alexa Research Note: Evaluation of Resequencing Technologies Parameters for CNV Genotyping | OMICS International
ISSN: 2161-1041

Hereditary Genetics: Current Research
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Research Article

Research Note: Evaluation of Resequencing Technologies Parameters for CNV Genotyping

Sergio Ivan Román-Ponce1,2,3*, Alessandro Bagnato2 and Theo Meuwissen3

1Centro Nacional de Investigación en Fisiología y Mejoramiento Animal, Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias, México

2Università degli Studi di Milano. Dipartimento di Scienze e Tecnologie Veterinarie per la Sicurezza Alimentare, Via Celoria 10. 20133 Milano, Italia

3Department of Animal and Aqua cultural Sciences, Norwegian University of Life Sciences, Norway

*Corresponding Author:
Dr. Sergio Ivan Roman Ponce
Centro Nacional de Investigación en
Fisiología y Mejoramiento Animal, Instituto
Nacional de Investigaciones Forestales
Agrícolas y Pecuarias, México
Tel: 01 800 088 22 22 0 (55) 38 71 87 00
E-mail: [email protected]

Received date: March 16, 2016; Accepted date: July 15, 2016; Published date: July 17, 2016

Citation: Román-Ponce SI, Bagnato A, Meuwissen T (2016) Research Note: Evaluation of Resequencing Technologies Parameters for CNV Genotyping. Hereditary Genet 5:170. doi:10.4172/2161-1041.1000170

Copyright: © 2016 Ponce SIR, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Whole genome (re)sequencing provides new opportunities to discover Copy Number Variation (CNV) on the genome. Due to the continuous reduction in sequencing costs, it has become as the principal methodology to detect CNV in livestock. One parameter that increases the genotyping cost is the depth of the coverage during sequencing. The main aim of this note was to assess the variation on CNV identification with different depth coverage and readlength on genome sequencing. The results point out that sequences coming from short read-length require less depth coverage than those obtained with long read-length. In addition, small CNV require deeper coverage to be detected. These results can reduce the discovering and genotyping costs since sequencing technologies with short read-lengths are often less costly. Finally, a general formula was derived to optimize the sequencing costs.

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