BMC genomic data最新文献

Background: Bacterial infections pose a global health threat across clinical and community settings. Over the past decade, the alarming expansion of antimicrobial resistance (AMR) has progressively narrowed therapeutic options, particularly for healthcare-associated infections. This critical situation has been formally recognized by the World Health Organization as a major public health concern. Epidemiological studies have demonstrated that the dissemination of AMR is frequently mediated by specific high-risk bacterial lineages, often designated as "global clones" or "clonal complexes." Consequently, surveillance of these epidemic clones and elucidation of their pathogenic mechanisms and AMR acquisition pathways have become essential research priorities. The advent of whole genome sequencing has revolutionized these investigations, enabling comprehensive epidemiological tracking and detailed analysis of mobile genetic elements responsible for resistance gene transfer. However, despite the exponential increase in available bacterial genome sequences, significant challenges persist. Current genomic datasets often suffer from uneven representation of clinically relevant strains and inconsistent availability of accompanying metadata. These limitations create substantial obstacles for large-scale comparative studies and hinder effective surveillance efforts.

Description: This database represents a comprehensive genomic analysis of 98,950 Staphylococcus aureus isolates, a high-priority bacterial pathogen of global clinical significance. We provide detailed isolate characterization through several established typing schemes including multilocus sequence typing (MLST), clonal complex (CC) assignments, spa typing results, and core genome MLST (cgMLST) profiles. The dataset also documents the presence of CRISPR-Cas systems in these isolates. Beyond fundamental typing data, our resource incorporates the distribution of antimicrobial resistance determinants, virulence factors, and plasmid replicons. These systematically curated genomic features offer researchers valuable insights into isolate epidemiology, resistance mechanisms, and horizontal gene transfer patterns in this highly concerning pathogen.

Conclusion: This database is freely available under CC BY-NC-SA at https://doi.org/10.5281/zenodo.14833440 . The data provided enables researchers to identify optimal reference isolates for various genomic studies, supporting critical investigations into S. aureus epidemiology and antimicrobial resistance evolution. This resource will ultimately inform the development of more effective prevention and control measures against this high-priority pathogen.

Background: A great deal of previous research describes the impact of the maternal metabolic and genetic milieu on newborn adiposity outcomes. However, much of this research does not focus on all aspects of the problem simultaneously. Studies focusing on metabolic factors may not distinguish between maternal and fetal genetic pathways, while studies that do focus on these different genetic pathways may not incorporate metabolic information into effect estimates or variant classifications. In this paper, we introduce a novel multi-omics pipeline for maternal genetic variant selection and mediation effect testing that can handle all these pathways, and use it to investigate broad patterns in the effects of maternal genetic variants on newborn adiposity outcomes.

Results: A Bayesian network model is used to incorporate both metabolomic and genomic data into an initial filter for maternal variants likely to affect newborn adiposity outcomes through a direct maternal genetic effect, an indirect fetal genetic effect, a maternal metabolic effect, or some combination of these pathways. A mediation model is then fit to these candidate variants and associated outcomes to identify which of these pathways, if any, mediate the total effect. We then group maternal genetic variants according to the relative magnitudes of these three effect pathways. In an application to existing mother-newborn data from the HAPO study, we find that of 78 candidate variants, the majority influence newborn birthweight solely through either a direct maternal or indirect fetal genetic effect (37% and 40%, respectively), a smaller number through both of these (14%), relatively few exclusively through the maternal metabolic pathway (6%), and almost none through a combination of the maternal metabolic pathway with either of the two genetic pathways (3%). We also find that these overall patterns of mediation effects are similar across outcomes.

Conclusions: Our results reveal broad patterns in the effects of maternal genetic variants on newborn adiposity, and identify both new genetic loci and loci known from previous literature to influence newborn adiposity. These results demonstrate the potential for scientific discovery enabled by our multi-omics mediation pipeline, and the approach is broadly applicable for untangling path-specific contributions in the modern integrated multi-omics landscape.

Background: Olfactory dysfunction is among the earliest signs of many age-related neurodegenerative diseases and has been associated with increased mortality in older adults; however, its genetic basis remains largely unknown. Therefore, here we aimed to elucidate its genetic architecture through a genome-wide association study meta-analysis (GWMA).

