The loss and gain of functional amino acid residues is a common mechanism causing human inherited disease

Elucidating the precise molecular events altered by disease-causing genetic variants represents a major challenge in translational bioinformatics. To this end, many studies have investigated the structural and functional impact of amino acid substitutions. Most of these studies were however limited in scope to either individual molecular functions or were concerned with functional effects (e.g. deleterious vs. neutral) without specifically considering possible molecular alterations. The recent growth of structural, molecular and genetic data presents an opportunity for more comprehensive studies to consider the structural environment of a residue of interest, to hypothesize specific molecular effects of sequence variants and to statistically associate these effects with genetic disease. In this study, we analyzed data sets of disease-causing and putatively neutral human variants mapped to protein 3D structures as part of a systematic study of the loss and gain of various types of functional attribute potentially underlying pathogenic molecular alterations. We first propose a formal model to assess probabilistically function-impacting variants. We then develop an array of structure-based functional residue predictors, evaluate their performance, and use them to quantify the impact of disease-causing amino acid substitutions on catalytic activity, metal binding, macromolecular binding, ligand binding, allosteric regulation and post-translational modifications. We show that our methodology generates actionable biological hypotheses for up to 41% of disease-causing genetic variants mapped to protein structures suggesting that it can be reliably used to guide experimental validation. Our results suggest that a significant fraction of disease-causing human variants mapping to protein structures are function-altering both in the presence and absence of stability disruption

The sequencing and interpretation of the genome obtained from a Serbian individual

Recent genetic studies and whole-genome sequencing projects have greatly improved our understanding of human variation and clinically actionable genetic information. Smaller ethnic populations, however, remain underrepresented in both individual and large-scale sequencing efforts and hence present an opportunity to discover new variants of biomedical and demographic significance. This report describes the sequencing and analysis of a genome obtained from an individual of Serbian origin, introducing tens of thousands of previously unknown variants to the currently available pool. Ancestry analysis places this individual in close proximity of the Central and Eastern European populations; i.e., closest to Croatian, Bulgarian and Hungarian individuals and, in terms of other Europeans, furthest from Ashkenazi Jewish, Spanish, Sicilian, and Baltic individuals. Our analysis confirmed gene flow between Neanderthal and ancestral pan-European populations, with similar contributions to the Serbian genome as those observed in other European groups. Finally, to assess the burden of potentially disease-causing/clinically relevant variation in the sequenced genome, we utilized manually curated genotype-phenotype association databases and variant-effect predictors. We identified several variants that have previously been associated with severe early-onset disease that is not evident in the proband, as well as variants that could yet prove to be clinically relevant to the proband over the next decades. The presence of numerous private and low-frequency variants along with the observed and predicted disease-causing mutations in this genome exemplify some of the global challenges of genome interpretation, especially in the context of understudied ethnic groups.Comment: 18 pages, 2 figure

The sequencing and interpretation of the genome obtained from a Serbian individual

Recent genetic studies and whole-genome sequencing projects have greatly improved our understanding of human variation and clinically actionable genetic information. Smaller ethnic populations, however, remain underrepresented in both individual and large-scale sequencing efforts and hence present an opportunity to discover new variants of biomedical and demographic significance. This report describes the sequencing and analysis of a genome obtained from an individual of Serbian origin, introducing tens of thousands of previously unknown variants to the currently available pool. Ancestry analysis places this individual in close proximity to Central and Eastern European populations; i.e., closest to Croatian, Bulgarian and Hungarian individuals and, in terms of other Europeans, furthest from Ashkenazi Jewish, Spanish, Sicilian and Baltic individuals. Our analysis confirmed gene flow between Neanderthal and ancestral pan-European populations, with similar contributions to the Serbian genome as those observed in other European groups. Finally, to assess the burden of potentially disease-causing/clinically relevant variation in the sequenced genome, we utilized manually curated genotype-phenotype association databases and variant-effect predictors. We identified several variants that have previously been associated with severe early-onset disease that is not evident in the proband, as well as putatively impactful variants that could yet prove to be clinically relevant to the proband over the next decades. The presence of numerous private and low-frequency variants, along with the observed and predicted disease-causing mutations in this genome, exemplify some of the global challenges of genome interpretation, especially in the context of under-studied ethnic groups

Inferring the molecular and phenotypic impact of amino acid variants with MutPred2

