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ABSTRACTHistoplasmosis is an endemic mycosis in North America frequently reported along the Ohio and Mississippi River Valleys, although autochthonous cases occur in non-endemic areas. In the United States, the disease is provoked by two genetically distinct clades of Histoplasma capsulatum sensu lato, Histoplasma mississippiense (Nam1) and H. ohiense (Nam2). To bridge the molecular epidemiological gap, we genotyped 93 Histoplasma isolates (62 novel genomes) including clinical, environmental, and veterinarian samples from a broader geographical range by whole-genome sequencing, followed by evolutionary and species niche modelling analyses. We show that histoplasmosis is caused by two major lineages, H. ohiense and H. mississippiense; with sporadic cases caused by H. suramericanum in California and Texas. While H. ohiense is prevalent in eastern states, H. mississipiense was found to be prevalent in the central and western portions of the United States, but also geographically overlapping in some areas suggesting that these species might co-occur. Species Niche Modelling revealed that H. ohiense thrives in places with warmer and drier conditions, while H. mississippiense is endemic to areas with cooler temperatures and more precipitation. In addition, we predicted multiple areas of secondary contact zones where the two species co-occur, potentially facilitating gene exchange and hybridization. This study provides the most comprehensive understanding of the genomic epidemiology of histoplasmosis in the USA and lays a blueprint for the study of invasive fungal diseases.

OBJECTIVES: Mint oil is used in various commercial applications world-wide. Mint oil is typically harvested from commercial clones of peppermint or spearmints. Spearmints are the product of a cross between two diploid species: Mentha longifolia (horse mint) and Mentha suaveolens (apple mint). Peppermints are the product of an additional hybridization step between spearmint and an octoploid Mentha aquatica (water mint). Here, we present a chromosome-scale assembly of the genome of a clone of M. suaveolens. Together with the previously assembled genome of M. longifolia, these assemblies are instrumental in addressing questions regarding the origins of spearmint and peppermint oil and the genomic composition of commercial spearmints, and to start elaborating strategies for mint cultivar improvement. DATA DESCRIPTION: A Falcon assembly of the genome of M. suaveolens was generated from 103X coverage of PacBio long reads. Additional scaffolding was conducted by Dovetail Genomics, using a Chicago library, and a HiC library. The resulting assembly had an N50 of 44.7 Mb, and 98.45% of the 536 Mb of the assembly were contained within 12 large superscaffolds. Finally, a genetic map was applied to correct persistent misjoins. Illumina RNA-Seq libraries from a variety of tissues were used to annotate the genome.

BACKGROUND: TROP2 (TACSTD2) expression is associated with decreased overall survival (OS) in some solid tumors, and the TROP2-targeting antibody-drug conjugate (ADC) sacituzumab govitecan has been approved in breast and urothelial carcinomas. We aimed to explore the multi-omic landscape associated with TACSTD2 gene expression in various solid tumors to identify patients most likely to benefit from this approach. METHODS: Breast (N = 11 246), colorectal (N = 15 425), hepatocellular (N = 433), pancreatic (N = 5488), and urothelial (N = 4125) tumors were stratified into quartiles by TACSTD2 gene expression, analyzed by next-generation DNA sequencing, whole transcriptome sequencing, and immunohistochemistry at Caris Life Sciences (Phoenix, AZ). Survival data were obtained from insurance claims, and Kaplan-Meier estimates were calculated for molecularly defined cohorts. RESULTS: Several pathogenic mutations were associated with TACSTD2-high tumors, including TP53 in breast, colorectal (CRC), pancreatic, and hepatocellular cancers; KRAS in pancreatic and CRC cancers; ARID1A and FGFR3 in urothelial cancer; and CTNNB1 in hepatocellular cancer. TACSTD2-low breast tumors were enriched for copy number amplifications in CCND1 and FGF/R family member genes. TACSTD2 high was generally associated with more immune cell infiltration and greater T-cell inflammation scores. Patients with TACSTD2-high breast, CRC, and pancreatic cancers demonstrated a significantly shorter OS than TACSTD2-low tumors. This was restricted to CRC with microsatellite stable tumors and patients with pancreatic cancer with KRAS-mutant tumors. Patients with breast cancer with TACSTD2-high tumors also experienced significantly worse OS following immune checkpoint inhibitors. CONCLUSIONS: TACSTD2 expression is associated with key driver alterations and a more active immune microenvironment, suggesting possible combinatorial strategies with TROP2-targeting ADCs plus immunotherapy in various solid tumors.

Amphibians represent a diverse group of tetrapods, marked by deep divergence times between their three systematic orders and families. Studying amphibian biology through the genomics lens increases our understanding of the features of this animal class and that of other terrestrial vertebrates. The need for amphibian genomic resources is more urgent than ever due to the increasing threats to this group. Amphibians are one of the most imperiled taxonomic groups, with approximately 41% of species threatened with extinction due to habitat loss, changes in land use patterns, disease, climate change, and their synergistic effects. Amphibian genomic resources have provided a better understanding of ontogenetic diversity, tissue regeneration, diverse life history and reproductive modes, anti-predator strategies, and resilience and adaptive responses. They also serve as essential models for studying broad genomic traits, such as evolutionary genome expansions and contractions, as they exhibit the widest range of genome sizes among all animal taxa and possess multiple mechanisms of genetic sex determination. Despite these features, genome sequencing of amphibians has significantly lagged behind that of other vertebrates, primarily due to the challenges of assembling their large, repeat-rich genomes and the relative lack of societal support. The emergence of long-read sequencing technologies, combined with advanced molecular and computational techniques that improve scaffolding and reduce computational workloads, is now making it possible to address some of these challenges. To promote and accelerate the production and use of amphibian genomics research through international coordination and collaboration, we launched the Amphibian Genomics Consortium (AGC, https://mvs.unimelb.edu.au/amphibian-genomics-consortium ) in early 2023. This burgeoning community already has more than 282 members from 41 countries. The AGC aims to leverage the diverse capabilities of its members to advance genomic resources for amphibians and bridge the implementation gap between biologists, bioinformaticians, and conservation practitioners. Here we evaluate the state of the field of amphibian genomics, highlight previous studies, present challenges to overcome, and call on the research and conservation communities to unite as part of the AGC to enable amphibian genomics research to leap to the next level.

Cancer genomes are rife with genetic variants; one key outcome of this variation is widespread gain-of-cysteine mutations. These acquired cysteines can be both driver mutations and sites targeted by precision therapies. However, despite their ubiquity, nearly all acquired cysteines remain unidentified via chemoproteomics; identification is a critical step to enable functional analysis, including assessment of potential druggability and susceptibility to oxidation. Here, we pair cysteine chemoproteomics-a technique that enables proteome-wide pinpointing of functional, redox sensitive, and potentially druggable residues-with genomics to reveal the hidden landscape of cysteine genetic variation. Our chemoproteogenomics platform integrates chemoproteomic, whole exome, and RNA-seq data, with a customized two-stage false discovery rate (FDR) error controlled proteomic search, which is further enhanced with a user-friendly FragPipe interface. Chemoproteogenomics analysis reveals that cysteine acquisition is a ubiquitous feature of both healthy and cancer genomes that is further elevated in the context of decreased DNA repair. Reference cysteines proximal to missense variants are also found to be pervasive, supporting heretofore untapped opportunities for variant-specific chemical probe development campaigns. As chemoproteogenomics is further distinguished by sample-matched combinatorial variant databases and is compatible with redox proteomics and small molecule screening, we expect widespread utility in guiding proteoform-specific biology and therapeutic discovery.

