Prospects and potentials of allele mining in chickpea for qualitative and quantitative traits

Pandey, S., Anand, A., Rathore, A., Taddi, S., & Kole, C. (2024). Prospects and potentials of allele mining in chickpea for qualitative and quantitative traits. In allele mining for genomic designing of grain legume crops. CRC Press (pp. 50-70). https://doi.org/10.1201/9781003385059-3

The chickpea (Cicer arietinum L., family Fabaceae) is a diploid with a chromosome number of 2n = 16. It is a self-pollinated crop which is classified as a cool-season pulse. With a genome size of approximately 738 Mb, chickpea is cultivated in over 50 countries worldwide. Within the domain of chickpea genomics, a vast repository of genetic sequence data is gathered in publicly accessible databases, a consequence of comprehensive genome sequencing initiatives across crop species. The exploitation of this genomic resource is of paramount importance in the pursuit of novel and superior allelic variants present within agronomically important genes. These genetic variations, ensconced within the diverse chickpea gene reservoir, hold considerable potential for driving the advancement of improved cultivars. The approach of allele mining is a robust investigative approach geared toward the dissection of naturally occurring allelic diversity residing within candidate genes that exert key control over fundamental agronomic traits. Allele mining leads to the development of molecular markers tailored to the precise area of marker-assisted selection, thereby bolstering the efficacy of genetic enhancement endeavors. This book chapter discusses the concepts, approaches, and accomplishments of allele mining in chickpea, shedding light on its role in elucidating allelic evolution, discovering novel haplotypes, and developing allele-specific markers for marker-assisted selection.