Exome sequencing in extreme altitude mountaineers identifies pathogenic variants in RTEL1 and COL6A1 previously associated with respiratory failure

Adaptation of humans to challenging environmental conditions, such as extreme temperature, malnutrition, or hypoxia, is an interesting phenomenon for both basic and applied research. Identification of the genetic factors contributing to human adaptation to these conditions enhances our understanding of the underlying molecular and physiological mechanisms. In our study, we analyzed the exomes of 22 high altitude mountaineers to uncover genetic variants contributing to hypoxic adaptation. To our surprise, we identified two putative loss-of-function variants, rs1385101139 in RTEL1 and rs1002726737 in COL6A1 in two extremely high altitude (personal record of more than 8500 m) professional climbers. Both variants can be interpreted as pathogenic according to medical geneticists' guidelines, and are linked to inherited conditions involving respiratory failure (late-onset pulmonary fibrosis and severe Ullrich muscular dystrophy for rs1385101139 and rs1002726737, respectively). Our results suggest that a loss of gene function may act as an important factor of human adaptation, which is corroborated by previous reports in other human subjects.

Bioinformatics of germline variant discovery for rare disease diagnostics: current approaches and remaining challenges

Next-generation sequencing (NGS) has revolutionized the field of rare disease diagnostics. Whole exome and whole genome sequencing are now routinely used for diagnostic purposes; however, the overall diagnosis rate remains lower than expected. In this work, we review current approaches used for calling and interpretation of germline genetic variants in the human genome, and discuss the most important challenges that persist in the bioinformatic analysis of NGS data in medical genetics. We describe and attempt to quantitatively assess the remaining problems, such as the quality of the reference genome sequence, reproducible coverage biases, or variant calling accuracy in complex regions of the genome. We also discuss the prospects of switching to the complete human genome assembly or the human pan-genome and important caveats associated with such a switch. We touch on arguably the hardest problem of NGS data analysis for medical genomics, namely, the annotation of genetic variants and their subsequent interpretation. We highlight the most challenging aspects of annotation and prioritization of both coding and non-coding variants. Finally, we demonstrate the persistent prevalence of pathogenic variants in the coding genome, and outline research directions that may enhance the efficiency of NGS-based disease diagnostics.

Russian Regional Differences in Allele Frequencies of CFTR Gene Variants: Genetic Monitoring of Infertile Couples

A male factor, commonly associated with poor semen quality, is revealed in about 50% of infertile couples. CFTR gene (Cystic Fibrosis Transmembrane Conduction Regulator) variants are one of the common genetic causes of azoospermia-related male infertility. Notably, the spectrum and frequency of pathogenic CFTR variants vary between populations and geographical regions. In this work, we made an attempt to evaluate the allele frequency (AF) of 12 common CFTR variants in infertile Russian men and healthy individuals from different districts of Russia. Because of the limited number of population-based studies on Russian individuals, we characterized the population AFs based on data from the Registry of Russian cystic fibrosis (CF) patients. In addition to the CF patient registry, we estimated the local frequencies of the same set of variants based on the results of genotyping of CF patients in local biocollections (from St. Petersburg and Yugra regions). AFs of common CFTR variants calculated based on registry and biocollection data showed good concordance with directly measured population AFs. The estimated region-specific frequencies of CFTR variants allowed us to uncover statistically significant regional differences in the frequencies of the F508del (c.1521_1523del; p.Phe508del) and CFTRdele2,3(21kb) (c.54-5940_273+10250del21kb; p.Ser18ArgfsX) variants. The data from population-based studies confirmed previous observations that F508del, CFTRdele2,3(21kb), and L138ins (c.413_415dup; p.Leu138dup)variants are the most abundant among infertile patients, and their frequencies are significantly lower in healthy individuals and should be taken into account during genetic monitoring of the reproductive health of Russian individuals.

bioGWAS: A Simple and Flexible Tool for Simulating GWAS Datasets

Genome-wide association studies (GWAS) have proven to be a powerful tool for the identification of genetic susceptibility loci affecting human complex traits. In addition to pinpointing individual genes involved in a particular trait, GWAS results can be used to discover relevant biological processes for these traits. The development of new tools for extracting such information from GWAS results requires large-scale datasets with known biological ground truth. Simulation of GWAS results is a powerful method that may provide such datasets and facilitate the development of new methods. In this work, we developed bioGWAS, a simple and flexible pipeline for the simulation of genotypes, phenotypes, and GWAS summary statistics. Unlike existing methods, bioGWAS can be used to generate GWAS results for simulated quantitative and binary traits with a predefined set of causal genetic variants and/or molecular pathways. We demonstrate that the proposed method can recapitulate complete GWAS datasets using a set of reported genome-wide associations. We also used our method to benchmark several tools for gene set enrichment analysis for GWAS data. Taken together, our results suggest that bioGWAS provides an important set of functionalities that would aid the development of new methods for downstream processing of GWAS results.

