An atlas of bovine gene expression reveals novel distinctive tissue characteristics and evidence for improving genome annotation

Research Progress and Applications of Bovine Genome in the Tribe Bovini

Various bovine species have been domesticated and bred for thousands of years, and they provide adequate animal-derived products, including meat, milk, and leather, to meet human requirements. Despite the review studies on economic traits in cattle, the genetic basis of traits has only been partially explained by phenotype and pedigree breeding methods, due to the complexity of genomic regulation during animal development and growth. With the advent of next-generation sequencing technology, genomics projects, such as the 1000 Bull Genomes Project, Functional Annotation of Animal Genomes project, and Bovine Pangenome Consortium, have advanced bovine genomic research. These large-scale genomics projects gave us a comprehensive concept, technology, and public resources. In this review, we summarize the genomics research progress of the main bovine species during the past decade, including cattle (Bos taurus), yak (Bos grunniens), water buffalo (Bubalus bubalis), zebu (Bos indicus), and gayal (Bos frontalis). We mainly discuss the development of genome sequencing and functional annotation, focusing on how genomic analysis reveals genetic variation and its impact on phenotypes in several bovine species.

A protein-coding gene expression atlas from the brain of pregnant and non-pregnant goats

Background: The brain is an extraordinarily complex organ with multiple anatomical structures involved in highly specialized functions related with behavior and physiological homeostasis. Our goal was to build an atlas of protein-coding gene expression in the goat brain by sequencing the transcriptomes of 12 brain regions in seven female Murciano-Granadina goats, from which three of them were 1-month pregnant. Results: Between 14,889 (cerebellar hemisphere) and 15,592 (pineal gland) protein-coding genes were expressed in goat brain regions, and most of them displayed ubiquitous or broad patterns of expression across tissues. Principal component analysis and hierarchical clustering based on the patterns of mRNA expression revealed that samples from certain brain regions tend to group according to their position in the anterior-posterior axis of the neural tube, i.e., hindbrain (pons and medulla oblongata), midbrain (rostral colliculus) and forebrain (frontal neocortex, olfactory bulb, hypothalamus, and hippocampus). Exceptions to this observation were cerebellum and glandular tissues (pineal gland and hypophysis), which showed highly divergent mRNA expression profiles. Differential expression analysis between pregnant and non-pregnant goats revealed moderate changes of mRNA expression in the frontal neocortex, hippocampus, adenohypophysis and pons, and very dramatic changes in the olfactory bulb. Many genes showing differential expression in this organ are related to olfactory function and behavior in humans. Conclusion: With the exception of cerebellum and glandular tissues, there is a relationship between the cellular origin of sampled regions along the anterior-posterior axis of the neural tube and their mRNA expression patterns in the goat adult brain. Gestation induces substantial changes in the mRNA expression of the olfactory bulb, a finding consistent with the key role of this anatomical structure on the development of maternal behavior.

Lactoferrin, Osteopontin and Lactoferrin–Osteopontin Complex: A Critical Look on Their Role in Perinatal Period and Cardiometabolic Disorders

Milk-derived bioactive proteins have increasingly gained attention and consideration throughout the world due to their high-quality amino acids and multiple health-promoting attributes. Apparently, being at the forefront of functional foods, these bioactive proteins are also suggested as potential alternatives for the management of various complex diseases. In this review, we will focus on lactoferrin (LF) and osteopontin (OPN), two multifunctional dairy proteins, as well as to their naturally occurring bioactive LF–OPN complex. While describing their wide variety of physiological, biochemical, and nutritional functionalities, we will emphasize their specific roles in the perinatal period. Afterwards, we will evaluate their ability to control oxidative stress, inflammation, gut mucosal barrier, and intestinal microbiota in link with cardiometabolic disorders (CMD) (obesity, insulin resistance, dyslipidemia, and hypertension) and associated complications (diabetes and atherosclerosis). This review will not only attempt to highlight the mechanisms of action, but it will critically discuss the potential therapeutic applications of the underlined bioactive proteins in CMD.

Comparative transcriptomic analysis reveals region-specific expression patterns in different beef cuts

BACKGROUND

Beef cuts in different regions of the carcass have different meat quality due to their distinct physiological function. The objective of this study was to characterize the region-specific expression differences using comparative transcriptomics analysis among five representative beef cuts (tenderloin, longissimus lumborum, rump, neck, chuck).

RESULTS

We obtained 15,701 expressed genes in 30 muscle samples across five regions from carcass meat. We identified a total of 80 region-specific genes (RSGs), ranging from three (identified in the rump cut) to thirty (identified in the longissimus lumborum cut), and detected 25 transcription factors (TFs) for RSGs. Using a co-expression network analysis, we detected seven region-specific modules, including three positively correlated modules and four negatively correlated modules. We finally obtained 91 candidate genes related to meat quality, and the functional enrichment analyses showed that these genes were mainly involved in muscle fiber structure (e.g., TNNI1, TNNT1), fatty acids (e.g., SCD, LPL), amino acids (ALDH2, IVD, ACADS), ion channel binding (PHPT1, SNTA1, SUMO1, CNBP), protein processing (e.g., CDC37, GAPDH, NRBP1), as well as energy production and conversion (e.g., ATP8, COX8B, NDUFB6). Moreover, four candidate genes (ALDH2, CANX, IVD, PHPT1) were validated using RT-qPCR analyses which further supported our RNA-seq results.

CONCLUSIONS

Our results provide valuable insights into understanding the transcriptome regulation of meat quality in different beef cuts, and these findings may further help to improve the selection for health-beneficial meat in beef cattle.

Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

Background

A comprehensive analysis of gene expression profiling across tissues can provide necessary information for an in-depth understanding of their biological functions. We performed a large-scale gene expression analysis and generated a high-resolution atlas of the transcriptome in beef cattle.

