Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example

Luo Ziliang; Wang Meng; Long Yan; Yongju Huang; Lei Shi; Chunyu Zhang; Xiang  Liu; Bruce Fitt; Jinxia Xiang; Annaliese Mason; Rod Snowdon; Peifa Liu; Jinling Meng; Jun Zou

doi:10.1007/s00122-017-2911-7

Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example

Luo Ziliang, Wang Meng, Long Yan, Yongju Huang, Lei Shi, Chunyu Zhang, Xiang Liu, Bruce Fitt, Jinxia Xiang, Annaliese Mason, Rod Snowdon, Peifa Liu, Jinling Meng, Jun Zou

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Abstract

Most agronomic traits of interest for crop improvement
(including seed yield) are highly complex quantitative
traits controlled by numerous genetic loci, which brings challenges
for comprehensively capturing associated markers/
genes. We propose that multiple trait interactions underlie
complex traits such as seed yield, and that considering these component traits and their interactions can dissect individual
quantitative trait loci (QTL) effects more effectively and
improve yield predictions. Using a segregating rapeseed (Brassica
napus) population, we analyzed a large set of trait data
generated in 19 independent experiments to investigate correlations
between seed yield and other complex traits, and further
identified QTL in this population with a SNP-based genetic bin
map. A total of 1904 consensus QTL accounting for 22 traits,
including 80 QTL directly affecting seed yield, were anchored
to the B. napus reference sequence. Through trait association
analysis and QTL meta-analysis, we identified a total of 525
indivisible QTL that either directly or indirectly contributed
to seed yield, of which 295 QTL were detected across multiple
environments. A majority (81.5%) of the 525 QTL were
pleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrasting
genetic effects, as well as 31 QTL with minor complementary
effects. Implementation of the 525 QTL in genomic
prediction models improved seed yield prediction accuracy.
Dissecting the genetic and phenotypic interrelationships underlying
complex quantitative traits using this method will provide
valuable insights for genomics-based crop improvement.

Original language	English
Pages (from-to)	1569-1585
Number of pages	17
Journal	Theoretical and Applied Genetics (TAG)
Volume	130
Issue number	8
Early online date	28 Apr 2017
DOIs	https://doi.org/10.1007/s00122-017-2911-7
Publication status	Published - 30 Aug 2017

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Luo et al pleiotropic paper Published VersionFinal published version, 1.79 MBLicence: CC BY

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Ziliang, L., Meng, W., Yan, L., Huang, Y., Shi, L., Zhang, C., Liu, X., Fitt, B., Xiang, J., Mason, A., Snowdon, R., Liu, P., Meng, J., & Zou, J. (2017). Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example. Theoretical and Applied Genetics (TAG), 130(8), 1569-1585. https://doi.org/10.1007/s00122-017-2911-7

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title = "Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example",

abstract = "Most agronomic traits of interest for crop improvement(including seed yield) are highly complex quantitativetraits controlled by numerous genetic loci, which brings challengesfor comprehensively capturing associated markers/genes. We propose that multiple trait interactions underliecomplex traits such as seed yield, and that considering these component traits and their interactions can dissect individualquantitative trait loci (QTL) effects more effectively andimprove yield predictions. Using a segregating rapeseed (Brassicanapus) population, we analyzed a large set of trait datagenerated in 19 independent experiments to investigate correlationsbetween seed yield and other complex traits, and furtheridentified QTL in this population with a SNP-based genetic binmap. A total of 1904 consensus QTL accounting for 22 traits,including 80 QTL directly affecting seed yield, were anchoredto the B. napus reference sequence. Through trait associationanalysis and QTL meta-analysis, we identified a total of 525indivisible QTL that either directly or indirectly contributedto seed yield, of which 295 QTL were detected across multipleenvironments. A majority (81.5%) of the 525 QTL werepleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrastinggenetic effects, as well as 31 QTL with minor complementaryeffects. Implementation of the 525 QTL in genomicprediction models improved seed yield prediction accuracy.Dissecting the genetic and phenotypic interrelationships underlyingcomplex quantitative traits using this method will providevaluable insights for genomics-based crop improvement.",

author = "Luo Ziliang and Wang Meng and Long Yan and Yongju Huang and Lei Shi and Chunyu Zhang and Xiang Liu and Bruce Fitt and Jinxia Xiang and Annaliese Mason and Rod Snowdon and Peifa Liu and Jinling Meng and Jun Zou",

note = "{\textcopyright} The Author(s) 2017 This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.",

