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Precision medicine and sequence-based clinical diagnostics seek to predict disease risk or to identify causative variants from sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype-phenotype prediction challenges; participants build models, undergo assessment, and share key findings. In the past, few CAGI challenges have addressed the impact of sequence variants on splicing. In CAGI5, two challenges (Vex-seq and MaPSY) involved prediction of the effect of variants, primarily single-nucleotide changes, on splicing. Although there are significant differences between these two challenges, both involved prediction of results from high-throughput exon inclusion assays. Here, we discuss the methods used to predict the impact of these variants on splicing, their performance, strengths, and weaknesses, and prospects for predicting the impact of sequence variation on splicing and disease phenotypes.

Locus specific databases (LSDBs) make a key contribution to our understanding of heritable and acquired human disorders, disease susceptibility, and adverse drug reactions. As data have accumulated in LSDBs, a greater reliance on their use has arisen in clinical practice. Even though LSDBs have existed in recognizable form for only a quarter of a century, their origin lies in the manual cataloging of data that began around 50 years ago. Analysis and recording of sequence variation in the globin genes, and the proteins which they encode, can confidently be said to be the foundation for what we now refer to as LSDBs. Their growth over the years has primarily been underpinned by software developments and the advent of the World Wide Web. However, it is also important to recognize the evolution of reporting standards and reference sequences, without which accurate and consistent reporting of sequence variants would be impossible. Nowadays, LSDBs exist for many human protein-coding genes and the focus of efforts has moved toward minor tidying up of the variant reporting nomenclature and processes for assuring the completeness, correctness, and consistency of the data. The next 25 years will doubtless witness further developments in the evolution of LSDBs.

The 11th International Symposium on Mutations in the Genome was held on 6-10 June, 2011, in Santorini, Greece. Meeting participants described novel detection technologies, rapid advances in whole genome and whole-exome sequencing, but also highlighted the urgent need for the development of sequence variation databases and the clinical interpretation of the genomic data. This report summarizes some of the major themes presented during the meeting.

New technologies allow rapid discovery of novel sequence variants among which those involving complex structural rearrangements. The description of such complex variants challenges the existing standard sequence variation nomenclature of the Human Genome Variation Society (HGVS, http://www.hgvs.org/mutnomen), because this mainly focuses on simple variants. Here, we suggest several extensions of the HGVS nomenclature guidelines to facilitate unambiguous description of complex sequence variants at the DNA level. These include: (1) nesting to support description of changes within inversions and duplications, and (2) composite changes to support concatenation of inserted sequences. The advantage of these additions is that inversions and duplications with small differences and more complex variants can be described without reverting to the less informative indel description. In addition, they should provide sufficient flexibility and consistency, thereby limiting alternative interpretations and ambiguous descriptions. The specifications should allow easy implementation in sequence variant nomenclature checkers (e.g., Mutalyzer, http://www.mutalyzer.nl/). We are extending the functionality of Mutalyzer to incorporate the latest version of the HGVS sequence variation nomenclature guidelines.

Hybridization probe melting analysis can be complicated by the presence of sequence variation (benign polymorphisms or other mutations) near the targeted mutation. We investigated the use of "masking" probes to differentiate alleles with similar probe melting temperatures. Selected sequence variation was masked by incorporating mismatches (deletion, unmatched nucleotide, or universal base) into hybridization probes at the polymorphic location. Such masking probes create a probe/target mismatch with all possible alleles at the selected polymorphic location. Any allele with additional variation at another site is identified by a lower probe melting temperature than alleles that vary only at the masked position. This "masking technique" was applied to RET protooncogene and HPA6 mutation detection using unlabeled hybridization probes, a saturating dsDNA dye, and high-resolution melting analysis. Masking probes clearly distinguished all targeted mutations from polymorphisms when at least 1 base pair (bp) separated the mutation from the masked variation. We were able to mask polymorphisms immediately adjacent to mutations, except in certain cases, such as those involving single-base deletion probes when both adjacent positions had the same polymorphic nucleotides. The masking probes can also localize mutations to specific codons or nucleotide positions. Masking probes can simplify melting analysis of complex regions and eliminate the need for sequencing.

