Genomic selection (GS) approaches, in combination with reproductive technologies, are revolutionizing the design and implementation of breeding programs in livestock species, particularly in cattle. GS leverages genomic readouts to provide estimates of breeding value early in the life of animals. However, the capacity of these approaches for improving genetic gain in breeding programs is limited by generation interval, the average age of an animal when replacement progeny are born.
View Article and Find Full Text PDFBackground: Obesity is a particularly complex disease that at least partially involves genetic and environmental perturbations to gene-networks connecting the hypothalamus and several metabolic tissues, resulting in an energy imbalance at the systems level.
Results: To provide an inter-tissue view of obesity with respect to molecular states that are associated with physiological states, we developed a framework for constructing tissue-to-tissue coexpression networks between genes in the hypothalamus, liver or adipose tissue. These networks have a scale-free architecture and are strikingly independent of gene-gene coexpression networks that are constructed from more standard analyses of single tissues.
The success of genome-wide association (GWA) studies for the detection of sequence variation affecting complex traits in human has spurred interest in the use of large-scale high-density single nucleotide polymorphism (SNP) genotyping for the identification of quantitative trait loci (QTL) and for marker-assisted selection in model and agricultural species. A cost-effective and efficient approach for the development of a custom genotyping assay interrogating 54,001 SNP loci to support GWA applications in cattle is described. A novel algorithm for achieving a compressed inter-marker interval distribution proved remarkably successful, with median interval of 37 kb and maximum predicted gap of <350 kb.
View Article and Find Full Text PDFUnderstanding the genetic architecture of traits such as growth, body composition, and energy balance has become a primary focus for biomedical and agricultural research. The objective of this study was to map QTL in a large F(2) (n = 1181) population resulting from an intercross between the M16 and ICR lines of mice. The M16 line, developed by long-term selection for 3- to 6-week weight gain, is larger, heavier, fatter, hyperphagic, and diabetic relative to its randomly selected control line of ICR origin.
View Article and Find Full Text PDFObjective: To characterize the phenotypic consequences of long-term selective breeding for rapid weight gain, with an emphasis on obesity and obesity-induced diabetes (diabesity).
Research Methods And Procedures: M16 is the result of long-term selection for 3- to 6-week weight gain from an ICR base population. Experiment 1 characterized males from both lines for body weights (3, 6, and 8 weeks), feed (4 to 8 weeks) and H(2)O (6 to 8 weeks) consumption, and heat loss, body composition, and levels of several plasma proteins at 8 weeks of age.
Mouse lines divergently selected for heat loss were evaluated for correlated responses in the hypothalamic transcriptome. High (MH) heat loss mice have approximately 50% greater heat loss, approximately 35% less body fat, approximately 20% greater feed intake, approximately 100% greater locomotor activity levels, and higher core body temperature compared with low (ML) heat loss mice. We evaluated hypothalamic expression between inbred lines derived from MH and ML lines (IH and IL, respectively) using cDNA microarrays and selected genes previously isolated in a large differential-display PCR experiment.
View Article and Find Full Text PDFThis study was undertaken to test for differential gene expression in intramuscular adipocytes during fat deposition of feedlot steers. Angus x Hereford steers (n = 50) were fed a high-energy concentrate ration ad libitum for 20 (n = 5), 86 (n = 15), 121 (n = 15), and 146 days (n = 15) to obtain various degrees of intramuscular adipocyte development. Carcass traits were significantly different (P < 0.
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