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Abstract Microsatellites are powerful markers for tracking genetic variation in wildlife populations due to their high polymorphism and genome-wide abundance. While polymerase chain reaction (PCR)-based fragment size analysis has been the standard for genotyping microsatellites, high-throughput sequencing offers greater resolution and the opportunity to sync historical datasets with modern analyses. We evaluated how genotypes from whole-genome sequencing align with PCR data for 15 microsatellite loci in 11 North American brown bears (Ursus arctos). Brown bear populations in the 48 contiguous United States have declined from approximately 50,000 to fewer than 2,000 over the past decades. Their endangered status has prompted extensive research and genetic monitoring, yielding large, multiyear microsatellite datasets upon which future conservation efforts can build. We achieved an overall microsatellite genotype concordance rate of 94.5% comparing high-throughput sequencing results to PCR based-fragment size results. All discrepancies occurred at complex loci containing multiple insertions and/or deletions (indels). Physically linked indels or single nucleotide polymorphisms (SNPs) occurring within the loci were misinterpreted as independent insertions, underscoring the need for genotyping tools that incorporate phasing when genotyping. To evaluate coverage effects, we downsampled high-throughput sequence data from 30x to 2x. Concordance remained high at 20 to 30x but dropped sharply at 10x, with 5x and 2x having discordant genotypes or insufficient coverage for genotyping. Accurate genotyping required both sufficient depth and number of reads spanning the entire repeat regions. Our results show that short-read whole-genome sequencing can recover microsatellite genotypes with high accuracy when paired with careful variant interpretation. By aligning historical PCR datasets with modern sequencing data, we can preserve decades of genetic insight and strengthen long-term monitoring of at-risk populations. 

Abstract Estimates of de novo mutation rates are essential for phylogenetic and demographic analyses, but their inference has previously been impeded by high error rates in sequence data and uncertainty in the fossil record. Here, we directly estimate de novo germline mutation rates for all extant members of Panthera, as well as the closely related outgroup Neofelis nebulosa, using pedigrees. We use a previously validated pipeline (RatesTools) to calculate mutation rates for each species and subsequently explore the impacts of the novel rates on historic effective population size estimates in each of these charismatic felids of conservation concern. Importantly, we find that the choice of reference genome, the data type and coverage, and the individual all impact estimates of the mutation rate, but these can be largely ameliorated through extensive manual curation. Despite these stochastic effects, manual validation of de novo mutation candidates permitted the reliable inference of pantherine mutation rates. We inferred that base pair mutation rates for all species fell between 3.6 × 10−9 and 7.6 × 10−9 per generation per base pair (mean 5.5 × 10−9 ± 1.7 × 10−9 across Pantherinae at a mean parental age of 5.5 years). Similar to other studies, we show a positive trend of mean parental age with mutation rate and our inferred rates are well within the expected range for other mammals. 

Abstract Hibernation in brown bears is an annual process involving multiple physiologically distinct seasons—hibernation, active, and hyperphagia. While recent studies have characterized broad patterns of differential gene regulation and isoform usage between hibernation and active seasons, patterns of gene and isoform expression during hyperphagia remain relatively poorly understood. The hyperphagia stage occurs between active and hibernation seasons and involves the accumulation of large fat reserves in preparation for hibernation. Here, we use time-series analyses of gene expression and isoform usage to interrogate transcriptomic regulation associated with all three seasons. We identify a large number of genes with significant differential isoform usage (DIU) across seasons and show that these patterns of isoform usage are largely tissue-specific. We also show that DIU and differential gene-level expression responses are generally non-overlapping, with only a small subset of multi-isoform genes showing evidence of both gene-level expression changes and changes in isoform usage across seasons. Additionally, we investigate nuanced regulation of candidate genes involved in the insulin signaling pathway and find evidence of hyperphagia-specific gene expression and isoform regulation that may enhance fat accumulation during hyperphagia. Our findings highlight the value of using temporal analyses of both gene- and isoform-level gene expression when interrogating complex physiological phenotypes and provide new insight into the mechanisms underlying seasonal changes in bear physiology. 

Abstract Environmental change is intensifying the biodiversity crisis and threatening species across the tree of life. Conservation genomics can help inform conservation actions and slow biodiversity loss. However, more training, appropriate use of novel genomic methods and communication with managers are needed. Here, we review practical guidance to improve applied conservation genomics. We share insights aimed at ensuring effectiveness of conservation actions around three themes: (1) improving pedagogy and training in conservation genomics including for online global audiences, (2) conducting rigorous population genomic analyses properly considering theory, marker types and data interpretation and (3) facilitating communication and collaboration between managers and researchers. We aim to update students and professionals and expand their conservation toolkit with genomic principles and recent approaches for conserving and managing biodiversity. The biodiversity crisis is a global problem and, as such, requires international involvement, training, collaboration and frequent reviews of the literature and workshops as we do here. 

