Jeroen F. J. Laros

LOVD v.2.0: the next generation in gene variant databases

Locus‐Specific DataBases (LSDBs) store information on gene sequence variation associated with human phenotypes and are frequently used as a reference by researchers and clinicians. We developed the Leiden Open‐source Variation Database (LOVD) as a platform‐independent Web‐based LSDB‐in‐a‐Box package. LOVD was designed to be easy to set up and maintain and follows the Human Genome Variation Society (HGVS) recommendations. Here we describe LOVD v.2.0, which adds enhanced flexibility and functionality and has the capacity to store sequence variants in multiple genes per patient. To reduce redundancy, patient and sequence variant data are stored in separate tables. Tables are linked to generate connections between sequence variant data for each gene and every patient. The dynamic structure allows database managers to add custom columns. The database structure supports fast queries and allows storage of sequence variants from high‐throughput sequence analysis, as demonstrated by the X‐chromosomal Mental Retardation LOVD installation. LOVD contains measures to ensure database security from unauthorized access. Currently, the LOVD Website (http://www.LOVD.nl/) lists 71 public LOVD installations hosting 3,294 gene variant databases with 199,000 variants in 84,000 patients. To promote LSDB standardization and thereby database interoperability, we offer free server space and help to establish an LSDB on our Leiden server.

Roux-en-Y Gastric Bypass Surgery, but Not Calorie Restriction, Reduces Plasma Branched-Chain Amino Acids in Obese Women Independent of Weight Loss or the Presence of Type 2 Diabetes

OBJECTIVE Obesity and type 2 diabetes mellitus (T2DM) have been associated with increased levels of circulating branched-chain amino acids (BCAAs) that may be involved in the pathogenesis of insulin resistance. However, weight loss has not been consistently associated with the reduction of BCAA levels. RESEARCH DESIGN AND METHODS We included 30 obese normal glucose-tolerant (NGT) subjects, 32 obese subjects with T2DM, and 12 lean female subjects. Obese subjects underwent either a restrictive procedure (gastric banding [GB], a very low-calorie diet [VLCD]), or a restrictive/bypass procedure (Roux-en-Y gastric bypass [RYGB] surgery). Fasting blood samples were taken for the determination of amine group containing metabolites 4 weeks before, as well as 3 weeks and 3 months after the intervention. RESULTS BCAA levels were higher in T2DM subjects, but not in NGT subjects, compared with lean subjects. Principal component (PC) analysis revealed a concise PC consisting of all BCAAs, which showed a correlation with measures of insulin sensitivity and glucose tolerance. Only after the RYGB procedure, and at both 3 weeks and 3 months, were circulating BCAA levels reduced. CONCLUSIONS Our data confirm an association between deregulation of BCAA metabolism in plasma and insulin resistance and glucose intolerance. Three weeks after undergoing RYGB surgery, a significant decrease in BCAAs in both NGT as well as T2DM subjects was observed. After 3 months, despite inducing significant weight loss, neither GB nor VLCD induced a reduction in BCAA levels. Our results indicate that the bypass procedure of RYGB surgery, independent of weight loss or the presence of T2DM, reduces BCAA levels in obese subjects.

TSSV: a tool for characterization of complex allelic variants in pure and mixed genomes

MOTIVATIONnAdvances in sequencing technologies and computational algorithms have enabled the study of genomic variants to dissect their functional consequence. Despite this unprecedented progress, current tools fail to reliably detect and characterize more complex allelic variants, such as short tandem repeats (STRs). We developed TSSV as an efficient and sensitive tool to specifically profile all allelic variants present in targeted loci. Based on its design, requiring only two short flanking sequences, TSSV can work without the use of a complete reference sequence to reliably profile highly polymorphic, repetitive or uncharacterized regions.nnnRESULTSnWe show that TSSV can accurately determine allelic STR structures in mixtures with 10% representation of minor alleles or complex mixtures in which a single STR allele is shared. Furthermore, we show the universal utility of TSSV in two other independent studies: characterizing de novo mutations introduced by transcription activator-like effector nucleases (TALENs) and profiling the noise and systematic errors in an IonTorrent sequencing experiment. TSSV complements the existing tools by aiding the study of highly polymorphic and complex regions and provides a high-resolution map that can be used in a wide range of applications, from personal genomics to forensic analysis and clinical diagnostics.nnnAVAILABILITY AND IMPLEMENTATIONnWe have implemented TSSV as a Python package that can be installed through the command-line using pip install TSSV command. Its source code and documentation are available at https://pypi.python.org/pypi/tssv and http://www.lgtc.nl/tssv.

