Investigation of major gene for milk yield, milking speed, dry matter intake, and body weight in dairy cattle

Karacaören, Burak; Kadarmideen, Haja N.; Janss, Luc

doi:10.1007/bf03194643

Cited by 4 publications

(1 citation statement)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The existence of major genes in livestock has been reported in several studies (e.g., in pigs, Kadarmideen and Janss, 2005; in dairy cattle, Karacaören et al, 2006; and in laying hens, Hagger et al, 2004). Renieri et al (2009) and Sponenberg (2010) reported that HU and SU inheritance can be described by a single dominant gene.…”

Section: Introductionmentioning

confidence: 96%

Analysis of the existence of major genes affecting alpaca fiber traits1

Pérez-Cabal

Cervantes

Morante³

et al. 2010

Journal of Animal Science

View full text Add to dashboard Cite

the World Wide Web at:The online version of this article, along with updated information and services, is located on www.asas.org at UOV / Biblioteca Universitaria on December 11, 2012 www.journalofanimalscience.org Downloaded from ABSTRACT: The aim of this study was to determine the presence of major genes for fiber diameter (FD), SD of FD (SDFD), CV of FD, and comfort factor (CF) in Huacaya (HU) and Suri (SU) Peruvian alpaca breeds. Bayesian segregation analyses with relaxed transmission probabilities were performed using 1,906 and 6,592 available records for SU and HU breeds. Evidence for the presence of major genes was statistically supported when the 95% posterior density did not include zero. Significant major genes were found associated with decreased FD, SDFD, CV values, and increased CF values. Additive effects of the major genes were 4.18 and 4.23 μm for FD, 1.67 and 1.61 μm for SDFD, 3.32 and 3.76% for CV, and 15.03 and 14.90% for CF in HU and SU breeds, respectively. Dominance effects were −1.98 and −2.03 μm for FD, −0.88 and −1.11 μm for SDFD, −1.37 and −2.17% for CV, and 13.0 and 11.8% for CF in HU and SU breeds, respectively. Major gene variance was larger than the polygenic variance for all traits. Major gene allelic frequencies for FD, SDFD, and CV ranged from 0.81 to 0.86 for HU breed and from 0.70 to 0.77 for the SU breed and were 0.24 and 0.36, respectively, for CF. It can be concluded that a major gene affecting these traits could be segregating. Then, molecular identification and monitoring of animals carrying favorable genes throughout the worldwide alpaca population would allow for a quick genetic improvement.

show abstract

Section: Introductionmentioning

confidence: 96%

Analysis of the existence of major genes affecting alpaca fiber traits1

Pérez-Cabal

Cervantes

Morante³

et al. 2010

Journal of Animal Science

View full text Add to dashboard Cite

show abstract

Evidence of major gene(s) affecting milk traits in the Chios sheep breed

Chatziplis¹,

Tzamaloukas²,

Miltiadou³

et al. 2012

Small Ruminant Research

View full text Add to dashboard Cite

Combined genetic, genomic and transcriptomic methods in the analysis of animal traits.

Kadarmideen

Reverter²

2007

CABI Reviews

View full text Add to dashboard Cite

This paper reviews advances and current status in genetic, genomic and transcriptomic investigations of quantitative traits in livestock species and proposes possible strategies for integrating the vast amounts of information (outputs/datasets) arising from all three investigations into a systems genetics approach. This systems genetics approach is characterized by investigations of the genetic basis of -omic variations and gene regulatory/co-regulatory networks. This review is structured as follows. Genetics/genomics, transcriptomics, combined transcriptomics-genomics and, finally, systems genetics/biology. In the genetics or genomics part, we discuss current status and advances in quantitative trait loci (QTLs) mapping to fine-map multiple causative/candidate genes. We discuss the potential of single nucleotide polymorphism (SNP) genotyping arrays (e.g. Affymetrix GeneChip arrays) to identify SNP-trait associations and fine-map QTLs to less than 0.1 cM. We provide references and resources for SNP analytical methods and tools. In the transcriptomics part, we formulate common biological questions relevant to livestock microarray gene expression profiling (MGEP) experiments to detect differentially expressed (DE) genes. In the combined transcriptomics-genomics (known as genetical genomics), we discuss detection and mapping of expression QTL (eQTL) that harbour regulatory genes for normal trait QTLs or candidate genes detected under 'genetics' and 'genomics' approaches. Illustrations from our own recent genetical genomic investigations in mouse and pigs are provided. One of the current challenges in genetical genomics is to have a coherent approach to design an experiment with due considerations for sample size and controlling false discovery rates (FDRs), while maintaining statistical power to detect eQTLs. Here we provide some concepts for the design of genetical genomics experiments with factors affecting FDR and power. This is followed by a systems biology/genetics section where we focus on combining research outputs from four different sources, namely: genetics or genomics (e.g. SNP, QTL and eQTLs), transcriptomics (e.g. DE genes, gene networks, and heritability of gene transcripts) and phenomics (e.g. phenotypes and pedigree). As a proof of principle, we provide results from systems biology/genetics approach anchored to a gene network for myogenin (MYOG), a muscle-specific transcription factor essential for the development of skeletal muscle. Using bovine expression datasets and in silico approaches, we built a gene network for MYOG that represents 35 significant connections between genes in this network. In conclusion, this paper provides strategies and tools to integrate data from genetics and -omics experiments in animals and highlighted the value of such 'systems genetics' strategy in understanding the genetics of complex traits.

show abstract

Investigation of major gene for milk yield, milking speed, dry matter intake, and body weight in dairy cattle

Cited by 4 publications

References 23 publications

Analysis of the existence of major genes affecting alpaca fiber traits1

Analysis of the existence of major genes affecting alpaca fiber traits1

Evidence of major gene(s) affecting milk traits in the Chios sheep breed

Combined genetic, genomic and transcriptomic methods in the analysis of animal traits.

Contact Info

Product

Resources

About