Identifying pathogenic variants and underlying functional alterations is challenging. To this end, we introduce MutPred2, a tool that improves the prioritization of pathogenic amino acid substitutions over existing methods, generates molecular mechanisms potentially causative of disease, and returns interpretable pathogenicity score distributions on individual genomes. Whilst its prioritization performance is state-of-the-art, a distinguishing feature of MutPred2 is the probabilistic modeling of variant impact on specific aspects of protein structure and function that can serve to guide experimental studies of phenotype-altering variants. We demonstrate the utility of MutPred2 in the identification of the structural and functional mutational signatures relevant to Mendelian disorders and the prioritization of de novo mutations associated with complex neurodevelopmental disorders. We then experimentally validate the functional impact of several variants identified in patients with such disorders. We argue that mechanism-driven studies of human inherited disease have the potential to significantly accelerate the discovery of clinically actionable variants

Alu insertion polymorphisms shared by Papio baboons and Theropithecus gelada reveal an intertwined common ancestry

© 2019 The Author(s). Background: Baboons (genus Papio) and geladas (Theropithecus gelada) are now generally recognized as close phylogenetic relatives, though morphologically quite distinct and generally classified in separate genera. Primate specific Alu retrotransposons are well-established genomic markers for the study of phylogenetic and population genetic relationships. We previously reported a computational reconstruction of Papio phylogeny using large-scale whole genome sequence (WGS) analysis of Alu insertion polymorphisms. Recently, high coverage WGS was generated for Theropithecus gelada. The objective of this study was to apply the high-Throughput poly-Detect method to computationally determine the number of Alu insertion polymorphisms shared by T. gelada and Papio, and vice versa, by each individual Papio species and T. gelada. Secondly, we performed locus-specific polymerase chain reaction (PCR) assays on a diverse DNA panel to complement the computational data. Results: We identified 27,700 Alu insertions from T. gelada WGS that were also present among six Papio species, with nearly half (12,956) remaining unfixed among 12 Papio individuals. Similarly, each of the six Papio species had species-indicative Alu insertions that were also present in T. gelada. In general, P. kindae shared more insertion polymorphisms with T. gelada than did any of the other five Papio species. PCR-based genotype data provided additional support for the computational findings. Conclusions: Our discovery that several thousand Alu insertion polymorphisms are shared by T. gelada and Papio baboons suggests a much more permeable reproductive barrier between the two genera then previously suspected. Their intertwined evolution likely involves a long history of admixture, gene flow and incomplete lineage sorting

Pathogenicity and functional impact of non-frameshifting insertion/deletion variation in the human genome.

Differentiation between phenotypically neutral and disease-causing genetic variation remains an open and relevant problem. Among different types of variation, non-frameshifting insertions and deletions (indels) represent an understudied group with widespread phenotypic consequences. To address this challenge, we present a machine learning method, MutPred-Indel, that predicts pathogenicity and identifies types of functional residues impacted by non-frameshifting insertion/deletion variation. The model shows good predictive performance as well as the ability to identify impacted structural and functional residues including secondary structure, intrinsic disorder, metal and macromolecular binding, post-translational modifications, allosteric sites, and catalytic residues. We identify structural and functional mechanisms impacted preferentially by germline variation from the Human Gene Mutation Database, recurrent somatic variation from COSMIC in the context of different cancers, as well as de novo variants from families with autism spectrum disorder. Further, the distributions of pathogenicity prediction scores generated by MutPred-Indel are shown to differentiate highly recurrent from non-recurrent somatic variation. Collectively, we present a framework to facilitate the interrogation of both pathogenicity and the functional effects of non-frameshifting insertion/deletion variants. The MutPred-Indel webserver is available at http://mutpred.mutdb.org/

Summary of amino acid substitution (AAS) data sets.

<p>Summary of amino acid substitution (AAS) data sets.</p

Performance assessment of structural and functional residue predictors using cross-validation on positive-unlabeled data sets.

<p>Performance assessment of structural and functional residue predictors using cross-validation on positive-unlabeled data sets.</p

3D visualization of protein structures with experimentally supported loss and gain of function predictions.

<p>Left: SOD1 protein (chain A of PDB entry 2xjl) where residues H63, H71, H80 and D83 form a zinc binding pocket. The substitution D83G gives rise to a loss of zinc binding. Right: CA2 protein (chain A of PDB entry 1fqr) where H94, H96 and H119 are zinc-binding sites. Mutation T198E leads to an increase in zinc affinity.</p