Evidence map›Paper›PMID 26167172›Full record

ArticleInternational journal of plant genomics2015

Toward Coalescing Gene Expression and Function with QTLs of Water-Deficit Stress in Cotton.

Hirut Kebede, Paxton Payton, Hanh Thi My Pham, Randy D Allen, Robert J Wright

Open access · hybridAbstract read
In one paragraph

Article in International journal of plant genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.6field-weighted citation impact, top 14% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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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 3 institutions in 1 country.

Hirut KebedeUSDA-ARS Crop Genetics Research Unit, Stoneville, MS 38776, USA.
Paxton PaytonUSDA-ARS Cropping Systems Research Laboratory, Lubbock, TX 79415, USA.
Hanh Thi My PhamDepartment of Plant and Soil Science, Texas Tech University, Lubbock, TX 79409, USA.
Randy D AllenDepartment of Biochemistry and Molecular Biology, Oklahoma State University, Stillwater, OK 73401, USA.
Robert J WrightDepartment of Plant and Soil Science, Texas Tech University, Lubbock, TX 79409, USA.
Texas Tech University · USCropping Systems Research Laboratory · USOklahoma State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cotton exhibits moderately high vegetative tolerance to water-deficit stress but lint production is restricted by the available rainfed and irrigation capacity. We have described the impact of water-deficit stress on the genetic and metabolic control of fiber quality and production. Here we examine the association of tentative consensus sequences (TCs) derived from various cotton tissues under irrigated and water-limited conditions with stress-responsive QTLs. Three thousand sixteen mapped sequence-tagged-sites were used as anchored targets to examine sequence homology with 15,784 TCs to test the hypothesis that putative stress-responsive genes will map within QTLs associated with stress-related phenotypic variation more frequently than with other genomic regions not associated with these QTLs. Approximately 1,906 of 15,784 TCs were mapped to the consensus map. About 35% of the annotated TCs that mapped within QTL regions were genes involved in an abiotic stress response. By comparison, only 14.5% of the annotated TCs mapped outside these QTLs were classified as abiotic stress genes. A simple binomial probability calculation of this degree of bias being observed if QTL and non-QTL regions are equally likely to contain stress genes was P (x ≥ 85) = 7.99  × 10(-15). These results suggest that the QTL regions have a higher propensity to contain stress genes.

Identifiers

PMID26167172
PMCPMC4488579
OpenAlexW1565515275

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.