Texel sheep are renowned for their exceptional meatiness. To identify the genes underlying this economically important feature, we performed a whole-genome scan in a Romanov x Texel F2 population. We mapped a quantitative trait locus with a major effect on muscle mass to chromosome 2 and subsequently fine-mapped it to a chromosome interval encompassing the myostatin (GDF8) gene. We herein demonstrate that the GDF8 allele of Texel sheep is characterized by a G to A transition in the 3' UTR that creates a target site for mir1 and mir206, microRNAs (miRNAs) that are highly expressed in skeletal muscle. This causes translational inhibition of the myostatin gene and hence contributes to the muscular hypertrophy of Texel sheep. Analysis of SNP databases for humans and mice demonstrates that mutations creating or destroying putative miRNA target sites are abundant and might be important effectors of phenotypic variation.

In this paper we consider the detection of individual loci controlling quantitative traits of interest (quantitative trait loci or QTLs) in the large half-sib family structure found in some species. Two simple approaches using multiple markers are proposed, one using least squares and the other maximum likelihood. These methods are intended to provide a relatively fast screening of the entire genome to pinpoint regions of interest for further investigation. They are compared with a more traditional single-marker least-squares approach. The use of multiple markers is shown to increase power and has the advantage of providing an estimate for the location of the QTL. The maximum-likelihood and the least-squares approaches using multiple markers give similar power and estimates for the QTL location, although the likelihood approach also provides estimates of the QTL effect and sire heterozygote frequency. A number of assumptions have been made in order to make the likelihood calculations feasible, however, and computationally it is still more demanding than the least-squares approach. The least-squares approach using multiple markers provides a fast method that can easily be extended to include additional effects.

The immune system is known to be involved in the early phase of scrapie pathogenesis. However, the infection route of naturally occurring scrapie and its spread within the host are not entirely known. In this study, the pathogenesis of scrapie was investigated in sheep of three PrP genotypes, from 2 to 9 months of age, which were born and raised together in a naturally scrapie-affected Romanov flock. The kinetics of PrP Sc accumulation in sheep organs were determined by immunohistochemistry. PrP Sc was detected only in susceptible VRQ/VRQ sheep, from 2 months of age, with an apparent entry site at the ileal Peyer's patch as well as its draining mesenteric lymph node. At the cellular level, PrP Sc deposits were associated with CD68-positive cells of the dome area and B follicles before being detected in follicular dendritic cells. In 3-to 6-month-old sheep, PrP Sc was detected in most of the gut-associated lymphoid tissues (GALT) and to a lesser extent in more systemic lymphoid formations such as the spleen or the mediastinal lymph node. All secondary lymphoid organs showed a similar intensity of PrP Sc -immunolabelling at 9 months of age. At this time-point, PrPSc was also detected in the autonomic myenteric nervous plexus and in the nucleus parasympathicus nervi X of the brain stem. These data suggest that natural scrapie infection occurs by the oral route via infection of the Peyer's patches followed by replication in the GALT. It may then spread to the central nervous system through the autonomic nervous fibres innervating the digestive tract.

Selection plans in plant and animal breeding are driven by genetic evaluation. Recent developments suggest using massive genetic marker information, known as ''genomic selection.'' There is little evidence of its performance, though. We empirically compared three strategies for selection: (1) use of pedigree and phenotypic information, (2) use of genomewide markers and phenotypic information, and (3) the combination of both. We analyzed four traits from a heterogeneous mouse population (http:/ / gscan.well.ox.ac.uk/), including 1884 individuals and 10,946 SNP markers. We used linear mixed models, using extensions of association analysis. Cross-validation techniques were used, providing assumption-free estimates of predictive ability. Sampling of validation and training data sets was carried out across and within families, which allows comparing across-and within-family information. Use of genomewide genetic markers increased predictive ability up to 0.22 across families and up to 0.03 within families. The latter is not statistically significant. These values are roughly comparable to increases of up to 0.57 (across family) and 0.14 (within family) in accuracy of prediction of genetic value. In this data set, within-family information was more accurate than across-family information, and populational linkage disequilibrium was not a completely accurate source of information for genetic evaluation. This fact questions some applications of genomic selection.T HIS work evaluates the empirical performance of the so-called genomewide selection strategy for markerassisted selection (MAS) in a mouse population, using massive molecular marker information. MAS techniques are advocated as a tool for more efficient selection schemes in plant and animal populations (Dekkers and Hospital 2002). In general, MAS techniques are based on tracing the inheritance of the quantitative trait loci (QTL) of interest throughout the pedigree with the help of molecular markers. However, the use of MAS techniques in animal populations is still not much extended, because of its complexity in practice (Boichard et al. 2006) and relatively small additional gains. For example, Chamberlain and Goddard (2006) estimated by cross-validation an increase in prediction accuracy over pedigree index (no use of MAS) of, at best, 0.02. Recent developments in massive single-nucleotide polymorphism (SNP) marker genotyping increased the interest for MAS techniques. Dense marker maps capture much richer information, including not only recombination events in the genotyped pedigree (i.e., linkage analysis) but also the populational linkage disequilibrium pattern in the genome, i.e., the possibility of predicting alleles at some loci on the basis of alleles in other (possibly close) loci. This allows for a much finer description of the genome.

Ewes from the Booroola strain of Australian Mé rino sheep are characterized by high ovulation rate and litter size. This phenotype is due to the action of the FecB B allele of a major gene named FecB, as determined by statistical analysis of phenotypic data. By genetic analysis of 31 informative half-sib families from heterozygous sires, we showed that the FecB locus is situated in the region of ovine chromosome 6 corresponding to the human chromosome 4q22-23 that contains the bone morphogenetic protein receptor IB (BMPR-IB) gene encoding a member of the transforming growth factor-␤ (TGF-␤) receptor family. A nonconservative substitution (Q249R) in the BMPR-IB coding sequence was found to be associated fully with the hyperprolificacy phenotype of Booroola ewes. In vitro, ovarian granulosa cells from FecB B ͞FecB B ewes were less responsive than granulosa cells from FecB ؉ ͞FecB ؉ ewes to the inhibitory effect on steroidogenesis of GDF-5 and BMP-4, natural ligands of BMPR-IB. It is suggested that in FecB B ͞FecB B ewes, BMPR-IB would be inactivated partially, leading to an advanced differentiation of granulosa cells and an advanced maturation of ovulatory follicles.