding in pigeonpea.

Genome-wide identification and characterization of microRNA genes and their targets in flax (Linum usitatissimum)

MicroRNAs (miRNAs) are small (20–24 nucleotide long) endogenous regulatory RNAs that play important roles in plant growth and development. They regulate gene expression at the post-transcriptional level by translational repression or target degradation and gene silencing. In this study, we identified 116 conserved miRNAs belonging to 23 families from the flax (Linum usitatissimum L.) genome using a computational approach. The precursor miRNAs varied in length; while most of the mature miRNAs were 21 nucleotide long, intergenic and showed conserved signatures of RNA polymerase II transcripts in their upstream regions. Promoter region analysis of the flax miRNA genes indicated prevalence of MYB transcription factor binding sites. Four miRNA gene clusters containing members of three phylogenetic groups were identified. Further, 142 target genes were predicted for these miRNAs and most of these represent transcriptional regulators. The miRNA encoding genes were expressed in diverse tissues as determined by digital expression analysis as well as real-time PCR. The expression of fourteen miRNAs and nine target genes was independently validated using the quantitative reverse transcription PCR (qRT-PCR). This study suggests that a large number of conserved plant miRNAs are also found in flax and these may play important roles in growth and development of flax.

Development of genomic simple sequence repeat markers for linseed using next generation sequencing technology

Linseed (Linum usitatissimum L.) is regarded as a cash crop of tomorrow because of the presence of nutraceutically important α-linolenic acid (ALA) and lignan. However, only limited breeding progress has been made in this crop, mainly due to the lack of sufficient genetic and genomic resources. Among these, simple sequence repeats (SSR) are useful DNA markers for diversity analysis, genetic mapping and tagging traits because of their co-dominant and highly polymorphic nature. In order to develop SSR markers for linseed, we used three microsatellite isolation methods, viz., PCR Isolation of Microsatellite Arrays (PIMA), 5′-anchored PCR method, and Fast Isolation by AFLP of Sequences COntaining repeats (FIASCO). The amplified products from these methods were pooled and sequenced using the 454 GS-FLX platform. A total of 36,332 reads were obtained, which assembled into 2,183 contigs and 2,509 singlets. The contigs and the singlets contained 1,842 microsatellite motifs, with dinucleotide motifs as the most abundant repeat type (54%) followed by trinucleotide motifs (44%). Based on this, 290 SSR markers were designed, 52 of which were evaluated using a panel of 27 diverse linseed genotypes. Among the three enrichment methods, the 5′-anchored PCR method was most efficient for isolation of microsatellites, while FIASCO was most efficient for developing SSR markers. We show the utility of next-generation sequencing technology for efficiently discovering a large number of microsatellite markers in non-model plants.

Proteome profiling of flax (linum usitatissimum) seed: characterization of functional metabolic pathways operating during seed development

Flax (Linum usitatissimum L.) seeds are an important source of food and feed due to the presence of various health promoting compounds, making it a nutritionally and economically important plant. An in-depth analysis of the proteome of developing flax seed is expected to provide significant information with respect to the regulation and accumulation of such storage compounds. Therefore, a proteomic analysis of seven seed developmental stages (4, 8, 12, 16, 22, 30, and 48 days after anthesis) in a flax variety, NL-97 was carried out using a combination of 1D-SDS-PAGE and LC-MSE methods. A total 1716 proteins were identified and their functional annotation revealed that a majority of them were involved in primary metabolism, protein destination, storage and energy. Three carbon assimilatory pathways appeared to operate in flax seeds. Reverse transcription quantitative PCR of selected 19 genes was carried out to understand their roles during seed development. Besides storage proteins, methionine synthase, RuBisCO and S-adenosylmethionine synthetase were highly expressed transcripts, highlighting their importance in flax seed development. Further, the identified proteins were mapped onto developmental seed specific expressed sequence tag (EST) libraries of flax to obtain transcriptional evidence and 81% of them had detectable expression at the mRNA level. This study provides new insights into the complex seed developmental processes operating in flax.

