Assessment of milk metabolites as biomarkers for predicting feed efficiency in dairy sheep

Estimating feed efficiency (FE) in dairy sheep is challenging due to the high cost of systems that measure individual feed intake. Identifying proxies that can serve as effective predictors of FE could make it possible to introduce FE into breeding programs. Here, 39 Assaf ewes in first lactation were evaluated regarding their FE by 2 metrics, residual feed intake (RFI) and feed conversion ratio (FCR). The ewes were classified into high, medium and low groups for each metric. Milk samples of the 39 ewes were subjected to untargeted metabolomics analysis. The complete milk metabolomic signature was used to discriminate the FE groups using partial least squares discriminant analysis. A total of 41 and 26 features were selected as the most relevant features for the discrimination of RFI and FCR groups, respectively. The predictive ability when utilizing the complete milk metabolomic signature and the reduced data sets were investigated using 4 machine-learning algorithms and a multivariate regression method. The Orthogonal Partial Least Square algorithm outperformed other ML algorithms for the FCR prediction in the scenarios using the complete milk metabolite signature (r2 = 0.62 ± 0.06) and the 26 selected features (0.62 ± 0.15). Regarding RFI predictions, the scenarios using the 41 selected features outperformed the scenario with the complete milk metabolite signature, where the Multilayer feedforward artificial neural network (r2 = 0.18 ± 0.14) and extreme gradient boosting (r2 = 0.17 ± 0.15) outperformed other algorithms. The functionality of the selected metabolites implied that the metabolism of glucose, galactose, fructose, sphingolipids, amino acids, insulin, and thyroid hormones was at play. Compared with the use of traditional methods, practical applications of these biomarkers might simplify and reduce costs in selecting feed-efficient ewes.

Epigenetic regulation of functional candidate genes for milk production traits in dairy sheep subjected to protein restriction in the prepubertal stage

BACKGROUND

As the prepubertal stage is a crucial point for the proper development of the mammary gland and milk production, this study aims to evaluate how protein restriction at this stage can affect methylation marks in milk somatic cells. Here, 28 Assaf ewes were subjected to 42.3% nutritional protein restriction (14 animals, NPR) or fed standard diets (14 animals, C) during the prepubertal stage. During the second lactation, the milk somatic cells of these ewes were sampled, and the extracted DNA was subjected to whole-genome bisulfite sequencing.

RESULTS

A total of 1154 differentially methylated regions (DMRs) were identified between the NPR and C groups. Indeed, the results of functional enrichment analyses of the genes harboring these DMRs suggested their relevant effects on the development of the mammary gland and lipid metabolism in sheep. The additional analysis of the correlations of the mean methylation levels within these DMRs with fat, protein, and dry extract percentages in the milk and milk somatic cell counts suggested associations between several DMRs and milk production traits. However, there were no phenotypic differences in these traits between the NPR and C groups.

CONCLUSION

In light of the above, the results obtained in the current study might suggest potential candidate genes for the regulation of milk production traits in the sheep mammary gland. Further studies focusing on elucidating the genetic mechanisms affected by the identified DMRs may help to better understand the biological mechanisms modified in the mammary gland of dairy sheep as a response to nutritional challenges and their potential effects on milk production.

Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep

The present study aimed to ascertain how different strategies for leveraging genomic information enhance the accuracy of estimated breeding values for milk and cheese-making traits and to evaluate the implementation of a low-density (LowD) SNP chip designed explicitly for that aim. Thus, milk samples from a total of 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra) were collected and analyzed to determine 3 milk production and composition traits and 2 traits related to milk coagulation properties and cheese yield. The 2 studied populations were genotyped with a customized 50K Affymetrix SNP chip (Affymetrix Inc.) containing 55,627 SNP markers. The prediction accuracies were obtained using different multitrait methodologies, such as the BLUP model based on pedigree information, the genomic BLUP (GBLUP), and the BLUP at the SNP level (SNP-BLUP), which are based on genotypic data, and the single-step GBLUP (ssGBLUP), which combines both sources of information. All of these methods were analyzed by cross-validation, comparing predictions of the whole population with the test population sets. Additionally, we describe the design of a LowD SNP chip (3K) and its prediction accuracies through the different methods mentioned previously. Furthermore, the results obtained using the LowD SNP chip were compared with those based on the 50K SNP chip data sets. Finally, we conclude that implementing genomic selection through the ssGBLUP model in the current breeding programs would increase the accuracy of the estimated breeding values compared with the BLUP methodology in the Assaf (from 0.19 to 0.39) and Churra (from 0.27 to 0.44) dairy sheep populations. The LowD SNP chip is cost-effective and has proven to be an accurate tool for estimating genomic breeding values for milk and cheese-making traits, microsatellite imputation, and parentage verification. The results presented here suggest that the routine use of this LowD SNP chip could potentially increase the genetic gains of the breeding selection programs of the 2 Spanish dairy sheep breeds considered here.

