Whole-genome Sequencing Datasets Research Articles

Targeted sputum sequencing for rapid and broad drug resistance of Mycobacterium tuberculosis.

Rapid detection of drug resistance in Mycobacterium tuberculosis (Mtb) from clinical samples facilitates the timely provision of optimal treatment regimens for tuberculosis (TB) patients. In November, 2023, the WHO released its second catalogue of resistance-conferring mutations in Mtb. Utilizing this information, we developed a single 17-plex PCR assay covering 16 key resistance genes and modified thermo-protection buffer to amplify 30 kbp DNA directly from sputum samples for nanopore sequencing. We implemented our protocol using rapid barcoding for sequencing with both a Flongle and a MinION flow cell. The single multiplex PCR assay was successfully validated on clinical sputum samples using the thermo-protection buffer. The protocol was applied to both Flongle and MinION flow cells, analyzing 12 and 40 samples, respectively. Data analysis suggested that optimal performance could be achieved by processing 6 and 12 samples with similar microscope staining scores on these two platforms. This approach facilitated rapid antimicrobial resistance (AMR) predictions directly from sputum on the day of collection or the following day, with a cost of less than $35 per sample. Compared to AMR predictions based on whole-genome sequencing (WGS) using Mykrobe and TBProfiler, our amplicon-based analysis tool, ARapidTb, demonstrated superior resistance detection capabilities. When analyzing publicly available nanopore WGS datasets for 442 isolates, ARapidTb achieved agreement rates of 95.8% and 98.0%, outperforming Mykrobe (89.4% and 98.3%) and TBProfiler (75.6% and 89.8%). Our study significantly reduces the time required for drug resistance detection, enabling quicker initiation of appropriate treatments and potentially improving patient outcomes and TB management.

Blood DNA virome associates with autoimmune diseases and COVID-19

Aberrant immune responses to viral pathogens contribute to pathogenesis, but our understanding of pathological immune responses caused by viruses within the human virome, especially at a population scale, remains limited. We analyzed whole-genome sequencing datasets of 6,321 Japanese individuals, including patients with autoimmune diseases (psoriasis vulgaris, rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), pulmonary alveolar proteinosis (PAP) or multiple sclerosis) and coronavirus disease 2019 (COVID-19), or healthy controls. We systematically quantified two constituents of the blood DNA virome, endogenous HHV-6 (eHHV-6) and anellovirus. Participants with eHHV-6B had higher risks of SLE and PAP; the former was validated in All of Us. eHHV-6B-positivity and high SLE disease activity index scores had strong correlations. Genome-wide association study and long-read sequencing mapped the integration of the HHV-6B genome to a locus on chromosome 22q. Epitope mapping and single-cell RNA sequencing revealed distinctive immune induction by eHHV-6B in patients with SLE. In addition, high anellovirus load correlated strongly with SLE, RA and COVID-19 status. Our analyses unveil relationships between the human virome and autoimmune and infectious diseases.

Hierarchical population genetic structure and signatures of adaptation in Lates calcarifer

Context Lates calcarifer is a widespread Indo-Pacific fish that is important in aquaculture, recreational and commercial fisheries. Genetic divergences from different data sources and sampling schemes have been reported. Aims To conduct phylogenetic and population genetic analyses from a geographically and phylogenetically representative data set to identify hierarchical divisions within L. calcarifer. We further test the evolutionary significance of genetic units in terms of signatures of adaptation. Methods Using a whole-genome sequence data set of 61 fish, including an outgroup, we conducted phylogenetic and population genetic analyses. We also generated measures of fixation index (Fst), nucleotide diversity (π) and Tajima’s D (D). Key results We identified three main lineages of L. calcarifer, corresponding to the Indian subcontinent, South-east Asia and Australasia. Subdivision within each of the three main lineages was also identified and characterised. Adaptively significant differences are indicated within and among the three main lineages. Conclusions L. calcarifer exhibits genetic divergences at different levels that originate before and during the Pleistocene. These divergences are associated with adaptive divergence but unclear phenotypic changes. Implications This study has highlighted the need for comprehensive sampling and integrative study of genotypes and phenotypes across the range of L. calcarifer.