Recent increases in frequency and intensity of warm water anomalies and marine heatwaves have led to shifts in species ranges and assemblages. Genomic tools can be instrumental in detecting such shifts. In the early stages of a project assessing population genetic structure in Pacific Sardine (Sardinops sagax), we detected the presence of Japanese Sardine (Sardinops melanosticta) along the west coast of North America for the first time. We assembled a high quality, chromosome-scale reference genome of the Pacific Sardine and generated low coverage, whole genome sequence (lcWGS) data for 345 sardine collected in the California Current Large Marine Ecosystem (CCLME) in 2021 and 2022. Fifty individuals sampled in 2022 were identified as Japanese Sardine based on strong differentiation observed in lcWGS SNP and full mitogenome data. Although we detected a single case of mitochondrial introgression, we did not observe evidence for recent hybridization events. These findings change our understanding of Sardinops spp. distribution and dispersal in the Pacific and highlight the importance of long-term monitoring programs.

Soilborne Ralstonia solanacearum species complex (RSSC) pathogens disrupt microbial communities as they invade roots and fatally wilt plants. RSSC pathogens secrete antimicrobial toxins using a type VI secretion system (T6SS). To investigate how evolution and ecology have shaped the T6SS of these bacterial pathogens, we analyzed the T6SS gene content and architecture across the RSSC and their evolutionary relatives. Our analysis reveals that two ecologically similar Burkholderiaceae taxa, xylem-pathogenic RSSC and Paracidovorax, have convergently evolved to wield large arsenals of T6SS toxins. To understand the mechanisms underlying genomic enrichment of T6SS toxins, we compiled an atlas of 1,066 auxiliary T6SS toxin clusters (aux clusters) across 99 high-quality RSSC genomes. We classified 25 types of aux clusters with toxins that predominantly target lipids, nucleic acids, or unknown cellular substrates. The aux clusters were located in diverse genetic neighborhoods and had complex phylogenetic distributions, suggesting frequent horizontal gene flow. Phages and other mobile genetic elements account for most of the aux cluster acquisition on the chromosome but very little on the megaplasmid. Nevertheless, RSSC genomes were more enriched in aux clusters on the megaplasmid. Although the single, ancestral T6SS was broadly conserved in the RSSC, the T6SS has been convergently lost in atypical, non-soilborne lineages. Overall, our data suggest dynamic interplay between the lifestyle of RSSC lineages and the evolution of T6SSes with robust arsenals of toxins. This pangenomic atlas poises the RSSC as an emerging, tractable model to understand the role of the T6SS in shaping pathogen populations.IMPORTANCEWe explored the eco-evolutionary dynamics that shape the inter-microbial warfare mechanisms of a globally significant plant pathogen, the Ralstonia solanacearum species complex. We discovered that most Ralstonia wilt pathogens have evolved extensive and diverse repertoires of type VI secretion system-associated antimicrobial toxins. These expansive toxin arsenals potentially enhance the ability of Ralstonia pathogens to invade plant microbiomes, enabling them to rapidly colonize and kill their host plants. We devised a classification system to categorize the Ralstonia toxins. Interestingly, many of the toxin gene clusters are encoded on mobile genetic elements, including prophages, which may be mutualistic symbionts that enhance the inter-microbial competitiveness of Ralstonia wilt pathogens. Moreover, our findings suggest that the convergent loss of this multi-gene trait contributes to genome reduction in two vector-transmitted lineages of Ralstonia pathogens. Our findings demonstrate that the interplay between microbial ecology and pathogen lifestyle shapes the evolution of a genetically complex antimicrobial weapon.

Some Basidiomycete fungi are important plant pathogens, and certain species have been associated with the grapevine trunk disease esca. We present the genomes of 4 species associated with esca: Fomitiporia mediterranea, Fomitiporia polymorpha, Tropicoporus texanus, and Inonotus vitis. We generated high-quality phased genome assemblies using long-read sequencing. The genomic and functional comparisons identified potential virulence factors, suggesting their roles in disease development. Similar to other white-rot fungi known for their ability to degrade lignocellulosic substrates, these 4 genomes encoded a variety of lignin peroxidases and carbohydrate-active enzymes (CAZymes) such as CBM1, AA9, and AA2. The analysis of gene family expansion and contraction revealed dynamic evolutionary patterns, particularly in genes related to secondary metabolite production, plant cell wall decomposition, and xenobiotic degradation. The availability of these genomes will serve as a reference for further studies of diversity and evolution of virulence factors and their roles in esca symptoms and host resistance.

Drosophila prolongata is a member of the melanogaster species group and rhopaloa subgroup native to the subtropical highlands of Southeast Asia. This species exhibits an array of recently evolved male-specific morphological, physiological, and behavioral traits that distinguish it from its closest relatives, making it an attractive model for studying the evolution of sexual dimorphism and testing theories of sexual selection. The lack of genomic resources has impeded the dissection of the molecular basis of sex-specific development and behavior in this species. To address this, we assembled the genome of D. prolongata using long-read sequencing and Hi-C scaffolding, resulting in a highly complete and contiguous (scaffold N50 2.2 Mb) genome assembly of 220 Mb. The repetitive content of the genome is 24.6%, the plurality of which are long terminal repeats retrotransposons (33.2%). Annotations based on RNA-seq data and homology to related species revealed a total of 19,330 genes, of which 16,170 are protein-coding. The assembly includes 98.5% of Diptera BUSCO genes, including 93.8% present as a single copy. Despite some likely regional duplications, the completeness of this genome suggests that it can be readily used for gene expression, genome-wide association studies (GWAS), and other genomic analyses.

UNLABELLED: To gain insights into the diversity of Pseudomonas syringae sensu lato affecting sweet cherry in California, we sequenced and analyzed the phylogenomic and genomic architecture of 86 fluorescent pseudomonads isolated from symptomatic and asymptomatic cherry tissues. Fifty-eight isolates were phylogenetically placed within the P. syringae species complex and taxonomically classified into five genomospecies: P. syringae pv. syringae, P. syringae, Pseudomonas cerasi, Pseudomonas viridiflava, and A. We annotated components of the type III secretion system and phytotoxin-encoding genes and correlated the data with pathogenicity phenotypes. Intact probable regulatory protein HrpR was annotated in the genomic sequences of all isolates of P. syringae pv. syringae, P. syringae, P. cerasi, and A. Isolates of P. viridiflava had atypical probable regulatory protein HrpR. Syringomycin and syringopeptin-encoding genes were annotated in isolates of all genomospecies except for A and P. viridiflava. All isolates of P. syringae pv. syringae caused cankers, leaf spots, and fruit lesions in the field. In contrast, all isolates of P. syringae and P. cerasi and some isolates of P. viridiflava caused only cankers. Isolates of genomospecies A could not cause any symptoms suggesting phytotoxins are essential for pathogenicity. On detached immature cherry fruit pathogenicity assays, isolates of all five genomospecies produced symptoms (black-dark brown lesions). However, symptoms of isolates of genomospecies A were significantly (P < 0.01) less severe than those of other genomospecies. We also mined for genes conferring resistance to copper and kasugamycin and correlated these data with in vitro antibiotic sensitivity tests. IMPORTANCE: Comprehensive identification of phytopathogens and an in-depth understanding of their genomic architecture, particularly virulence determinants and antibiotic-resistant genes, are critical for several practical reasons. These include disease diagnosis, improved knowledge of disease epidemiology, pathogen diversity, and determination of the best possible management strategies. In this study, we provide the first report of the presence and pathogenicity of genomospecies Pseudomonas cerasi and Pseudomonas viridiflava in California sweet cherry. More importantly, we report a relatively high level of resistance to copper among the population of Pseudomonas syringae pv. syringae (47.5%). This implies copper cannot be effectively used to control bacterial blast and bacterial canker of sweet cherries. On the other hand, no isolates were resistant to kasugamycin, an indication that kasugamycin could be effectively used for the control of bacterial blast and bacterial canker. Our findings are important to improve the management of bacterial blast and bacterial canker of sweet cherries in California.