Methods: This GWMA included the participants of European ancestry (N = 22,730) enrolled in four different large population-based studies followed by a multi-ancestry GWMA including participants of African ancestry (N = 1,030). Olfactory dysfunction was assessed using a 12-item smell identification test.

Results: GWMA revealed a novel genome-wide significant locus (tagged by single nucleotide polymorphism rs11228623 at the 11q12 locus) associated with olfactory dysfunction. Gene-based analysis revealed a high enrichment for olfactory receptor genes in this region. Phenome-wide association studies demonstrated associations between genetic variants related to olfactory dysfunction and blood cell counts, kidney function, skeletal muscle mass, cholesterol levels and cardiovascular disease. Using individual-level data, we also confirmed and quantified the strength of these associations on a phenotypic level. Moreover, employing two-sample Mendelian Randomization analyses, we found evidence for causal associations between olfactory dysfunction and these phenotypes.

Conclusions: Our findings provide novel insights into the genetic architecture of the sense of smell and highlight its importance for many aspects of human health. Moreover, these findings could facilitate the identification and monitoring of individuals at increased risk of olfactory dysfunction and associated diseases.

Objective: The Cuban Painted Landsnail is an iconic endemic tree snail species with distinctive colourful shells used in traditional handicrafts. This species won the International Mollusc of the Year 2022 competition in an open public vote. As the competition prize, we have assembled the draft genome of this species.

Data description: Genomic DNA from Polymita picta (Born, 1778) was sequenced using PacBio HiFi sequencing with a yield of 5.3 million reads (41.4 Gb) and an N50 of 8.1 Kb. The genome size of P. picta was estimated to be 2.9 Gb, and the final assembly was 1.85 Gb, with a total of 22,619 contigs and a contig N50 of 124.2 Kb. BUSCO analysis of the genome assembly indicated a genome completeness of 88.4%, with 7% complete duplicated BUSCOs in metazoa_odb10. The draft genome will be a valuable resource for work on the endangered Cuban Painted Landsnail including monitoring genetic diversity and establishing captive breeding for conservation.

Objectives: Lacticaseibacillus rhamnosus is a widely recognized probiotic bacteria with therapeutic applications in human and animal health. The L. rhamnosus B3421 strain, isolated from Panax ginseng, has been reported to be associated with antioxidant and anti-inflammatory properties, supporting its functional potential. We sequenced and analyzed the genome of L. rhamnosus B3421 to evaluate its probiotic potential for human healthcare and animal applications, focusing on genomic features related to safety and functionality.

Data description: In this study, we isolated L. rhamnosus B3421 from Panax ginseng C. A. Meyer (Ginseng) and performed whole-genome sequencing. The genome of L. rhamnosus B3421 consists of 3,000,051 base pairs (bp) with a guanine + cytosine (G + C) content of 46.70%. It encodes 59 transfer RNAs, 15 ribosomal RNAs, and 2,807 coding sequences (CDSs). Of these CDSs, 99.13% (2,758 proteins) were assigned to functional categories in the Clusters of Orthologous Group (COGs) classification system, while 49 proteins remained uncharacterized. Our genome analysis identified no antibiotic resistance (ABR) or antimicrobial resistance (AMR) genes, indicating that L. rhamnosus B3421 is a safe probiotic bacterium with minimal risk of contributing to the horizontal transfer of antibiotic resistance within the gut microbiome. Additionally, the genome contains genes associated with the ggmotif (PF10439), Enterocin X chain beta, and Carnocin CP52, as identified through BAGEL4 analysis, along with 24 other genes related to reductase or peroxidase activities. These genes may confer competitive advantages against pathogenic bacteria and oxidative stress. Our findings highlight the probiotic potential of L. rhamnosus B3421 and its prospective applications in promoting human and animal health.

Objectives: This amplicon metagenomic study examines the relative abundance, taxonomic profiles and community structure of bacterial and fungal communities associated with the roots of parsley (Petroselinum crispum) and celery (Apium graveolens) under monocropping and intercropping systems. The study aims to provide a baseline understanding of how intercropping influences rhizosphere microbial dynamics.

