Selection in action: dissecting the molecular underpinnings of the increasing muscle mass of Belgian Blue Cattle

Evaluation of heritability partitioning approaches in livestock populations

BACKGROUND

Heritability partitioning approaches estimate the contribution of different functional classes, such as coding or regulatory variants, to the genetic variance. This information allows a better understanding of the genetic architecture of complex traits, including complex diseases, but can also help improve the accuracy of genomic selection in livestock species. However, methods have mainly been tested on human genomic data, whereas livestock populations have specific characteristics, such as high levels of relatedness, small effective population size or long-range levels of linkage disequilibrium.

RESULTS

Here, we used data from 14,762 cows, imputed at the whole-genome sequence level for 11,537,240 variants, to simulate traits in a typical livestock population and evaluate the accuracy of two state-of-the-art heritability partitioning methods, GREML and a Bayesian mixture model. In simulations where a single functional class had increased contribution to heritability, we observed that the estimators were unbiased but had low precision. When causal variants were enriched in variants with low (< 0.05) or high (> 0.20) minor allele frequency or low (below 1st quartile) or high (above 3rd quartile) linkage disequilibrium scores, it was necessary to partition the genetic variance into multiple classes defined on the basis of allele frequencies or LD scores to obtain unbiased results. When multiple functional classes had variable contributions to heritability, estimators showed higher levels of variation and confounding between certain categories was observed. In addition, estimators from small categories were particularly imprecise. However, the estimates and their ranking were still informative about the contribution of the classes. We also demonstrated that using methods that estimate the contribution of a single category at a time, a commonly used approach, results in an overestimation. Finally, we applied the methods to phenotypes for muscular development and height and estimated that, on average, variants in open chromatin regions had a higher contribution to the genetic variance (> 45%), while variants in coding regions had the strongest individual effects (> 25-fold enrichment on average). Conversely, variants in intergenic or intronic regions showed lower levels of enrichment (0.2 and 0.6-fold on average, respectively).

CONCLUSIONS

Heritability partitioning approaches should be used cautiously in livestock populations, in particular for small categories. Two-component approaches that fit only one functional category at a time lead to biased estimators and should not be used.

Sequenced-based GWAS for linear classification traits in Belgian Blue beef cattle reveals new coding variants in genes regulating body size in mammals

BACKGROUND

Cohorts of individuals that have been genotyped and phenotyped for genomic selection programs offer the opportunity to better understand genetic variation associated with complex traits. Here, we performed an association study for traits related to body size and muscular development in intensively selected beef cattle. We leveraged multiple trait information to refine and interpret the significant associations.

RESULTS

After a multiple-step genotype imputation to the sequence-level for 14,762 Belgian Blue beef (BBB) cows, we performed a genome-wide association study (GWAS) for 11 traits related to muscular development and body size. The 37 identified genome-wide significant quantitative trait loci (QTL) could be condensed in 11 unique QTL regions based on their position. Evidence for pleiotropic effects was found in most of these regions (e.g., correlated association signals, overlap between credible sets (CS) of candidate variants). Thus, we applied a multiple-trait approach to combine information from different traits to refine the CS. In several QTL regions, we identified strong candidate genes known to be related to growth and height in other species such as LCORL-NCAPG or CCND2. For some of these genes, relevant candidate variants were identified in the CS, including three new missense variants in EZH2, PAPPA2 and ADAM12, possibly two additional coding variants in LCORL, and candidate regulatory variants linked to CCND2 and ARMC12. Strikingly, four other QTL regions associated with dimension or muscular development traits were related to five (recessive) deleterious coding variants previously identified.

CONCLUSIONS

Our study further supports that a set of common genes controls body size across mammalian species. In particular, we added new genes to the list of those associated with height in both humans and cattle. We also identified new strong candidate causal variants in some of these genes, strengthening the evidence of their causality. Several breed-specific recessive deleterious variants were identified in our QTL regions, probably as a result of the extreme selection for muscular development in BBB cattle.

