Classification of light Yorkshire pigs at different production stages using ordinary least squares and machine learning methods.

Pig homogeneity and growth are major concerns for the pig industry today. Variability in pigs' size has a strong impact on profitability as uniformity plays a key role in the overall economic value of pigs produced. This research focused on statistical methods to identify pigs at risk of growth retardation at different stages of production. Data from 125 083 Yorkshire pigs at weaning (18-28 d), 59 533 pigs at the end of the nursery period (70-82 d) and 48 862 pigs at slaughter (155-170 d) were analyzed under three different cut-points (lowest 10, 20 and 30%) to characterize light animals. Records were randomly split into 2:1 training:testing sets, and each training data set was analyzed through an ordinary least squares approach and four machine learning algorithms (decision tree, random forest, and two alternative boosting approaches). A wide range of weighting functions were applied to give increased relevance to lighter pigs. Each resulting classification norm was used to classify light pigs in the testing data set. Both sensitivity and specificity were retained to construct the receiver operating characteristic curve, and the statistical performance of each analytical approach was evaluated by the area under the curve (AUC). In all production stages and cut-points, the random forest machine learning algorithm provided the highest AUC, closely followed by boosting procedures. For weaning BW (WW), factors related to birth BW and litter size accounted for more than 75% of the important prediction factors for light pigs. BW at the end of the nursery period and slaughter BW analyses revealed a similar pattern where WW and BW at the end of the nursery period accounted for more than 40 and 50% of statistical importance among the prediction factors, respectively. Machine learning algorithms are useful tools to easily evaluate the risk factors affecting the efficiency and homogeneity in swine. Since the BW at birth and weaning are key factors, sow nutrition and feeding management during gestation and lactation, along with piglet management during lactation, are identified as important influences on pig weight variability.

Distortion of Mendelian segregation across the Angus cattle genome uncovering regions affecting reproduction.

Nowadays, the availability of genotyped trios (sire-dam-offspring) in the livestock industry enables the implementation of the transmission ratio distortion (TRD) approach to discover deleterious alleles in the genome. Various biological mechanisms at different stages of the reproductive cycle such as gametogenesis, embryo development and postnatal viability can induce signals of TRD (i.e., deviation from Mendelian inheritance expectations). In this study, TRD was evaluated using both SNP-by-SNP and sliding windows of 2-, 4-, 7-, 10- and 20-SNP across 92,942 autosomal SNPs for 258,140 genotyped Angus cattle including 7,486 sires, 72,688 dams and 205,966 offspring. Transmission ratio distortion was characterized using allelic (specific- and unspecific-parent TRD) and genotypic parameterizations (additive- and dominance-TRD). Across the Angus autosomal chromosomes, 851 regions were clearly found with decisive evidence for TRD. Among these findings, 19 haplotypes with recessive patterns (potential lethality for homozygote individuals) and 52 regions with allelic patterns exhibiting complete or quasi-complete absence for homozygous individuals in addition to under-representation (potentially reduced viability) of the carrier (heterozygous) offspring were found. In addition, 64 (12) and 20 (4) regions showed significant influence on the trait heifer pregnancy at p-value < 0.05 (after chromosome-wise false discovery rate) and 0.01, respectively, reducing the pregnancy rate up to 15%, thus, supporting the biological importance of TRD phenomenon in reproduction.

Transmission ratio distortion regions in the context of genomic evaluation and their effects on reproductive traits in cattle.