Results

Our transcriptome atlas was generated from 135 bovine tissues in adult beef cattle, covering 51 tissue types of major organ systems (e.g., muscular system, digestive system, immune system, reproductive system). Approximately 94.76% of sequencing reads were successfully mapped to the reference genome assembly ARS-UCD1.2. We detected a total of 60,488 transcripts, and 32% of them were not reported before. We identified 2654 housekeeping genes (HKGs) and 477 tissue-specific genes (TSGs) across tissues. Using weighted gene co-expression network analysis, we obtained 24 modules with 237 hub genes (HUBGs). Functional enrichment analysis showed that HKGs mainly maintain the basic biological activities of cells, while TSGs were involved in tissue differentiation and specific physiological processes. HKGs in bovine tissues were more conserved in terms of expression pattern as compared to TSGs and HUBGs among multiple species. Finally, we obtained a subset of tissue-specific differentially expressed genes (DEGs) between beef and dairy cattle and several functional pathways, which may be involved in production and health traits.

Conclusions

We generated a large-scale gene expression atlas across the major tissues in beef cattle, providing valuable information for enhancing genome assembly and annotation. HKGs, TSGs, and HUBGs further contribute to better understanding the biology and evolution of multiple tissues in cattle. DEGs between beef and dairy cattle also fill in the knowledge gaps about differential transcriptome regulation of bovine tissues underlying economically important traits.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01269-4.

Network Analyses Predict Small RNAs That Might Modulate Gene Expression in the Testis and Epididymis of Bos indicus Bulls

Spermatogenesis relies on complex molecular mechanisms, essential for the genesis and differentiation of the male gamete. Germ cell differentiation starts at the testicular parenchyma and finishes in the epididymis, which has three main regions: head, body, and tail. RNA-sequencing data of the testicular parenchyma (TP), head epididymis (HE), and tail epididymis (TE) from four bulls (three biopsies per bull: 12 samples) were subjected to differential expression analyses, functional enrichment analyses, and co-expression analyses. The aim was to investigate the co-expression and infer possible regulatory roles for transcripts involved in the spermatogenesis of Bos indicus bulls. Across the three pairwise comparisons, 3,826 differentially expressed (DE) transcripts were identified, of which 384 are small RNAs. Functional enrichment analysis pointed to gene ontology (GO) terms related to ion channel activity, detoxification of copper, neuroactive receptors, and spermatogenesis. Using the regulatory impact factor (RIF) algorithm, we detected 70 DE small RNAs likely to regulate the DE transcripts considering all pairwise comparisons among tissues. The pattern of small RNA co-expression suggested that these elements are involved in spermatogenesis regulation. The 3,826 DE transcripts (mRNAs and small RNAs) were further subjected to co-expression analyses using the partial correlation and information theory (PCIT) algorithm for network prediction. Significant correlations underpinned the co-expression network, which had 2,216 transcripts connected by 158,807 predicted interactions. The larger network cluster was enriched for male gamete generation and had 15 miRNAs with significant RIF. The miRNA bta-mir-2886 showed the highest number of connections (601) and was predicted to down-regulate ELOVL3, FEZF2, and HOXA13 (negative co-expression correlations and confirmed with TargetScan). In short, we suggest that bta-mir-2886 and other small RNAs might modulate gene expression in the testis and epididymis, in Bos indicus cattle.

Expression of mitochondrial protein genes encoded by nuclear and mitochondrial genomes correlate with energy metabolism in dairy cattle

Background

Mutations in the mitochondrial genome have been implicated in mitochondrial disease, often characterized by impaired cellular energy metabolism. Cellular energy metabolism in mitochondria involves mitochondrial proteins (MP) from both the nuclear (NuMP) and mitochondrial (MtMP) genomes. The expression of MP genes in tissues may be tissue specific to meet varying specific energy demands across the tissues. Currently, the characteristics of MP gene expression in tissues of dairy cattle are not well understood. In this study, we profile the expression of MP genes in 29 adult and six foetal tissues in dairy cattle using RNA sequencing and gene expression analyses: particularly differential gene expression and co-expression network analyses.

Results

MP genes were differentially expressed (DE; over-expressed or under-expressed) across tissues in cattle. All 29 tissues showed DE NuMP genes in varying proportions of over-expression and under-expression. On the other hand, DE of MtMP genes was observed in < 50% of tissues and notably MtMP genes within a tissue was either all over-expressed or all under-expressed. A high proportion of NuMP (up to 60%) and MtMP (up to 100%) genes were over-expressed in tissues with expected high metabolic demand; heart, skeletal muscles and tongue, and under-expressed (up to 45% of NuMP, 77% of MtMP genes) in tissues with expected low metabolic rates; leukocytes, thymus, and lymph nodes. These tissues also invariably had the expression of all MtMP genes in the direction of dominant NuMP genes expression. The NuMP and MtMP genes were highly co-expressed across tissues and co-expression of genes in a cluster were non-random and functionally enriched for energy generation pathway. The differential gene expression and co-expression patterns were validated in independent cow and sheep datasets.

Conclusions

The results of this study support the concept that there are biological interaction of MP genes from the mitochondrial and nuclear genomes given their over-expression in tissues with high energy demand and co-expression in tissues. This highlights the importance of considering MP genes from both genomes in future studies related to mitochondrial functions and traits related to energy metabolism.

Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle

By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biology, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testis-specific genes evolve fastest). Through integrative analyses of those tissue-specific genes with large-scale genome-wide association studies, we detected relevant tissues/cell types and candidate genes for 45 economically important traits in cattle, including blood/immune system (e.g., CCDC88C) for male fertility, brain (e.g., TRIM46 and RAB6A) for milk production, and multiple growth-related tissues (e.g., FGF6 and CCND2) for body conformation. We validated these findings by using epigenomic data across major somatic tissues and sperm. Collectively, our findings provided novel insights into the genetic and biological mechanisms underlying complex traits in cattle, and our transcriptome atlas can serve as a primary source for biological interpretation, functional validation, studies of adaptive evolution, and genomic improvement in livestock.