Myostatin mutation causing double muscling could affect increased psoroptic mange sensitivity in dual purpose Belgian Blue cattle

Belgian Blue cattle are known for their high degree of muscling and good carcass qualities. This high degree of muscling is mainly caused by a mutation in the myostatin gene (MSTN). Although the MSTN mutation is considered as fixed in the Belgian Blue breed, segregation is occurring in a sub-population bred for dual purpose. In the latter population, we observed an association between the mutation in MSTN and susceptibility to psoroptic mange, a skin disease caused by Psoroptes ovis mites that heavily plagues Belgian Blue cattle. In total, 291 animals were sampled and screened for their susceptibility for mange lesions and their MSTN genotype. Via linear mixed modelling, we observed that homozygous mutant animals had a significant increase in the size of mange lesions (+2.51% lesion extent) compared to homozygous wild type. These findings were confirmed with zero-inflated modelling, an animal model and odds analysis. Risk ratios for developing severe mange lesions were 5.9 times as high for homozygous mutant animals. All analyses confirmed an association between the MSTN genotype and psoroptic mange lesion size.

Genetic Variations and Haplotypic Diversity in the Myostatin Gene of Different Cattle Breeds in Russia

Simple Summary

This paper presents the results of the study of two polymorphisms of the myostatin gene associated with muscular hypertrophy in the Russian populations of Aberdeen Angus, Limousin, Simmental, and Belgian Blue cattle breeds. For their diagnostics, test systems based on modern molecular genetic methods were developed, and the population analysis showed a low frequency of the undesirable allele associated with the genetic defect of double-muscling, and a high frequency of the allele that presumably positively influences meat productivity traits.

Abstract

The myostatin gene (MSTN) in cattle has a number of polymorphisms associated with increased muscle mass. The aim of the current study was to determine the haplotype frequencies of F94L and nt821(del11) MSTN polymorphisms among cattle bred for meat in Russia, using DNA analysis. Using the earlier created test systems based on the AS-PCR and PCR-RFLP methods, six populations of Aberdeen Angus (n = 684), two populations of Limousin (n = 54), one population of Simmental (n = 55), and one population of Belgian Blue (n = 137) belonging to Russian farms were genotyped on nt821(del11) and F94LMSTN polymorphisms. The animal carriers of the mutant allele of nt821(del11)MSTN associated with the double-muscling genetic defect were found in one Aberdeen Angus population at a frequency of 2.18%, but were not found in the Limousin and Simmental populations. However, 100% of the Belgian Blue population were heterozygous carriers of nt821(del11)MSTN. The frequencies of the A allele F94LMSTN desirable for productivity traits in the Limousin populations were the highest and accounted for 0.97 and 1 in populations one and two, while in the Aberdeen Angus, Simmental, and Belgian Blue populations, these figures were considerably lower at 0.04–0.08, depending on the population. The obtained data show the high genetic potential of Russian beef cattle, and facilitate an improvement in meat productivity by preserving the health of animals.

The Molecular Bases Study of the Inherited Diseases for the Health Maintenance of the Beef Cattle

The article highlighted the problem of meat cattle genetic defects. The aim was the development of DNA tests for some genetic defects diagnostics, the determination of the animal carriers and their frequencies tracking in time. The 1490 DNA samples from the Aberdeen Angus (n = 701), Hereford (n = 385), Simmental (n = 286) and Belgian Blue (n = 118) cattle have been genotyped on the genetic defects by newly created and earlier developed DNA tests based on AS-PCR and PCR-RFLP methods. The Aberdeen Angus cattle genotyping has revealed 2.38 ± 0.31% AMC-cows and 1.67 ± 0.19 % AMC-bulls, 0.65 ± 0.07% DDC-cows and 0.90 ± 0.10% DDC-bulls. The single animals among the Hereford cattle were carriers of MSUD and CWH (on 0.27 ± 0.05%), ICM and HY (on 0.16 ± 0.03%). The Simmental cattle were free from OS. All Belgian Blue livestock were M1- and 0.84%-CMD1-carriers. The different ages Aberdeen Angus cattle genotyping has shown the tendency of the AMC- and DDC frequencies to increase in the later generations. The statistically significant increase of DDC of 1.17% in the cows’ population born in 2019 compared to those born in 2015 allows concluding the further development of the DNA analysis-based measures preventing the manifestation of the genetic anomalies in meat cattle herds is necessary.