Study on the concordance between different SNP-genotyping platforms in sheep

Different SNP genotyping technologies are commonly used in multiple studies to perform QTL detection, genotype imputation, and genomic predictions. Therefore, genotyping errors cannot be ignored, as they can reduce the accuracy of different procedures applied in genomic selection, such as genomic imputation, genomic predictions, and false-positive results in genome-wide association studies. Currently, whole-genome resequencing (WGR) also offers the potential for variant calling analysis and high-throughput genotyping. WGR might overshadow array-based genotyping technologies due to the larger amount and precision of the genomic information provided; however, its comparatively higher price per individual still limits its use in larger populations. Thus, the objective of this work was to evaluate the accuracy of the two most popular SNP-chip technologies, namely, Affymetrix and Illumina, for high-throughput genotyping in sheep considering high-coverage WGR datasets as references. Analyses were performed using two reference sheep genome assemblies, the popular Oar_v3.1 reference genome and the latest available version Oar_rambouillet_v1.0. Our results demonstrate that the genotypes from both platforms are suggested to have high concordance rates with the genotypes determined from reference WGR datasets (96.59% and 99.51% for Affymetrix and Illumina technologies, respectively). The concordance results provided in the current study can pinpoint low reproducible markers across multiple platforms used for sheep genotyping data. Comparing results using two reference genome assemblies also informs how genome assembly quality can influence genotype concordance rates among different genotyping platforms. Moreover, we describe an efficient pipeline to test the reliability of markers included in sheep SNP-chip panels against WGR datasets available on public databases. This pipeline may be helpful for discarding low-reliability markers before exploiting genomic information for gene mapping analyses or genomic prediction.

Genome-wide association studies (GWAS) and post-GWAS analyses for technological traits in Assaf and Churra dairy breeds

This study aimed to perform a GWAS to identify genomic regions associated with milk and cheese-making traits in Assaf and Churra dairy sheep breeds; second, it aimed to identify possible positional and functional candidate genes and their interactions through post-GWAS studies. For 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra), milk samples were collected and analyzed to determine 6 milk production and composition traits and 6 traits related to milk coagulation properties and cheese yield. The genetic profiles of the ewes were obtained using a genotyping chip array that included 50,934 SNP markers. For both milk and cheese-making traits, separate single-breed GWAS were performed using GCTA software. The set of positional candidate genes identified via GWAS was subjected to guilt-by-association-based prioritization analysis with ToppGene software. Totals of 84 and 139 chromosome-wise significant associations for the 6 milk traits and the 6 cheese-making traits were identified in this study. No significant SNPs were found in common between the 2 studied breeds, possibly due to their genetic heterogeneity of the phenotypes under study. Additionally, 63 and 176 positional candidate genes were located in the genomic intervals defined as confidence regions in relation to the significant SNPs identified for the analyzed traits for Assaf and Churra breeds. After the functional prioritization analysis, 71 genes were identified as promising positional and functional candidate genes and proposed as targets of future research to identify putative causative variants in relation to the traits under examination. In addition, this multitrait study allowed us to identify variants that have a pleiotropic effect on both milk production and cheese-related traits. The incorporation of variants among the proposed functional and positional candidate genes into genomic selection strategies represent an interesting approach for achieving rapid genetic gains, specifically for those traits difficult to measure, such as cheese-making traits.

Estimation of genetic parameters for cheese-making traits in Spanish Churra sheep

The global production of sheep milk is growing, and the main industrial use of sheep milk is cheese making. The Spanish Churra sheep breed is one of the most important native dairy breeds in Spain. The present study aimed to estimate genetic parameters for a wide range of traits influencing the cheese-making ability of Churra sheep milk. Using a total of 1,049 Churra ewes, we studied the following cheese-making traits: 4 traits related to milk coagulation properties (rennet coagulation time, curd-firming time, and curd firmness at 30 and 60 min after addition of rennet), 2 traits related to cheese yield (individual laboratory cheese yield and individual laboratory dried curd yield), and 3 traits measuring curd firmness over time (maximum curd firmness, time to attain maximum curd firmness, and syneresis). In addition, a list of milk traits, including the native pH of the milk and several milk production and composition traits (milk yield; the fat, protein, and dried extract percentages; and the somatic cell count), were also analyzed for the studied animals. After discarding the noncoagulating samples (only 3.7%), data of 1,010 ewes were analyzed with multiple-trait animal models by using the restricted maximum likelihood method to estimate (co)variance components, heritabilities, and genetic correlations. In general, the heritability estimates were low to moderate, ranging from 0.08 (for the individual laboratory dried curd yield trait) to 0.42 (for the fat percentage trait). High genetic correlations were found within pairs of related traits (i.e., 0.93 between fat and dried extract percentages, -0.93 between the log of the curd-firming time and curd firmness at 30 min, 0.70 between individual laboratory cheese yield and individual laboratory dried curd yield, and -0.94 between time to attain maximum curd firmness and syneresis). Considering all the information provided here, we suggest that in addition to the current consideration of the protein percentage trait for improving cheese yield traits, the inclusion of the pH of milk as a measured trait in the Churra dairy breeding program would represent an efficient strategy for improving the cheese-making ability of milk from this breed.