Fasciola hepatica Infection in Cattle: Analyzing Responses of Peripheral Blood Mononuclear Cells (PBMC) Using a Transcriptomics Approach

The parasitic helminth Fasciola hepatica (liver fluke) causes economic loss to the livestock industry globally and also causes zoonotic disease. New control strategies such as vaccines are urgently needed, due to the rise of drug resistance in parasite populations. Vaccine development requires a comprehensive understanding of the immunological events during infection. Previous in vivo studies by our group have investigated global differentially expressed genes (DEGs) in ovine peripheral blood mononuclear cells (PBMC) in response to both acute and chronic F. hepatica infection. This work demonstrated that pathways involved in the pathogenesis of ovine fasciolosis included fibrosis, inhibition of macrophage nitric oxide production, and antibody isotype switching, among others. Transcriptomic changes in PBMC populations following F. hepatica infection in cattle, in which the disease phenotype is quite different, have not yet been examined. Using RNA sequencing we investigated gene expression changes in PBMC isolated from 9 non-infected and 11 F. hepatica-experimentally-infected calves immediately before infection, at 1 and at 14 weeks post-infection. Longitudinal time-course comparisons between groups revealed 21 and 1,624 DEGs driven exclusively by F. hepatica infection in cattle at acute and chronic stages, respectively. These results show that fewer DEGs at the acute stage of infection can be identified in cattle, as compared with sheep. In addition, the log₂ fold-changes of these DEGs were relatively low (−1 to 3) reflecting the different clinical presentation of F. hepatica infection in cattle. Gene pathways for hepatic fibrosis and hepatic cholestasis along with apoptosis of antigen-presenting cells were enriched at chronic stages. Our results reflect the major differences in the disease phenotype between cattle and sheep and may indicate pathways to target in vaccine development.

Genetic and epigenetic architecture of paternal origin contribute to gestation length in cattle

The length of gestation can affect offspring health and performance. Both maternal and fetal effects contribute to gestation length; however, paternal contributions to gestation length remain elusive. Using genome-wide association study (GWAS) in 27,214 Holstein bulls with millions of gestation records, here we identify nine paternal genomic loci associated with cattle gestation length. We demonstrate that these GWAS signals are enriched in pathways relevant to embryonic development, and in differentially methylated regions between sperm samples with long and short gestation length. We reveal that gestation length shares genetic and epigenetic architecture in sperm with calving ability, body depth, and conception rate. While several candidate genes are detected in our fine-mapping analysis, we provide evidence indicating ZNF613 as a promising candidate for cattle gestation length. Collectively, our findings support that the paternal genome and epigenome can impact gestation length potentially through regulation of the embryonic development.

Lingzhao Fang et al. studied the paternal genetic variants that affect gestational length in cattle. They found that paternal genes from pathways involved in embryonic development were associated with gestation length, and that these were often found in differentially methylated regions of the genome.

Candidate genes associated with the heritable humoral response to Mycobacterium avium ssp. paratuberculosis in dairy cows have factors in common with gastrointestinal diseases in humans

Infection of cattle with bovine paratuberculosis (i.e., Johne's disease) is caused by Mycobacterium avium ssp. paratuberculosis (MAP) and results in a chronic incurable gastroenteritis. This disease, which has economic ramifications for the cattle industry, is increasing in detected prevalence globally; subclinically infected animals can silently shed the bacterium into the environment for years, exposing contemporaries and hampering disease-control programs. The objective of the present study was to first quantify the genetic parameters for humoral response to MAP in dairy cattle. This was followed by a genome-based association analysis and subsequent downstream bioinformatic analyses from imputed whole genome sequence SNP data. After edits, ELISA test records were available on 136,767 cows; analyses were also undertaken on a subset of 33,818 of these animals from herds with at least 5 MAP ELISA-positive cows, with at least 1 of those positive cows being homebred. Variance components were estimated using univariate animal and sire linear mixed models. The heritability calculated from the animal model for humoral response to MAP using alternative phenotype definitions varied from 0.02 (standard error = 0.003) to 0.05 (standard error = 0.008). The genome-based associations were undertaken within a mixed model framework using weighted deregressed estimated breeding values as a dependent variable on 1,883 phenotyped animals that were ≥87.5% Holstein-Friesian. Putative susceptibility quantitative trait loci (QTL) were identified on Bos taurus autosome 1, 3, 5, 6, 8, 9, 10, 11, 13, 14, 18, 21, 23, 25, 26, 27, and 29; mapping the most significant SNP to genes within and overlapping these QTL revealed that the most significant associations were with the 10 functional candidate genes KALRN, ZBTB20, LPP, SLA2, FI3A1, LRCH3, DNAJC6, ZDHHC14, SNX1, and HAS2. Pathway analysis failed to reveal significantly enriched biological pathways, when both bovine-specific pathway data and human ortholog data were taken into account. The existence of genetic variation for MAP susceptibility in a large data set of dairy cows signifies the potential of breeding programs for reducing MAP susceptibility. Furthermore, the identification of susceptible QTL facilitates greater biological understanding of bovine paratuberculosis and potential therapeutic targets for future investigation. The novel molecular similarities identified between bovine paratuberculosis and human inflammatory bowel disease suggest potential for human therapeutic interventions to be translated to veterinary medicine and vice versa.

An intersection network based on combining SNP coassociation and RNA coexpression networks for feed utilization traits in Japanese Black cattle

Genome-wide association studies (GWAS) of quantitative traits have detected numerous genetic associations, but they encounter difficulties in pinpointing prominent candidate genes and inferring gene networks. The present study used a systems genetics approach integrating GWAS results with external RNA-expression data to detect candidate gene networks in feed utilization and growth traits of Japanese Black cattle, which are matters of concern. A SNP coassociation network was derived from significant correlations between SNPs with effects estimated by GWAS across 7 phenotypic traits. The resulting network genes contained significant numbers of annotations related to the traits. Using bovine transcriptome data from a public database, an RNA coexpression network was inferred based on the similarity of expression patterns across different tissues. An intersection network was then generated by superimposing the SNP and RNA networks and extracting shared interactions. This intersection network contained 4 tissue-specific modules: nervous system, reproductive system, muscular system, and glands. To characterize the structure (topographical properties) of the 3 networks, their scale-free properties were evaluated, which revealed that the intersection network was the most scale-free. In the subnetwork containing the most connected transcription factors (URI1, ROCK2, and ETV6), most genes were widely expressed across tissues, and genes previously shown to be involved in the traits were found. Results indicated that the current approach might be used to construct a gene network that better reflects biological information, providing encouragement for the genetic dissection of economically important quantitative traits.