Transmission ratio distortion (TRD), which is a deviation from Mendelian expectations, has been associated with basic mechanisms of life such as sperm and ova fertility and viability at developmental stages of the reproductive cycle. In this study different models including TRD regions were tested for different reproductive traits [days from first service to conception (FSTC), number of services, first service nonreturn rate (NRR), and stillbirth (SB)]. Thus, in addition to a basic model with systematic and random effects, including genetic effects modeled through a genomic relationship matrix, we developed 2 additional models, including a second genomic relationship matrix based on TRD regions, and TRD regions as a random effect assuming heterogeneous variances. The analyses were performed with 10,623 cows and 1,520 bulls genotyped for 47,910 SNPs, 590 TRD regions, and several records ranging from 9,587 (FSTC) to 19,667 (SB). The results of this study showed the ability of TRD regions to capture some additional genetic variance for some traits; however, this did not translate into higher accuracy for genomic prediction. This could be explained by the nature of TRD itself, which may arise in different stages of the reproductive cycle. Nevertheless, important effects of TRD regions were found on SB (31 regions) and NRR (18 regions) when comparing at-risk versus control matings, especially for regions with allelic TRD pattern. Particularly for NRR, the probability of observing nonpregnant cow increases by up to 27% for specific TRD regions, and the probability of observing stillbirth increased by up to 254%. These results support the relevance of several TRD regions on some reproductive traits, especially those with allelic patterns that have not received as much attention as recessive TRD patterns.

Discovering lethal alleles across the turkey genome using a transmission ratio distortion approach.

Deviation from Mendelian inheritance expectations (transmission ratio distortion, TRD) has been observed in several species, including the mouse and humans. In this study, TRD was characterized in the turkey genome using both allelic (specific- and unspecific-parent TRD) and genotypic (additive- and dominance-TRD) parameterizations within a Bayesian framework. In this study, we evaluated TRD for 23 243 genotyped Turkeys across 56 393 autosomal SNPs. The analyses included 500 sires, 2013 dams and 11 047 offspring (trios). Three different haplotype sliding windows of 4, 10 and 20 SNPs were used across the autosomal chromosomes. Based on the genotypic parameterizations, 14 haplotypes showed additive and dominance TRD effects highlighting regions with a recessive TRD pattern. In contrast, the allelic model uncovered 12 haplotype alleles with the allelic TRD pattern which showed an underrepresentation of heterozygous offspring in addition to the absence of homozygous animals. For regions with the allelic pattern, only one particular region showed a parent-specific TRD where the penetrance was high via the dam, but low via the sire. The gene set analysis uncovered several gene ontology functional terms, Reactome pathways and several Medical Subject Headings that showed significant enrichment of genes associated with TRD. Many of these gene ontology functional terms (e.g. mitotic spindle assembly checkpoint, DRM complex and Aneuploidy), Reactome pathways (e.g. Mismatch repair) and Medical Subject Headings (e.g. Adenosine monophosphate) are known to be related to fertility, embryo development and lethality. The results of this study revealed potential novel candidate lethal haplotypes, functional terms and pathways that may enhance breeding programs in Turkeys through reducing mortality and improving reproduction rate.

Discriminating between allele- and genotype-specific transmission ratio distortion.

Transmission ratio distortion (TRD) is defined as the observed deviation from the expected Mendelian inheritance of alleles from heterozygous parents. This phenomenon is attributed to various biological mechanisms acting on germ cells, embryos or fetuses, or even in early postnatal life. Current statistical approaches typically use two independent parametrizations assuming that TRD relies on allele- or genotype-related mechanisms, although they have never been tested and compared. This study compared allele- and genotype-related TRD models on simulated datasets with 1000 genotyped offspring and real data from 168 sire-dam-offspring beef cattle trios. The analysis of simulated datasets favored the true model of analysis in most cases (>93%), and a low percentage of missidentification occurred under (almost) null dominance (genotype-related model) or similar and moderate-to-low sire- and dam-specific TRD parameters (allele-related model). Moreover, the correlation between simulated and predicted distortion parameters was high (>0.97) under the true model. The comparison of allele- and genotype-related TRD models is an appealing tool to infer the biological source of TRD (i.e. haploid vs. diploid cells) when screening the whole genome. The analysis of beef cattle data corroborated a TRD region previously reported in chromosome 4, although discarding allele-related mechanisms and favoring the genotype-related model as the more reliable one. The results of this study highlight the relevance of implementing and comparing different parametrizations to capture all kinds of TRD, and to compare them using appropriate statistical methods.

