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1.  Phenotypic and genotypic background underlying variations in fatty acid composition and sensory parameters in European bovine breeds 
Background
Consuming moderate amounts of lean red meat as part of a balanced diet valuably contributes to intakes of essential nutrients. In this study, we merged phenotypic and genotypic information to characterize the variation in lipid profile and sensory parameters and to represent the diversity among 15 cattle populations. Correlations between fat content, organoleptic characteristics and lipid profiles were also investigated.
Methods
A sample of 436 largely unrelated purebred bulls belonging to 15 breeds and reared under comparable management conditions was analyzed. Phenotypic data -including fatness score, fat percentage, individual fatty acids (FA) profiles and sensory panel tests- and genotypic information from 11 polymorphisms was used.
Results
The correlation coefficients between muscle total lipid measurements and absolute vs. relative amounts of polyunsaturated FA (PUFA) were in opposite directions. Increasing carcass fat leads to an increasing amount of FAs in triglycerides, but at the same time the relative amount of PUFAs is decreasing, which is in concordance with the negative correlation obtained here between the percentage of PUFA and fat measurements, as well as the weaker correlation between total phospholipids and total lipid muscle content compared with neutral lipids. Concerning organoleptic characteristics, a negative correlation between flavour scores and the percentage of total PUFA, particularly to n-6 fraction, was found. The correlation between juiciness and texture is higher than with flavour scores. The distribution of SNPs plotted by principal components analysis (PCA) mainly reflects their known trait associations, although influenced by their specific breed allele frequencies.
Conclusions
The results presented here help to understand the phenotypic and genotypic background underlying variations in FA composition and sensory parameters between breeds. The wide range of traits and breeds studied, along with the genotypic information on polymorphisms previously associated with different lipid traits, provide a broad characterization of beef meat, which allows giving a better response to the variety of consumers’ preferences. Also, the development and implementation of low-density SNP panels with predictive value for economically important traits, such as those summarized here, may be used to improve production efficiency and meat quality in the beef industry.
doi:10.1186/2049-1891-5-20
PMCID: PMC4019361  PMID: 24735897
Bos taurus; Beef; Fatty acids; Omega-3; Genotype assisted selection
2.  The GENOTEND chip: a new tool to analyse gene expression in muscles of beef cattle for beef quality prediction 
Background
Previous research programmes have described muscle biochemical traits and gene expression levels associated with beef tenderness. One of our results concerning the DNAJA1 gene (an Hsp40) was patented. This study aims to confirm the relationships previously identified between two gene families (heat shock proteins and energy metabolism) and beef quality.
Results
We developed an Agilent chip with specific probes for bovine muscular genes. More than 3000 genes involved in muscle biology or meat quality were selected from genetic, proteomic or transcriptomic studies, or from scientific publications. As far as possible, several probes were used for each gene (e.g. 17 probes for DNAJA1). RNA from Longissimus thoracis muscle samples was hybridised on the chips. Muscles samples were from four groups of Charolais cattle: two groups of young bulls and two groups of steers slaughtered in two different years. Principal component analysis, simple correlation of gene expression levels with tenderness scores, and then multiple regression analysis provided the means to detect the genes within two families (heat shock proteins and energy metabolism) which were the most associated with beef tenderness. For the 25 Charolais young bulls slaughtered in year 1, expression levels of DNAJA1 and other genes of the HSP family were related to the initial or overall beef tenderness. Similarly, expression levels of genes involved in fat or energy metabolism were related with the initial or overall beef tenderness but in the year 1 and year 2 groups of young bulls only. Generally, the genes individually correlated with tenderness are not consistent across genders and years indicating the strong influence of rearing conditions on muscle characteristics related to beef quality. However, a group of HSP genes, which explained about 40% of the variability in tenderness in the group of 25 young bulls slaughtered in year 1 (considered as the reference group), was validated in the groups of 30 Charolais young bulls slaughtered in year 2, and in the 21 Charolais steers slaughtered in year 1, but not in the group of 19 steers slaughtered in year 2 which differ from the reference group by two factors (gender and year). When the first three groups of animals were analysed together, this subset of genes explained a 4-fold higher proportion of the variability in tenderness than muscle biochemical traits.
Conclusion
This study underlined the relevance of the GENOTEND chip to identify markers of beef quality, mainly by confirming previous results and by detecting other genes of the heat shock family as potential markers of beef quality. However, it was not always possible to extrapolate the relevance of these markers to all animal groups which differ by several factors (such as gender or environmental conditions of production) from the initial population of reference in which these markers were identified.
doi:10.1186/1746-6148-8-135
PMCID: PMC3438070  PMID: 22894653
Predictors; Beef; Tenderness; Array; Gene expression
3.  Cotranscription and intergenic splicing of the PPARG and TSEN2 genes in cattle 
BMC Genomics  2006;7:71.
