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Bridging the gap between legacy polymerase chain reaction-based microsatellite data with high-throughput sequencing data for conservation genomics.

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.

Animals

A portable recalibration workflow for reference-based variant calling in non-human genomes.

A key computational step in reference-based variant calling is distinguishing true genetic variants from sequencing errors. Advanced tools and workflows have been developed to handle this by computational modelling of technical errors from the sequencing machines. However, these recalibration workflows have largely been evaluated for human data only and its exact applicability for non-human data remains unknown. Here, we conducted a systematic evaluation of variant calling on human, rice, sheep, and chickpea data, and found that existing workflows introduce unexpected statistical bias, thus leading to suboptimal variant calls for non-human data. To address this problem, we present simple guidelines for constructing a "pseudo-"database (pseudoDB) of genetic variants as a scalable and portable solution for recalibration and variant calling. With human data, our pseudoDB-based workflow performs comparably to existing dbSNP-based GATK3 workflows and those using DeepVariant, Strelka2, and FreeBayes. We extend this to other non-human genomes, namely cattle, brown bear, swan goose, African oil palm, Komodo dragon, and stevia, altogether resulting in the identification of up to 242.0% unique genetic variants. The majority of newly identified variants are within the non-coding regions, hinting at the rich diversity of genome regulation in the non-human population. Our pseudoDB-based workflow is agnostic to reference genomes and modular for easy integration with other computational workflows for human and non-human resequencing data.

Humans

mRNA vaccine immunity is enhanced by hepatocyte detargeting and not dependent on dendritic cell expression.

Proteins encoded by mRNA vaccines can be expressed by a diversity of transfected cell types but how cell-type-specific expression influences immunity is poorly understood. To investigate this, we incorporated synthetic microRNA target sites (miRT) into lipid nanoparticle (LNP)-delivered mRNA vaccines to silence mRNA expression specifically in professional antigen-presenting cells (pAPCs), hepatocytes or myocytes. We found that mRNA expression in pAPCs was dispensable for priming antigen-specific T cells, whereas mRNA expression in myocytes induced similar or stronger immune responses, including for SARS-CoV-2, suggesting that antigen cross-presentation or cross-dressing may be more impactful than direct mRNA expression in pAPCs. In contrast, mRNA expression in hepatocytes suppressed the antigen-specific T cell response, partly through PD1/PDL1. In mice bearing tumor-associated antigen (TAA)-expressing lymphoma cells, miRT-mediated hepatocyte-silenced TAA mRNA vaccine enhanced immune response and reduced tumor burden. Thus, non-pAPC expression shapes immunity to mRNA-encoded protein and inclusion of miRTs can boost or blunt mRNA-LNP immunogenicity.

Journal Article