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.

Genetic parameters and direct, maternal and heterosis effects on litter size in a diallel cross among three commercial varieties of Iberian pig.

The Iberian pig is one of the pig breeds that has the highest meat quality. Traditionally, producers have bred one of the available varieties, exclusively, and have not used crosses between them, which has contrasted sharply with other populations of commercial pigs for which crossbreeding has been a standard procedure. The objective of this study was to perform an experiment under full diallel design among three contemporary commercial varieties of Iberian pig and estimate the additive genetic variation and the crossbreeding effects (direct, maternal and heterosis) for prolificacy. The data set comprised 18 193 records for total number born and number born alive from 3800 sows of three varieties of the Iberian breed (Retinto, Torbiscal and Entrepelado) and their reciprocal crosses (Retinto × Torbiscal, Torbiscal × Retinto, Retinto × Entrepelado, Entrepelado × Retinto, Torbiscal × Entrepelado and Entrepelado × Torbiscal), and a pedigree of 4609 individuals. The analysis was based on a multiple population repeatability model, and we developed a model comparison test that indicated the presence of direct line, maternal and heterosis effects. The results indicated the superiorities of the direct line effect of the Retinto and the maternal effect of the Entrepelado populations. All of the potential crosses produced significant heterosis, and additive genetic variation was higher in the Entrepelado than it was in the other two populations. The recommended cross for the highest yield in prolificacy is a Retinto father and an Entrepelado mother to generate a hybrid commercial sow.

Analysis of lambing distribution in the Ripollesa sheep breed. II. Environmental and genetic sources of variation.

Seasonal reproduction patterns are typically observed in small ruminants and are a major limitation for production efficiency in most meat- and dairy-type production systems. Indeed, selection for reduced seasonality could be an appealing strategy for the small ruminant industry worldwide, although its genetic background has been poorly analyzed. One of the main limitations relied on the availability of appropriate analytical tools to cope with the circular (i.e. year-round) pattern of lambing and kidding data. The recent development of a heteroskedastic circular mixed model provided the statistical tool to go deeply into the knowledge of seasonality in small ruminants. In this study, 26 005 lambing distribution records from 4764 Ripollesa ewes collected in 20 purebred flocks were analyzed. The model accounted for systematic (lambing interval and ewe age), permanent environmental (flock-year-season and ewe) and additive genetic sources of variation influencing both mean and dispersion pattern (i.e. heteroskedasticity). Systematic effects suggested that first-lambing ewes and short lambing intervals delayed lambing date (~30 days) and increased dispersion of the lambing period. Nevertheless, this was partially compensated by ewe age, given that youngest females tended to concentrate the lambing peak. Flock-year-season, permanent ewe and additive genetic sources of variation reached moderate variance components for direct (and residual) effects on lambing distribution, they being 0.119 (0.156), 0.092 (0.132) and 0.195 (0.170) radians2, respectively. Moreover, all 95% credibility intervals were placed far from the null estimate. Covariances between direct and residual effects where high and positive for additive genetic (posterior mean, 0.814) and permanent ewe effects (posterior mean, 0.917), whereas it was not relevant for flock-year-season. Selection for direct additive genetic effects should be able to advance or delay the lambing peak, whereas selection applied on residual additive genetic effects should increase or reduce seasonality (i.e. concentrate or flatten the lambing peak). Moreover, the positive and relevant genetic covariance between direct and residual effects also suggested correlated genetic responses. As example, genetic selection for earlier lambing peaks must also reduce seasonality, whereas selection for narrower lambing seasons may originate a delay in the lambing peak. These results must be viewed as the first attempt to analyze systematic, environmental and genetic sources of variation of lambing distribution within the circular paradigm, they providing a reliable characterization of these effects within the context of an heteroskedastic model.

Analysis of lambing distribution in the Ripollesa sheep breed. I. Development and comparison of circular von Mises models.

