BMC genomic data最新文献

Background: Mycobacterium tuberculosis (MTB) is a human-specific pathogen that primarily infects humans, causing tuberculosis (TB). Antimicrobial resistance (AMR) in MTB presents a formidable challenge to global health. The employment of machine learning on whole-genome sequencing data (WGS) presents significant potential for uncovering the genomic mechanisms underlying drug resistance in MTB.

Methods: We used 18 binary matrices, each consisting of genotypes and antimicrobial susceptibility testing phenotypes from a specific MTB-antimicrobial dataset. By constructing training and test datasets on all SNPs, intersected SNPs, and randomly generated SNPs, we developed a Machine learning (ML) framework using twelve different algorithms. Then, we compared the performances of the various ML models and used the SHapley Additive exPlanations (SHAP) framework to decipher why and how decisions are made within the optimal algorithm. Lastly, we applied the models to predict the resistance phenotype to rifampicin (RIF) and isoniazid (INH) in the additional independent MTB isolate datasets from India and Israel.

Results: In our study, the Gradient Boosting Classifier (GBC) model was the best in terms of correctly identified percentages (97.28%, 96.06%, 94.19%, and 92.81% for the four first-line drugs, RIF, INH, pyrazinamide, and ethambutol respectively). By estimating the contributions of AMR-related SNPs by SHAP values, we found that position 761,155 (rpoB_p.Ser450), 2,155,168 (katG_p.Ser315) rank top in RIF and INH, their higher values (1 for alternative allele) tend to predict the resistance trait for these two drugs. In addition, the best model GBC generalizes well in predicting the resistance phenotypes for RIF and INH in the external independent MTB isolate datasets from India and Israel.

Conclusions: This study integrates ML methods into antimicrobial resistance research, develops a framework for predicting resistance phenotypes, and explores AMR-related SNPs in MTB. Quantifying the important SNPs' contribution to model decisions makes the ML algorithmic process more transparent, interpretable enabling and enables clinical practice.

Background: Local livestock breeds play a pivotal role in maintaining agricultural sustainability, conserving biodiversity, and preserving cultural heritage. These breeds often possess unique genetic characteristics tailored to their specific environments. The Cinisara is a dual-purpose local cattle breed of Podolian origin, primarily farmed in western Sicily, Italy. However, reports of spurious crossbreeding with cosmopolitan breeds aimed at improving the breed productivity exist. To assess the conservation status and ongoing selective pressures on this unique breed, we genotyped 71 unrelated Cinisara cattle (CIN_A) at 65k SNPs, and extended the dataset with publicly available genotype data of 30 Cinisara individuals sampled 20 years ago (CIN_B). We also included 194 individuals from seven cattle breeds, including the Podolica (POD) breed and the cosmopolitan Holstein (HOL) and Brown Swiss (BRW) breeds. We assessed the genetic diversity, population structure, and determined the extent of introgression from cosmopolitan breeds into Cinisara using local ancestry inference.

Results: Population structure analyses confirmed the Cinisara's Podolian lineage and revealed significant HOL and BRW introgression. While both Cinisara populations, CIN_A and CIN_B, displayed broadly comparable genetic diversity to larger breeds, CIN_B showed reduced heterozygosity and increased inbreeding. CIN_A exhibited higher introgression, suggesting ongoing crossbreeding. Local ancestry was inferred using POD, HOL, and BRW references. CIN_A showed about 258/257 HOL/BRW introgressed SNPs, intercepting 186/131 genes and 1,584/1,772 QTLs. CIN_B had approximately 256/254 HOL/BRW introgressed SNPs, intercepting 218/184 genes and 547/437 QTLs. Predominantly, these regions overlapped with milk production QTLs, but some intercepted genes linked to unique Cinisara traits, like milk quality and climate adaptation, potentially altering breed typicality. Notably, CIN_B shows a potentially higher relative BRW contribution, while CIN_A shows a higher HOL contribution.

Conclusion: Our findings align with the reports of crossbreeding with cosmopolitan breeds to enhance the production performance of Cinisara, and reflect breeding choices such as a reduction in BRW crossing or a preference for HOL. This raises significant concerns regarding the preservation of local breeds, livestock biodiversity, and their cultural and economic value, and highlights the importance of developing informed breeding strategies that balance production improvements with the conservation of genetic heritage.

Objective: The innate immune response of an infected host is an essential defense mechanism to fight influenza virus infections in the respiratory tract. This response is essential to limit virus replication and spread. However, an exacerbated response may cause severe immune-pathologies. Therefore, it is very important to better understand innate immune responses at the level of its molecular networks in the context of viral infections.

Data: We infected human lung adenocarcinoma (A549) and human monocytic (THP-1) cells with H3N2 influenza virus A virus and performed transcriptome analysis using next generation RNA sequencing at various times post infection. We report raw sequence data and normalized log₂ transformed gene expression values. This data will allow researchers in the field to identify differentially expressed genes and pathways between the two cell types and over times post infection. Furthermore, our data enables comparisons to molecular studies performed in humans and animal models in the context of respiratory viral infections.