A comprehensive manually-curated compendium of bovine transcription factors

Transcription factors (TFs) are pivotal regulatory proteins that control gene expression in a context-dependent and tissue-specific manner. In contrast to human, where comprehensive curated TF collections exist, bovine TFs are only rudimentary recorded and characterized. In this article, we present a manually-curated compendium of 865 sequence-specific DNA-binding bovines TFs, which we analyzed for domain family distribution, evolutionary conservation, and tissue-specific expression. In addition, we provide a list of putative transcription cofactors derived from known interactions with the identified TFs. Since there is a general lack of knowledge concerning the regulation of gene expression in cattle, the curated list of TF should provide a basis for an improved comprehension of regulatory mechanisms that are specific to the species.

A high resolution atlas of gene expression in the domestic sheep (Ovis aries)

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of 'guilt by association' was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages.

Genomewide association study of liver abscess in beef cattle

Fourteen percent of U.S. cattle slaughtered in 2011 had liver abscesses, resulting in reduced carcass weight, quality, and value. Liver abscesses can result from a common bacterial cause, , which inhabits rumen lesions caused by acidosis and subsequently escapes into the blood stream, is filtered by the liver, and causes abscesses in the liver. Our aim was to identify SNP associated with liver abscesses in beef cattle. We used lung samples as a DNA source because they have low economic value, they have abundant DNA, and we had unrestricted access to sample them. We collected 2,304 lung samples from a beef processing plant: 1,152 from animals with liver abscess and 1,152 from animals without liver abscess. Lung tissue from pairs of animals, 1 with abscesses and another without, were collected from near one another on the viscera table to ensure that pairs of phenotypically extreme animals came from the same lot. Within each phenotype (abscess or no abscess), cattle were pooled by slaughter sequence into 12 pools of 96 cattle for each phenotype for a total of 24 pools. The pools were constructed by equal volume of frozen lung tissue from each animal. The DNA needed to allelotype each pool was then extracted from pooled lung tissue and the BovineHD Bead Array (777,962 SNP) was run on all 24 pools. Total intensity (TI), an indicator of copy number variants, was the sum of intensities from red and green dyes. Pooling allele frequency (PAF) was red dye intensity divided TI. Total intensity and PAF were weighted by the inverse of their respective genomic covariance matrices computed over all SNP across the genome. A false discovery rate ≤ 5% was achieved for 15 SNP for PAF and 20 SNP for TI. Genes within 50 kbp from significant SNP were in diverse pathways including maintenance of pH homeostasis in the gastrointestinal tract, maintain immune defenses in the liver, migration of leukocytes from the blood into infected tissues, transport of glutamine into the kidney in response to acidosis to facilitate production of bicarbonate to increase pH, aggregate platelets to liver injury to facilitate liver repair, and facilitate axon guidance. Evidence from the 35 detected SNP associations combined with evidence of polygenic variation indicate that there is adequate genetic variation in incidence rate of liver abscesses, which could be exploited to select sires for reduced susceptibility to subacute acidosis and associated liver abscess.

Genomic Selection in Dairy Cattle: The USDA Experience

Genomic selection has revolutionized dairy cattle breeding. Since 2000, assays have been developed to genotype large numbers of single-nucleotide polymorphisms (SNPs) at relatively low cost. The first commercial SNP genotyping chip was released with a set of 54,001 SNPs in December 2007. Over 15,000 genotypes were used to determine which SNPs should be used in genomic evaluation of US dairy cattle. Official USDA genomic evaluations were first released in January 2009 for Holsteins and Jerseys, in August 2009 for Brown Swiss, in April 2013 for Ayrshires, and in April 2016 for Guernseys. Producers have accepted genomic evaluations as accurate indications of a bull's eventual daughter-based evaluation. The integration of DNA marker technology and genomics into the traditional evaluation system has doubled the rate of genetic progress for traits of economic importance, decreased generation interval, increased selection accuracy, reduced previous costs of progeny testing, and allowed identification of recessive lethals.

Reduced representation bisulphite sequencing of ten bovine somatic tissues reveals DNA methylation patterns and their impacts on gene expression

Background

As a major epigenetic component, DNA methylation plays important functions in individual development and various diseases. DNA methylation has been well studied in human and model organisms, but only limited data exist in economically important animals like cattle.

Results

Using reduced representation bisulphite sequencing (RRBS), we obtained single-base-resolution maps of bovine DNA methylation from ten somatic tissues. In total, we evaluated 1,868,049 cytosines in CG-enriched regions. While we found slightly low methylation levels (29.87 to 38.06 %) in cattle, the methylation contexts (CGs and non-CGs) of cattle showed similar methylation patterns to other species. Non-CG methylation was detected but methylation levels in somatic tissues were significantly lower than in pluripotent cells. To study the potential function of the methylation, we detected 10,794 differentially methylated cytosines (DMCs) and 836 differentially methylated CG islands (DMIs). Further analyses in the same tissues revealed many DMCs (including non-CGs) and DMIs, which were highly correlated with the expression of genes involved in tissue development.

Conclusions

In summary, our study provides a baseline dataset and essential information for DNA methylation profiles of cattle.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3116-1) contains supplementary material, which is available to authorized users.

Genome-wide CNV analysis reveals variants associated with growth traits in Bos indicus

BACKGROUND

Apart from single nucleotide polymorphism (SNP), copy number variation (CNV) is another important type of genetic variation, which may affect growth traits and play key roles for the production of beef cattle. To date, no genome-wide association study (GWAS) for CNV and body traits in beef cattle has been reported, so the present study aimed to investigate this type of association in one of the most important cattle subspecies: Bos indicus (Nellore breed).

RESULTS

We have used intensity data from over 700,000 SNP probes across the bovine genome to detect common CNVs in a sample of 2230 Nellore cattle, and performed GWAS between the detected CNVs and nine growth traits. After filtering for frequency and length, a total of 231 CNVs ranging from 894 bp to 4,855,088 bp were kept and tested as predictors for each growth trait using linear regression analysis with principal components correction. There were 49 significant associations identified among 17 CNVs and seven body traits after false discovery rate correction (P < 0.05). Among the 17 CNVs, three were significant or marginally significant for all the traits. We have compared the locations of associated CNVs with quantitative trait locus and the RefGene database, and found two sets of 9 CNVs overlapping with either known QTLs or genes, respectively. The gene overlapping with CNV100, KCNJ12, is a functional candidate for muscle development and plays critical roles in muscling traits.

