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 (ML) algorithms and a multivariate regression method. The orthogonal partial least squares algorithm outperformed other ML algorithms for FCR prediction in the scenarios using the complete milk metabolite signature (R2 = 0.62 ± 0.06) and the 26 selected features (R2 = 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.

Low genome-wide homozygosity in 11 Spanish ovine breeds.

The population of Spanish sheep has decreased from 24 to 15 million heads in the last 75 years due to multiple social and economic factors. Such a demographic reduction might have caused an increase in homozygosity and inbreeding, thus limiting the viability of local breeds with excellent adaptations to harsh ecosystems. The main goal of our study was to investigate the homozygosity patterns of 11 Spanish ovine breeds and to elucidate the relationship of these Spanish breeds with reference populations from Europe, Africa and the Near East. By using Ovine SNP50 BeadChip data retrieved from previous publications, we have found that the majority of studied Spanish ovine breeds have close genetic relatedness with other European populations; the one exception is the Canaria de Pelo breed, which is similar to North African breeds. Our analysis has also demonstrated that, with few exceptions, the genomes of Spanish sheep harbor fewer than 50 runs of homozygosity (ROH) with a total length of less than 350 Mb. Moreover, the frequencies of very long ROH (>30 Mb) are very low, and the inbreeding coefficients (FROH ) are generally small (FROH  < 0.10), ranging from 0.008 (Rasa Aragonesa) to 0.086 (Canaria de Pelo). The low levels of homozygosity observed in the 11 Spanish sheep under analysis might be due to their extensive management and the high number of small to medium farms.

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).

Estimations of linkage disequilibrium, effective population size and ROH-based inbreeding coefficients in Spanish Churra sheep using imputed high-density SNP genotypes.

In this study, the availability of the Ovine HD SNP BeadChip (HD-chip) and the development of an imputation strategy provided an opportunity to further investigate the extent of linkage disequilibrium (LD) at short distances in the genome of the Spanish Churra dairy sheep breed. A population of 1686 animals, including 16 rams and their half-sib daughters, previously genotyped for the 50K-chip, was imputed to the HD-chip density based on a reference population of 335 individuals. After assessing the imputation accuracy for beagle v4.0 (0.922) and fimpute v2.2 (0.921) using a cross-validation approach, the imputed HD-chip genotypes obtained with beagle were used to update the estimates of LD and effective population size for the studied population. The imputed genotypes were also used to assess the degree of homozygosity by calculating runs of homozygosity and to obtain genomic-based inbreeding coefficients. The updated LD estimations provided evidence that the extent of LD in Churra sheep is even shorter than that reported based on the 50K-chip and is one of the shortest extents compared with other sheep breeds. Through different comparisons we have also assessed the impact of imputation on LD and effective population size estimates. The inbreeding coefficient, considering the total length of the run of homozygosity, showed an average estimate (0.0404) lower than the critical level. Overall, the improved accuracy of the updated LD estimates suggests that the HD-chip, combined with an imputation strategy, offers a powerful tool that will increase the opportunities to identify genuine marker-phenotype associations and to successfully implement genomic selection in Churra sheep.

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.

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.

Isolation of RNA from milk somatic cells as an alternative to biopsies of mammary tissue for nutrigenomic studies in dairy ewes.

Nutrigenomic studies of mammary lipogenesis in ruminants often rely on the use of mammary tissue (MT) collected either by biopsy or at slaughter. However, isolating RNA from milk would be a useful and cost-effective technique that may avoid distress to the animal and facilitate the collection of samples in time series experiments. This assay was therefore conducted to test the hypothesis that RNA extracted from milk somatic cells (MSC) in dairy sheep would be a feasible alternative to the performance of MT biopsies for nutrigenomic analyses. To meet this objective, 8 lactating Assaf ewes were divided in 2 groups and offered a total mixed ration without supplementation (control) or supplemented with 2.4% dry matter of fish oil, which was known not only to elicit milk fat depression but also to downregulate the expression of some candidate genes involved in mammary lipogenesis. Total RNA was extracted from MSC and biopsied MT to examine whether the potential changes in the abundance of transcripts was similarly detected with both RNA sources. Milk fatty acid profile was also analyzed by gas chromatography, and variations in mRNA abundance were determined by reverse transcription quantitative PCR. Values of RNA integrity number were always ≥7.7. The expected and designed decrease of milk fat concentration with fish oil (-29%), was associated with a lower transcript abundance of genes coding for enzymes involved in fatty acid activation (ACSS1), de novo synthesis (ACACA and FASN), uptake from plasma lipids (LPL), and esterification of fatty acids to glycerol (LPIN1), as well as of a transcription factor that may regulate their expression (INSIG1). Stable mRNA levels were showed in other candidate genes, such as FABP3, GPAT4, or SCD. Changes due to the dietary treatment were similarly detected with both RNA sources (MSC and MT biopsies), which supports the initial hypothesis and would validate the use of milk as an alternative RNA source for nutrigenomic analyses in dairy sheep.

Milk transcriptome biomarker identification to enhance feed efficiency and reduce nutritional costs in dairy ewes.

In recent years, rising prices for high-quality protein-based feeds have significantly increased nutrition costs. Consequently, investigating strategies to reduce these expenses and improve feed efficiency (FE) have become increasingly important for the dairy sheep industry. This research investigates the impact of nutritional protein restriction (NPR) during prepuberty and FE on the milk transcriptome of dairy Assaf ewes (sampled during the first lactation). To this end, we first compared transcriptomic differences between NPR and control ewes. Subsequently, we evaluated gene expression differences between ewes with divergent FE, using feed conversion ratio (FCR), residual feed intake (RFI), and consensus classifications of high- and low-FE animals for both indices. Lastly, we assess milk gene expression as a predictor of FE phenotype using random forest. No effect was found for the prepubertal NPR on milk performance or FE. Moreover, at the milk transcriptome level, only one gene, HBB, was differentially expressed between the NPR (n = 14) and the control group (n = 14). Further, the transcriptomic analysis between divergent FE sheep revealed 114 differentially expressed genes (DEGs) for RFI index (high-FERFI = 10 vs low-FERFI = 10), 244 for FCR (high-FEFCR = 10 vs low-FEFCR = 10), and 1 016 DEGs between divergent consensus ewes for both indices (high-FEconsensus = 8 vs low-FEconsensus = 8). These results underscore the critical role of selected FE indices for RNA-Seq analyses, revealing that consensus divergent animals for both indices maximise differences in transcriptomic responses. Genes overexpressed in high-FEconsensus ewes were associated with milk production and mammary gland development, while low-FEconsensus genes were linked to higher metabolic expenditure for tissue organisation and repair. The best prediction accuracy for FE phenotype using random forest was obtained for a set of 44 genes consistently differentially expressed across lactations, with Spearman correlations of 0.37 and 0.22 for FCR and RFI, respectively. These findings provide insights into potential sustainability strategies for dairy sheep, highlighting the utility of transcriptomic markers as FE proxies.

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.

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.

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.