Comprehensive genome analysis and variant detection at scale using DRAGEN.

Research and medical genomics require comprehensive, scalable methods for the discovery of novel disease targets, evolutionary drivers and genetic markers with clinical significance. This necessitates a framework to identify all types of variants independent of their size or location. Here we present DRAGEN, which uses multigenome mapping with pangenome references, hardware acceleration and machine learning-based variant detection to provide insights into individual genomes, with ~30 min of computation time from raw reads to variant detection. DRAGEN outperforms current state-of-the-art methods in speed and accuracy across all variant types (single-nucleotide variations, insertions or deletions, short tandem repeats, structural variations and copy number variations) and incorporates specialized methods for analysis of medically relevant genes. We demonstrate the performance of DRAGEN across 3,202 whole-genome sequencing datasets by generating fully genotyped multisample variant call format files and demonstrate its scalability, accuracy and innovation to further advance the integration of comprehensive genomics. Overall, DRAGEN marks a major milestone in sequencing data analysis and will provide insights across various diseases, including Mendelian and rare diseases, with a highly comprehensive and scalable platform.

A genome-based survey of invasive pneumococci in Norway over four decades reveals lineage-specific responses to vaccination

BackgroundStreptococcus pneumoniae is a major cause of mortality globally. The introduction of pneumococcal conjugate vaccines (PCVs) has reduced the incidence of the targeted serotypes significantly, but expansion of non-targeted serotypes, serotype replacement, and incomplete vaccine-targeting contribute to pneumococcal disease in the vaccine era. Here, we characterize the changing population genetic landscape of S. pneumoniae in Norway over a 41-year period (1982–2022).MethodsSince 2018, all cases of invasive pneumococcal disease have undergone whole-genome sequencing (WGS) at the Norwegian Institute of Public Health. In order to characterize the changing population over time, historical isolates were re-cultured and sequenced, resulting in a historical WGS dataset. Isolates were assigned to global pneumococcal sequence clusters (GPSCs) using PathogenWatch and assigned to serotypes using in silico (SeroBA) and in vitro methods (Quellung reaction). Temporal phylogenetic analyses were performed on GPSCs of particular interest.ResultsThe availability of WGS data allowed us to study capsular variation at the level of individual lineages. We detect highly divergent fates for different GPSCs following the introduction of PCVs. For two out of eight major GPSCs, we identified multiple instances of serotype switching from vaccine types to non-vaccine types. Dating analyses suggest that most instances of serotype switching predated the introduction of PCVs, but expansion occurred after their introduction. Furthermore, selection for penicillin non-susceptibility was not a driving force for the changing serotype distribution within the GPSCs over time.ConclusionsPCVs have been major shapers of the Norwegian disease-causing pneumococcal population, both at the level of serotype distributions and the underlying lineage dynamics. Overall, the introduction of PCVs has reduced the incidence of invasive disease. However, some GPSCs initially dominated by vaccine types escaped the effect of vaccination through expansion of non-vaccine serotypes. Close monitoring of circulating lineages and serotypes will be key for ensuring optimal vaccination coverage going forward.

Large-scale analysis of whole genome sequencing data from formalin-fixed paraffin-embedded cancer specimens demonstrates preservation of clinical utility

Whole genome sequencing (WGS) provides comprehensive, individualised cancer genomic information. However, routine tumour biopsies are formalin-fixed and paraffin-embedded (FFPE), damaging DNA, historically limiting their use in WGS. Here we analyse FFPE cancer WGS datasets from England’s 100,000 Genomes Project, comparing 578 FFPE samples with 11,014 fresh frozen (FF) samples across multiple tumour types. We use an approach that characterises rather than discards artefacts. We identify three artefactual signatures, including one known (SBS57) and two previously uncharacterised (SBS FFPE, ID FFPE), and develop an “FFPEImpact” score that quantifies sample artefacts. Despite inferior sequencing quality, FFPE-derived data identifies clinically-actionable variants, mutational signatures and permits algorithmic stratification. Matched FF/FFPE validation cohorts shows good concordance while acknowledging SBS, ID and copy-number artefacts. While FF-derived WGS data remains the gold standard, FFPE-samples can be used for WGS if required, using analytical advancements developed here, potentially democratising whole cancer genomics to many.

