Systematic trait dissection in oilseed rape provides a comprehensive view, further insight, and exact roadmap for yield determination.
Brassica napus
Positive or negative pleiotropy
Residual heterozygosity
Segregation distortion
Target or candidate genes
Trade-off
Trait-QTL network
Yield determination
Journal
Biotechnology for biofuels and bioproducts
ISSN: 2731-3654
Titre abrégé: Biotechnol Biofuels Bioprod
Pays: England
ID NLM: 9918300888906676
Informations de publication
Date de publication:
19 Apr 2022
19 Apr 2022
Historique:
received:
18
01
2022
accepted:
03
04
2022
entrez:
20
4
2022
pubmed:
21
4
2022
medline:
21
4
2022
Statut:
epublish
Résumé
Yield 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. In 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. The 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.
Sections du résumé
BACKGROUND
BACKGROUND
Yield 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.
RESULTS
RESULTS
In 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.
CONCLUSIONS
CONCLUSIONS
The 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.
Identifiants
pubmed: 35440054
doi: 10.1186/s13068-022-02134-w
pii: 10.1186/s13068-022-02134-w
pmc: PMC9019968
doi:
Types de publication
Journal Article
Langues
eng
Pagination
38Subventions
Organisme : Agricultural Science and Technology Innovation Program of China
ID : CAAS-ZDRW202105
Organisme : Agricultural Science and Technology Innovation Project of China
ID : CAAS-ASTIP-2013-OCRI
Organisme : Fundamental Research Funds for Central Non-Profit Institute of Crop Sciences, CAAS
ID : Y2020YJ09
Organisme : Natural Science Foundation of China
ID : 31771840
Organisme : Agriculture Research System of MOF and MARA of China
ID : CARS-13
Informations de copyright
© 2022. The Author(s).
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