Advances in sequencing technologies have enabled the comparison of high-quality genomes of diverse primate species, revealing vast amounts of divergence due to structural variation. Given their large size, structural variants (SVs) can simultaneously alter the function and regulation of multiple genes. Studies estimate that collectively more than 3.5% of the genome is divergent in humans versus other great apes, impacting thousands of genes. Functional genomics and gene-editing tools in various model systems recently emerged as an exciting frontier - investigating the wide-ranging impacts of SVs on molecular, cellular, and systems-level phenotypes. This review examines existing research and identifies future directions to broaden our understanding of the functional roles of SVs on phenotypic innovations and diversity impacting uniquely human features, ranging from cognition to metabolic adaptations.

Large-scale sequencing efforts have been undertaken to understand the mutational landscape of the coding genome. However, the vast majority of variants occur within non-coding genomic regions. We designed an integrative computational and experimental framework to identify recurrently mutated non-coding regulatory regions that drive tumor progression. Applying this framework to sequencing data from a large prostate cancer patient cohort revealed a large set of candidate drivers. We used (1) in silico analyses, (2) massively parallel reporter assays, and (3) in vivo CRISPR interference screens to systematically validate metastatic castration-resistant prostate cancer (mCRPC) drivers. One identified enhancer region, GH22I030351, acts on a bidirectional promoter to simultaneously modulate expression of the U2-associated splicing factor SF3A1 and chromosomal protein CCDC157. SF3A1 and CCDC157 promote tumor growth in vivo. We nominated a number of transcription factors, notably SOX6, to regulate expression of SF3A1 and CCDC157. Our integrative approach enables the systematic detection of non-coding regulatory regions that drive human cancers.

Thermophily is a trait scattered across the fungal tree of life, with its highest prevalence within three fungal families (Chaetomiaceae, Thermoascaceae, and Trichocomaceae), as well as some members of the phylum Mucoromycota. We examined 37 thermophilic and thermotolerant species and 42 mesophilic species for this study and identified thermophily as the ancestral state of all three prominent families of thermophilic fungi. Thermophilic fungal genomes were found to encode various thermostable enzymes, including carbohydrate-active enzymes such as endoxylanases, which are useful for many industrial applications. At the same time, the overall gene counts, especially in gene families responsible for microbial defense such as secondary metabolism, are reduced in thermophiles compared to mesophiles. We also found a reduction in the core genome size of thermophiles in both the Chaetomiaceae family and the Eurotiomycetes class. The Gene Ontology terms lost in thermophilic fungi include primary metabolism, transporters, UV response, and O-methyltransferases. Comparative genomics analysis also revealed higher GC content in the third base of codons (GC3) and a lower effective number of codons in fungal thermophiles than in both thermotolerant and mesophilic fungi. Furthermore, using the Support Vector Machine classifier, we identified several Pfam domains capable of discriminating between genomes of thermophiles and mesophiles with 94% accuracy. Using AlphaFold2 to predict protein structures of endoxylanases (GH10), we built a similarity network based on the structures. We found that the number of disulfide bonds appears important for protein structure, and the network clusters based on protein structures correlate with the optimal activity temperature. Thus, comparative genomics offers new insights into the biology, adaptation, and evolutionary history of thermophilic fungi while providing a parts list for bioengineering applications.

While there has been significant progress in controlling falciparum malaria in the Lao Peoples Democratic Republic (PDR), sporadic cases persist in southern provinces where the extent and patterns of transmission remain largely unknown. To assess parasite transmission in this area, 53 Plasmodium falciparum (Pf) positive cases detected through active test and treat campaigns from December 2017 to November 2018 were sequenced, targeting 204 highly polymorphic amplicons. Two R packages, MOIRE and Dcifer, were applied to assess the multiplicity of infections (MOI), effective MOI (eMOI), within-host parasite relatedness, and between-host parasite relatedness ([Formula: see text]). Genomic data were integrated with survey data to characterize the temporal and spatial structures of identified clusters. The positive cases were mainly captured during the focal test and treat campaign conducted in 2018, and in the Pathoomphone area, which had the highest test positivity and forest activity. About 30% of the cases were polyclonal infections, with over half of theses (63%) showing within-host relatedness greater than 0.6, suggesting that cotransmission rather than superinfection was primarily responsible for maintaining polyclonality. A large majority of cases (81%) were infected by parasites genetically linked to one or more other cases. We identified five genetically distinct clusters in forest fringe villages within the Pathoomphone district, characterized by a high degree of genetic relatedness between parasites (mean [Formula: see text] = 0.8). Four smaller clusters of 2-3 cases linked Moonlapamok and Pathoomphone districts, with an average [Formula: see text] of 0.6, suggesting cross-district transmission. Most of the clustered cases occurred within 20 km and 2 months of each other, consistent with focal transmission. Transmission clusters identified in this study confirm the role of ongoing focal parasite transmission occurring within the forest or forest-fringe in the highly mobile population.

Cannabis use disorder (CanUD) has increased with the legalization of the use of cannabis. Around 20% of individuals using cannabis develop CanUD, and the number of users has grown with increasing ease of access. CanUD and other substance use disorders (SUDs) are associated phenotypically and genetically. We leveraged new CanUD genomics data to undertake genetically-informed analyses with unprecedented power, to investigate the genetic architecture and causal relationships between CanUD and lifetime cannabis use with risk for developing SUDs and substance use traits. Analyses included calculating local and global genetic correlations, genomic structural equation modeling (genomicSEM), and Mendelian Randomization (MR). Results from the genetic correlation and genomicSEM analyses demonstrated that CanUD and cannabis use differ in their relationships with SUDs and substance use traits. We found significant causal effects of CanUD influencing all the analyzed traits: opioid use disorder (OUD) (Inverse variant weighted, IVW β = 0.925 ± 0.082), problematic alcohol use (PAU) (IVW β = 0.443 ± 0.030), drinks per week (DPW) (IVW β = 0.182 ± 0.025), Fagerström Test for Nicotine Dependence (FTND) (IVW β = 0.183 ± 0.052), cigarettes per day (IVW β = 0.150 ± 0.045), current versus former smokers (IVW β = 0.178 ± 0.052), and smoking initiation (IVW β = 0.405 ± 0.042). We also found evidence of bidirectionality showing that OUD, PAU, smoking initiation, smoking cessation, and DPW all increase risk of developing CanUD. For cannabis use, bidirectional relationships were inferred with PAU, smoking initiation, and DPW; cannabis use was also associated with a higher risk of developing OUD (IVW β = 0.785 ± 0.266). GenomicSEM confirmed that CanUD and cannabis use load onto different genetic factors. We conclude that CanUD and cannabis use can increase the risk of developing other SUDs. This has substantial public health implications; the move towards legalization of cannabis use may be expected to increase other kinds of problematic substance use. These harmful outcomes are in addition to the medical harms associated directly with CanUD.