Identification of potential functional variants underlying ovine resistance to gastrointestinal nematode infection by using RNA-Seq

In dairy sheep flocks from Mediterranean countries, replacement and adult ewes are the animals most affected by gastrointestinal nematode (GIN) infections. In this study, we have exploited the information derived from an RNA-Seq experiment with the aim of identifying potential causal mutations related to GIN resistance in sheep. Considering the RNA-Seq samples from 12 ewes previously classified as six resistant and six susceptible animals to experimental infection by Teladorsagia circumcincta, we performed a variant calling analysis pipeline using two different types of software, gatk version 3.7 and Samtools version 1.4. The variants commonly identified by the two packages (high-quality variants) within two types of target regions - (i) QTL regions previously reported in sheep for parasite resistance based on SNP-chip or sequencing technology studies and (ii) functional candidate genes selected from gene expression studies related to GIN resistance in sheep - were further characterised to identify mutations with a potential functional impact. Among the genes harbouring these potential functional variants (930 and 553 respectively for the two types of regions), we identified 111 immune-related genes in the QTL regions and 132 immune-related genes from the initially selected candidate genes. For these immune-related genes harbouring potential functional variants, the enrichment analyses performed highlighted significant GO terms related to apoptosis, adhesion and inflammatory response, in relation to the QTL related variants, and significant disease-related terms such as inflammation, adhesion and necrosis, in relation to the initial candidate gene list. Overall, the study provides a valuable list of potential causal mutations that could be considered as candidate causal mutations in relation to GIN resistance in sheep. Future studies should assess the role of these suggested mutations with the aim of identifying genetic markers that could be directly implemented in sheep breeding programmes considering not only production traits, but also functional traits such as resistance to GIN infections.

Early adipose deposits in sheep: comparative analysis of the perirenal fat transcriptome of Assaf and Churra suckling lambs

Adipose deposits influence the quality of ruminant carcasses, and in suckling lambs, internal types of adipose deposits represent a notable proportion of total fat. The aim of this study was to perform a comparative analysis of the perirenal fat transcriptomes of suckling lambs from two breeds with different growth and carcass characteristics. The perirenal fat tissue from 14 suckling lambs (Assaf, n = 8; Churra, n = 6) was used for the RNA-seq analysis. The functional enrichment analysis of the 670 highly expressed genes (>150 fragments per kilobase of exon per million fragments mapped) in the perirenal fat transcriptome of both breeds revealed that the majority of these genes were involved in energy processes. The expression of the UCP1 gene, a classical biomarker of brown fat, and the presence of multilocular adipocytes in the two breeds supported the presence of brown fat at the transition stage towards white fat tissue. The differential expression analysis performed identified 373 differentially expressed genes (DEGs) between the two compared breeds. Brown/white fat gene biomarkers were not included in the list of DEGs. In Assaf lambs, DEGs were enriched in Gene Ontology (GO) biological processes related to fatty-acid oxidation, whereas in Churra lambs, the majority of the significantly enriched GO terms were related to cholesterol synthesis, which suggests that upregulated DEGs in Assaf lambs are implicated in fat burning, whereas the Churra upregulated DEGs are linked to fat accumulation. These results can help to increase knowledge of the genes controlling early fat deposition in ruminants and shed light on fundamental aspects of adipose tissue growth.

Detection of quantitative trait loci and putative causal variants affecting somatic cell score in dairy sheep by using a 50K SNP chip and whole-genome sequencing

This study presents a scan of the ovine genome to identify quantitative trait loci (QTL) influencing the somatic cell score (SCS), a classical indicator of subclinical mastitis in sheep, and a subsequent high-resolution analysis of one of the identified QTL regions based on the analysis of whole-genome sequence data sets. A half-sib commercial population of Churra sheep genotyped with a 50K SNP chip was analyzed using linkage analysis (LA) and combined linkage and linkage disequilibrium analysis (LDLA). By LA, 2 5% chromosome-wide significant QTL on OAR5 and OAR25 and one 5% genome-wide significant QTL on ovine chromosome 20 (OAR20) were detected, whereas 22 significant associations were identified by LDLA. Two of the associations detected by LDLA replicated LA-detected effects (OAR20, OAR25). We compared the detected associations with previously reported QTL in sheep and cattle, and functional candidate genes were identified within the estimated confidence intervals. We then performed a high-resolution analysis of the OAR20 QTL region, the most significant QTL region identified by LA that replicated a QTL previously described in Churra sheep for SCS using microsatellite markers. For that, 2 segregating trios of 2 segregating families for the OAR20 QTL (each including the Qq sire and 2 daughters, QQ and qq) were selected for whole-genome sequencing. The bioinformatic analysis of the 6 sequenced samples performed across the genomic interval considered (14.2-41.7 Mb) identified a total of 227,030 variants commonly identified by 2 independent software packages. For the 3 different concordance tests considered, due to discrepancies regarding the QTL peak in the segregating families, the list of mutations concordant with the QTL segregating pattern was processed to identify the variants identified in immune-related genes that show a moderate/high impact on the encoded protein function. Among a list of 85 missense variants concordant with the QTL segregation pattern that were within candidate immune-related genes, 13 variants distributed across 7 genes [PKHD1, NOTCH4, AGER, ENSOARG00000009395 (HLA-C, Homo sapiens), ENSOARG00000015002 (HLA-B, H. sapiens), MOG, and ENSOARG00000018075 (BoLA, Bos taurus, orthologous to human HLA-A] were predicted to cause deleterious effects on protein function. Future studies should assess the possible associations of the candidate variants identified herein in commercial populations with indicator traits of udder inflammation (SCS, clinical mastitis).