The Landscape of Point Mutations in Human Protein Coding Genes Leading to Pregnancy Loss

Pregnancy loss is the most frequent complication of a pregnancy which is devastating for affected families and poses a significant challenge for the health care system. Genetic factors are known to play an important role in the etiology of pregnancy loss; however, despite advances in diagnostics, the causes remain unexplained in more than 30% of cases. In this review, we aggregated the results of the decade-long studies into the genetic risk factors of pregnancy loss (including miscarriage, termination for fetal abnormality, and recurrent pregnancy loss) in euploid pregnancies, focusing on the spectrum of point mutations associated with these conditions. We reviewed the evolution of molecular genetics methods used for the genetic research into causes of pregnancy loss, and collected information about 270 individual genetic variants in 196 unique genes reported as genetic cause of pregnancy loss. Among these, variants in 18 genes have been reported by multiple studies, and two or more variants were reported as causing pregnancy loss for 57 genes. Further analysis of the properties of all known pregnancy loss genes showed that they correspond to broadly expressed, highly evolutionary conserved genes involved in crucial cell differentiation and developmental processes and related signaling pathways. Given the features of known genes, we made an effort to construct a list of candidate genes, variants in which may be expected to contribute to pregnancy loss. We believe that our results may be useful for prediction of pregnancy loss risk in couples, as well as for further investigation and revealing genetic etiology of pregnancy loss.

Plasma microRNA Profiling in Type 2 Diabetes Mellitus: A Pilot Study

Type 2 diabetes mellitus (T2D) is a chronic metabolic disease characterized by insulin resistance and β-cell dysfunction and leading to many micro- and macrovascular complications. In this study we analyzed the circulating miRNA expression profiles in plasma samples from 44 patients with T2D and 22 healthy individuals using next generation sequencing and detected 229 differentially expressed miRNAs. An increased level of miR-5588-5p, miR-125b-2-3p, miR-1284, and a reduced level of miR-496 in T2D patients was verified. We also compared the expression landscapes in the same group of patients depending on body mass index and identified differential expression of miR-144-3p and miR-99a-5p in obese individuals. Identification and functional analysis of putative target genes was performed for miR-5588-5p, miR-125b-2-3p, miR-1284, and miR-496, showing chromatin modifying enzymes and apoptotic genes being among the significantly enriched pathways.

Statistical Dissection of the Genetic Determinants of Phenotypic Heterogeneity in Genes with Multiple Associated Rare Diseases

Phenotypicheterogeneity is a phenomenon in which distinct phenotypes can develop in individuals bearing pathogenic variants in the same gene. Genetic factors, gene interactions, and environmental factors are usually considered the key mechanisms of this phenomenon. Phenotypic heterogeneity may impact the prognosis of the disease severity and symptoms. In our work, we used publicly available data on the association between genetic variants and Mendelian disease to investigate the genetic factors (such as the intragenic localization and type of a variant) driving the heterogeneity of gene-disease relationships. First, we showed that genes linked to multiple rare diseases (GMDs) are more constrained and tend to encode more transcripts with high levels of expression across tissues. Next, we assessed the role of variant localization and variant types in specifying the exact phenotype for GMD variants. We discovered that none of these factors is sufficient to explain the phenomenon of such heterogeneous gene-disease relationships. In total, we identified only 38 genes with a weak trend towards significant differences in variant localization and 30 genes with nominal significant differences in variant type for the two associated disorders. Remarkably, four of these genes showed significant differences in both tests. At the same time, our analysis suggests that variant localization and type are more important for genes linked to autosomal dominant disease. Taken together, our results emphasize the gene-level factors dissecting distinct Mendelian diseases linked to one common gene based on open-access genetic data and highlight the importance of exploring other factors that contributed to phenotypic heterogeneity.

Current Status and Prospects of the Single-Cell Sequencing Technologies for Revealing the Pathogenesis of Pregnancy-Associated Disorders

Single-cell RNA sequencing (scRNA-seq) is a method that focuses on the analysis of gene expression profile in individual cells. This method has been successfully applied to answer the challenging questions of the pathogenesis of multifactorial diseases and open up new possibilities in the prognosis and prevention of reproductive diseases. In this article, we have reviewed the application of scRNA-seq to the analysis of the various cell types and their gene expression changes in normal pregnancy and pregnancy complications. The main principle, advantages, and limitations of single-cell technologies and data analysis methods are described. We discuss the possibilities of using the scRNA-seq method for solving the fundamental and applied tasks related to various pregnancy-associated disorders. Finally, we provide an overview of the scRNA-seq findings for the common pregnancy-associated conditions, such as hyperglycemia in pregnancy, recurrent pregnancy loss, preterm labor, polycystic ovary syndrome, and pre-eclampsia.

Biobanking as a Tool for Genomic Research: From Allele Frequencies to Cross-Ancestry Association Studies

In recent years, great advances have been made in the field of collection, storage, and analysis of biological samples. Large collections of samples, biobanks, have been established in many countries. Biobanks typically collect large amounts of biological samples and associated clinical information; the largest collections include over a million samples. In this review, we summarize the main directions in which biobanks aid medical genetics and genomic research, from providing reference allele frequency information to allowing large-scale cross-ancestry meta-analyses. The largest biobanks greatly vary in the size of the collection, and the amount of available phenotype and genotype data. Nevertheless, all of them are extensively used in genomics, providing a rich resource for genome-wide association analysis, genetic epidemiology, and statistical research into the structure, function, and evolution of the human genome. Recently, multiple research efforts were based on trans-biobank data integration, which increases sample size and allows for the identification of robust genetic associations. We provide prominent examples of such data integration and discuss important caveats which have to be taken into account in trans-biobank research.

