Genome assembly can be challenging for species that are characterized by high amounts of polymorphism, heterozygosity, and large effective population sizes. High levels of heterozygosity can result in genome mis-assemblies and a larger than expected genome size due to the haplotig versions of a single locus being assembled as separate loci. Here, we describe the first chromosome-level genome for the eastern oyster, Crassostrea virginica. Publicly released and annotated in 2017, the assembly has a scaffold N50 of 54 mb and is over 97.3% complete based on BUSCO analysis. The genome assembly for the eastern oyster is a critical resource for foundational research into molluscan adaptation to a changing environment and for selective breeding for the aquaculture industry. Subsequent resequencing data suggested the presence of haplotigs in the original assembly, and we developed a post hoc method to break up chimeric contigs and mask haplotigs in published heterozygous genomes and evaluated improvements to the accuracy of downstream analysis. Masking haplotigs had a large impact on SNP discovery and estimates of nucleotide diversity and had more subtle and nuanced effects on estimates of heterozygosity, population structure analysis, and outlier detection. We show that haplotig masking can be a powerful tool for improving genomic inference, and we present an open, reproducible resource for the masking of haplotigs in any published genome.

Landscape transcriptomics is an emerging field studying how genome-wide expression patterns reflect dynamic landscape-scale environmental drivers, including habitat, weather, climate, and contaminants, and the subsequent effects on organismal function. This field is benefitting from advancing and increasingly accessible molecular technologies, which in turn are allowing the necessary characterization of transcriptomes from wild individuals distributed across natural landscapes. This research is especially important given the rapid pace of anthropogenic environmental change and potential impacts that span levels of biological organization. We discuss three major themes in landscape transcriptomic research: connecting transcriptome variation across landscapes to environmental variation, generating and testing hypotheses about the mechanisms and evolution of transcriptomic responses to the environment, and applying this knowledge to species conservation and management. We discuss challenges associated with this approach and suggest potential solutions. We conclude that landscape transcriptomics has great promise for addressing fundamental questions in organismal biology, ecology, and evolution, while providing tools needed for conservation and management of species.