Genome-wide detection of CNVs in Chinese indigenous sheep with different types of tails using ovine high-density 600K SNP arrays

Zhu, Caiye; Fan, Hongying; Yuan, Zehu; Hu, Shanming; Ma, Xiongfeng; Xuan, Junli; Wang, Hongwei; Zhang, Li; Wei, Caihong; Zhang, Qin; Zhao, Fuping; Du, Lixin

doi:10.1038/srep27822

Cited by 68 publications

(85 citation statements)

References 62 publications

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“…Moioli et al performed a genome-wide scan using approximately 50 000 SNP, and detected BMP2 and VNRT genes related to fat deposition in sheep tails [70] . Through a genome-wide high-density SNP study of sheep with three tail types, Zhu et al detected several regions with CNVs harboring functional genes associated with fat deposition, such as PPARA, RXRA and KLF11 [71] . Furthermore, Yuan et al applied selection tests based on 50K SNP genotype data, and showed that HOXA11, BMP2, PPP1CC, SP3, SP9, WDR92, PROKR1 and ETAA1 genes may be involved in the formation of fat tails in sheep [72] .…”

Section: Tail Traitsmentioning

confidence: 99%

Recent advances in understanding genetic variants associated with economically important traits in sheep (Ovis aries) revealed by high-throughput screening technologies

Xu¹,

Li²

2017

Front. Agr. Sci. Eng.

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Sheep are one of the most economically important domesticated animals for human society. However, genetic improvements for the key traits associated with meat, growth, milk, wool, reproduction, horns and tails progress slowly using conventional crossbreeding methods. With the development and utilization of highthroughput screening technologies over the last decade, a list of functional genes and genetic variants associated with these traits has been identified. This review covers recent genome-wide studies on sheep productive traits using high-throughput screening technologies, including those based on single-nucleotide polymorphisms and copy number variants at the whole-genome level (e.g., genome-wide association studies), transcriptome and DNA methylation sequences. Additionally, comprehensive information on functional genes and genetic variants associated with economically important traits in sheep is provided.

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Section: Tail Traitsmentioning

confidence: 99%

Recent advances in understanding genetic variants associated with economically important traits in sheep (Ovis aries) revealed by high-throughput screening technologies

Xu¹,

Li²

2017

Front. Agr. Sci. Eng.

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“…In 2013, Liu et al analyzed 329 individuals of three sheep breeds (Sunit, Dubois, and German meat sheep) using SNP50 chips for sheep and detected 238 CNV regions, including 73 CNV regions with frequencies greater than 3% [9]. In 2016, Zhu et al [10] found that genes such as PPARA, RXRA, and KLF11 were related to fat deposition and affected the tail type of sheep. These CNV regions contain a large number of genes associated with fat metabolism and GTPase activity.…”

Section: Introductionmentioning

confidence: 99%

Copy Number Variation of the PIGY Gene in Sheep and Its Association Analysis with Growth Traits

Feng

Cheng

et al. 2020

Animals

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Simple Summary:The PIGY (phosphatidylinositol glycan anchor biosynthesis class Y) gene is a member of the PIG gene family and encodes the glycosylphosphatidylinositol-Nacetylglucosaminyltransferase (GPI-GnT) complex. It initiates the biosynthesis of GPI and plays an important role in cell-cell interactions. Sequencing has revealed a 3600 bp copy number variation (CNV) in exon 2 of the PIGY gene in sheep, potentially altering a functional part of the protein. The CNV overlaps 28 quantitative trait loci that are relevant to some economic traits like muscle density and carcass weight. We screened for this CNV of the PIGY gene in 569 individuals, namely, 240 Chaka sheep (CKS), 168 Hu sheep (HS), and 161 small-tailed Han sheep (STHS), and analyzed the association between the presence of this CNV and sheep body size traits. The results showed that the loss-type CNV was more prevalent than other types in these three breeds, and there were significant effects of the PIGY gene CNV on body weight, chest circumference, and circumference of cannon bone of sheep. The results showed that sheep with gain-type CNV had better growth traits than those with other types. The findings reveal the relationship between the CNV of the PIGY gene and growth traits of sheep, suggesting that CNV could be utilized for improved molecular breeding of sheep.Abstract: Copy number variation (CNV) is a type of genomic variation with an important effect on animal phenotype. We found that the PIGY gene contains a 3600 bp copy number variation (CNV) region located in chromosome 6 of sheep (Oar_v4.0 36,121,601-36,125,200 bp). This region overlaps with multiple quantitative trait loci related to phenotypes like muscle density and carcass weight. Therefore, in this study, the copy number variation of the PIGY gene was screened in three Chinese sheep breeds, namely, Chaka sheep (CKS, May of 2018, Wulan County, Qinghai Province, China), Hu sheep (HS, May of 2015, Mengjin County, Henan Province, China), and small-tailed Han sheep (STHS, May of 2016, Yongjing, Gansu Province, China). Association analyses were performed on the presence of CNV and sheep body size traits. We used real-time quantitative PCR (qPCR) to detect the CNV for association analysis. According to the results, the loss-type CNV was more common than other types in the three breeds (global average: loss = 61.5%, normal = 17.5%, and gain = 21.0%). The association analysis also showed significant effects of the PIGY gene CNV on body weight, chest circumference, and circumference of the cannon bone of sheep. Sheep with gain-type CNV had better growth traits than those with other types. The results indicate a clear relationship between the PIGY gene CNV and growth traits of sheep, suggesting the use of CNV as a new molecular breeding marker.

