Global copy number analyses by next generation sequencing provide insight into pig genome variation

An effect of large-scale deletions and duplications on transcript expression

Since copy number variants (CNVs) have been recognized as an important source of genetic and transcriptomic variation, we aimed to characterize the impact of CNVs located within coding, intergenic, upstream, and downstream gene regions on the expression of transcripts. Regions in which deletions occurred most often were introns, while duplications in coding regions. The transcript expression was lower for deleted coding (P = 0.008) and intronic regions (P = 1.355 × 10^-10), but it was not changed in the case of upstream and downstream gene regions (P = 0.085). Moreover, the expression was decreased if duplication occurred in the coding region (P = 8.318 × 10^-5). Furthermore, a negative correlation (r =  - 0.27) between transcript length and its expression was observed. The correlation between the percent of deleted/duplicated transcript and transcript expression level was not significant for all concerned genomic regions in five out of six animals. The exceptions were deletions in coding regions (P = 0.004) and duplications in introns (P = 0.01) in one individual. CNVs in coding (deletions, duplications) and intronic (deletions) regions are important modulators of transcripts by reducing their expression level. We hypothesize that deletions imply severe consequences by interrupting genes. The negative correlation between the size of the transcript and its expression level found in this study is consistent with the hypothesis that selection favours shorter introns and a moderate number of exons in highly expressed genes. This may explain the transcript expression reduction by duplications. We did not find the correlation between the size of deletions/duplications and transcript expression level suggesting that expression is modulated by CNVs regardless of their size.

MRI radiogenomics for intelligent diagnosis of breast tumors and accurate prediction of neoadjuvant chemotherapy responses-a review

BACKGROUND AND OBJECTIVE

This paper aims to overview multidimensional mining algorithms in relation to Magnetic Resonance Imaging (MRI) radiogenomics for computer aided detection and diagnosis of breast tumours. The work also aims to address a new problem in radiogenomics mining: how to combine structural radiomics information with non-structural genomics information for improving the accuracy and efficacy of Neoadjuvant Chemotherapy (NAC).

METHODS

This requires the automated extraction of parameters from non-structural breast radiomics data, and finding feature vectors with diagnostic value, which then are combined with genomics data. In order to address the problem of weakly labelled tumour images, a Generative Adiversarial Networks (GAN) based deep learning strategy is proposed for the classification of tumour types; this has significant potential for providing accurate real-time identification of tumorous regions from MRI scans. In order to efficiently integrate in a deep learning framework different features from radiogenomics datasets at multiple spatio-temporal resolutions, pyramid structured and multi-scale densely connected U-Nets are proposed. A bidirectional gated recurrent unit (BiGRU) combined with an attention based deep learning approach is also proposed.

RESULTS

The aim is to accurately predict NAC responses by combining imaging and genomic datasets. The approaches discussed incorporate some of the latest developments in of current signal processing and artificial intelligence and have significant potential in advancing and provide a development platform for future cutting-edge biomedical radiogenomics analysis.

CONCLUSIONS

The association of genotypic and phenotypic features is at the core of the emergent field of Precision Medicine. It makes use of advances in biomedical big data analysis, which enables the correlation between disease-associated phenotypic characteristics, genetics polymorphism and gene activation to be revealed.

Genome-Wide Assessment Characteristics of Genes Overlapping Copy Number Variation Regions in Duroc Purebred Population

Copy number variations (CNVs) are important structural variations that can cause significant phenotypic diversity. Reliable CNVs mapping can be achieved by identification of CNVs from different genetic backgrounds. Investigations on the characteristics of overlapping between CNV regions (CNVRs) and protein-coding genes (CNV genes) or miRNAs (CNV-miRNAs) can reveal the potential mechanisms of their regulation. In this study, we used 50 K SNP arrays to detect CNVs in Duroc purebred pig. A total number of 211 CNVRs were detected with a total length of 118.48 Mb, accounting for 5.23% of the autosomal genome sequence. Of these CNVRs, 32 were gains, 175 losses, and four contained both types (loss and gain within the same region). The CNVRs we detected were non-randomly distributed in the swine genome and were significantly enriched in the segmental duplication and gene density region. Additionally, these CNVRs were overlapping with 1,096 protein-coding genes (CNV-genes), and 39 miRNAs (CNV-miRNAs), respectively. The CNV-genes were enriched in terms of dosage-sensitive gene list. The expression of the CNV genes was significantly higher than that of the non-CNV genes in the adult Duroc prostate. Of all detected CNV genes, 22.99% genes were tissue-specific (TSI > 0.9). Strong negative selection had been underway in the CNV-genes as the ones that were located entirely within the loss CNVRs appeared to be evolving rapidly as determined by the median dN plus dS values. Non-CNV genes tended to be miRNA target than CNV-genes. Furthermore, CNV-miRNAs tended to target more genes compared to non-CNV-miRNAs, and a combination of two CNV-miRNAs preferentially synergistically regulated the same target genes. We also focused our efforts on examining CNV genes and CNV-miRNAs functions, which were also involved in the lipid metabolism, including DGAT1, DGAT2, MOGAT2, miR143, miR335, and miRLET7. Further molecular experiments and independent large studies are needed to confirm our findings.

Genome-Wide Detection of Structural Variations Reveals New Regions Associated with Domestication in Small Ruminants

During domestication processes, changes in selective pressures induce multiple phenotypical, physiological, and behavioral changes in target species. The rise of next-generation sequencing has provided a chance to study the genetics bases of these changes, most of the time based on single nucleotide polymorphisms (SNPs). However, several studies have highlighted the impact of structural variations (SVs) on individual fitness, particularly in domestic species. We aimed at unraveling the role of SVs during the domestication and later improvement of small ruminants by analyzing whole-genome sequences of 40 domestic sheep and 11 of their close wild relatives (Ovis orientalis), and 40 goats and 18 of their close wild relatives (Capra aegagrus). Using a combination of detection tools, we called 45,796 SVs in Ovis and 15,047 SVs in Capra genomes, including insertions, deletions, inversions, copy number variations, and chromosomal translocations. Most of these SVs were previously unreported in small ruminants. 69 and 45 SVs in sheep and goats, respectively, were in genomic regions with neighboring SNPs highly differentiated between wilds and domestics (i.e., putatively related to domestication). Among them, 25 and 20 SVs were close to or overlapping with genes related to physiological and morpho-anatomical traits linked with productivity (e.g., size, meat or milk quality, wool color), reproduction, or immunity. Finally, several of the SVs differentiated between wilds and domestics would not have been detected by screening only the differentiation of SNPs surrounding them, highlighting the complementarity of SVs and SNPs based approaches to detect signatures of selection.

