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.

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.

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.

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.

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.