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doi = "10.1007/s00122-017-2911-7",

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Ziliang, L, Meng, W, Yan, L, Huang, Y, Shi, L, Zhang, C, Liu, X, Fitt, B, Xiang, J, Mason, A, Snowdon, R, Liu, P, Meng, J & Zou, J 2017, 'Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example', Theoretical and Applied Genetics (TAG), vol. 130, no. 8, pp. 1569-1585. https://doi.org/10.1007/s00122-017-2911-7

TY - JOUR

T1 - Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example

AU - Ziliang, Luo

AU - Meng, Wang

AU - Yan, Long

AU - Huang, Yongju

AU - Shi, Lei

AU - Zhang, Chunyu

AU - Liu, Xiang

AU - Fitt, Bruce

AU - Xiang, Jinxia

AU - Mason, Annaliese

AU - Snowdon, Rod

AU - Liu, Peifa

AU - Meng, Jinling

AU - Zou, Jun

N1 - © The Author(s) 2017 This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

PY - 2017/8/30

Y1 - 2017/8/30

N2 - Most agronomic traits of interest for crop improvement(including seed yield) are highly complex quantitativetraits controlled by numerous genetic loci, which brings challengesfor comprehensively capturing associated markers/genes. We propose that multiple trait interactions underliecomplex traits such as seed yield, and that considering these component traits and their interactions can dissect individualquantitative trait loci (QTL) effects more effectively andimprove yield predictions. Using a segregating rapeseed (Brassicanapus) population, we analyzed a large set of trait datagenerated in 19 independent experiments to investigate correlationsbetween seed yield and other complex traits, and furtheridentified QTL in this population with a SNP-based genetic binmap. A total of 1904 consensus QTL accounting for 22 traits,including 80 QTL directly affecting seed yield, were anchoredto the B. napus reference sequence. Through trait associationanalysis and QTL meta-analysis, we identified a total of 525indivisible QTL that either directly or indirectly contributedto seed yield, of which 295 QTL were detected across multipleenvironments. A majority (81.5%) of the 525 QTL werepleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrastinggenetic effects, as well as 31 QTL with minor complementaryeffects. Implementation of the 525 QTL in genomicprediction models improved seed yield prediction accuracy.Dissecting the genetic and phenotypic interrelationships underlyingcomplex quantitative traits using this method will providevaluable insights for genomics-based crop improvement.

AB - Most agronomic traits of interest for crop improvement(including seed yield) are highly complex quantitativetraits controlled by numerous genetic loci, which brings challengesfor comprehensively capturing associated markers/genes. We propose that multiple trait interactions underliecomplex traits such as seed yield, and that considering these component traits and their interactions can dissect individualquantitative trait loci (QTL) effects more effectively andimprove yield predictions. Using a segregating rapeseed (Brassicanapus) population, we analyzed a large set of trait datagenerated in 19 independent experiments to investigate correlationsbetween seed yield and other complex traits, and furtheridentified QTL in this population with a SNP-based genetic binmap. A total of 1904 consensus QTL accounting for 22 traits,including 80 QTL directly affecting seed yield, were anchoredto the B. napus reference sequence. Through trait associationanalysis and QTL meta-analysis, we identified a total of 525indivisible QTL that either directly or indirectly contributedto seed yield, of which 295 QTL were detected across multipleenvironments. A majority (81.5%) of the 525 QTL werepleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrastinggenetic effects, as well as 31 QTL with minor complementaryeffects. Implementation of the 525 QTL in genomicprediction models improved seed yield prediction accuracy.Dissecting the genetic and phenotypic interrelationships underlyingcomplex quantitative traits using this method will providevaluable insights for genomics-based crop improvement.

U2 - 10.1007/s00122-017-2911-7

DO - 10.1007/s00122-017-2911-7

M3 - Article

SN - 0040-5752

VL - 130

SP - 1569

EP - 1585

JO - Theoretical and Applied Genetics (TAG)

JF - Theoretical and Applied Genetics (TAG)

IS - 8

ER -

Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example

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