Model research of the pig’s microbiome based on “One Health” concept in the light of the shared human and animal health

The human microbiome in terms of the number of bacteria exceeds the number of cells in the human body. It is defined as an additional “forgotten organ” and plays a key role in maintaining a high health status, which is conditioned by the maintenance of certain proportions and natural relations between bacteria and cells of the host organism. New diagnostic methods can enable profiling not only the human microbiome, but also livestock. An innovative analytical method, which is next generation sequencing (NGS), is increasingly used in the study of the microbiome. Many bacteria are referred to as “uncultivated” or “non-culturable” and metagenomics has played an important role in detecting these bacteria and has contributed to the development of new media for their cultivation. The main application of NGS in microbiology is to replace the conventional characterization of pathogens based on the assessment of morphology, staining properties and metabolic traits with their genome related characteristics. There are several platforms, i.e. “diagnostic tools”, that use a variety of DNA sequencing technologies, among others Ion Torrent Personal Genome Machine (PGM), Pacific Biosciences (PacBio) and Illumina MiSeq. In the case of swine microbiome, studies of the microbiome with the use of modern sequencing technologies seem to be particularly interesting in the aspect of the upcoming, inevitable changes in preventive and therapeutic procedures in animals. Analyses of this type integrate with the concept of the shared human and animal health and enable an in-depth assessment of the impact of specific factors on the population of intestinal microbes and learning how to “form” the composition of the microbiome in order to improve the quality of husbandry and to maintain the pig’s proper health status.

Copy number variation of the HPGDS gene in the Ashidan yak and its associations with growth traits

Copy number variation (CNV) is a structural variation at the submicroscopic level of the genome, which can affect gene-related phenotypes by changing genes dosage and transcript structure. Hematopoietic prostaglandin D synthase (HPGDS) is a member whose functions are closely related to weight gain and inflammatory diseases of the glutathione S-transferase (GSTs) family. In this study, the growth characteristics (body weight, withers height, body length, and chest girth) of 336 Ashidan yaks were monitored at four stages (6 months, 12 months, 18 months, and 30 months). In addition, CNV of the HPGDS gene was detected, discovered relationships of CNV with growth traits, and explored the level of gene expression. Based on the statistical analysis by IBM SPSS software, significant correlations were observed between HPGDS-CNV and body weight in 12-month-old yak (P < 0.01), 18-month-old yak (P < 0.001) and 30-month-old yak (P < 0.001) and body length in 18-month-old yak (P < 0.05) and 30-month-old yak (P < 0.05), respectively. Additionally, the individuals with gain copy number type performed better in body weight and body length than those with normal or loss copy number type. To our best of knowledge, this is the first time to make efforts to probe into the role of HPGDS-CNV and its interaction with livestock growth traits. Our results suggested that the CNV of the HPGDS gene may be an active candidate gene for the marker-assisted selection (MAS) of yaks.

Identification and population genetic analyses of copy number variations in six domestic goat breeds and Bezoar ibexes using next-generation sequencing

Background

Copy number variations (CNVs) are a major form of genetic variations and are involved in animal domestication and genetic adaptation to local environments. We investigated CNVs in the domestic goat (Capra hircus) using Illumina short-read sequencing data, by comparing our lab data for 38 goats from three Chinese breeds (Chengdu Brown, Jintang Black, and Tibetan Cashmere) to public data for 26 individuals from three other breeds (two Moroccan and one Chinese) and 21samples from Bezoar ibexes.

Results

We obtained a total of 2394 CNV regions (CNVRs) by merging 208,649 high-confidence CNVs, which spanned ~ 267 Mb of total length and accounted for 10.80% of the goat autosomal genome. Functional analyses showed that 2322 genes overlapping with the CNVRs were significantly enriched in 57 functional GO terms and KEGG pathways, most related to the nervous system, metabolic process, and reproduction system. Clustering patterns of all 85 samples generated separately from duplications and deletions were generally consistent with the results from SNPs, agreeing with the geographical origins of these goats. Based on genome-wide F_ST at each CNV locus, some genes overlapping with the highly divergent CNVs between domestic and wild goats were mainly enriched for several immunity-related pathways, whereas the genes overlapping with the highly differentiated CNVs between highland and lowland goats were mainly related to vitamin and lipid metabolism. Remarkably, a 507-bp deletion at ~ 14 kb downstream of FGF5 on chromosome 6 showed highly divergent (F_ST = 0.973) between the highland and lowland goats. Together with an enhancer activity of this sequence shown previously, the function of this duplication in regulating fiber growth deserved to be further investigated in detail.

Conclusion

We generated a comprehensive map of CNVs in goats. Many genetically differentiated CNVs among various goat populations might be associated with the population characteristics of domestic goat breeds.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07267-6.

