Measuring genetic distances between breeds: use of some distances in various short term evolution models

Many works demonstrate the benefits of using highly polymorphic markers such as microsatellites in order to measure the genetic diversity between closely related breeds. But it is sometimes difficult to decide which genetic distance should be used. In this paper we review the behaviour of the main distances encountered in the literature in various divergence models. In the first part, we consider that breeds are populations in which the assumption of equilibrium between drift and mutation is verified. In this case some interesting distances can be expressed as a function of divergence time, t, and therefore can be used to construct phylogenies. Distances based on allele size distribution (such as (δμ)2 and derived distances), taking a mutation model of microsatellites, the Stepwise Mutation Model, specifically into account, exhibit large variance and therefore should not be used to accurately infer phylogeny of closely related breeds. In the last section, we will consider that breeds are small populations and that the divergence times between them are too small to consider that the observed diversity is due to mutations: divergence is mainly due to genetic drift. Expectation and variance of distances were calculated as a function of the Wright-Malécot inbreeding coefficient, F. Computer simulations performed under this divergence model show that the Reynolds distance [57]is the best method for very closely related breeds

Gene array and real time PCR analysis of the adrenal sensitivity to adrenocorticotropic hormone in pig

<p>Abstract</p> <p>Background</p> <p>Variability in hypothalamic-pituitary-adrenal (HPA) axis activity has been shown to be influenced by genetic factors and related to great metabolic differences such as obesity. The aim of this study was to investigate molecular bases of genetic variability of the adrenal sensitivity to ACTH, a major source of variability, in Meishan (MS) and Large White (LW) pigs, MS being reported to exhibit higher basal cortisol levels, response to ACTH and fatness than LW. A pig cDNA microarray was used to identify changes in gene expression in basal conditions and in response to ACTH stimulation.</p> <p>Results</p> <p>Genotype and/or ACTH affected the expression of 211 genes related to transcription, cell growth/maintenance, signal transduction, cell structure/adhesion/extra cellular matrix and protein kinase/phosphatase activity. No change in the expression of known key regulator proteins of the ACTH signaling pathway or of steroidogenic enzymes was found. However, <it>Mdh2</it>, <it>Sdha</it>, <it>Suclg2</it>, genes involved in the tricarboxylic acid (TCA) pathway, were over-expressed in MS pigs. Higher TCA cycle activity in MS than in LW may thus result in higher steroidogenic activity and thus explain the typically higher cortisol levels in MS compared to LW. Moreover, up-regulation of <it>Star </it>and <it>Ldlr </it>genes in MS and/or in response to ACTH suggest that differences in the adrenal function between MS and LW may also involve mechanisms requisite for cholesterol supply to steroidogenesis.</p> <p>Conclusion</p> <p>The present study provides new potential candidate genes to explain genetic variations in the adrenal sensitivity to ACTH and better understand relationship between HPA axis activity and obesity.</p

Estimation of genetic variation in residual variance in female and male broiler chickens

In breeding programs, robustness of animals and uniformity of end product can be improved by exploiting genetic variation in residual variance. Residual variance can be defined as environmental variance after accounting for all identifiable effects. The aims of this study were to estimate genetic variance in residual variance of body weight, and to estimate genetic correlations between body weight itself and its residual variance and between female and male residual variance for broilers. The data sets comprised 26 972 female and 24 407 male body weight records. Variance components were estimated with ASREML. Estimates of the heritability of residual variance were in the range 0.029 (s.e.50.003) to 0.047 (s.e.50.004). The genetic coefficients of variation were high, between 0.35 and 0.57. Heritabilities were higher in females than in males. Accounting for heterogeneous residual variance increased the heritabilities for body weight as well. Genetic correlations between body weight and its residual variance were 20.41 (s.e.50.032) and 20.45 (s.e.50.040), respectively, in females and males. The genetic correlation between female and male residual variance was 0.11 (s.e.50.089), indicating that female and male residual variance are different traits. Results indicate good opportunities to simultaneously increase the mean and improve uniformity of body weight of broilers by selection

A review on SNP and other types of molecular markers and their use in animal genetics

During the last ten years, the use of molecular markers, revealing polymorphism at the DNA level, has been playing an increasing part in animal genetics studies. Amongst others, the microsatellite DNA marker has been the most widely used, due to its easy use by simple PCR, followed by a denaturing gel electrophoresis for allele size determination, and to the high degree of information provided by its large number of alleles per locus. Despite this, a new marker type, named SNP, for Single Nucleotide Polymorphism, is now on the scene and has gained high popularity, even though it is only a bi-allelic type of marker. In this review, we will discuss the reasons for this apparent step backwards, and the pertinence of the use of SNPs in animal genetics, in comparison with other marker types