Comprehensive analysis of microbial content in whole-genome sequencing samples from The Cancer Genome Atlas project.

Analysis of microbial content in 5,734 whole-genome sequencing samples from TCGA yields a comprehensive new resource for investigating the role of microbes in cancer.

Phylogenetic insights into the Salicaceae: The evolution of willows and beyond

The Salicaceae includes approximately 54 genera and over 1,400 species with a cosmopolitan distribution. Members of the family are well-known for their diverse secondary plant metabolites, and they play crucial roles in tropical and temperate forest ecosystems. Phylogenetic reconstruction of the Salicaceae has been historically challenging due to the limitations of molecular markers and the extensive history of hybridization and polyploidy within the family. Our study employs whole-genome sequencing of 74 species to generate an extensive phylogeny of the Salicaceae. We generated two RAD-Seq enriched whole-genome sequence datasets and extracted two additional gene sets corresponding to the universal Angiosperms353 and Salicaceae-specific targeted-capture arrays. We reconstructed maximum likelihood-based molecular phylogenies using supermatrix and coalescent-based supertree approaches. Our fossil-calibrated phylogeny estimates that the Salicaceae originated around 128 million years ago and unravels the complex taxonomic relationships within the family. Our findings confirm the non-monophyly of the subgenus Salix s.l. and further support the merging of subgenera Chamaetia and Vetrix, both of which exhibit intricate patterns within and among different sections. Overall, our study not only enhances our understanding of the evolution of the Salicaceae, but also provides valuable insights into the complex relationships within the family.

Genetic characterization of Tibetan pigs adapted to high altitude under natural selection based on a large whole-genome dataset

The Qinghai-Tibet Plateau is a valuable genetic resource pool, and the high-altitude adaptation of Tibetan pigs is a classic example of the adaptive evolution of domestic animals. Here, we report the presence of Darwinian positive selection signatures in Tibetan pigs (TBPs) using 348 genome-wide datasets (127 whole-genome sequence datasets (WGSs) and 221 whole-genome single-nucleotide polymorphism (SNP) chip datasets). We characterized a high-confidence list of genetic signatures related response to high-altitude adaptation in Tibetan pigs, including 4,598 candidate SNPs and 131 candidate genes. Functional annotation and enrichment analysis revealed that 131 candidate genes are related to multiple systems and organs in Tibetan pigs. Notably, eight of the top ten novel genes, RALB, NBEA, LIFR, CLEC17A, PRIM2, CDH7, GK5 and FAM83B, were highlighted and associated with improved adaptive heart functions in Tibetan pigs high-altitude adaptation. Moreover, genome-wide association analysis revealed that 29 SNPs were involved in 13 candidate genes associated with at least one adaptive trait. In particular, among the top ten candidate genes, CLEC17A is related to a reduction in hemoglobin (HGB) in Tibetan pigs. Overall, our study provides a robust SNP/gene list involving genetic adaptation for Tibetan pig high-altitude adaptation, and it will be a valuable resource for future Tibetan pig studies.

