63 K and 50 K SNP array based high-density genetic mapping and QTL analysis for productivity and fiber quality traits in cotton

Gowda, S. Anjan; Katageri, I. S.; Patil, Rajesh S.; Kumar, Parveen; Tiwari, Gopal Ji; Jena, Satya Narayan; Sawant, Samir V.

doi:10.1007/s10681-022-03039-3

Cited by 2 publications

(1 citation statement)

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“…Recently, 34 SNPs corresponding to 22 QTLs for LP, including 13 novel QTLs, were detected from 254 upland cotton accessions via GWAS [ 55 ]. Two stable LP QTLs and three BW QTLs were identified in the RIL mapping population derived from the inter-specific cross between G. hirsutum cv DS-28 and G. barbadense cv SBYF-425 [ 56 ]. We also identified one QTL for LP, and nine QTLs for BW from a BC 5 F 3:5 chromosome segment substitution line population derived from G. hirsutum CCRI36 and G. barbadense Hai1 [ 57 ].…”

Section: Discussionmentioning

confidence: 99%

Lint percentage and boll weight QTLs in three excellent upland cotton (Gossypium hirsutum): ZR014121, CCRI60, and EZ60

et al. 2023

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Background Upland cotton (Gossypium hirsutum L.) is the most economically important species in the cotton genus (Gossypium spp.). Enhancing the cotton yield is a major goal in cotton breeding programs. Lint percentage (LP) and boll weight (BW) are the two most important components of cotton lint yield. The identification of stable and effective quantitative trait loci (QTLs) will aid the molecular breeding of cotton cultivars with high yield. Results Genotyping by target sequencing (GBTS) and genome-wide association study (GWAS) with 3VmrMLM were used to identify LP and BW related QTLs from two recombinant inbred line (RIL) populations derived from high lint yield and fiber quality lines (ZR014121, CCRI60 and EZ60). The average call rate of a single locus was 94.35%, and the average call rate of an individual was 92.10% in GBTS. A total of 100 QTLs were identified; 22 of them were overlapping with the reported QTLs, and 78 were novel QTLs. Of the 100 QTLs, 51 QTLs were for LP, and they explained 0.29–9.96% of the phenotypic variation; 49 QTLs were for BW, and they explained 0.41–6.31% of the phenotypic variation. One QTL (qBW-E-A10-1, qBW-C-A10-1) was identified in both populations. Six key QTLs were identified in multiple-environments; three were for LP, and three were for BW. A total of 108 candidate genes were identified in the regions of the six key QTLs. Several candidate genes were positively related to the developments of LP and BW, such as genes involved in gene transcription, protein synthesis, calcium signaling, carbon metabolism, and biosynthesis of secondary metabolites. Seven major candidate genes were predicted to form a co-expression network. Six significantly highly expressed candidate genes of the six QTLs after anthesis were the key genes regulating LP and BW and affecting cotton yield formation. Conclusions A total of 100 stable QTLs for LP and BW in upland cotton were identified in this study; these QTLs could be used in cotton molecular breeding programs. Putative candidate genes of the six key QTLs were identified; this result provided clues for future studies on the mechanisms of LP and BW developments.

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Section: Discussionmentioning

confidence: 99%