Implementation of an extended ZINB model in the study of low levels of natural gastrointestinal nematode infections in adult sheep

Background

In this study, two traits related with resistance to gastrointestinal nematodes (GIN) were measured in 529 adult sheep: faecal egg count (FEC) and activity of immunoglobulin A in plasma (IgA). In dry years, FEC can be very low in semi-extensive systems, such as the one studied here, which makes identifying animals that are resistant or susceptible to infection a difficult task. A zero inflated negative binomial model (ZINB) model was used to calculate the extent of zero inflation for FEC; the model was extended to include information from the IgA responses.

Results

In this dataset, 64 % of animals had zero FEC while the ZINB model suggested that 38 % of sheep had not been recently infected with GIN. Therefore 26 % of sheep were predicted to be infected animals with egg counts that were zero or below the detection limit and likely to be relatively resistant to nematode infection. IgA activities of all animals were then used to decide which of the sheep with zero egg counts had been exposed and which sheep had not been recently exposed. Animals with zero FEC and high IgA activity were considered resistant while animals with zero FEC and low IgA activity were considered as not recently infected. For the animals considered as exposed to the infection, the correlations among the studied traits were estimated, and the influence of these traits on the discrimination between unexposed and infected animals was assessed.

Conclusions

The model presented here improved the detection of infected animals with zero FEC. The correlations calculated here will be useful in the development of a reliable index of GIN resistance that could be of assistance for the study of host resistance in studies based on natural infection, especially in adult sheep, and also the design of breeding programs aimed at increasing resistance to parasites.

Electronic supplementary material

The online version of this article (doi:10.1186/s12917-016-0723-7) contains supplementary material, which is available to authorized users.

Transcriptome expression analysis of candidate milk genes affecting cheese-related traits in 2 sheep breeds

Because ewe milk is principally used for cheese making, its quality is related to its content of total solids and the way in which milk constituents influence cheese yield and determine the technological and organoleptic characteristics of dairy products. Therefore, an in-depth knowledge of the expression levels of milk genes influencing cheese-related traits is essential. In the present study, the milk transcriptome data set of 2 dairy sheep breeds, Assaf and Spanish Churra, was used to evaluate the expression levels of 77 transcripts related to cheese yield and quality traits. For the comparison between both breeds, we selected the RNA sequencing (RNA-Seq) data at d 10 of lactation because this is the time point at which within and between breed differences due to lactation length are minimal. The evaluated genes encode major milk proteins (caseins and whey proteins), endogenous proteases, and enzymes related to fatty acid metabolism and citrate content. Through this analysis, we identified the genes predominantly expressed in each of the analyzed pathways that appear to be key genes for traits related to sheep milk cheese. Among the highly expressed genes in both breeds were the genes encoding caseins and whey proteins (CSN2, CSN3, CSN1S1, ENSOARG00000005099/PAEP, CSN1S2, LALBA), genes related to lipid metabolism (BTN1A1, XDH, FASN, ADFP, SCD, H-FABP, ACSS2), and one endogenous protease (CTSB). Moreover, a differential expression analysis between Churra and Assaf sheep allowed us to identify 7 genes that are significantly differentially expressed between the 2 breeds. These genes were mainly linked to endogenous protease activity (CTSL, CTSK, KLK10, KLK6, SERPINE2). Additionally, there were 2 differentially expressed genes coding for an intracellular fatty acid transporter (FABP4), an intermediate molecule of the citric acid cycle (SUCNR1), and 2 heat shock proteins (HSP70, HSPB8) that could be related to high protein production. The differential expression of these genes could have a direct influence on the different phenotypes observed between the 2 analyzed breeds.