Detection and characterisation of a sixth Candida auris clade in Singapore: a genomic and phenotypic study

The emerging fungal pathogen Candida auris poses a serious threat to global public health due to its worldwide distribution, multidrug resistance, high transmissibility, propensity to cause outbreaks, and high mortality. We aimed to characterise three unusual Cauris isolates detected in Singapore, and to determine whether they constitute a novel clade distinct from all previously known Cauris clades (I-V). In this genotypic and phenotypic study, we characterised three Cauris clinical isolates, which were cultured from epidemiologically unlinked inpatients at a large tertiary hospital in Singapore. The index isolate was detected in April, 2023. We performed whole-genome sequencing (WGS) and obtained hybrid assemblies of these Cauris isolates. The complete genomes were compared with representative genomes of all known Cauris clades. To provide a global context, 3651international WGS data from the National Center for Biotechnology Information (NCBI) database were included in a high-resolution single nucleotide polymorphism (SNP) analysis. Antifungal susceptibility testing was done and antifungal resistance genes, mating-type locus, and chromosomal rearrangements were characterised from the WGS data of the three investigated isolates. We further implemented Bayesian logistic regression models to classify isolates into known clades and simulate the automatic detection of isolates belonging to novel clades as their WGS data became available. The three investigated isolates were separated by at least 37 000SNPs (range 37 000-236 900) from all existing Cauris clades. These isolates had opposite mating-type allele and different chromosomal rearrangements when compared with their closest clade IV relatives. The isolates were susceptible to all tested antifungals. Therefore, we propose that these isolates represent a new clade of Cauris, clade VI. Furthermore, an independent WGS dataset from Bangladesh, accessed via the NCBI Sequence Read Archive, was found to belong to this new clade. As a proof-of-concept, our Bayesian logistic regression model was able to flag these outlier genomes as a potential new clade. The discovery of a new Cauris clade in Singapore and Bangladesh in the Indomalayan zone, showing a close relationship to cladeIV members most commonly found in South America, highlights the unknown genetic diversity and origin of Cauris, particularly in under-resourced regions. Active surveillance in clinical settings, along with effective sequencing strategies and downstream analysis, will be essential in the identification of novel strains, tracking of transmission, and containment of adverse clinical effects of Cauris infections. Duke-NUS Academic Medical Center Nurturing Clinician Researcher Scheme, and the Genedant-GIS Innovation Program.

Abstract PR04: Characterization of an essential MYC enhancer targeted by focal genomic alterations in diffuse large B-cell lymphoma