Aggregation of Genome-Wide Association Data from FinnGen and UK Biobank Replicates Multiple Risk Loci for Pregnancy Complications

Complications endangering mother or fetus affect around one in seven pregnant women. Investigation of the genetic susceptibility to such diseases is of high importance for better understanding of the disease biology as well as for prediction of individual risk. In this study, we collected and analyzed GWAS summary statistics from the FinnGen cohort and UK Biobank for 24 pregnancy complications. In FinnGen, we identified 11 loci associated with pregnancy hypertension, excessive vomiting, and gestational diabetes. When UK Biobank and FinnGen data were combined, we discovered six loci reaching genome-wide significance in the meta-analysis. These include rs35954793 in FGF5 (p=6.1×10-9), rs10882398 in PLCE1 (p=8.9×10-9), and rs167479 in RGL3 (p=5.2×10-9) for pregnancy hypertension, rs10830963 in MTNR1B (p=4.5×10-41) and rs36090025 in TCF7L2 (p=3.4×10-15) for gestational diabetes, and rs2963457 in the EBF1 locus (p=6.5×10-9) for preterm birth. In addition to the identified genome-wide associations, we also replicated 14 out of 40 previously reported GWAS markers for pregnancy complications, including four more preeclampsia-related variants. Finally, annotation of the GWAS results identified a causal relationship between gene expression in the cervix and gestational hypertension, as well as both known and previously uncharacterized genetic correlations between pregnancy complications and other traits. These results suggest new prospects for research into the etiology and pathogenesis of pregnancy complications, as well as early risk prediction for these disorders.

Genetic and Phenotypic Factors Affecting Glycemic Response to Metformin Therapy in Patients with Type 2 Diabetes Mellitus

Metformin is an oral hypoglycemic agent widely used in clinical practice for treatment of patients with type 2 diabetes mellitus (T2DM). The wide interindividual variability of response to metformin therapy was shown, and recently the impact of several genetic variants was reported. To assess the independent and combined effect of the genetic polymorphism on glycemic response to metformin, we performed an association analysis of the variants in ATM, SLC22A1, SLC47A1, and SLC2A2 genes with metformin response in 299 patients with T2DM. Likewise, the distribution of allele and genotype frequencies of the studied gene variants was analyzed in an extended group of patients with T2DM (n = 464) and a population group (n = 129). According to our results, one variant, rs12208357 in the SLC22A1 gene, had a significant impact on response to metformin in T2DM patients. Carriers of TT genotype and T allele had a lower response to metformin compared to carriers of CC/CT genotypes and C allele (p-value = 0.0246, p-value = 0.0059, respectively). To identify the parameters that had the greatest importance for the prediction of the therapy response to metformin, we next built a set of machine learning models, based on the various combinations of genetic and phenotypic characteristics. The model based on a set of four parameters, including gender, rs12208357 genotype, familial T2DM background, and waist–hip ratio (WHR) showed the highest prediction accuracy for the response to metformin therapy in patients with T2DM (AUC = 0.62 in cross-validation). Further pharmacogenetic studies may aid in the discovery of the fundamental mechanisms of type 2 diabetes, the identification of new drug targets, and finally, it could advance the development of personalized treatment.

Molecular Genetics and Pathogenesis of the Floating Harbor Syndrome: Case Report of Long-Term Growth Hormone Treatment and a Literature Review

Introduction: Floating Harbor syndrome (FHS) is an extremely rare disorder, with slightly more than a hundred cases reported worldwide. FHS is caused by heterozygous mutations in the SRCAP gene; however, little is known about the pathogenesis of FHS or the effectiveness of its treatment.

Methods: Whole-exome sequencing (WES) was performed for the definitive molecular diagnosis of the disease. Identified variants were validated using Sanger sequencing. In addition, systematic literature and public data on genetic variation in SRCAP and the effects of growth hormone (GH) treatment was conducted.

Results: We herein report the first case of FHS in the Russian Federation. The male proband presented with most of the typical phenotypic features of FHS, including short stature, skeletal and facial features, delayed growth and bone age, high pitched voice, and intellectual impairment. The proband also had partial growth hormone deficiency. We report the history of treatment of the proband with GH, which resulted in modest improvement in growth prior to puberty. WES revealed a pathogenic c.7466C>G (p.Ser2489*) mutation in the last exon of the FHS-linked SRCAP gene. A systematic literature review and analysis of available genetic variation datasets highlighted an unusual distribution of pathogenic variants in SRCAP and confirmed the lack of pathogenicity for variants outside of exons 33 and 34. Finally, we suggested a new model of FHS pathogenesis which provides possible basis for the dominant negative nature of FHS-causing mutations and explains limited effects of GH treatment in FHS.

