Sousa, C. | Search bioRxiv

bioRxiv2019

Quantifying genetic regulatory variation in human populations improves transcriptome analysis in rare disease patients

Transcriptome data holds substantial promise for better interpretation of rare genetic variants in basic research and clinical settings. Here, we introduce ANalysis of Expression VAriation (ANEVA) to quantify genetic variation in gene dosage from allelic expression (AE) data in a population. Application to GTEx data showed that this variance estimate is robust across datasets and is correlated with selective constraint in a gene. We next used ANEVA variance estimates in a Dosage Outlier Test (ANEVA-DOT) to identify genes in an individual that are affected by a rare regulatory variant with an unusually strong effect. Applying ANEVA-DOT to AE data form 70 Mendelian muscular disease patients showed high accuracy in detecting genes with pathogenic variants in previously resolved cases, and lead to one confirmed and several potential new diagnoses in cases previously unresolved. Using our reference estimates from GTEx data, ANEVA-DOT can be readily incorporated in rare disease diagnostic pipelines to better utilize RNA-seq data.\n\nOne Sentence SummaryNew statistical framework for modelling allelic expression characterizes genetic regulatory variation in populations and informs diagnosis in rare disease patients

genomics↗

bioRxiv2019

On the front line of Klebsiella pneumoniae surface structures understanding: establishment of Fourier Transform Infrared (FT-IR) spectroscopy as a capsule typing method

Genomics-based population analysis of multidrug resistant (MDR) Klebsiella pneumoniae (Kp) motivated a renewed interest on capsule (K) types given their importance as evolutionary and virulence markers of clinically relevant strains. However, there is a gap between genotypic based predictions and information on capsular polysaccharide structure and composition. We used molecular genotypic, comparative genomics, biochemical and phenotypic data on the cps locus to support the usefulness of Fourier-Transform Infrared (FT-IR) spectroscopy as a phenotypic approach for K-type characterization and identification. The approach was validated with a collection of representative MDR Kp isolates from main lineages/Clonal Groups (CGs) involved in local or nationwide epidemics in 6 European and South American countries. FT-IR-based K-type assignments were compared with those obtained by genotypic methods and WGS (cps operon), and further complemented with data on the polysaccharide composition and structure of known K-types. We demonstrate that our FT-IR-based spectroscopy approach can discriminate all 21 K-types identified with a resolution comparable (or even higher) to that provided by WGS, considered gold-standard methodology. Besides contributing to enlighten K-type diversity among a significant MDR Kp collection, the specific associations between certain K-types and Kp lineages identified in different geographic regions over time support the usefulness of our FT-IR-based approach for strain typing. Additionally, we demonstrate that FT-IR discriminatory ability is correlated with variation on the structure/composition of known K-types and, supported on WGS data, we were able to predict the sugar composition and chemical structure of new KL-types. Our data revealed an unprecedent resolution at a quick and low-cost rate of Kp K-types at the phenotypic level. Our FT-IR spectroscopy-based approach might be extremely useful not only as a cost-effective Kp typing tool, but also to improve our understanding on sugar-based coating structures of high relevance for strain evolution and host adaptation.

developmental biology↗