Unraveling the genetic background of bovine milk fat composition

Research output: Thesisinternal PhD, WU

Abstract

Identification of genomic regions, and preferably individual genes, responsible for genetic variation in bovine milk fat composition enhances the understanding of biological pathways involved in fatty acid synthesis and is expected to increase opportunities for changing bovine milk fat composition by means of selective breeding. This thesis aimed to unravel the genetic background of bovine milk fat composition by detection, confirmation and fine-mapping of quantitative trait loci (QTL) for milk fatty acids in Dutch Holstein Friesian cattle. In addition, causal relations between fatty acids were explored. For this study roughly 2,000 dairy cows were genotyped with 50,000 DNA markers and phenotyped for individual fatty acids in both winter and summer milk samples using gas chromatography. Genome-wide association studies (GWAS) showed that milk fat composition has a complex genetic background with three major QTL that explain a relatively large fraction of the genetic variation of several milk fatty acids, and many QTL that explain a relatively small fraction of the genetic variation. Results from the GWAS for summer milk fatty acids confirmed most associations that were detected in the winter milk samples. Moving from linkage analysis toward GWAS confirmed and refined the size of previously detected QTL regions and resulted in new QTL regions. Performing GWAS based on individual fatty acids resulted in additional QTL as compared to GWAS based on fat percentage or yield. This shows that refinement of complex phenotypes into underlying components results in better links between genes and phenotypes. By increasing the marker density, the QTL on BTA19 was refined to a linkage disequilibrium block that contained 2 genes: coiled-coil domain containing 57 and fatty acid synthase. A search for causal relations between fatty acids resulted in a pathway from C4:0 to C12:0, which resembled the de novo synthesis pathway. Causal relation between the QTL on BTA19 and de novo fatty acids showed that the QTL affects C4:0, C6:0, C8:0, C10:0 and C14:0 directly, while C12:0 was indirectly affected by the QTL through its effect on C10:0. The potential of GWAS based on MIR predicted fatty acids was explored but failed to detect some QTL and resulted in additional QTL that were not detected based on GC measurements. Therefore, MIR predicted phenotypes add complexity to the genotype-phenotype relationship, and renders MIR predicted phenotypes less appropriate to identify candidate genes and to infer the biological background of traits.

Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Wageningen University
Supervisors/Advisors
  • van Arendonk, Johan, Promotor
  • Bovenhuis, Henk, Co-promotor
  • Visker, Marleen, Co-promotor
Award date16 May 2014
Place of PublicationWageningen
Publisher
Print ISBNs9789461739063
Publication statusPublished - 2014

Fingerprint

genetic background
milk fat
quantitative trait loci
milk
fatty acids
phenotype
genetic variation
genes
fatty-acid synthase
synthesis
winter
summer
selection methods
linkage disequilibrium
linkage (genetics)
genome-wide association study
Holstein
dairy cows
gas chromatography
genomics

Keywords

  • animal breeding
  • dairy farming
  • dairy cattle
  • milk production
  • fatty acids
  • genomics
  • quantitative trait loci

Cite this

Bouwman, A.C.. / Unraveling the genetic background of bovine milk fat composition. Wageningen : Wageningen University, 2014. 176 p.
@phdthesis{2ddd47ee3c5c45a2acf44ef20688560a,
title = "Unraveling the genetic background of bovine milk fat composition",
abstract = "Identification of genomic regions, and preferably individual genes, responsible for genetic variation in bovine milk fat composition enhances the understanding of biological pathways involved in fatty acid synthesis and is expected to increase opportunities for changing bovine milk fat composition by means of selective breeding. This thesis aimed to unravel the genetic background of bovine milk fat composition by detection, confirmation and fine-mapping of quantitative trait loci (QTL) for milk fatty acids in Dutch Holstein Friesian cattle. In addition, causal relations between fatty acids were explored. For this study roughly 2,000 dairy cows were genotyped with 50,000 DNA markers and phenotyped for individual fatty acids in both winter and summer milk samples using gas chromatography. Genome-wide association studies (GWAS) showed that milk fat composition has a complex genetic background with three major QTL that explain a relatively large fraction of the genetic variation of several milk fatty acids, and many QTL that explain a relatively small fraction of the genetic variation. Results from the GWAS for summer milk fatty acids confirmed most associations that were detected in the winter milk samples. Moving from linkage analysis toward GWAS confirmed and refined the size of previously detected QTL regions and resulted in new QTL regions. Performing GWAS based on individual fatty acids resulted in additional QTL as compared to GWAS based on fat percentage or yield. This shows that refinement of complex phenotypes into underlying components results in better links between genes and phenotypes. By increasing the marker density, the QTL on BTA19 was refined to a linkage disequilibrium block that contained 2 genes: coiled-coil domain containing 57 and fatty acid synthase. A search for causal relations between fatty acids resulted in a pathway from C4:0 to C12:0, which resembled the de novo synthesis pathway. Causal relation between the QTL on BTA19 and de novo fatty acids showed that the QTL affects C4:0, C6:0, C8:0, C10:0 and C14:0 directly, while C12:0 was indirectly affected by the QTL through its effect on C10:0. The potential of GWAS based on MIR predicted fatty acids was explored but failed to detect some QTL and resulted in additional QTL that were not detected based on GC measurements. Therefore, MIR predicted phenotypes add complexity to the genotype-phenotype relationship, and renders MIR predicted phenotypes less appropriate to identify candidate genes and to infer the biological background of traits.",
keywords = "dierveredeling, melkveehouderij, melkvee, melkproductie, vetzuren, genomica, loci voor kwantitatief kenmerk, animal breeding, dairy farming, dairy cattle, milk production, fatty acids, genomics, quantitative trait loci",
author = "A.C. Bouwman",
note = "WU thesis 5739",
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language = "English",
isbn = "9789461739063",
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Bouwman, AC 2014, 'Unraveling the genetic background of bovine milk fat composition', Doctor of Philosophy, Wageningen University, Wageningen.