Circular data originates in a wide range of scientific fields and can be analyzed on the basis of directional statistics and special distributions wrapped around the circumference. However, both propensity to transform non-linear to linear data and complexity of directional statistics limited the generalization of the circular paradigm in the animal breeding framework, among others. Here, we generalized a circular mixed (CM) model within the context of Bayesian inference. Three different parametrizations with different hierarchical structures were developed on basis of the von Mises distribution; moreover, both goodness of fit and predictive ability from each parametrization were compared through the analyses of 110 116 lambing distribution records collected from Ripollesa sheep herds between 1976 and 2017. The naive circular (NC) model only accounted for population mean and homogeneous circular variance, and reached the lowest goodness-of-fit and predictive ability. The CM model assumed a hierarchical structure for the population mean by accounting for systematic (ewe age and lambing interval) and permanent environmental sources of variation (flock-year-season and ewe). This improved goodness of fit by reducing both the deviance information criterion (DIC; -2520 units) and the mean square error (MSE; -12.4%) between simulated and predicted lambing data when compared against the NC model. Finally, the last parametrization expanded CM model by also assuming a hierarchical structure with systematic and permanent environmental factors for the variance parameter of the von Mises distribution (i.e. circular canalization (CC) model). This last model reached the best goodness of fit to lambing distribution data with a DIC estimate 5425 units lower than the one for NC model (MSE reduced 13.2%). The same pattern revealed when models were compared in terms of predictive ability. The superiority revealed by CC model emphasized the relevance of heteroskedasticity for the analysis of lambing distribution in the Ripollesa breed, and suggested potential applications for the sheep industry, even genetic selection for canalization. The development of CM models on the basis of the von Mises distribution has allowed to integrate flexible hierarchical structures accounting for different sources of variation and affecting both mean and dispersion terms. This must be viewed as a useful statistical tool with multiple applications in a wide range of research fields, as well as the livestock industry. The next mandatory step should be the inclusion of genetic terms in the hierarchical structure of the models in order to evaluate their potential contribution to current selection programs.

Screening for epistatic selection signatures: A simulation study.

Detecting combinations of alleles that diverged between subpopulations via selection signature statistics can contribute to decipher the phenomenon of epistasis. This research focused on the simulation of genomic data from subpopulations under divergent epistatic selection (ES). We used D'IS2 and FST statistics in pairs of loci to scan the whole-genome. The results showed the ability to identify loci under additive-by-additive ES (ESaa) by reporting large statistical departures between subpopulations with a high level of divergence, while it did not show the same advantage in the other types of ES. Despite this, limitations such as the difficulty to distinguish between the quasi-complete fixation of one locus by ESaa from other events were observed. However, D'IS2 can detect loci under ESaa by defining a minimum boundary for the minor allele frequency on a multiple subpopulation analysis where ES only takes place in one subset. Even so, the major limitation was distinguishing between ES and single-locus selection (SS); therefore, we can conclude that divergent locus can be also a result of ES. The test conditions with D-statistics of both Ohta (1982a, 1982b) and Black and Krafsur (1985) did not provide evidence to differentiate ES in our simulation framework of isolated subpopulations.

Implementation of Bayesian methods to identify SNP and haplotype regions with transmission ratio distortion across the whole genome: TRDscan v.1.0.

