Evidence map›Paper›PMID 36743549›Full record

ArticleFrontiers in plant science2022

Fine mapping and candidate gene analysis of proportion of four-seed pods by soybean CSSLs.

Fubin Cao, Ruru Wei, Jianguo Xie, Lilong Hou, Chaorui Kang, Tianyu Zhao, Chengcheng Sun, Mingliang Yang, Ying Zhao, Candong Li and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in plant science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

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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

3 citing papers in PubMed.

  1. Genetic diversity, GWAS, and candidate genes identification for plant architecture traits in maize (Zea mays L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    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

15 authors.

Fubin CaoCollege of Agriculture, Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin, China.
Ruru WeiCollege of Agriculture, Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin, China.
Jianguo XieJilin Academy of Agricultural Sciences, Soybean Research Institute, Changchun, Jilin, China.
Lilong HouCollege of Agriculture, Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin, China.
Chaorui KangCollege of Agriculture, Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin, China.
Tianyu ZhaoCollege of Agriculture, Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin, China.
Chengcheng SunCollege of Agriculture, Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin, China.
Mingliang YangCollege of Agriculture, Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin, China.
Ying ZhaoCollege of Agriculture, Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin, China.
Candong LiJiamusi Branch Institute, Heilongjiang Academy of Agricultural Sciences, Jiamusi, Heilongjiang, China.
Nannan WangJiamusi Branch Institute, Heilongjiang Academy of Agricultural Sciences, Jiamusi, Heilongjiang, China.
Xiaoxia WuCollege of Agriculture, Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin, China.
Chunyan LiuCollege of Agriculture, Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin, China.
Hongwei JiangJilin Academy of Agricultural Sciences, Soybean Research Institute, Changchun, Jilin, China.
Qingshan ChenCollege of Agriculture, Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soybean yield, as one of the most important and consistent breeding goals, can be greatly affected by the proportion of four-seed pods (PoFSP). In this study, QTL mapping was performed by PoFSP data and BLUE (Best Linear Unbiased Estimator) value of the chromosome segment substitution line population (CSSLs) constructed previously by the laboratory from 2016 to 2018, and phenotype-based bulked segregant analysis (BSA) was performed using the plant lines with PoFSP extreme phenotype. Totally, 5 ICIM QTLs were repeatedly detected, and 6 BSA QTLs were identified in CSSLs. For QTL (

Indexed as

BSAcandidate geneCSSLsQTL for the proportion of four-seed podssecondary segregation populationwild soybean

Identifiers

PMID36743549
PMCPMC9890659

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