CONCLUSION

This study presents the first CNV-based GWAS of growth traits using high density SNP microarray data in cattle. We detected 17 CNVs significantly associated with seven growth traits and one of them (CNV100) may be involved in growth traits through KCNJ12.

Effects of Pseudorabies Virus Infection on the Tracheobronchial Lymph Node Transcriptome

This study represents the first swine transcriptome hive plots created from gene set enrichment analysis (GSEA) data and provides a novel insight into the global transcriptome changes occurring in tracheobronchial lymph nodes (TBLN) and spanning the swine genome. RNA isolated from draining TBLN from 5-week-old pigs, either clinically infected with a feral isolate of Pseudorabies virus or uninfected, was interrogated using Illumina Digital Gene Expression Tag Profiling. More than 100 million tag sequences were observed, representing 4,064,189 unique 21-base sequences collected from TBLN at time points 1, 3, 6, and 14 days post-inoculation (dpi). Multidimensional statistical tests were applied to determine the significant changes in tag abundance, and then the tags were annotated. Hive plots were created to visualize the differential expression within the swine transcriptome defined by the Broad Institute’s GSEA reference datasets between infected and uninfected animals, allowing us to directly compare different conditions.

Fertility and genomics: comparison of gene expression in contrasting reproductive tissues of female cattle

To compare gene expression among bovine tissues, large bovine RNA-seq datasets were used, comprising 280 samples from 10 different bovine tissues (uterine endometrium, granulosa cells, theca cells, cervix, embryos, leucocytes, liver, hypothalamus, pituitary, muscle) and generating 260 Gbases of data. Twin approaches were used: an information–theoretic analysis of the existing annotated transcriptome to identify the most tissue-specific genes and a de-novo transcriptome annotation to evaluate general features of the transcription landscape. Expression was detected for 97% of the Ensembl transcriptome with at least one read in one sample and between 28% and 66% at a level of 10 tags per million (TPM) or greater in individual tissues. Over 95% of genes exhibited some level of tissue-specific gene expression. This was mostly due to different levels of expression in different tissues rather than exclusive expression in a single tissue. Less than 1% of annotated genes exhibited a highly restricted tissue-specific expression profile and approximately 2% exhibited classic housekeeping profiles. In conclusion, it is the combined effects of the variable expression of large numbers of genes (73%–93% of the genome) and the specific expression of a small number of genes (<1% of the transcriptome) that contribute to determining the outcome of the function of individual tissues.

Improvement of genome assembly completeness and identification of novel full-length protein-coding genes by RNA-seq in the giant panda genome

High-quality and complete gene models are the basis of whole genome analyses. The giant panda (Ailuropoda melanoleuca) genome was the first genome sequenced on the basis of solely short reads, but the genome annotation had lacked the support of transcriptomic evidence. In this study, we applied RNA-seq to globally improve the genome assembly completeness and to detect novel expressed transcripts in 12 tissues from giant pandas, by using a transcriptome reconstruction strategy that combined reference-based and de novo methods. Several aspects of genome assembly completeness in the transcribed regions were effectively improved by the de novo assembled transcripts, including genome scaffolding, the detection of small-size assembly errors, the extension of scaffold/contig boundaries, and gap closure. Through expression and homology validation, we detected three groups of novel full-length protein-coding genes. A total of 12.62% of the novel protein-coding genes were validated by proteomic data. GO annotation analysis showed that some of the novel protein-coding genes were involved in pigmentation, anatomical structure formation and reproduction, which might be related to the development and evolution of the black-white pelage, pseudo-thumb and delayed embryonic implantation of giant pandas. The updated genome annotation will help further giant panda studies from both structural and functional perspectives.

Application of Functional Genomics for Bovine Respiratory Disease Diagnostics

Bovine respiratory disease (BRD) is the most common economically important disease affecting cattle. For developing accurate diagnostics that can predict disease susceptibility/resistance and stratification, it is necessary to identify the molecular mechanisms that underlie BRD. To study the complex interactions among the bovine host and the multitude of viral and bacterial pathogens, as well as the environmental factors associated with BRD etiology, genome-scale high-throughput functional genomics methods such as microarrays, RNA-seq, and proteomics are helpful. In this review, we summarize the progress made in our understanding of BRD using functional genomics approaches. We also discuss some of the available bioinformatics resources for analyzing high-throughput data, in the context of biological pathways and molecular interactions. Although resources for studying host response to infection are avail-able, the corresponding information is lacking for majority of BRD pathogens, impeding progress in identifying diagnostic signatures for BRD using functional genomics approaches.

Comparative Proteomics of Human and Macaque Milk Reveals Species-Specific Nutrition during Postnatal Development

Milk has been well established as the optimal nutrition source for infants, yet there is still much to be understood about its molecular composition. Therefore, our objective was to develop and compare comprehensive milk proteomes for human and rhesus macaques to highlight differences in neonatal nutrition. We developed a milk proteomics technique that overcomes previous technical barriers including pervasive post-translational modifications and limited sample volume. We identified 1606 and 518 proteins in human and macaque milk, respectively. During analysis of detected protein orthologs, we identified 88 differentially abundant proteins. Of these, 93% exhibited increased abundance in human milk relative to macaque and include lactoferrin, polymeric immunoglobulin receptor, alpha-1 antichymotrypsin, vitamin D-binding protein, and haptocorrin. Furthermore, proteins more abundant in human milk compared with macaque are associated with development of the gastrointestinal tract, the immune system, and the brain. Overall, our novel proteomics method reveals the first comprehensive macaque milk proteome and 524 newly identified human milk proteins. The differentially abundant proteins observed are consistent with the perspective that human infants, compared with nonhuman primates, are born at a slightly earlier stage of somatic development and require additional support through higher quantities of specific proteins to nurture human infant maturation.

