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Lehnert, K.

Publications and source records attributed to Lehnert, K..

2 recordsLinked to original sources

RBV: Read balance validator, a tool for prioritising copy number variations in germline conditions

BackgroundThe popularisation and decreased cost of genome resequencing has resulted in an increased use in molecular diagnostics. While there are a number of established and high quality bioinfomatic tools for identifying small genetic variants including single nucleotide variants and indels, currently there is no established standard for the detection of copy number variants (CNVs) from sequence data. The requirement for CNV detection from high throughput sequencing has resulted in the development of a large number of software packages. These tools typically utilise the sequence data characteristics: read depth, split reads, read pairs, and assembly-based techniques. However the additional source of information from read balance, defined as relative proportion of reads of each allele at each position, has been underutilised in the existing applications.\n\nResultsWe present Read Balance Validator (RBV), a bioinformatic tool which uses read balance for prioritisation and validation of putative CNVs. The software simultaneously interrogates nominated regions for the presence of deletions or multiplications, and can differentiate larger CNVs from diploid regions. Additionally, the utility of RBV to test for inheritance of CNVs is demonstrated in this report.\n\nConclusionsRBV is a CNV validation and prioritisation bioinformatic tool for both genome and exome sequencing available as a python package from https://github.com/whitneywhitford/RBV

bioinformatics

Copy number variants implicate cardiac function and development pathways in earthquake-induced stress cardiomyopathy

The pathophysiology of stress cardiomyopathy (SCM), also known as takotsubo syndrome, is poorly understood. SCM usually occurs sporadically, often in association with a stressful event, but clusters of cases are reported after major natural disasters. There is some evidence that this is a familial condition. We have examined three possible models for an underlying genetic predisposition to SCM. Our primary study cohort consists of 28 women who suffered SCM as a result of two devastating earthquakes that struck the city of Christchurch, New Zealand, in 2010 and 2011. To seek possible underlying genetic factors we carried out exome analysis, Cardio-MetaboChip genotyping array analysis and array comparative genomic hybridization on these subjects. The most striking finding from these analyses was the observation of a markedly elevated rate of rare, heterogeneous copy number variants (CNV) of uncertain clinical significance (in 12/28 subjects). Several of these CNVs clearly impacted on genes of cardiac relevance including RBFOX1, GPC5, KCNRG, CHODL, and GPBP1L1. There is no physical overlap between the CNVs, and the genes they impact do not fall into a clear pathophysiological pathway. However, the recognition that SCM cases display a high rate of unusual CNV, and that SCM predisposition may therefore be associated with these CNVs, offers a novel perspective and a new approach by which to understand this enigmatic condition.

genetics