With over 2,500 identified species across the globe, fleas are notorious veterinary pests and vectors of pathogens, including Rickettsia typhi (murine typhus), R. felis (murine typhus-like illness), Bartonella henselae (cat-scratch disease), and myxoma virus (Myxomatosis). Speciation of fleas is reliant on distinguishing morphological features; however, studies have also used certain mitochondrial genes for systematic analyses. This dataset is comprised of the C. felis mitochondrial genome, a novel resource for comparative genomics of fleas and other insects. The genome (Genbank accession number: MT594468) encodes the full repertoire of 37 genes, including 22 tRNAs, 13 protein coding genes, and 2 rRNAs with the conserved synteny observed in those of other Siphonaptera mitogenomes and the general insect mitochondrial gene order.
This dataset was used to overview the taxonomic composition of the gastrointestinal microbiomes during the first two years of life with the intent to better understand the effects of the invasive pathogen, Shigella. Data was collected through a two year longitudinal study of a mother-infant cohort in Malawi, using 16S rRNA amplicon sequencing to characterize the gastrointestinal microbiota. Rectal swab samples were collected every 6 six months during well-child visits or when an infant visiting the clinic presented diarrhea to diagnose Shigella infection. 16S rRNA gene amplicon libraries yielded an average of 23,720 reads per sample with a total of 8,729,027 reads and a total of 325 taxa were identified after quality filtering.
This study introduces a novel application of the MAGMA (Multi-marker Analysis of GenoMic Annotation) software tool that enables testing for associations between enhancer attributes and risk to determine the enhancer characteristics that are associated with risk for schizophrenia. The study uses the RWAS (Regulome Wide Association Study) framework to first collect enhancer annotations in a tissue relevant to the trait of interest, then identifies specific risk-associated enhancers by aggregating the effects of all SNPs (single nucleotide polymorphisms) that overlap the enhancer’s position in the genome, and finally, tests for associations of enhancer features with disease risk using a regression framework.
The dataset contains data pertaining to the examination of draft genomes of 388 methicillin-resistant Staphylococcus aureus isolates obtained from intensive care unit patients at three geographically distributed hospitals. The purpose of the study was to determine genomic diversity associated with potential health care worker-associated transmission. Relevant statistics, including linked GenBank and SRA accession numbers for each genome assembly, are included in Table 1 of the associated publication.