Evidence map›Paper›PMID 31620883›Full record

ArticleMolecular genetics and genomics : MGG2020

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

Mauricio Ulloa, Luis M De Santiago, Amanda M Hulse-Kemp, David M Stelly, John J Burke

Abstract read
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In one paragraph

Article in Molecular genetics and genomics : MGG, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
5.2field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 32 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Mauricio UlloaUSDA-ARS, PA, CSRL, Plant Stress and Germplasm Development Research, Lubbock, TX, 79415, USA. Mauricio.Ulloa@usda.gov.ORCID http://orcid.org/0000-0002-3358-8889
Luis M De SantiagoDepartment of Soil and Crop Sciences, Texas A&M University, College Station, TX, 77843, USA.
Amanda M Hulse-KempUSDA-ARS, Genomics and Bioinformatics Research Unit, Raleigh, NC, 27695, USA.ORCID http://orcid.org/0000-0001-9670-9433
David M StellyDepartment of Soil and Crop Sciences, Texas A&M University, College Station, TX, 77843, USA.ORCID http://orcid.org/0000-0002-3468-4119
John J BurkeUSDA-ARS, PA, CSRL, Plant Stress and Germplasm Development Research, Lubbock, TX, 79415, USA.
Agricultural Research Service · USTexas A&M University · US

Funding

Cotton Incorporated 042Cotton Incorporated 047Cotton Incorporated 58-3096-002Cotton Incorporated 58-3096-009
6 · The paper itself

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.

Indexed as

BreedingChromosome MappingCotton FiberDroughtsGenetic LinkageGenome, PlantGenotypeGossypiumPhenotypePolymorphism, Single NucleotideQuantitative Trait LociBreedingDroughtGenetic mappingLinkage analysisMapping populationMolecular markersPlant stressQuantitative trait loci (QTLs)Recombinant inbred line (RIL)SNP

Identifiers

PMID31620883
OpenAlexW2980504693

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.