Analysis of copy number variations among diverse cattle breeds
Ontology highlight
ABSTRACT:
ORGANISM(S): Bos taurus
PROVIDER: GSE19866 | GEO | 2010/03/03
SECONDARY ACCESSION(S): PRJNA121953
REPOSITORIES: GEO
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Project description:Genomic structural variation is an important and abundant source of genetic and phenotypic variation. Here we describe the first systematic and genome-wide analysis of copy number variations (CNVs) in modern domesticated cattle using array comparative genomic hybridization (array CGH), quantitative PCR (qPCR) and fluorescent in situ hybridization (FISH). The array CGH panel included 90 animals from 11 Bos taurus, 3 Bos indicus and 3 composite breeds for beef, dairy or dual purpose. We identified over 200 candidate CNV regions (CNVRs) in total and 177 within known chromosomes, which harbor or are adjacent to gains or losses. These 177 high-confidence CNVRs cover 28.1 mega bases or ~1.07% of the genome. Over 50% of the CNVRs (89/177) were found in multiple animals or breeds and analysis revealed breed-specific frequency differences and reflected aspects of the known ancestry of these cattle breeds. Selected CNVs were further validated by independent methods using qPCR and FISH. Approximately 67% of the CNVRs (119/177) completely or partially span cattle genes and 61% of the CNVRs (108/177) directly overlap with segmental duplications. The CNVRs span about 400 annotated cattle genes that are significantly enriched for specific biological functions such as immunity, lactation, reproduction and rumination. Multiple gene families, including ULBP, have gone through ruminant lineage-specific gene amplification. We detected and confirmed marked differences in their CNV frequencies across diverse breeds, indicating that some cattle CNVs are likely to arise independently in breeds and contribute to breed differences. Our results provide a valuable resource beyond microsatellites and single nucleotide polymorphisms to explore the full dimension of genetic variability for future cattle genomic research. The custom aCGH chips that interrogated the whole genome CNVs were build for 90 cattles from diverse breeds, with Hereford L1 Dominette 01449 as refference sample.
2010-03-02 | E-GEOD-19866 | biostudies-arrayexpress
Project description:Here we describe a genome-wide analysis of copy number variations (CNVs) in Chinese domestic cattle by using array comparative genomic hybridization (array CGH) and quantitative PCR (qPCR). We conducted array CGH analysis on 30 male cattle individuals, animals from consisting of 12 breeds of Bos taurus/Bos indicus, 1 Bos grunniens and and two ones of Bubalus bubalis breeds for with beef, and/or dairy or dual purpose. We identified over 470 candidate CNV regions (CNVRs) in Bos B. taurus/B. indicus; 118 candidate CNV regions (CNVRs) in B. grunniens, 139 CNVRs in B. bubalis. Furthermore, based on the Y haplotypes of B. taurus/ B. indicus, Wwe also identified 69, 337, and 251 candidate CNV regions (CNVRs) in the sub-groups of Y1, Y2 and Y3 haplotypes.
2014-12-30 | GSE47086 | GEO
Project description:Copy number variations (CNVs) have been demonstrated as crucial substrates for evolution, adaptation and breed formation. Chinese indigenous cattle breeds exhibit a broad geographical distribution and diverse environmental adaptability. Here, we analyzed the population structure and adaptation to high altitude of Chinese indigenous cattle based on genome-wide CNVs derived from the high-density BovineHD SNP array. We successfully detected the genome-wide CNVs of 318 individuals from 24 Chinese indigenous cattle breeds and 37 yaks as outgroups. A total of 5,818 autosomal CNV regions (683 bp - 4,477,860 bp in size), covering ~14.34% of the bovine genome (UMD3.1), were identified, showing abundant CNV resources. Neighbor-joining clustering, principal component analysis (PCA), and population admixture analysis based on these CNVs support that most Chinese cattle breeds are hybrids of Bos taurus taurus (hereinafter to be referred as Bos taurus) and Bos taurus indicus (Bos indicus). The distribution patterns of the CNVs could to some extent be related to the geographical backgrounds of the habitat of the breeds, and admixture among cattle breeds from different districts. We analyzed the selective signatures of CNVs positively involved in high-altitude adaptation using pairwise Fst analysis within breeds with a strong Bos taurus background (taurine-type breeds) and within Bos taurus×Bos indicus hybrids, respectively. CNV-overlapping genes with strong selection signatures (at top 0.5% of Fst value), including LETM1 (Fst = 0.490), TXNRD2 (Fst=0.440) and STUB1 (Fst=0.420) within taurine-type breeds, and NOXA1 (Fst = 0.233), RUVBL1 (Fst=0.222) and SLC4A3 (Fst=0.154) within hybrids, were potentially involved in the adaptation to hypoxia. Thus, we provide a new profile of population structure from the CNV aspects of Chinese indigenous cattle and new insights into high-altitude adaptation in cattle.