Realized deviations from the expected Mendelian inheritance of alleles from heterozygous parents have been previously reported in a broad range of organisms (i.e., transmission ratio distortion; TRD). Various biological mechanisms affecting gametes, embryos, fetuses, or even postnatal offspring can produce patterns of TRD. However, knowledge about its prevalence and potential causes in livestock species is still scarce. Specific Bayesian models have been recently developed for the analyses of TRD for biallelic loci, which accommodated a wide range of population structures, enabling TRD investigation in livestock populations. The parameterization of these models is flexible and allows the study of overall (parent-unspecific) TRD and sire- and dam-specific TRD. This research aimed at deriving Bayesian models for fitting TRD on the basis of haplotypes, testing the models for both haplotype- and SNP-based methods in simulated data and actual Holstein genotypes, and developing a specific software for TRD analyses. Results obtained on simulated data sets showed that the statistical power of the analysis increased with sample size of trios (n), proportion of heterozygous parents, and the magnitude of the TRD. On the other hand, the statistical power to detect TRD decreased with the number of alleles at each loci. Bayesian analyses showed a strong Pearson correlation coefficient (≥0.97) between simulated and estimated TRD that reached the significance level of Bayes factor ≥10 for both single-marker and haplotype analyses when n ≥ 25. Moreover, the accuracy in terms of the mean absolute error decreased with the increase of the sample size and increased with the number of alleles at each loci. Using real data (55,732 genotypes of Holstein trios), SNP- and haplotype-based distortions were detected with overall TRD, sire-TRD, or dam-TRD, showing different magnitudes of TRD and statistical relevance. Additionally, the haplotype-based method showed more ability to capture TRD compared with individual SNP. To discard possible random TRD in real data, an approximate empirical null distribution of TRD was developed. The program TRDscan v.1.0 was written in Fortran 2008 language and provides a powerful statistical tool to scan for TRD regions across the whole genome. This developed program is freely available at http://www.casellas.info/files/TRDscan.zip.

Expression patterns and genetic variation of the ovine skeletal muscle transcriptome of sheep from five Spanish meat breeds.

The goal of the current study is to analyse the gene expression profile of the ovine skeletal muscle as well as to characterize the genetic variation of transcripts expressed in such tissue. This aim has been achieved by sequencing the longissimus dorsi transcriptomes of 50 sheep distributed in five pools representing the Canaria de Pelo, Roja Mallorquina, Gallega, Xisqueta and Ripollesa Spanish autochthonous breeds. Approximately, 363 million reads per pool have been produced and 71.9-82.9% have been successfully mapped to the ovine genome in a paired-end mode (2 × 75 bp). The 200 most expressed muscle transcripts (≈1% of the total transcript count) account for 51% (Canaria de Pelo) to 67% (Gallega) of the total ovine skeletal muscle mRNA expression. These highly expressed genes play key roles in pathways related with striated muscle contraction, gluconeogenesis, glycolysis, citric acid cycle and respiratory electron transport. RNA-Sequencing of muscle transcripts has also revealed that ~72% of the SNPs detected with this approach are shared by at least two pools, and 10% of them segregate in the five pools under analysis. Most of the substitutions detected by RNA-Seq are synonymous or missense and only a minority are predicted to have consequences on protein function.

On individual-specific prediction of hidden inbreeding depression load.

Inbreeding depression is caused by increased homozygosity in the genome and merges two genetic mechanisms, a higher impact from recessive mutations and the waste of overdominance contributions. It is of major concern for the conservation of endangered populations of plants and animals, as major abnormalities are more frequent in inbred families than in outcrosses. Nevertheless, we lack appropriate analytical methods to estimate the hidden inbreeding depression load (IDL) in the genome of each individual. Here, a new mixed linear model approach has been developed to account for the inbreeding depression-related background of each individual in the pedigree. Within this context, inbred descendants contributed relevant information to predict the IDL contained in the genome of a given ancestor; moreover, known relationships spread these predictions to the remaining individuals in the pedigree, even if not contributing inbred offspring. Results obtained from the analysis of weaning weight in the MARET rabbit population demonstrated that the genetic background of inbreeding depression distributed heterogeneously across individuals and inherited generation by generation. Moreover, this approach was clearly preferred in terms of model fit and complexity when compared with classical approaches to inbreeding depression. This methodology must be viewed as a new tool for a better understanding of inbreeding in domestic and wild populations.

Technical note: PaGELL v.1.5: A flexible parametric program for the Bayesian analysis of longevity data within the context of animal breeding.

