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New Mendelian genetic conditions, which adversely affect livestock, arise all the time. To manage them effectively, some methods need to be devised that are quick and accurate. Until recently, finding the causal genomic site of a new autosomal recessive genetic disease has required a two-stage approach using single-nucleotide polymorphism (SNP) chip genotyping to locate the region containing the new variant. This region is then explored using fine-mapping methods to locate the actual site of the new variant. This study explores bioinformatic methods that can be used to identify the causative variants of recessive genetic disorders with full penetrance with just nine whole genome-sequenced animals to simplify and expedite the process to a one-step procedure. Using whole genome sequencing of only three cases and six carriers, the site of a novel variant causing perinatal mortality in Irish moiled calves was located. Four methods were used to interrogate the variant call format (VCF) data file of these nine animals, they are genotype criteria (GCR), autozygosity-by-difference (ABD), variant prediction scoring, and registered SNP information. From more than nine million variants in the VCF file, only one site was identified by all four methods (Chr4: g.77173487A>T (ARS-UCD1.2 (GCF_002263795.1)). This site was a splice acceptor variant located in the glucokinase gene ( GCK). It was verified on an independent sample of animals from the breed using genotyping by polymerase chain reaction at the candidate site and autozygosity-by-difference using SNP-chips. Both methods confirmed the candidate site. Investigation of the GCR method found that sites meeting the GCR were not evenly spread across the genome but concentrated in regions of long runs of homozygosity. Locating GCR sites was best performed using two carriers to every case, and the carriers should be distantly related to the cases, within the breed concerned. Fewer than 20 animals need to be sequenced when using the GCR and ABD methods together. The genomic site of novel autosomal recessive Mendelian genetic diseases can be located using fewer than 20 animals combined with two bioinformatic methods, autozygosity-by-difference, and genotype criteria. In many instances it may also be confirmed with variant prediction scoring. This should speed-up and simplify the management of new genetic diseases to a single-step process.

There is very little information about how the genome is regulated in domestic pigs (Sus scrofa). This lack of knowledge hinders efforts to define and predict the effects of genetic variants in pig breeding programs. To address this knowledge gap, we need to identify regulatory sequences in the pig genome starting with regions of open chromatin. We used the "Improved Protocol for the Assay for Transposase-Accessible Chromatin (Omni-ATAC-Seq)" to identify putative regulatory regions in flash-frozen semitendinosus muscle from 24 male piglets. We collected samples from the smallest-, average-, and largest-sized male piglets from each litter through five developmental time points. Of the 4661 ATAC-Seq peaks identified that represent regions of open chromatin, >50% were within 1 kb of known transcription start sites. Differential read count analysis revealed 377 ATAC-Seq defined genomic regions where chromatin accessibility differed significantly across developmental time points. We found regions of open chromatin associated with downregulation of genes involved in muscle development that were present in small-sized fetal piglets but absent in large-sized fetal piglets at day 90 of gestation. The dataset that we have generated provides a resource for studies of genome regulation in pigs and contributes valuable functional annotation information to filter genetic variants for use in genomic selection in pig breeding programs.

Additional file 9: Figure S5. Sex assignment for the 1159 goats sampled in VarGoats. Representation of the ratio of read number between the autosomes and the X chromosome and the read number on the Y chromosome for each animal to determine its sex. The horizontal bar corresponds to the threshold of 25 reads from the Y scaffold allowing to differentiate males from females.

Additional file 2: Supplementary Fig. 1. Additional figures supporting the main text of the manuscript. Referred to as Supplementary Figs. 1–3. Supplementary Fig. 1. Volcano plot of differentially expressed genes (padj 1). Supplementary Fig. 2. Outliers detected by sample clustering (WGCNA). Supplementary Fig. 3. Principal component analysis of herd effect. A) with herd effect, B) herd effect removed.

Additional file 6: Figure S4. Tranche plot produced by VariantRecalibrator for SNPs. Description: Partition of the call sets into quality tranches. The tranches correspond to certain levels of sensitivity relative to the truth sets (the highest tranche corresponds to a high accuracy call set but with the lowest value of sensitivity).