Bipolar disorder (BD) is a heritable disorder characterized by shifts in mood that manifest in manic or depressive episodes. Clinical studies have identified abnormalities of the circadian system in BD patients as a hallmark of underlying pathophysiology. Fibroblasts are a well-established in vitro model for measuring circadian patterns. We set out to examine the underlying genetic architecture of circadian rhythm in fibroblasts, with the goal to assess its contribution to the polygenic nature of BD disease risk. We collected, from primary cell lines of 6 healthy individuals, temporal genomic features over a 48 h period from transcriptomic data (RNA-seq) and open chromatin data (ATAC-seq). The RNA-seq data showed that only a limited number of genes, primarily the known core clock genes such as ARNTL, CRY1, PER3, NR1D2 and TEF display circadian patterns of expression consistently across cell cultures. The ATAC-seq data identified that distinct transcription factor families, like those with the basic helix-loop-helix motif, were associated with regions that were increasing in accessibility over time. Whereas known glucocorticoid receptor target motifs were identified in those regions that were decreasing in accessibility. Further evaluation of these regions using stratified linkage disequilibrium score regression analysis failed to identify a significant presence of them in the known genetic architecture of BD, and other psychiatric disorders or neurobehavioral traits in which the circadian rhythm is affected. In this study, we characterize the biological pathways that are activated in this in vitro circadian model, evaluating the relevance of these processes in the context of the genetic architecture of BD and other disorders, highlighting its limitations and future applications for circadian genomic studies.

The Human Genome Project was an enormous accomplishment, providing a foundation for countless explorations into the genetics and genomics of the human species. Yet for many years, the human genome reference sequence remained incomplete and lacked representation of human genetic diversity. Recently, two major advances have emerged to address these shortcomings: complete gap-free human genome sequences, such as the one developed by the Telomere-to-Telomere Consortium, and high-quality pangenomes, such as the one developed by the Human Pangenome Reference Consortium. Facilitated by advances in long-read DNA sequencing and genome assembly algorithms, complete human genome sequences resolve regions that have been historically difficult to sequence, including centromeres, telomeres, and segmental duplications. In parallel, pangenomes capture the extensive genetic diversity across populations worldwide. Together, these advances usher in a new era of genomics research, enhancing the accuracy of genomic analysis, paving the path for precision medicine, and contributing to deeper insights into human biology.

UNLABELLED: Infections caused by antimicrobial-resistant Escherichia coli are the leading cause of death attributed to antimicrobial resistance (AMR) worldwide, and the known AMR mechanisms involve a range of functional proteins. Here, we employed a pan-genome wide association study (GWAS) approach on over 1,000 E. coli isolates from sick dogs collected across the US and Canada and identified a strong statistical association (empirical P < 0.01) of AMR, involving a range of antibiotics to a group 1 capsular (CPS) gene cluster. This cluster included genes under relaxed selection pressure, had several loci missing, and had pseudogenes for other key loci. Furthermore, this cluster is widespread in E. coli and Klebsiella clinical isolates across multiple host species. Earlier studies demonstrated that the octameric CPS polysaccharide export protein Wza can transmit macrolide antibiotics into the E. coli periplasm. We suggest that the CPS in question, and its highly divergent Wza, functions as an antibiotic trap, preventing antimicrobial penetration. We also highlight the high diversity of lineages circulating in dogs across all regions studied, the overlap with human lineages, and regional prevalence of resistance to multiple antimicrobial classes. IMPORTANCE: Much of the human genomic epidemiology data available for E. coli mechanism discovery studies has been heavily biased toward shiga-toxin producing strains from humans and livestock. E. coli occupies many niches and produces a wide variety of other significant pathotypes, including some implicated in chronic disease. We hypothesized that since dogs tend to share similar strains with their owners and are treated with similar antibiotics, their pathogenic isolates will harbor unexplored AMR mechanisms of importance to humans as well as animals. By comparing over 1,000 genomes with in vitro antimicrobial susceptibility data from sick dogs across the US and Canada, we identified a strong multidrug resistance association with an operon that appears to have once conferred a type 1 capsule production system.

The American black bear, Ursus americanus, is a widespread and ecologically important species in North America. In California, the black bear plays an important role in a variety of ecosystems and serves as an important species for recreational hunting. While research suggests that the populations in California are currently healthy, continued monitoring is critical, with genomic analyses providing an important surveillance tool. Here we report a high-quality, near chromosome-level genome assembly from a U. americanus sample from California. The primary assembly has a total length of 2.5 Gb contained in 316 scaffolds, a contig N50 of 58.9 Mb, a scaffold N50 of 67.6 Mb, and a BUSCO completeness score of 96%. This U. americanus genome assembly will provide an important resource for the targeted management of black bear populations in California, with the goal of achieving an appropriate balance between the recreational value of black bears and the maintenance of viable populations. The high quality of this genome assembly will also make it a valuable resource for comparative genomic analyses among black bear populations and among bear species.

The California Pipevine, Aristolochia californica Torr., is the only endemic California species within the cosmopolitan birthwort family Aristolochiaceae. It occurs as an understory vine in riparian and chaparral areas and in forest edges and windrows. The geographic range of this plant species almost entirely overlaps with that of its major specialized herbivore, the California Pipevine Swallowtail Butterfly Battus philenor hirsuta. While this species pair is a useful, ecologically well-understood system to study co-evolution, until recently, genomic resources for both have been lacking. Here, we report a new, chromosome-level assembly of A. californica as part of the California Conservation Genomics Project (CCGP). Following the sequencing and assembly strategy of the CCGP, we used Pacific Biosciences HiFi long reads and Hi-C chromatin proximity sequencing technology to produce a de novo assembled genome. Our genome assembly, the first for any species in the genus, contains 531 scaffolds spanning 661 megabase (Mb) pairs, with a contig N50 of 6.53 Mb, a scaffold N50 of 42.2 Mb, and BUSCO complete score of 98%. In combination with the recently published B. philenor hirsuta reference genome assembly, the A. californica reference genome assembly will be a powerful tool for studying co-evolution in a rapidly changing California landscape.

As demonstrated by the SARS-CoV-2 pandemic, the emergence of novel viral strains with increased transmission rates poses a serious threat to global health. Statistical models of genome sequence evolution may provide a critical tool for early detection of these strains. Using a novel stochastic model that links transmission rates to the entire viral genome sequence, we study the utility of phylogenetic methods that use a phylogenetic tree relating viral samples versus count-based methods that use case counts of variants over time exclusively to detect increased transmission rates and identify candidate causative mutations. We find that phylogenies in particular can detect novel transmission-enhancing variants very soon after their origin and may facilitate the development of early detection systems for outbreak surveillance.

The higher classification of termites requires substantial revision as the Neoisoptera, the most diverse termite lineage, comprise many paraphyletic and polyphyletic higher taxa. Here, we produce an updated termite classification using genomic-scale analyses. We reconstruct phylogenies under diverse substitution models with ultraconserved elements analyzed as concatenated matrices or within the multi-species coalescence framework. Our classification is further supported by analyses controlling for rogue loci and taxa, and topological tests. We show that the Neoisoptera are composed of seven family-level monophyletic lineages, including the Heterotermitidae Froggatt, Psammotermitidae Holmgren, and Termitogetonidae Holmgren, raised from subfamilial rank. The species-rich Termitidae are composed of 18 subfamily-level monophyletic lineages, including the new subfamilies Crepititermitinae, Cylindrotermitinae, Forficulitermitinae, Neocapritermitinae, Protohamitermitinae, and Promirotermitinae; and the revived Amitermitinae Kemner, Microcerotermitinae Holmgren, and Mirocapritermitinae Kemner. Building an updated taxonomic classification on the foundation of unambiguously supported monophyletic lineages makes it highly resilient to potential destabilization caused by the future availability of novel phylogenetic markers and methods. The taxonomic stability is further guaranteed by the modularity of the new termite classification, designed to accommodate as-yet undescribed species with uncertain affinities to the herein delimited monophyletic lineages in the form of new families or subfamilies.