FDSTools: A software package for analysis of massively parallel sequencing data with the ability to recognise and correct STR stutter and other PCR or sequencing noise

Massively parallel sequencing (MPS) is on the advent of a broad scale application in forensic research and casework. The improved capabilities to analyse evidentiary traces representing unbalanced mixtures is often mentioned as one of the major advantages of this technique. However, most of the available software packages that analyse forensic short tandem repeat (STR) sequencing data are not well suited for high throughput analysis of such mixed traces. The largest challenge is the presence of stutter artefacts in STR amplifications, which are not readily discerned from minor contributions. FDSTools is an open-source software solution developed for this purpose. The level of stutter formation is influenced by various aspects of the sequence, such as the length of the longest uninterrupted stretch occurring in an STR. When MPS is used, STRs are evaluated as sequence variants that each have particular stutter characteristics which can be precisely determined. FDSTools uses a database of reference samples to determine stutter and other systemic PCR or sequencing artefacts for each individual allele. In addition, stutter models are created for each repeating element in order to predict stutter artefacts for alleles that are not included in the reference set. This information is subsequently used to recognise and compensate for the noise in a sequence profile. The result is a better representation of the true composition of a sample. Using Promega Powerseq™ Auto System data from 450 reference samples and 31 two-person mixtures, we show that the FDSTools correction module decreases stutter ratios above 20% to below 3%. Consequently, much lower levels of contributions in the mixed traces are detected. FDSTools contains modules to visualise the data in an interactive format allowing users to filter data with their own preferred thresholds.

Transmission of human mtDNA heteroplasmy in the Genome of the Netherlands families: support for a variable-size bottleneck

Although previous studies have documented a bottleneck in the transmission of mtDNA genomes from mothers to offspring, several aspects remain unclear, including the size and nature of the bottleneck. Here, we analyze the dynamics of mtDNA heteroplasmy transmission in the Genomes of the Netherlands (GoNL) data, which consists of complete mtDNA genome sequences from 228 trios, eight dizygotic (DZ) twin quartets, and 10 monozygotic (MZ) twin quartets. Using a minor allele frequency (MAF) threshold of 2%, we identified 189 heteroplasmies in the trio mothers, of which 59% were transmitted to offspring, and 159 heteroplasmies in the trio offspring, of which 70% were inherited from the mothers. MZ twin pairs exhibited greater similarity in MAF at heteroplasmic sites than DZ twin pairs, suggesting that the heteroplasmy MAF in the oocyte is the major determinant of the heteroplasmy MAF in the offspring. We used a likelihood method to estimate the effective number of mtDNA genomes transmitted to offspring under different bottleneck models; a variable bottleneck size model provided the best fit to the data, with an estimated mean of nine individual mtDNA genomes transmitted. We also found evidence for negative selection during transmission against novel heteroplasmies (in which the minor allele has never been observed in polymorphism data). These novel heteroplasmies are enhanced for tRNA and rRNA genes, and mutations associated with mtDNA diseases frequently occur in these genes. Our results thus suggest that the female germ line is able to recognize and select against deleterious heteroplasmies.

Downregulation of the acetyl-CoA metabolic network in adipose tissue of obese diabetic individuals and recovery after weight loss

Aims/hypothesisNot all obese individuals develop type 2 diabetes. Why some obese individuals retain normal glucose tolerance (NGT) is not well understood. We hypothesise that the biochemical mechanisms that underlie the function of adipose tissue can help explain the difference between obese individuals with NGT and those with type 2 diabetes.MethodsRNA sequencing was used to analyse the transcriptome of samples extracted from visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) of obese women with NGT or type 2 diabetes who were undergoing bariatric surgery. The gene expression data was analysed by bioinformatic visualisation and statistical analyses techniques.ResultsA network-based approach to distinguish obese individuals with NGT from obese individuals with type 2 diabetes identified acetyl-CoA metabolic network downregulation as an important feature in the pathophysiology of type 2 diabetes in obese individuals. In general, genes within two reaction steps of acetyl-CoA were found to be downregulated in the VAT and SAT of individuals with type 2 diabetes. Upon weight loss and amelioration of metabolic abnormalities three months following bariatric surgery, the expression level of these genes recovered to levels seen in individuals with NGT. We report four novel genes associated with type 2 diabetes and recovery upon weight loss: ACAT1 (encoding acetyl-CoA acetyltransferase 1), ACACA (encoding acetyl-CoA carboxylase α), ALDH6A1 (encoding aldehyde dehydrogenase 6 family, member A1) and MTHFD1 (encoding methylenetetrahydrofolate dehydrogenase).Conclusions/interpretationDownregulation of the acetyl-CoA network in VAT and SAT is an important feature in the pathophysiology of type 2 diabetes in obese individuals. ACAT1, ACACA, ALDH6A1 and MTHFD1 represent novel biomarkers in adipose tissue associated with type 2 diabetes in obese individuals.

