Genome-wide association mapping of yield components and drought tolerance-related traits in cotton

Abstract

Drought causes serious yield losses in cotton production throughout the world. Association mapping allows identification and localization of the genes controlling drought-related traits which will be helpful in cotton breeding. In the present study, genetic diversity analysis and association mapping of yield and drought traits were performed on a panel of 99 upland cotton genotypes using 177 SSR (simple sequence repeat) markers. Yield parameters and drought tolerancerelated traits were evaluated for two seasons under two watering regimes: water-stressed and well-watered. The traits included seed cotton yield (SCY), lint yield (LY), lint percentage (LP), water-use efficiency (WUE), yield potential (YP), yield reduction (YR), yield index (YI), drought sensitivity index (DSI), stress tolerance index (STI), harmonic mean (HM), and geometric mean productivity (GMP). The genotypes with the least change in seed cotton yield under drought stress were Zeta 2, Delcerro, Nazilli 87, and DAK 66/3 which were also the most water-use efficient cultivars. The average genetic diversity of the panel was 0.38. The linkage disequilibrium decayed relatively rapidly at 20-30 cM (r 2 ≥ 0.5). We identified 30 different SSR markers associated with the traits. Fifteen and 23 SSR markers were linked to the traits under well-watered and water-stress conditions, respectively. To our knowledge, most of these quantitative yield and drought toleranceassociated loci were newly identified. The genetic diversity and association mapping results should facilitate the development of drought-tolerant cotton lines with high yield in molecular breeding programs.

Molecular mapping of QTLs for fiber quality traits in Gossypium hirsutum multi-parent recombinant inbred lines

“…Together with two adjacent markers, DPL783 (Zhang et al 2016) and MUSB958 (Yu et al 2014), the region of JESPR274 is an informative QTL for lint percentage within an interval of 5.7 cM. DPL322, associated with lint percentage in this study, was linked to lint percentage and lint yield in previous work (Baytar et al 2018a) and also proposed as a useful marker for improvement of ber traits (Saeed and Elçi 2017). DPL322 is on chromosome 15 (51.4 cM) where marker-ber trait associations clustered within 3.1 cM: DPL003 was linked to seed cotton weight (Zhang et al 2016), MUSB1267 and TMB2931 linked to ber neness and short ber content (Yu et al 2014) and BNL2496 associated with seed cotton weight, seed index (Zhang et et al 2016) and ber uniformity (Wang et al 2017).…”

“…Seed cotton yield is greatly affected by genotype, temperature and growing conditions. For example, Baytar et al (2018a) detected a signi cant decrease in seed cotton yield (27%, p < 0.001) with insu cient soil moisture. These factors may account for the contradictions among ber quality studies.…”

“…JESPR274 on chromosome 9 was associated with lint percentage and ber neness in this study. We previously identi ed JESPR274 as associated with plant structural features (Baytar et al 2018b) as well as lint and seed cotton yield (Baytar et al 2018a). This marker was also linked to lint index (Wang et al 2007) and ber maturity (Qin et al 2015).…”

“…Many association mapping studies have targeted ber quality in Upland cotton using simple sequence repeat (SSR) markers. These include work that examined ber traits (Shermotov et al 2010;Baytar et al 2018b;Zeng et al 2009), yield traits (Li et al 2017;Baytar et al 2018a;Mei et al 2013) yield and ber traits (Abdurakhmonov et al 2010) and ber quality traits (Abdurakhmonov et al 2008(Abdurakhmonov et al , 2009Cai et al 2014;Nie et al 2016;Ademe et al 2017;Iqbal and Rahman 2017;Dong et al 2019). For example, Cai et al (2014) identi ed 107 signi cant ber trait-associations in 99 G. hirsutum accessions using 97 polymorphic SSR markers.…”

Heat Stress in Cotton: A Review on Predicted and Unpredicted Growth-Yield Anomalies and Mitigating Breeding Strategies

“…Association mapping is also an effective technique for cotton improvement when information on population structure and linkage disequilibrium (LD) is available. This method is quite useful for reducing the laborious work involved in screening large populations [158]. Genome-wide association studies (GWAS) represent a powerful approach for identifying the locations of genetic factors that underlie complex traits.…”