The ENIGMA research consortium develops and applies methods to determine clinical significance of variants in hereditary breast and ovarian cancer genes. An ENIGMA BRCA1/2 classification sub-group, formed in 2015 as a ClinGen external expert panel, evolved into a ClinGen internal Variant Curation Expert Panel (VCEP) to align with Food and Drug Administration recognized processes for ClinVar contributions. The VCEP reviewed American College of Medical Genetics and Genomics/Association of Molecular Pathology (ACMG/AMP) classification criteria for relevance to interpreting BRCA1 and BRCA2 variants. Statistical methods were used to calibrate evidence strength for different data types. Pilot specifications were tested on 40 variants and documentation revised for clarity and ease of use. The original criterion descriptions for 13 evidence codes were considered non-applicable or overlapping with other criteria. Scenario of use was extended or re-purposed for eight codes. Extensive analysis and/or data review informed specification descriptions and weights for all codes. Specifications were applied to pilot variants with pre-existing ClinVar classification as follows: 13 uncertain significance or conflicting, 14 pathogenic and/or likely pathogenic, and 13 benign and/or likely benign. Review resolved classification for 11/13 uncertain significance or conflicting variants and retained or improved confidence in classification for the remaining variants. Alignment of pre-existing ENIGMA research classification processes with ACMG/AMP classification guidelines highlighted several gaps in the research processes and the baseline ACMG/AMP criteria. Calibration of evidence strength was key to justify utility and strength of different data types for gene-specific application. The gene-specific criteria demonstrated value for improving ACMG/AMP-aligned classification of BRCA1 and BRCA2 variants.

Precision medicine holds great promise for improving cancer outcomes. Yet, there are large inequities in the demographics of patients from whom genomic data and models, including patient-derived xenografts (PDX), are developed and for whom treatments are optimized. In this study, we developed a genetic ancestry pipeline for the Cancer Genomics Cloud, which we used to assess the diversity of models currently available in the National Cancer Institute-supported PDX Development and Trial Centers Research Network (PDXNet). We showed that there is an under-representation of models derived from patients of non-European ancestry, consistent with other cancer model resources. We discussed these findings in the context of disparities in cancer incidence and outcomes among demographic groups in the US, as well as power analyses for biomarker discovery, to highlight the immediate need for developing models from minority populations to address cancer health equity in precision medicine. Our analyses identified key priority disparity-associated cancer types for which new models should be developed.SignificanceUnderstanding whether and how tumor genetic factors drive differences in outcomes among U.S. minority groups is critical to addressing cancer health disparities. Our findings suggest that many additional models will be necessary to understand the genome-driven sources of these disparities.

BACKGROUND: A number of deep learning models have been developed to predict epigenetic features such as chromatin accessibility from DNA sequence. Model evaluations commonly report performance genome-wide; however, cis regulatory elements (CREs), which play critical roles in gene regulation, make up only a small fraction of the genome. Furthermore, cell type-specific CREs contain a large proportion of complex disease heritability. RESULTS: We evaluate genomic deep learning models in chromatin accessibility regions with varying degrees of cell type specificity. We assess two modeling directions in the field: general purpose models trained across thousands of outputs (cell types and epigenetic marks) and models tailored to specific tissues and tasks. We find that the accuracy of genomic deep learning models, including two state-of-the-art general purpose models-Enformer and Sei-varies across the genome and is reduced in cell type-specific accessible regions. Using accessibility models trained on cell types from specific tissues, we find that increasing model capacity to learn cell type-specific regulatory syntax-through single-task learning or high capacity multi-task models-can improve performance in cell type-specific accessible regions. We also observe that improving reference sequence predictions does not consistently improve variant effect predictions, indicating that novel strategies are needed to improve performance on variants. CONCLUSIONS: Our results provide a new perspective on the performance of genomic deep learning models, showing that performance varies across the genome and is particularly reduced in cell type-specific accessible regions. We also identify strategies to maximize performance in cell type-specific accessible regions.

Strains across the Lactobacillaceae family form the basis for a trillion-dollar industry. Our understanding of the genomic basis for their key traits is fragmented, however, including the metabolism that is foundational to their industrial uses. Pangenome analysis of publicly available Lactobacillaceae genomes allowed us to generate genome-scale metabolic network reconstructions for 26 species of industrial importance. Their manual curation led to more than 75,000 gene-protein-reaction associations that were deployed to generate 2,446 genome-scale metabolic models. Cross-referencing genomes and known metabolic traits allowed for manual metabolic network curation and validation of the metabolic models. As a result, we provide the first pangenomic basis for metabolism in the Lactobacillaceae family and a collection of predictive computational metabolic models that enable a variety of practical uses.IMPORTANCELactobacillaceae, a bacterial family foundational to a trillion-dollar industry, is increasingly relevant to biosustainability initiatives. Our study, leveraging approximately 2,400 genome sequences, provides a pangenomic analysis of Lactobacillaceae metabolism, creating over 2,400 curated and validated genome-scale models (GEMs). These GEMs successfully predict (i) unique, species-specific metabolic reactions; (ii) niche-enriched reactions that increase organism fitness; (iii) essential media components, offering insights into the global amino acid essentiality of Lactobacillaceae; and (iv) fermentation capabilities across the family, shedding light on the metabolic basis of Lactobacillaceae-based commercial products. This quantitative understanding of Lactobacillaceae metabolic properties and their genomic basis will have profound implications for the food industry and biosustainability, offering new insights and tools for strain selection and manipulation.

Maintenance of water homeostasis is a fundamental cellular process required by all living organisms. Here, we use the single-celled green alga Chlamydomonas reinhardtii to establish a foundational understanding of osmotic-stress signaling pathways through transcriptomics, phosphoproteomics, and functional genomics approaches. Comparison of pathways identified through these analyses with yeast and Arabidopsis allows us to infer their evolutionary conservation and divergence across these lineages. 76 genes, acting across diverse cellular compartments, were found to be important for osmotic-stress tolerance in Chlamydomonas through their functions in cytoskeletal organization, potassium transport, vesicle trafficking, mitogen-activated protein kinase and chloroplast signaling. We show that homologs for five of these genes have conserved functions in stress tolerance in Arabidopsis and reveal a novel PROFILIN-dependent stage of acclimation affecting the actin cytoskeleton that ensures tissue integrity upon osmotic stress. This study highlights the conservation of the stress response in algae and land plants, and establishes Chlamydomonas as a unicellular plant model system to dissect the osmotic stress signaling pathway.

During the last decade, the spotted wing drosophila, Drosophila suzukii, has spread from eastern Asia to the Americas, Europe, and Africa. This fly attacks many species of cultivated and wild fruits with soft, thin skins, where its serrated ovipositor allows it to lay eggs in undamaged fruit. Parasitoids from the native range of D. suzukii may provide sustainable management of this polyphagous pest. Among these parasitoids, host-specificity testing has revealed a lineage of Ganaspis near brasiliensis, referred to in this paper as G1, that appears to be a cryptic species more host-specific to D. suzukii than other parasitoids. Differentiation among cryptic species is critical for introduction and subsequent evaluation of their impact on D. suzukii. Here, we present results on divergence in genomic sequences and architecture and reproductive isolation between lineages of Ganaspis near brasiliensis that appear to be cryptic species. We studied five populations, two from China, two from Japan, and one from Canada, identified as the G1 vs G3 lineages based on differences in cytochrome oxidase l sequences. We assembled and annotated the genomes of these populations and analyzed divergences in sequence and genome architecture between them. We also report results from crosses to test reproductive compatibility between the G3 lineage from China and the G1 lineage from Japan. The combined results on sequence divergence, differences in genome architectures, ortholog divergence, reproductive incompatibility, differences in host ranges and microhabitat preferences, and differences in morphology show that these lineages are different species. Thus, the decision to evaluate the lineages separately and only import and introduce the more host-specific lineage to North America and Europe was appropriate.