This technical note presents the program PaGELL v.1.5 (Parametric Genetic Evaluation of Lifespan in Livestock), a flexible software program to analyze (right-censored) longevity data in livestock populations, with a special emphasis on the genetic evaluation of the breeding stock. This software relies on a parametric generalization of the proportional hazard model; more specifically, the baseline hazard function follows a Weibull process and flexibility is gained by including an additional time-dependent effect with the number of change points defined by the user. The program can accommodate 3 different sources of variation (i.e., systematic, permanent environmental, and additive genetic effects) and both fixed and time-dependent patterns (only for systematic and permanent environmental effects). Analyses are performed within a Bayesian context by sampling from the joint posterior distribution of the model, and model fit can be easily determined by the calculation of the deviance information criterion. Although this software has already been used on field data sets, its performance has been double-checked on simulated data set, and results are presented in this technical note. PaGELL v.1.5 was written in Fortran 95 language and, after compiling with the GNU Fortran Compiler v.4.7 and later, it has been tested in Windows, Linux, and MacOS operating systems (both 32- and 64-bit platforms). This program is available at http://www.casellas.info/files/pageII.zip.

Bayesian analysis of parent-specific transmission ratio distortion in seven Spanish beef cattle breeds.

Transmission ratio distortion (TRD) is the departure from the expected Mendelian ratio in offspring, a poorly investigated biological phenomenon in livestock species. Given the current availability of specific parametric methods for the analysis of segregation data, this study focused on the screening of TRD in 602 402 single nucleotide polymorphisms covering all autosomal chromosomes in seven Spanish beef cattle breeds. On average, 0.13% (n = 786) and 0.01% (n = 29) of genetic markers evidenced sire- or dam-specific TRD respectively. There were no single nucleotide polymorphisms accounting for both sire- and dam-specific TRD at the same time, and only one marker (rs43147474) accounted for (sire-specific) TRD in all seven breeds. It must be noted that rs43147474 is located in the fourth intronic region of the GTP-binding protein 10 gene, and this locus has been previously linked to the maintenance of mitochondria and nucleolar architectures. Alternatively, other candidate genes surround this hot-spot for sire-specific TRD in the cattle genome, and they are related to embryonic and postnatal lethality as well as prostate cancer, among others. This research characterized the distribution of TRD in the bovine genome, highlighting heterogeneous results when comparing across breeds.

Linkage disequilibrium, persistence of phase, and effective population size in Spanish local beef cattle breeds assessed through a high-density single nucleotide polymorphism chip.

Linkage disequilibrium (LD) and persistence of phase are fundamental approaches for exploring the genetic basis of economically important traits in cattle, including the identification of QTL for genomic selection and the estimation of effective population size () to determine the size of the training populations. In this study, we have used the Illumina BovineHD chip in 168 trios of 7 Spanish beef cattle breeds to obtain an overview of the magnitude of LD and the persistence of LD phase through the physical distance between markers. Also, we estimated the time of divergence based on the persistence of the LD phase and calculated past from LD estimates using different alternatives to define the recombination rate. Estimates of average (as a measure of LD) for adjacent markers were close to 0.52 in the 7 breeds and decreased with the distance between markers, although in long distances, some LD still remained (0.07 and 0.05 for markers 200 kb and 1 Mb apart, respectively). A panel with a lower boundary of 38,000 SNP would be necessary to launch a successful within-breed genomic selection program. Persistence of phase, measured as the pairwise correlations between estimates of in 2 breeds at short distances (10 kb), was in the 0.89 to 0.94 range and decreased from 0.33 to 0.52 to a range of 0.01 to 0.08 when marker distance increased from 200 kb to 1 Mb, respectively. The magnitude of the persistence of phase between the Spanish beef breeds was similar to those found in dairy breeds. For across-breed genomic selection, the size of the SNP panels must be in the range of 50,000 to 83,000 SNP. Estimates of past showed values ranging from 26 to 31 for 1 generation ago in all breeds. The divergence among breeds occurred between 129 and 207 generations ago. The results of this study are relevant for the future implementation of within- and across-breed genomic selection programs in the Spanish beef cattle populations. Our results suggest that a reduced subset of the SNP panel would be enough to achieve an adequate precision of the genomic predictions.

