Population genetic analysis of Bartonella bacilliformis isolates from areas of Peru where Carrion\u27s disease is endemic and epidemic

Carrion's disease is caused by infection with the α-proteobacterium Bartonella bacilliformis. Distribution of the disease is considered coincident with the distribution of its known vector, the sand fly Lutzomyia verrucarum. Recent epidemics of B. bacilliformis infections associated with atypical symptomatology in nonendemic regions have raised questions regarding the historic and present distribution of this bacterium and the scope of disease that infection causes. Phylogenetic relationships and genomic diversity of 18 B. bacilliformis isolates (10 isolates from a region where Carrion's disease is epidemic, Cuzco, Peru, and 8 isolates from a region where Carrion's disease is endemic, Caraz, Peru) were assessed using genomic data generated by infrequent restriction site PCR and gene sequence analysis of the flagellin gltA and ialB genes. A population genetic analysis of the genomic diversity suggests that what was once considered an epidemic region of Peru did not result from the recent introduction of B. bacilliformis

Patterns of Synonymous Codon Usage in Drosophila melanogaster Genes With Sex-Biased Expression

The nonrandom use of synonymous codons (codon bias) is a well-established phenomenon in Drosophila. Recent reports suggest that levels of codon bias differ among genes that are differentially expressed between the sexes, with male-expressed genes showing less codon bias than female-expressed genes. To examine the relationship between sex-biased gene expression and level of codon bias on a genomic scale, we surveyed synonymous codon usage in 7276 D. melanogaster genes that were classified as male-, female-, or non-sex-biased in their expression in microarray experiments. We found that male-biased genes have significantly less codon bias than both female- and non-sex-biased genes. This pattern holds for both germline and somatically expressed genes. Furthermore, we find a significantly negative correlation between level of codon bias and degree of sex-biased expression for male-biased genes. In contrast, female-biased genes do not differ from non-sex-biased genes in their level of codon bias and show a significantly positive correlation between codon bias and degree of sex-biased expression. These observations cannot be explained by differences in chromosomal distribution, mutational processes, recombinational environment, gene length, or absolute expression level among genes of the different expression classes. We propose that the observed codon bias differences result from differences in selection at synonymous and/or linked nonsynonymous sites between genes with male- and female-biased expression

Scalable detection of technically challenging variants through modified next‐generation sequencing

Abstract Background Some clinically important genetic variants are not easily evaluated with next‐generation sequencing (NGS) methods due to technical challenges arising from high‐ similarity copies (e.g., PMS2, SMN1/SMN2, GBA1, HBA1/HBA2, CYP21A2), repetitive short sequences (e.g., ARX polyalanine repeats, FMR1 AGG interruptions in CGG repeats, CFTR poly‐T/TG repeats), and other complexities (e.g., MSH2 Boland inversions). Methods We customized our NGS processes to detect the technically challenging variants mentioned above with adaptations including target enrichment and bioinformatic masking of similar sequences. Adaptations were validated with samples of known genotypes. Results Our adaptations provided high‐sensitivity and high‐specificity detection for most of the variants and provided a high‐sensitivity primary assay to be followed with orthogonal disambiguation for the others. The sensitivity of the NGS adaptations was 100% for all of the technically challenging variants. Specificity was 100% for those in PMS2, GBA1, SMN1/SMN2, and HBA1/HBA2, and for the MSH2 Boland inversion; 97.8%–100% for CYP21A2 variants; and 85.7% for ARX polyalanine repeats. Conclusions NGS assays can detect technically challenging variants when chemistries and bioinformatics are jointly refined. The adaptations described support a scalable, cost‐effective path to identifying all clinically relevant variants within a single sample

Whole exome sequencing in patients with white matter abnormalities

Here we report whole exome sequencing (WES) on a cohort of 71 patients with persistently unresolved white matter abnormalities with a suspected diagnosis of leukodystrophy or genetic leukoencephalopathy. WES analyses were performed on trio, or greater, family groups. Diagnostic pathogenic variants were identified in 35% (25 of 71) of patients. Potentially pathogenic variants were identified in clinically relevant genes in a further 7% (5 of 71) of cases, giving a total yield of clinical diagnoses in 42% of individuals. These findings provide evidence that WES can substantially decrease the number of unresolved white matter cases

Optimization of Next-Generation Sequencing Informatics Pipelines for Clinical Laboratory Practice

We direct your readers’ attention to the principles and guidelines (see Supplementary Guidelines) developed by the Next-generation Sequencing: Standardization of Clinical Testing II (Nex-StoCT II) informatics workgroup, which was convened by the Centers for Disease Control and Prevention (CDC). This work represents the first effort to systematically review current practices and present consensus recommendations for the design, optimization, and implementation of an informatics pipeline for clinical next-generation sequencing (NGS) in compliance with existing regulatory and professional quality standards1. Workgroup participants included informatics experts, clinical and research laboratory professionals, physicians with experience in NGS results interpretation, NGS test platform and software developers, and participants from US government agencies and professional organizations. The primary focus was the design, optimization, and implementation of an NGS informatics pipeline for the detection of germline sequence variants; however, the workgroup also discussed use of NGS for cancer and infectious disease testing. The typical NGS analytical process and selected workgroup recommendations are summarized in Table 1, Supplementary Fig. 1 and the Supplementary Guidelines