Abstract We sought to identify mechanisms that activate MYC expression in germinal center B cell-(GCB) diffuse large B-cell lymphomas (DLBCL) in the absence of MYC rearrangement. High-throughput CRISPR-interference screens in MYC-rearranged (n=4) and non-MYC-rearranged (n=2) GCB-DLBCL cell lines revealed a distal enhancer complex 436 kb downstream of MYC, GME-1, that was uniquely essential in non-rearranged (MYC-intact) cell lines. CRISPR-interference studies confirmed growth inhibition and MYC downregulation upon GME-1 repression in 4 DLBCL cell lines. ChIP-Seq showed that GME-1 subunits were bound by OCT2, OCA-B, and MEF2B, which are known to activate germinal center-specific enhancers, and knockdown of the corresponding genes reduced MYC expression. GME-1 subunits showed GCB-specific acetylation and accessibility across normal human B cell populations in public chromatin datasets. The mouse ortholog of GME-1 showed germinal center B cell-specific accessibility. GME-1 was strongly acetylated in MYC-intact but not MYC-rearranged GCB-DLBCL cell lines and patient biopsies. Hi-C revealed significant looping of GME-1 to the MYC promoter in MYC protein+, MYC-intact DLBCL biopsies (n=2), but not MYC-rearranged DLBCL (n=2). We used sequence conservation and chromatin accessibility data to define four GME-1 subunits (195A/B and196A/B), which were cloned into luciferase enhancer reporter constructs and compared to two subunits of the BCL6 distal super-enhancer complex that had previously been identified as regulated by the OCT2/OCA-B/MEF2B complex. GME-1 subunit 195B was the only strongly transcription-activating element based on luciferase assays across three MYC-intact cells lines, where it showed activity comparable to BCL6 enhancers. In contrast, GME-1 enhancers were minimally active in reporter assays performed in two MYC-rearranged GCB-DLBCL cell lines. Deletion of a conserved OCT2 binding site or knockdown of the POU2F2 and POU2AF1 genes reduced activity of GME-1. Thus GME-1 trans-regulation is divergent from that of previously characterized GCB enhancers, despite shared dependency on the OCT2 ternary complex. Whole-genome sequencing (WGS) revealed that the GME-1 dependent cell line SUDHL5 bears a 176bp tandem duplication within GME-1 195B. This altered enhancer showed stronger luciferase reporter activity across three MYC-intact cell lines. Published WGS datasets showed isolated genomic tandem copy gains of GME-1 in 2/49 biopsies from recurrent/refractory DLBCL and 1/93 unselected DLBCL. In a cohort of 18 DLBCL with the high-risk DZSig gene expression signature, GME-1 amplification was seen in two biopsies with concurrent deletion of the PVT1 promoter (PVT1-P) and no inter-chromosomal MYC locus rearrangement. CRISPRi showed that PVT1-P repression reduced growth and MYC expression in GME-1-dependent DLBCL, but not in cell lines where rearrangements removed PVT-P from its position in cis with the MYC gene. Our findings identify GME-1 as an activator of MYC expression and target of rare but recurrent genomic copy gains in high-risk DLBCL. Citation Format: Aishwarya Gurumurthy, Ashwin R. Iyer, Shih-Chun A. Chu, Marcin P. Cieslik, Russell J.H. Ryan. Characterization of an essential MYC enhancer targeted by focal genomic alterations in diffuse large B-cell lymphoma [abstract]. In: Proceedings of the Fourth AACR International Meeting on Advances in Malignant Lymphoma: Maximizing the Basic-Translational Interface for Clinical Application; 2024 Jun 19-22; Philadelphia, PA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5(3_Suppl):Abstract nr PR04.

MDB-19. THE 3D CHROMATIN LANDSCAPE OF MEDULLOBLASTOMA

Abstract BACKGROUND Medulloblastoma (MB) is a highly malignant childhood cerebellar tumor comprised of four molecularly and clinically distinct subgroups. Sporadic yet subgroup-specific genetic and epigenetic landscapes suggest that higher-order chromatin topology may contribute to distinct subgroup identities and disease biology. Herein, we investigated the 3D chromatin landscape of MB by performing genome-wide chromosome conformation capture (Hi-C) across molecular subgroups using a cohort of n=24 patient-derived xenografts and primary tumor specimens, aiming to elucidate regulatory mechanisms facilitated by genome organization. METHODS Integrative analyses were adapted to incorporate a wide variety of sample-paired datasets. Chromatin contact matrices generated from Hi-C allowed for the mapping of active/inactive compartments (A/B compartments), topologically associated domains (TADs), and distal pairwise chromatin contacts (loops). Topological insights of chromatin architecture were complemented with whole-genome sequencing, RNA-seq, ATAC-seq, DNA methylation, CTCF and histone modification (H3K27ac/H3K27me3) ChIP-seq datasets to dissect mechanisms of gene regulation. RESULTS Unsupervised analysis revealed that chromatin compartmentalization is subgroup stratified. Gene loci contained in subgroup-unique active compartments correspondingly exhibited subgroup-specific chromatin contact patterns, adopted open chromatin conformations, and remained transcriptionally active. As an example, LIN28B resides within a Group 3-specific ‘A’ compartment where its local topology displays higher complexity compared to that of other subgroups. This consequentially facilitates a Group 3-unique loop connecting the LIN28B promoter with a distal enhancer, resulting in subgroup-specific transcriptional upregulation. Targeted displacement of CTCF that anchors and stabilizes chromatin looping at the LIN28B locus was sufficient to alter its transcriptional activity. Using similar lines of investigation, mechanistic insights into the topological determinants of known enhancer-hijacking events, including GFI1, GFI1B and PRDM6, were resolved. CONCLUSIONS Pioneering this integrative approach centered on comprehensive Hi-C maps, our study provides a high-resolution blueprint of the 3D chromatin landscape defining MB subgroups, informing the mechanistic basis of recurrent driver gene activation, and disclosing putative subgroup-specific vulnerabilities.