DNA analysis of the Russian populations of Aberdeen Angus, Hereford and Belgian Blue cattle

The use of specialized meat breeds in cattle breeding programs is considered very promising for improving herds' productivity. However, in animal genotype, along with genes that positively affect the productivity signs, there are genes whose mutations, known as genetic defects, negatively affect the health of animals. The aim of the study was the screening of the Russian populations of Aberdeen Angus, Hereford and Belgian Blue cattle on gene mutations associated with the genetic defects of arthrogryposis multiplex (AM), osteopetrosis (OS), developmental duplication (DD), double muscling (M1), hypotrichosis (HY) and maple syrup urine disease (MSUD) as well as the F94L polymorphism of myostatin gene (MSTN) linked with the gene responsible for less fat content in the carcass by means of DNA analysis. In the article, test systems based on the polymerase chain reaction method are presented. The analysis of the Aberdeen Angus (n=4480) population has revealed 0.19 ± 0.09 % animal M1 carriers, 0.53 ± 0.03 % OS carriers, 1.92 ± 0.09 % AM carriers and 9.00 ± 0.20 % DD carriers. The genotyping of Hereford cattle of Russian populations (n=525) has not revealed any individual carriers of MSUD or HY genetic defects. All of the Belgian Blue population (n=92) animals were heterozygous M1 carriers. The study of the F94LMSTN polymorphism has demonstrated extremely high frequencies of the desirable A allele (0.93 and 0.90) in two Aberdeen Angus populations with an average mean of 0.63 ± 0.08, which was 32 % higher compared to the Belgian Blue population. The results suggest the high genetic potential of the Aberdeen Angus and Belgian Blue cattle, but the existence in the genotypes of the mutant alleles associated with hereditary diseases indicates the risk of uncontrolled use of these breeds.

An evaluation of inbreeding measures using a whole-genome sequenced cattle pedigree

The estimation of the inbreeding coefficient (F) is essential for the study of inbreeding depression (ID) or for the management of populations under conservation. Several methods have been proposed to estimate the realized F using genetic markers, but it remains unclear which one should be used. Here we used whole-genome sequence data for 245 individuals from a Holstein cattle pedigree to empirically evaluate which estimators best capture homozygosity at variants causing ID, such as rare deleterious alleles or loci presenting heterozygote advantage and segregating at intermediate frequency. Estimators relying on the correlation between uniting gametes (F_UNI) or on the genomic relationships (F_GRM) presented the highest correlations with these variants. However, homozygosity at rare alleles remained poorly captured. A second group of estimators relying on excess homozygosity (F_HOM), homozygous-by-descent segments (F_HBD), runs-of-homozygosity (F_ROH) or on the known genealogy (F_PED) was better at capturing whole-genome homozygosity, reflecting the consequences of inbreeding on all variants, and for young alleles with low to moderate frequencies (0.10 < . < 0.25). The results indicate that F_UNI and F_GRM might present a stronger association with ID. However, the situation might be different when recessive deleterious alleles reach higher frequencies, such as in populations with a small effective population size. For locus-specific inbreeding measures or at low marker density, the ranking of the methods can also change as F_HBD makes better use of the information from neighboring markers. Finally, we confirmed that genomic measures are in general superior to pedigree-based estimates. In particular, F_PED was uncorrelated with locus-specific homozygosity.

Performances of Adaptive MultiBLUP, Bayesian regressions, and weighted-GBLUP approaches for genomic predictions in Belgian Blue beef cattle

BACKGROUND

Genomic selection has been successfully implemented in many livestock and crop species. The genomic best linear unbiased predictor (GBLUP) approach, assigning equal variance to all SNP effects, is one of the reference methods. When large-effect variants contribute to complex traits, it has been shown that genomic prediction methods that assign a higher variance to subsets of SNP effects can achieve higher prediction accuracy. We herein compared the efficiency of several such approaches, including the Adaptive MultiBLUP (AM-BLUP) that uses local genomic relationship matrices (GRM) to automatically identify and weight genomic regions with large effects, to predict genetic merit in Belgian Blue beef cattle.