A formalized description of the standard human variant nomenclature in Extended Backus-Naur Form

BackgroundThe use of a standard human sequence variant nomenclature is advocated by the Human Genome Variation Society in order to unambiguously describe genetic variants in databases and literature. There is a clear need for tools that allow the mining of data about human sequence variants and their functional consequences from databases and literature. Existing text mining focuses on the recognition of protein variants and their effects. The recognition of variants at the DNA and RNA levels is essential for dissemination of variant data for diagnostic purposes. Development of new tools is hampered by the complexity of the current nomenclature, which requires processing at the character level to recognize the specific syntactic constructs used in variant descriptions.ResultsWe approached the gene variant nomenclature as a scientific sublanguage and created two formal descriptions of the syntax in Extended Backus-Naur Form: one at the DNA-RNA level and one at the protein level. To ensure compatibility to older versions of the human sequence variant nomenclature, previously recommended variant description formats have been included. The first grammar versions were designed to help build variant description handling in the Alamut mutation interpretation software. The DNA and RNA level descriptions were then updated and used to construct the context-free parser of the Mutalyzer 2 sequence variant nomenclature checker, which has already been used to check more than one million variant descriptions.ConclusionsThe Extended Backus-Naur Form provided an overview of the full complexity of the syntax of the sequence variant nomenclature, which remained hidden in the textual format and the division of the recommendations across the DNA, RNA and protein sections of the Human Genome Variation Society nomenclature website (http://www.hgvs.org/mutnomen/). This insight into the syntax of the nomenclature could be used to design detailed and clear rules for software development. The Mutalyzer 2 parser demonstrated that it facilitated decomposition of complex variant descriptions into their individual parts. The Extended Backus-Naur Form or parts of it can be used or modified by adding rules, allowing the development of specific sequence variant text mining tools and other programs, which can generate or handle sequence variant descriptions.

SplicePie: a novel analytical approach for the detection of alternative, non-sequential and recursive splicing

Alternative splicing is a powerful mechanism present in eukaryotic cells to obtain a wide range of transcripts and protein isoforms from a relatively small number of genes. The mechanisms regulating (alternative) splicing and the paradigm of consecutive splicing have recently been challenged, especially for genes with a large number of introns. RNA-Seq, a powerful technology using deep sequencing in order to determine transcript structure and expression levels, is usually performed on mature mRNA, therefore not allowing detailed analysis of splicing progression. Sequencing pre-mRNA at different stages of splicing potentially provides insight into mRNA maturation. Although the number of tools that analyze total and cytoplasmic RNA in order to elucidate the transcriptome composition is rapidly growing, there are no tools specifically designed for the analysis of nuclear RNA (which contains mixtures of pre- and mature mRNA). We developed dedicated algorithms to investigate the splicing process. In this paper, we present a new classification of RNA-Seq reads based on three major stages of splicing: pre-, intermediate- and post-splicing. Applying this novel classification we demonstrate the possibility to analyze the order of splicing. Furthermore, we uncover the potential to investigate the multi-step nature of splicing, assessing various types of recursive splicing events. We provide the data that gives biological insight into the order of splicing, show that non-sequential splicing of certain introns is reproducible and coinciding in multiple cell lines. We validated our observations with independent experimental technologies and showed the reliability of our method. The pipeline, named SplicePie, is freely available at: https://github.com/pulyakhina/splicing_analysis_pipeline. The example data can be found at: https://barmsijs.lumc.nl/HG/irina/example_data.tar.gz.

Determining the quality and complexity of next-generation sequencing data without a reference genome

We describe an open-source kPAL package that facilitates an alignment-free assessment of the quality and comparability of sequencing datasets by analyzing k-mer frequencies. We show that kPAL can detect technical artefacts such as high duplication rates, library chimeras, contamination and differences in library preparation protocols. kPAL also successfully captures the complexity and diversity of microbiomes and provides a powerful means to study changes in microbial communities. Together, these features make kPAL an attractive and broadly applicable tool to determine the quality and comparability of sequence libraries even in the absence of a reference sequence. kPAL is freely available at https://github.com/LUMC/kPAL.

The Implicitome: A Resource for Rationalizing Gene-Disease Associations

High-throughput experimental methods such as medical sequencing and genome-wide association studies (GWAS) identify increasingly large numbers of potential relations between genetic variants and diseases. Both biological complexity (millions of potential gene-disease associations) and the accelerating rate of data production necessitate computational approaches to prioritize and rationalize potential gene-disease relations. Here, we use concept profile technology to expose from the biomedical literature both explicitly stated gene-disease relations (the explicitome) and a much larger set of implied gene-disease associations (the implicitome). Implicit relations are largely unknown to, or are even unintended by the original authors, but they vastly extend the reach of existing biomedical knowledge for identification and interpretation of gene-disease associations. The implicitome can be used in conjunction with experimental data resources to rationalize both known and novel associations. We demonstrate the usefulness of the implicitome by rationalizing known and novel gene-disease associations, including those from GWAS. To facilitate the re-use of implicit gene-disease associations, we publish our data in compliance with FAIR Data Publishing recommendations [https://www.force11.org/group/fairgroup] using nanopublications. An online tool (http://knowledge.bio) is available to explore established and potential gene-disease associations in the context of other biomedical relations.