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Seed composition is a major factor that influences grain utilization and end-use. To improve chickpea (Cicer arietinum L.) seed quality, it is imperative to identify novel genetic resources with desired seed composition for use in breeding programs. The specific objectives of the study were: 1) to characterize natural variation for selected chickpea seed composition traits; and 2) to identify the chickpea genomic regions associated with variations in seed constituent traits. The study is based on the hypothesis that natural variation exists for chickpea seed composition and it is associated with specific genomic regions. Seed composition characters such as one thousand seed weight (TSW), protein, starch and amylose concentrations were analyzed in three distinct chickpea germplasm collections grown in multiple environments. The study utilized three distinct germplasm collections: (i) a reference (237 genotypes); (ii) composite (168 genotypes) and (iii) a recombinant inbred lines (RIL, 224 genotypes) grown in multiple environments. All the three chickpea germplasm collections showed variability in seed composition traits. The multiple environment testing also revealed strong effects of genotype by environment interaction on the selected quality traits showing a high broad sense heritability for TSW (0.65 – 0.87) and medium to low heritability for total starch (0.13 – 0.48), protein (0.16 – 0.57) and amylose (0.11 – 0.17). The negative correlation of TSW and total starch with amylose and protein complicates the direct selection for a trait of interest. Therefore, a compromise needs to be made to select genotypes that exhibit a relatively balanced seed composition. Three desi (ICC 16903, ICC 4958 and ICC 93954), two kabuli (ICC 7255 and ICC 8261), and one pea-shaped accession (ICC 8350) were identified that showed desired seed composition and consistent performance across the environments. The composite collection was genotyped by the Diversity Array Technology (DArT) and the RIL population was genotyped by genotyping by sequencing (GBS) to identify genomic regions associated with seed composition traits. The association mapping study with the composite germplasm collection using 380 DArT markers identified two sub-populations that were also confirmed by Principal Coordinate Analysis (PCoA). The mixed linear model identified 33 marker-trait associations for all the traits in both desi and kabuli accessions, explaining 4.2 – 10.3 % variance for TSW, 3.7 – 16.1 % for total starch, 5.1 – 9.0 % for protein, and 4.1 – 11.0 % for amylose, respectively. The bi-parental RIL mapping population analyzed by GBS identified 415 single nucleotide polymorphisms (SNP) that identified eight linkage groups. Six quantitative trait loci (QTLs) for TSW explained 2.5 – 24.6 % of total variance, four QTLs explained 2.5 – 19.4 % of phenotypic variance for protein and one QTL for total starch and amylose explained 18.6 % and 8.3 % of phenotypic variance, respectively. QTL robustness was low for amylose. Epistatic effects were low and did not affect the common QTLs. Within the identified QTLs, seven putative genes were associated with the phenotypic variation observed in the RILs. These 33 marker-trait associations (MTAs) and putative genes need to be further studied to develop molecular markers that can be utilized in marker assisted selection (MAS) to accelerate the development of chickpea genotypes with desired seed composition. The results support the hypothesis that chickpea germplasm varies for chickpea seed composition and it is associated with specific regions of chickpea genome.



Chickpea, seed constituent traits, genotype x environment interaction, marker-trait associations, QTLs, candidate genes



Doctor of Philosophy (Ph.D.)


Plant Sciences


Plant Science



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