Population structure of eleven Spanish ovine breeds and detection of selective sweeps with BayeScan and hapFLK.

The goals of the current work were to analyse the population structure of 11 Spanish ovine breeds and to detect genomic regions that may have been targeted by selection. A total of 141 individuals were genotyped with the Infinium 50 K Ovine SNP BeadChip (Illumina). We combined this dataset with Spanish ovine data previously reported by the International Sheep Genomics Consortium (N = 229). Multidimensional scaling and Admixture analyses revealed that Canaria de Pelo and, to a lesser extent, Roja Mallorquina, Latxa and Churra are clearly differentiated populations, while the remaining seven breeds (Ojalada, Castellana, Gallega, Xisqueta, Ripollesa, Rasa Aragonesa and Segureña) share a similar genetic background. Performance of a genome scan with BayeScan and hapFLK allowed us identifying three genomic regions that are consistently detected with both methods i.e. Oar3 (150-154 Mb), Oar6 (4-49 Mb) and Oar13 (68-74 Mb). Neighbor-joining trees based on polymorphisms mapping to these three selective sweeps did not show a clustering of breeds according to their predominant productive specialization (except the local tree based on Oar13 SNPs). Such cryptic signatures of selection have been also found in the bovine genome, posing a considerable challenge to understand the biological consequences of artificial selection.

Genetic and environmental relationships of detailed milk fatty acids profile determined by gas chromatography in Brown Swiss cows.

The aim of this study was to characterize the profile of 47 fatty acids, including conjugated linoleic acid (CLA), 13 fatty acid groups, and 5 Δ(9)-desaturation indices in milk samples from Brown Swiss cows. The genetic variation was assessed and the statistical relevance of the genetic background for each trait was evaluated using the Bayes factor test. The additive genetic, herd-date, and residual relationships were also estimated among all single fatty acids and groups of fatty acids. Individual milk samples were collected from 1,158 Italian Brown Swiss cows and a detailed analysis of fat percentages and milk fatty acid compositions was performed by gas chromatography. Bayesian animal models were used for (co)variance components estimation. Exploitable genetic variation was observed for most of the de novo synthesized fatty acids and saturated fatty acids, except for C4:0 and C6:0, whereas long-chain fatty acids and unsaturated fatty acids (including CLA) were mainly influenced by herd-date effects. Herd-date effect explained large portions of the total phenotypic variance for C18:2 cis-9,cis-12 (0.668), C18:3 cis-9,cis-12,cis-15 (0.631), and the biohydrogenation and elongation products of these fatty acids. The desaturation ratios showed higher heritability estimates than the individual fatty acids, except for CLA desaturation index (0.098). Among the medium-chain fatty acids, C12:0 had greater heritability than C14:0 (0.243 vs. 0.097, respectively). Both C14:0 and C16:0 showed negative additive genetic correlations with the main monounsaturated and polyunsaturated fatty acids of milk fat, suggesting that their synthesis in the mammary gland may be influenced by the presence of unsaturated fatty acids. No correlation was observed between C4:0 and the other short-chain fatty acids (except for C6:0), confirming the independence of C4:0 from de novo mammary fatty acid synthesis. Among the genetic correlations dealing with potentially beneficial fatty acids, C18:0 was positively correlated with vaccenic and rumenic acids and negatively with linoleic acid. Finally, fatty acids C6:0 through C14:0 showed relevant correlations due to unknown environmental effects, suggesting the potential existence of genetic variances in micro-environmental sensitivity. This study allowed us to acquire new knowledge about the genetic and the environmental relationships among fatty acids. Likewise, the existence of genetic variation for most of de novo synthetized fatty acids and saturated fatty acids was also observed. Overall, these results provide useful information to combine feeding with genetic selection strategies for obtaining a desirable milk fatty acids profile, depending on the origin of fatty acids in milk.

