Sequencing & Pangenomes

A Low-Pass Whole-Genome Sequencing and Imputation Pipeline for Cobia (Rachycentron canadum): Bridging Laboratory Innovation and Bioinformatics Development

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Abstract

Advancing genomic resources for emerging aquaculture species requires integrated approaches that bridge laboratory innovation and bioinformatics development. In this work, we describe the establishment of a complete workflow for generating and imputing low-pass whole-genome sequencing (WGS) data in Cobia (Rachycentron canadum). The optimized workflow leverages a TnX transposon system, which integrates a combined tagmentation-ligation strategy to minimize positional bias while generating full-length unique dual-index (UDI) libraries compatible with the Element AVITI sequencing platform. Implementation of this approach on various aquatic species, with focus here on Cobia, results in a streamlined workflow capable of maintaining library complexity while increasing sample processing throughput, reducing hands-on bench time, and improving overall cost-efficiency for low-pass WGS applications. On the bioinformatics side, we constructed a phased haplotype reference panel using high-coverage (∼20à—) WGS data from 104 broodstock individuals, comprising the full set of 94 current male and female broodstock and 10 individuals from a previous generation, and retaining approximately 1.3-1.5 million high-quality genome-wide SNPs after stringent filtering. Variant calling, phasing, and imputation workflows were optimized using GLIMPSE2 to recover dense genotypes from low-pass sequencing data. Pipeline performance was evaluated across multiple coverage depths (0.2à—-1à—) and reference configurations by downsampling held-out test individuals and comparing imputed genotypes to their corresponding high-coverage calls. Across test datasets, the optimized pipeline achieved a mean genotype concordance of approximately 97% across ~1.3 million SNPs, demonstrating robust imputation accuracy even at low coverage. This workflow establishes a foundation for imputation-enabled genomic selection in Cobia and provides a scalable model for extending low-pass WGS and imputation strategies to other aquaculture species where high-density genotyping resources are limited.

Keywords: 2026

How to Cite:

Allen, M., Mashruwala, D., Stannard, J., Sauri, S., Pulgarin, , Arlacon, , Castillo, & Verbyla, K., (2026) “A Low-Pass Whole-Genome Sequencing and Imputation Pipeline for Cobia (Rachycentron canadum): Bridging Laboratory Innovation and Bioinformatics Development”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2286854. doi: https://doi.org/10.31274/wcgalp.24146

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