Genetic components of litter size variability in sheep

Classical selection for increasing prolificacy in sheep leads to a concomitant increase in its variability, even though the objective of the breeder is to maximise the frequency of an intermediate litter size rather than the frequency of high litter sizes. For instance, in the Lacaune sheep breed raised in semi-intensive conditions, ewes lambing twins represent the economic optimum. Data for this breed, obtained from the national recording scheme, were analysed. Variance components were estimated in an infinitesimal model involving genes controlling the mean level as well as its environmental variability. Large heritability was found for the mean prolificacy, but a high potential for increasing the percentage of twins at lambing while reducing the environmental variability of prolificacy is also suspected. Quantification of the response to such a canalising selection was achieved

Prediction of the response to a selection for canalisation of a continuous trait in animal breeding

International audienc

Pathway results from the chicken data set using GOTM, Pathway Studio and Ingenuity softwares

Background: As presented in the introduction paper, three sets of differentially regulated genes were found after the analysis of the chicken infection data set from EADGENE. Different methods were used to interpret these results.[br/] Results: GOTM, Pathway Studio and Ingenuity softwares were used to investigate the three lists of genes. The three softwares allowed the analysis of the data and highlighted different networks. However, only one set of genes, showing a differential expression between primary and secondary response gave significant biological interpretation.[br/] Conclusion: Combining these databases that were developed independently on different annotation sources supplies a useful tool for a global biological interpretation of microarray data, even if they may contain some imperfections (e.g. gene not or not well annotated)

The Structure of a Gene Co-Expression Network Reveals Biological Functions Underlying eQTLs

What are the commonalities between genes, whose expression level is partially controlled by eQTL, especially with regard to biological functions? Moreover, how are these genes related to a phenotype of interest? These issues are particularly difficult to address when the genome annotation is incomplete, as is the case for mammalian species. Moreover, the direct link between gene expression and a phenotype of interest may be weak, and thus difficult to handle. In this framework, the use of a co-expression network has proven useful: it is a robust approach for modeling a complex system of genetic regulations, and to infer knowledge for yet unknown genes. In this article, a case study was conducted with a mammalian species. It showed that the use of a co-expression network based on partial correlation, combined with a relevant clustering of nodes, leads to an enrichment of biological functions of around 83%. Moreover, the use of a spatial statistics approach allowed us to superimpose additional information related to a phenotype; this lead to highlighting specific genes or gene clusters that are related to the network structure and the phenotype. Three main results are worth noting: first, key genes were highlighted as a potential focus for forthcoming biological experiments; second, a set of biological functions, which support a list of genes under partial eQTL control, was set up by an overview of the global structure of the gene expression network; third, pH was found correlated with gene clusters, and then with related biological functions, as a result of a spatial analysis of the network topology

Changes induced by dietary energy intake and divergent selection for muscle fat content in rainbow trout (Oncorhynchus mykiss), assessed by transcriptome and proteome analysis of the liver

<p>Abstract</p> <p>Background</p> <p>Growing interest is turned to fat storage levels and allocation within body compartments, due to their impact on human health and quality properties of farm animals. Energy intake and genetic background are major determinants of fattening in most animals, including humans. Previous studies have evidenced that fat deposition depends upon balance between various metabolic pathways. Using divergent selection, we obtained rainbow trout with differences in fat allocation between visceral adipose tissue and muscle, and no change in overall body fat content. Transcriptome and proteome analysis were applied to characterize the molecular changes occurring between these two lines when fed a low or a high energy diet. We focused on the liver, center of intermediary metabolism and the main site for lipogenesis in fish, as in humans and most avian species.</p> <p>Results</p> <p>The proteome and transcriptome analyses provided concordant results. The main changes induced by the dietary treatment were observed in lipid metabolism. The level of transcripts and proteins involved in intracellular lipid transport, fatty acid biosynthesis and anti-oxidant metabolism were lower with the lipid rich diet. In addition, genes and proteins involved in amino-acid catabolism and proteolysis were also under expressed with this diet. The major changes related to the selection effect were observed in levels of transcripts and proteins involved in amino-acid catabolism and proteolysis that were higher in the fat muscle line than in the lean muscle line.</p> <p>Conclusion</p> <p>The present study led to the identification of novel genes and proteins that responded to long term feeding with a high energy/high fat diet. Although muscle was the direct target, the selection procedure applied significantly affected hepatic metabolism, particularly protein and amino acid derivative metabolism. Interestingly, the selection procedure and the dietary treatment used to increase muscle fat content exerted opposite effects on the expression of the liver genes and proteins, with little interaction between the two factors. Some of the molecules we identified could be used as markers to prevent excess muscle fat accumulation.</p