Literature DB >> 31620883

Enhancing Upland cotton for drought resilience, productivity, and fiber quality: comparative evaluation and genetic dissection.

Mauricio Ulloa1, Luis M De Santiago2,3, Amanda M Hulse-Kemp4,5, David M Stelly2, John J Burke6.   

Abstract

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.

Entities:  

Keywords:  Breeding; Drought; Genetic mapping; Linkage analysis; Mapping population; Molecular markers; Plant stress; Quantitative trait loci (QTLs); Recombinant inbred line (RIL); SNP

Mesh:

Year:  2019        PMID: 31620883     DOI: 10.1007/s00438-019-01611-6

Source DB:  PubMed          Journal:  Mol Genet Genomics        ISSN: 1617-4623            Impact factor:   3.291


  42 in total

1.  QTL analysis of genotype x environment interactions affecting cotton fiber quality.

Authors:  A H Paterson; Y Saranga; M Menz; C-X Jiang; R J Wright
Journal:  Theor Appl Genet       Date:  2002-09-19       Impact factor: 5.699

2.  Sequencing of allotetraploid cotton (Gossypium hirsutum L. acc. TM-1) provides a resource for fiber improvement.

Authors:  Tianzhen Zhang; Yan Hu; Wenkai Jiang; Lei Fang; Xueying Guan; Jiedan Chen; Jinbo Zhang; Christopher A Saski; Brian E Scheffler; David M Stelly; Amanda M Hulse-Kemp; Qun Wan; Bingliang Liu; Chunxiao Liu; Sen Wang; Mengqiao Pan; Yangkun Wang; Dawei Wang; Wenxue Ye; Lijing Chang; Wenpan Zhang; Qingxin Song; Ryan C Kirkbride; Xiaoya Chen; Elizabeth Dennis; Danny J Llewellyn; Daniel G Peterson; Peggy Thaxton; Don C Jones; Qiong Wang; Xiaoyang Xu; Hua Zhang; Huaitong Wu; Lei Zhou; Gaofu Mei; Shuqi Chen; Yue Tian; Dan Xiang; Xinghe Li; Jian Ding; Qiyang Zuo; Linna Tao; Yunchao Liu; Ji Li; Yu Lin; Yuanyuan Hui; Zhisheng Cao; Caiping Cai; Xiefei Zhu; Zhi Jiang; Baoliang Zhou; Wangzhen Guo; Ruiqiang Li; Z Jeffrey Chen
Journal:  Nat Biotechnol       Date:  2015-04-20       Impact factor: 54.908

3.  A meta-analysis of quantitative trait loci for abiotic and biotic stress resistance in tetraploid cotton.

Authors:  Abdelraheem Abdelraheem; Feng Liu; Mingzhou Song; Jinfa F Zhang
Journal:  Mol Genet Genomics       Date:  2017-06-24       Impact factor: 3.291

4.  BLAST+: architecture and applications.

Authors:  Christiam Camacho; George Coulouris; Vahram Avagyan; Ning Ma; Jason Papadopoulos; Kevin Bealer; Thomas L Madden
Journal:  BMC Bioinformatics       Date:  2009-12-15       Impact factor: 3.169

5.  Meta-analysis of cotton fiber quality QTLs across diverse environments in a Gossypium hirsutum x G. barbadense RIL population.

Authors:  Jean-Marc Lacape; Danny Llewellyn; John Jacobs; Tony Arioli; David Becker; Steve Calhoun; Yves Al-Ghazi; Shiming Liu; Oumarou Palaï; Sophie Georges; Marc Giband; Henrique de Assunção; Paulo Augusto Vianna Barroso; Michel Claverie; Gérard Gawryziak; Janine Jean; Michèle Vialle; Christopher Viot
Journal:  BMC Plant Biol       Date:  2010-06-28       Impact factor: 4.215

6.  Identification of QTL for Fiber Quality and Yield Traits Using Two Immortalized Backcross Populations in Upland Cotton.

Authors:  Hantao Wang; Cong Huang; Wenxia Zhao; Baosheng Dai; Chao Shen; Beibei Zhang; Dingguo Li; Zhongxu Lin
Journal:  PLoS One       Date:  2016-12-01       Impact factor: 3.240

7.  Genome-wide association study discovered genetic variation and candidate genes of fibre quality traits in Gossypium hirsutum L.

Authors:  Zhengwen Sun; Xingfen Wang; Zhengwen Liu; Qishen Gu; Yan Zhang; Zhikun Li; Huifeng Ke; Jun Yang; Jinhua Wu; Liqiang Wu; Guiyin Zhang; Caiying Zhang; Zhiying Ma
Journal:  Plant Biotechnol J       Date:  2017-03-07       Impact factor: 9.803

8.  Genetic Map Construction and Fiber Quality QTL Mapping Using the CottonSNP80K Array in Upland Cotton.

Authors:  Zhaoyun Tan; Zhiqin Zhang; Xujing Sun; Qianqian Li; Ying Sun; Peng Yang; Wenwen Wang; Xueying Liu; Chunling Chen; Dexing Liu; Zhonghua Teng; Kai Guo; Jian Zhang; Dajun Liu; Zhengsheng Zhang
Journal:  Front Plant Sci       Date:  2018-02-27       Impact factor: 5.753

9.  Quantitative trait loci analysis of fiber quality traits using a random-mated recombinant inbred population in Upland cotton (Gossypium hirsutum L.).

Authors:  David D Fang; Johnie N Jenkins; Dewayne D Deng; Jack C McCarty; Ping Li; Jixiang Wu
Journal:  BMC Genomics       Date:  2014-05-24       Impact factor: 3.969

10.  Identification of Introgressed Alleles Conferring High Fiber Quality Derived From Gossypium barbadense L. in Secondary Mapping Populations of G. hirsutum L.

Authors:  Yu Chen; Guodong Liu; Hehuan Ma; Zhangqiang Song; Chuanyun Zhang; Jingxia Zhang; Junhao Zhang; Furong Wang; Jun Zhang
Journal:  Front Plant Sci       Date:  2018-07-18       Impact factor: 5.753

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  2 in total

1.  Genome-Wide Dissection of the Genetic Basis for Drought Tolerance in Gossypium hirsutum L. Races.

Authors:  Xinlei Guo; Yuanyuan Wang; Yuqing Hou; Zhongli Zhou; Runrun Sun; Tengfei Qin; Kunbo Wang; Fang Liu; Yuhong Wang; Zhongwen Huang; Yanchao Xu; Xiaoyan Cai
Journal:  Front Plant Sci       Date:  2022-06-28       Impact factor: 6.627

2.  High-Temperature and Drought-Resilience Traits among Interspecific Chromosome Substitution Lines for Genetic Improvement of Upland Cotton.

Authors:  Kambham Raja Reddy; Raju Bheemanahalli; Sukumar Saha; Kulvir Singh; Suresh B Lokhande; Bandara Gajanayake; John J Read; Johnie N Jenkins; Dwaine A Raska; Luis M De Santiago; Amanda M Hulse-Kemp; Robert N Vaughn; David M Stelly
Journal:  Plants (Basel)       Date:  2020-12-10
  2 in total

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