The completion of the human genome project has initiated, as well as provided the basis for, the collection and study of all sequence variation between individuals. Direct access to up-to-date information on sequence variation is currently provided most efficiently through web-based, gene-centered, locus-specific databases (LSDBs). We have developed the Leiden Open (source) Variation Database (LOVD) software approaching the “LSDB-in-a-Box” idea for the easy creation and maintenance of a fully web-based gene sequence variation database. LOVD is platform-independent and uses PHP and MySQL open source software only. The basic gene-centered and modular design of the database follows the recommendations of the Human Genome Variation Society (HGVS) and focuses on the collection and display of DNA sequence variations. With minimal effort, the LOVD platform is extendable with clinical data. The open set-up should both facilitate and promote functional extension with scripts written by the community. The LOVD software is freely available from the Leiden Muscular Dystrophy pages (www.DMD.nl/LOVD/). To promote the use of LOVD, we currently offer curators the possibility to set up an LSDB on our Leiden server. Hum Mutat 26(2), 1–6, 2005. © 2005 Wiley-Liss, Inc.

The sequence variation project at EBI aims to create a unified resource for browsing and searching sequence differences. Technical advances in reading in new data types and in validating and cross-referencing entries are reported. It is suggested that the hardest problems in unifying mutation databases are related to intellectual property rights. The concept of copylefting is introduced as a potential solution to these.

Nine populations (Germans, Turks, Moroccans, Ovambos, Ugandans, Chinese, Japanese, Papuans, and Australian Aborigines) were investigated using six microsatellite systems (HumCD4, Hum F13B, HumFES/FPS, HumTH01, HumVWA, and D21S11), so-called STRs (short tandem repeats). Allele frequency data and sequencing results were used to compare the population genetic diversity among these populations. The genetic differences varied depending on the STR applied. According to the systems investigated, we defined three categories of STR microvariation: LOMs (low microvariation systems), INMs (intermediate microvariation systems), and HIMs (high microvariation systems). LOMs (STRs: CD4, FES, F13B, TH01) are characterised by a number of repeats between 5–15 and a stable repeat sequence. INMs and HIMs each showed an increasing number of repeats and additional sequence variation in the repeat motifs. The rate of new mutations was associated with the extent of microvariation. The reconstruction of phylogenetic trees led to a clustering in an early split of the African populations followed by further branching of the Asian/Melanesian and the Caucasian groups. Hum Mutat 11:135–144, 1998. © 1998 Wiley-Liss, Inc.

The increasing amount of sequence data provides new opportunities and challenges to derive mechanistic models that can link sequence variations to phenotypic diversity. Here we introduce a new computational framework to suggest possible consequences of sequence variations on regulatory networks. Our method, called sTRAP (strap.molgen.mpg.de), analyses variations in the DNA sequence and predicts quantitative changes to the binding strength of any transcription factor for which there is a binding model. We have tested the method against a set of known associations between SNPs and their regulatory consequences. Our predictions are robust with respect to different parameters and model assumptions. Importantly we set an objective and quantifiable benchmark against which future improvements can be compared. Given the good performance of our method, we developed a publicly available tool that can serve as an important starting point for routine analysis of disease-associated sequence regions.

The Human Genome Variation Society (HGVS) variant nomenclature is widely used to describe sequence variants in scientific publications, clinical reports and databases. However, the HGVS recommendations are complex and this often results in inaccurate variant descriptions being reported. The open-source hgvs Python package (https://github.com/biocommons/hgvs) provides a programmatic interface for parsing, manipulating, formatting and validating of variants according to the HGVS recommendations, but does not provide a user-friendly web interface. We have developed a web-based variant validation tool, VariantValidator (https://variantvalidator.org/), which utilizes the hgvs Python package and provides additional functionality to assist users who wish to accurately describe and report sequence-level variations that are compliant with the HGVS recommendations. VariantValidator was designed to ensure that users are guided through the intricacies of the HGVS nomenclature, e.g. if the user makes a mistake, VariantValidator automatically corrects the mistake if it can, or provides helpful guidance if it cannot. In addition, VariantValidator has the facility to interconvert genomic variant descriptions in HGVS and Variant Call Format (VCF) with a degree of accuracy which surpasses most competing solutions. This article is protected by copyright. All rights reserved