Genomic structural variations are an important source of genetic diversity. Copy number variations (CNVs), gains and losses of large regions of genomic sequence between individuals of a species, have been associated with a wide variety of phenotypic traits. However, in cattle, as well as many other species, relatively little is understood about CNV, including frequency of CNVs in the genome, sizes, and locations, chromosomal properties, and evolutionary processes acting to shape CNV. In this work, we focused on copy number variation in the bovine genome, with the aim to detect CNVs in Bos taurus coding sequence and explore potential evolutionary mechanisms shaping these CNV. We identified and characterized CNV regions by utilizing exome sequence from 175 influential sires used in the Germplasm Evaluation project, representing 10 breeds. We examined various evolutionary and functional aspects of these CNVs, including selective constraint on CNV-overlapped genes, centrality of CNV genes in protein-protein interaction networks, and tissue-specific expression of CNV genes. Patterns of CNV in the Bos taurus genome reveal that reduced functional constraint and mutational bias may play a prominent role in shaping this type of structural variation.

Ongoing developments and cost decreases in next-generation sequencing (NGS) technologies have led to an increase in their application, which has greatly enhanced the fields of genetics and genomics. Mapping sequence reads onto a reference genome is a fundamental step in the analysis of NGS data. Efficient alignment of the reads onto the reference genome with high accuracy is very important because it determines the global quality of downstream analyses. In this study, we evaluate the performance of three Burrows-Wheeler transform-based mappers, BWA, Bowtie2, and HISAT2, in the context of paired-end Illumina whole-genome sequencing of livestock, using simulated sequence data sets with varying sequence read lengths, insert sizes, and levels of genomic coverage, as well as five real data sets. The mappers were evaluated based on two criteria, computational resource/time requirements and robustness of mapping. Our results show that BWA and Bowtie2 tend to be more robust than HISAT2, while HISAT2 was significantly faster and used less memory than both BWA and Bowtie2. We conclude that there is not a single mapper that is ideal in all scenarios but rather the choice of alignment tool should be driven by the application and sequencing technology.

This study aimed to identify transcriptome differences between distinct or transitional stage spherical, ovoid, and tubular porcine blastocysts throughout the initiation of elongation. We performed a global transcriptome analysis of differential gene expression using RNA‐Seq with high temporal resolution between spherical, ovoid, and tubular stage blastocysts at specific sequential stages of development from litters containing conceptus populations of distinct or transitional blastocysts. After RNA‐Seq analysis, significant differentially expressed genes (DEGs) and pathways were identified between distinct morphologies or sequential development stages. Overall, 1898 significant DEGs were identified between distinct spherical and ovoid morphologies, with 311 total DEGs between developmental stages throughout this first morphological transition, while 15 were identified between distinct ovoid and tubular, with eight total throughout these second morphological transition developmental stages. The high quantity of DEGs and pathways between conceptus stages throughout the spherical to ovoid transition suggests the importance of gene regulation during this first morphological transition for initiating elongation. Further, extensive DEG coverage of known elongation signaling pathways was illustrated from spherical to ovoid, and regulation of lipid signaling and membrane/ECM remodeling across these early conceptus stages were implicated as essential to this process, providing novel insights into potential mechanisms governing this rapid morphological change.

Decreasing costs are making low coverage sequencing with imputation to a comprehensive reference panel an attractive alternative to obtain functional variant genotypes that can increase the accuracy of genomic prediction. To assess the potential of low-pass sequencing, genomic sequence of 77 steers sequenced to >10X coverage was downsampled to 1X and imputed to a reference of 946 cattle representing multiple Bos taurus and Bos indicus-influenced breeds. Genotypes for nearly 60 million variants detected in the reference were imputed from the downsampled sequence. The imputed genotypes strongly agreed with the SNP array genotypes (r¯=0.99) and the genotypes called from the transcript sequence (r¯=0.97). Effects of BovineSNP50 and GGP-F250 variants on birth weight, postweaning gain, and marbling were solved without the steers’ phenotypes and genotypes, then applied to their genotypes, to predict the molecular breeding values (MBV). The steers’ MBV were similar when using imputed and array genotypes. Replacing array variants with functional sequence variants might allow more robust MBV. Imputation from low coverage sequence offers a viable, low-cost approach to obtain functional variant genotypes that could improve genomic prediction.