Identification of quantitative trait loci underlying milk traits in Spanish dairy sheep using linkage plus combined linkage disequilibrium and linkage analysis approaches

In this study, 2 procedures were used to analyze a data set from a whole-genome scan, one based on linkage analysis information and the other combing linkage disequilibrium and linkage analysis (LDLA), to determine the quantitative trait loci (QTL) influencing milk production traits in sheep. A total of 1,696 animals from 16 half-sib families were genotyped using the OvineSNP50 BeadChip (Illumina Inc., San Diego, CA) and analysis was performed using a daughter design. Moreover, the same data set has been previously investigated through a genome-wide association (GWA) analysis and a comparison of results from the 3 methods has been possible. The linkage analysis and LDLA methodologies yielded different results, although some significantly associated regions were common to both procedures. The linkage analysis detected 3 overlapping genome-wise significant QTL on sheep chromosome (OAR) 2 influencing milk yield, protein yield, and fat yield, whereas 34 genome-wise significant QTL regions were detected using the LDLA approach. The most significant QTL for protein and fat percentages was detected on OAR3, which was reported in a previous GWA analysis. Both the linkage analysis and LDLA identified many other chromosome-wise significant associations across different sheep autosomes. Additional analyses were performed on OAR2 and OAR3 to determine the possible causality of the most significant polymorphisms identified for these genetic effects by the previously reported GWA analysis. For OAR3, the analyses demonstrated additional genetic proof of the causality previously suggested by our group for a single nucleotide polymorphism located in the α-lactalbumin gene (LALBA). In summary, although the results shown here suggest that in commercial dairy populations, the LDLA method exhibits a higher efficiency to map QTL than the simple linkage analysis or linkage disequilibrium methods, we believe that comparing the 3 analysis methods is the best approach to obtain a global picture of all identifiable QTL segregating in the population at both family-based and population-based levels.

Analysis of genetic diversity in Bolivian llama populations using microsatellites

South American camelids (SACs) have a major role in the maintenance and potential future of rural Andean human populations. More than 60% of the 3.7 million llamas living worldwide are found in Bolivia. Due to the lack of studies focusing on genetic diversity in Bolivian llamas, this analysis investigates both the genetic diversity and structure of 12 regional groups of llamas that span the greater part of the range of distribution for this species in Bolivia. The analysis of 42 microsatellite markers in the considered regional groups showed that, in general, there were high levels of polymorphism (a total of 506 detected alleles; average PIC across per marker: 0.66), which are comparable with those reported for other populations of domestic SACs. The estimated diversity parameters indicated that there was high intrapopulational genetic variation (average number of alleles and average expected heterozygosity per marker: 12.04 and 0.68, respectively) and weak genetic differentiation among populations (FST range: 0.003-0.052). In agreement with these estimates, Bolivian llamas showed a weak genetic structure and an intense gene flow between all the studied regional groups, which is due to the exchange of reproductive males between the different flocks. Interestingly, the groups for which the largest pairwise FST estimates were observed, Sud Lípez and Nor Lípez, showed a certain level of genetic differentiation that is probably due to the pattern of geographic isolation and limited communication infrastructures of these southern localities. Overall, the population parameters reported here may serve as a reference when establishing conservation policies that address Bolivian llama populations.

Analysis of mitochondrial DNA in Bolivian llama, alpaca and vicuna populations: a contribution to the phylogeny of the South American camelids

The objectives of this work were to assess the mtDNA diversity of Bolivian South American camelid (SAC) populations and to shed light on the evolutionary relationships between the Bolivian camelids and other populations of SACs. We have analysed two different mtDNA regions: the complete coding region of the MT-CYB gene and 513 bp of the D-loop region. The populations sampled included Bolivian llamas, alpacas and vicunas, and Chilean guanacos. High levels of genetic diversity were observed in the studied populations. In general, MT-CYB was more variable than D-loop. On a species level, the vicunas showed the lowest genetic variability, followed by the guanacos, alpacas and llamas. Phylogenetic analyses performed by including additional available mtDNA sequences from the studied species confirmed the existence of the two monophyletic clades previously described by other authors for guanacos (G) and vicunas (V). Significant levels of mtDNA hybridization were found in the domestic species. Our sequence analyses revealed significant sequence divergence within clade G, and some of the Bolivian llamas grouped with the majority of the southern guanacos. This finding supports the existence of more than the one llama domestication centre in South America previously suggested on the basis of archaeozoological evidence. Additionally, analysis of D-loop sequences revealed two new matrilineal lineages that are distinct from the previously reported G and V clades. The results presented here represent the first report on the population structure and genetic variability of Bolivian camelids and may help to elucidate the complex and dynamic domestication process of SAC populations.