Abstract The brown bear (Ursus arctos) is the second largest and most widespread extant terrestrial carnivore on Earth and has recently emerged as a medical model for human metabolic diseases. Here, we report a fully phased chromosome-level assembly of a male North American brown bear built by combining Pacific Biosciences (PacBio) HiFi data and publicly available Hi-C data. The final genome size is 2.47 Gigabases (Gb) with a scaffold and contig N50 length of 70.08 and 43.94 Megabases (Mb), respectively. Benchmarking Universal Single-Copy Ortholog (BUSCO) analysis revealed that 94.5% of single copy orthologs from Mammalia were present in the genome (the highest of any ursid genome to date). Repetitive elements accounted for 44.48% of the genome and a total of 20,480 protein coding genes were identified. Based on whole genome alignment to the polar bear, the brown bear is highly syntenic with the polar bear, and our phylogenetic analysis of 7,246 single-copy orthologs supports the currently proposed species tree for Ursidae. This highly contiguous genome assembly will support future research on both the evolutionary history of the bear family and the physiological mechanisms behind hibernation, the latter of which has broad medical implications. 

Abstract Spiders (Araneae) have a diverse spectrum of morphologies, behaviors, and physiologies. Attempts to understand the genomic-basis of this diversity are often hindered by their large, heterozygous, and AT-rich genomes with high repeat content resulting in highly fragmented, poor-quality assemblies. As a result, the key attributes of spider genomes, including gene family evolution, repeat content, and gene function, remain poorly understood. Here, we used Illumina and Dovetail Chicago technologies to sequence the genome of the long-jawed spider Tetragnatha kauaiensis, producing an assembly distributed along 3,925 scaffolds with an N50 of ∼2 Mb. Using comparative genomics tools, we explore genome evolution across available spider assemblies. Our findings suggest that the previously reported and vast genome size variation in spiders is linked to the different representation and number of transposable elements. Using statistical tools to uncover gene-family level evolution, we find expansions associated with the sensory perception of taste, immunity, and metabolism. In addition, we report strikingly different histories of chemosensory, venom, and silk gene families, with the first two evolving much earlier, affected by the ancestral whole genome duplication in Arachnopulmonata (∼450 Ma) and exhibiting higher numbers. Together, our findings reveal that spider genomes are highly variable and that genomic novelty may have been driven by the burst of an ancient whole genome duplication, followed by gene family and transposable element expansion. 

The unprecedented rate of extinction calls for efficient use of genetics to help conserve biodiversity. Several recent genomic and simulation-based studies have argued that the field of conservation biology has placed too much focus on conserving genome-wide genetic variation, and that the field should instead focus on managing the subset of functional genetic variation that is thought to affect fitness. Here, we critically evaluate the feasibility and likely benefits of this approach in conservation. We find that population genetics theory and empirical results show that conserving genome-wide genetic variation is generally the best approach to prevent inbreeding depression and loss of adaptive potential from driving populations toward extinction. Focusing conservation efforts on presumably functional genetic variation will only be feasible occasionally, often misleading, and counterproductive when prioritized over genome-wide genetic variation. Given the increasing rate of habitat loss and other environmental changes, failure to recognize the detrimental effects of lost genome-wide genetic variation on long-term population viability will only worsen the biodiversity crisis. 

In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various nonhuman species have been published. However, methodological differences among studies in detecting germline mutations and estimating mutation rates make direct comparisons difficult. Here, we describe the many different steps involved in estimating pedigree-based mutation rates, including sampling, sequencing, mapping, variant calling, filtering, and appropriately accounting for false-positive and false-negative rates. For each step, we review the different methods and parameter choices that have been used in the recent literature. Additionally, we present the results from a ‘Mutationathon,’ a competition organized among five research labs to compare germline mutation rate estimates for a single pedigree of rhesus macaques. We report almost a twofold variation in the final estimated rate among groups using different post-alignment processing, calling, and filtering criteria, and provide details into the sources of variation across studies. Though the difference among estimates is not statistically significant, this discrepancy emphasizes the need for standardized methods in mutation rate estimations and the difficulty in comparing rates from different studies. Finally, this work aims to provide guidelines for computational and statistical benchmarks for future studies interested in identifying germline mutations from pedigrees.