Aposematic organisms rely on their conspicuous appearance to signal that they are defended and unpalatable. Such phenotypes are strongly tied to survival and reproduction. Aposematic colors and patterns are highly variable; however, the genetic, biochemical, and physiological mechanisms producing this conspicuous coloration remain largely unidentified. Here, we identify genes potentially affecting color variation in two color morphs of Ranitomeya imitator: the orange-banded Sauce and the redheaded Varadero morphs. We examine gene expression in black and orange skin patches from the Sauce morph and black and red skin patches from the Varadero morph. We identified genes differentially expressed between skin patches, including those that are involved in melanin synthesis (e.g. mlana, pmel, tyrp1), iridophore development (e.g. paics, ppat, ak1), pteridine synthesis (e.g. gch1, pax3-a, xdh), and carotenoid metabolism (e.g. dgat2, rbp1, scarb2). In addition, using weighted correlation network analysis, we identified the top 50 genes with high connectivity from the most significant network associated with gene expression differences between color morphs. Of these 50 genes, 13 were known to be related to color production (gch1, gmps, gpr143, impdh1, mc1r, pax3-a, pax7, ppat, rab27a, rlbp1, tfec, trpm1, xdh).

Polygenic scores (PGS) have emerged as the tool of choice for genomic prediction in a wide range of fields. We show that PGS performance varies broadly across contexts and biobanks. Contexts such as age, sex and income can impact PGS accuracy with similar magnitudes as genetic ancestry. Here we introduce an approach (CalPred) that models all contexts jointly to produce prediction intervals that vary across contexts to achieve calibration (include the trait with 90% probability), whereas existing methods are miscalibrated. In analyses of 72 traits across large and diverse biobanks (All of Us and UK Biobank), we find that prediction intervals required adjustment by up to 80% for quantitative traits. For disease traits, PGS-based predictions were miscalibrated across socioeconomic contexts such as annual household income levels, further highlighting the need of accounting for context information in PGS-based prediction across diverse populations.

Author(s): Ashok Kumar Saxena (corresponding author) [1]; Suman Choudhary [2]; Geetanjali Chilkote [1] Anaesthesiologists and pain physicians approach the genetics of pain management differently, intrigued by significant interindividual differences in [...]

Juvenile dermatomyositis (JDM) is one of several childhood-onset autoimmune disorders characterized by a type I IFN response and autoantibodies. Treatment options are limited due to an incomplete understanding of how the disease emerges from dysregulated cell states across the immune system. We therefore investigated the blood of patients with JDM at different stages of disease activity using single-cell transcriptomics paired with surface protein expression. By immunophenotyping peripheral blood mononuclear cells, we observed skewing of the B cell compartment toward an immature naive state as a hallmark of JDM at diagnosis. Furthermore, we find that these changes in B cells are paralleled by T cell signatures suggestive of Th2-mediated inflammation that persist despite disease quiescence. We applied network analysis to reveal that hyperactivation of the type I IFN response in all immune populations is coordinated with previously masked cell states including dysfunctional protein processing in CD4+ T cells and regulation of cell death programming in NK cells, CD8+ T cells, and γδ T cells. Together, these findings unveil the coordinated immune dysregulation underpinning JDM and provide insight into strategies for restoring balance in immune function.

Fermentation is a type of metabolism carried out by organisms in environments without oxygen. Despite being studied for over 185 years, the diversity and complexity of this metabolism are just now becoming clear. Our review starts with the definition of fermentation, which has evolved over the years and which we help further refine. We then examine the range of organisms that carry out fermentation and their traits. Over one-fourth of all prokaryotes are fermentative, use more than 40 substrates, and release more than 50 metabolic end products. These insights come from studies analyzing records of thousands of organisms. Next, our review examines the complexity of fermentation at the biochemical level. We map out pathways of glucose fermentation in unprecedented detail, covering over 120 biochemical reactions. We also review recent studies coupling genomics and enzymology to reveal new pathways and enzymes. Our review concludes with practical applications for agriculture, human health, and industry. All these areas depend on fermentation and could be improved through manipulating fermentative microbes and enzymes. We discuss potential approaches for manipulation, including genetic engineering, electrofermentation, probiotics, and enzyme inhibitors. We hope our review underscores the importance of fermentation research and stimulates the next 185 years of study.

Activating signal co-integrator complex 1 (ASCC1) acts with ASCC-ALKBH3 complex in alkylation damage responses. ASCC1 uniquely combines two evolutionarily ancient domains: nucleotide-binding K-Homology (KH) (associated with regulating splicing, transcriptional, and translation) and two-histidine phosphodiesterase (PDE; associated with hydrolysis of cyclic nucleotide phosphate bonds). Germline mutations link loss of ASCC1 function to spinal muscular atrophy with congenital bone fractures 2 (SMABF2). Herein analysis of The Cancer Genome Atlas (TCGA) suggests ASCC1 RNA overexpression in certain tumors correlates with poor survival, Signatures 29 and 3 mutations, and genetic instability markers. We determined crystal structures of Alvinella pompejana (Ap) ASCC1 and Human (Hs) PDE domain revealing high-resolution details and features conserved over 500 million years of evolution. Extending our understanding of the KH domain Gly-X-X-Gly sequence motif, we define a novel structural Helix-Clasp-Helix (HCH) nucleotide binding motif and show ASCC1 sequence-specific binding to CGCG-containing RNA. The V-shaped PDE nucleotide binding channel has two His-Φ-Ser/Thr-Φ (HXT) motifs (Φ being hydrophobic) positioned to initiate cyclic phosphate bond hydrolysis. A conserved atypical active-site histidine torsion angle implies a novel PDE substrate. Flexible active site loop and arginine-rich domain linker appear regulatory. Small-angle X-ray scattering (SAXS) revealed aligned KH-PDE RNA binding sites with limited flexibility in solution. Quantitative evolutionary bioinformatic analyses of disease and cancer-associated mutations support implied functional roles for RNA binding, phosphodiesterase activity, and regulation. Collective results inform ASCC1's roles in transactivation and alkylation damage responses, its targeting by structure-based inhibitors, and how ASCC1 mutations may impact inherited disease and cancer.

Many autism spectrum disorder (ASD)-associated genes act as transcriptional regulators (TRs). Chromatin immunoprecipitation sequencing (ChIP-seq) was used to identify the regulatory targets of ARID1B, BCL11A, FOXP1, TBR1, and TCF7L2, ASD-associated TRs in the developing human and mouse cortex. These TRs shared substantial overlap in the binding sites, especially within open chromatin. The overlap within a promoter region, 1-2,000 bp upstream of the transcription start site, was highly predictive of brain-expressed genes. This signature was observed in 96 out of 102 ASD-associated genes. In vitro CRISPRi against ARID1B and TBR1 delineated downstream convergent biology in mouse cortical cultures. After 8 days, NeuN+ and CALB+ cells were decreased, GFAP+ cells were increased, and transcriptomic signatures correlated with the postmortem brain samples from individuals with ASD. We suggest that functional convergence across five ASD-associated TRs leads to shared neurodevelopmental outcomes of haploinsufficient disruption.