Investigation of the genetic architecture of a bone carcass weight QTL on BTA6

A previous analysis of an F(2) /Backcross Charolais × Holstein cross population identified the presence of a highly significant QTL on chromosome 6 (BTA6) affecting the proportion of bone in the carcass. Two closely linked QTL affected birth weight (BW) and body length at birth (BBL). In this report, the marker density around the QTL on BTA6 was increased, adding four additional microsatellite markers across the chromosome and 46 SNPs within the target QTL confidence interval. Of the SNPs, 26 were in positional candidate genes and the remaining 20 provided an even distribution of markers in the target QTL region. As a bone-related trait, the sum of the bone weight for all the left fore- and hindquarter joints of the carcass was analysed. We also studied the BW and BBL. Analyses of the data substantially reduced the QTL confidence interval. No strong evidence was found that the QTL for the three traits studied are different, and we conclude that the results are consistent with a single pleiotropic QTL influencing the three traits, with the largest effects on the proportion of bone in the carcass. The analyses also suggest that none of the SNPs tested is the sole causative variant of the QTL effects. Specifically, the SNP in the NCAPG gene previously reported as a causal mutation for foetal growth and carcass traits in other cattle populations was excluded as the causal mutation for the QTL reported here. Polymorphisms located in other previously identified candidate genes including SPP1, ABCG2, IBSP, MEPE and PPARGC1A were also excluded. The results suggest that SNP51_BTA-119876 is the polymorphism in strongest linkage disequilibrium with the causal mutation(s). Further research is required to identify the causal variant(s) associated with this bone-related QTL.

Replication and refinement of a quantitative trait locus influencing milk protein percentage on ovine chromosome 3

A previous genome scan that was conducted in Spanish Churra sheep identified a significant quantitative trait locus (QTL) for milk protein percentage (PP) on chromosome 3 (OAR3), between markers KD103 and OARVH34. The aim of this study was to replicate these results and to refine the mapped position of this QTL. To accomplish this goal, we analysed 14 new half-sib families of Spanish Churra sheep including 1661 ewes from 29 different flocks. These animals were genotyped for 21 microsatellite markers mapping to OAR3. In addition to a classical linkage analysis (LA), a combined linkage disequilibrium and linkage analysis (LDLA) was performed with the aim of enhancing the resolution of the QTL mapping. The LA that was performed in this sheep population identified the presence of a highly significant QTL for PP near marker KD103 (P(c) < 0.001; P(exp) < 0.001). The phenotypic variance that was owing to the QTL was 2.74%. Two segregating families for the target QTL were identified in this population with QTL effect estimates of 0.47 and 0.95 SD. The LDLA identified the same QTL as the previous analyses with a high level of statistical significance (P = 9.184 E-11) and narrowed the confidence interval (CI) to a 13 cM region. These results confirm the segregation of the previously identified OAR3 QTL that influences PP in Spanish Churra sheep. Future research will aim to increase the marker density across the refined CI and to analyse the corresponding candidate genes to identify the allelic variant or variants that underlie this genetic effect.

The role of bovine causal genes underlying dairy traits in Spanish Churra sheep

In dairy cattle, quantitative trait nucleotides (QTNs) underlying quantitative trait loci (QTL) for milk production traits have been identified in bovine DGAT1, GHR and ABCG2 genes. The SPP1 gene has also been proposed to be a regulator of lactation. In sheep, QTL underlying milk production traits have been reported only recently, and no proven QTN has been identified. Taking into account the close phylogenetic relationship between sheep and cattle, this study examined the possible effects of the aforementioned genes on sheep milk production traits. We first studied the genetic variability of the DGAT1, GHR, ABCG2 and SPP1 genes in 15 rams of the Spanish Churra dairy sheep breed. Second, we performed an association analysis between SNPs identified in these genes and three milk production traits recorded in a commercial population of Churra sheep. This analysis revealed only three significant associations at the nominal level (P-value <0.05) involving allelic variants of the ABCG2 gene, whereas no significant association was found for the DGAT1, GHR and SPP1 genes. When the Bonferroni correction was applied to take into account the multiple tests performed, none of the associations identified at the nominal level remained significant. Nevertheless, taking into account the high level of false-negative findings that can arise when applying the stringent Bonferroni correction, we think that our results provide a valuable primary assessment of strong candidate genes for milk traits in sheep.

Detection of quantitative trait loci affecting the milk fatty acid profile on sheep chromosome 22: role of the stearoyl-CoA desaturase gene in Spanish Churra sheep

Sheep milk fat contains several components that may provide human health benefits, such as monounsaturated fatty acids and conjugated linoleic acid (CLA). Most of the CLA in ruminant milk is synthesized in the mammary gland by the action of the enzyme stearoyl-CoA desaturase (SCD) on circulating vaccenic acid (trans-11 C18:2; VA). Previous studies have found significant associations between polymorphisms in the SCD gene and the fatty acid composition of ruminant products, including sheep milk. Based on this, we performed a quantitative trait loci (QTL) analysis of an ovine chromosome (22) that harbors the SCD gene for effects on milk fatty acid composition traits and classical milk production traits. We identified a suggestive QTL influencing the CLA/VA ratio with the maximum statistic at position 26 cM of the studied chromosome, whereas the SCD gene has been mapped to position 41.6 cM. The individual introduction of 4 SCD single nucleotide polymorphisms in the QTL model did not cause a reduction of the variance explained by the QTL, which suggests that the SCD gene is not directly responsible for the detected effect in the Churra population studied herein. This conclusion was supported by the lack of any significant association identified between the 4 SCD single nucleotide polymorphisms and the CLA/VA ratio. This association analysis suggested a possible effect of the SCD gene on milk fat percentage in Churra sheep. An independent confirmation of these primary results will be required before attempting its practical implementation in selection programs.

