Mutalyzer 2: next generation HGVS nomenclature checker.

MOTIVATION: Unambiguous variant descriptions are of utmost importance in clinical genetic diagnostics, scientific literature and genetic databases. The Human Genome Variation Society (HGVS) publishes a comprehensive set of guidelines on how variants should be correctly and unambiguously described. We present the implementation of the Mutalyzer 2 tool suite, designed to automatically apply the HGVS guidelines so users do not have to deal with the HGVS intricacies explicitly to check and correct their variant descriptions. RESULTS: Mutalyzer is profusely used by the community, having processed over 133 million descriptions since its launch. Over a five year period, Mutalyzer reported a correct input in ∼50% of cases. In 41% of the cases either a syntactic or semantic error was identified and for ∼7% of cases, Mutalyzer was able to automatically correct the description. AVAILABILITY AND IMPLEMENTATION: Mutalyzer is an Open Source project under the GNU Affero General Public License. The source code is available on GitHub (https://github.com/mutalyzer/mutalyzer) and a running instance is available at: https://mutalyzer.nl.

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.

A SNP panel for identification of DNA and RNA specimens.

BACKGROUND: SNP panels that uniquely identify an individual are useful for genetic and forensic research. Previously recommended SNP panels are based on DNA profiles and mostly contain intragenic SNPs. With the increasing interest in RNA expression profiles, we aimed for establishing a SNP panel for both DNA and RNA-based genotyping. RESULTS: To determine a small set of SNPs with maximally discriminative power, genotype calls were obtained from DNA and blood-derived RNA sequencing data belonging to healthy, geographically dispersed, Dutch individuals. SNPs were selected based on different criteria like genotype call rate, minor allele frequency, Hardy-Weinberg equilibrium and linkage disequilibrium. A panel of 50 SNPs was sufficient to identify an individual uniquely: the probability of identity was 6.9 × 10- 20 when assuming no family relations and 1.2 × 10- 10 when accounting for the presence of full sibs. The ability of the SNP panel to uniquely identify individuals on DNA and RNA level was validated in an independent population dataset. The panel is applicable to individuals from European descent, with slightly lower power in non-Europeans. Whereas most of the genes containing the 50 SNPs are expressed in various tissues, our SNP panel needs optimization for other tissues than blood. CONCLUSIONS: This first DNA/RNA SNP panel will be useful to identify sample mix-ups in biomedical research and for assigning DNA and RNA stains in crime scenes to unique individuals.

An efficient algorithm for the extraction of HGVS variant descriptions from sequences.

MOTIVATION: Unambiguous sequence variant descriptions are important in reporting the outcome of clinical diagnostic DNA tests. The standard nomenclature of the Human Genome Variation Society (HGVS) describes the observed variant sequence relative to a given reference sequence. We propose an efficient algorithm for the extraction of HGVS descriptions from two sequences with three main requirements in mind: minimizing the length of the resulting descriptions, minimizing the computation time and keeping the unambiguous descriptions biologically meaningful. RESULTS: Our algorithm is able to compute the HGVS descriptions of complete chromosomes or other large DNA strings in a reasonable amount of computation time and its resulting descriptions are relatively small. Additional applications include updating of gene variant database contents and reference sequence liftovers. AVAILABILITY: The algorithm is accessible as an experimental service in the Mutalyzer program suite (https://mutalyzer.nl). The C++ source code and Python interface are accessible at: https://github.com/mutalyzer/description-extractor. CONTACT: j.k.vis@lumc.nl.

Full-length mRNA sequencing uncovers a widespread coupling between transcription initiation and mRNA processing.