FinaleToolkit: Accelerating Cell-Free DNA Fragmentation Analysis with a High-Speed Computational Toolkit.

Cell-free DNA (cfDNA) fragmentation pattern represents a promising non-invasive biomarker for disease diagnosis and prognosis. Numerous fragmentation features, such as end motif and window protection score (WPS), have been characterized in cfDNA genomic sequencing. However, the analytical tools developed in these studies are often not released to the liquid biopsy community or are inefficient for genome-wide analysis in large datasets. To address this gap, we have developed FinaleToolkit, a fast and memory efficient Python package designed to generate comprehensive fragmentation features from large cfDNA genomic sequencing data. For instance, FinaleToolkit can generate genome-wide WPS features from a ~100X cfDNA whole-genome sequencing (WGS) dataset in 1.2 hours using 16 CPU cores, offering up to a ~50-fold increase in processing speed compared to original implementations in the same dataset. We have benchmarked FinaleToolkit against original studies or implementations where possible, confirming its efficacy. Furthermore, FinaleToolkit enabled the genome-wide analysis of fragmentation patterns over arbitrary genomic intervals, significantly boosting the performance for cancer early detection. FinaleToolkit is open source and thoroughly documented with both command line interface and Python application programming interface (API) to facilitate its widespread adoption and use within the research community: https://github.com/epifluidlab/FinaleToolkit.

Data Harmonization Guidelines to Combine Multi-platform Genomic Data from Admixed Populations and Boost Power in Genome-Wide Association Studies.

Data harmonization involves combining data from multiple independent sources and processing the data to produce one uniform dataset. Merging separate genotypes or whole-genome sequencing datasets has been proposed as a strategy to increase the statistical power of association tests by increasing the effective sample size. However, data harmonization is not a widely adopted strategy due to the difficulties with merging data (including confounding produced by batch effects and population stratification). Detailed data harmonization protocols are scarce and are often conflicting. Moreover, data harmonization protocols that accommodate samples of admixed ancestry are practically non-existent. Existing data harmonization procedures must be modified to ensure the heterogeneous ancestry of admixed individuals is incorporated into additional downstream analyses without confounding results. Here, we propose a set of guidelines for merging multi-platform genetic data from admixed samples that can be adopted by any investigator with elementary bioinformatics experience. We have applied these guidelines to aggregate 1544 tuberculosis (TB) case-control samples from six separate in-house datasets and conducted a genome-wide association study (GWAS) of TB susceptibility. The GWAS performed on the merged dataset had improved power over analyzing the datasets individually and produced summary statistics free from bias introduced by batch effects and population stratification. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Processing separate datasets comprising array genotype data Alternate Protocol 1: Processing separate datasets comprising array genotype and whole-genome sequencing data Alternate Protocol 2: Performing imputation using a local reference panel Basic Protocol 2: Merging separate datasets Basic Protocol 3: Ancestry inference using ADMIXTURE and RFMix Basic Protocol 4: Batch effect correction using pseudo-case-control comparisons.

Phylogenomic analyses revealed widely occurring hybridization events across Elsholtzieae (Lamiaceae)