A genome-wide survey reveals a deletion polymorphism associated with resistance to gastrointestinal nematodes in Angus cattle

Gastrointestinal (GI) nematode infections are a worldwide threat to human health and animal production. In this study, we performed a genome-wide association study between copy number variations (CNVs) and resistance to GI nematodes in an Angus cattle population. Using a linear regression analysis, we identified one deletion CNV which reaches genome-wide significance after Bonferroni correction. With multiple mapped human olfactory receptor genes but no annotated bovine genes in the region, this significantly associated CNV displays high population frequencies (58.26 %) with a length of 104.8 kb on chr7. We further investigated the linkage disequilibrium (LD) relationships between this CNV and its nearby single nucleotide polymorphisms (SNPs) and genes. The underlining haplotype blocks contain immune-related genes such as ZNF496 and NLRP3. As this CNV co-segregates with linked SNPs and associated genes, we suspect that it could contribute to the detected variations in gene expression and thus differences in host parasite resistance.

Gene expression profiling in winged and wingless cotton aphids, Aphis gossypii (Hemiptera: Aphididae)

While trade-offs between flight capability and reproduction is a common phenomenon in wing dimorphic insects, the molecular basis is largely unknown. In this study, we examined the transcriptomic differences between winged and wingless morphs of cotton aphids, Aphis gossypii, using a tag-based digital gene expression (DGE) approach. Ultra high-throughput Illumina sequencing generated 5.30 and 5.39 million raw tags, respectively, from winged and wingless A. gossypii DGE libraries. We identified 1,663 differentially expressed transcripts, among which 58 were highly expressed in the winged A. gossypii, whereas 1,605 expressed significantly higher in the wingless morphs. Bioinformatics tools, including Gene Ontology, Cluster of Orthologous Groups, euKaryotic Orthologous Groups and Kyoto Encyclopedia of Genes and Genomes pathways, were used to functionally annotate these transcripts. In addition, 20 differentially expressed transcripts detected by DGE were validated by the quantitative real-time PCR. Comparative transcriptomic analysis of sedentary (wingless) and migratory (winged) A. gossyii not only advances our understanding of the trade-offs in wing dimorphic insects, but also provides a candidate molecular target for the genetic control of this agricultural insect pest.

The mammary gland in domestic ruminants: a systems biology perspective

Milk and dairy products are central elements in the human diet. It is estimated that 108kg of milk per year are consumed per person worldwide. Therefore, dairy production represents a relevant fraction of the economies of many countries, being cattle, sheep, goat, water buffalo, and other ruminants the main species used worldwide. An adequate management of dairy farming cannot be achieved without the knowledge on the biological mechanisms behind lactation in ruminants. Thus, understanding the morphology, development and regulation of the mammary gland in health, disease and production is crucial. Presently, innovative and high-throughput technologies such as genomics, transcriptomics, proteomics and metabolomics allow a much broader and detailed knowledge on such issues. Additionally, the application of a systems biology approach to animal science is vastly growing, as new advances in one field of specialization or animal species lead to new lines of research in other areas or/and are expanded to other species. This article addresses how modern research approaches may help us understand long-known issues in mammary development, lactation biology and dairy production.

BIOLOGICAL SIGNIFICANCE

Dairy production depends upon the knowledge of the morphology and regulation of the mammary gland and lactation. High-throughput technologies allow a much broader and detailed knowledge on the biology of the mammary gland. This paper reviews the major contributions that genomics, transcriptomics, metabolomics and proteomics approaches have provided to understand the regulation of the mammary gland in health, disease and production. In the context of mammary gland "omics"-based research, the integration of results using a Systems Biology Approach is of key importance.

An expression atlas of human primary cells: inference of gene function from coexpression networks

BACKGROUND

The specialisation of mammalian cells in time and space requires genes associated with specific pathways and functions to be co-ordinately expressed. Here we have combined a large number of publically available microarray datasets derived from human primary cells and analysed large correlation graphs of these data.

RESULTS

Using the network analysis tool BioLayout Express3D we identify robust co-associations of genes expressed in a wide variety of cell lineages. We discuss the biological significance of a number of these associations, in particular the coexpression of key transcription factors with the genes that they are likely to control.

CONCLUSIONS

We consider the regulation of genes in human primary cells and specifically in the human mononuclear phagocyte system. Of particular note is the fact that these data do not support the identity of putative markers of antigen-presenting dendritic cells, nor classification of M1 and M2 activation states, a current subject of debate within immunological field. We have provided this data resource on the BioGPS web site (http://biogps.org/dataset/2429/primary-cell-atlas/) and on macrophages.com (http://www.macrophages.com/hu-cell-atlas).

Identification of a nonsense mutation in CWC15 associated with decreased reproductive efficiency in Jersey cattle

With the recent advent of genomic tools for cattle, several recessive conditions affecting fertility have been identified and selected against, such as deficiency of uridine monophosphate synthase, complex vertebral malformation, and brachyspina. The current report refines the location of a recessive haplotype affecting fertility in Jersey cattle using crossover haplotypes, discovers the causative mutation using whole genome sequencing, and examines the gene's role in embryo loss. In an attempt to identify unknown recessive lethal alleles in the current dairy population, a search using deep Mendelian sampling of 5,288 Jersey cattle was conducted for high-frequency haplotypes that have a deficit of homozygotes at the population level. This search led to the discovery of a putative recessive lethal in Jersey cattle on Bos taurus autosome 15. The haplotype, denoted JH1, was associated with reduced fertility, and further investigation identified one highly-influential Jersey bull as the putative source ancestor. By combining SNP analysis of whole-genome sequences aligned to the JH1 interval and subsequent SNP validation a nonsense mutation in CWC15 was identified as the likely causative mutation underlying the fertility phenotype. No homozygous recessive individuals were found in 749 genotyped animals, whereas all known carriers and carrier haplotypes possessed one copy of the mutant allele. This newly identified lethal has been responsible for a substantial number of spontaneous abortions in Jersey dairy cattle throughout the past half-century. With the mutation identified, selection against the deleterious allele in breeding schemes will aid in reducing the incidence of this defect in the population. These results also show that carrier status can be imputed with high accuracy. Whole-genome resequencing proved to be a powerful strategy to rapidly identify a previously mapped deleterious mutation in a known carrier of a recessive lethal allele.