Additional file 3: Figure S1. Distribution of the concordance rates. Concordance rates (CR) between sequence variants and 50 k genotypes for 457 individuals. The figure shows a clear disruption in the distribution of CR, thus we found it easy and relevant to discard the samples below a concordance rate of 70% between sequence and chip SNP data.

Additional file 5: Figure S3. Pairwise comparisons of the annotations chosen in VQSR for InDels. Description: Modeling report generated by GATK VariantRecalibrator for every pairwise combination of annotations used (QD, DP, FS, MQRankSum, ReadPosRankSum and SOR), with a 2D projection of the Gaussian mixture model.

The aim of this study was to identify genomic regions associated with 305‐day milk yield and lactation curve parameters on primiparous (n = 9,910) and multiparous (n = 11,158) Holstein cows. The SNP solutions were estimated using a weighted single‐step genomic BLUP approach and imputed high‐density panel (777k) genotypes. The proportion of genetic variance explained by windows of 50 consecutive SNP (with an average of 165 Kb) was calculated, and regions that accounted for more than 0.50% of the variance were used to search for candidate genes. Estimated heritabilities were 0.37, 0.34, 0.17, 0.12, 0.30 and 0.19, respectively, for 305‐day milk yield, peak yield, peak time, ramp, scale and decay for primiparous cows. Genetic correlations of 305‐day milk yield with peak yield, peak time, ramp, scale and decay in primiparous cows were 0.99, 0.63, 0.20, 0.97 and −0.52, respectively. The results identified three windows on BTA14 associated with 305‐day milk yield and the parameters of lactation curve in primi‐ and multiparous cows. Previously proposed candidate genes for milk yield supported by this work include GRINA, CYHR1, FOXH1, TONSL, PPP1R16A, ARHGAP39, MAF1, OPLAH and MROH1, whereas newly identified candidate genes are MIR2308, ZNF7, ZNF34, SLURP1, MAFA and KIFC2 (BTA14). The protein lipidation biological process term, which plays a key role in controlling protein localization and function, was identified as the most important term enriched by the identified genes.

Bovine Tuberculosis (bTB) caused by Mycobacterium bovis is a livestock disease of global economic and public health importance. There are currently no effective vaccines available for livestock and so control relies on animal level surveillance and pasteurisation of dairy products. A new alternative control approach is to exploit the genetic variability of the host; recent studies have demonstrated that breeding Bos taurus cattle for increased resistance to bTB is feasible. The utility of such an approach is still unknown for the Bos indicus cattle population. This study aims to assess genetic variation in bTB resistance and the underlying genomic architecture in Bos indicus breeds in Cameroon. We conducted a cross-sectional study of slaughter cattle in Cameroon and genotyped a sample of 213 cattle. Their genomic diversity was characterised using PCA, hierarchical clustering and admixture analysis. We assessed genetic variation in bTB resistance using heritability analysis and compared quantitative trait loci. Previous studies had found that breed was an important factor in explaining the epidemiology of bTB, with Fulani cattle appearing to be more susceptible than mixed breeds. However, we show that the apparent phenotypic differences in visual appearance between the breeds was not reflected by clear genomic differences. At the genetic level, cattle belonging to different hierarchical genomic clusters differed in their susceptibility to bTB. There was evidence of a genomic association between M. bovis infection status with specific SNPs. We highlight the need to understand the challenges faced by livestock in specific settings both in terms of pathogens and the environment, in addition to their intended purpose and how they fit into a defined management system. It is only at this point livestock keepers can then make informed breeding choices, not only for resistance to disease but also for increasing production

Improving nitrogen efficiency of individual cows has become a key target in dairy production systems, both for environmental and economic reasons. Results of this study demonstrate the potential of MIR analysis of milk to provide information on nitrogen use efficiency. This approach has the potential to allow future large-scale predictions for genetic studies, as well as providing a tool for herd and diet management.Potential of milk mid-infrared spectra to predict nitrogen use efficiency of individual dairy cows in early lactation.