Obtaining a robust phylogeny proves challenging due to the intricate evolutionary history of species, where processes such as hybridization and incomplete lineage sorting can introduce conflicting signals, thereby complicating phylogenetic inference. In this study, we conducted comprehensive sampling of Elsholtzieae, with a particular focus on its largest genus, Elsholtzia. We utilized 503 nuclear loci and complete plastome sequences obtained from 99 whole-genome sequencing datasets to elucidate the interspecific relationships within the Elsholtzieae. Additionally, we explored various sources of conflicts between gene trees and species trees. Fully supported backbone phylogenies were recovered, and the monophyly of Elsholtzia and Keiskea was not supported. Significant gene tree heterogeneity was observed at numerous nodes, particularly regarding the placement of Vuhuangia and the E. densa clade. Further investigations into potential causes of this discordance revealed that incomplete lineage sorting (ILS), coupled with hybridization events, has given rise to substantial gene tree discordance. Several species, represented by multiple samples, exhibited a closer association with geographical distribution rather than following a strictly monophyletic pattern in plastid trees, suggesting chloroplast capture within Elsholtzieae and providing evidence of hybridization. In conclusion, this study provides phylogenomic insights to untangle taxonomic problems in the tribe Elsholtzieae, especially the genus Elsholtzia.

PGPg_finder: A comprehensive and user-friendly pipeline for identifying plant growth-promoting genes in genomic and metagenomic data

Identifying and comparing plant growth-promoting traits (PGPT) within whole-genome and metagenomic sequencing data can significantly advance agricultural research and promote sustainable crop production. This study introduces PGPg_finder, a comprehensive pipeline designed to annotate and compare PGPT from both whole-genome and metagenome sequencing datasets. This pipeline utilizes direct sequence annotation alongside de novo assembly methods to accurately detect PGPT. By cross-referencing sequences from the PLaBAse database, it identifies and quantifies the presence of these genes within the original datasets, facilitating an intuitive comparison of the abundance and distribution of PGPT across various samples. We evaluated the performance of PGPg_finder by analyzing genomes from five rhizobacterial strains: Paenibacillus vini, Paenibacillus polymyxa, Fictibacillus sp., Brevibacillus agri, and Bacillus cereus, and also metagenomic samples from bulk soils subjected to forest-to-pasture conversion in the Amazon rainforest. The genomic workflow revealed several genes associated with substrate utilization, abiotic stress neutralization, phosphate solubilization, and iron acquisition. It also identified genes unique to specific lineages, including those associated with colonization and plant-derived substrate usage in P. polymyxa, quorum sensing response and biofilm formation in P. vini, heavy metal detoxification and nitrogen acquisition in B. agri, and spore production and neutralizing biotic stress in B. cereus. The strain Fictibacillus sp. presented several unique genes related to surface attachment, stress response, xenobiotic degradation, phosphate solubilization, and phytohormone production. The use of PGPg_finder highlights its potential to uncover novel inoculants and strains. The metagenomic workflow distinguished plant-growth promotion gene profiles between soils from the Amazon rainforest and pasture, with the latter showing a profile more aligned with simple carbohydrate consumption, abiotic stress tolerance, motility and chemotaxis, and phosphorus mineralization. Native forests exhibited a profile associated with the degradation of complex organic matter, oxidative stress tolerance, xenobiotic degradation, bactericidal activity, iron acquisition, and volatile pathways. These findings underscore the effectiveness and sensitivity of PGPg_finder in accurately identifying and comparing PGPT genes, highlighting both commonalities and variations across samples. The application of this pipeline has the potential to significantly facilitate the identification of plant growth-promoting microbes.

Decoding triancestral origins, archaic introgression, and natural selection in the Japanese population by whole-genome sequencing.

We generated Japanese Encyclopedia of Whole-Genome/Exome Sequencing Library (JEWEL), a high-depth whole-genome sequencing dataset comprising 3256 individuals from across Japan. Analysis of JEWEL revealed genetic characteristics of the Japanese population that were not discernible using microarray data. First, rare variant-based analysis revealed an unprecedented fine-scale genetic structure. Together with population genetics analysis, the present-day Japanese can be decomposed into three ancestral components. Second, we identified unreported loss-of-function (LoF) variants and observed that for specific genes, LoF variants appeared to be restricted to a more limited set of transcripts than would be expected by chance, with PTPRD as a notable example. Third, we identified 44 archaic segments linked to complex traits, including a Denisovan-derived segment at NKX6-1 associated with type 2 diabetes. Most of these segments are specific to East Asians. Fourth, we identified candidate genetic loci under recent natural selection. Overall, our work provided insights into genetic characteristics of the Japanese population.

