Vanika Garg

Gene Expression and Yeast Two-Hybrid Studies of 1R-MYB Transcription Factor Mediating Drought Stress Response in Chickpea (Cicer arietinum L.)

Drought stress has been one of the serious constraints affecting chickpea productivity to a great extent. Genomics-assisted breeding has a potential to accelerate breeding precisely and efficiently. In order to do so, understanding the molecular mechanisms for drought tolerance and identification of candidate genes are crucial. Transcription factors (TFs) have important roles in the regulation of plant stress related genes. In this context, quantitative real time-PCR (qRT-PCR) was used to study the differential gene expression of selected TFs, identified from large-scale expressed sequence tags (ESTs) analysis, in contrasting drought responsive genotypes. Root tissues of ICC 4958 (tolerant), ICC 1882 (sensitive), JG 11 (elite), and JG 11+ (introgression line) were used for the study. Subsequently, a candidate single repeat MYB (1R-MYB) transcript that was remarkably induced in the drought tolerant genotypes under drought stress was cloned (coding sequence region for the 1R-MYB protein) and subjected to yeast two-hybrid (Y2H) analysis. The screening of a root cDNA library with Y2H using the 1R-MYB bait protein, identified three CDS encoding peptides namely, galactinol-sucrose galactosyltransferase 2, CBL (Calcineurin B-like)-interacting serine/threonine-protein kinase 25, and ABA responsive 17-like, which were confirmed by co-transformation in yeast. These findings provide preliminary insights into the ability of this 1R-MYB transcription factor to co-regulate drought tolerance mechanism in chickpea.

Draft genome of the peanut A-genome progenitor (Arachis duranensis) provides insights into geocarpy, oil biosynthesis, and allergens

Significance We present a draft genome of the peanut A-genome progenitor, Arachis duranensis, providing details on total genes present in the genome. Genome analysis suggests that the peanut lineage was affected by at least three polyploidizations since the origin of eudicots. Resequencing of synthetic Arachis tetraploids reveals extensive gene conversion since their formation by human hands. The A. duranensis genome provides a major source of candidate genes for fructification, oil biosynthesis, and allergens, expanding knowledge of understudied areas of plant biology and human health impacts of plants. This study also provides millions of structural variations that can be used as genetic markers for the development of improved peanut varieties through genomics-assisted breeding. Peanut or groundnut (Arachis hypogaea L.), a legume of South American origin, has high seed oil content (45–56%) and is a staple crop in semiarid tropical and subtropical regions, partially because of drought tolerance conferred by its geocarpic reproductive strategy. We present a draft genome of the peanut A-genome progenitor, Arachis duranensis, and 50,324 protein-coding gene models. Patterns of gene duplication suggest the peanut lineage has been affected by at least three polyploidizations since the origin of eudicots. Resequencing of synthetic Arachis tetraploids reveals extensive gene conversion in only three seed-to-seed generations since their formation by human hands, indicating that this process begins virtually immediately following polyploid formation. Expansion of some specific gene families suggests roles in the unusual subterranean fructification of Arachis. For example, the S1Fa-like transcription factor family has 126 Arachis members, in contrast to no more than five members in other examined plant species, and is more highly expressed in roots and etiolated seedlings than green leaves. The A. duranensis genome provides a major source of candidate genes for fructification, oil biosynthesis, and allergens, expanding knowledge of understudied areas of plant biology and human health impacts of plants, informing peanut genetic improvement and aiding deeper sequencing of Arachis diversity.

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.

QTL-seq for rapid identification of candidate genes for 100-seed weight and root/total plant dry weight ratio under rainfed conditions in chickpea

Summary Terminal drought is a major constraint to chickpea productivity. Two component traits responsible for reduction in yield under drought stress include reduction in seeds size and root length/root density. QTL‐seq approach, therefore, was used to identify candidate genomic regions for 100‐seed weight (100SDW) and total dry root weight to total plant dry weight ratio (RTR) under rainfed conditions. Genomewide SNP profiling of extreme phenotypic bulks from the ICC 4958 × ICC 1882 population identified two significant genomic regions, one on CaLG01 (1.08 Mb) and another on CaLG04 (2.7 Mb) linkage groups for 100SDW. Similarly, one significant genomic region on CaLG04 (1.10 Mb) was identified for RTR. Comprehensive analysis revealed four and five putative candidate genes associated with 100SDW and RTR, respectively. Subsequently, two genes (Ca_04364 and Ca_04607) for 100SDW and one gene (Ca_04586) for RTR were validated using CAPS/dCAPS markers. Identified candidate genomic regions and genes may be useful for molecular breeding for chickpea improvement.

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.

QTL-seq approach identified genomic regions and diagnostic markers for rust and late leaf spot resistance in groundnut (Arachis hypogaea L.)

