Copy number variation profiling in pharmacogenes using panel-based exome resequencing and correlation to human liver expression.

Structural variants including copy number variations (CNV) have gained widespread attention, especially in pharmacogenomics but for several genes functional relevance and clinical evidence are still lacking. Detection of CNVs in next-generation sequencing data is challenging but offers widespread applications. We developed a cohort-based CNV detection workflow to extract CNVs from read counts of targeted NGS of 340 genes involved in absorption, distribution, metabolism and excretion (ADME) of drugs. We applied our method to 150 human liver tissue samples and correlated identified CNVs to mRNA expression levels. In total, we identified 445 deletions (73%) and 167 duplications (27%) in 36 pharmacogenes including all well-known CNVs of CYPs, GSTs, SULTs, UGTs, numerous described rare CNVs of CYP2E1, SLC16A3 or UGT2B15 as well as novel observations, e.g., for SLC22A12, SLC22A17 and GPS2 (G Protein Pathway Suppressor 2). We were able to fine-map complex CNVs of CYP2A6 and CYP2D6 with exon resolution. Correlation analysis confirmed known expression patterns for common CNVs and suggested an influence on expression variability for some rare CNVs. Our straightforward CNV detection workflow can be easily applied to any NGS coverage data and helped to analyze CNVs in an ADME-NGS panel of 340 pharmacogenes to improve genotype-phenotype correlations.

Analysis of the intestinal microbiota using SOLiD 16S rRNA gene sequencing and SOLiD shotgun sequencing.

BACKGROUND: Metagenomics seeks to understand microbial communities and assemblages by DNA sequencing. Technological advances in next generation sequencing technologies are fuelling a rapid growth in the number and scope of projects aiming to analyze complex microbial environments such as marine, soil or the gut. Recent improvements in longer read lengths and paired-sequencing allow better resolution in profiling microbial communities. While both 454 sequencing and Illumina sequencing have been used in numerous metagenomic studies, SOLiD sequencing is not commonly used in this area, as it is believed to be more suitable in the context of reference-guided projects. RESULTS: To investigate the performance of SOLiD sequencing in a metagenomic context, we compared taxonomic profiles of SOLiD mate-pair sequencing reads with Sanger paired reads and 454 single reads. All sequences were obtained from the bacterial 16S rRNA gene, which was amplified from microbial DNA extracted from a human fecal sample. Additionally, from the same fecal sample, complete genomic microbial DNA was extracted and shotgun sequenced using SOLiD sequencing to study the composition of the intestinal microbiota and the existing microbial metabolism. We found that the microbiota composition of 16S rRNA gene sequences obtained using Sanger, 454 and SOLiD sequencing provide results comparable to the result based on shotgun sequencing. Moreover, with SOLiD sequences we obtained more resolution down to the species level. In addition, the shotgun data allowed us to determine a functional profile using the databases SEED and KEGG. CONCLUSIONS: This study shows that SOLiD mate-pair sequencing is a viable and cost-efficient option for analyzing a complex microbiome. To the best of our knowledge, this is the first time that SOLiD sequencing has been used in a human sample.

Targeted next generation sequencing as a diagnostic tool in epileptic disorders.

