posted on 2021-07-18, 22:56authored byPM Arbon, CNS Silva, DB Jones, D Jaccoud, M Gervis, DR Jerry, Jan Strugnell
To enable cumulative increases in aquaculture productivity, structured and efficient selective breeding programs are required. These are contingent on the management of genetic resources within the breeding population though the attainment of accurate pedigree information which can be provided by DNA-based parentage analysis. This study developed a SNP panel for greenlip abalone, Haliotis laevigata, from DArTSeq data produced from a genetic audit of greenlip abalone (n = 336) from five farms. The initial dataset consisted of 15,320 SNPs. Strict filtering on SNP quality control metrics was conducted to select the most informative 1,004 SNPs for the design of a DArTag™ genotyping panel for greenlip abalone. Sixteen broodstock and 1035 hatchery produced progeny were genotyped using the 1,004 SNP DArTag™ panel. The resulting genotypes were filtered, to produce 705 high performing SNPs. In silico parentage analysis using subsets of these SNPs (highest ranked by polymorphic information content) revealed that the inclusion of < 50 SNPs were satisfactory to resolve parentage for 10,000 simulated progeny to up to 200 candidate parents. The resolving power of the panel was also assessed under high levels of inbreeding (0–50 %) and relatedness (0–50 %) between candidate parents, and conditions of missing parental genotypes (10–50 %) in silico. Under all levels of inbreeding, relatedness and missing parental genotypes simulated, the panel was able to accurately assign parental pairs to the offspring. To validate these in silico results, parentage analysis of the hatchery produced progeny of the 16 candidate broodstock was conducted using both CERVUS and APIS. Complete parentage was assigned to all experimental progeny, with 100 % consensus between the two methods used. This study indicates this panel will serve as an efficient and cost-effective tool for accurate pedigree establishment for greenlip abalone.
History
Publication Date
2021-06-16
Journal
Aquaculture Reports
Volume
20
Article Number
100746
Pagination
p. 8
Publisher
Elsevier
ISSN
2352-5134
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