Copy number variations (CNVs) are large insertions, deletions or duplications in the genome that vary between members of a species and are known to affect a wide variety of phenotypic traits. In this study, we identified CNVs in a population of bulls using low coverage next-generation sequence data. First, in order to determine a suitable strategy for CNV detection in our data, we compared the performance of three distinct CNV detection algorithms on benchmark CNV datasets and concluded that using the multiple sample read depth approach was the best method for identifying CNVs in our sequences. Using this technique, we identified a total of 1341 copy number variable regions (CNVRs) from genome sequences of 154 purebred sires used in Cycle VII of the USMARC Germplasm Evaluation Project. These bulls represented the seven most popular beef breeds in the United States: Hereford, Charolais, Angus, Red Angus, Simmental, Gelbvieh and Limousin. The CNVRs covered 6.7% of the bovine genome and spanned 2465 protein-coding genes and many known quantitative trait loci (QTL). Genes harbored in the CNVRs were further analyzed to determine their function as well as to find any breed-specific differences that may shed light on breed differences in adaptation, health and production.

BackgroundFeed intake and body weight gain are economically important inputs and outputs of beef production systems. The purpose of this study was to discover differentially expressed genes that will be robust for feed intake and gain across a large segment of the cattle industry. Transcriptomic studies often suffer from issues with reproducibility and cross-validation. One way to improve reproducibility is by integrating multiple datasets via meta-analysis. RNA sequencing (RNA-Seq) was performed on longissimus dorsi muscle from 80 steers (5 cohorts, each with 16 animals) selected from the outside fringe of a bivariate gain and feed intake distribution to understand the genes and pathways involved in feed efficiency. In each cohort, 16 steers were selected from one of four gain and feed intake phenotypes (n = 4 per phenotype) in a 2 × 2 factorial arrangement with gain and feed intake as main effect variables. Each cohort was analyzed as a single experiment using a generalized linear model and results from the 5 cohort analyses were combined in a meta-analysis to identify differentially expressed genes (DEG) across the cohorts.ResultsA total of 51 genes were differentially expressed for the main effect of gain, 109 genes for the intake main effect, and 11 genes for the gain x intake interaction (Pcorrected < 0.05). A jackknife sensitivity analysis showed that, in general, the meta-analysis produced robust DEGs for the two main effects and their interaction. Pathways identified from over-represented genes included mitochondrial energy production and oxidative stress pathways for the main effect of gain due to DEG including GPD1, NDUFA6, UQCRQ, ACTC1, and MGST3. For intake, metabolic pathways including amino acid biosynthesis and degradation were identified, and for the interaction analysis the pathways identified included GADD45, pyridoxal 5’phosphate salvage, and caveolar mediated endocytosis signaling.ConclusionsVariation among DEG identified by cohort suggests that environment and breed may play large roles in the expression of genes associated with feed efficiency in the muscle of beef cattle. Meta-analyses of transcriptome data from groups of animals over multiple cohorts may be necessary to elucidate the genetics contributing these types of biological phenotypes.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4769-8) contains supplementary material, which is available to authorized users.