Intratumor heterogeneity underlies cancer evolution and treatment resistance, but targetable mechanisms driving intratumor heterogeneity are poorly understood. Meningiomas are the most common primary intracranial tumors and are resistant to all medical therapies, and high-grade meningiomas have significant intratumor heterogeneity. Here we use spatial approaches to identify genomic, biochemical and cellular mechanisms linking intratumor heterogeneity to the molecular, temporal and spatial evolution of high-grade meningiomas. We show that divergent intratumor gene and protein expression programs distinguish high-grade meningiomas that are otherwise grouped together by current classification systems. Analyses of matched pairs of primary and recurrent meningiomas reveal spatial expansion of subclonal copy number variants associated with treatment resistance. Multiplexed sequential immunofluorescence and deconvolution of meningioma spatial transcriptomes using cell types from single-cell RNA sequencing show decreased immune infiltration, decreased MAPK signaling, increased PI3K-AKT signaling and increased cell proliferation, which are associated with meningioma recurrence. To translate these findings to preclinical models, we use CRISPR interference and lineage tracing approaches to identify combination therapies that target intratumor heterogeneity in meningioma cell co-cultures.

Genomic mosaicism describes the phenomenon where some but not all cells within a tissue harbor unique genetic mutations. Traditionally, research focused on the impact of genomic mosaicism on clinical phenotype-motivated by its involvement in cancers and overgrowth syndromes. More recently, we increasingly shifted towards the plethora of neutral mosaic variants that can act as recorders of cellular lineage and environmental exposures. Here, we summarize the current state of the field of genomic mosaicism research with a special emphasis on our current understanding of this phenomenon in brain development and homeostasis. Although the field of genomic mosaicism has a rich history, technological advances in the last decade have changed our approaches and greatly improved our knowledge. We will provide current definitions and an overview of contemporary detection approaches for genomic mosaicism. Finally, we will discuss the impact and utility of genomic mosaicism.

BACKGROUND: The colonization of land and the diversification of terrestrial plants is intimately linked to the evolutionary history of their symbiotic fungal partners. Extant representatives of these fungal lineages include mutualistic plant symbionts, the arbuscular mycorrhizal (AM) fungi in Glomeromycota and fine root endophytes in Endogonales (Mucoromycota), as well as fungi with saprotrophic, pathogenic and endophytic lifestyles. These fungal groups separate into three monophyletic lineages but their evolutionary relationships remain enigmatic confounding ancestral reconstructions. Their taxonomic ranks are currently fluid. RESULTS: In this study, we recognize these three monophyletic linages as phyla, and use a balanced taxon sampling and broad taxonomic representation for phylogenomic analysis that rejects a hard polytomy and resolves Glomeromycota as sister to a clade composed of Mucoromycota and Mortierellomycota. Low copy numbers of genes associated with plant cell wall degradation could not be assigned to the transition to a plant symbiotic lifestyle but appears to be an ancestral phylogenetic signal. Both plant symbiotic lineages, Glomeromycota and Endogonales, lack numerous thiamine metabolism genes but the lack of fatty acid synthesis genes is specific to AM fungi. Many genes previously thought to be missing specifically in Glomeromycota are either missing in all analyzed phyla, or in some cases, are actually present in some of the analyzed AM fungal lineages, e.g. the high affinity phosphorus transporter Pho89. CONCLUSION: Based on a broad taxon sampling of fungal genomes we present a well-supported phylogeny for AM fungi and their sister lineages. We show that among these lineages, two independent evolutionary transitions to mutualistic plant symbiosis happened in a genomic background profoundly different from that known from the emergence of ectomycorrhizal fungi in Dikarya. These results call for further reevaluation of genomic signatures associated with plant symbiosis.

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

BackgroundInfection prevention (IP) measures are designed to mitigate the transmission of pathogens in healthcare. Using large-scale viral genomic and social network analyses, we determined if IP measures used during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were adequate in protecting healthcare workers (HCWs) and patients from acquiring SARS-CoV-2.MethodsWe performed retrospective cross-sectional analyses of viral genomics from all available SARS-CoV-2 viral samples collected at UC San Diego Health and social network analysis using the electronic medical record to derive temporospatial overlap of infections among related viromes and supplemented with contact tracing data. The outcome measure was any instance of healthcare transmission, defined as cases with closely related viral genomes and epidemiological connection within the healthcare setting during the infection window. Between November 2020 through January 2022, 12 933 viral genomes were obtained from 35 666 patients and HCWs.ResultsAmong 5112 SARS-CoV-2 viral samples sequenced from the second and third waves of SARS-CoV-2 (pre-Omicron), 291 pairs were derived from persons with a plausible healthcare overlap. Of these, 34 pairs (12%) were phylogenetically linked: 19 attributable to household and 14 to healthcare transmission. During the Omicron wave, 2106 contact pairs among 7821 sequences resulted in 120 (6%) related pairs among 32 clusters, of which 10 were consistent with healthcare transmission. Transmission was more likely to occur in shared spaces in the older hospital compared with the newer hospital (2.54 vs 0.63 transmission events per 1000 admissions, P < .001).ConclusionsIP strategies were effective at identifying and preventing healthcare SARS-CoV-2 transmission.

Tanoak (Notholithocarpus densiflorus) is an evergreen tree in the Fagaceae family found in California and southern Oregon. Historically, tanoak acorns were an important food source for Native American tribes, and the bark was used extensively in the leather tanning process. Long considered a disjunct relictual element of the Asian stone oaks (Lithocarpus spp.), phylogenetic analysis has determined that the tanoak is an example of convergent evolution. Tanoaks are deeply divergent from oaks (Quercus) of the Pacific Northwest and comprise a new genus with a single species. These trees are highly susceptible to sudden oak death (SOD), a plant pathogen (Phytophthora ramorum) that has caused widespread deaths of tanoaks. In this study, we set out to assemble the genome and perform comparative studies among a number of individuals that demonstrated varying levels of susceptibility to SOD. First, we sequenced and de novo assembled a draft reference genome of N. densiflorus using cobarcoded library processing methods and an MGI DNBSEQ-G400 sequencer. To increase the contiguity of the final assembly, we also sequenced Oxford Nanopore long reads to 30× coverage. To our knowledge, the draft genome reported here is one of the more contiguous and complete genomes of a tree species published to date, with a contig N50 of ∼1.2 Mb, a scaffold N50 of ∼2.1 Mb, and a complete gene score of 95.5% through BUSCO analysis. In addition, we sequenced 11 genetically distinct individuals and mapped these onto the draft reference genome, enabling the discovery of almost 25 million single nucleotide polymorphisms and ∼4.4 million small insertions and deletions. Finally, using cobarcoded data, we were able to generate a complete haplotype coverage of all 11 genomes.

Whitebark pine (WBP, Pinus albicaulis) is a white pine of subalpine regions in the Western contiguous United States and Canada. WBP has become critically threatened throughout a significant part of its natural range due to mortality from the introduced fungal pathogen white pine blister rust (WPBR, Cronartium ribicola) and additional threats from mountain pine beetle (Dendroctonus ponderosae), wildfire, and maladaptation due to changing climate. Vast acreages of WBP have suffered nearly complete mortality. Genomic technologies can contribute to a faster, more cost-effective approach to the traditional practices of identifying disease-resistant, climate-adapted seed sources for restoration. With deep-coverage Illumina short reads of haploid megagametophyte tissue and Oxford Nanopore long reads of diploid needle tissue, followed by a hybrid, multistep assembly approach, we produced a final assembly containing 27.6 Gb of sequence in 92,740 contigs (N50 537,007 bp) and 34,716 scaffolds (N50 2.0 Gb). Approximately 87.2% (24.0 Gb) of total sequence was placed on the 12 WBP chromosomes. Annotation yielded 25,362 protein-coding genes, and over 77% of the genome was characterized as repeats. WBP has demonstrated the greatest variation in resistance to WPBR among the North American white pines. Candidate genes for quantitative resistance include disease resistance genes known as nucleotide-binding leucine-rich repeat receptors (NLRs). A combination of protein domain alignments and direct genome scanning was employed to fully describe the 3 subclasses of NLRs. Our high-quality reference sequence and annotation provide a marked improvement in NLR identification compared to previous assessments that leveraged de novo-assembled transcriptomes.

