C. Bharadwaj

Genomics-assisted breeding for drought tolerance in chickpea

Terminal drought is one of the major constraints in chickpea (Cicer arietinum L.), causing more than 50% production losses. With the objective of accelerating genetic understanding and crop improvement through genomics-assisted breeding, a draft genome sequence has been assembled for the CDC Frontier variety. In this context, 544.73Mb of sequence data were assembled, capturing of 73.8% of the genome in scaffolds. In addition, large-scale genomic resources including several thousand simple sequence repeats and several million single nucleotide polymorphisms, high-density diversity array technology (15360 clones) and Illumina GoldenGate assay genotyping platforms, high-density genetic maps and transcriptome assemblies have been developed. In parallel, by using linkage mapping approach, one genomic region harbouring quantitative trait loci for several drought tolerance traits has been identified and successfully introgressed in three leading chickpea varieties (e.g. JG 11, Chefe, KAK 2) by using a marker-assisted backcrossing approach. A multilocation evaluation of these marker-assisted backcrossing lines provided several lines with 10-24% higher yield than the respective recurrent parents.Modern breeding approaches like marker-assisted recurrent selection and genomic selection are being deployed for enhancing drought tolerance in chickpea. Some novel mapping populations such as multiparent advanced generation intercross and nested association mapping populations are also being developed for trait mapping at higher resolution, as well as for enhancing the genetic base of chickpea. Such advances in genomics and genomics-assisted breeding will accelerate precision and efficiency in breeding for stress tolerance in chickpea.

High-density linkage map construction and mapping of seed trait QTLs in chickpea (Cicer arietinum L.) using Genotyping-by-Sequencing (GBS).

This study reports the use of Genotyping-by-Sequencing (GBS) for large-scale SNP discovery and simultaneous genotyping of recombinant inbred lines (RILs) of an intra-specific mapping population of chickpea contrasting for seed traits. A total of 119,672 raw SNPs were discovered, which after stringent filtering revealed 3,977 high quality SNPs of which 39.5% were present in genic regions. Comparative analysis using physically mapped marker loci revealed a higher degree of synteny with Medicago in comparison to soybean. The SNP genotyping data was utilized to construct one of the most saturated intra-specific genetic linkage maps of chickpea having 3,363 mapped positions including 3,228 SNPs on 8 linkage groups spanning 1006.98 cM at an average inter marker distance of 0.33 cM. The map was utilized to identify 20 quantitative trait loci (QTLs) associated with seed traits accounting for phenotypic variations ranging from 9.97% to 29.71%. Analysis of the genomic sequence corresponding to five robust QTLs led to the identification of 684 putative candidate genes whose expression profiling revealed that 101 genes exhibited seed specific expression. The integrated approach utilizing the identified QTLs along with the available genome and transcriptome could serve as a platform for candidate gene identification for molecular breeding of chickpea.

Molecular diversity and phylogeny in geographical collection of chickpea (Cicer sp.) accessions.

Chickpea (Cicer arietinum L.) is the third most important pulse crop in the world and India is the largest producer of this crop. Nevertheless, its yield in India is low (0.7 tone per hectare (t/ha)) as compared to Australia, Egypt, Israel and Italy (1 t/ha) (FAOSTAT 2008, http://faostat.fao.org/). There has been a significant change in the scenario of chickpea cultivation in India during the past three decades. The expansion of irrigated agriculture in northern India has led to displacement of chickpea with wheat in large area. As a result, the area under chickpea reduced from 3.2 million ha to 1.0 million ha in northern and northwestern India (Punjab, Haryana and Uttar Pradesh), while it increased from 2.6 million ha to 4.3 million ha in central and southern India (Madhya Pradesh, Maharashtra, Andhra Pradesh and Karnataka) from 1985 to 1990. Because of relatively warm environments in central and southern India, the crop is challenged by Fusarium wilt, a major yield reducing disease, while in northwestern India, due to cooler environments, the crop is exposed to a severe foliar disease Ascochyta blight. The narrow genetic base among cultivated chickpea accessions is limiting genetic improvement of chickpea through breeding efforts. Understanding the extent of natural variation among cultivated chickpea and wild accessions at molecular level is essential to develop prebreeding and breeding strategies for chickpea. Until recently, the low intraspecific and inter-specific polymorphism in chickpea accessions detected by molecular markers and the scarcity of codominant DNA-based markers were serious constraints that hindered the preparation of dense molecular genetic maps or tagging of important traits in chickpea. However, recent studies using STMS markers reveal fairly high levels of

