Title
Development of a 76K alpaca (Vicugna pacos) single nucleotide polymorphisms (SNPs) microarray
Date Issued
01 February 2021
Access level
open access
Resource Type
journal article
Publisher(s)
MDPI AG
Abstract
Small farm producers’ sustenance depends on their alpaca herds and the production of fiber. Genetic improvement of fiber characteristics would increase their economic benefits and quality of life. The incorporation of molecular marker technology could overcome current limitations for the implementation of genetic improvement programs. Hence, the aim of this project was the generation of an alpaca single nucleotide polymorphism (SNP) microarray. A sample of 150 Huacaya alpacas from four farms, two each in Puno and Cerro de Pasco were used for SNP discovery by genotyping by sequencing (GBS). Reduced representation libraries, two per animal, were produced after DNA digestion with ApeK1 and double digestion with Pst1-Msp1. Ten alpaca genomes, sequenced at depths between 12× to 30×, and the VicPac3.1 reference genome were used for read alignments. Bioinformatics analysis discovered 76,508 SNPs included in the microarray. Candidate genes SNPs (302) for fiber quality and color are also included. The microarray SNPs cover 90.5% of the genome length with a density of about 39 ± 2.51 SNPs/Mb of DNA at an average interval of 26.45 ± 18.57 kbp. The performance was evaluated by genotyping 30 family trios and comparing them to their pedigrees, as well as comparing microarray to GBS genotypes. Concordance values of 0.93 and 0.94 for ApeK1 and Pst1-Msp1 generated SNPs were observed. Similarly, 290 fiber quality and color candidate gene SNPs were validated. Availability of this microarray will facilitate genome-wide association studies, marker-assisted selection and, in time, genomic selection.
Start page
1
End page
18
Volume
12
Issue
2
Language
English
OCDE Knowledge area
Ciencia animal, Ciencia de productos lácteos
Scopus EID
2-s2.0-85101943755
PubMed ID
Source
Genes
ISSN of the container
20734425
Sponsor(s)
Funding: The authors acknowledge the financial support from PNIA through projects 028—2016 INIA PNIA-UPMSI-IE and VLIR-UOS funding to the UNALM (IUC) program. Opinions of the author(s) do not automatically reflect those of either the Belgian government or VLIR-UOS and can bind neither the Belgian Government nor VLIR-UOS. The authors acknowledge the financial support from PNIA through projects 028?2016 INIA PNIA-UPMSI-IE and VLIR-UOS funding to the UNALM (IUC) program. Opinions of the author(s) do not automatically reflect those of either the Belgian government or VLIR-UOS and can bind neither the Belgian Government nor VLIR-UOS. The authors acknowledge the Bioinformatic high-performance computing server at UNALM as well as the in-kind support of the Minnesota Super Computer Institute for provid-ing resources for data analysis reported in this paper. Likewise, authors acknowledge the farm community of San Pedro de Racco, GACOCEN S.R.L., INCA TOPS S.A. and Instituto Nacional de Innovacion Agraria (INIA) for facilitating the collection of alpaca blood samples at their facilities. The authors appreciate the comments and contributions made by the reviewers, as well as the critical review provided by Charles Muscoplat.
Sources of information: Directorio de Producción Científica Scopus