ArticleBMC plant biology2026
From gene discovery to breeding tools: functional KASP markers for flowering time selection in chickpea.
Article in BMC plant biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Genetic interactions among flowering loci influence phenology, vigour, and yield in chickpea.Molecular breeding : new strategies in plant improvement · 2026Article
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5 authors.
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Abstract
backgroundFlowering time is a key phenological trait in chickpea (Cicer arietinum L.), determining adaptation to different agro-climatic conditions and directly influencing yield. Here, we investigated the genetic basis of flowering time in four recombinant inbred line populations (RIP1, RIP8, RIP10, and RIP12) derived from intra- and interspecific crosses.
resultsPhenotypic evaluation revealed continuous, near-normal distributions in RIP1, RIP8, and RIP10 (consistent with polygenic control) whereas the bimodal distribution observed in RIP12 indicated the presence of a major-effect locus. Phenotype-genotype association analyses identified numerous SNPs associated with flowering time across multiple chromosomes, some of which, although located outside coding regions, may reside in regulatory elements or be tightly linked to causal variants. Several putative genes for flowering time were highlighted, including LOC101493933 (RIC7), implicated in cytoskeletal regulation and ROS-mediated signaling; LOC101497495, associated with lipid metabolism and FT signaling; and LOC101498370, a BRCA1-related protein with potential roles in chromatin remodeling. In RIP12, LOC101495197 (MOS14), a nuclear import factor, and LOC101498578 (apyrase 2), a regulator of extracellular ATP, together explained more than 86% of phenotypic variance, supporting their involvement in floral induction. Notably, LOC101489383 (HisIE), a histidine-biosynthesis gene, accounted for over 70% of flowering-time variance in RIP8 and showed exceptionally high expression in floral tissues, underscoring the contribution of amino acid metabolism to reproductive development. From SNPs within these genes, six allele-specific KASP markers were developed, achieving 81–90% efficiency in distinguishing early- and late-flowering phenotypes.
conclusionsOverall, this work reveals a complex genetic landscape underlying flowering time in chickpea, shaped by both minor and major-effect loci. The integration of phenotypic, genotypic, and in-silico analyses with KASP marker development provides valuable resources for marker-assisted selection, supporting the breeding of early-flowering cultivars adapted to changing environments.
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