EcoTILLING-Based Association Mapping Efficiently Delineates Functionally Relevant Natural Allelic Variants of Candidate Genes Governing Agronomic Traits in Chickpea

The large-scale mining and high-throughput genotyping of novel gene-based allelic variants in natural mapping population are essential for association mapping to identify functionally relevant molecular tags governing useful agronomic traits in chickpea. The present study employs an alternative time-saving, non-laborious and economical pool-based EcoTILLING approach coupled with agarose gel detection assay to discover 1133 novel SNP allelic variants from diverse coding and regulatory sequence components of 1133 transcription factor (TF) genes by genotyping in 192 diverse desi and kabuli chickpea accessions constituting a seed weight association panel. Integrating these SNP genotyping data with seed weight field phenotypic information of 192 structured association panel identified eight SNP alleles in the eight TF genes regulating seed weight of chickpea. The associated individual and combination of all SNPs explained 10–15 and 31% phenotypic variation for seed weight, respectively. The EcoTILLING-based large-scale allele mining and genotyping strategy implemented for association mapping is found much effective for a diploid genome crop species like chickpea with narrow genetic base and low genetic polymorphism. This optimized approach thus can be deployed for various genomics-assisted breeding applications with optimal expense of resources in domesticated chickpea. The seed weight-associated natural allelic variants and candidate TF genes delineated have potential to accelerate marker-assisted genetic improvement of chickpea.

Deciphering Genomic Regions for High Grain Iron and Zinc Content Using Association Mapping in Pearl Millet

Micronutrient malnutrition, especially deficiency of two mineral elements, iron [Fe] and zinc [Zn] in the developing world needs urgent attention. Pearl millet is one of the best crops with many nutritional properties and is accessible to the poor. We report findings of the first attempt to mine favorable alleles for grain iron and zinc content through association mapping in pearl millet. An association mapping panel of 130 diverse lines was evaluated at Delhi, Jodhpur and Dharwad, representing all the three pearl millet growing agro-climatic zones of India, during 2014 and 2015. Wide range of variation was observed for grain iron (32.3–111.9 ppm) and zinc (26.6–73.7 ppm) content. Genotyping with 114 representative polymorphic SSRs revealed 0.35 mean gene diversity. STRUCTURE analysis revealed presence of three sub-populations which was further supported by Neighbor-Joining method of clustering and principal coordinate analysis (PCoA). Marker-trait associations (MTAs) were analyzed with 267 markers (250 SSRs and 17 genic markers) in both general linear model (GLM) and mixed linear model (MLM), however, MTAs resulting from MLM were considered for more robustness of the associations. After appropriate Bonferroni correction, Xpsmp 2261 (13.34% R2-value), Xipes 0180 (R2-value of 11.40%) and Xipes 0096 (R2-value of 11.38%) were consistently associated with grain iron and zinc content for all the three locations. Favorable alleles and promising lines were identified for across and specific environments. PPMI 1102 had highest number (7) of favorable alleles, followed by four each for PPMFeZMP 199 and PPMI 708 for across the environment performance for both grain Fe and Zn content, while PPMI 1104 had alleles specific to Dharwad for grain Fe and Zn content. When compared with the reference genome Tift 23D2B1-P1-P5, Xpsmp 2261 amplicon was identified in intergenic region on pseudomolecule 5, while the other marker, Xipes 0810 was observed to be overlapping with aspartic proteinase (Asp) gene on pseudomolecule 3. Thus, this study can help in breeding new lines with enhanced micronutrient content using marker-assisted selection (MAS) in pearl millet leading to improved well-being especially for women and children.

A Multiple QTL-Seq Strategy Delineates Potential Genomic Loci Governing Flowering Time in Chickpea