Sensory neurons in trigeminal ganglia (TG) of calves latently infected with bovine herpesvirus 1 (BoHV-1) abundantly express latency-related (LR) gene products, including a protein (ORF2) and two micro-RNAs. Recent studies in mouse neuroblastoma cells (Neuro-2A) demonstrated ORF2 interacts with β-catenin and a β-catenin coactivator, high-mobility group AT-hook 1 (HMGA1) protein, which correlates with increased β-catenin-dependent transcription and cell survival. β-Catenin and HMGA1 are readily detected in a subset of latently infected TG neurons but not TG neurons from uninfected calves or reactivation from latency. Consequently, we hypothesized that the Wnt/β-catenin signaling pathway is differentially expressed during the latency and reactivation cycle and an active Wnt pathway promotes latency. RNA-sequencing studies revealed that 102 genes associated with the Wnt/β-catenin signaling pathway were differentially expressed in TG during the latency-reactivation cycle in calves. Wnt agonists were generally expressed at higher levels during latency, but these levels decreased during dexamethasone-induced reactivation. The Wnt agonist bone morphogenetic protein receptor 2 (BMPR2) was intriguing because it encodes a serine/threonine receptor kinase that promotes neuronal differentiation and inhibits cell death. Another differentially expressed gene encodes a protein kinase (Akt3), which is significant because Akt activity enhances cell survival and is linked to herpes simplex virus 1 latency and neuronal survival. Additional studies demonstrated ORF2 increased Akt3 steady-state protein levels and interacted with Akt3 in transfected Neuro-2A cells, which correlated with Akt3 activation. Conversely, expression of Wnt antagonists increased during reactivation from latency. Collectively, these studies suggest Wnt signaling cooperates with LR gene products, in particular ORF2, to promote latency. Lifelong BoHV-1 latency primarily occurs in sensory neurons. The synthetic corticosteroid dexamethasone consistently induces reactivation from latency in calves. RNA sequencing studies revealed 102 genes associated with the Wnt/β-catenin signaling pathway are differentially regulated during the latency-reactivation cycle. Two protein kinases associated with the Wnt pathway, Akt3 and BMPR2, were expressed at higher levels during latency but were repressed during reactivation. Furthermore, five genes encoding soluble Wnt antagonists and β-catenin-dependent transcription inhibitors were induced during reactivation from latency. These findings are important because Wnt, BMPR2, and Akt3 promote neurogenesis and cell survival, processes crucial for lifelong viral latency. In transfected neuroblastoma cells, a viral protein expressed during latency (ORF2) interacts with and enhances Akt3 protein kinase activity. These findings provide insight into how cellular factors associated with the Wnt signaling pathway cooperate with LR gene products to regulate the BoHV-1 latency-reactivation cycle.

Copy number variations (CNVs) are gains and losses of large regions of genomic sequence between individuals of a species. Although CNVs have been associated with various phenotypic traits in humans and other species, the extent to which CNVs impact phenotypic variation remains unclear. In swine, as well as many other species, relatively little is understood about the frequency of CNV in the genome, sizes, locations, and other chromosomal properties. In this work, we identified and characterized CNV by utilizing whole-genome sequence from 240 members of an intensely phenotyped experimental swine herd at the U.S. Meat Animal Research Center (USMARC). These animals included all 24 of the purebred founding boars (12 Duroc and 12 Landrace), 48 of the founding Yorkshire-Landrace composite sows, 109 composite animals from generations 4 through 9, 29 composite animals from generation 15, and 30 purebred industry boars (15 Landrace and 15 Yorkshire) used as sires in generations 10 through 15. Using a combination of split reads, paired-end mapping, and read depth approaches, we identified a total of 3,538 copy number variable regions (CNVRs), including 1,820 novel CNVRs not reported in previous studies. The CNVRs covered 0.94% of the porcine genome and overlapped 1,401 genes. Gene ontology analysis identified that CNV-overlapped genes were enriched for functions related to organism development. Additionally, CNVRs overlapped with many known quantitative trait loci (QTL). In particular, analysis of QTL previously identified in the USMARC herd showed that CNVRs were most overlapped with reproductive traits, such as age of puberty and ovulation rate, and CNVRs were significantly enriched for reproductive QTL.