A New GTSeq Resource to Facilitate Multijurisdictional Research and Management of Walleye Sander Vitreus

Conservation and management professionals often work across jurisdictional boundaries to identify broad ecological patterns. These collaborations help to protect populations whose distributions span political borders. One common limitation to multijurisdictional collaboration is consistency in data recording and reporting. This limitation can impact genetic research, which relies on data about specific markers in an organism\u27s genome. Incomplete overlap of markers between separate studies can prevent direct comparisons of results. Standardized marker panels can reduce the impact of this issue and provide a common starting place for new research. Genotyping-in-thousands (GTSeq) is one approach used to create standardized marker panels for nonmodel organisms. Here, we describe the development, optimization, and early assessments of a new GTSeq panel for use with walleye (Sander vitreus) from the Great Lakes region of North America. High genome-coverage sequencing conducted using RAD capture provided genotypes for thousands of single nucleotide polymorphisms (SNPs). From these markers, SNP and microhaplotype markers were chosen, which were informative for genetic stock identification (GSI) and kinship analysis. The final GTSeq panel contained 500 markers, including 197 microhaplotypes and 303 SNPs. Leave-one-out GSI simulations indicated that GSI accuracy should be greater than 80% in most jurisdictions. The false-positive rates of parent-offspring and full-sibling kinship identification were found to be low. Finally, genotypes could be consistently scored among separate sequencing runs \u3e94% of the time. Results indicate that the GTSeq panel that we developed should perform well for multijurisdictional walleye research throughout the Great Lakes region

Comparative Genomic Analyses of the Moraxella catarrhalis Serosensitive and Seroresistant Lineages Demonstrate Their Independent Evolution

Contains fulltext : 172169.pdf (publisher's version ) (Open Access)The bacterial speciesMoraxella catarrhalishas been hypothesized as being composed of two distinct lineages (referred to as the seroresistant [SR] and serosensitive [SS]) with separate evolutionary histories based on several molecular typing methods, whereas 16S ribotyping has suggested an additional split within the SS lineage. Previously, we characterized whole-genome sequences of 12 SR-lineage isolates, which revealed a relatively small supragenome when compared with other opportunistic nasopharyngeal pathogens, suggestive of a relatively short evolutionary history. Here, we performed whole-genome sequencing on 18 strains from both ribotypes of the SS lineage, an additional SR strain, as well as four previously identified highly divergent strains based on multilocus sequence typing analyses. All 35 strains were subjected to a battery of comparative genomic analyses which clearly show that there are three lineages-the SR, SS, and the divergent. The SR and SS lineages are closely related, but distinct from each other based on three different methods of comparison: Allelic differences observed among core genes; possession of lineage-specific sets of core and distributed genes; and by an alignment of concatenated core sequences irrespective of gene annotation. All these methods show that the SS lineage has much longer interstrain branches than the SR lineage indicating that this lineage has likely been evolving either longer or faster than the SR lineage. There is evidence of extensive horizontal gene transfer (HGT) within both of these lineages, and to a lesser degree between them. In particular, we identified very high rates of HGT between these two lineages for ss-lactamase genes. The four divergent strains aresui generis, being much more distantly related to both the SR and SS groups than these other two groups are to each other. Based on average nucleotide identities, gene content, GC content, and genome size, this group could be considered as a separate taxonomic group. The SR and SS lineages, although distinct, clearly form a single species based on multiple criteria including a large common core genome, average nucleotide identity values, GC content, and genome size. Although neither of these lineages arose from within the other based on phylogenetic analyses, the question of how and when these lineages split and then subsequently reunited in the human nasopharynx is explored

Integrated analyses highlight interactions between the three-dimensional genome and DNA, RNA and epigenomic alterations in metastatic prostate cancer.

The impact of variations in the three-dimensional structure of the genome has been recognized, but solid cancer tissue studies are limited. Here, we performed integrated deep Hi-C sequencing with matched whole-genome sequencing, whole-genome bisulfite sequencing, 5-hydroxymethylcytosine (5hmC) sequencing and RNA sequencing across a cohort of 80 biopsy samples from patients with metastatic castration-resistant prostate cancer. Dramatic differences were present in gene expression, 5-methylcytosine/5hmC methylation and in structural variation versus mutation rate between A and B (open and closed) chromatin compartments. A subset of tumors exhibited depleted regional chromatin contacts at the AR locus, linked to extrachromosomal circular DNA (ecDNA) and worse response to AR signaling inhibitors. We also identified topological subtypes associated with stark differences in methylation structure, gene expression and prognosis. Our data suggested that DNA interactions may predispose to structural variant formation, exemplified by the recurrent TMPRSS2-ERG fusion. This comprehensive integrated sequencing effort represents a unique clinical tumor resource

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Walleye clone filtered

Clone filtered (filtered) VCF file of walleye genotype data. VCF files were generated using stacks 2.46 with minimal filters (STACKS flags = -r 0.3, --min_maf 0.05). Data generated using the SbfI enzyme, methods outlined in Ali et al. (2016) prepared in the Larson Laboratory at the University of Wisconsin-Stevens Point and sequenced on a HiSeq 4000 (PE 150bp reads, 192 samples/lane) at the Michigan State Genomics Core Facility

Brook trout unfiltered

Non-clone filtered (unfiltered) VCF file of brook trout genotype data. VCF files were generated using stacks 2.46 with minimal filters (STACKS flags = -r 0.3, --min_maf 0.05). Data was generated using the SbfI enzyme, methods outlined in Ali et al. (2016)and prepared in the Genomic Variation Lab at the University of California--Davis and sequenced on Illumina NextSeq 500 (PE 75 bp reads, 96 samples/lane) at the Cornell Institute of Biotechnolog

Cisco clone filtered

Clone filtered (filtered) VCF file of cisco genotype data. VCF files were generated using stacks 2.46 with minimal filters (STACKS flags = -r 0.3, --min_maf 0.05). Data generated using the SbfI enzyme, methods outlined in Ali et al. (2016) prepared in the Larson Laboratory at the University of Wisconsin-Stevens Point and sequenced on a HiSeq 4000 (PE 150bp reads, 96 samples/lane) at the Michigan State Genomics Core Facility

Cisco unfiltered

Non-clone filtered (unfiltered) VCF file of cisco genotype data. VCF files were generated using stacks 2.46 with minimal filters (STACKS flags = -r 0.3, --min_maf 0.05). Data generated using the SbfI enzyme, methods outlined in Ali et al. (2016) prepared in the Larson Laboratory at the University of Wisconsin-Stevens Point and sequenced on a HiSeq 4000 (PE 150bp reads, 96 samples/lane) at the Michigan State Genomics Core Facility