Identification of functionally relevant potential genomic loci using an economical, simpler and user-friendly genomics-assisted breeding strategy is vital for rapid genetic dissection of complex flowering time quantitative trait in chickpea. A high-throughput multiple QTL-seq strategy was employed in two inter (Cicer arietinum desi accession ICC 4958 × C reticulatum wild accession ICC 17160)- and intra (ICC 4958 × C. arietinum kabuli accession ICC 8261)-specific RIL mapping populations to identify the major QTL genomic regions governing flowering time in chickpea. The whole genome resequencing discovered 1635117 and 592486 SNPs exhibiting differentiation between early- and late-flowering mapping parents and bulks, constituted by pooling the homozygous individuals of extreme flowering time phenotypic trait from each of two aforesaid RIL populations. The multiple QTL-seq analysis using these mined SNPs in two RIL mapping populations narrowed-down two longer (907.1 kb and 1.99 Mb) major flowering time QTL genomic regions into the high-resolution shorter (757.7 kb and 1.39 Mb) QTL intervals on chickpea chromosome 4. This essentially identified regulatory as well as coding (non-synonymous/synonymous) novel SNP allelic variants from two efl1 (early flowering 1) and GI (GIGANTEA) genes regulating flowering time in chickpea. Interestingly, strong natural allelic diversity reduction (88–91%) of two known flowering genes especially mapped at major QTL intervals as compared to that of background genomic regions (where no flowering time QTLs were mapped; 61.8%) in cultivated vis-à-vis wild Cicer gene pools was evident inferring the significant impact of evolutionary bottlenecks on these loci during chickpea domestication. Higher association potential of coding non-synonymous and regulatory SNP alleles mined from efl1 (36–49%) and GI (33–42%) flowering genes for early and late flowering time differentiation among chickpea accessions was evident. The robustness and validity of two functional allelic variants-containing genes localized at major flowering time QTLs was apparent by their identification from multiple intra-/inter-specific mapping populations of chickpea. The functionally relevant molecular tags delineated can be of immense use for deciphering the natural allelic diversity-based domestication pattern of flowering time and expediting genomics-aided crop improvement to develop early flowering cultivars of chickpea.

Genetic dissection of plant growth habit in chickpea

A combinatorial genomics-assisted breeding strategy encompassing association analysis, genetic mapping and expression profiling is found most promising for quantitative dissection of complex traits in crop plants. The present study employed GWAS (genome-wide association study) using 24,405 SNPs (single nucleotide polymorphisms) obtained with genotyping-by-sequencing (GBS) of 92 sequenced desi and kabuli accessions of chickpea. This identified eight significant genomic loci associated with erect (E)/semi-erect (SE) vs. spreading (S)/semi-spreading (SS)/prostrate (P) plant growth habit (PGH) trait differentiation regardless of diverse desi and kabuli genetic backgrounds of chickpea. These associated SNPs in combination explained 23.8% phenotypic variation for PGH in chickpea. Five PGH-associated genes were validated successfully in E/SE and SS/S/P PGH-bearing parental accessions and homozygous individuals of three intra- and interspecific RIL (recombinant inbred line) mapping populations as well as 12 contrasting desi and kabuli chickpea germplasm accessions by selective genotyping through Sequenom MassARRAY. The shoot apical, inflorescence and floral meristems-specific expression, including upregulation (seven-fold) of five PGH-associated genes especially in germplasm accessions and homozygous RIL mapping individuals contrasting with E/SE PGH traits was apparent. Collectively, this integrated genomic strategy delineated diverse non-synonymous SNPs from five candidate genes with strong allelic effects on PGH trait variation in chickpea. Of these, two vernalization-responsive non-synonymous SNP alleles carrying SNF2 protein-coding gene and B3 transcription factor associated with PGH traits were found to be the most promising in chickpea. The SNP allelic variants associated with E/SE/SS/S PGH trait differentiation were exclusively present in all cultivated desi and kabuli chickpea accessions while wild species/accessions belonging to primary, secondary and tertiary gene pools mostly contained prostrate PGH-associated SNP alleles. This indicates strong adaptive natural/artificial selection pressure (Tajima’s D 3.15 to 4.57) on PGH-associated target genomic loci during chickpea domestication. These vital leads thus have potential to decipher complex transcriptional regulatory gene function of PGH trait differentiation and for understanding the selective sweep-based PGH trait evolution and domestication pattern in cultivated and wild chickpea accessions adapted to diverse agroclimatic conditions. Collectively, the essential inputs generated will be of profound use in marker-assisted genetic enhancement to develop cultivars with desirable plant architecture of erect growth habit types in chickpea.

Molecular and phenotypic diversity among chickpea (Cicer arietinum) genotypes as a function of drought tolerance

Abstract. Diversity as a function of drought tolerance may be identified by morphological characters, and molecular tools used to find the most divergent genotypes for breeding programs for drought tolerance in future. The narrow genetic base of chickpea can be circumvented by using diverse lines in breeding programs. Forty chickpea genotypes were studied for their morphological and molecular diversity with an objective of identifying the most diverse drought-tolerant lines. In total, 90 alleles were detected with 3.6 alleles per locus. Polymorphism information content (PIC) values ranged from 0.155 to 0.782 with an average value of 0.4374 per locus. The size of amplified products ranged from 160 bp to 390 bp. Primer TA136 with eight alleles showed the highest PIC value of 0.7825, indicating its ability to differentiate the genotypes at molecular level. DARwin neighbour-joining tree analysis based on dissimilarity estimates was done for the molecular data and sequential agglomerative hierarchical non-overlapping (SAHN) grouping for the morphological data. It could clearly discriminate the tolerance and the sensitivity of genotypes. Two-dimensional principal coordinates analysis (PCoA) plot indicated good diversity for drought tolerance. The genetic similarity coefficients ranged from 0.115 (genotypes BGD72 to ICCV 5308) to 0.828 (genotypes ICCV 10316 to ICCV 92337).