Conclusion: Our findings expand the number of reported FHS cases and provide new insights into disease genetics and the efficiency of GH therapy for FHS patients.

Structure and Polymorphism of Amyloid and Amyloid-Like Aggregates

Amyloids are protein aggregates with the cross-β structure. The interest in amyloids is explained, on the one hand, by their role in the development of socially significant human neurodegenerative diseases, and on the other hand, by the discovery of functional amyloids, whose formation is an integral part of cellular processes. To date, more than a hundred proteins with the amyloid or amyloid-like properties have been identified. Studying the structure of amyloid aggregates has revealed a wide variety of protein conformations. In the review, we discuss the diversity of protein folds in the amyloid-like aggregates and the characteristic features of amyloid aggregates that determine their unusual properties, including stability and interaction with amyloid-specific dyes. The review also describes the diversity of amyloid aggregates and its significance for living organisms.

Systematic benchmark of state-of-the-art variant calling pipelines identifies major factors affecting accuracy of coding sequence variant discovery

BACKGROUND

Accurate variant detection in the coding regions of the human genome is a key requirement for molecular diagnostics of Mendelian disorders. Efficiency of variant discovery from next-generation sequencing (NGS) data depends on multiple factors, including reproducible coverage biases of NGS methods and the performance of read alignment and variant calling software. Although variant caller benchmarks are published constantly, no previous publications have leveraged the full extent of available gold standard whole-genome (WGS) and whole-exome (WES) sequencing datasets.

RESULTS

In this work, we systematically evaluated the performance of 4 popular short read aligners (Bowtie2, BWA, Isaac, and Novoalign) and 9 novel and well-established variant calling and filtering methods (Clair3, DeepVariant, Octopus, GATK, FreeBayes, and Strelka2) using a set of 14 "gold standard" WES and WGS datasets available from Genome In A Bottle (GIAB) consortium. Additionally, we have indirectly evaluated each pipeline's performance using a set of 6 non-GIAB samples of African and Russian ethnicity. In our benchmark, Bowtie2 performed significantly worse than other aligners, suggesting it should not be used for medical variant calling. When other aligners were considered, the accuracy of variant discovery mostly depended on the variant caller and not the read aligner. Among the tested variant callers, DeepVariant consistently showed the best performance and the highest robustness. Other actively developed tools, such as Clair3, Octopus, and Strelka2, also performed well, although their efficiency had greater dependence on the quality and type of the input data. We have also compared the consistency of variant calls in GIAB and non-GIAB samples. With few important caveats, best-performing tools have shown little evidence of overfitting.

CONCLUSIONS

The results show surprisingly large differences in the performance of cutting-edge tools even in high confidence regions of the coding genome. This highlights the importance of regular benchmarking of quickly evolving tools and pipelines. We also discuss the need for a more diverse set of gold standard genomes that would include samples of African, Hispanic, or mixed ancestry. Additionally, there is also a need for better variant caller assessment in the repetitive regions of the coding genome.

Direct proof of the amyloid nature of yeast prions [PSI+] and [PIN+] by the method of immunoprecipitation of native fibrils

Prions are proteins that can exist in several structurally and functionally distinct states, one or more of which is transmissible. Yeast proteins Sup35 and Rnq1 in prion state ([PSI+] and [PIN+], respectively) form oligomers and aggregates, which are transmitted from parents to offspring in a series of generations. Several pieces of indirect evidence indicate that these aggregates also possess amyloid properties, but their binding to amyloid-specific dyes has not been shown in vivo. Meanwhile, it is the specific binding to the Congo Red dye and birefringence in polarized light after such staining that is considered the gold standard for proving the amyloid properties of a protein. Here, we used immunoprecipitation to extract native fibrils of the Sup35 and Rnq1 proteins from yeast strains with different prion status. These fibrils are detected by electron microscopy, stained with Congo Red and exhibit yellow-green birefringence after such staining. All these data show that the Sup35 and Rnq1 proteins in prion state form amyloid fibrils in vivo. The technology of fibrils extraction in combination with standard cytological methods can be used to identify new pathological and functional amyloids in any organism and to analyze the structural features of native amyloid fibrils.

Chromosome-level genome assembly and structural variant analysis of two laboratory yeast strains from the Peterhof Genetic Collection lineage

Thousands of yeast genomes have been sequenced with both traditional and long-read technologies, and multiple observations about modes of genome evolution for both wild and laboratory strains have been drawn from these sequences. In our study, we applied Oxford Nanopore and Illumina technologies to assemble complete genomes of two widely used members of a distinct laboratory yeast lineage, the Peterhof Genetic Collection (PGC), and investigate the structural features of these genomes including transposable element content, copy number alterations, and structural rearrangements. We identified numerous notable structural differences between genomes of PGC strains and the reference S288C strain. We discovered a substantial enrichment of mid-length insertions and deletions within repetitive coding sequences, such as in the SCH9 gene or the NUP100 gene, with possible impact of these variants on protein amyloidogenicity. High contiguity of the final assemblies allowed us to trace back the history of reciprocal unbalanced translocations between chromosomes I, VIII, IX, XI, and XVI of the PGC strains. We show that formation of hybrid alleles of the FLO genes during such chromosomal rearrangements is likely responsible for the lack of invasive growth of yeast strains. Taken together, our results highlight important features of laboratory yeast strain evolution using the power of long-read sequencing.

