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Analysis of QTL–allele system conferring drought tolerance at seedling stage in a nested association mapping population of soybean [Glycine max (L.) Merr.] using a novel GWAS procedure

Overview of attention for article published in Planta, July 2018
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Title
Analysis of QTL–allele system conferring drought tolerance at seedling stage in a nested association mapping population of soybean [Glycine max (L.) Merr.] using a novel GWAS procedure
Published in
Planta, July 2018
DOI 10.1007/s00425-018-2952-4
Pubmed ID
Authors

Mueen Alam Khan, Fei Tong, Wubin Wang, Jianbo He, Tuanjie Zhao, Junyi Gai

Abstract

RTM-GWAS identified 111 DT QTLs, 262 alleles with high proportion of QEI and genetic variation accounting for 88.55-95.92% PV in NAM, from which QTL-allele matrices were established and candidate genes annotated. Drought tolerance (DT) is one of the major challenges for world soybean production. A nested association mapping (NAM) population with 403 lines comprising two recombinant inbred line (RIL) populations: M8206 × TongShan and ZhengYang × M8206 was tested for DT using polyethylene-glycol (PEG) treatment under spring and summer environments. The population was sequenced using restriction-site-associated DNA sequencing (RAD-seq) filtered with minor allele frequency (MAF) ≥ 0.01, 55,936 single nucleotide polymorphisms (SNPs) were obtained and organized into 6137 SNP linkage disequilibrium blocks (SNPLDBs). The restricted two-stage multi-locus genome-wide association studies (RTM-GWAS) identified 73 and 38 QTLs with 174 and 88 alleles contributed main effect 40.43 and 26.11% to phenotypic variance (PV) and QTL-environment interaction (QEI) effect 24.64 and 10.35% to PV for relative root length (RRL) and relative shoot length (RSL), respectively. The DT traits were characterized with high proportion of QEI variation (37.52-41.65%), plus genetic variation (46.90-58.40%) in a total of 88.55-95.92% PV. The identified QTLs-alleles were organized into main-effect and QEI-effect QTL-allele matrices, showing the genetic and QEI architecture of the three parents/NAM population. From the matrices, the possible best genotype was predicted to have a weighted average value over two indicators (WAV) of 1.873, while the top ten optimal crosses among RILs with 95th percentile WAV 1.098-1.132, transgressive over the parents (0.651-0.773) but much less than 1.873, implying further pyramiding potential. From the matrices, 134 candidate genes were annotated involved in nine biological processes. The present results provide a novel way for molecular breeding in QTL-allele-based genomic selection for optimal cross selection.

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Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 14%
Student > Master 5 11%
Other 3 7%
Student > Doctoral Student 2 5%
Student > Bachelor 2 5%
Other 8 18%
Unknown 18 41%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 43%
Biochemistry, Genetics and Molecular Biology 2 5%
Business, Management and Accounting 1 2%
Computer Science 1 2%
Psychology 1 2%
Other 2 5%
Unknown 18 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 08 July 2018.
All research outputs
#15,012,809
of 23,094,276 outputs
Outputs from Planta
#1,802
of 2,742 outputs
Outputs of similar age
#197,988
of 327,716 outputs
Outputs of similar age from Planta
#9
of 44 outputs
Altmetric has tracked 23,094,276 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,742 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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 327,716 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.