2020-02-21 | GSE142218 | GEO
Project description:We carried out a cross species cattle-sheep array comparative genome hybridization (aCGH) experiment in order to identify copy number variations (CNVs) in the sheep genome analysing animals of Italian dairy breeds (Sarda, Bagnolese, Laticauda, Massese and Valle del Belice) using a tiling oligonucleotide array with ~385,000 probes designed on the bovine genome. We identified 135 CNV regions (CNVRs) covering about 10.5 Mb of the virtual sheep genome referred to the bovine genome (0.398%) with a mean and median equal to 77.6 kb and 55.9 kb, respectively. A comparative analysis between the identified sheep CNVRs and those reported in the cattle and goat genomes indicated that overlaps between sheep and goat and sheep and cattle CNVRs are highly significant (P<0.0001) suggesting that several chromosome regions might contain recurrent interspecies CNVRs. Many sheep CNVs affect genes with important biological functions. Further studies are needed to evaluate the functional relevance of these CNVs. In this study we made use of the high conservation and homology between the cattle and sheep genomes determined by their phylogenetic closeness to identify CNVs in sheep applying the same approach we carried out to identify CNVs in the goat genome. We used a custom tiling array including ~385,000 oligonucleotide probes designed on the Btau_4.0 version of the Bos taurus genome assembly and analysed genomic DNA samples of 11 sheep belonging to 6 different Italian dairy sheep breeds (2 Sarda, 2 Bagnolese, 2 Comisana, 2 Massese, 2 Laticauda and 1 Valle del Belice) compared to the reference DNA of another Sarda sheep.
2010-11-16 | E-GEOD-25122 | biostudies-arrayexpress
Project description:Structural and functional impacts of copy number variations (CNVs) on livestock genomes are not yet well understood. In this study, we have identified 1853 CNV regions (CNVRs) using population-scale sequencing data generated from 75 cattle of 8 breeds (Holstein, Angus, Jersey, Limousin, Romagnola, Brahman, Gir and Nelore). Individual genome sequence coverage ranged from 4 to 30 fold, with a mean of 11.8 fold. A total of 3.1% (87.5 Mb) of the cattle genome is predicted to be copy number variable, representing a substantial increase over the previous estimates (~2%). This dataset was highly correlated with array CGH data (r2 = 0.761) and was validated to be accurate with an estimated 12% false positive rate and a 19% false negative rate based on qPCR and array CGH, respectively. Hundreds of CNVs were found to be either breed specific or differentially variable across breeds, including the RICTOR gene in dairy breeds and the PNPLA3 gene in the beef breeds. In contrast, clusters of the PRP and PAG genes are duplicated in all sequenced animals, implicating that subfunctionalization, neofunctionalization or overdominance play a role in diversifying these fertility related genes. Further population-genetic analyses based on CNVs revealed the population structures of these taurine and indicine breeds and uncovered hundreds of positively selected CNV candidates near important functional genes. These CNV results provide a new glimpse of diverse selections during cattle speciation, domestication, breed formation, and recent genetic improvement.
2015-11-04 | GSE62990 | GEO
Project description:We carried out a cross species cattle-sheep array comparative genome hybridization (aCGH) experiment in order to identify copy number variations (CNVs) in the sheep genome analysing animals of Italian dairy breeds (Sarda, Bagnolese, Laticauda, Massese and Valle del Belice) using a tiling oligonucleotide array with ~385,000 probes designed on the bovine genome. We identified 135 CNV regions (CNVRs) covering about 10.5 Mb of the virtual sheep genome referred to the bovine genome (0.398%) with a mean and median equal to 77.6 kb and 55.9 kb, respectively. A comparative analysis between the identified sheep CNVRs and those reported in the cattle and goat genomes indicated that overlaps between sheep and goat and sheep and cattle CNVRs are highly significant (P<0.0001) suggesting that several chromosome regions might contain recurrent interspecies CNVRs. Many sheep CNVs affect genes with important biological functions. Further studies are needed to evaluate the functional relevance of these CNVs.