Objectives: This study investigates the nerve cord transcriptome of Asterias amurensis to explore its regenerative abilities. By comparing gene expression between a normal group and a group 72 h post-amputation, key genes involved in regeneration were identified. Functional annotation using GO, KEGG, NR, and UniProt databases provided insights into the biological roles of these genes. This research enhances the understanding of A. amurensis regeneration and highlights the need for further transcriptome analysis across different tissues.

Data description: A. amurensis, a starfish species found in the northwestern Pacific, is known for its strong predatory behavior and impact on marine biodiversity. In this study, individuals were divided into a normal group and a 72-hour post-amputation group. De novo transcriptome assembly of the nerve cord identified 257,769 unigenes, which were functionally annotated using GO, KEGG, NR, and UniProt databases. Since only nerve cord tissue was analyzed, additional transcriptome studies on various tissues are required for a more comprehensive understanding of A. amurensis biology.

Background: Primary carnitine deficiency (PCD) is an autosomal recessive rare disorder of carnitine cycle and carnitine transport caused by pathogenic variants in the SLC22A5 gene. The prevalence of PCD is unclear. This study aimed to estimate the carrier frequency and genetic prevalence of PCD using Genome Aggregation Database (gnomAD) data.

Methods: The pathogenicity of SLC22A5 variants was interpreted according to the American College of Medical Genetics and Genomics (ACMG) standards and guidelines. The minor allele frequency (MAF) of the variants of the SLC22A5 gene in 807,162 individuals was examined to estimate the global prevalence of PCD in nine ethnicities: African/African American (afr), Admixed American (amr), East Asian (eas), Non-Finnish European (nfe), South Asian (sas), Ashkenazi Jewish (asj), Middle Eastern (mid), Finnish (fin) and Remaining individuals (rmi). The global and population-specific carrier frequency and genetic prevalence of PCD were calculated using the Hardy-Weinberg equation.

Results: Total of 213 pathogenic/likely pathogenic variants (PV/LPV) of the SLC22A5 gene were identified according to the ACMG standards and guidelines. The global carrier frequency and genetic prevalence of PCD were 10.6 per thousand (1/95) and 28.2 per million (1/35427), respectively.

Conclusions: The prevalence of PCD is estimated to be 1/35,000 globally, with a range of between 1/450,000 and 1/20,000 depending on ethnicity.

Objectives: The degradation products of chitin exhibit various biological activities, giving them significant application potential. Chitinase-producing bacteria can be isolated from diverse environments such as soil, natural waters, and rhizospheres. However, their chitinolytic activity is often limited, particularly at low temperatures.

Data description: In this study, complete genome sequencing of a cold-adapted chitinolytic Pseudomonas strain, GWSMS-1, revealed a 4,606,781-bp linear chromosome with a G+C content of 59%. The genome encodes 4,599 protein-coding genes, 73 tRNA genes, and 27 rRNA genes. Functional annotation through GO, KEGG, and CAZy databases identified a substantial number of chitinase-encoding genes, which likely contribute to its high chitin-degrading capacity. The genomic insights into GWSMS-1 highlight its potential for applications in chitin degradation and offer valuable gene candidates for further research.

Antibiotic resistance is a major global health concern that caused by the overuse and misuse of antibiotics. Mobile genetic elements have a roles in the transmission of antibiotic resistance genes. The distribution and diversity of antibiotic resistance genes and mobile genetic elements in the microbiome of Sof Umer Cave have yet to be explored. To map the distribution and diversity of antibiotic resistance genes and mobile genetic elements in the microbiome of Sof Umer Cave using high-throughput shotgun sequencing. High-molecular-weight DNA was extracted from homogenized sample using the GeneAll DNA Soil Mini Kit. Purified environmental DNA was sequenced using a NovaSeq PE150. Analysis of the pathogen host interaction database revealed the predominance of pathogenic organisms such as Xanthomonas oryzae, Acinetobacter baumannii, Erwinia amylovora, and Mycobacterium tuberculosis. Similarly, analysis of the virulence factor database confirmed the presence of Type IV pili (VF1240), lipopolysaccharides, capsules, heme biosynthesis (VF0758), and alginate. More than 800 antibiotic resistance genes were identified, with 50% related to glycopeptide resistance, followed by antibiotic resistance genes associated with multidrug efflux pumps (30%), aminoglycoside resistance genes (10%), and unknown genes. A variety of mobile genetic elements were also identified, highlighting their importance in the genetic diversity and adaptation of the microbiome of Sof Umer Cave. These findings underscore the importance of the Sof Umer Cave habitat as a reservoir for antibiotic resistance, emphasizing the need for ongoing monitoring to enhance the understanding and control of antibiotic resistance genes.