Amyloid and Amyloid-Like Aggregates: Diversity and the Term Crisis

Active accumulation of the data on new amyloids continuing nowadays dissolves boundaries of the term "amyloid". Currently, it is most often used to designate aggregates with cross-β structure. At the same time, amyloids also exhibit a number of other unusual properties, such as: detergent and protease resistance, interaction with specific dyes, and ability to induce transition of some proteins from a soluble form to an aggregated one. The same features have been also demonstrated for the aggregates lacking cross-β structure, which are commonly called "amyloid-like" and combined into one group, although they are very diverse. We have collected and systematized information on the properties of more than two hundred known amyloids and amyloid-like proteins with emphasis on conflicting examples. In particular, a number of proteins in membraneless organelles form aggregates with cross-β structure that are morphologically indistinguishable from the other amyloids, but they can be dissolved in the presence of detergents, which is not typical for amyloids. Such paradoxes signify the need to clarify the existing definition of the term amyloid. On the other hand, the demonstrated structural diversity of the amyloid-like aggregates shows the necessity of their classification.

Identification of novel variants in the LDLR gene in Russian patients with familial hypercholesterolemia using targeted sequencing

Familial hypercholesterolemia (FH) is caused by mutations in various genes, including the LDLR, APOB and PSCK9 genes; however, the spectrum of these mutations in Russian individuals has not been fully investigated. In the present study, mutation screening was performed on the LDLR gene and other FH-associated genes in patients with definite or possible FH, using next-generation sequencing. In total, 59 unrelated patients were recruited and sorted into two separate groups depending on their age: Adult (n=31; median age, 49; age range, 23-70) and children/adolescent (n=28; median age, 11; age range, 2-21). FH-associated variants were identified in 18 adults and 25 children, demonstrating mutation detection rates of 58 and 89% for the adult and children/adolescent groups, respectively. In the adult group, 13 patients had FH-associated mutations in the LDLR gene, including two novel variants [NM_000527.4: c.433_434dupG p.(Val145Glyfs*35) and c.1186G>C p.(Gly396Arg)], 3 patients had APOB mutations and two had ABCG5/G8 mutations. In the children/adolescent group, 21 patients had FH-causing mutations in the LDLR gene, including five novel variants [NM_000527.4: c.325T>G p.(Cys109Gly), c.401G>C p.(Cys134Ser), c.616A>C p.(Ser206Arg), c.1684_1691delTGGCCCAA p.(Pro563Hisfs*14) and c.940+1_c.940+4delGTGA], and 2 patients had APOB mutations, as well as ABCG8 and LIPA mutations, being found in different patients. The present study reported seven novel LDLR variants considered to be pathogenic or likely pathogenic. Among them, four missense variants were located in the coding regions, which corresponded to functional protein domains, and two frameshifts were identified that produced truncated proteins. These variants were observed only once in different patients, whereas a splicing variant in intron 6 (c.940+1_c.940+4delGTGA) was detected in four unrelated individuals. Previously reported variants in the LDLR, APOB, ABCG5/8 and LIPA genes were observed in 33 patients. The LDLR p.(Gly592Glu) variant was detected in 6 patients, representing 10% of the FH cases reported in the present study, thus it may be a major variant present in the Russian population. In conclusion, the present study identified seven novel variants of the LDLR gene and broadens the spectrum of mutations in FH-related genes in the Russian Federation.

Analysis of the Spectrum of ACE2 Variation Suggests a Possible Influence of Rare and Common Variants on Susceptibility to COVID-19 and Severity of Outcome

OBJECTIVES

In March 2020, the World Health Organization declared that an infectious respiratory disease caused by a new severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2, causing coronavirus disease 2019 (COVID-19)] became a pandemic. In our study, we have analyzed a large publicly available dataset, the Genome Aggregation Database (gnomAD), as well as a cohort of 37 Russian patients with COVID-19 to assess the influence of different classes of genetic variants in the angiotensin-converting enzyme-2 (ACE2) gene on the susceptibility to COVID-19 and the severity of disease outcome.

RESULTS

We demonstrate that the European populations slightly differ in alternative allele frequencies at the 2,754 variant sites in ACE2 identified in the gnomAD database. We find that the Southern European population has a lower frequency of missense variants and slightly higher frequency of regulatory variants. However, we found no statistical support for the significance of these differences. We also show that the Russian population is similar to other European populations when comparing the frequencies of the ACE2 variants. Evaluation of the effect of various classes of ACE2 variants on COVID-19 outcome in a cohort of Russian patients showed that common missense and regulatory variants do not explain the differences in disease severity. At the same time, we find several rare ACE2 variants (including rs146598386, rs73195521, rs755766792, and others) that are likely to affect the outcome of COVID-19. Our results demonstrate that the spectrum of genetic variants in ACE2 may partially explain the differences in severity of the COVID-19 outcome.