Comparison between linear and proportional hazard models for the analysis of age at first lambing in the Ripollesa breed.

Age at first lambing (AFL) plays a key role on the reproductive performance of sheep flocks, although there are no genetic selection programs accounting for this trait in the sheep industry. This could be due to the non-Gaussian distribution pattern of AFL data, which must be properly accounted for by the analytical model. In this manuscript, two different parameterizations were implemented to analyze AFL in the Ripollesa sheep breed, that is, the skew-Gaussian mixed linear model (sGML) and the piecewise Weibull proportional hazards model (PWPH). Data were available from 10 235 ewes born between 1972 and 2013 in 14 purebred Ripollesa flocks located in the north-east region of Spain. On average, ewes gave their first lambing short after their first year and a half of life (590.9 days), and within-flock averages ranged between 523.4 days and 696.6 days. Model fit was compared using the deviance information criterion (DIC; the smaller the DIC statistic, the better the model fit). Model sGML was clearly penalized (DIC=200 059), whereas model PWPH provided smaller estimates and reached the minimum DIC when one cut point was added to the initial Weibull model (DIC=132 545). The pure Weibull baseline and parameterizations with two or more cut points were discarded due to larger DIC estimates (>134 200). The only systematic effect influencing AFL was the season of birth, where summer- and fall-born ewes showed a remarkable shortening of their AFL, whereas neither birth type nor birth weight had a relevant impact on this reproductive trait. On the other hand, heritability on the original scale derived from model PWPH was high, with a model estimate place at 0.114 and its highest posterior density region ranging from 0.079 and 0.143. As conclusion, Gaussian-related mixed linear models should be avoided when analyzing AFL, whereas model PWPH must be viewed as better alternative with superior goodness of fit; moreover, the additive genetic background underlying this reproductive trait supports its inclusion into current genetic selection programs given its economic importance.

Genetic variation and effects of candidate-gene polymorphisms on coagulation properties, curd firmness modeling and acidity in milk from Brown Swiss cows.

The aims of this study were to estimate the genetic variation of traditional milk coagulation properties (MCPs), milk acidity, curd firmness (CF) modeled on time t (CF(t) ; comprising: RCT(eq), rennet coagulation time estimated from the equation; CF(P), the asymptotic potential curd firmness; k(CF), the curd firming instant rate constant; and k(SR), the syneresis instant rate constant) and maximum CF traits (MCF; comprising CF(max), the maximum CF value; and tmax, the time of attainment). Furthermore, we investigated 96 single nucleotide polymorphisms (SNPs) from 54 candidate genes, testing their associations with the above-listed traits. Milk and blood samples were collected from 1271 cows (each sampled once) from 85 herds. Genotyping was performed using a custom Illumina VeraCode GoldenGate approach. A Bayesian linear animal model (including the effects of herd, days in milk, parity and additive polygenic effects) was used to estimate the genetic parameters of the studied traits. The same model with the addition of the SNP genotype effect was used for our association analysis. The heritability estimates of CF t and the MCF traits (RCT(eq)=0.258; k(CF)=0.230; CF(max)=0.191; t(max)=0.278) were similar to those obtained using traditional MCPs (0.187 to 0.267), except for the lower estimates for CF(P) (0.064) and k(SR) (0.077). A total of 13 of the 51 tested SNPs had relevant additive effects on at least one trait. We observed associations between MCPs and SNPs in the genes encoding ATP-binding cassette sub-family G member 2 (ABCG2), chemokine ligand 2 (CCL2), growth hormone 1 (GH1), prolactin (PRL) and toll-like receptor 2 (TLR2). Whereas, CF(t) and the MCF traits were associated with polymorphisms in the α-s1-casein (CSN1S1), ß-casein (CSN2), GH1, oxidized low-density lipoprotein receptor 1 (OLR1), phospholipase C ß1 (PLCB1), PRL and signal transducer and activator of transcription 5A (STAT5A) genes.