InnateDB: systems biology of innate immunity and beyond--recent updates and continuing curation

InnateDB (http://www.innatedb.com) is an integrated analysis platform that has been specifically designed to facilitate systems-level analyses of mammalian innate immunity networks, pathways and genes. In this article, we provide details of recent updates and improvements to the database. InnateDB now contains >196 000 human, mouse and bovine experimentally validated molecular interactions and 3000 pathway annotations of relevance to all mammalian cellular systems (i.e. not just immune relevant pathways and interactions). In addition, the InnateDB team has, to date, manually curated in excess of 18 000 molecular interactions of relevance to innate immunity, providing unprecedented insight into innate immunity networks, pathways and their component molecules. More recently, InnateDB has also initiated the curation of allergy- and asthma-related interactions. Furthermore, we report a range of improvements to our integrated bioinformatics solutions including web service access to InnateDB interaction data using Proteomics Standards Initiative Common Query Interface, enhanced Gene Ontology analysis for innate immunity, and the availability of new network visualizations tools. Finally, the recent integration of bovine data makes InnateDB the first integrated network analysis platform for this agriculturally important model organism.

Porcine tissue-specific regulatory networks derived from meta-analysis of the transcriptome

The processes that drive tissue identity and differentiation remain unclear for most tissue types. So are the gene networks and transcription factors (TF) responsible for the differential structure and function of each particular tissue, and this is particularly true for non model species with incomplete genomic resources. To better understand the regulation of genes responsible for tissue identity in pigs, we have inferred regulatory networks from a meta-analysis of 20 gene expression studies spanning 480 Porcine Affymetrix chips for 134 experimental conditions on 27 distinct tissues. We developed a mixed-model normalization approach with a covariance structure that accommodated the disparity in the origin of the individual studies, and obtained the normalized expression of 12,320 genes across the 27 tissues. Using this resource, we constructed a network, based on the co-expression patterns of 1,072 TF and 1,232 tissue specific genes. The resulting network is consistent with the known biology of tissue development. Within the network, genes clustered by tissue and tissues clustered by site of embryonic origin. These clusters were significantly enriched for genes annotated in key relevant biological processes and confirm gene functions and interactions from the literature. We implemented a Regulatory Impact Factor (RIF) metric to identify the key regulators in skeletal muscle and tissues from the central nervous systems. The normalization of the meta-analysis, the inference of the gene co-expression network and the RIF metric, operated synergistically towards a successful search for tissue-specific regulators. Novel among these findings are evidence suggesting a novel key role of ERCC3 as a muscle regulator. Together, our results recapitulate the known biology behind tissue specificity and provide new valuable insights in a less studied but valuable model species.

miR-BAG: bagging based identification of microRNA precursors

Non-coding elements such as miRNAs play key regulatory roles in living systems. These ultra-short, ∼21 bp long, RNA molecules are derived from their hairpin precursors and usually participate in negative gene regulation by binding the target mRNAs. Discovering miRNA candidate regions across the genome has been a challenging problem. Most of the existing tools work reliably only for limited datasets. Here, we have presented a novel reliable approach, miR-BAG, developed to identify miRNA candidate regions in genomes by scanning sequences as well as by using next generation sequencing (NGS) data. miR-BAG utilizes a bootstrap aggregation based machine learning approach, successfully creating an ensemble of complementary learners to attain high accuracy while balancing sensitivity and specificity. miR-BAG was developed for wide range of species and tested extensively for performance over a wide range of experimentally validated data. Consideration of position-specific variation of triplet structural profiles and mature miRNA anchored structural profiles had a positive impact on performance. miR-BAG’s performance was found consistent and the accuracy level was observed to be >90% for most of the species considered in the present study. In a detailed comparative analysis, miR-BAG performed better than six existing tools. Using miR-BAG NGS module, we identified a total of 22 novel miRNA candidate regions in cow genome in addition to a total of 42 cow specific miRNA regions. In practice, discovery of miRNA regions in a genome demands high-throughput data analysis, requiring large amount of processing. Considering this, miR-BAG has been developed in multi-threaded parallel architecture as a web server as well as a user friendly GUI standalone version.

Transcriptomic changes in the bovine conceptus between the blastocyst stage and initiation of implantation

Conceptus-maternal communication is vital for the successful establishment and maintenance of pregnancy, yet relatively little information exists for many of the mechanisms and the nature of the conceptus signals responsible for this cross-talk. Sub-optimal communication, resulting from impairment of conceptus development and/or from abnormal uterine receptivity, contributes to a high incidence of embryonic mortality. Therefore, detailed examination of the mechanisms regulating both pre- and peri-implantation conceptus development are necessary to fully understand the factors regulating successful post-hatching development, pregnancy recognition and implantation signaling. Despite significant progress in understanding of the temporal changes in the transcriptome of the uterine endometrium, there is only a rudimentary knowledge of the genes and pathways governing growth and development of the cattle conceptus. Furthermore, although there are a large number of studies describing gene expression profiles in bovine embryos focused mainly during the earlier preimplantation stages (up to and including Day 7), very little information exists for the post-hatching embryo and elongating conceptus. This period of development is arguably more important as a significant proportion of all embryonic loss occurs between Days 8 and 16 of pregnancy in cattle, corresponding to the time of hatching of the blastocyst from the zona pellucida and its subsequent elongation coincident with the time of maternal recognition of pregnancy. Given that this is a critical period in development leading up to maternal recognition and establishment of pregnancy, the identification of key genes and pathways regulating these crucial developmental events is essential.

Bovine ncRNAs are abundant, primarily intergenic, conserved and associated with regulatory genes

It is apparent that non-coding transcripts are a common feature of higher organisms and encode uncharacterized layers of genetic regulation and information. We used public bovine EST data from many developmental stages and tissues, and developed a pipeline for the genome wide identification and annotation of non-coding RNAs (ncRNAs). We have predicted 23,060 bovine ncRNAs, 99% of which are un-annotated, based on known ncRNA databases. Intergenic transcripts accounted for the majority (57%) of the predicted ncRNAs and the occurrence of ncRNAs and genes were only moderately correlated (r = 0.55, p-value<2.2e-16). Many of these intergenic non-coding RNAs mapped close to the 3′ or 5′ end of thousands of genes and many of these were transcribed from the opposite strand with respect to the closest gene, particularly regulatory-related genes. Conservation analyses showed that these ncRNAs were evolutionarily conserved, and many intergenic ncRNAs proximate to genes contained sequence-specific motifs. Correlation analysis of expression between these intergenic ncRNAs and protein-coding genes using RNA-seq data from a variety of tissues showed significant correlations with many transcripts. These results support the hypothesis that ncRNAs are common, transcribed in a regulated fashion and have regulatory functions.