Data description: The dataset provides insight into the effects of parsley-celery intercropping system on soil microbial richness, diversity and community structure. Amplicon metagenomic sequencing was performed on the DNA samples, targeting the 16S rRNA gene (V3-V4 region) and the ITS region for bacterial and fungal communities, respectively. The quantified libraries were pooled and sequenced using Illumina platforms, and the raw sequences were analyzed using the Quantitative Insights Into Microbial Ecology (QIIME 2 version 2019.1.) pipeline. The resulting Amplicon Sequence Variant (ASV) profiles revealed Actinobacteria and Protobacteria as the most predominant bacteria phyla, followed by Bacteroidota, Gemmatimonadota and Acidobacteriaota. The most predominant taxonomic distribution of fungi at the phylum level includes Ascomycota and Mortierellomycota. The dataset includes raw sequence reads in FASTQ format (.fastq.gz), which have been deposited in the Sequence Read Archive (SRA) of the National Center for Biotechnology Information (NCBI) under the Bioproject Accession numbers; SRP540554 (16S rRNA) and SRP540675 (ITS).

Objectives: Finnsheep, a highly prolific breed of sheep, has been globally exported for improving fertility traits of many sheep breeds. Published genomic studies of Finnsheep have been based on Texel and Rambouillet reference genomes, which may not capture its unique genetic features. Our main objective was to generate a high-quality Finnsheep genome assembly and its annotation that could serve as a breed-specific reference for studying fertility and adaptation in Finnsheep and other short-tailed northern European sheep breeds.

Data description: We generated a 2.53 Gb assembly using PacBio HiFi long-reads and Hi-C sequencing from a highly fertile Finnsheep ewe. The assembly, scaffolded with Hi-C data has a contig N50 of 35.5 Mb and scaffold N50 of 100.6 Mb. Gene annotation identified 42,533 genes spanning 46.5 Mb of coding region. BUSCO completeness for the assembly and annotation was 94.9% and 84.3%, respectively. This data, including raw reads, assembly, and annotations supports genomic studies of Finnsheep and other prolific breeds of sheep that are particularly adapted to northern European environments.

Objectives: Haloferax volcanii is an extreme halophile belonging to the Haloferacaceae family that thrives in hypersaline environments. This study presents the complete genome sequence of the H. volcanii strain PC0224 isolated from a Thai solar saltern. Genomic data will enhance our understanding of circadian rhythm mechanisms and their evolutionary significance in extremophilic archaea.

Data description: The H. volcanii PC0224 genome comprises four circular sequences containing 3,773,977 bp and 66.16% GC content. Sequenced using Illumina and PacBio technologies and assembled with Hybracter, the genome contained 3,731 CDS, 6 rRNAs, 54 tRNAs, 2 ncRNAs, and 4 CRISPR arrays. This dataset enables the investigation of circadian rhythm regulatory systems and comparative genomic studies of temporal adaptation mechanisms in extremophilic archaea.

Objectives: A composite core collection (CCC) in sesame (Sesamum indicum L.) will help utilize genetic resources efficiently. This study reports, using genomics tools, a representative minimal set (CCC) that capture maximal genetic diversity from a set of 5,856 sesame accessions being conserved at the National Genebank (NGB) of the ICAR-NBPGR. The CCC will serve as a valuable resource for researchers and breeders to facilitate sesame improvement for traits such as yield, disease resistance, stress resilience, and nutritional content. Ultimately, this work contributes to the broader goal of improving sesame for an ever-increasing demand for vegetable oil, to meet our food security challenges.

Data description: This study presents ddRAD-seq data for a total of 5,856 sesame accessions that includes 2,496 accessions (a subset of 5,856 accessions) that was reported by us recently. Using next-generation sequencing (NGS) short-reads over 2.16 Terabases of sequence data were generated, with each sample averaging 1.2 million reads. The study identifies a set of 1,768 sesame accessions as the CCC that captures maximal diversity, genotypic and phenotypic. This will aid researchers in trait discovery, association studies, pre-breeding, and parental selection for complex traits viz., yield, disease resistance, stress resilience, and other economically important traits.