Genome-wide detection of copy number variants in European autochthonous and commercial pig breeds by whole-genome sequencing of DNA pools identified breed-characterising copy number states

In this study, we identified copy number variants (CNVs) in 19 European autochthonous pig breeds and in two commercial breeds (Italian Large White and Italian Duroc) that represent important genetic resources for this species. The genome of 725 pigs was sequenced using a breed-specific DNA pooling approach (30-35 animals per pool) obtaining an average depth per pool of 42×. This approach maximised CNV discovery as well as the related copy number states characterising, on average, the analysed breeds. By mining more than 17.5 billion reads, we identified a total of 9592 CNVs (~683 CNVs per breed) and 3710 CNV regions (CNVRs; 1.15% of the reference pig genome), with an average of 77 CNVRs per breed that were considered as private. A few CNVRs were analysed in more detail, together with other information derived from sequencing data. For example, the CNVR encompassing the KIT gene was associated with coat colour phenotypes in the analysed breeds, confirming the role of the multiple copies in determining breed-specific coat colours. The CNVR covering the MSRB3 gene was associated with ear size in most breeds. The CNVRs affecting the ELOVL6 and ZNF622 genes were private features observed in the Lithuanian Indigenous Wattle and in the Turopolje pig breeds respectively. Overall, the genome variability unravelled here can explain part of the genetic diversity among breeds and might contribute to explain their origin, history and adaptation to a variety of production systems.

CNV analysis of Meishan pig by next-generation sequencing and effects of AHR gene CNV on pig reproductive traits

Background

Reproductive performance of livestock is an economically important aspect of global food production. The Chinese Meishan pig is a prolific breed, with an average of three to five more piglets per litter than European breeds; however, the genetic basis for this difference is not well understood.

Results

In this study, we investigated copy number variations (CNVs) of 32 Meishan pigs and 29 Duroc pigs by next-generation sequencing. A genome-wide analysis of 61 pigs revealed 12,668 copy number variable regions (CNVRs) that were further divided into three categories based on copy number (CN) of the whole population, i.e., gain (n = 7,638), and loss (n = 5,030) CNVRs. We then compared Meishan and Duroc pigs and identified 17.17 Mb of 6,387 CNVRs that only existing in Meishan pigs CNVRs that overlapped the reproduction-related gene encoding the aryl hydrocarbon receptor (AHR) gene. We found that normal AHR CN was more frequent than CN loss in four different pig breeds. An association analysis showed that AHR CN had a positive effect on litter size (P < 0.05) and that a higher CN was associated with higher total number born (P < 0.05), number born alive (P < 0.05), number of weaned piglets, and birth weight.

Conclusions

The present study provides comprehensive CNVRs for Meishan and Duroc pigs through large-scale population resequencing. Our results provide a supplement for the high-resolution map of copy number variation in the porcine genome and valuable information for the investigation of genomic structural variation underlying traits of interest in pig. In addition, the association results provide evidence for AHR as a candidate gene associated with reproductive traits that can be used as a genetic marker in pig breeding programs.

Copy Number Variation of the CADM2 Gene and Its Association with Growth Traits in Yak

Simple Summary

Cell adhesion molecule 2 (CADM2), also known as synaptic cell adhesion molecule 2 (SYNCAM2), is the mediator of synaptic signals enriched in the brain. Overlaps between copy number variation (CNV) regions in CADM2 and quantitative trait loci (QTL) related to body weight have been clarified in a previous study. In this study, two loci were amplified in the CADM2 gene (CNV1: 235,915 bp, exon 1 and partial intron 1; CNV2: 60,430 bp, intron 9) to explore the relationship between CNV types in the CADM2 gene and growth traits in 350 Ashidan yaks. Association analysis illustrated that no significant effect was found on growth traits in CNV1. However, the CNV2 mutation had a significant effect on body weight at the sixth month (p < 0.05). Individuals with the gain-type copy number variation CNV2 were significantly superior to those with loss- or normal-type in terms of body weight (p < 0.05). In summary, this study confirmed that CADM2-CNVs affect growth traits in yaks, and may be candidate genes for successful yak breeding and genetics projects.

Abstract

Copy number variation (CNV) is currently accepted as a common source of genetic variation. It is reported that CNVs may influence the resistance to disease and complex economic traits, such as residual feed intake, muscle formation, and fat deposition in livestock. Cell adhesion molecule 2 (CADM2) is expressed widely in the brain and adipose tissue and can regulate body weight through the central nervous system. Growth traits are important economic traits for animal selection. In this study, we aimed to explore the effect of CADM2 gene copy number variants on yak growth traits. Here, two CNVs in the CADM2 gene were investigated using the quantitative polymerase chain reaction (qPCR), and the association of the CNVs with growth traits in yak was analyzed using statistical methods by SPSS software. Differences were considered significant if the p value was < 0.05. Statistical analysis indicated significant association of CADM2-CNV2 with the body weight of the Chinese Ashidan yak. A significant effect of CNV2 (p < 0.05) was found on body weight at 6 months. In CNV2, the gain-type copy number variation exhibited greater performance than the other variants, with greater body weight observed at 6 months (p < 0.05). To the best of our knowledge, this is the first attempt to investigate the function of CADM2-CNVs and their association with growth traits in animals. This may be a useful candidate marker in marker-assisted selection of yaks.

Detection and analysis of genome-wide copy number variation in the pig genome using an 80 K SNP Beadchip

Copy number variation (CNV) is an important source of genetic variability in human or animal genomes and play key roles in phenotypic diversity and disease susceptibility. In the present study, we performed a genome-wide analysis for CNV detection using SNP genotyping data of 857 Large White pigs. A total of 312 CNV regions (CNVRs) were detected with the PennCNV algorithm, which covered 57.76 Mb of the pig genome and correspond to 2.36% of the genome sequence. The length of the CNVRs on autosomes ranged from 1.77 Kb to 1.76 Mb with an average of 185.11 Kb. Of these, 220 completely or partially overlapped with 1,092 annotated genes, which enriched a wide variety of biological processes. Comparisons with previously reported pig CNVR revealed 92 (29.49%) novel CNVRs. Experimentally, 80% of CNVRs selected randomly were validated by quantitative PCR (qPCR). We also performed an association analysis between some of the CNVRs and reproductive traits, with results demonstrating the potential importance of CNVR61 and CNVR283 associated with litter sizes. Notably, the GPER1 gene located in CNVR61 plays a key role in reproduction. Our study is an important complement to the CNV map in the pig genome and provides valuable information for investigating the association between genomic variation and economic traits.

