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Enhancing Upland cotton for drought resilience, productivity, and fiber quality: comparative evaluation and genetic dissection.
Ulloa, Mauricio; De Santiago, Luis M; Hulse-Kemp, Amanda M; Stelly, David M; Burke, John J.
Affiliation
  • Ulloa M; USDA-ARS, PA, CSRL, Plant Stress and Germplasm Development Research, Lubbock, TX, 79415, USA. Mauricio.Ulloa@usda.gov.
  • De Santiago LM; Department of Soil and Crop Sciences, Texas A&M University, College Station, TX, 77843, USA.
  • Hulse-Kemp AM; Interdisciplinary Genetics Program, Texas A&M University, College Station, TX, 77843, USA.
  • Stelly DM; USDA-ARS, Genomics and Bioinformatics Research Unit, Raleigh, NC, 27695, USA.
  • Burke JJ; Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC, 27695, USA.
Mol Genet Genomics ; 295(1): 155-176, 2020 Jan.
Article in En | MEDLINE | ID: mdl-31620883
To provision the world sustainably, modern society must increase overall crop production, while conserving and preserving natural resources. Producing more with diminishing water resources is an especially daunting endeavor. Toward the goal of genetically improving drought resilience of cultivated Upland cotton (Gossypium hirsutum L.), this study addresses the genetics of differential yield components referred to as productivity and fiber quality traits under regular-water versus low-water (LW) field conditions. We used ten traits to assess water stress deficit, which included six productivity and four fiber quality traits on two recombinant inbred line (RIL) populations from reciprocally crossed cultivars, Phytogen 72 and Stoneville 474. To facilitate genetic inferences, we genotyped RILs with the CottonSNP63K array, assembled high-density linkage maps of over 7000 SNPs and then analyzed quantitative trait variations. Analysis of variance revealed significant differences for all traits (p < 0.05) in these RIL populations. Although the LW irrigation regime significantly reduced all traits, except lint percent, the RILs exhibited a broad phenotypic spectrum of heritable differences across the water regimes. Transgressive segregation occurred among the RILs, suggesting the possibility of genetic gain through phenotypic selection for drought resilience and perhaps through marker-based selection. Analyses revealed more than 150 quantitative trait loci (QTLs) associated with productivity and fiber quality traits (p < 0.005) on different genomic regions of the cotton genome. The multiple-QTL models analysis with LOD > 3.0 detected 21 QTLs associated with productivity and 22 QTLs associated with fiber quality. For fiber traits, strong clustering and QTL associations occurred in c08 and its homolog c24 as well as c10, c14, and c21. Using contemporary genome sequence assemblies and bioinformatically related information, the identification of genomic regions associated with responses to plant stress/drought elevates the possibility of using marker-assisted and omics-based selection to enhance breeding for drought resilient cultivars and identifying candidate genes and networks. RILs with different responses to drought indicated that it is possible to maintain high fiber quality under LW conditions or reduce the of LW impact on quality. The heritable variation among elite bi-parental RILs for productivity and quality under field drought conditions, and their association of QTLs, and thus specific genomic regions, indicate opportunities for breeding-based gains in water resource conservation, i.e., enhancing cotton's agricultural sustainability.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome, Plant / Gossypium Type of study: Prognostic_studies Language: En Journal: Mol Genet Genomics Journal subject: BIOLOGIA MOLECULAR / GENETICA Year: 2020 Document type: Article Affiliation country: United States Country of publication: Germany

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome, Plant / Gossypium Type of study: Prognostic_studies Language: En Journal: Mol Genet Genomics Journal subject: BIOLOGIA MOLECULAR / GENETICA Year: 2020 Document type: Article Affiliation country: United States Country of publication: Germany