Recent breeding programs enhanced genetic diversity in both desi and kabuli varieties of chickpea (Cicer arietinum L.)

Abstract

In order to understand the impact of breeding on genetic diversity and gain insights into temporal trends in diversity in chickpea, a set of 100 chickpea varieties released in 14 countries between 1948 and 2012 were re-sequenced. For analysis, the re-sequencing data for 29 varieties available from an earlier study was also included. Copy number variations and presence absence variations identified in the present study have potential to drive phenotypic variations for trait improvement. Re-sequencing of a large number of varieties has provided opportunities to inspect the genetic and genomic changes reflecting the history of breeding, which we consider as breeding signatures and the selected loci may provide targets for crop improvement. Our study also reports enhanced diversity in both desi and kabuli varieties as a result of recent chickpea breeding efforts. The current study will aid the explicit efforts to breed for local adaptation in the context of anticipated climate changes.

Accelerating genetic gains in legumes for the development of prosperous smallholder agriculture: integrating genomics, phenotyping, systems modelling and agronomy

“…In addition, genome-wide single nucleotide polymorphisms (SNPs) were also used to identify significant marker trait associations for economically important traits (Zhou et al, 2015a;Varshney et al, 2017). Resequencing germplasm lines also enabled us to understand the spatial and temporal trends in diversity in released varieties of chickpea (Thudi et al, 2016a), cultivated and wild accessions of soybean (Lam et al, 2010;Zhou et al, 2015a), and a reference set of pigeonpea Table 1). Resequencing of 28 Brazilian soybean cultivars suggested that, despite the diversification of modern Brazilian cultivars, the soybean germplasm remains very narrow because of the large number of genome regions that exhibit low diversity (Maldonado dos Santos et al, 2016).…”

“…BeadChip (Akond et al, 2013) • SoySNP50K array (Song et al, 2013) • 384 SNP GoldenGate assay (Hyten et al, 2008 (Varshney et al, 2012a) • 292 lines • 20 (crossing parentals of recombinant inbred lines, introgression lines, MAGIC and NAM population; Kumar et al, 2016) • 60K Axiom®Cajanus SNP array (Saxena et al, 2017 and unpublished) (Gupta et al, 2017) • 35 (parental genotypes of mapping populations; Thudi et al, 2016a) • 129 released varieties (Thudi et al, 2016b) • 300 lines (ICRISAT, unpublished) • 3000 lines (ICRISAT, unpublished) • GoldenGate assays based on VeraCode technology (Roorkiwal et al, 2013) • 60K Axiom®Cicer SNP array (Roorkiwal et al, 2017 (Chen et al, 2016) • 11 genotypes including synthetics and their diploid parents (Chen et al, 2016) • 41 diverse genotypes (30 tetraploids and 11 diploids) (Clevenger et al, 2017;Pandey et al, 2017a) • 58K Axiom®Arachis SNP array (Pandey et al, 2017a) •1536 SNP GoldenGate assay (Nagy et al, 2012) Common bean • 80.57% of Phaseolus vulgaris var G19833 genome (587 Mb); 26 279 protein coding genes (Schmutz et al, 2014) • 17 varieties • BARCBean6K_1, BARCBean6K_2 chips, BARCBean6K_3 SNP chips (Song et al, 2013 (Deulvot et al, 2010) • Combines custom-made growth vessels and new image analysis algorithms to non-destructively monitor RSA development over space (2D) and time • Allows information on soil properties (e.g. moisture)…”

Integrating genomics for chickpea improvement: achievements and opportunities

“…In a similar way, chickpea has graduated from simple pre-curser to one of the principal crops in Ethiopia based on its increasing socio-economic values. The availability of draft genome assemblies, large-scale re-sequencing, molecular markers, low-to high-density genotyping assays and quality check panels have enabled translational genomics in crop breeding (Varshney et al 2013a(Varshney et al , 2019bThudi et al 2016;Rasheed et al 2017;Roorkiwal et al 2018a). The development of ultra-high-throughput genotyping platforms that are cost-effective for use in breeding programmes will become a priority for the chickpea community in the coming years.…”

Relative potential of seed yield component traits as selection criteria in the segregating generations of a desi × kabuli cross of chickpea

“…India produced 7.82 million tonnes of chickpea from 8.39 million hectares of land with a share of more than 60% of world's area and production (FAOSTAT, 2016). However, chickpea productivity in India is very low (931 kg/ha) compared to the estimated potential of 6 t/ha under optimum growing conditions (Thudi et al, 2016). Hence, it is imperative to improve the productivity potential of chickpea to achieve increased availability of pulses.…”