The identification of QTL that affect the fatty acid composition of milk on sheep chromosome 11

In this work, we analysed 11 genetic markers localized on OAR11 in a commercial population of Spanish Churra sheep to detect QTL that underlie milk fatty acid (FA) composition traits. Following a daughter design, we analysed 799 ewes distributed in 15 half-sib families. Eight microsatellite markers and three novel SNPs identified in two genes related to fatty acid metabolism, acetyl-CoA carboxylase alpha (ACACA) and fatty acid synthase (FASN), were genotyped in the whole population under study. The phenotypic traits considered in the study included 22 measurements related to the FA composition of the milk and three other milk production traits (milk protein percentage, milk fat percentage and milk yield). Across-family regression analysis revealed four significant QTL at the 5% chromosome-wise level influencing contents of capric acid (C10:0), lauric acid (C12:0), linoleic conjugated acid (CLA) and polyunsaturated fatty acids (PUFA) respectively. The peaks of the QTL affecting C10:0 and PUFA contents in milk map close to the FASN gene, which has been evaluated as a putative positional candidate for these QTL. The QTL influencing C12:0 content reaches its maximum significance at 58 cM, close to the gene coding for the glucose-dependent insulinotropic polypeptide. We were not able to find any candidate genes related to fat metabolism at the QTL influencing CLA content, which is located at the proximal end of the chromosome. Further research efforts will be needed to confirm and refine the QTL locations reported here.

Assessment of selection mapping near the myostatin gene (GDF-8) in cattle

Domestic species provide a unique opportunity to examine the effects of selection on the genome. The myostatin gene (GDF-8) has been under strong selection in a number of cattle breeds because of its influence on muscle conformation and association with the 'double-muscling' phenotype. This study examined genetic diversity near this gene in a set of breeds including some nearly fixed for the allele associated with double-muscling (MH), some where the allele is segregating at intermediate frequency and some where the allele is absent. A set of microsatellites and SNPs were used to examine patterns of diversity at the centromeric end of bovine chromosome 2, the region where GDF-8 is located, using various statistical methods. The putative position of a selected gene was moved across the genomic region to determine, by regression, a best position of reduced heterozygosity. Additional analyses examined extended homozygous regions and linkage disequilibrium patterns. While the SNP data was not found to be very informative for selection mapping in this dataset, analyses of the microsatellite data provided evidence of selection on GDF-8 in several breeds. These results suggested that, of the breeds examined, the allele was most recently introduced into the South Devon. Limitations to the selection-mapping approach were highlighted from the analysis of the SNP data and the situation where the MH allele was at intermediate frequency.

A male linkage map constructed for QTL mapping in Spanish Churra sheep

A male ovine linkage map has been constructed on the basis of 11 half-sib families of a commercial population of Spanish Churra sheep as part of a genome scan for quantitative trait loci mapping. A total of 1421 daughters and their sires were genotyped for 182 microsatellite markers evenly distributed along the ovine autosomes. A total of 259,192 genotypes were obtained, generating an average of 669 informative meioses per marker. An autosomal genome length of 3262 cM was estimated for the Churra population with a mean marker interval of 17.86 cM. Our map represents an approximate 90% coverage of the autosomal ovine genome and constitutes a useful tool for the genetic dissection of complex traits in this breed. General agreement was found between the Churra map and other published maps for sheep, despite certain length discrepancies.

Short communication: detection of quantitative trait loci influencing somatic cell score in Spanish Churra sheep

Eleven half-sib ovine families, including 1,421 Spanish Churra ewes, were analyzed for 181 microsatellite markers spanning the entire autosomic ovine genome. Using a multimarker regression method, a daughter experimental design was used to identify putative quantitative trait loci (QTL) affecting the somatic cell score (SCS). Chromosome-wise significance thresholds were set empirically by permuting the phenotypic data. Marker order and genetic distances of the autosomic linkage map built for this commercial population were in accordance with the published ovine linkage map. An across-family association analysis revealed a region on chromosome 20 suggestive of evidence for a QTL. Segregation of the QTL into 2 families was inferred from the within-family analysis, and differences in the position of the suggested QTL were found between the 2 half-sib groups. This could be the result of incomplete information associated with the markers for the significant families. The location of the major histocompatibility complex in proximity to the across-family effect suggests this region may harbor a segregating QTL for the SCS in the Churra population. Studies in dairy cattle examining the SCS have reported linkage associations on corresponding bovine orthologous regions, supporting the validity of our findings.