NTN1 Affects Porcine Intramuscular Fat Content by Affecting the Expression of Myogenic Regulatory Factors

Simple Summary

Intramuscular fat (IMF) is a key meat quality trait in the pork industry. In this study, we validated the effect of the copy number of Netrin-1 (NTN1-CNV) on Netrin-1 (NTN1) protein expression and explored the possible affective mechanism of NTN1 on IMF. The results indicated that NTN1-CNV may affect the expression of NTN1 protein by its gene dose, and the expression of NTN1 may affect the proliferation and differentiation of muscle cells by the AMP-activated protein kinase (AMPK) pathway and finally influence the IMF content.

Abstract

Intramuscular fat (IMF) content is an important economic trait for pork quality. Our previous results regarding the genome-wide association between IMF content and copy number variations (CNVs) indicated that the CNV within Netrin-1(NTN1-CNV) was significantly associated with IMF. In order to validate the effect of NTN1-CNV, we detected the Netrin-1 (NTN1) gene dose and protein expression content in the longissimus dorsi of different IMF content pigs using Western blotting and investigated the expression of NTN1 RNA in different tissues using real-time quantitative polymerase chain reaction (qPCR). The knock-down of the NTN1 gene in C2C12 and 3T3-L1 cells and over-expression in C2C12 cells during the proliferation and differentiation stage were also investigated to explore the possible pathway of action of NTN1. The results showed that in individuals with IMF content differences, the gene dose of NTN1 and the expression of NTN1 protein were also significantly different, which indicated that NTN1-CNV may directly affect IMF by its coding protein. NTN1 had the highest expression in pig longissimus dorsi and backfat tissues, which indicates that NTN1 may play an important role in muscle and fat tissues. The in vitro validation assay indicated that NTN1 silencing could promote the proliferation and inhibit the differentiation of C2C12 cells, with no effect on 3T3-L1 cells. Additionally, NTN1 over-expression could inhibit the proliferation and promote the differentiation of C2C12 cells. Combined with previous research, we conclude that NTN1-CNV may affect IMF by its gene dose, and the expression of NTN1 may affect the proliferation and differentiation of muscle cells by the AMP-activated protein kinase (AMPK) pathway and finally influence the IMF.

A Survey of Copy Number Variation in the Porcine Genome Detected From Whole-Genome Sequence

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.

A genome-wide single nucleotide polymorphism and copy number variation analysis for number of piglets born alive

Background

In this study we integrated the CNV (copy number variation) and WssGWAS (weighted single-step approach for genome-wide association) analyses to increase the knowledge about number of piglets born alive, an economically important reproductive trait with significant impact on production efficiency of pigs.

Results

A total of 3892 samples were genotyped with the Porcine SNP80 BeadChip. After quality control, a total of 57,962 high-quality SNPs from 3520 Duroc pigs were retained. The PennCNV algorithm identified 46,118 CNVs, which were aggregated by overlapping in 425 CNV regions (CNVRs) ranging from 2.5 Kb to 9718.4 Kb and covering 197 Mb (~ 7.01%) of the pig autosomal genome. The WssGWAS identified 16 genomic regions explaining more than 1% of the additive genetic variance for number of piglets born alive. The overlap between CNVR and WssGWAS analyses identified common regions on SSC2 (4.2–5.2 Mb), SSC3 (3.9–4.9 Mb), SSC12 (56.6–57.6 Mb), and SSC17 (17.3–18.3 Mb). Those regions are known for harboring important causative variants for pig reproductive traits based on their crucial functions in fertilization, development of gametes and embryos. Functional analysis by the Panther software identified 13 gene ontology biological processes significantly represented in this study such as reproduction, developmental process, cellular component organization or biogenesis, and immune system process, which plays relevant roles in swine reproductive traits.

Conclusion

Our research helps to improve the understanding of the genetic architecture of number of piglets born alive, given that the combination of GWAS and CNV analyses allows for a more efficient identification of the genomic regions and biological processes associated with this trait in Duroc pigs. Pig breeding programs could potentially benefit from a more accurate discovery of important genomic regions.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5687-0) contains supplementary material, which is available to authorized users.

Computational detection and experimental validation of segmental duplications and associated copy number variations in water buffalo ( Bubalus bubalis )

Duplicated sequences are an important source of gene evolution and structural variation within mammalian genomes. Using a read depth approach based on next-generation sequencing, we performed a genome-wide analysis of segmental duplications (SDs) and associated copy number variations (CNVs) in the water buffalo (Bubalus bubalis). By aligning short reads of Olimpia (the reference water buffalo) to the UMD3.1 cattle genome, we identified 1,038 segmental duplications comprising 44.6 Mb (equivalent to ~1.73% of the cattle genome) of the autosomal and X chromosomal sequence in the buffalo genome. We experimentally validated 70.3% (71/101) of these duplications using fluorescent in situ hybridization. We also detected a total of 1,344 CNV regions across 14 additional water buffaloes, amounting to 59.8 Mb of variable sequence or the equivalent of 2.2% of the cattle genome. The CNV regions overlap 1,245 genes that are significantly enriched for specific biological functions including immune response, oxygen transport, sensory system and signal transduction. Additionally, we performed array Comparative Genomic Hybridization (aCGH) experiments using the 14 water buffaloes as test samples and Olimpia as the reference. Using a linear regression model, a high Pearson correlation (r = 0.781) was observed between the log₂ ratios between copy number estimates and the log₂ ratios of aCGH probes. We further designed Quantitative PCR assays to confirm CNV regions within or near annotated genes and found 74.2% agreement with our CNV predictions. These results confirm sub-chromosome-scale structural rearrangements present in the cattle and water buffalo. The information on genome variation that will be of value for evolutionary and phenotypic studies, and may be useful for selective breeding of both species.

A global analysis of CNVs in diverse yak populations using whole-genome resequencing

Background

Genomic structural variation represents a source for genetic and phenotypic variation, which may be subject to selection during the environmental adaptation and population differentiation. Here, we described a genome-wide analysis of copy number variations (CNVs) in 16 populations of yak based on genome resequencing data and CNV-based cluster analyses of these populations.