Patterns recovered in phylogenomic analysis of Candida auris and close relatives implicate broad environmental flexibility in Candida/Clavispora clade yeasts.

Fungal pathogens commonly originate from benign or non-pathogenic strains living in the natural environment. The recently emerged human pathogen, Candida auris, is one example of a fungus believed to have originated in the environment and recently transitioned into a clinical setting. To date, however, there is limited evidence about the origins of this species in the natural environment and when it began associating with humans. One approach to overcome this gap is to reconstruct phylogenetic relationships between (1) strains isolated from clinical and non-clinical environments and (2) between species known to cause disease in humans and benign environmental saprobes. C. auris belongs to the Candida/Clavispora clade, a diverse group of 45 yeast species including human pathogens and environmental saprobes. We present a phylogenomic analysis of the Candida/Clavispora clade aimed at understanding the ecological breadth and evolutionary relationships between an expanded sample of environmentally and clinically isolated yeasts. To build a robust framework for investigating these relationships, we developed a whole-genome sequence dataset of 108 isolates representing 18 species, including four newly sequenced species and 18 environmentally isolated strains. Our phylogeny, based on 619 orthologous genes, shows environmentally isolated species and strains interspersed with clinically isolated counterparts, suggesting that there have been many transitions between humans and the natural environment in this clade. Our findings highlight the breadth of environments these yeasts inhabit and imply that many clinically isolated yeasts in this clade could just as easily live outside the human body in diverse natural environments and vice versa.

Comparison of structural variant callers for massive whole-genome sequence data

BackgroundDetecting structural variations (SVs) at the population level using next-generation sequencing (NGS) requires substantial computational resources and processing time. Here, we compared the performances of 11 SV callers: Delly, Manta, GridSS, Wham, Sniffles, Lumpy, SvABA, Canvas, CNVnator, MELT, and INSurVeyor. These SV callers have been recently published and have been widely employed for processing massive whole-genome sequencing datasets. We evaluated the accuracy, sequence depth, running time, and memory usage of the SV callers.ResultsNotably, several callers exhibited better calling performance for deletions than for duplications, inversions, and insertions. Among the SV callers, Manta identified deletion SVs with better performance and efficient computing resources, and both Manta and MELT demonstrated relatively good precision regarding calling insertions. We confirmed that the copy number variation callers, Canvas and CNVnator, exhibited better performance in identifying long duplications as they employ the read-depth approach. Finally, we also verified the genotypes inferred from each SV caller using a phased long-read assembly dataset, and Manta showed the highest concordance in terms of the deletions and insertions.ConclusionsOur findings provide a comprehensive understanding of the accuracy and computational efficiency of SV callers, thereby facilitating integrative analysis of SV profiles in diverse large-scale genomic datasets.

A revamped rat reference genome improves the discovery of genetic diversity in laboratory rats

The seventh iteration of the reference genome assembly for Rattus norvegicus-mRatBN7.2-corrects numerous misplaced segments and reduces base-level errors by approximately 9-fold and increases contiguity by 290-fold compared with its predecessor. Gene annotations are now more complete, improving the mapping precision of genomic, transcriptomic, and proteomics datasets. We jointly analyzed 163 short-read whole-genome sequencing datasets representing 120 laboratory rat strains and substrains using mRatBN7.2. We defined ∼20.0 million sequence variations, of which 18,700 are predicted to potentially impact the function of 6,677 genes. We also generated a new rat genetic map from 1,893 heterogeneous stock rats and annotated transcription start sites and alternative polyadenylation sites. The mRatBN7.2 assembly, along with the extensive analysis of genomic variations among rat strains, enhances our understanding of the rat genome, providing researchers with an expanded resource for studies involving rats.