2010-11-16 | GSE25122 | GEO
Project description:Background The goat (Capra hircus) represents one of the most important farm animal species. It is reared in all continents with an estimated world population of about 800 million of animals. Despite its importance, studies on the goat genome are still in their infancy compared to those in other farm animal species. Comparative mapping between cattle and goat showed only a few rearrangements in agreement with the similarity of chromosome banding. We carried out a cross species cattle-goat array comparative genome hybridization (aCGH) experiment in order to identify copy number variations (CNVs) in the goat genome analysing animals of different breeds (Saanen, Camosciata delle Alpi, Girgentana, and Murciano-Granadina) using a tiling oligonucleotide array with ~385,000 probes designed on the bovine genome. Results We identified a total of 161 CNVs (an average of 17.9 CNVs per goat), with the largest number in the Saanen breed and the lowest in the Camosciata delle Alpi goat. By aggregating overlapping CNVs identified in different animals we determined CNV regions (CNVRs): on the whole, we identified 127 CNVRs covering about 11.47 Mb of the virtual goat genome referred to the bovine genome (0.435% of the latter genome). These 127 CNVRs included 86 loss and 41 gain and ranged from about 24 kb to about 1.07 Mb with a mean and median equal to 90,292 bp and 49,530 bp, respectively. To evaluate whether the identified goat CNVRs overlap with those reported in the cattle genome, we compared our results with those obtained in four independent cattle experiments. Overlapping between goat and cattle CNVRs was highly significant (P<0.0001) suggesting that several chromosome regions might contain recurrent interspecies CNVRs. Genes with environmental functions were over-represented in goat CNVRs as reported in other mammals. Conclusions We describe a first map of goat CNVRs. This provides information on a comparative basis with the cattle genome by identifying putative recurrent interspecies CNVs between these two ruminant species. Several goat CNVs affect genes with important biological functions. Further studies are needed to evaluate the functional relevance of these CNVs and their effects on behavior, production, and disease resistance traits in goats.
2010-11-09 | GSE24436 | GEO
Project description:Copy number variations (CNVs) are an important source of genomic structural variation, and can be used as markers to investigate phenotypic and economic traits. CNVs also have functional effects on gene expression and can contribute to disease susceptibility in mammals. Currently, single nucleotide polymorphism genotyping arrays (SNP chips) are the technology of choice for identifying CNV variations. Microarray technologies have recently been used to study the bovine genome. The objective of the present study was to develop CNVs in Holstein cows from the Northwest of Mexico using the Affymetrix Axiom Genome-Wide BOS 1 Array, which assays 648,315 SNPs and provides a wide coverage for genome-wide studies. We applied the two most widely used algorithms for the discovery of CNVs (PennCNV and QuantiSNP) and found 56 CNV regions (CNVRs) representing 0.33% of the bovine genome (8.46 Mb). These CNVRs ranged from 1.5 to 970.8 kb with an average length of 151 kb. They involved 103 genes and showed a 28% overlap with CNVRs already reported. Of the 56 CNVRs found, 20 were novel. In this study we present the first genomic analysis of CNVs in Mexican cattle using highdensity SNP data. Our results provide a new reference basis for future genomic variation and association studies between CNVs and phenotypes, especially in Mexican cattle.