Results

In total, we identified 51,461 CNV events and defined 3174 copy number variation regions (CNVRs) that covered 163.8 Mb (6.2%) of yak genome with more “loss” events than both “gain” and “both” events, and we confirmed 31 CNVRs in 36 selected yaks using quantitative PCR. Of the total 163.8 Mb CNVR coverage, a 10.8 Mb region of high-confidence CNVRs directly overlapped with the 52.9 Mb of segmental duplications, and we confirmed their uneven distributions across chromosomes. Furthermore, functional annotation indicated that the CNVR-harbored genes have a considerable variety of molecular functions, including immune response, glucose metabolism, and sensory perception. Notably, some of the identified CNVR-harbored genes associated with adaptation to hypoxia (e.g., DCC, MRPS28, GSTCD, MOGAT2, DEXI, CIITA, and SMYD1). Additionally, cluster analysis, based on either individuals or populations, showed that the CNV clustering was divided into two origins, indicating that some yak CNVs are likely to arisen independently in different populations and contribute to population difference.

Conclusions

Collectively, the results of the present study advanced our understanding of CNV as an important type of genomic structural variation in yak, and provide a useful genomic resource to facilitate further research on yak evolution and breeding.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5451-5) contains supplementary material, which is available to authorized users.

Detection of genome-wide structural variations in the Shanghai Holstein cattle population using next-generation sequencing

Objective

The Shanghai Holstein cattle breed is susceptible to severe mastitis and other diseases due to the hot weather and long-term humidity in Shanghai, which is the main distribution centre for providing Holstein semen to various farms throughout China. Our objective was to determine the genetic mechanisms influencing economically important traits, especially diseases that have huge impact on the yield and quality of milk as well as reproduction.

Methods

In our study, we detected the structural variations of 1,092 Shanghai Holstein cows by using next-generation sequencing. We used the DELLY software to identify deletions and insertions, cn.MOPS to identify copy-number variants (CNVs). Furthermore, we annotated these structural variations using different bioinformatics tools, such as gene ontology, cattle quantitative trait locus (QTL) database and ingenuity pathway analysis (IPA).

Results

The average number of high-quality reads was 3,046,279. After filtering, a total of 16,831 deletions, 12,735 insertions and 490 CNVs were identified. The annotation results showed that these mapped genes were significantly enriched for specific biological functions, such as disease and reproduction. In addition, the enrichment results based on the cattle QTL database showed that the number of variants related to milk and reproduction was higher than the number of variants related to other traits. IPA core analysis found that the structural variations were related to reproduction, lipid metabolism, and inflammation. According to the functional analysis, structural variations were important factors affecting the variation of different traits in Shanghai Holstein cattle. Our results provide meaningful information about structural variations, which may be useful in future assessments of the associations between variations and important phenotypes in Shanghai Holstein cattle.

Conclusion

Structural variations identified in this study were extremely different from those of previous studies. Many structural variations were found to be associated with mastitis and reproductive system diseases; these results are in accordance with the characteristics of the environment that Shanghai Holstein cattle experience.

Copy number variations of MTHFSD gene across pig breeds and its association with litter size traits in Chinese indigenous Xiang pig

Copy number variation (CNV) is a major proportion of genetic variation, which changes the gene structure and dosage and affects gene expression and function. To validate the presence and the function of CNV in pig, we used real-time quantitative polymerase chain reaction (qPCR) method to validate a 496 kb CNV region comprising MTHFSD gene on chromosome 6 of Xiang pig detected by single nucleotide polymorphism (SNP) array. Then we investigated the distribution of the MTHFSD CNV in a total of 545 pigs in four breeds. About 46.2% and 32.7% individuals in the four pig breeds were detected to be types of loss and gain of MTHFSD locus. The relative copy numbers of MTHFSD gene showed the largest variation range (0-55 copies) in the Xiang pig population. The copy numbers of MTHFSD gene presented the positive correlations with the transcript level of MTHFSD gene in adult ovaries. Statistical analysis indicated that CNVs of MTHFSD gene was significantly changed the litter size traits of Xiang pigs, and the individuals with CNV gain showed more litter size than the CNV loss pigs. We have reasons to believe that the MTHFSD as RNA-binding protein play an important role in pig reproduction as a result of regulating MTHFS mRNA metabolism.

Mapping of genome-wide copy number variations in the Iranian indigenous cattle using a dense SNP data set

The objective of this study was to present the first map of the copy number variations (CNVs) in Iranian indigenous cattle based on a high-density single nucleotide polymorphism (SNP) dataset. A total of 90 individuals were genotyped using the Illumina BovineHD BeadChip containing 777 962 SNPs. The QuantiSNP algorithm was used to perform a genome-wide CNV detection across autosomal genome. After merging the overlapping CNV, a total of 221 CNV regions were identified encompassing 36.4 Mb or 1.44% of the bovine autosomal genome. The length of the CNV regions ranged from 3.5 to 2252.8 Kb with an average of 163.8 Kb. These regions included 147 loss (66.52%) and 74 gain (33.48%) events containing a total of 637 annotated Ensembl genes. Gene ontology analysis revealed that most of genes in the CNV regions were involved in environmental responses, disease susceptibility and immune system functions. Furthermore, 543 of these genes corresponded to the human orthologous genes, which involved in a wide range of biological functions. Altogether, 73% of the 221 CNV regions overlapped either completely or partially with those previously reported in other cattle studies. Moreover, novel CNV regions involved several quantitative trait loci (QTL)-related to adaptative traits of Iranian indigenous cattle. These results provided a basis to conduct future studies on association between CNV regions and phenotypic variations in the Iranian indigenous cattle.

