Evidence map›Paper›PMID 35440054›Full record

ArticleBiotechnology for biofuels and bioproducts2022

Systematic trait dissection in oilseed rape provides a comprehensive view, further insight, and exact roadmap for yield determination.

Huabing Liang, Jiang Ye, Ying Wang, Xinfa Wang, Xue-Rong Zhou, Jacqueline Batley, Graham J King, Liang Guo, Jinxing Tu, Jiaqin Shi and 1 more

Open access · goldAbstract read
In one paragraph

Article in Biotechnology for biofuels and bioproducts, 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
0.9field-weighted citation impact, top 23% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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, 5 citations in OpenAlex.

  1. 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

11 authors at 5 institutions in 2 countries.

Huabing Liang *Oil Crops Research Institute of the Chinses Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Wuhan, China.
Jiang Ye *Oil Crops Research Institute of the Chinses Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Wuhan, China.
Ying WangOil Crops Research Institute of the Chinses Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Wuhan, China.
Xinfa WangOil Crops Research Institute of the Chinses Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Wuhan, China.
Xue-Rong ZhouCommonwealth Scientific & Industrial Research Organisation (CSIRO) Agriculture & Food, Canberra, ACT, Australia.
Jacqueline BatleySchool of Biological Sciences, The University of Western Australia, Crawley, WA, 6009, Australia.
Graham J KingSouthern Cross Plant Science, Southern Cross University, Lismore, NSW, Australia.
Liang GuoNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Jinxing TuNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Jiaqin ShiOil Crops Research Institute of the Chinses Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Wuhan, China. shijiaqin@caas.cn.
Hanzhong WangOil Crops Research Institute of the Chinses Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Wuhan, China.
Oil Crops Research Institute · CNHuazhong Agricultural University · CNCommonwealth Scientific and Industrial Research Organisation · AUSouthern Cross University · AUUniversity of Western Australia · AU

Funding

Agricultural Science and Technology Innovation Program of China CAAS-ZDRW202105Agricultural Science and Technology Innovation Project of China CAAS-ASTIP-2013-OCRIAgriculture Research System of MOF and MARA of China CARS-13Fundamental Research Funds for Central Non-Profit Institute of Crop Sciences, CAAS Y2020YJ09Natural Science Foundation of China 31771840
6 · The paper itself

Abstract

backgroundYield is the most important and complex trait that is influenced by numerous relevant traits with very complicated interrelations. While there are a large number of studies on the phenotypic relationship and genetic basis of yield traits, systematic studies with further dissection focusing on yield are limited. Therefore, there is still lack of a comprehensive and in-depth understanding of the determination of yield.

resultsIn this study, yield was systematically dissected at the phenotypic, genetic to molecular levels in oilseed rape (Brassica napus L.). The analysis of correlation, network, and principal component for 21 traits in BnaZN-RIL population showed that yield was determined by a complex trait network with key contributors. The analysis of the constructed high-density single nucleotide polymorphism (SNP) linkage map revealed the concentrated distribution of distorted and heterozygous markers, likely due to selection on genes controlling the growth period and yield heterosis. A total of 134 consensus quantitative trait loci (QTL) were identified for 21 traits, of which all were incorporated into an interconnecting QTL network with dozens of hub-QTL. Four representative hub-QTL were further dissected to the target or candidate genes that governed the causal relationships between the relevant traits.

conclusionsThe highly consistent results at the phenotypic, genetic, and molecular dissecting demonstrated that yield was determined by a multilayer composite network that involved numerous traits and genes showing complex up/down-stream and positive/negative regulation. This provides a systematic view, further insight, and exact roadmap for yield determination, which represents a significant advance toward the understanding and dissection of complex traits.

Indexed as

Brassica napusPositive or negative pleiotropyResidual heterozygositySegregation distortionTarget or candidate genesTrade-offTrait-QTL networkYield determination

Identifiers

PMID35440054
PMCPMC9019968
OpenAlexW4224256042

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Registered trials

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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.