Quantitative assessment of chaperone binding to amyloid aggregates identifies specificity of Hsp40 interaction with yeast prion fibrils

Yeast self-perpetuating protein aggregates (yeast prions) provide a framework to investigate the interaction of misfolded proteins with the protein quality control machinery. The major component of this system that facilitates propagation of all known yeast amyloid prions is the Hsp104 chaperone that catalyzes fibril fragmentation. Overproduction of Hsp104 cures some yeast prions via a fragmentation-independent mechanism. Importantly, major cytosolic chaperones of the Hsp40 group, Sis1 and Ydj1, oppositely affect yeast prion propagation, and are capable of stimulating different activities of Hsp104. In this work, we developed a quantitative method to investigate the Hsp40 binding to amyloid aggregates. We demonstrate that Sis1 binds fibrils formed by the Sup35NM protein with higher affinity compared to Ydj1. Moreover, the interaction of Sis1 with the fibrils formed by the other yeast prion protein, Rnq1, is orders of magnitude weaker. We show that the deletion of the dimerization domain of Sis1 (crucial for the curing of [PSI+] by excess Hsp104) decreases its affinity to both Sup35NM and Rnq1 fibrils. Taken together, these results suggest that tight binding of Hsp40 to the amyloid fibrils is likely to enhance aggregate malpartition instead of fibril fragmentation.

A Data-Driven Review of the Genetic Factors of Pregnancy Complications

Over the recent years, many advances have been made in the research of the genetic factors of pregnancy complications. In this work, we use publicly available data repositories, such as the National Human Genome Research Institute GWAS Catalog, HuGE Navigator, and the UK Biobank genetic and phenotypic dataset to gain insights into molecular pathways and individual genes behind a set of pregnancy-related traits, including the most studied ones—preeclampsia, gestational diabetes, preterm birth, and placental abruption. Using both HuGE and GWAS Catalog data, we confirm that immune system and, in particular, T-cell related pathways are one of the most important drivers of pregnancy-related traits. Pathway analysis of the data reveals that cell adhesion and matrisome-related genes are also commonly involved in pregnancy pathologies. We also find a large role of metabolic factors that affect not only gestational diabetes, but also the other traits. These shared metabolic genes include IGF2, PPARG, and NOS3. We further discover that the published genetic associations are poorly replicated in the independent UK Biobank cohort. Nevertheless, we find novel genome-wide associations with pregnancy-related traits for the FBLN7, STK32B, and ACTR3B genes, and replicate the effects of the KAZN and TLE1 genes, with the latter being the only gene identified across all data resources. Overall, our analysis highlights central molecular pathways for pregnancy-related traits, and suggests a need to use more accurate and sophisticated association analysis strategies to robustly identify genetic risk factors for pregnancy complications.

The spectrum of pathogenic variants of the ATP7B gene in Wilson disease in the Russian Federation

BACKGROUND

Wilson's disease (WD) is a rare inherited disorder caused by mutations in the ATP7B gene resulting in copper accumulation in different organs. However, data on ATP7B mutation spectrum in Russia and worldwide are insufficient and contradictory. The objective of the present study was estimation of the frequency of ATP7B gene mutations in the Russian population of WD patients.

MATERIALS AND METHODS

75 WDpatients were examined by next-generation sequencing (NGS). A targeted panel NimbleGen SeqCap EZ Choice: 151012_HG38_CysFib_EZ_HX3 (ROCHE)was designed for analysis of ATP7B gene and possible modifier genes. Retrospective assessment of a diagnostic WD score (Leipzig, 2001) was also performed.

RESULTS

31 mutations in ATP7B gene were detected. Two most frequent mutations were c.3207C > A (51,85% of alleles) and c.3190 G > A (8,64% of alleles). Single rare mutations were detected in 29% of cases. In 96% cases mutations of both copies of the ATP7B were revealed. We also observed 3 novel potentially pathogenic variants which were not previously described (c.1870-8A > G, c.3655A > T (p.Ile1219Phe), c.3036dupC (p.Lys1013fs). For 25% of patients at the time of the manifestation the diagnosis WD could not be established using the earlier proposed diagnostic score. There was a remarkable delay in diagnosis for the majority of patients. Only 33% of patients WD was diagnosed in three months after the first symptoms, 29%patients - in 3-12 months, 30% - in 1-10 years, in 8% - more than 10 years. Generally, clinical appearance of WD may be rather variable at manifestation and genetic profiling at this step is the only way to confirm the presence of WD.