Similar genomic proportions of copy number variation within gray wolves and modern dog breeds inferred from whole genome sequencing

BACKGROUND

Whole genome re-sequencing data from dogs and wolves are now commonly used to study how natural and artificial selection have shaped the patterns of genetic diversity. Single nucleotide polymorphisms, microsatellites and variants in mitochondrial DNA have been interrogated for links to specific phenotypes or signals of domestication. However, copy number variation (CNV), despite its increasingly recognized importance as a contributor to phenotypic diversity, has not been extensively explored in canids.

RESULTS

Here, we develop a new accurate probabilistic framework to create fine-scale genomic maps of segmental duplications (SDs), compare patterns of CNV across groups and investigate their role in the evolution of the domestic dog by using information from 34 canine genomes. Our analyses show that duplicated regions are enriched in genes and hence likely possess functional importance. We identify 86 loci with large CNV differences between dogs and wolves, enriched in genes responsible for sensory perception, immune response, metabolic processes, etc. In striking contrast to the observed loss of nucleotide diversity in domestic dogs following the population bottlenecks that occurred during domestication and breed creation, we find a similar proportion of CNV loci in dogs and wolves, suggesting that other dynamics are acting to particularly select for CNVs with potentially functional impacts.

CONCLUSIONS

This work is the first comparison of genome wide CNV patterns in domestic and wild canids using whole-genome sequencing data and our findings contribute to study the impact of novel kinds of genetic changes on the evolution of the domestic dog.

A global analysis of CNVs in swine using whole genome sequence data and association analysis with fatty acid composition and growth traits

Copy number variations (CNVs) are important genetic variants complementary to SNPs, and can be considered as biomarkers for some economically important traits in domestic animals. In the present study, a genomic analysis of porcine CNVs based on next-generation sequencing data was carried out to identify CNVs segregating in an Iberian x Landrace backcross population and study their association with fatty acid composition and growth-related traits. A total of 1,279 CNVs, including duplications and deletions, were detected, ranging from 106 to 235 CNVs across samples, with an average of 183 CNVs per sample. Moreover, we detected 540 CNV regions (CNVRs) containing 245 genes. Functional annotation suggested that these genes possess a great variety of molecular functions and may play a role in production traits in commercial breeds. Some of the identified CNVRs contained relevant functional genes (e.g., CLCA4, CYP4X1, GPAT2, MOGAT2, PLA2G2A and PRKG1, among others). The variation in copy number of four of them (CLCA4, GPAT2, MOGAT2 and PRKG1) was validated in 150 BC1_LD (25% Iberian and 75% Landrace) animals by qPCR. Additionally, their contribution regarding backfat and intramuscular fatty acid composition and growth–related traits was analyzed. Statistically significant associations were obtained for CNVR112 (GPAT2) for the C18:2(n-6)/C18:3(n-3) ratio in backfat and carcass length, among others. Notably, GPATs are enzymes that catalyze the first step in the biosynthesis of both triglycerides and glycerophospholipids, suggesting that this CNVR may contribute to genetic variation in fatty acid composition and growth traits. These findings provide useful genomic information to facilitate the further identification of trait-related CNVRs affecting economically important traits in pigs.

Detection and assessment of copy number variation using PacBio long-read and Illumina sequencing in New Zealand dairy cattle

Single nucleotide polymorphisms have been the DNA variant of choice for genomic prediction, largely because of the ease of single nucleotide polymorphism genotype collection. In contrast, structural variants (SV), which include copy number variants (CNV), translocations, insertions, and inversions, have eluded easy detection and characterization, particularly in nonhuman species. However, evidence increasingly shows that SV not only contribute a substantial proportion of genetic variation but also have significant influence on phenotypes. Here we present the discovery of CNV in a prominent New Zealand dairy bull using long-read PacBio (Pacific Biosciences, Menlo Park, CA) sequencing technology and the Sniffles SV discovery tool (version 0.0.1; https://github.com/fritzsedlazeck/Sniffles). The CNV identified from long reads were compared with CNV discovered in the same bull from Illumina sequencing using CNVnator (read depth-based tool; Illumina Inc., San Diego, CA) as a means of validation. Subsequently, further validation was undertaken using whole-genome Illumina sequencing of 556 cattle representing the wider New Zealand dairy cattle population. Very limited overlap was observed in CNV discovered from the 2 sequencing platforms, in part because of the differences in size of CNV detected. Only a few CNV were therefore able to be validated using this approach. However, the ability to use CNVnator to genotype the 557 cattle for copy number across all regions identified as putative CNV allowed a genome-wide assessment of transmission level of copy number based on pedigree. The more highly transmissible a putative CNV region was observed to be, the more likely the distribution of copy number was multimodal across the 557 sequenced animals. Furthermore, visual assessment of highly transmissible CNV regions provided evidence supporting the presence of CNV across the sequenced animals. This transmission-based approach was able to confirm a subset of CNV that segregates in the New Zealand dairy cattle population. Genome-wide identification and validation of CNV is an important step toward their inclusion in genomic selection strategies.

Characterization of genome-wide segmental duplications reveals a common genomic feature of association with immunity among domestic animals

BACKGROUND

Segmental duplications (SDs) commonly exist in plant and animal genomes, playing crucial roles in genomic rearrangement, gene innovation and the formation of copy number variants. However, they have received little attention in most livestock species.

RESULTS

Aiming at characterizing SDs across the genomes of diverse livestock species, we mapped genome-wide SDs of horse, rabbit, goat, sheep and chicken, and also enhanced the existing SD maps of cattle and pig genomes based on the most updated genome assemblies. We adopted two different detection strategies, whole genome analysis comparison and whole genome shotgun sequence detection, to pursue more convincing findings. Accordingly we identified SDs for each species with the length of from 21.7 Mb to 164.1 Mb, and 807 to 4,560 genes were harboured within the SD regions across different species. More interestingly, many of these SD-related genes were involved in the process of immunity and response to external stimuli. We also found the existence of 59 common genes within SD regions in all studied species except goat. These common genes mainly consisted of both UDP glucuronosyltransferase and Interferon alpha families, implying the connection between SDs and the evolution of these gene families.

