PHACTboost: A Phylogeny-Aware Pathogenicity Predictor for Missense Mutations via Boosting.

Most algorithms that are used to predict the effects of variants rely on evolutionary conservation. However, a majority of such techniques compute evolutionary conservation by solely using the alignment of multiple sequences while overlooking the evolutionary context of substitution events. We had introduced PHACT, a scoring-based pathogenicity predictor for missense mutations that can leverage phylogenetic trees, in our previous study. By building on this foundation, we now propose PHACTboost, a gradient boosting tree-based classifier that combines PHACT scores with information from multiple sequence alignments, phylogenetic trees, and ancestral reconstruction. By learning from data, PHACTboost outperforms PHACT. Furthermore, the results of comprehensive experiments on carefully constructed sets of variants demonstrated that PHACTboost can outperform 40 prevalent pathogenicity predictors reported in the dbNSFP, including conventional tools, metapredictors, and deep learning-based approaches as well as more recent tools such as AlphaMissense, EVE, and CPT-1. The superiority of PHACTboost over these methods was particularly evident in case of hard variants for which different pathogenicity predictors offered conflicting results. We provide predictions of 215 million amino acid alterations over 20,191 proteins. PHACTboost is available at https://github.com/CompGenomeLab/PHACTboost. PHACTboost can improve our understanding of genetic diseases and facilitate more accurate diagnoses.

PHACT: Phylogeny-Aware Computing of Tolerance for Missense Mutations.

Evolutionary conservation is a fundamental resource for predicting the substitutability of amino acids and the loss of function in proteins. The use of multiple sequence alignment alone-without considering the evolutionary relationships among sequences-results in the redundant counting of evolutionarily related alteration events, as if they were independent. Here, we propose a new method, PHACT, that predicts the pathogenicity of missense mutations directly from the phylogenetic tree of proteins. PHACT travels through the nodes of the phylogenetic tree and evaluates the deleteriousness of a substitution based on the probability differences of ancestral amino acids between neighboring nodes in the tree. Moreover, PHACT assigns weights to each node in the tree based on their distance to the query organism. For each potential amino acid substitution, the algorithm generates a score that is used to calculate the effect of substitution on protein function. To analyze the predictive performance of PHACT, we performed various experiments over the subsets of two datasets that include 3,023 proteins and 61,662 variants in total. The experiments demonstrated that our method outperformed the widely used pathogenicity prediction tools (i.e., SIFT and PolyPhen-2) and achieved a better predictive performance than other conventional statistical approaches presented in dbNSFP. The PHACT source code is available at https://github.com/CompGenomeLab/PHACT.

Phylogenetic analysis of SARS-CoV-2 genomes in Turkey.

COVID-19 has effectively spread worldwide. As of May 2020, Turkey is among the top ten countries with the most cases. A comprehensive genomic characterization of the virus isolates in Turkey is yet to be carried out. Here, we built a phylogenetic tree with globally obtained 15,277 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes. We identified the subtypes based on the phylogenetic clustering in comparison with the previously annotated classifications. We performed a phylogenetic analysis of the first 30 SARS-CoV-2 genomes isolated and sequenced in Turkey. We suggest that the first introduction of the virus to the country is earlier than the first reported case of infection. Virus genomes isolated from Turkey are dispersed among most types in the phylogenetic tree. We find 2 of the seventeen subclusters enriched with the isolates of Turkey, which likely have spread expansively in the country. Finally, we traced virus genomes based on their phylogenetic placements. This analysis suggested multiple independent international introductions of the virus and revealed a hub for the inland transmission. We released a web application to track the global and interprovincial virus spread of the isolates from Turkey in comparison to thousands of genomes worldwide.

SURF1 related Leigh syndrome: Clinical and molecular findings of 16 patients from Turkey.

INTRODUCTION: Pathogenic variants in SURF1, a nuclear-encoded gene encoding a mitochondrial chaperone involved in COX assembly, are one of the most common causes of Leigh syndrome (LS). MATERIAL-METHODS: Sixteen patients diagnosed to have SURF1-related LS between 2012 and 2020 were included in the study. Their clinical, biochemical and molecular findings were recorded. 10/16 patients were diagnosed using whole-exome sequencing (WES), 4/16 by Sanger sequencing of SURF1, 1/16 via targeted exome sequencing and 1/16 patient with whole-genome sequencing (WGS). The pathogenicity of SURF1 variants was evaluated by phylogenetic studies and modelling on the 3D structure of the SURF1 protein. RESULTS: We identified 16 patients from 14 unrelated families who were either homozygous or compound heterozygous for SURF1 pathogenic variants. Nine different SURF1 variants were detected The c.769G > A was the most common variant with an allelic frequency of 42.8% (12/28), c.870dupT [(p.Lys291*); (8/28 28.5%)], c.169delG [(p.Glu57Lysfs*15), (2/24; 7.1%)], c.532 T > A [(p.Tyr178Asn); (2/28, 7.1%)], c.653_654delCT [(p.Pro218Argfs*29); (4/28, 14.2%)] c.595_597delGGA [(p.Gly199del); (1/28, 3.5%)], c.751 + 1G > A (2/28, 4.1%), c.356C > T [(p.Pro119Leu); (2/28, 3.5%)] were the other detected variants. Two pathogenic variants, C.595_597delGGA and c.356C > T, were detected for the first time. The c.769 G > A variant detected in 6 patients from 5 families was evaluated in terms of phenotype-genotype correlation. There was no definite genotype - phenotype correlation. CONCLUSIONS: To date, more than 120 patients of LS with SURF1 pathogenic variants have been reported. We shared the clinical, molecular data and natural course of 16 new SURF1 defect patients from our country. This study is the first comprehensive research from Turkey that provides information about disease-causing variants in the SURF1 gene. The identification of common variants and phenotype of the SURF1 gene is important for understanding SURF1 related LS. SYNOPSIS: SURF1 gene defects are one of the most important causes of LS; patients have a homogeneous clinical and biochemical phenotype.