The Alliance of Genome Resources (Alliance) is an extensible coalition of knowledge bases focused on the genetics and genomics of intensively studied model organisms. The Alliance is organized as individual knowledge centers with strong connections to their research communities and a centralized software infrastructure, discussed here. Model organisms currently represented in the Alliance are budding yeast, Caenorhabditis elegans, Drosophila, zebrafish, frog, laboratory mouse, laboratory rat, and the Gene Ontology Consortium. The project is in a rapid development phase to harmonize knowledge, store it, analyze it, and present it to the community through a web portal, direct downloads, and application programming interfaces (APIs). Here, we focus on developments over the last 2 years. Specifically, we added and enhanced tools for browsing the genome (JBrowse), downloading sequences, mining complex data (AllianceMine), visualizing pathways, full-text searching of the literature (Textpresso), and sequence similarity searching (SequenceServer). We enhanced existing interactive data tables and added an interactive table of paralogs to complement our representation of orthology. To support individual model organism communities, we implemented species-specific landing pages and will add disease-specific portals soon; in addition, we support a common community forum implemented in Discourse software. We describe our progress toward a central persistent database to support curation, the data modeling that underpins harmonization, and progress toward a state-of-the-art literature curation system with integrated artificial intelligence and machine learning (AI/ML).

Vitamin A deficiency remains prevalent on a global scale, including in regions where maize constitutes a high percentage of human diets. One solution for alleviating this deficiency has been to increase grain concentrations of provitamin A carotenoids in maize (Zea mays ssp. mays L.)-an example of biofortification. The International Maize and Wheat Improvement Center (CIMMYT) developed a Carotenoid Association Mapping panel of 380 inbred lines adapted to tropical and subtropical environments that have varying grain concentrations of provitamin A and other health-beneficial carotenoids. Several major genes have been identified for these traits, 2 of which have particularly been leveraged in marker-assisted selection. This project assesses the predictive ability of several genomic prediction strategies for maize grain carotenoid traits within and between 4 environments in Mexico. Ridge Regression-Best Linear Unbiased Prediction, Elastic Net, and Reproducing Kernel Hilbert Spaces had high predictive abilities for all tested traits (β-carotene, β-cryptoxanthin, provitamin A, lutein, and zeaxanthin) and outperformed Least Absolute Shrinkage and Selection Operator. Furthermore, predictive abilities were higher when using genome-wide markers rather than only the markers proximal to 2 or 13 genes. These findings suggest that genomic prediction models using genome-wide markers (and assuming equal variance of marker effects) are worthwhile for these traits even though key genes have already been identified, especially if breeding for additional grain carotenoid traits alongside β-carotene. Predictive ability was maintained for all traits except lutein in between-environment prediction. The TASSEL (Trait Analysis by aSSociation, Evolution, and Linkage) Genomic Selection plugin performed as well as other more computationally intensive methods for within-environment prediction. The findings observed herein indicate the utility of genomic prediction methods for these traits and could inform their resource-efficient implementation in biofortification breeding programs.

The coppery titi monkey (Plecturocebus cupreus) is an emerging nonhuman primate model system for behavioral and neurobiological research. At the same time, the almost entire absence of genomic resources for the species has hampered insights into the genetic underpinnings of the phenotypic traits of interest. To facilitate future genotype-to-phenotype studies, we here present a high-quality, fully annotated de novo genome assembly for the species with chromosome-length scaffolds spanning the autosomes and chromosome X (scaffold N50 = 130.8 Mb), constructed using data obtained from several orthologous short- and long-read sequencing and scaffolding techniques. With a base-level accuracy of ∼99.99% in chromosome-length scaffolds as well as benchmarking universal single-copy ortholog and k-mer completeness scores of >99.0% and 95.1% at the genome level, this assembly represents one of the most complete Pitheciidae genomes to date, making it an invaluable resource for comparative evolutionary genomics research to improve our understanding of lineage-specific changes underlying adaptive traits as well as deleterious mutations associated with disease.

Health equity is the state in which everyone has fair and just opportunities to attain their highest level of health. The field of human genomics has fallen short in increasing health equity, largely because the diversity of the human population has been inadequately reflected among participants of genomics research. This lack of diversity leads to disparities that can have scientific and clinical consequences. Achieving health equity related to genomics will require greater effort in addressing inequities within the field. As part of the commitment of the National Human Genome Research Institute (NHGRI) to advancing health equity, it convened experts in genomics and health equity research to make recommendations and performed a review of current literature to identify the landscape of gaps and opportunities at the interface between human genomics and health equity research. This Perspective describes these findings and examines health equity within the context of human genomics and genomic medicine.

Despite numerous studies in the field of dementia and Alzheimer's disease (AD), a comprehensive understanding of this devastating disease remains elusive. Bulk transcriptomics have provided insights into the underlying genetic factors at a high level. Subsequent technological advancements have focused on single-cell omics, encompassing techniques such as single-cell RNA sequencing and epigenomics, enabling the capture of RNA transcripts and chromatin states at a single cell or nucleus resolution. Furthermore, the emergence of spatial omics has allowed the study of gene responses in the vicinity of amyloid beta plaques or across various brain regions. With the vast amount of data generated, utilizing gene regulatory networks to comprehensively study this disease has become essential. This review delves into some techniques employed in the field of AD, explores the discoveries made using these techniques, and provides insights into the future of the field.

Plants rely on Nucleotide-binding, Leucine-rich repeat Receptors (NLRs) for pathogen recognition. Highly variable NLRs (hvNLRs) show remarkable intraspecies diversity, while their low-variability paralogs (non-hvNLRs) are conserved between ecotypes. At a population level, hvNLRs provide new pathogen-recognition specificities, but the association between allelic diversity and genomic and epigenomic features has not been established. Our investigation of NLRs in Arabidopsis Col-0 has revealed that hvNLRs show higher expression, less gene body cytosine methylation, and closer proximity to transposable elements than non-hvNLRs. hvNLRs show elevated synonymous and nonsynonymous nucleotide diversity and are in chromatin states associated with an increased probability of mutation. Diversifying selection maintains variability at a subset of codons of hvNLRs, while purifying selection maintains conservation at non-hvNLRs. How these features are established and maintained, and whether they contribute to the observed diversity of hvNLRs is key to understanding the evolution of plant innate immune receptors.

Phylogenetic trees provide a framework for organizing evolutionary histories across the tree of life and aid downstream comparative analyses such as metagenomic identification. Methods that rely on single-marker genes such as 16S rRNA have produced trees of limited accuracy with hundreds of thousands of organisms, whereas methods that use genome-wide data are not scalable to large numbers of genomes. We introduce updating trees using divide-and-conquer (uDance), a method that enables updatable genome-wide inference using a divide-and-conquer strategy that refines different parts of the tree independently and can build off of existing trees, with high accuracy and scalability. With uDance, we infer a species tree of roughly 200,000 genomes using 387 marker genes, totaling 42.5 billion amino acid residues.