Estimation of amyloid aggregate sizes with semi-denaturing detergent agarose gel electrophoresis and its limitations

Semi-denaturing detergent agarose gel electrophoresis (SDD-AGE) was proposed by Vitaly V. Kushnirov in the Michael D. Ter-Avanesyan’s laboratory as a method to compare sizes of amyloid aggregates. Currently, this method is widely used for amyloid investigation, but mostly as a qualitative approach. In this work, we assessed the possibilities and limitations of the quantitative analysis of amyloid aggregate size distribution using SDD-AGE results. For this purpose, we used aggregates of two well-characterized yeast amyloid-forming proteins, Sup35 and Rnq1, and developed a protocol to standardize image analysis and process the result. A detailed investigation of factors that may affect the results of SDD-AGE revealed that both the cell lysis method and electrophoresis conditions can substantially affect the estimation of aggregate size. Despite this, quantitative analysis of SDD-AGE results is possible when one needs to estimate and compare the size of aggregates on the same gel, or even in different experiments, if the experimental conditions are tightly controlled and additional standards are used.

Systematic dissection of biases in whole-exome and whole-genome sequencing reveals major determinants of coding sequence coverage

Advantages and diagnostic effectiveness of the two most widely used resequencing approaches, whole exome (WES) and whole genome (WGS) sequencing, are often debated. WES dominated large-scale resequencing projects because of lower cost and easier data storage and processing. Rapid development of 3^rd generation sequencing methods and novel exome sequencing kits predicate the need for a robust statistical framework allowing informative and easy performance comparison of the emerging methods. In our study we developed a set of statistical tools to systematically assess coverage of coding regions provided by several modern WES platforms, as well as PCR-free WGS. We identified a substantial problem in most previously published comparisons which did not account for mappability limitations of short reads. Using regression analysis and simple machine learning, as well as several novel metrics of coverage evenness, we analyzed the contribution from the major determinants of CDS coverage. Contrary to a common view, most of the observed bias in modern WES stems from mappability limitations of short reads and exome probe design rather than sequence composition. We also identified the ~ 500 kb region of human exome that could not be effectively characterized using short read technology and should receive special attention during variant analysis. Using our novel metrics of sequencing coverage, we identified main determinants of WES and WGS performance. Overall, our study points out avenues for improvement of enrichment-based methods and development of novel approaches that would maximize variant discovery at optimal cost.

Phenome-wide functional dissection of pleiotropic effects highlights key molecular pathways for human complex traits

Over the recent decades, genome-wide association studies (GWAS) have dramatically changed the understanding of human genetics. A recent genetic data release by UK Biobank (UKB) has allowed many researchers worldwide to have comprehensive look into the genetic architecture of thousands of human phenotypes. In this study, we used GWAS summary statistics derived from the UKB cohort to investigate functional mechanisms of pleiotropic effects across the human phenome. We find that highly pleiotropic variants often correspond to broadly expressed genes with ubiquitous functions, such as matrisome components and cell growth regulators; and tend to colocalize with tissue-shared eQTLs. At the same time, signaling pathway components are more prevalent among highly pleiotropic genes compared to regulatory proteins such as transcription factors. Our results suggest that protein-level pleiotropy mediated by ubiquitously expressed genes is the most prevalent mechanism of pleiotropic genetic effects across the human phenome.

Whole-exome sequencing provides insights into monogenic disease prevalence in Northwest Russia

BACKGROUND

Allele frequency data from large exome and genome aggregation projects such as the Genome Aggregation Database (gnomAD) are of ultimate importance to the interpretation of medical resequencing data. However, allele frequencies might significantly differ in poorly studied populations that are underrepresented in large-scale projects, such as the Russian population.

METHODS

In this work, we leveraged our access to a large dataset of 694 exome samples to analyze genetic variation in the Northwest Russia. We compared the spectrum of genetic variants to the dbSNP build 151, and made estimates of ClinVar-based autosomal recessive (AR) disease allele prevalence as compared to gnomAD r. 2.1.

RESULTS

An estimated 9.3% of discovered variants were not present in dbSNP. We report statistically significant overrepresentation of pathogenic variants for several Mendelian disorders, including phenylketonuria (PAH, rs5030858), Wilson's disease (ATP7B, rs76151636), factor VII deficiency (F7, rs36209567), kyphoscoliosis type of Ehlers-Danlos syndrome (FKBP14, rs542489955), and several other recessive pathologies. We also make primary estimates of monogenic disease incidence in the population, with retinal dystrophy, cystic fibrosis, and phenylketonuria being the most frequent AR pathologies.

CONCLUSION

Our observations demonstrate the utility of population-specific allele frequency data to the diagnosis of monogenic disorders using high-throughput technologies.

Whole‑exome sequencing in Russian children with non‑type 1 diabetes mellitus reveals a wide spectrum of genetic variants in MODY‑related and unrelated genes

