See the published version of this preprint at Journal of Cotton Research.
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Research
Xinhui Nie
Shihezi University College of Agriculture
Corresponding Author
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Background: Meta-analysis of quantitative trait locus (QTL) is a computational technique to identify consensus QTL and refine QTL positions on the consensus map from multiple mapping studies. The combination of meta-QTL intervals, significant SNPs and transcriptome analysis has been widely used to identify candidate genes in various plants.
Results: In our study, 884 QTLs associated with cotton fiber quality traits from 12 studies were used for meta-QTL analysis based on reference genome TM-1, as a result, 74 meta-QTLs were identified, including 19 meta-QTLs for fiber length (FL); 18 meta-QTLs for fiber strength (FS); 11 meta-QTLs for fiber uniformity (FU); 11 meta-QTLs for fiber elongation (FE); and 15 meta-QTLs for micronaire (MIC). Combined with 8,589 significant SNPs associated with fiber quality traits collected from 15 studies, 297 candidate genes were identified in the meta-QTL intervals, 20 of which showed high expression specifically in the developing fibers. According to the function annotations, some of the 20 key candidate genes are associated with the fiber development.
Conclusions: This study provides not only stable QTLs used for marker-assisted selection (MAS), but also candidate genes to uncover the molecular mechanisms for cotton fiber development.
Keywords
Fiber quality traits, Meta-QTL, Significant SNPs, Candidate genes, Transcriptomic data
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CURRENT STATUS: Published
View the published article at Journal of Cotton Research.
No community comments so far
Editorial decision: Accept
On 28 Oct, 2020
Editor assigned
On 26 Oct, 2020
Submission checks complete
On 25 Oct, 2020
Editor invited
On 25 Oct, 2020
Version 2
Posted 21 Oct, 2020
No comments provided
Editorial decision: Minor revision
On 22 Oct, 2020
Review #1 received
Received 20 Oct, 2020
Reviewer #1 agreed
On 13 Oct, 2020
Editor assigned
On 12 Oct, 2020
Reviewers invited
Invitations sent on 12 Oct, 2020
Submission checks complete
On 11 Oct, 2020
Editor invited
On 11 Oct, 2020
No comments provided
Editorial decision: Major revision
On 24 Sep, 2020
Review #4 received
Received 18 Sep, 2020
Reviewer #4 agreed
On 03 Sep, 2020
Review #3 received
Received 28 Aug, 2020
Reviewer #3 agreed
On 12 Aug, 2020
Review #1 received
Received 21 Jul, 2020
Reviewer #2 agreed
On 21 Jul, 2020
Review #2 received
Received 21 Jul, 2020
Reviewer #1 agreed
On 16 Jul, 2020
Reviewers invited
Invitations sent on 13 Jul, 2020
Editor assigned
On 12 Jul, 2020
First submitted
On 11 Jul, 2020
Submission checks complete
On 11 Jul, 2020
Editor invited
On 11 Jul, 2020
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Subject Areas
Health Economics and Outcomes Research
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See the published version of this preprint at Journal of Cotton Research.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Xinhui Nie
Shihezi University College of Agriculture
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at Journal of Cotton Research.
No community comments so far
Editorial decision: Accept
On 28 Oct, 2020
Editor assigned
On 26 Oct, 2020
Submission checks complete
On 25 Oct, 2020
Editor invited
On 25 Oct, 2020
Version 2
Posted 21 Oct, 2020
No comments provided
Editorial decision: Minor revision
On 22 Oct, 2020
Review #1 received
Received 20 Oct, 2020
Reviewer #1 agreed
On 13 Oct, 2020
Editor assigned
On 12 Oct, 2020
Reviewers invited
Invitations sent on 12 Oct, 2020
Submission checks complete
On 11 Oct, 2020
Editor invited
On 11 Oct, 2020
No comments provided
Editorial decision: Major revision
On 24 Sep, 2020
Review #4 received
Received 18 Sep, 2020
Reviewer #4 agreed
On 03 Sep, 2020
Review #3 received
Received 28 Aug, 2020
Reviewer #3 agreed
On 12 Aug, 2020
Review #1 received
Received 21 Jul, 2020
Reviewer #2 agreed
On 21 Jul, 2020
Review #2 received
Received 21 Jul, 2020
Reviewer #1 agreed
On 16 Jul, 2020
Reviewers invited
Invitations sent on 13 Jul, 2020
Editor assigned
On 12 Jul, 2020
First submitted
On 11 Jul, 2020
Submission checks complete
On 11 Jul, 2020
Editor invited
On 11 Jul, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Health Economics and Outcomes Research
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Journal of Cotton Research.
Background: Meta-analysis of quantitative trait locus (QTL) is a computational technique to identify consensus QTL and refine QTL positions on the consensus map from multiple mapping studies. The combination of meta-QTL intervals, significant SNPs and transcriptome analysis has been widely used to identify candidate genes in various plants.
Results: In our study, 884 QTLs associated with cotton fiber quality traits from 12 studies were used for meta-QTL analysis based on reference genome TM-1, as a result, 74 meta-QTLs were identified, including 19 meta-QTLs for fiber length (FL); 18 meta-QTLs for fiber strength (FS); 11 meta-QTLs for fiber uniformity (FU); 11 meta-QTLs for fiber elongation (FE); and 15 meta-QTLs for micronaire (MIC). Combined with 8,589 significant SNPs associated with fiber quality traits collected from 15 studies, 297 candidate genes were identified in the meta-QTL intervals, 20 of which showed high expression specifically in the developing fibers. According to the function annotations, some of the 20 key candidate genes are associated with the fiber development.
Conclusions: This study provides not only stable QTLs used for marker-assisted selection (MAS), but also candidate genes to uncover the molecular mechanisms for cotton fiber development.
Figure 1
Figure 2
Figure 3
This is a list of supplementary files associated with this preprint. Click to download.
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