Vikas K. Singh

A draft genome sequence of the pulse crop chickpea (Cicer arietinum L.).

Cicer arietinum L. (chickpea) is the third most important food legume crop. We have generated the draft sequence of a desi-type chickpea genome using next-generation sequencing platforms, bacterial artificial chromosome end sequences and a genetic map. The 520-Mb assembly covers 70% of the predicted 740-Mb genome length, and more than 80% of the gene space. Genome analysis predicts the presence of 27,571 genes and 210 Mb as repeat elements. The gene expression analysis performed using 274 million RNA-Seq reads identified several tissue-specific and stress-responsive genes. Although segmental duplicated blocks are observed, the chickpea genome does not exhibit any indication of recent whole-genome duplication. Nucleotide diversity analysis provides an assessment of a narrow genetic base within the chickpea cultivars. We have developed a resource for genetic markers by comparing the genome sequences of one wild and three cultivated chickpea genotypes. The draft genome sequence is expected to facilitate genetic enhancement and breeding to develop improved chickpea varieties.

Marker-Assisted Backcrossing to Introgress Resistance to Fusarium Wilt Race 1 and Ascochyta Blight in C 214, an Elite Cultivar of Chickpea

Fusarium wilt (FW) and Ascochyta blight (AB) are two major constraints to chickpea (Cicer arietinum L.) production. Therefore, two parallel marker‐assisted backcrossing (MABC) programs by targeting foc1 locus and two quantitative trait loci (QTL) regions, ABQTL‐I and ABQTL‐II, were undertaken to introgress resistance to FW and AB, respectively, in C 214, an elite cultivar of chickpea. In the case of FW, foreground selection (FGS) was conducted with six markers (TR19, TA194, TAA60, GA16, TA110, and TS82) linked to foc1 in the cross C 214 × WR 315 (FW‐resistant). On the other hand, eight markers (TA194, TR58, TS82, GA16, SCY17, TA130, TA2, and GAA47) linked with ABQTL‐I and ABQTL‐II were used in the case of AB by deploying C 214 × ILC 3279 (AB‐resistant) cross. Background selection (BGS) in both crosses was employed with evenly distributed 40 (C 214 × WR 315) to 43 (C 214 × ILC 3279) SSR markers in the chickpea genome to select plant(s) with higher recurrent parent genome (RPG) recovery. By using three backcrosses and three rounds of selfing, 22 BC3F4 lines were generated for C 214 × WR 315 cross and 14 MABC lines for C 214 × ILC 3279 cross. Phenotyping of these lines has identified three resistant lines (with 92.7–95.2% RPG) to race 1 of FW, and seven resistant lines (with 81.7–85.40% RPG) to AB that may be tested for yield and other agronomic traits under multilocation trials for possible release and cultivation.

Fast-track introgression of “QTL-hotspot” for root traits and other drought tolerance traits in JG 11, an elite and leading variety of chickpea

A “QTL‐hotspot” containing quantitative trait loci (QTL) for several root and drought tolerance traits was transferred through marker‐assisted backcrossing into JG 11, a leading variety of chickpea (Cicer arietinum L.) in India from the donor parent ICC 4958. Foreground selection with up to three simple sequence repeat markers, namely TAA170, ICCM0249, and STMS11, and background selection with up to 10 amplified fragment length polymorphism primer combinations was undertaken. After undertaking three backcrosses with foreground and background selection and selfing, 29 BC3F2 plants homozygous for two markers (ICCM0249 and TAA170) were selected and referred as introgression lines (ILs). Root trait phenotyping of these ILs showed higher rooting depth (RDp) (average 115.21 ± 2.24 cm) in all 29 ILs, better root length density (RLD) (average 0.41 ± 0.02 cm cm−3) in 26 ILs, and higher root dry weight (RDW) (average 1.25 ± 0.08 g per cylinder) as compared to the recurrent parent, JG 11 (111.70 cm for RDp, 0.39 cm cm−3 for RLD, and 1.10 g per cylinder for RDW), as well as the donor parent, ICC 4958 (114.20 cm for RDp, 0.45 cm cm−3 for RLD, and 1.25 g per cylinder for RDW). These ILs, developed in 3 yr, after multilocation field trials may be released as improved variety with enhanced drought tolerance.

MAGIC populations in crops: current status and future prospects

Key messageMAGIC populations present novel challenges and opportunities in crops due to their complex pedigree structure. They offer great potential both for dissecting genomic structure and for improving breeding populations.AbstractThe past decade has seen the rise of multiparental populations as a study design offering great advantages for genetic studies in plants. The genetic diversity of multiple parents, recombined over several generations, generates a genetic resource population with large phenotypic diversity suitable for high-resolution trait mapping. While there are many variations on the general design, this review focuses on populations where the parents have all been inter-mated, typically termed Multi-parent Advanced Generation Intercrosses (MAGIC). Such populations have already been created in model animals and plants, and are emerging in many crop species. However, there has been little consideration of the full range of factors which create novel challenges for design and analysis in these populations. We will present brief descriptions of large MAGIC crop studies currently in progress to motivate discussion of population construction, efficient experimental design, and genetic analysis in these populations. In addition, we will highlight some recent achievements and discuss the opportunities and advantages to exploit the unique structure of these resources post-QTL analysis for gene discovery.