RESULTS

We used a population of approximately 10,000 genotyped cows and their phenotypes for 14 traits, mostly related to muscular development and body dimensions. According to the trait, we found that 4 to 25% of the genetic variance could be associated with 2 to 12 genomic regions harbouring large-effect variants. Noteworthy, three previously identified recessive deleterious variants presented heterozygote advantage and were among the most significant SNPs for several traits. The AM-BLUP resulted in increased reliability of genomic predictions compared to GBLUP (+ 2%), but Bayesian methods proved more efficient (+ 3%). Overall, the reliability gains remained thus limited although higher gains were observed for skin thickness, a trait affected by two genomic regions having particularly large effects. Higher accuracies than those from the original AM-BLUP were achieved when applying the Bayesian Sparse Linear Mixed Model to pre-select groups of SNPs with large effects and subsequently use their estimated variance to build a weighted GRM. Finally, the single-step GBLUP performed best and could be further improved (+ 3% prediction accuracy) by using these weighted GRM.

CONCLUSIONS

The AM-BLUP is an attractive method to automatically identify and weight genomic regions with large effects on complex traits. However, the method was less accurate than Bayesian methods. Overall, weighted methods achieved modest accuracy gains compared to GBLUP. Nevertheless, the computational efficiency of the AM-BLUP might be valuable at higher marker density, including with whole-genome sequencing data. Furthermore, weighted GRM are particularly useful to account for large variance loci in the single-step GBLUP.

Negative Energy Balance Does Not Alter Fat-Free Mass During the Yukon Arctic Ultra-The Longest and the Coldest Ultramarathon

Purpose: The objective of this study was to determine alterations in caloric balance, body composition, metabolites, and cytokines in athletes participating in the Yukon Arctic Ultra.

Methods: Ten participants traveling on foot in the 2017 692-km event were recruited for the study. Measurements and samples were obtained at pre-event, 278 km (C1), 384 km (C2), and post-event. Body composition measurements were obtained using bioelectrical impedance analysis. Accelerometer devices were utilized to provide an estimation of caloric expenditure and dietary recalls provided assessments of caloric intake. Blood serum samples were collected, processed, and analyzed using enzyme-linked immunosorbent assays or nuclear magnetic resonance. Results were analyzed using linear mixed model, presented as means ± SD, and considered significant at p < 0.05.

Results: Participants (8 males, 2 females; age: 37 ± 10 years; body mass index: 24.4 ± 2.5 kg/m²) were recruited. Four males and one female completed the entire event in 260 ± 19 h. Caloric intake/expenditure was 4,126 ± 1,115 kcal/day and 6,387 ± 781 kcal/day, respectively, indicating a caloric deficit of 2,261 ± 1,543 kcal/day. Total mass, body mass index, and fat mass were reduced at each time point of the event. Fat-free mass (FFM) was unchanged throughout the event. Follistatin was increased at C1 (1,715 ± 876 pg/ml) in comparison to baseline. Acetoacetate increased significantly at post-event (6.1 ± 1.5 mg/ml).

Conclusions: Despite a pronounced caloric deficit and sustained activity under extreme cold conditions, FFM was preserved with an increase in serum follistatin and acetoacetate. Future studies should be directed at the role of nutrient strategies and/or training methods on the retention of FFM under these conditions.