PURPOSE: Epilepsies have a highly heterogeneous background with a strong genetic contribution. The variety of unspecific and overlapping syndromic and nonsyndromic phenotypes often hampers a clear clinical diagnosis and prevents straightforward genetic testing. Knowing the genetic basis of a patient's epilepsy can be valuable not only for diagnosis but also for guiding treatment and estimating recurrence risks. METHODS: To overcome these diagnostic restrictions, we composed a panel of genes for Next Generation Sequencing containing the most relevant epilepsy genes and covering the most relevant epilepsy phenotypes known so far. With this method, 265 genes were analyzed per patient in a single step. We evaluated this panel on a pilot cohort of 33 index patients with concise epilepsy phenotypes or with a severe but unspecific seizure disorder covering both sporadic and familial cases. KEY FINDINGS: We identified presumed disease-causing mutations in 16 of 33 patients comprising sequence alterations in frequently as well as in less commonly affected genes. The detected aberrations encompassed known and unknown point mutations (SCN1A p.R222X, p. E289V, p.379R, p.R393H; SCN2A p.V208E; STXBP1 p.R122X; KCNJ10 p.L68P, p.I129V; KCTD7 p.L108M; KCNQ3 p.P574S; ARHGEF9 p.R290H; SMS p.F58L; TPP1 p.Q278R, p.Q422H; MFSD8 p.T294K), a putative splice site mutation (SCN1A c.693A> p.T/P231P) and small deletions (SCN1A p.F1330Lfs3X [1 bp]; MFSD8 p.A138Dfs10X [7 bp]). All mutations have been confirmed by conventional Sanger sequencing and, where possible, validated by parental testing and segregation analysis. In three patients with either Dravet syndrome or myoclonic epilepsy, we detected SCN1A mutations (p.R222X, p.P231P, p.R393H), even though other laboratories had previously excluded aberrations of this gene by Sanger sequencing or high-resolution melting analysis. SIGNIFICANCE: We have developed a fast and cost-efficient diagnostic screening method to analyze the genetic basis of epilepsies. We were able to detect mutations in patients with clear and with unspecific epilepsy phenotypes, to uncover the genetic basis of many so far unresolved cases with epilepsy including mutation detection in cases in which previous conventional methods yielded falsely negative results. Our approach thus proved to be a powerful diagnostic tool that may contribute to collecting information on both common and unknown epileptic disorders and in delineating associated phenotypes of less frequently mutated genes.

A New Panel-Based Next-Generation Sequencing Method for ADME Genes Reveals Novel Associations of Common and Rare Variants With Expression in a Human Liver Cohort.

We developed a panel-based NGS pipeline for comprehensive analysis of 340 genes involved in absorption, distribution, metabolism and excretion (ADME) of drugs, other xenobiotics, and endogenous substances. The 340 genes comprised phase I and II enzymes, drug transporters and regulator/modifier genes within their entire coding regions, adjacent intron regions and 5' and 3'UTR regions, resulting in a total panel size of 1,382 kbp. We applied the ADME NGS panel to sequence genomic DNA from 150 Caucasian liver donors with available comprehensive gene expression data. This revealed an average read-depth of 343 (range 27-811), while 99% of the 340 genes were covered on average at least 100-fold. Direct comparison of variant annotation with 363 available genotypes determined independently by other methods revealed an overall accuracy of >99%. Of 15,727 SNV and small INDEL variants, 12,022 had a minor allele frequency (MAF) below 2%, including 8,937 singletons. In total we found 7,273 novel variants. Functional predictions were computed for coding variants (n = 4,017) by three algorithms (Polyphen 2, Provean, and SIFT), resulting in 1,466 variants (36.5%) concordantly predicted to be damaging, while 1,019 variants (25.4%) were predicted to be tolerable. In agreement with other studies we found that less common variants were enriched for deleterious variants. Cis-eQTL analysis of variants with (MAF ≥ 2%) revealed significant associations for 90 variants in 31 genes after Bonferroni correction, most of which were located in non-coding regions. For less common variants (MAF < 2%), we applied the SKAT-O test and identified significant associations to gene expression for ADH1C and GSTO1. Moreover, our data allow comparison of functional predictions with additional phenotypic data to prioritize variants for further analysis.

Panel-based next generation sequencing as a reliable and efficient technique to detect mutations in unselected patients with retinal dystrophies.

Hereditary retinal dystrophies (RD) constitute a group of blinding diseases that are characterized by clinical variability and pronounced genetic heterogeneity. The different forms of RD can be caused by mutations in >100 genes, including >1600 exons. Consequently, next generation sequencing (NGS) technologies are among the most promising approaches to identify mutations in RD. So far, NGS is not routinely used in gene diagnostics. We developed a diagnostic NGS pipeline to identify mutations in 170 genetically and clinically unselected RD patients. NGS was applied to 105 RD-associated genes. Underrepresented regions were examined by Sanger sequencing. The NGS approach was successfully established using cases with known sequence alterations. Depending on the initial clinical diagnosis, we identified likely causative mutations in 55% of retinitis pigmentosa and 80% of Bardet-Biedl or Usher syndrome cases. Seventy-one novel mutations in 40 genes were newly associated with RD. The genes USH2A, EYS, ABCA4, and RHO were more frequently affected than others. Occasionally, cases carried mutations in more than one RD-associated gene. In addition, we found possible dominant de-novo mutations in cases with sporadic RD, which implies consequences for counseling of patients and families. NGS-based mutation analyses are reliable and cost-efficient approaches in gene diagnostics of genetically heterogeneous diseases like RD.