Evidence map›Paper›PMID 28647758›Full record

SynthesisMolecular genetics and genomics : MGG2017

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

Abdelraheem Abdelraheem, Feng Liu, Mingzhou Song, Jinfa F Zhang

Abstract readMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Molecular genetics and genomics : MGG, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
9.1field-weighted citation impact, top 3% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 66 citations in OpenAlex.

  1. Pooled it
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  13. GBS-SNP and SSR based genetic mapping and QTL analysis for drought tolerance in upland cotton.Physiology and molecular biology of plants : an international journal of functional plant biology · 2021
    Article
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  15. QTL controlling fiber quality traits under salt stress in upland cotton (Gossypium hirsutum L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021
    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

4 authors at 1 institution in 1 country.

Abdelraheem AbdelraheemDepartment of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA.
Feng LiuDepartment of Computer Science, New Mexico State University, Las Cruces, NM, 88003, USA.
Mingzhou SongDepartment of Computer Science, New Mexico State University, Las Cruces, NM, 88003, USA.
Jinfa F ZhangDepartment of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA. jinzhang@nmsu.edu.
New Mexico State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The number and location of mapped quantitative trait loci (QTL) depend on genetic populations and testing environments. The identification of consistent QTL across genetic backgrounds and environments is a pre-requisite to marker-assisted selection. This study analyzed a total of 661 abiotic and biotic stress resistance QTL based on our previous work and other publications using the meta-analysis software Biomercator. It identified chromosomal regions containing QTL clusters for different resistance traits and hotspots for a particular resistance trait in cotton from 98 QTL for drought tolerance under greenhouse (DT) and 150 QTL in field conditions (FDT), 80 QTL for salt tolerance in the greenhouse conditions (ST), 201 QTL for resistance to Verticillium wilt (VW, Verticillium dahliae), 47 QTL for resistance to Fusarium wilt (FW, Fusarium oxysporum f. sp. vasinfectum), and 85 QTL for resistance to root-knot nematodes (RKN, Meloiodogyne incognita) and reniform nematodes (RN, Rotylenchulus reniformis). The traits used in QTL mapping for abiotic stress tolerance included morphological traits-plant height and fresh and dry shoot and root weights, physiological traits-chlorophyll content, osmotic potential, carbon isotope ratio, stomatal conductance, photosynthetic rate, transpiration, canopy temperature, and leaf area index, agronomic traits-seedcotton yield, lint yield, boll weight, and lint percent, and fiber quality traits-fiber length, uniformity, strength, elongation, and micronaire. The results showed that resistance QTL are not uniformly distributed across the cotton genome; some chromosomes carried disproportionally more QTL, QTL clusters, or hotspots. Twenty-three QTL clusters were found on 15 chromosomes (c3, c4, c5, c6, c7, c11, c14, c15, c16, c19, c20, c23, c24, c25, and c26). Moreover, 28 QTL hotshots were associated with different resistance traits including one hotspot on c4 for Verticillium wilt resistance, two QTL hotspots on c24 for chlorophyll content measured under both drought and salt stress conditions, and three other hotspots on c19 for the resistance to Verticillium wilt and Fusarium wilt, and micronaire under drought stress conditions. This meta-analysis of stress tolerance QTL provides an important foundation for cotton breeding and further studies on the genetic mechanisms of abiotic and biotic stress resistance in cotton.

Indexed as

Quantitative Trait LociTetraploidyChromosomes, PlantGossypiumStress, PhysiologicalAbiotic stress toleranceBiotic stress resistanceCottonMeta analysisQuantitative trait loci

Identifiers

PMID28647758
OpenAlexW2640044766

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.