Correction: The sockeye salmon genome, transcriptome, and analyses identifying population defining regions of the genome.

[This corrects the article DOI: 10.1371/journal.pone.0240935.].

The sockeye salmon genome, transcriptome, and analyses identifying population defining regions of the genome.

Sockeye salmon (Oncorhynchus nerka) is a commercially and culturally important species to the people that live along the northern Pacific Ocean coast. There are two main sockeye salmon ecotypes-the ocean-going (anadromous) ecotype and the fresh-water ecotype known as kokanee. The goal of this study was to better understand the population structure of sockeye salmon and identify possible genomic differences among populations and between the two ecotypes. In pursuit of this goal, we generated the first reference sockeye salmon genome assembly and an RNA-seq transcriptome data set to better annotate features of the assembly. Resequenced whole-genomes of 140 sockeye salmon and kokanee were analyzed to understand population structure and identify genomic differences between ecotypes. Three distinct geographic and genetic groups were identified from analyses of the resequencing data. Nucleotide variants in an immunoglobulin heavy chain variable gene cluster on chromosome 26 were found to differentiate the northwestern group from the southern and upper Columbia River groups. Several candidate genes were found to be associated with the kokanee ecotype. Many of these genes were related to ammonia tolerance or vision. Finally, the sex chromosomes of this species were better characterized, and an alternative sex-determination mechanism was identified in a subset of upper Columbia River kokanee.

Design patterns for wildlife-related camera trap image analysis.

This paper describes and explains design patterns for software that supports how analysts can efficiently inspect and classify camera trap images for wildlife-related ecological attributes. Broadly speaking, a design pattern identifies a commonly occurring problem and a general reusable design approach to solve that problem. A developer can then use that design approach to create a specific software solution appropriate to the particular situation under consideration. In particular, design patterns for camera trap image analysis by wildlife biologists address solutions to commonly occurring problems they face while inspecting a large number of images and entering ecological data describing image attributes. We developed design patterns for image classification based on our understanding of biologists' needs that we acquired over 8 years during development and application of the freely available Timelapse image analysis system. For each design pattern presented, we describe the problem, a design approach that solves that problem, and a concrete example of how Timelapse addresses the design pattern. Our design patterns offer both general and specific solutions related to: maintaining data consistency, efficiencies in image inspection, methods for navigating between images, efficiencies in data entry including highly repetitious data entry, and sorting and filtering image into sequences, episodes, and subsets. These design patterns can inform the design of other camera trap systems and can help biologists assess how competing software products address their project-specific needs along with determining an efficient workflow.