Genome-Wide Signatures of Selection Reveal Genes Associated With Performance in American Quarter Horse Subpopulations

Selective breeding for athletic performance in various disciplines has resulted in population stratification within the American Quarter Horse (QH) breed. The goals of this study were to utilize high density genotype data to: (1) identify genomic regions undergoing positive selection within and among QH subpopulations; (2) investigate haplotype structure within each QH subpopulation; and (3) identify candidate genes within genomic regions of interest (ROI), as well as biological pathways, predicted to play a role in elite performance in each group. For that, 65K SNP genotyping data on 143 elite individuals from 6 QH subpopulations (cutting, halter, racing, reining, western pleasure, and working cow) were imputed to 2M SNPs. Signatures of selection were identified using F_ST-based (d_i ) and haplotype-based (hapFLK) analyses, accompanied by identification of local haplotype structure and sharing within subpopulations (hapQTL). Regions undergoing positive selection were identified on all 31 autosomes, and ROI on 2 chromosomes were identified by all 3 methods combined. Genes within each ROI were retrieved and used to identify pathways and genes that might contribute to performance in each subpopulation. These included, among others, candidate genes associated with skeletal muscle development, metabolism, and central nervous system development. This work improves our understanding of equine breed development, and provides breeders with a better understanding of how selective breeding impacts the performance of QH populations.

Age-based partitioning of individual genomic inbreeding levels in Belgian Blue cattle

Background

Inbreeding coefficients can be estimated either from pedigree data or from genomic data, and with genomic data, they are either global or local (when the linkage map is used). Recently, we developed a new hidden Markov model (HMM) that estimates probabilities of homozygosity-by-descent (HBD) at each marker position and automatically partitions autozygosity in multiple age-related classes (based on the length of HBD segments). Our objectives were to: (1) characterize inbreeding with our model in an intensively selected population such as the Belgian Blue Beef (BBB) cattle breed; (2) compare the properties of the model at different marker densities; and (3) compare our model with other methods.

Results

When using 600 K single nucleotide polymorphisms (SNPs), the inbreeding coefficient (probability of sampling an HBD locus in an individual) was on average 0.303 (ranging from 0.258 to 0.375). HBD-classes associated to historical ancestors (with small segments ≤ 200 kb) accounted for 21.6% of the genome length (71.4% of the total length of the genome in HBD segments), whereas classes associated to more recent ancestors accounted for only 22.6% of the total length of the genome in HBD segments. However, these recent classes presented more individual variation than more ancient classes. Although inbreeding coefficients obtained with low SNP densities (7 and 32 K) were much lower (0.060 and 0.093), they were highly correlated with those obtained at higher density (r = 0.934 and 0.975, respectively), indicating that they captured most of the individual variation. At higher SNP density, smaller HBD segments are identified and, thus, more past generations can be explored. We observed very high correlations between our estimates and those based on homozygosity (r = 0.95) or on runs-of-homozygosity (r = 0.95). As expected, pedigree-based estimates were mainly correlated with recent HBD-classes (r = 0.56).

Conclusions

Although we observed high levels of autozygosity associated with small HBD segments in BBB cattle, recent inbreeding accounted for most of the individual variation. Recent autozygosity can be captured efficiently with low-density SNP arrays and relatively simple models (e.g., two HBD classes). The HMM framework provides local HBD probabilities that are still useful at lower SNP densities.

Electronic supplementary material

The online version of this article (10.1186/s12711-017-0370-x) contains supplementary material, which is available to authorized users.

Invited review: A perspective on the future of genomic selection in dairy cattle

Genomic evaluation has been successfully implemented in the United States, Canada, Great Britain, Ireland, New Zealand, Australia, France, the Netherlands, Germany, and the Scandinavian countries. Adoption of this technology in the major dairy producing countries has led to significant changes in the worldwide dairy industry. Gradual elimination of the progeny test system has led to a reduction in the number of sires with daughter records and fewer genetic ties between years. As genotyping costs decrease, the number of cows genotyped will continue to increase, and these records will become the basic data used to compute genomic evaluations, most likely via application of "single-step" methodologies. Although genomic selection has been successful in increasing rates of genetic gain, we still know very little about the genetic architecture of quantitative variation. Apparently, a very large number of genes affect nearly all economic traits, in accordance with the infinitesimal model for quantitative traits. Less emphasis in selection goals will be placed on milk production traits, and more on health, reproduction, and efficiency traits and on environmentally friendly production with reduced waste and gas emission. Genetic variance for economic traits is maintained by the increase in frequency of rare alleles, new mutations, and changes in selection goals and management. Thus, it is unlikely that a selection plateau will be reached in the near future.

