Evidence map›Paper›PMID 33719333›Full record

ArticleFrontiers in genetics2021

Identification of the QTL-allele System Underlying Two High-Throughput Physiological Traits in the Chinese Soybean Germplasm Population.

Lei Wang, Fangdong Liu, Xiaoshuai Hao, Wubin Wang, Guangnan Xing, Jingjing Luo, Guodong Zhou, Jianbo He, Junyi Gai

Abstract read
In one paragraph

Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Lei WangSoybean Research Institute, Nanjing Agricultural University, Nanjing, China.
Fangdong LiuSoybean Research Institute, Nanjing Agricultural University, Nanjing, China.
Xiaoshuai HaoSoybean Research Institute, Nanjing Agricultural University, Nanjing, China.
Wubin WangSoybean Research Institute, Nanjing Agricultural University, Nanjing, China.
Guangnan XingSoybean Research Institute, Nanjing Agricultural University, Nanjing, China.
Jingjing LuoPlant Phenomics Research Center, Nanjing Agricultural University, Nanjing, China.
Guodong ZhouPlant Phenomics Research Center, Nanjing Agricultural University, Nanjing, China.
Jianbo HeSoybean Research Institute, Nanjing Agricultural University, Nanjing, China.
Junyi GaiSoybean Research Institute, Nanjing Agricultural University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The QTL-allele system underlying two spectral reflectance physiological traits, NDVI (normalized difference vegetation index) and CHL (chlorophyll index), related to plant growth and yield was studied in the Chinese soybean germplasm population (CSGP), which consisted of 341 wild accessions (WA), farmer landraces (LR), and released cultivars (RC). Samples were evaluated in the Photosynthetic System II imaging platform at Nanjing Agricultural University. The NDVI and CHL data were obtained from hyperspectral reflectance images in a randomized incomplete block design experiment with two replicates. The NDVI and CHL ranged from 0.05-0.18 and 1.20-4.78, had averages of 0.11 and 3.57, and had heritabilities of 78.3% and 69.2%, respectively; the values of NDVI and CHL were both significantly higher in LR and RC than in WA. Using the RTM-GWAS (restricted two-stage multi-locus genome-wide association study) method, 38 and 32 QTLs with 89 and 82 alleles and 2-4 and 2-6 alleles per locus were identified for NDVI and CHL, respectively, which explained 48.36% and 51.35% of the phenotypic variation for NDVI and CHL, respectively. The QTL-allele matrices were established and separated into WA, LR, and RC submatrices. From WA to LR + RC, 4 alleles and 2 new loci emerged, and 1 allele was excluded for NDVI, whereas 6 alleles emerged, and no alleles were excluded, in LR + RC for CHL. Recombination was the major motivation of evolutionary differences. For NDVI and CHL, 39 and 32 candidate genes were annotated and assigned to GO groups, respectively, indicating a complex gene network. The NDVI and CHL were upstream traits that were relatively conservative in their genetic changes compared with those of downstream agronomic traits. High-throughput phenotyping integrated with RTM-GWAS provides an efficient procedure for studying the population genetics of traits.

Indexed as

annual wild soybean (G. soja Sieb. & Zucc.)chlorophyll index (CHL)cultivated soybean (G. max (L.) Merr.)high-throughput phenotypingnormalized difference vegetation index (NDVI)QTL-allele matrixrestricted two-stage multi-locus genome-wide association study (RTM-GWAS)spectral reflectance image

Identifiers

PMID33719333
PMCPMC7947801

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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.