METHODS: Genomic DNA was extracted from Salmonella strain PS01 and was sequenced using an Illumina HiSeq 2000 platform. The generated reads were de novo assembled using CLC Genomics Workbench. The draft genome was annotated and the presence of antimicrobial resistance genes was identified.
RESULTS: The 5 036 442bp genome contains various antimicrobial resistance genes conferring resistance to aminoglycosides, fluoroquinolones, fosfomycin, macrolides, phenicols, sulphonamides, tetracyclines and trimethoprim. The β-lactamase gene blaTEM-176 encoding TEM-176 was also found in this strain.
CONCLUSIONS: The genome sequence will aid in the understanding of drug resistance mechanisms in foodborne Salmonella Brancaster and highlights the need to ensure the judicious use of antibiotics in animal husbandry as well as the importance of implementing proper food handling and preparation practices.
RESULTS: We present an automated gene prediction pipeline, Seqping that uses self-training HMM models and transcriptomic data. The pipeline processes the genome and transcriptome sequences of the target species using GlimmerHMM, SNAP, and AUGUSTUS pipelines, followed by MAKER2 program to combine predictions from the three tools in association with the transcriptomic evidence. Seqping generates species-specific HMMs that are able to offer unbiased gene predictions. The pipeline was evaluated using the Oryza sativa and Arabidopsis thaliana genomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis showed that the pipeline was able to identify at least 95% of BUSCO's plantae dataset. Our evaluation shows that Seqping was able to generate better gene predictions compared to three HMM-based programs (MAKER2, GlimmerHMM and AUGUSTUS) using their respective available HMMs. Seqping had the highest accuracy in rice (0.5648 for CDS, 0.4468 for exon, and 0.6695 nucleotide structure) and A. thaliana (0.5808 for CDS, 0.5955 for exon, and 0.8839 nucleotide structure).
CONCLUSIONS: Seqping provides researchers a seamless pipeline to train species-specific HMMs and predict genes in newly sequenced or less-studied genomes. We conclude that the Seqping pipeline predictions are more accurate than gene predictions using the other three approaches with the default or available HMMs.
METHODS AND RESULTS: In view of the lack of study on their mitogenome, we sequenced (by next generation sequencing) and annotated the complete mitogenome of D. vijaysegarani from Malaysia to determine its features and phylogenetic relationship. The whole mitogenome of D. vijaysegarani has identical gene order with the published mitogenomes of the genus Dacus, with 13 protein-coding genes, two rRNA genes, 22 tRNAs, a non-coding A + T rich control region, and intergenic spacer and overlap sequences. Phylogenetic analysis based on 15 mitochondrial genes (13 PCGs and two rRNA genes), reveals Dacus, Zeugodacus and Bactrocera forming a distinct clade. The genus Dacus forms a monophyletic group in the subclade containing also the Zeugodacus group; this Dacus-Zeugodacus subclade is distinct from the Bactrocera subclade. D. (Mellesis) vijaysegarani forms a lineage with D. (Mellesis) trimacula in the subcluster containing also the lineage of D. (Mellesis) conopsoides and D. (Callantra) longicornis. D. (Dacus) bivittatus and D. (Didacus) ciliatus form a distinct subcluster. Based on cox1 sequences, the Malaysia and Vietnam taxa of D. vijaysegarani may not be conspecific.
CONCLUSIONS: Overall, the mitochondrial genome of D. vijaysegarani provided essential molecular data that could be useful for further studies for species diagnosis, evolution and phylogeny research of other tephritid fruit flies in the future.
OBJECTIVE: To investigate the genetics of depression among individuals of East Asian and European descent living in different geographic locations, and with different outcome definitions for depression.
DESIGN, SETTING, AND PARTICIPANTS: Genome-wide association analyses followed by meta-analysis, which included data from 9 cohort and case-control data sets comprising individuals with depression and control individuals of East Asian descent. This study was conducted between January 2019 and May 2021.
EXPOSURES: Associations of genetic variants with depression risk were assessed using generalized linear mixed models and logistic regression. The results were combined across studies using fixed-effects meta-analyses. These were subsequently also meta-analyzed with the largest published GWAS for depression among individuals of European descent. Additional meta-analyses were carried out separately by outcome definition (clinical depression vs symptom-based depression) and region (East Asian countries vs Western countries) for East Asian ancestry cohorts.
MAIN OUTCOMES AND MEASURES: Depression status was defined based on health records and self-report questionnaires.
RESULTS: There were a total of 194 548 study participants (approximate mean age, 51.3 years; 62.8% women). Participants included 15 771 individuals with depression and 178 777 control individuals of East Asian descent. Five novel associations were identified, including 1 in the meta-analysis for broad depression among those of East Asian descent: rs4656484 (β = -0.018, SE = 0.003, P = 4.43x10-8) at 1q24.1. Another locus at 7p21.2 was associated in a meta-analysis restricted to geographically East Asian studies (β = 0.028, SE = 0.005, P = 6.48x10-9 for rs10240457). The lead variants of these 2 novel loci were not associated with depression risk in European ancestry cohorts (β = -0.003, SE = 0.005, P = .53 for rs4656484 and β = -0.005, SE = 0.004, P = .28 for rs10240457). Only 11% of depression loci previously identified in individuals of European descent reached nominal significance levels in the individuals of East Asian descent. The transancestry genetic correlation between cohorts of East Asian and European descent for clinical depression was r = 0.413 (SE = 0.159). Clinical depression risk was negatively genetically correlated with body mass index in individuals of East Asian descent (r = -0.212, SE = 0.084), contrary to findings for individuals of European descent.
CONCLUSIONS AND RELEVANCE: These results support caution against generalizing findings about depression risk factors across populations and highlight the need to increase the ancestral and geographic diversity of samples with consistent phenotyping.