Current insights into the molecular genetic basis of dwarfism in livestock

Impairment of bone growth at a young age leads to dwarfism in adulthood. Dwarfism can be categorised as either proportionate, an overall size reduction without changes in body proportions, or disproportionate, a size reduction in one or more limbs, with changes in body proportions. Many forms of dwarfism are inherited and result from structural disruptions or disrupted signalling pathways. Hormonal disruptions are evident in Brooksville miniature Brahman cattle and Z-linked dwarfism in chickens, caused by mutations in GH1 and GHR. Furthermore, mutations in IHH are the underlying cause of creeper achondroplasia in chickens. Belgian blue cattle display proportionate dwarfism caused by a mutation in RNF11, while American Angus cattle dwarfism is caused by a mutation in PRKG2. Mutations in EVC2 are associated with dwarfism in Japanese brown cattle and Tyrolean grey cattle. Fleckvieh dwarfism is caused by mutations in the GON4L gene. Mutations in COL10A1 and COL2A1 cause dwarfism in pigs and Holstein cattle, both associated with structural disruptions, while several mutations in ACAN are associated with bulldog-type dwarfism in Dexter cattle and dwarfism in American miniature horses. In other equine breeds, such as Shetland ponies and Friesian horses, dwarfism is caused by mutations in SHOX and B4GALT7. In Texel sheep, chondrodysplasia is associated with a deletion in SLC13A1. This review discusses genes known to be involved in these and other forms of dwarfism in livestock.

The Valdostana goat: a genome-wide investigation of the distinctiveness of its selective sweep regions

The Valdostana goat is an alpine breed, raised only in the northern Italian region of the Aosta Valley. This breed's main purpose is to produce milk and meat, but is peculiar for its involvement in the "Batailles de Chèvres," a recent tradition of non-cruel fight tournaments. At both the genetic and genomic levels, only a very limited number of studies have been performed with this breed and there are no studies about the genomic signatures left by selection. In this work, 24 unrelated Valdostana animals were screened for runs of homozygosity to identify highly homozygous regions. Then, six different approaches (ROH comparison, Fst single SNPs and windows based, Bayesian, Rsb, and XP-EHH) were applied comparing the Valdostana dataset with 14 other Italian goat breeds to confirm regions that were different among the comparisons. A total of three regions of selection that were also unique among the Valdostana were identified and located on chromosomes 1, 7, and 12 and contained 144 genes. Enrichment analyses detected genes such as cytokines and lymphocyte/leukocyte proliferation genes involved in the regulation of the immune system. A genetic link between an aggressive challenge, cytokines, and immunity has been hypothesized in many studies both in humans and in other species. Possible hypotheses associated with the signals of selection detected could be therefore related to immune-related factors as well as with the peculiar battle competition, or other breed-specific traits, and provided insights for further investigation of these unique regions, for the understanding and safeguard of the Valdostana breed.

Coding and noncoding variants in HFM1, MLH3, MSH4, MSH5, RNF212, and RNF212B affect recombination rate in cattle

We herein study genetic recombination in three cattle populations from France, New Zealand, and the Netherlands. We identify 2,395,177 crossover (CO) events in 94,516 male gametes, and 579,996 CO events in 25,332 female gametes. The average number of COs was found to be larger in males (23.3) than in females (21.4). The heritability of global recombination rate (GRR) was estimated at 0.13 in males and 0.08 in females, with a genetic correlation of 0.66 indicating that shared variants are influencing GRR in both sexes. A genome-wide association study identified seven quantitative trait loci (QTL) for GRR. Fine-mapping following sequence-based imputation in 14,401 animals pinpointed likely causative coding (5) and noncoding (1) variants in genes known to be involved in meiotic recombination (HFM1, MSH4, RNF212, MLH3, MSH5) for 5/7 QTL, and noncoding variants (3) in RNF212B for 1/7 QTL. This suggests that this RNF212 paralog might also be involved in recombination. Most of the identified mutations had significant effects in both sexes, with three of them each accounting for ∼10% of the genetic variance in males.

