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Efficient QTL detection of flowering date in a soybean RIL population using the novel restricted two-stage multi-locus GWAS procedure

Overview of attention for article published in Theoretical and Applied Genetics, August 2018
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  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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Title
Efficient QTL detection of flowering date in a soybean RIL population using the novel restricted two-stage multi-locus GWAS procedure
Published in
Theoretical and Applied Genetics, August 2018
DOI 10.1007/s00122-018-3174-7
Pubmed ID
Authors

Liyuan Pan, Jianbo He, Tuanjie Zhao, Guangnan Xing, Yufeng Wang, Deyue Yu, Shouyi Chen, Junyi Gai

Abstract

Eighty-six R1 QTLs accounting for 89.92% phenotypic variance in a soybean RIL population were identified using RTM-GWAS with SNPLDB marker which performed superior over CIM and MLM-GWAS with BIN/SNPLDB marker. A population (NJRIKY) composed of 427 recombinant inbred lines (RILs) derived from Kefeng-1 × NN1138-2 (MGII × MGV, MG maturity group) was applied for detecting flowering date (R1) quantitative trait locus (QTL) system in soybean. From a low-depth re-sequencing (~ 0.75 ×), 576,874 SNPs were detected and organized into 4737 BINs (recombination breakpoint determinations) and 3683 SNP linkage disequilibrium blocks (SNPLDBs), respectively. Using the association mapping procedures "Restricted Two-stage Multi-locus Genome-wide Association Study" (RTM-GWAS), "Mixed Linear Model Genome-wide Association Study" (MLM-GWAS) and the linkage mapping procedure "Composite Interval Mapping" (CIM), 67, 36 and 10 BIN-QTLs and 86, 14 and 23 SNPLDB-QTLs were detected with their phenotypic variance explained (PVE) 88.70-89.92% (within heritability 98.2%), 146.41-353.62% (overflowing) and 88.29-172.34% (overflowing), respectively. The RTM-GWAS with SNPLDBs which showed to be more efficient and reasonable than the others was used to identify the R1 QTL system in NJRIKY. The detected 86 SNPLDB-QTLs with their PVE from 0.02 to 30.66% in a total of 89.92% covered 51 out of 104 R1 QTLs in 18 crosses in SoyBase and 26 out of 139 QTLs in a nested association mapping population, while the rest 29 QTLs were novel ones. From the QTL system, 52 candidate genes were annotated, including the verified gene E1, E2, E9 and J, and grouped into 3 categories of biological processes, among which 24 genes were enriched into three protein-protein interaction networks, suggesting gene networks working together. Since NJRIKY involves only MGII and MGV, the QTL/gene system among MG000-MGX should be explored further.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 19%
Researcher 5 16%
Student > Doctoral Student 2 6%
Unspecified 2 6%
Professor > Associate Professor 2 6%
Other 5 16%
Unknown 9 29%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 45%
Biochemistry, Genetics and Molecular Biology 2 6%
Unspecified 2 6%
Computer Science 2 6%
Psychology 1 3%
Other 0 0%
Unknown 10 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 September 2018.
All research outputs
#6,023,745
of 23,794,258 outputs
Outputs from Theoretical and Applied Genetics
#1,089
of 3,565 outputs
Outputs of similar age
#101,457
of 336,015 outputs
Outputs of similar age from Theoretical and Applied Genetics
#15
of 50 outputs
Altmetric has tracked 23,794,258 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 3,565 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 69% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 336,015 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.