CONCLUSIONS

Our findings provide insights into livestock genome evolution and offer rich genomic sources for livestock genomic research.

CNV discovery for milk composition traits in dairy cattle using whole genome resequencing

Background

Copy number variations (CNVs) are important and widely distributed in the genome. CNV detection opens a new avenue for exploring genes associated with complex traits in humans, animals and plants. Herein, we present a genome-wide assessment of CNVs that are potentially associated with milk composition traits in dairy cattle.

Results

In this study, CNVs were detected based on whole genome re-sequencing data of eight Holstein bulls from four half- and/or full-sib families, with extremely high and low estimated breeding values (EBVs) of milk protein percentage and fat percentage. The range of coverage depth per individual was 8.2–11.9×. Using CNVnator, we identified a total of 14,821 CNVs, including 5025 duplications and 9796 deletions. Among them, 487 differential CNV regions (CNVRs) comprising ~8.23 Mb of the cattle genome were observed between the high and low groups. Annotation of these differential CNVRs were performed based on the cattle genome reference assembly (UMD3.1) and totally 235 functional genes were found within the CNVRs. By Gene Ontology and KEGG pathway analyses, we found that genes were significantly enriched for specific biological functions related to protein and lipid metabolism, insulin/IGF pathway-protein kinase B signaling cascade, prolactin signaling pathway and AMPK signaling pathways. These genes included INS, IGF2, FOXO3, TH, SCD5, GALNT18, GALNT16, ART3, SNCA and WNT7A, implying their potential association with milk protein and fat traits. In addition, 95 CNVRs were overlapped with 75 known QTLs that are associated with milk protein and fat traits of dairy cattle (Cattle QTLdb).

Conclusions

In conclusion, based on NGS of 8 Holstein bulls with extremely high and low EBVs for milk PP and FP, we identified a total of 14,821 CNVs, 487 differential CNVRs between groups, and 10 genes, which were suggested as promising candidate genes for milk protein and fat traits.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3636-3) contains supplementary material, which is available to authorized users.

Genome-wide copy number variation (CNV) detection in Nelore cattle reveals highly frequent variants in genome regions harboring QTLs affecting production traits

Background

Copy number variations (CNVs) have been shown to account for substantial portions of observed genomic variation and have been associated with qualitative and quantitative traits and the onset of disease in a number of species. Information from high-resolution studies to detect, characterize and estimate population-specific variant frequencies will facilitate the incorporation of CNVs in genomic studies to identify genes affecting traits of importance.

Results

Genome-wide CNVs were detected in high-density single nucleotide polymorphism (SNP) genotyping data from 1,717 Nelore (Bos indicus) cattle, and in NGS data from eight key ancestral bulls. A total of 68,007 and 12,786 distinct CNVs were observed, respectively. Cross-comparisons of results obtained for the eight resequenced animals revealed that 92 % of the CNVs were observed in both datasets, while 62 % of all detected CNVs were observed to overlap with previously validated cattle copy number variant regions (CNVRs). Observed CNVs were used for obtaining breed-specific CNV frequencies and identification of CNVRs, which were subsequently used for gene annotation. A total of 688 of the detected CNVRs were observed to overlap with 286 non-redundant QTLs associated with important production traits in cattle. All of 34 CNVs previously reported to be associated with milk production traits in Holsteins were also observed in Nelore cattle. Comparisons of estimated frequencies of these CNVs in the two breeds revealed 14, 13, 6 and 14 regions in high (>20 %), low (<20 %) and divergent (NEL > HOL, NEL < HOL) frequencies, respectively.

Conclusions

Obtained results significantly enriched the bovine CNV map and enabled the identification of variants that are potentially associated with traits under selection in Nelore cattle, particularly in genome regions harboring QTLs affecting production traits.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2752-9) contains supplementary material, which is available to authorized users.

Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare

In the past years, there has been a remarkable development of high-throughput omics (HTO) technologies such as genomics, epigenomics, transcriptomics, proteomics and metabolomics across all facets of biology. This has spearheaded the progress of the systems biology era, including applications on animal production and health traits. However, notwithstanding these new HTO technologies, there remains an emerging challenge in data analysis. On the one hand, different HTO technologies judged on their own merit are appropriate for the identification of disease-causing genes, biomarkers for prevention and drug targets for the treatment of diseases and for individualized genomic predictions of performance or disease risks. On the other hand, integration of multi-omic data and joint modelling and analyses are very powerful and accurate to understand the systems biology of healthy and sustainable production of animals. We present an overview of current and emerging HTO technologies each with a focus on their applications in animal and veterinary sciences before introducing an integrative systems genomics framework for analysing and integrating multi-omic data towards improved animal production, health and welfare. We conclude that there are big challenges in multi-omic data integration, modelling and systems-level analyses, particularly with the fast emerging HTO technologies. We highlight existing and emerging systems genomics approaches and discuss how they contribute to our understanding of the biology of complex traits or diseases and holistic improvement of production performance, disease resistance and welfare.

Genetics of Adiposity in Large Animal Models for Human Obesity-Studies on Pigs and Dogs

The role of domestic mammals in the development of human biomedical sciences has been widely documented. Among these model species the pig and dog are of special importance. Both are useful for studies on the etiology of human obesity. Genome sequences of both species are known and advanced genetic tools [eg, microarray SNP for genome wide association studies (GWAS), next generation sequencing (NGS), etc.] are commonly used in such studies. In the domestic pig the accumulation of adipose tissue is an important trait, which influences meat quality and fattening efficiency. Numerous quantitative trait loci (QTLs) for pig fatness traits were identified, while gene polymorphisms associated with these traits were also described. The situation is different in dog population. Generally, excessive accumulation of adipose tissue is considered, similar to humans, as a complex disease. However, research on the genetic background of canine obesity is still in its infancy. Between-breed differences in terms of adipose tissue accumulation are well known in both animal species. In this review we show recent advances of studies on adipose tissue accumulation in pigs and dogs, and their potential importance for studies on human obesity.