Search for quantitative trait loci affecting growth and carcass traits in a cross population of beef and dairy cattle

A genome scan to detect QTL influencing growth and carcass-related traits was conducted in a Charolais x Holstein crossbred cattle population. Phenotypic measurements related to growth and carcass traits were made on the 235 second-generation crossbred males of this herd (F2 and reciprocal backcrosses), which were born in 4 consecutive annual cohorts. Traits measured in vivo were related to birth dimensions, growth rates, and ultrasound measurements of fat and muscle depth. The animals were slaughtered near a target BW of 550 kg, and a wide range of postmortem traits were measured: visual assessment of carcass conformation and carcass fatness, estimated subcutaneous fat percentage, weights of kidney knob and channel fat, and weights of carcass components after commercial and full-tissue dissections. The whole population, including grandparents, parents, and the crossbred bulls, was genotyped initially for 139 genome-wide microsatellite markers. Twenty-six additional markers were subsequently analyzed to increase marker density on some of the chromosomes where QTL had been initially identified. The linear regression analyses based on the 165 markers revealed a total of 51 significant QTL at the suggestive level, 21 of which were highly significant (F-value >or=9; based on the genome-wide thresholds obtained in the initial scan). A large proportion of the highly significant associations were found on chromosomes 5 and 6. The most highly significant QTL was localized between markers DIK1054 and DIK082 on chromosome 6 and explained about 20% of the phenotypic variance for the total bone proportion estimated after the commercial dissection. In the adjacent marker interval on this chromosome, 2 other highly significant QTL were found that explain about 30% of the phenotypic variance for birth dimension traits (BW and body length at birth). On chromosome 5, the most significant association influenced the lean:bone ratio at the forerib joint and was flanked by markers DIK4782 and BR2936. Other highly significant associations were detected on chromosomes 10 (estimated subcutaneous fat percentage), 11 (total saleable meat proportion), 16 (prehousing growth rate), and 22 (bone proportion at the leg joint). These results provide a useful starting point for the identification of the genes associated with traits of direct interest to the beef industry, using fine mapping or positional candidate gene approaches.

Detection of quantitative trait loci for meat quality traits in cattle

A whole-genome scan was carried out to detect quantitative trait loci (QTL) affecting sensory, organoleptic, physical and chemical properties of meat. The study used phenotypic data from 235 second-generation cross-bred bull calves of a Charolais x Holstein experimental population. Loin muscle samples were evaluated for yield force, intramuscular fat and nitrogen contents, myofibrillar fragmentation index, haem pigment concentration, moisture content and pH at 24 h postmortem. A sensory assessment was performed on grilled loin and roasted silverside joints by trained panellists. A linear regression analysis based on 165 markers revealed 35 QTL at the 5% chromosome-wide significance level (20 for sensory traits and 15 for physical and chemical traits), five of which were highly significant (F-value: > or =9). The most significant QTL was located on chromosome 6 (with the best likely position at 39 cM) and affected haem pigment concentration. The Holstein allele for this QTL was associated with an increase of 0.53 SD in the haem scores. A QTL for pH(24h) was identified on chromosome 14 (at 40 cM) and a QTL for moisture content was identified on chromosome 22 (at 21 cM). Two highly significant QTL were identified for sensory panel-assessed traits: beef odour intensity (grilled sample) on chromosome 10 (at 119 cM), and juiciness (roast sample) on chromosome 16 (at 70 cM). The proportion of phenotypic variance explained by the significant QTL ranged from 3.6% (for nitrogen content on chromosome 10) to 9.5% (for juiciness, roast sample on chromosome 16).

Influence of Prion Protein Genotypes on Milk Production Traits in Spanish Churra Sheep

The aim of this work was to analyze the possible relationships between milk production traits and prion protein genotypes in Spanish Churra sheep. For this purpose, 2 analyses were carried out. First, an association study was performed of the prion protein genotypes of 12,533 Churra ewes and their milk yield, protein percentage, fat percentage, and somatic cell score as phenotypes, followed by a quantitative trait loci screening on the chromosome where the prion protein gene was located in this population. The latter analysis was carried out using 8 genetic markers (7 microsatellites and the prion protein genotypes) spanning ovine chromosome 13 using a daughter design. Regarding genotype frequencies, the most frequent allele was ARQ (75.90%), which linked with a high susceptibility to scrapie, followed by the resistant haplotype, ARR (18.16 %). The frequency of the most susceptible allele, VRQ, was around 1%. No evidence of association or linkage between prion protein genotypes and milk traits has been detected in Churra sheep. These results indicate that increasing the ARR frequency in Churra population will not have an adverse effect on selection for milk traits included in the breeding objectives. However, the low allele frequencies for ARR should be considered in the initial stages to prevent possible bottlenecks in future genetic progress.