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“…In total, 90 CNVRs were detected across all the individuals, which represented the commonly shared CNVRs. A total of 55,44,82,15,14,72,190,18, and 5 CNVRs were detected as line-speci c CNVRs in line 6 3 , 7 2 , F 1 , RCS-A, D, J, L, M, and X, respectively, as compared to other lines (Table1, Additional le 6: Table S5). Importantly, the line 6 3 and 7 2 lineage-speci c CNVRs could potentially offer certain clues to explore the genetic mechanisms of MD resistance or susceptibility.…”

Section: Shared Versus Line-speci C Cnvrsmentioning

confidence: 99%

“…Following the rst two genome-wide scans for CNVs in human genome [7,8], an large number of CNV detection studies have been performed, which revealed that CNVs are ubiquitously distributed in the genome and can in uence the phenotype via regulations of gene expression and gene dosage [9][10][11]. Besides, numerous studies in other species have also shown that CNVs contributed to phenotypic variation of complex diseases and traits [12][13][14][15][16][17][18][19], including MD in chicken [20][21][22]. Two major traditional platforms employed in CNV detection are based on SNP chips, one is known as comparative genomic hybridization (CGH) array, and the other is SNP genotyping array.…”

Section: Introductionmentioning

confidence: 99%

Genome-wide characterization of copy number variations in the host genome in genetic resistance to Marek's disease using next generation sequencing

Bai

Ding

et al. 2020

Preprint

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Background: Marek’s disease (MD) is a highly neoplastic disease primarily affecting chickens, and remains as a chronic infectious disease that threatens the poultry industry. Copy number variation (CNV) has been examined in many species and is recognized as a major source of genetic variation that directly contributes to phenotypic variation such as resistance to infectious diseases. Two highly inbred chicken lines 63 (MD-resistant) and 72 (MD-susceptible), as well as their F1 generation and six recombinant congenic strains (RCSs) with varied susceptibility to MD, are considered as ideal models to identify the complex mechanisms of genetic and molecular resistance to MD.Results: In the present study, to unravel the potential genetic mechanisms underlying resistance to MD, we performed a genome-wide CNV detection using next generation sequencing on the inbred chicken lines with the assistance of CNVnator. As a result, a total of 1,649 CNV regions (CNVRs) were successfully identified after merging all the nine datasets, of which 90 CNVRs were overlapped across all the chicken lines. Within these shared regions, 1,360 harbored genes were identified. In addition, 55 and 44 CNVRs with 62 and 57 harbored genes were specifically identified in line 63 and 72, respectively. Bioinformatics analysis showed that the nearby genes were significantly enriched in 36 GO terms and 6 KEGG pathways including JAK/STAT signaling pathway. Ten CNVRs (nine deletions and one duplication) involved in 10 disease-related genes were selected for validation by using qRT-PCR, all of which were successfully confirmed. Finally, qRT-PCR was also used to validate two deletion events in line 72 that were definitely normal in line 63. One high-confidence gene, IRF2 was identified as the most promising candidate gene underlying resistance and susceptibility to MD in view of its function and overlaps with data from previous study.Conclusions: Our findings provide valuable insights for understanding the genetic mechanism of resistance to MD and the identified gene and pathway could be considered as the subject of further functional characterization.

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Genome-wide detection of CNVs in Chinese indigenous sheep with different types of tails using ovine high-density 600K SNP arrays

Cited by 68 publications

References 62 publications

Recent advances in understanding genetic variants associated with economically important traits in sheep (Ovis aries) revealed by high-throughput screening technologies

Recent advances in understanding genetic variants associated with economically important traits in sheep (Ovis aries) revealed by high-throughput screening technologies

Copy Number Variation of the PIGY Gene in Sheep and Its Association Analysis with Growth Traits

Genome-wide characterization of copy number variations in the host genome in genetic resistance to Marek's disease using next generation sequencing

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