Construction of genotyping-by-sequencing based high-density genetic maps and QTL mapping for fusarium wilt resistance in pigeonpea

Fusarium wilt (FW) is one of the most important biotic stresses causing yield losses in pigeonpea. Genetic improvement of pigeonpea through genomics-assisted breeding (GAB) is an economically feasible option for the development of high yielding FW resistant genotypes. In this context, two recombinant inbred lines (RILs) (ICPB 2049 × ICPL 99050 designated as PRIL_A and ICPL 20096 × ICPL 332 designated as PRIL_B) and one F2 (ICPL 85063 × ICPL 87119) populations were used for the development of high density genetic maps. Genotyping-by-sequencing (GBS) approach was used to identify and genotype SNPs in three mapping populations. As a result, three high density genetic maps with 964, 1101 and 557 SNPs with an average marker distance of 1.16, 0.84 and 2.60 cM were developed in PRIL_A, PRIL_B and F2, respectively. Based on the multi-location and multi-year phenotypic data of FW resistance a total of 14 quantitative trait loci (QTLs) including six major QTLs explaining >10% phenotypic variance explained (PVE) were identified. Comparative analysis across the populations has revealed three important QTLs (qFW11.1, qFW11.2 and qFW11.3) with upto 56.45% PVE for FW resistance. This is the first report of QTL mapping for FW resistance in pigeonpea and identified genomic region could be utilized in GAB.

Mapping Quantitative Trait Loci of Resistance to Tomato Spotted Wilt Virus and Leaf Spots in a Recombinant Inbred Line Population of Peanut (Arachis hypogaea L.) from SunOleic 97R and NC94022

Peanut is vulnerable to a range of diseases, such as Tomato spotted wilt virus (TSWV) and leaf spots which will cause significant yield loss. The most sustainable, economical and eco-friendly solution for managing peanut diseases is development of improved cultivars with high level of resistance. We developed a recombinant inbred line population from the cross between SunOleic 97R and NC94022, named as the S-population. An improved genetic linkage map was developed for the S-population with 248 marker loci and a marker density of 5.7 cM/loci. This genetic map was also compared with the physical map of diploid progenitors of tetraploid peanut, resulting in an overall co-linearity of about 60% with the average co-linearity of 68% for the A sub-genome and 47% for the B sub-genome. The analysis using the improved genetic map and multi-season (2010–2013) phenotypic data resulted in the identification of 48 quantitative trait loci (QTLs) with phenotypic variance explained (PVE) from 3.88 to 29.14%. Of the 48 QTLs, six QTLs were identified for resistance to TSWV, 22 QTLs for early leaf spot (ELS) and 20 QTLs for late leaf spot (LLS), which included four, six, and six major QTLs (PVE larger than 10%) for each disease, respectively. A total of six major genomic regions (MGR) were found to have QTLs controlling more than one disease resistance. The identified QTLs and resistance gene-rich MGRs will facilitate further discovery of resistance genes and development of molecular markers for these important diseases.

Development and evaluation of high‐density Axiom®CicerSNP Array for high‐resolution genetic mapping and breeding applications in chickpea

Summary To accelerate genomics research and molecular breeding applications in chickpea, a high‐throughput SNP genotyping platform ‘Axiom® CicerSNP Array’ has been designed, developed and validated. Screening of whole‐genome resequencing data from 429 chickpea lines identified 4.9 million SNPs, from which a subset of 70 463 high‐quality nonredundant SNPs was selected using different stringent filter criteria. This was further narrowed down to 61 174 SNPs based on p‐convert score ≥0.3, of which 50 590 SNPs could be tiled on array. Among these tiled SNPs, a total of 11 245 SNPs (22.23%) were from the coding regions of 3673 different genes. The developed Axiom® CicerSNP Array was used for genotyping two recombinant inbred line populations, namely ICCRIL03 (ICC 4958 × ICC 1882) and ICCRIL04 (ICC 283 × ICC 8261). Genotyping data reflected high success and polymorphic rate, with 15 140 (29.93%; ICCRIL03) and 20 018 (39.57%; ICCRIL04) polymorphic SNPs. High‐density genetic maps comprising 13 679 SNPs spanning 1033.67 cM and 7769 SNPs spanning 1076.35 cM were developed for ICCRIL03 and ICCRIL04 populations, respectively. QTL analysis using multilocation, multiseason phenotyping data on these RILs identified 70 (ICCRIL03) and 120 (ICCRIL04) main‐effect QTLs on genetic map. Higher precision and potential of this array is expected to advance chickpea genetics and breeding applications.