Cryptic Genetic Variation in Evolutionary Developmental Genetics

Evolutionary developmental genetics has traditionally been conducted by two groups: Molecular evolutionists who emphasize divergence between species or higher taxa, and quantitative geneticists who study variation within species. Neither approach really comes to grips with the complexities of evolutionary transitions, particularly in light of the realization from genome-wide association studies that most complex traits fit an infinitesimal architecture, being influenced by thousands of loci. This paper discusses robustness, plasticity and lability, phenomena that we argue potentiate major evolutionary changes and provide a bridge between the conceptual treatments of macro- and micro-evolution. We offer cryptic genetic variation and conditional neutrality as mechanisms by which standing genetic variation can lead to developmental system drift and, sheltered within canalized processes, may facilitate developmental transitions and the evolution of novelty. Synthesis of the two dominant perspectives will require recognition that adaptation, divergence, drift and stability all depend on similar underlying quantitative genetic processes-processes that cannot be fully observed in continuously varying visible traits.

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.

Reverse genetic screen for loss-of-function mutations uncovers a frameshifting deletion in the melanophilin gene accountable for a distinctive coat color in Belgian Blue cattle

In the course of a reverse genetic screen in the Belgian Blue cattle breed, we uncovered a 10-bp deletion (c.87_96del) in the first coding exon of the melanophilin gene (MLPH), which introduces a premature stop codon (p.Glu32Aspfs*1) in the same exon, truncating 94% of the protein. Recessive damaging mutations in the MLPH gene are well known to cause skin, hair, coat or plumage color dilution phenotypes in numerous species, including human, mice, dog, cat, mink, rabbit, chicken and quail. Large-scale array genotyping undertaken to identify p.Glu32Aspfs*1 homozygous mutant animals revealed a mutation frequency of 5% in the breed and allowed for the identification of 10 homozygous mutants. As expression of a colored coat requires at least one wild-type allele at the co-dominant Roan locus encoded by the KIT ligand gene (KITLG), homozygous mutants for p.Ala227Asp corresponding with the missense mutation were excluded. The six remaining colored calves displayed a distinctive dilution phenotype as anticipated. This new coat color was named 'cool gray'. It is the first damaging mutation in the MLPH gene described in cattle and extends the already long list of species with diluted color due to recessive mutations in MLPH and broadens the color palette of gray in this breed.

Gene co-expression network analysis provides novel insights into myostatin regulation at three different mouse developmental timepoints

Myostatin (Mstn) knockout mice exhibit large increases in skeletal muscle mass. However, relatively few of the genes that mediate or modify MSTN effects are known. In this study, we performed co-expression network analysis using whole transcriptome microarray data from MSTN-null and wild-type mice to identify genes involved in important biological processes and pathways related to skeletal muscle and adipose development. Genes differentially expressed between wild-type and MSTN-null mice were further analyzed for shared DNA motifs using DREME. Differentially expressed genes were identified at 13.5 d.p.c. during primary myogenesis and at d35 during postnatal muscle development, but not at 17.5 d.p.c. during secondary myogenesis. In total, 283 and 2034 genes were differentially expressed at 13.5 d.p.c. and d35, respectively. Over-represented transcription factor binding sites in differentially expressed genes included SMAD3, SP1, ZFP187, and PLAGL1. The use of regulatory (RIF) and phenotypic (PIF) impact factor and differential hubbing co-expression analyses identified both known and potentially novel regulators of skeletal muscle growth, including Apobec2, Atp2a2, and Mmp13 at d35 and Sox2, Tmsb4x, and Vdac1 at 13.5 d.p.c. Among the genes with the highest PIF scores were many fiber type specifying genes. The use of RIF, PIF, and differential hubbing analyses identified both known and potentially novel regulators of muscle development. These results provide new details of how MSTN may mediate transcriptional regulation as well as insight into novel regulators of MSTN signal transduction that merit further study regarding their physiological roles in muscle and adipose development.