ArticleFrontiers in genetics2021
Discovering Copy Number Variation in Dual-Purpose XinJiang Brown Cattle.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 15 citations in OpenAlex.
- Mapping copy number variable regions correlated with reproduction and production traits in Karan Fries cattle mammalian genomics.Mammalian genome : official journal of the International Mammalian Genome Society · 2025Article
- Kangayam and Tharparkar cattle exhibit higher duplications in innate immune genes compared to Sahiwal, Gir, Karan Fries, and Holstein Friesian: insights from an array comparative genomic hybridization.Mammalian genome : official journal of the International Mammalian Genome Society · 2025Article
- Multi-tool copy number detection highlights common body size-associated variants in miniature pig breeds from different geographical regions.BMC genomics · 2025Article
- Analysis of Population Structure and Selective Signatures for Milk Production Traits in Xinjiang Brown Cattle and Chinese Simmental Cattle.International journal of molecular sciences · 2025Article
- Chromosomal quality control in hPSCs: A practical guide to SNP array analysis with GenomeStudio.Frontiers in cell and developmental biology · 2025Article
- Increased rumen Prevotella enhances BCAA synthesis, leading to synergistically increased skeletal muscle in myostatin-knockout cattle.Communications biology · 2024Article
- A comprehensive map of copy number variations in dromedary camels based on whole genome sequence data.Scientific reports · 2024Article
- A Pilot Detection and Associate Study of Gene Presence-Absence Variation in Holstein Cattle.Animals : an open access journal from MDPI · 2024Article
- Genome-wide investigation to assess copy number variants in the Italian local chicken population.Journal of animal science and biotechnology · 2024Article
- Genome-wide analysis of the Siboney de Cuba cattle breed: genetic characterization and framing with cattle breeds worldwide.Frontiers in genetics · 2024Article
- Analysis of genomic copy number variations through whole-genome scan in Yunling cattle.Frontiers in veterinary science · 2024Article
- Genome-Wide Detection of Copy Number Variations Associated with Miniature Features in Horses.Genes · 2023Article
- Analysis of genomic copy number variations through whole-genome scan in Chinese Qaidam cattle.Frontiers in veterinary science · 2023Article
- Advancements in copy number variation screening in herbivorous livestock genomes and their association with phenotypic traits.Frontiers in veterinary science · 2023Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Copy number variants (CNVs), which are a class of structural variant, can be important in relating genomic variation to phenotype. The primary aims of this study were to discover the common CNV regions (CNVRs) in the dual-purpose XinJiang-Brown cattle population and to detect differences between CNVs inferred using the ARS-UCD 1.2 (ARS) or the UMD 3.1 (UMD) genome assemblies based on the 150K SNP (Single Nucleotide Polymorphisms) Chip. PennCNV and CNVPartition methods were applied to calculate the deviation of the standardized signal intensity of SNPs markers to detect CNV status. Following the discovery of CNVs, we used the R package HandyCNV to generate and visualize CNVRs, compare CNVs and CNVRs between genome assemblies, and identify consensus genes using annotation resources. We identified 38 consensus CNVRs using the ARS assembly with 1.95% whole genome coverage, and 33 consensus CNVRs using the UMD assembly with 1.46% whole genome coverage using PennCNV and CNVPartition. We identified 37 genes that intersected 13 common CNVs (>5% frequency), these included functionally interesting genes such as
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.