Whole genome assembly of the snout otter clam, Lutraria rhynchaena, using Nanopore and Illumina data, benchmarked against bivalve genome assemblies

Production of cultured bivalve molluscs was 17.1 million tons in 2016 accounting for 21.4% of global aquaculture production. The lack of genomic resources coupled with limited understanding of the molecular basis of gene expression and phenotypic variation have limited advances in aquaculture-based productivity of marine bivalves. Understanding the molecular basis of phenotypic variation and gene function is therefore important for selective breeding programs for traits such as increased growth and disease resistance. Similarly, whole genome assemblies support GWAS studies to identify trait-specific loci and for genomic-based selective breeding. To this end, whole-genome sequencing has been conducted on several commercial bivalve species, including the edible oysters Crassostrea virginica, Crassostrea gigas, pearl oysters and clams. However, in general, genomic data for bivalve molluscs, which includes a taxonomically diverse group of species, are sparse.

In this study we present the first genomic resources for a species of clam from the superfamily Mactroidea and for a Vietnamese shellfish species and generate a draft reference genome to form the basis of on-going selective breeding studies.

This study also demonstrates the efficacy of using Oxford Nanopore Technology (ONT) reads to scaffold bivalve genome assemblies and shows the value of these relatively inexpensive long reads for spanning large repetitive regions and overcoming complex assembly issues caused by high heterozygosity, which typically confounds short read only assemblies. The quality of our assembly is also benchmarked against other bivalve genome assemblies and we present an initial phylogenomic analysis for the class Bivalvia, which illustrates the value and potential of the increasing number of high quality genomic data sets for phylogenetics.

Authors: Binh Thanh Thai, Yin Peng Lee, Han Ming Gan, Christopher M. Austin, Laurence J. Croft, Tuan Anh Trieu, Mun Hua Tan