Identifying Transcription Factor Genes Associated with Yield Traits in Chickpea

Identification of potential transcription factor (TF) gene-derived natural SNP allelic variants regulating pod and seed yield component traits by large-scale mining and genotyping of SNPs in natural germplasm accessions coupled with high-resolution association mapping is vital for understanding the complex genetic architecture of quantitative yield traits in chickpea. In these perspectives, the current study employed a genome-wide GBS (genotyping-by-sequencing) and targeted gene amplicon resequencing-based simultaneous SNP discovery and genotyping assays, which discovered 1611 novel SNPs from 736 TF genes physically mapped on eight chromosomes and unanchored scaffolds of kabuli chickpea genome. These SNPs were structurally and functionally annotated in diverse synonymous and non-synonymous coding as well as non-coding regulatory and intronic sequence components of chickpea TF genes. A high-resolution genetic association analysis was performed by correlating the genotyping information of 1611 TF gene-based SNPs with multi-location/years field phenotyping data of six major pod and seed yield traits evaluated in a constituted association panel (326 desi and kabuli germplasm accessions) of chickpea. This essentially identified 27 TF gene-derived SNPs exhibiting significant association with six major yield traits, namely days to 50% flowering (DF), plant height (PH), branch number (BN), pod number (PN), seed number (SN) and seed weight (SW) in chickpea. These trait-associated SNPs individually and in combination explained 10–23% and 32% phenotypic variation respectively for the studied yield component traits. Interestingly, novel non-synonymous coding SNP allelic variants in five potential candidate TF genes encoding SBP (squamosal promoter binding protein), SNF2 (sucrose non-fermenting 2), GRAS [Gibberellic acid insensitive (GAI)-Repressor of GAI (RGA)-SCARECROW (SCR)], bZIP (basic leucine zipper) and LOB (lateral organ boundaries)-domain proteins associated strongly with DF, PH, BN, PN, SN and SW traits respectively were found most promising in chickpea. The functionally relevant molecular signatures (TFs and natural SNP alleles) delineated by us have potential to accelerate marker-assisted genetic enhancement by developing high pod and seed yielding cultivars of chickpea.

Tolerance to post-emergence herbicide Imazethapyr in chickpea

The present research work aimed at identification of sources of tolerance to herbicide Imazethapyr for their possible utilization in development of herbicide tolerant chickpea. Sixty five genotypes (55 desi and 10 kabuli) screened included accessions from ICRISAT core collection, advanced breeding lines and cultivars. The herbicide tolerance score ranged from 1.9 to 5.0. Nine tolerant to moderately tolerant and three susceptible genotypes were further evaluated under control and sprayed condition. Genotype x environment interactions were observed for days to 50% flowering, NDVI, days to maturity, seed yield, biomass, harvest index, 100-seed weight and branched chain amino acids (BCAA) viz., valine, leucine and isoleucine content. Highly significant reduction in seed yield was observed in all the genotypes except ICCV 10, ICCL 82104 and ICC 1710 as revealed by pairwise comparison of means using Tukeys test. The spraying of herbicide reduced the total biomass production. Analysis of BCAA content in sample revealed non-significant differences for percent valine content in ICCIL 04001, ICCV 00305, ICCV 96003 and ICCL 82104, for isoleucine content in all the genotypes except, ICCV 3 and ICCV 96003 and for leucine content in case of ICCV 03407, ICCIL 04001, ICCV 10, ICCV 96003, ICC 1710, ICCV 00108 and ICCL 82104. The genotypes tolerant to post-emergence herbicide Imazethapyr identified based on non-significant reduction in the yield attributes and BCAA content in the sample were ICC 82104, ICCV 10, ICCV 96003, ICC 00305 and ICC 1710. These genotypes can be used to study the genetics of herbicide tolerance in chickpea and in breeding programs for developing lines with tolerance to post-emergence herbicide Imazethapyr.