Summary Rust and late leaf spot (LLS) are the two major foliar fungal diseases in groundnut, and their co‐occurrence leads to significant yield loss in addition to the deterioration of fodder quality. To identify candidate genomic regions controlling resistance to rust and LLS, whole‐genome resequencing (WGRS)‐based approach referred as ‘QTL‐seq’ was deployed. A total of 231.67 Gb raw and 192.10 Gb of clean sequence data were generated through WGRS of resistant parent and the resistant and susceptible bulks for rust and LLS. Sequence analysis of bulks for rust and LLS with reference‐guided resistant parent assembly identified 3136 single‐nucleotide polymorphisms (SNPs) for rust and 66 SNPs for LLS with the read depth of ≥7 in the identified genomic region on pseudomolecule A03. Detailed analysis identified 30 nonsynonymous SNPs affecting 25 candidate genes for rust resistance, while 14 intronic and three synonymous SNPs affecting nine candidate genes for LLS resistance. Subsequently, allele‐specific diagnostic markers were identified for three SNPs for rust resistance and one SNP for LLS resistance. Genotyping of one RIL population (TAG 24 × GPBD 4) with these four diagnostic markers revealed higher phenotypic variation for these two diseases. These results suggest usefulness of QTL‐seq approach in precise and rapid identification of candidate genomic regions and development of diagnostic markers for breeding applications.

Pearl millet genome sequence provides a resource to improve agronomic traits in arid environments

Pearl millet [Cenchrus americanus (L.) Morrone] is a staple food for more than 90 million farmers in arid and semi-arid regions of sub-Saharan Africa, India and South Asia. We report the ∼1.79 Gb draft whole genome sequence of reference genotype Tift 23D2B1-P1-P5, which contains an estimated 38,579 genes. We highlight the substantial enrichment for wax biosynthesis genes, which may contribute to heat and drought tolerance in this crop. We resequenced and analyzed 994 pearl millet lines, enabling insights into population structure, genetic diversity and domestication. We use these resequencing data to establish marker trait associations for genomic selection, to define heterotic pools, and to predict hybrid performance. We believe that these resources should empower researchers and breeders to improve this important staple crop.

Genome-wide dissection of AP2/ERF and HSP90 gene families in five legumes and expression profiles in chickpea and pigeonpea

Summary APETALA2/ethylene response factor (AP2/ERF) and heat‐shock protein 90 (HSP90) are two significant classes of transcription factor and molecular chaperone proteins which are known to be implicated under abiotic and biotic stresses. Comprehensive survey identified a total of 147 AP2/ERF genes in chickpea, 176 in pigeonpea, 131 in Medicago, 179 in common bean and 140 in Lotus, whereas the number of HSP90 genes ranged from 5 to 7 in five legumes. Sequence alignment and phylogenetic analyses distinguished AP2, ERF, DREB, RAV and soloist proteins, while HSP90 proteins segregated on the basis of their cellular localization. Deeper insights into the gene structure allowed ERF proteins to be classified into AP2s based on DNA‐binding domains, intron arrangements and phylogenetic grouping. RNA‐seq and quantitative real‐time PCR (qRT‐PCR) analyses in heat‐stressed chickpea as well as Fusarium wilt (FW)‐ and sterility mosaic disease (SMD)‐stressed pigeonpea provided insights into the modus operandi of AP2/ERF and HSP90 genes. This study identified potential candidate genes in response to heat stress in chickpea while for FW and SMD stresses in pigeonpea. For instance, two DREB genes (Ca_02170 and Ca_16631) and three HSP90 genes (Ca_23016, Ca_09743 and Ca_25602) in chickpea can be targeted as potential candidate genes. Similarly, in pigeonpea, a HSP90 gene, C.cajan_27949, was highly responsive to SMD in the resistant genotype ICPL 20096, can be recommended for further functional validation. Also, two DREB genes, C.cajan_41905 and C.cajan_41951, were identified as leads for further investigation in response to FW stress in pigeonpea.

First-generation HapMap in Cajanus spp. reveals untapped variations in parental lines of mapping populations

Summary Whole genome re‐sequencing (WGRS) was conducted on a panel of 20 Cajanus spp. accessions (crossing parentals of recombinant inbred lines, introgression lines, multiparent advanced generation intercross and nested association mapping population) comprising of two wild species and 18 cultivated species accessions. A total of 791.77 million paired‐end reads were generated with an effective mapping depth of ~12X per accession. Analysis of WGRS data provided 5 465 676 genome‐wide variations including 4 686 422 SNPs and 779 254 InDels across the accessions. Large structural variations in the form of copy number variations (2598) and presence and absence variations (970) were also identified. Additionally, 2 630 904 accession‐specific variations comprising of 2 278 571 SNPs (86.6%), 166 243 deletions (6.3%) and 186 090 insertions (7.1%) were also reported. Identified polymorphic sites in this study provide the first‐generation HapMap in Cajanus spp. which will be useful in mapping the genomic regions responsible for important traits.

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.