Unraveling the genetic background of bovine milk fat composition. / Bouwman, A.C.

Wageningen : Wageningen University, 2014. 176 p.

Research output: Thesisinternal PhD, WU

TY - THES

T1 - Unraveling the genetic background of bovine milk fat composition

AU - Bouwman, A.C.

N1 - WU thesis 5739

PY - 2014

Y1 - 2014

N2 - Identification of genomic regions, and preferably individual genes, responsible for genetic variation in bovine milk fat composition enhances the understanding of biological pathways involved in fatty acid synthesis and is expected to increase opportunities for changing bovine milk fat composition by means of selective breeding. This thesis aimed to unravel the genetic background of bovine milk fat composition by detection, confirmation and fine-mapping of quantitative trait loci (QTL) for milk fatty acids in Dutch Holstein Friesian cattle. In addition, causal relations between fatty acids were explored. For this study roughly 2,000 dairy cows were genotyped with 50,000 DNA markers and phenotyped for individual fatty acids in both winter and summer milk samples using gas chromatography. Genome-wide association studies (GWAS) showed that milk fat composition has a complex genetic background with three major QTL that explain a relatively large fraction of the genetic variation of several milk fatty acids, and many QTL that explain a relatively small fraction of the genetic variation. Results from the GWAS for summer milk fatty acids confirmed most associations that were detected in the winter milk samples. Moving from linkage analysis toward GWAS confirmed and refined the size of previously detected QTL regions and resulted in new QTL regions. Performing GWAS based on individual fatty acids resulted in additional QTL as compared to GWAS based on fat percentage or yield. This shows that refinement of complex phenotypes into underlying components results in better links between genes and phenotypes. By increasing the marker density, the QTL on BTA19 was refined to a linkage disequilibrium block that contained 2 genes: coiled-coil domain containing 57 and fatty acid synthase. A search for causal relations between fatty acids resulted in a pathway from C4:0 to C12:0, which resembled the de novo synthesis pathway. Causal relation between the QTL on BTA19 and de novo fatty acids showed that the QTL affects C4:0, C6:0, C8:0, C10:0 and C14:0 directly, while C12:0 was indirectly affected by the QTL through its effect on C10:0. The potential of GWAS based on MIR predicted fatty acids was explored but failed to detect some QTL and resulted in additional QTL that were not detected based on GC measurements. Therefore, MIR predicted phenotypes add complexity to the genotype-phenotype relationship, and renders MIR predicted phenotypes less appropriate to identify candidate genes and to infer the biological background of traits.

AB - Identification of genomic regions, and preferably individual genes, responsible for genetic variation in bovine milk fat composition enhances the understanding of biological pathways involved in fatty acid synthesis and is expected to increase opportunities for changing bovine milk fat composition by means of selective breeding. This thesis aimed to unravel the genetic background of bovine milk fat composition by detection, confirmation and fine-mapping of quantitative trait loci (QTL) for milk fatty acids in Dutch Holstein Friesian cattle. In addition, causal relations between fatty acids were explored. For this study roughly 2,000 dairy cows were genotyped with 50,000 DNA markers and phenotyped for individual fatty acids in both winter and summer milk samples using gas chromatography. Genome-wide association studies (GWAS) showed that milk fat composition has a complex genetic background with three major QTL that explain a relatively large fraction of the genetic variation of several milk fatty acids, and many QTL that explain a relatively small fraction of the genetic variation. Results from the GWAS for summer milk fatty acids confirmed most associations that were detected in the winter milk samples. Moving from linkage analysis toward GWAS confirmed and refined the size of previously detected QTL regions and resulted in new QTL regions. Performing GWAS based on individual fatty acids resulted in additional QTL as compared to GWAS based on fat percentage or yield. This shows that refinement of complex phenotypes into underlying components results in better links between genes and phenotypes. By increasing the marker density, the QTL on BTA19 was refined to a linkage disequilibrium block that contained 2 genes: coiled-coil domain containing 57 and fatty acid synthase. A search for causal relations between fatty acids resulted in a pathway from C4:0 to C12:0, which resembled the de novo synthesis pathway. Causal relation between the QTL on BTA19 and de novo fatty acids showed that the QTL affects C4:0, C6:0, C8:0, C10:0 and C14:0 directly, while C12:0 was indirectly affected by the QTL through its effect on C10:0. The potential of GWAS based on MIR predicted fatty acids was explored but failed to detect some QTL and resulted in additional QTL that were not detected based on GC measurements. Therefore, MIR predicted phenotypes add complexity to the genotype-phenotype relationship, and renders MIR predicted phenotypes less appropriate to identify candidate genes and to infer the biological background of traits.

KW - dierveredeling

KW - melkveehouderij

KW - melkvee

KW - melkproductie

KW - vetzuren

KW - genomica

KW - loci voor kwantitatief kenmerk

KW - animal breeding

KW - dairy farming

KW - dairy cattle

KW - milk production

KW - fatty acids

KW - genomics

KW - quantitative trait loci

M3 - internal PhD, WU

SN - 9789461739063

PB - Wageningen University

CY - Wageningen

ER -

Bouwman AC. Unraveling the genetic background of bovine milk fat composition. Wageningen: Wageningen University, 2014. 176 p.