BACKGROUND: The multifaceted control of gene expression requires tight coordination of regulatory mechanisms at transcriptional and post-transcriptional level. Here, we studied the interdependence of transcription initiation, splicing and polyadenylation events on single mRNA molecules by full-length mRNA sequencing. RESULTS: In MCF-7 breast cancer cells, we find 2700 genes with interdependent alternative transcription initiation, splicing and polyadenylation events, both in proximal and distant parts of mRNA molecules, including examples of coupling between transcription start sites and polyadenylation sites. The analysis of three human primary tissues (brain, heart and liver) reveals similar patterns of interdependency between transcription initiation and mRNA processing events. We predict thousands of novel open reading frames from full-length mRNA sequences and obtained evidence for their translation by shotgun proteomics. The mapping database rescues 358 previously unassigned peptides and improves the assignment of others. By recognizing sample-specific amino-acid changes and novel splicing patterns, full-length mRNA sequencing improves proteogenomics analysis of MCF-7 cells. CONCLUSIONS: Our findings demonstrate that our understanding of transcriptome complexity is far from complete and provides a basis to reveal largely unresolved mechanisms that coordinate transcription initiation and mRNA processing.

Identification of context-dependent expression quantitative trait loci in whole blood.

Genetic risk factors often localize to noncoding regions of the genome with unknown effects on disease etiology. Expression quantitative trait loci (eQTLs) help to explain the regulatory mechanisms underlying these genetic associations. Knowledge of the context that determines the nature and strength of eQTLs may help identify cell types relevant to pathophysiology and the regulatory networks underlying disease. Here we generated peripheral blood RNA-seq data from 2,116 unrelated individuals and systematically identified context-dependent eQTLs using a hypothesis-free strategy that does not require previous knowledge of the identity of the modifiers. Of the 23,060 significant cis-regulated genes (false discovery rate (FDR) ≤ 0.05), 2,743 (12%) showed context-dependent eQTL effects. The majority of these effects were influenced by cell type composition. A set of 145 cis-eQTLs depended on type I interferon signaling. Others were modulated by specific transcription factors binding to the eQTL SNPs.

Disease variants alter transcription factor levels and methylation of their binding sites.

Most disease-associated genetic variants are noncoding, making it challenging to design experiments to understand their functional consequences. Identification of expression quantitative trait loci (eQTLs) has been a powerful approach to infer the downstream effects of disease-associated variants, but most of these variants remain unexplained. The analysis of DNA methylation, a key component of the epigenome, offers highly complementary data on the regulatory potential of genomic regions. Here we show that disease-associated variants have widespread effects on DNA methylation in trans that likely reflect differential occupancy of trans binding sites by cis-regulated transcription factors. Using multiple omics data sets from 3,841 Dutch individuals, we identified 1,907 established trait-associated SNPs that affect the methylation levels of 10,141 different CpG sites in trans (false discovery rate (FDR) < 0.05). These included SNPs that affect both the expression of a nearby transcription factor (such as NFKB1, CTCF and NKX2-3) and methylation of its respective binding site across the genome. Trans methylation QTLs effectively expose the downstream effects of disease-associated variants.

Integrated Whole Genome and Transcriptome Analysis Identified a Therapeutic Minor Histocompatibility Antigen in a Splice Variant of ITGB2.