Emerging Genomic Tools for Legume Breeding: Current Status and Future Prospects

Legumes play a vital role in ensuring global nutritional food security and improving soil quality through nitrogen fixation. Accelerated higher genetic gains is required to meet the demand of ever increasing global population. In recent years, speedy developments have been witnessed in legume genomics due to advancements in next-generation sequencing (NGS) and high-throughput genotyping technologies. Reference genome sequences for many legume crops have been reported in the last 5 years. The availability of the draft genome sequences and re-sequencing of elite genotypes for several important legume crops have made it possible to identify structural variations at large scale. Availability of large-scale genomic resources and low-cost and high-throughput genotyping technologies are enhancing the efficiency and resolution of genetic mapping and marker-trait association studies. Most importantly, deployment of molecular breeding approaches has resulted in development of improved lines in some legume crops such as chickpea and groundnut. In order to support genomics-driven crop improvement at a fast pace, the deployment of breeder-friendly genomics and decision support tools seems appear to be critical in breeding programs in developing countries. This review provides an overview of emerging genomics and informatics tools/approaches that will be the key driving force for accelerating genomics-assisted breeding and ultimately ensuring nutritional and food security in developing countries.

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.

Association of nad7a Gene with Cytoplasmic Male Sterility in Pigeonpea

Cytoplasmic male sterility (CMS) has been exploited in the commercial pigeonpea [Cajanus cajan (L.) Millsp.] hybrid breeding system; however, the molecular mechanism behind this system is unknown. To understand the underlying molecular mechanism involved in A4 CMS system derived from C. cajanifolius (Haines) Maesen, 34 mitochondrial genes were analyzed for expression profiling and structural variation analysis between CMS line (ICRISAT Pigeonpea A line, ICPA 2039) and its cognate maintainer (ICPB 2039). Expression profiling of 34 mitochondrial genes revealed nine genes with significant fold differential gene expression at P ≤ 0.01, including one gene, nad4L, with 1366‐fold higher expression in CMS line as compared with the maintainer. Structural variation analysis of these mitochondrial genes identified length variation between ICPA 2039 and ICPB 2039 for nad7a (subunit of nad7 gene). Sanger sequencing of nad4L and nad7a genes in the CMS and the maintainer lines identified two single nucleotide polymorphisms (SNPs) in upstream region of nad4L and a deletion of 10 bp in nad7a in the CMS line. Protein structure evaluation showed conformational changes in predicted protein structures for nad7a between ICPA 2039 and ICPB 2039 lines. All above analyses indicate association of nad7a gene with the CMS for A4 cytoplasm in pigeonpea. Additionally, one polymerase chain reaction (PCR) based Indel marker (nad7a_del) has been developed and validated for testing genetic purity of A4 derived CMS lines to strengthen the commercial hybrid breeding program in pigeonpea.

Evaluation and Validation of Housekeeping Genes as Reference for Gene Expression Studies in Pigeonpea (Cajanus cajan) Under Drought Stress Conditions

Gene expression analysis using quantitative real-time PCR (qRT-PCR) is a very sensitive technique and its sensitivity depends on the stable performance of reference gene(s) used in the study. A number of housekeeping genes have been used in various expression studies in many crops however, their expression were found to be inconsistent under different stress conditions. As a result, species specific housekeeping genes have been recommended for different expression studies in several crop species. However, such specific housekeeping genes have not been reported in the case of pigeonpea (Cajanus cajan) despite the fact that genome sequence has become available for the crop. To identify the stable housekeeping genes in pigeonpea for expression analysis under drought stress conditions, the relative expression variations of 10 commonly used housekeeping genes (EF1α, UBQ10, GAPDH, 18SrRNA, 25SrRNA, TUB6, ACT1, IF4α, UBC and HSP90) were studied on root, stem and leaves tissues of Asha (ICPL 87119). Three statistical algorithms geNorm, NormFinder and BestKeeper were used to define the stability of candidate genes. geNorm analysis identified IF4α and TUB6 as the most stable housekeeping genes however, NormFinder analysis determined IF4α and HSP90 as the most stable housekeeping genes under drought stress conditions. Subsequently validation of the identified candidate genes was undertaken in qRT-PCR based gene expression analysis of uspA gene which plays an important role for drought stress conditions in pigeonpea. The relative quantification of the uspA gene varied according to the internal controls (stable and least stable genes), thus highlighting the importance of the choice of as well as validation of internal controls in such experiments. The identified stable and validated housekeeping genes will facilitate gene expression studies in pigeonpea especially under drought stress conditions.

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.