Background
Intergenic splicing resulting in the combination of mRNAs sequences from distinct genes is a newly identified mechanism likely to contribute to protein diversity. Few cases have been described, most of them involving neighboring genes and thus suggesting a cotranscription event presumably due to transcriptional termination bypass.
Results
We identified bovine chimeric transcripts resulting from cotranscription and intergenic splicing of two neighboring genes, PPARG and TSEN2. These two genes encode the Peroxisome Proliferator Activated Receptors γ1 and γ2 and the tRNA Splicing Endonuclease 2 homolog and are situated in the same orientation about 50 kb apart on bovine chromosome 22q24. Their relative position is conserved in human and mouse. We identified two types of chimeric transcripts containing all but the last exon of the PPARG gene followed by all but the first exon of the TSEN2 gene. The two chimers differ by the presence/absence of an intermediate exon resulting from transcription of a LINE L2 sequence situated between the two genes. Both transcripts use canonical splice sites for all exons coming from both genes, as well as for the LINE L2 sequence. One of these transcripts harbors a premature STOP codon and the other encodes a putative chimeric protein combining most of the PPARγ protein and the entire TSEN2 protein, but we could not establish the existence of this protein.
Conclusion
By showing that both individual and chimeric transcripts are transcribed from PPARG and TSEN2, we demonstrated regulation of transcription termination. Further, the existence and functionality of a chimeric protein harboring active motifs that are a priori unrelated is hypothesized.
doi:10.1186/1471-2164-7-71
PMCID: PMC1450281  PMID: 16595010
4.  Combined analysis of data from two granddaughter designs: A simple strategy for QTL confirmation and increasing experimental power in dairy cattle 
A joint analysis of five paternal half-sib Holstein families that were part of two different granddaughter designs (ADR- or Inra-design) was carried out for five milk production traits and somatic cell score in order to conduct a QTL confirmation study and to increase the experimental power. Data were exchanged in a coded and standardised form. The combined data set (JOINT-design) consisted of on average 231 sires per grandsire. Genetic maps were calculated for 133 markers distributed over nine chromosomes. QTL analyses were performed separately for each design and each trait. The results revealed QTL for milk production on chromosome 14, for milk yield on chromosome 5, and for fat content on chromosome 19 in both the ADR- and the Inra-design (confirmed within this study). Some QTL could only be mapped in either the ADR- or in the Inra-design (not confirmed within this study). Additional QTL previously undetected in the single designs were mapped in the JOINT-design for fat yield (chromosome 19 and 26), protein yield (chromosome 26), protein content (chromosome 5), and somatic cell score (chromosome 2 and 19) with genomewide significance. This study demonstrated the potential benefits of a combined analysis of data from different granddaughter designs.
doi:10.1186/1297-9686-35-3-319
PMCID: PMC2732702  PMID: 12729552
QTL mapping; granddaughter design; combined analysis; QTL confirmation; dairy cattle
5.  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.
doi:10.1186/1297-9686-35-1-77
PMCID: PMC2732691  PMID: 12605852
dairy cattle; QTL detection; genetic marker; granddaughter design
6.  A first genotyping assay of French cattle breeds based on a new allele of the extension gene encoding the melanocortin-1 receptor (Mc1r) 
The seven transmembrane domain melanocortin-1 receptor (Mc1r) encoded by the coat color extension gene (E) plays a key role in the signaling pathway of melanin synthesis. Upon the binding of agonist (melanocortin hormone, α-MSH) or antagonist (Agouti protein) ligands, the melanosomal synthesis of eumelanin and/or phaeomelanin pigments is stimulated or inhibited, respectively. Different alleles of the extension gene were cloned from unrelated animals belonging to French cattle breeds and sequenced. The wild type E allele was mainly present in Normande cattle, the dominant ED allele in animals with black color (i.e. Holstein), whereas the recessive e allele was identified in homozygous animals exhibiting a more or less strong red coat color (Blonde d'Aquitaine, Charolaise, Limousine and Salers). A new allele, named E1, was found in either homozygous (E1/E1) or heterozygous (E1/E) individuals in Aubrac and Gasconne breeds. This allele displayed a 4 amino acid duplication (12 nucleotides) located within the third cytoplasmic loop of the receptor, a region known to interact with G proteins. A first genotyping assay of the main French cattle breeds is described based on these four extension alleles.
doi:10.1186/1297-9686-32-5-511
PMCID: PMC2706875  PMID: 14736379
cattle; genotyping; coat color; extension; polymorphism

Results 1-6 (6)