2015-09-30 | GSE54813 | GEO
Project description:Background The goat (Capra hircus) represents one of the most important farm animal species. It is reared in all continents with an estimated world population of about 800 million of animals. Despite its importance, studies on the goat genome are still in their infancy compared to those in other farm animal species. Comparative mapping between cattle and goat showed only a few rearrangements in agreement with the similarity of chromosome banding. We carried out a cross species cattle-goat array comparative genome hybridization (aCGH) experiment in order to identify copy number variations (CNVs) in the goat genome analysing animals of different breeds (Saanen, Camosciata delle Alpi, Girgentana, and Murciano-Granadina) using a tiling oligonucleotide array with ~385,000 probes designed on the bovine genome. Results We identified a total of 161 CNVs (an average of 17.9 CNVs per goat), with the largest number in the Saanen breed and the lowest in the Camosciata delle Alpi goat. By aggregating overlapping CNVs identified in different animals we determined CNV regions (CNVRs): on the whole, we identified 127 CNVRs covering about 11.47 Mb of the virtual goat genome referred to the bovine genome (0.435% of the latter genome). These 127 CNVRs included 86 loss and 41 gain and ranged from about 24 kb to about 1.07 Mb with a mean and median equal to 90,292 bp and 49,530 bp, respectively. To evaluate whether the identified goat CNVRs overlap with those reported in the cattle genome, we compared our results with those obtained in four independent cattle experiments. Overlapping between goat and cattle CNVRs was highly significant (P<0.0001) suggesting that several chromosome regions might contain recurrent interspecies CNVRs. Genes with environmental functions were over-represented in goat CNVRs as reported in other mammals. Conclusions We describe a first map of goat CNVRs. This provides information on a comparative basis with the cattle genome by identifying putative recurrent interspecies CNVs between these two ruminant species. Several goat CNVs affect genes with important biological functions. Further studies are needed to evaluate the functional relevance of these CNVs and their effects on behavior, production, and disease resistance traits in goats. We analysed CNVs in the goat genome by means of a cross-species aCGH experiment using the Roche NimbleGen platform (Roche NimbleGen Inc., Madison, WI; http://www.nimblegen.com) based on custom tiling arrays designed on the bovine (Bos taurus) genome, Btau_4.0 version, including a fraction of BTA13 of the University of Maryland (UMD) Bos taurus v. 2.0 assembly (ftp://ftp.cbcb.umd.edu/pub/data/Bos_taurus/Bos_taurus_UMD_2.0/). Arrays contained ~385,000 probes on a single slide to provide an evenly distributed coverage with an average interval of ~6 kb for the Btau_4.0 genome. The BTA13 of the UMD v. 2.0 assembly was included from nucleotide position 48 M bp to nucleotide position 78 M bp (4,673 oligonucleotides and average spacing of ~6 kb). This chromosome region was analysed as internal control because it contains the ASIP gene, not assembled in the BTA13 of the Btau_4.0 version Goat genomic DNA was extracted from blood of 2 Camosciata delle Alpi, 3 Girgentana, 3 Saanen, 1 black and 1 brown Murciano-Granadina goats using the Wizard® Genomic DNA Purification kit (Promega Corporation, Madison, WI). All analysed animals were females. Reference DNA sample of one (C1) Camosciata delle Alpi goat was labeled with Cy5 and co-hybridised with the other test DNA samples labelled with Cy3 on 9 different arrays. A self hybridisation (reference labelled by both Cy5 and Cy3) was carried out in another array. Hybridization and array scanning were performed by Roche NimbleGen as previously described. Data normalization was conducted using the normalize.qsline method from the Bioconductor package in R. Then data were analysed for each hybridization using normalized log2 ratios using the CGHweb server (http://compbio.med.harvard.edu/CGHweb/) that includes multiple algorithms.
2010-11-09 | E-GEOD-24436 | biostudies-arrayexpress
Project description:Copy number variation (CNV) is an important type of genetic variation contributing to phenotypic differences among mammals. Up to now, GWAS analysis using CNV called by array CGH is lacking in livestock like Holstein cattle. The objectives of this work are to identify CNVs using high-density aCGH data and explore functional CNVs which are associated with complex traits by GWAS method in Holstein cattle. In this study, we reported a systematic CNV association analysis of CNVs and 39 complex production traits in Holsteins. This research identified 1043 CNV regions (CNVRs) by array CGH data in 47 Holstein bulls. Using a genome-wide association analysis (GWAS) approach, we identified 79 significant CNVRs associated with at least one complex traits after false discovery rate (FDR) correction. Notably, 24 CNVRs were markedly related to daughter pregnancy rate (DPR). This study observed the pleiotropy phenomenon of 39 CNV loci which can simultaneously regulate at least 2 complex traits. In summary, the significant CNVs identified in this research could be utilized additional molecular markers for genetic improvement programs in Holsteins.
2019-02-16 | GSE122478 | GEO