Structural Variant Detection by Large-scale Sequencing Reveals New Evolutionary Evidence on Breed Divergence between Chinese and European Pigs

In this study, we performed a genome-wide SV detection among the genomes of thirteen pigs from diverse Chinese and European originated breeds by next genetation sequencing, and constrcuted a single-nucleotide resolution map involving 56,930 putative SVs. We firstly identified a SV hotspot spanning 35 Mb region on the X chromosome specifically in the genomes of Chinese originated individuals. Further scrutinizing this region by large-scale sequencing data of extra 111 individuals, we obtained the confirmatory evidence on our initial finding. Moreover, thirty five SV-related genes within the hotspot region, being of importance for reproduction ability, rendered significant different evolution rates between Chinese and European originated breeds. The SV hotspot identified herein offers a novel evidence for assessing phylogenetic relationships, as well as likely explains the genetic difference of corresponding phenotypes and features, among Chinese and European pig breeds. Furthermore, we employed various SVs to infer genetic structure of individuls surveyed. We found SVs can clearly detect the difference of genetic background among individuals. This clues us that genome-wide SVs can capture majority of geneic variation and be applied into cladistic analyses. Characterizing whole genome SVs demonstrated that SVs are significantly enriched/depleted with various genomic features.

Efficacy of the porcine species in biomedical research

Since domestication, pigs have been used extensively in agriculture and kept as companion animals. More recently they have been used in biomedical research, given they share many physiological and anatomical similarities with humans. Recent technological advances in assisted reproduction, somatic cell cloning, stem cell culture, genome editing, and transgenesis now enable the creation of unique porcine models of human diseases. Here, we highlight the potential applications and advantages of using pigs, particularly minipigs, as indispensable large animal models in fundamental and clinical research, including the development of therapeutics for inherited and chronic disorders, and cancers.

Resequencing diverse Chinese indigenous breeds to enrich the map of genomic variations in swine

To enrich the map of genomic variations in swine, we randomly sequenced 13 domestic and wild individuals from China and Europe. We detected approximately 28.1 million single nucleotide variants (SNVs) and 3.6 million short insertions and deletions (INDELs), of which 2,530,248 SNVs and 3,456,626 INDELs were firstly identified compared with dbSNP 143. Moreover, 208,687 SNVs and 24,161 INDELs were uniquely observed in Chinese pigs, potentially accounting for phenotypic differences between Chinese and European pigs. Furthermore, significantly high correlation between SNV and INDEL was witnessed, which indicated that these two distinct variants may share similar etiologies. We also predicted loss of function genes and found that they were under weaker evolutionary constraints. This study gives interesting insights into the genomic features of the Chinese pig breeds. These data would be useful in the establishment of high-density SNP map and would lay a foundation for facilitating pig functional genomics study.

Copy number variation-based genome wide association study reveals additional variants contributing to meat quality in Swine

Pork quality is important both to the meat processing industry and consumers' purchasing attitude. Copy number variation (CNV) is a burgeoning kind of variants that may influence meat quality. In this study, a genome-wide association study (GWAS) was performed between CNVs and meat quality traits in swine. After false discovery rate (FDR) correction, a total of 8 CNVs on 6 chromosomes were identified to be significantly associated with at least one meat quality trait. All of the 8 CNVs were verified by next generation sequencing and six of them were verified by qPCR. Only the haplotype block containing CNV12 is adjacent to significant SNPs associated with meat quality, suggesting the effects of those CNVs were not likely captured by tag SNPs. The DNA dosage and EST expression of CNV12, which overlap with an obesity related gene Netrin-1 (Ntn1), were consistent with Ntn1 RNA expression, suggesting the CNV12 might be involved in the expression regulation of Ntn1 and finally influence meat quality. We concluded that CNVs may contribute to the genetic variations of meat quality beyond SNPs, and several candidate CNVs were worth further exploration.

Genome-Wide Copy Number Variations Using SNP Genotyping in a Mixed Breed Swine Population

Copy number variations (CNVs) are increasingly understood to affect phenotypic variation. This study uses SNP genotyping of trios of mixed breed swine to add to the catalog of known genotypic variation in an important agricultural animal. PorcineSNP60 BeadChip genotypes were collected from 1802 pigs that combined to form 1621 trios. These trios were from the crosses of 50 boars with 525 sows producing 1621 piglets. The pigs were part of a population that was a mix of ¼ Duroc, ½ Landrace and ¼ Yorkshire breeds. Merging the overlapping CNVs that were observed in two or more individuals to form CNV regions (CNVRs) yielded 502 CNVRs across the autosomes. The CNVRs intersected genes, as defined by RefSeq, 84% of the time – 420 out of 502. The results of this study are compared and contrasted to other swine studies using similar and different methods of detecting CNVR. While progress is being made in this field, more work needs to be done to improve consistency and confidence in CNVR results.

Improved Detection and Characterization of Copy Number Variations Among Diverse Pig Breeds by Array CGH

As a major component of genomic variation, copy number variations (CNVs) are considered as promising markers for some phenotypic and economically important traits in domestic animals. Using a custom-designed 1M array CGH (aCGH), we performed CNV discovery in 12 pig samples from one Asian wild boar population, six Chinese indigenous breeds, and two European commercial breeds. In total, we identified 758 CNV regions (CNVRs), covering 47.43 Mb of the pig genome sequence. Of the total porcine genes, 1295 genes were completely or partially overlapped with the identified CNVRs, which enriched in the terms related to sensory perception of the environment, neurodevelopmental processes, response to external stimuli, and immunity. Further probing the potential functions of these genes, we also found a suite of genes related important traits, which make them a promising resource for exploring the genetic basis of phenotype differences among diverse pig breeds. Compared with previous relevant studies, the current study highlights that different platforms can complement each other, and the combined implementation of different platforms is beneficial to achieve the most comprehensive CNV calls. CNVs detected in diverse populations herein are essentially complementary to the CNV map in the pig genome, which would be helpful for understanding the pig genome variants and investigating the associations between various phenotypes and CNVs.