PURPOSE: In HLA-matched allogeneic hematopoietic stem cell transplantation (alloSCT), donor T cells recognizing minor histocompatibility antigens (MiHAs) can mediate desired antitumor immunity as well as undesired side effects. MiHAs with hematopoiesis-restricted expression are relevant targets to augment antitumor immunity after alloSCT without side effects. To identify therapeutic MiHAs, we analyzed the in vivo immune response in a patient with strong antitumor immunity after alloSCT. EXPERIMENTAL DESIGN: T-cell clones recognizing patient, but not donor, hematopoietic cells were selected for MiHA discovery by whole genome association scanning. RNA-sequence data from the GEUVADIS project were analyzed to investigate alternative transcripts, and expression patterns were determined by microarray analysis and qPCR. T-cell reactivity was measured by cytokine release and cytotoxicity. RESULTS: T-cell clones were isolated for two HLA-B*15:01-restricted MiHA. LB-GLE1-1V is encoded by a nonsynonymous SNP in exon 6 of GLE1 For the other MiHAs, an associating SNP in intron 3 of ITGB2 was found, but no SNP disparity was present in the normal gene transcript between patient and donor. RNA-sequence analysis identified an alternative ITGB2 transcript containing part of intron 3. qPCR demonstrated that this transcript is restricted to hematopoietic cells and SNP-positive individuals. In silico translation revealed LB-ITGB2-1 as HLA-B*15:01-binding peptide, which was validated as hematopoietic MiHA by T-cell experiments. CONCLUSIONS: Whole genome and transcriptome analysis identified LB-ITGB2-1 as MiHAs encoded by an alternative transcript. Our data support the therapeutic relevance of LB-ITGB2-1 and illustrate the value of RNA-sequence analysis for discovery of immune targets encoded by alternative transcripts. Clin Cancer Res; 22(16); 4185-96. ©2016 AACR.

Next-generation sequencing-based genome diagnostics across clinical genetics centers: implementation choices and their effects.

Implementation of next-generation DNA sequencing (NGS) technology into routine diagnostic genome care requires strategic choices. Instead of theoretical discussions on the consequences of such choices, we compared NGS-based diagnostic practices in eight clinical genetic centers in the Netherlands, based on genetic testing of nine pre-selected patients with cardiomyopathy. We highlight critical implementation choices, including the specific contributions of laboratory and medical specialists, bioinformaticians and researchers to diagnostic genome care, and how these affect interpretation and reporting of variants. Reported pathogenic mutations were consistent for all but one patient. Of the two centers that were inconsistent in their diagnosis, one reported to have found 'no causal variant', thereby underdiagnosing this patient. The other provided an alternative diagnosis, identifying another variant as causal than the other centers. Ethical and legal analysis showed that informed consent procedures in all centers were generally adequate for diagnostic NGS applications that target a limited set of genes, but not for exome- and genome-based diagnosis. We propose changes to further improve and align these procedures, taking into account the blurring boundary between diagnostics and research, and specific counseling options for exome- and genome-based diagnostics. We conclude that alternative diagnoses may infer a certain level of 'greediness' to come to a positive diagnosis in interpreting sequencing results. Moreover, there is an increasing interdependence of clinic, diagnostics and research departments for comprehensive diagnostic genome care. Therefore, we invite clinical geneticists, physicians, researchers, bioinformatics experts and patients to reconsider their role and position in future diagnostic genome care.

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 webcite.

The Genome of the Netherlands: design, and project goals.

Within the Netherlands a national network of biobanks has been established (Biobanking and Biomolecular Research Infrastructure-Netherlands (BBMRI-NL)) as a national node of the European BBMRI. One of the aims of BBMRI-NL is to enrich biobanks with different types of molecular and phenotype data. Here, we describe the Genome of the Netherlands (GoNL), one of the projects within BBMRI-NL. GoNL is a whole-genome-sequencing project in a representative sample consisting of 250 trio-families from all provinces in the Netherlands, which aims to characterize DNA sequence variation in the Dutch population. The parent-offspring trios include adult individuals ranging in age from 19 to 87 years (mean=53 years; SD=16 years) from birth cohorts 1910-1994. Sequencing was done on blood-derived DNA from uncultured cells and accomplished coverage was 14-15x. The family-based design represents a unique resource to assess the frequency of regional variants, accurately reconstruct haplotypes by family-based phasing, characterize short indels and complex structural variants, and establish the rate of de novo mutational events. GoNL will also serve as a reference panel for imputation in the available genome-wide association studies in Dutch and other cohorts to refine association signals and uncover population-specific variants. GoNL will create a catalog of human genetic variation in this sample that is uniquely characterized with respect to micro-geographic location and a wide range of phenotypes. The resource will be made available to the research and medical community to guide the interpretation of sequencing projects. The present paper summarizes the global characteristics of the project.