Detection of genomic variations in nelore-breed cattle using genotyping and resequenced data

Author(s)

Joaquim Manoel Silva

• Document type: Doctoral Thesis
• Press: Campinas, SP.
• Institution: Universidade Estadual de Campinas (UNICAMP). Instituto de Biologia
• Defense date: 2015-10-22

Examining board members

Michel Eduardo Beleza Yamagishi; Maurício de Alvarenga Mudadu; Luiz Lehmann Coutinho; Roberto Hiroshi Higa; Adhemar Zerlotini Neto

• Advisor: Michel Eduardo Beleza Yamagishi; Alexandre Rodrigues Caetano

Abstract

Major technological advances have allowed for the use of genotyping and resequencing for the study of genomic variations, which include single-nucleotide polymorphisms (SNPs), small insertions or deletions, variations in the number of copies of alleles in the genome (otherwise known as copy number variations, or CNVs), and a range of structural variants. These advances have enabled complete genome analysis with good results at progressively lower costs. The present study seeks to detect genomic variations in Nelore cattle using genotyping and resequencing data. We used genotyping data from 1,709 Nelore bulls genotyped with a high-density chip with 777,962 SNP markers. A set of eight Nelore bulls representing historical sires were genotyped and resequenced with an average depth coverage of 20X. First, we determined whether the missing genotypes, or markers that fail in the entire population, contained relevant biological information. We investigated 3,200 SNPs that failed consistently in the population. We discovered that there are a total of 3,300 new SNPs in Nelore cattle. According to the literature on genomic annotation, 31% of these new SNPs are in genetic regions. These genes may be of interest to cattle improvement programs. We suggest applying the missing genotypes methodology to human health as a way to determine possible markers for rare diseases, hereditary genetic diseases and diseases caused by somatic mutations, such as cancer. The CNV study also enabled the development of a new algorithm for grouping together CNVs from genotyping and/or resequencing data from the CNV region (CNVR). The algorithm was implemented in a Java-Merging Copy Number Variant web server (JM-CNV). It possesses a user-friendly, open source, and configurable interface, meaning other researchers can adapt it to their needs. Its output file can be loaded into Genome Browser. We compared JM-CNV to two other programs ¿ HD-CNV and CNVRuler ¿ with the same objectives. JM-CNV was found to be faster and more efficient in resolving CNVR grouping in complex regions. To detect CNVs in Nelore cattle, we used the PennCNV software for the genotyping data and the LUMPY software for the resequencing data. We identified 68,007 CNV candidate regions in the 29 autosomal chromosomes, which were then grouped into 7,319 CNVRs using JM-CNV. Using the LUMPY software and the eight resequenced animals, we detected 13,122 CNVs, which were then grouped into 3,648 CNVRs using JM-CNV. Using the resequenced data, we were able to confirm 909 CNVs detected in the genotyping data and another 111 using the literature, for a total of 1,020 confirmed CNVs possessing many different genes and annotated QTLs. This study enriches the map of CNVs within the bovine genome, particularly the Nelore breed, and supplies important information that may support future studies on the association between CNVs and traits of interest in genetic improvement studies on cattle (AU)

• FAPESP's process: 12/05002-9 - Development of Methodologies for Prospection and Imputation of SNP Markers Based on Data from Resequencing of Complex Genomes
• Grantee: Joaquim Manoel da Silva
• Support Opportunities: Scholarships in Brazil - Doctorate