Gene network analyses of first service conception in Brangus heifers: use of genome and trait associations, hypothalamic-transcriptome information, and transcription factors

Measures of heifer fertility are economically relevant traits for beef production systems and knowledge of candidate genes could be incorporated into future genomic selection strategies. Ten traits related to growth and fertility were measured in 890 Brangus heifers (3/8 Brahman × 5/8 Angus, from 67 sires). These traits were: BW and hip height adjusted to 205 and 365 d of age, postweaning ADG, yearling assessment of carcass traits (i.e., back fat thickness, intramuscular fat, and LM area), as well as heifer pregnancy and first service conception (FSC). These fertility traits were collected from controlled breeding seasons initiated with estrous synchronization and AI targeting heifers to calve by 24 mo of age. The BovineSNP50 BeadChip was used to ascertain 53,692 SNP genotypes for ∼802 heifers. Associations of genotypes and phenotypes were performed and SNP effects were estimated for each trait. Minimally associated SNP (P < 0.05) and their effects across the 10 traits formed the basis for an association weight matrix and its derived gene network related to FSC (57.3% success and heritability = 0.06 ± 0.05). These analyses yielded 1,555 important SNP, which inferred genes linked by 113,873 correlations within a network. Specifically, 1,386 SNP were nodes and the 5,132 strongest correlations (|r| ≥ 0.90) were edges. The network was filtered with genes queried from a transcriptome resource created from deep sequencing of RNA (i.e., RNA-Seq) from the hypothalamus of a prepubertal and a postpubertal Brangus heifer. The remaining hypothalamic-influenced network contained 978 genes connected by 2,560 edges or predicted gene interactions. This hypothalamic gene network was enriched with genes involved in axon guidance, which is a pathway known to influence pulsatile release of LHRH. There were 5 transcription factors with 21 or more connections: ZMAT3, STAT6, RFX4, PLAGL1, and NR6A1 for FSC. The SNP that identified these genes were intragenic and were on chromosomes 1, 5, 9, and 11. Chromosome 5 harbored both STAT6 and RFX4. The large number of interactions and genes observed with network analyses of multiple sources of genomic data (i.e., GWAS and RNA-Seq) support the concept of FSC being a polygenic trait.

Flowering time and transcriptome variation in Capsella bursa-pastoris (Brassicaceae)

• Flowering is a major developmental transition and its timing in relation to environmental conditions is of crucial importance to plant fitness. Understanding the genetic basis of flowering time variation is important to determining how plants adapt locally. • Here, we investigated flowering time variation of Capsella bursa-pastoris collected from different latitudes in China. We also used a digital gene expression (DGE) system to generate partial gene expression profiles for 12 selected samples. • We found that flowering time was highly variable and most strongly correlated with day length and winter temperature. Significant differences in gene expression between early- and late-flowering samples were detected for 72 candidate genes for flowering time. Genes related to circadian rhythms were significantly overrepresented among the differentially expressed genes. • Our data suggest that circadian rhythms and circadian clock genes play an important role in the evolution of flowering time, and C. bursa-pastoris plants exhibit expression differences for candidate genes likely to affect flowering time across the broad range of environments they face in China.

Global assessment of genomic variation in cattle by genome resequencing and high-throughput genotyping

Background

Integration of genomic variation with phenotypic information is an effective approach for uncovering genotype-phenotype associations. This requires an accurate identification of the different types of variation in individual genomes.

Results

We report the integration of the whole genome sequence of a single Holstein Friesian bull with data from single nucleotide polymorphism (SNP) and comparative genomic hybridization (CGH) array technologies to determine a comprehensive spectrum of genomic variation. The performance of resequencing SNP detection was assessed by combining SNPs that were identified to be either in identity by descent (IBD) or in copy number variation (CNV) with results from SNP array genotyping. Coding insertions and deletions (indels) were found to be enriched for size in multiples of 3 and were located near the N- and C-termini of proteins. For larger indels, a combination of split-read and read-pair approaches proved to be complementary in finding different signatures. CNVs were identified on the basis of the depth of sequenced reads, and by using SNP and CGH arrays.

Conclusions

Our results provide high resolution mapping of diverse classes of genomic variation in an individual bovine genome and demonstrate that structural variation surpasses sequence variation as the main component of genomic variability. Better accuracy of SNP detection was achieved with little loss of sensitivity when algorithms that implemented mapping quality were used. IBD regions were found to be instrumental for calculating resequencing SNP accuracy, while SNP detection within CNVs tended to be less reliable. CNV discovery was affected dramatically by platform resolution and coverage biases. The combined data for this study showed that at a moderate level of sequencing coverage, an ensemble of platforms and tools can be applied together to maximize the accurate detection of sequence and structural variants.

Fine Mapping of a QTL for Fertility on BTA7 and Its Association With a CNV in the Israeli Holsteins

A quantitative trait locus (QTL) affecting female fertility, scored as the inverse of the number of inseminations to conception, on Bos taurus chromosome 7 was detected by a daughter design analysis of the Israeli Holstein population (P < 0.0003). Sires of five of the 10 families analyzed were heterozygous for the QTL. The 95% confidence interval of the QTL spans 27 cM from the centromere. Seven hundred and four SNP markers on the Illumina BovineSNP50 BeadChip within the QTL confidence interval were tested for concordance. A single SNP, NGS-58779, was heterozygous for all the five QTL heterozygous patriarchs, and homozygous for the remaining five QTL homozygous sires. A significant effect on fertility was associated with this marker in the sample of 900 sires genotyped (P < 10⁻⁶). Haplotype phase was the same for four of the five segregating sires. Thus concordance was obtained in nine of the ten families. We identified a common haplotype region associated with the rare and economically favorable allele of the SNP, spanning 270 kbp on BTA7 upstream to 4.72 Mbp. Eleven genes found in the common haplotype region should be considered as positional candidates for the identification of the causative quantitative trait nucleotide. Copy number variation was found in one of these genes, KIAA1683. Four gene variants were identified, but only the number of copies of a specific variant (V₁) was significantly associated with breeding values of sires for fertility.