Marie-Yvonne Boscher

Detection of quantitative trait loci for growth and fatness in pigs.

A quantitative trait locus (QTL) analysis of growth and fatness data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. Six boars and 23 F1 sows, the progeny of six LW boars and six MS sows, produced 530 F2 males and 573 F2 females. Nine growth traits, i.e. body weight at birth and at 3, 10, 13, 17 and 22 weeks of age, average daily gain from birth to 3 weeks, from 3 to 10 weeks and from 10 to 22 weeks of age, as well as backfat thickness at 13, 17 and 22 weeks of age and at 40 and 60 kg live weight were analysed. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using two interval mapping methods: a line-cross (LC) regression method where founder lines were assumed to be fixed for different QTL alleles and a half-/full-sib (HFS) maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Both methods revealed highly significant gene effects for growth on chromosomes 1, 4 and 7 and for backfat thickness on chromosomes 1, 4, 5, 7 and X, and significant gene effects on chromosome 6 for growth and backfat thickness. Suggestive QTLs were also revealed by both methods on chromosomes 2 and 3 for growth and 2 for backfat thickness. Significant gene effects were detected for growth on chromosomes 11, 13, 14, 16 and 18 and for backfat thickness on chromosome 8, 10, 13 and 14. LW alleles were associated with high growth rate and low backfat thickness, except for those of chromosome 7 and to a lesser extent early-growth alleles on chromosomes 1 and 2 and backfat thickness alleles on chromosome 6.

Detection of genes influencing economic traits in three French dairy cattle breeds

A project of QTL detection was carried out in the French Holstein, Normande, and Montbéliarde dairy cattle breeds. This granddaughter design included 1 548 artificial insemination bulls distributed in 14 sire families and evaluated after a progeny-test for 24 traits (production, milk composition, persistency, type, fertility, mastitis resistance, and milking ease). These bulls were also genotyped for 169 genetic markers, mostly microsatellites. The QTL were analysed by within-sire linear regression of daughter yield deviations or deregressed proofs on the probability that the son receives one or the other paternal QTL allele, given the marker information. QTL were detected for all traits, including those with a low heritability. One hundred and twenty QTL with a chromosome-wise significance lower than 3% were tabulated. This threshold corresponded to a 15% false discovery rate. Amongst them, 32 were genome-wise significant. Estimates of their contribution to genetic variance ranged from 6 to 40%. Most substitution effects ranged from 0.6 to 1.0 genetic standard deviation. For a given QTL, only 1 to 5 families out of 14 were informative. The confidence intervals of the QTL locations were large and always greater than 20 cM. This experiment confirmed several already published QTL but most of them were original, particularly for non-production traits.

An assessment of European pig diversity using molecular markers: Partitioning of diversity among breeds

Genetic diversity within and between breeds (and lines) of pigs was investigated. The sample comprised 68 European domestic breeds (and lines), including 29 local breeds, 18 varieties of major international breeds, namely Duroc, Hampshire, Landrace, Large White and Piétrain, and 21 commercial lines either purebred or synthetic, to which the Chinese Meishan and a sample of European wild pig were added. On average 46 animals per breed were sampled (range 12–68). The genetic markers were microsatellites (50 loci) and AFLP (amplified fragment length polymorphism, 148 loci). The analysis of diversity showed that the local breeds accounted for 56% of the total European between-breed microsatellite diversity, and slightly less for AFLP, followed by commercial lines and international breeds. Conversely, the group of international breeds contributed most to within-breed diversity, followed by commercial lines and local breeds. Individual breed contributions to the overall European between- and within-breed diversity were estimated. The range in between-breed diversity contributions among the 68 breeds was 0.04–3.94% for microsatellites and 0.24–2.94% for AFLP. The within-breed diversity contributions varied very little for both types of markers, but microsatellite contributions were negatively correlated with the between-breed contributions, so care is needed in balancing the two types of contribution when making conservation decisions. By taking into account the risks of extinction of the 29 local breeds, a cryopreservation potential (priority) was estimated for each of them.

Impact of Selection for Digestive Efficiency on Microbiota Composition in the Chicken.

Objectives Feed efficiency and its digestive component, digestive efficiency, are key factors in the environmental impact and economic output of poultry production. The interaction between the host and intestinal microbiota has a crucial role in the determination of the ability of the bird to digest its food and to the birds’ feed efficiency. We therefore investigated the phenotypic and genetic relationships between birds’ efficiency and the composition of the cecal microbiota in a F2 cross between broiler lines divergently selected for their high or low digestive efficiency. Methods Analyses were performed on 144 birds with extreme feed efficiency values at 3 weeks, with feed conversion values of 1.41±0.05 and 2.02±0.04 in the efficient and non-efficient groups, respectively. The total numbers of Lactobacillus, L. salivarius, L. crispatus, C. coccoides, C. leptum and E. coli per gram of cecal content were measured. Results The two groups mainly differed in larger counts of Lactobacillus, L. salivarius and E. coli in less efficient birds. The equilibrium between bacterial groups was also affected, efficient birds showing higher C. leptum, C. coccoides and L. salivarius to E. coli ratios. The heritability of the composition of microbiota was also estimated and L. crispatus, C. leptum, and C. coccoides to E. coli ratios were moderately but significantly heritable (0.16 to 0.24). The coefficient of fecal digestive use of dry matter was genetically and positively correlated with L. crispatus, C. leptum, C. coccoides (0.50 to 0.76) and negatively with E. coli (-0.66). Lipid digestibility was negatively correlated with E. coli (-0.64), and AMEn positively correlated with C. coccoides and with the C. coccoides to Lactobacillus ratio (0.48 to 0.64). We also detected 14 Quantitative Trait Loci (QTL) for microbiota on the host genome, mostly on C. leptum and Lactobacillus. The QTL for C. leptum on GGA6 was close to genome-wide significance. This region mainly includes genes involved in anti-inflammatory responses and in the motility of the gastrointestinal tract.

Genetic determinism of bone and mineral metabolism in meat-type chickens: A QTL mapping study

Skeletal integrity in meat-type chickens is affected by many factors including rapid growth rate, nutrition and genetics. To investigate the genetic basis of bone and mineral metabolism, a QTL detection study was conducted in an intercross between two lines of meat-type chickens divergently selected for their high (D +) or low (D −) digestive efficiency. Tibia size (length, diameter, volume) and ash content were determined at 3 weeks of age as well as phosphorus (P) retention and plasma concentration. Heritability of these traits and their genetic correlations with digestive efficiency were estimated. A QTL mapping study was performed using 3379 SNP markers. Tibia size, weight, ash content and breaking strength were highly heritable (0.42 to 0.61). Relative tibia diameter and volume as well as P retention were strongly and positively genetically correlated with digestive efficiency (0.57 to 0.80). A total of 35 QTL were identified (9 for tibia weight, 13 for tibia size, 5 for bone strength, 5 for bone mineralization, 2 for plasma P concentration and 1 for P retention). Six QTL were genome-wide significant, and 3 QTL for tibia relative volume, weight and ash weight on chromosome 6 were fixed, the positive allele coming from the D-line. For two QTL for ash content on chromosome 18 and relative tibia length on chromosome 26, the confidence intervals were small enough to identify potential candidate genes. These findings support the evidence of multiple genetic loci controlling bone and mineral metabolism. The identification of candidate genes may provide new perspectives in the understanding of bone regulation, even beyond avian species.