Abstract
BackgroundThe development of genome-wide genotyping resources has provided terrestrial livestock and crop industries with the unique ability to accurately assess genomic relationships between individuals, uncover the genetic architecture of commercial traits, as well as identify superior individuals for selection based on their specific genetic profile. Utilising recent advancements in de-novo genome-wide genotyping technologies, it is now possible to provide aquaculture industries with these same important genotyping resources, even in the absence of existing genome assemblies. Here, we present the development of a genome-wide SNP assay for the Black Tiger shrimp (Penaeus monodon) through utilisation of a reduced-representation whole-genome genotyping approach (DArTseq).ResultsBased on a single reduced-representation library, 31,262 polymorphic SNPs were identified across 650 individuals obtained from Australian wild stocks and commercial aquaculture populations. After filtering to remove SNPs with low read depth, low MAF, low call rate, deviation from HWE, and non-Mendelian inheritance, 7542 high-quality SNPs were retained. From these, 4236 high-quality genome-wide loci were selected for baits-probe development and 4194 SNPs were included within a finalized target-capture genotype-by-sequence assay (DArTcap). This assay was designed for routine and cost effective commercial application in large scale breeding programs, and demonstrates higher confidence in genotype calls through increased call rate (from 80.2 ± 14.7 to 93.0% ± 3.5%), increased read depth (from 20.4 ± 15.6 to 80.0 ± 88.7), as well as a 3-fold reduction in cost over traditional genotype-by-sequencing approaches.ConclusionImportantly, this assay equips the P. monodon industry with the ability to simultaneously assign parentage of communally reared animals, undertake genomic relationship analysis, manage mate pairings between cryptic family lines, as well as undertake advance studies of genome and trait architecture. Critically this assay can be cost effectively applied as P. monodon breeding programs transition to undertaking genomic selection.
Highlights
The development of genome-wide genotyping resources has provided terrestrial livestock and crop industries with the unique ability to accurately assess genomic relationships between individuals, uncover the genetic architecture of commercial traits, as well as identify superior individuals for selection based on their specific genetic profile
An average of ~ 2.5 million reads were allocated to each individual in library preparation and sequencing; after removal of low quality sequences, monomorphic loci, and SilicoDArT markers, an average of 459,987 ± 88,493 Standard deviation (SD) reads were associated with each individual (366,609,683 total reads over 650 individuals)
To ensure only the highest quality markers were available for baits probe selection and assay development, a series of Single nucleotide polymorphism (SNP) filtering thresholds were implemented to remove individual genotype calls with low confidence, remove less informative markers and remove erroneous data (Fig. 1)
Summary
The development of genome-wide genotyping resources has provided terrestrial livestock and crop industries with the unique ability to accurately assess genomic relationships between individuals, uncover the genetic architecture of commercial traits, as well as identify superior individuals for selection based on their specific genetic profile. Since publication of the first Restriction-site Associated DNA Sequencing (RAD-Seq) protocol by Miller [2], a number of innovative developments of RAD-Seq protocols have been published These include RAD [3], DArTSeq [4], ddRAD [5], 2bRAD [6], ezRAD [7] and 3RAD [8], all of which have seen dramatic improvements in the ease of generating reliable, repeatable and low-cost genotype data through GBS methods across a plethora of species (reviewed by [9]). By undertaking genomic complexity reduction steps (i.e. restriction enzyme digestion and/or fragment size selection) nextgeneration sequencing efforts can be focused more efficiently by consistently sequencing specific regions across each individuals’ genome [9]
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