The present study reports on the frequency and the spectrum of genetic variants causative of monogenic diabetes in Russian children with non-type 1 diabetes mellitus. The present study included 60 unrelated Russian children with non-type 1 diabetes mellitus diagnosed before the age of 18 years. Genetic variants were screened using whole-exome sequencing (WES) in a panel of 35 genes causative of maturity onset diabetes of the young (MODY) and transient or permanent neonatal diabetes. Verification of the WES results was performed using PCR-direct sequencing. A total of 38 genetic variants were identified in 33 out of 60 patients (55%). The majority of patients (27/33, 81.8%) had variants in MODY-related genes: GCK (n=19), HNF1A (n=2), PAX4 (n=1), ABCC8 (n=1), KCNJ11 (n=1), GCK+HNF1A (n=1), GCK+BLK (n=1) and GCK+BLK+WFS1 (n=1). A total of 6 patients (6/33, 18.2%) had variants in MODY-unrelated genes: GATA6 (n=1), WFS1 (n=3), EIF2AK3 (n=1) and SLC19A2 (n=1). A total of 15 out of 38 variants were novel, including GCK, HNF1A, BLK, WFS1, EIF2AK3 and SLC19A2. To summarize, the present study demonstrates a high frequency and a wide spectrum of genetic variants causative of monogenic diabetes in Russian children with non-type 1 diabetes mellitus. The spectrum includes previously known and novel variants in MODY-related and unrelated genes, with multiple variants in a number of patients. The prevalence of GCK variants indicates that diagnostics of monogenic diabetes in Russian children may begin with testing for MODY2. However, the remaining variants are present at low frequencies in 9 different genes, altogether amounting to ~50% of the cases and highlighting the efficiency of using WES in non-GCK-MODY cases.

Recent advances and perspectives in next generation sequencing application to the genetic research of type 2 diabetes

Type 2 diabetes (T2D) mellitus is a common complex disease that currently affects more than 400 million people worldwide and has become a global health problem. High-throughput sequencing technologies such as whole-genome and whole-exome sequencing approaches have provided numerous new insights into the molecular bases of T2D. Recent advances in the application of sequencing technologies to T2D research include, but are not limited to: (1) Fine mapping of causal rare and common genetic variants; (2) Identification of confident gene-level associations; (3) Identification of novel candidate genes by specific scoring approaches; (4) Interrogation of disease-relevant genes and pathways by transcriptional profiling and epigenome mapping techniques; and (5) Investigation of microbial community alterations in patients with T2D. In this work we review these advances in application of next-generation sequencing methods for elucidation of T2D pathogenesis, as well as progress and challenges in implementation of this new knowledge about T2D genetics in diagnosis, prevention, and treatment of the disease.

Identification of Novel Candidate Markers of Type 2 Diabetes and Obesity in Russia by Exome Sequencing with a Limited Sample Size

Type 2 diabetes (T2D) and obesity are common chronic disorders with multifactorial etiology. In our study, we performed an exome sequencing analysis of 110 patients of Russian ethnicity together with a multi-perspective approach based on biologically meaningful filtering criteria to detect novel candidate variants and loci for T2D and obesity. We have identified several known single nucleotide polymorphisms (SNPs) as markers for obesity (rs11960429), T2D (rs9379084, rs1126930), and body mass index (BMI) (rs11553746, rs1956549 and rs7195386) (p < 0.05). We show that a method based on scoring of case-specific variants together with selection of protein-altering variants can allow for the interrogation of novel and known candidate markers of T2D and obesity in small samples. Using this method, we identified rs328 in LPL (p = 0.023), rs11863726 in HBQ1 (p = 8 × 10⁻⁵), rs112984085 in VAV3 (p = 4.8 × 10⁻⁴) for T2D and obesity, rs6271 in DBH (p = 0.043), rs62618693 in QSER1 (p = 0.021), rs61758785 in RAD51B (p = 1.7 × 10⁻⁴), rs34042554 in PCDHA1 (p = 1 × 10⁻⁴), and rs144183813 in PLEKHA5 (p = 1.7 × 10⁻⁴) for obesity; and rs9379084 in RREB1 (p = 0.042), rs2233984 in C6orf15 (p = 0.030), rs61737764 in ITGB6 (p = 0.035), rs17801742 in COL2A1 (p = 8.5 × 10⁻⁵), and rs685523 in ADAMTS13 (p = 1 × 10⁻⁶) for T2D as important susceptibility loci in Russian population. Our results demonstrate the effectiveness of whole exome sequencing (WES) technologies for searching for novel markers of multifactorial diseases in cohorts of limited size in poorly studied populations.

To CURe or not to CURe? Differential effects of the chaperone sorting factor Cur1 on yeast prions are mediated by the chaperone Sis1

Yeast self-perpetuating protein aggregates (prions) provide a convenient model for studying various components of the cellular protein quality control system. Molecular chaperones and chaperone-sorting factors, such as yeast Cur1 protein, play key role in proteostasis via tight control of partitioning and recycling of misfolded proteins. In this study, we show that, despite the previously described ability of Cur1 to antagonize the yeast prion [URE3], it enhances propagation and phenotypic manifestation of another prion, [PSI⁺ ]. We demonstrate that both curing of [URE3] and enhancement of [PSI⁺ ] in the presence of excess Cur1 are counteracted by the cochaperone Hsp40-Sis1 in a dosage-dependent manner, and show that the effect of Cur1 on prions parallels effects of the attachment of nuclear localization signal to Sis1, indicating that Cur1 acts on prions via its previously reported ability to relocalize Sis1 from the cytoplasm to nucleus. This shows that the direction in which Cur1 influences a prion depends on how this specific prion responds to relocalization of Sis1.