Littorina snails and Microphallus trematodes: Diverse consequences of the trematode-induced metabolic shifts.

The intricate relationships between parasites and hosts encompass a wide range of levels, from molecular interactions to population dynamics. Parasites influence not only the physiological processes in the host organism, but also the entire ecosystem, affecting mortality of individuals, the number of offspring through parasitic castration, and matter and energy cycles. Understanding the molecular mechanisms that govern host-parasite relationships and their impact on host physiology and environment remains challenging. In this study, we analyzed how infection with Microphallus trematodes affects the metabolome of two Littorina snail species inhabiting different intertidal zone shore levels. We applied non-targeted GC-MS-based metabolomics to analyze biochemical shifts induced by trematode infection in a host organism. We have identified changes in energy, amino acid, sugar, and lipid metabolism. In particular, we observed intensified amino acid catabolism and nitrogenous catabolites (glutamine, urea) production. These changes primarily correlated with infection and interspecies differences of the hosts rather than shore level. The changes detected in the host metabolism indicate that other aspects of life may have been affected, both within the host organism and at a supra-organismal level. Therefore, we explored changes in microbiota composition, deviations in the host molluscs behavior, and acetylcholinesterase activity (ACE, an enzyme involved in neuromuscular transmission) in relation to infection. Infected snails displayed changes in their microbiome composition. Decreased ACE activity in snails was associated with reduced mobility, but whether it is associated with trematode infection remains unclear. The authors suggest a connection between the identified biochemical changes and the deformation of the shell of molluscs, changes in their behavior, and the associated microbiome. The role of parasitic systems formed by microphallid trematodes and Littorina snails in the nitrogen cycle at the ecosystem level is also assumed.

Genome-wide sequence analyses of ethnic populations across Russia.

The Russian Federation is the largest and one of the most ethnically diverse countries in the world, however no centralized reference database of genetic variation exists to date. Such data are crucial for medical genetics and essential for studying population history. The Genome Russia Project aims at filling this gap by performing whole genome sequencing and analysis of peoples of the Russian Federation. Here we report the characterization of genome-wide variation of 264 healthy adults, including 60 newly sequenced samples. People of Russia carry known and novel genetic variants of adaptive, clinical and functional consequence that in many cases show allele frequency divergence from neighboring populations. Population genetics analyses revealed six phylogeographic partitions among indigenous ethnicities corresponding to their geographic locales. This study presents a characterization of population-specific genomic variation in Russia with results important for medical genetics and for understanding the dynamic population history of the world's largest country.

Catching hidden variation: systematic correction of reference minor allele annotation in clinical variant calling.

PurposeWe comprehensively assessed the influence of reference minor alleles (RMAs), one of the inherent problems of the human reference genome sequence.MethodsThe variant call format (VCF) files provided by the 1000 Genomes and Exome Aggregation Consortium (ExAC) consortia were used to identify RMA sites. All coding RMA sites were checked for concordance with UniProt and the presence of same codon variants. RMA-corrected predictions of functional effect were obtained with SIFT, PolyPhen-2, and PROVEAN standalone tools and compared with dbNSFP v2.9 for consistency.ResultsWe systematically characterized the problem of RMAs and identified several possible ways in which RMA could interfere with accurate variant discovery and annotation. We have discovered a systematic bias in the automated variant effect prediction at the RMA loci, as well as widespread switching of functional consequences for variants located in the same codon as the RMA. As a convenient way to address the problem of RMAs we have developed a simple bioinformatic tool that identifies variation at RMA sites and provides correct annotations for all such substitutions. The tool is available free of charge at http://rmahunter.bioinf.me.ConclusionCorrection of RMA annotation enhances the accuracy of next-generation sequencing-based methods in clinical practice.

Mitochondrial Genome of Vannella croatica (Amoebozoa, Discosea, Vannellida).

Mitochondrial genome sequence of Vannella croatica (Amoebozoa, Discosea, Vannellida) was obtained using pulse-field gel electrophoretic isolation of the circular mitochondrial DNA, followed by the next-generation sequencing. The mitochondrial DNA of this species has the length of 28,933 bp and contains 12 protein-coding genes, two ribosomal RNAs, and 16 transfer RNAs. Vannella croatica mitochondrial genome is relatively short compared to other known amoebozoan mitochondrial genomes but is rather gene-rich and contains significant number of open reading frames.

Disruption of Transcriptional Coactivator Sub1 Leads to Genome-Wide Re-distribution of Clustered Mutations Induced by APOBEC in Active Yeast Genes.

Mutations in genomes of species are frequently distributed non-randomly, resulting in mutation clusters, including recently discovered kataegis in tumors. DNA editing deaminases play the prominent role in the etiology of these mutations. To gain insight into the enigmatic mechanisms of localized hypermutagenesis that lead to cluster formation, we analyzed the mutational single nucleotide variations (SNV) data obtained by whole-genome sequencing of drug-resistant mutants induced in yeast diploids by AID/APOBEC deaminase and base analog 6-HAP. Deaminase from sea lamprey, PmCDA1, induced robust clusters, while 6-HAP induced a few weak ones. We found that PmCDA1, AID, and APOBEC1 deaminases preferentially mutate the beginning of the actively transcribed genes. Inactivation of transcription initiation factor Sub1 strongly reduced deaminase-induced can1 mutation frequency, but, surprisingly, did not decrease the total SNV load in genomes. However, the SNVs in the genomes of the sub1 clones were re-distributed, and the effect of mutation clustering in the regions of transcription initiation was even more pronounced. At the same time, the mutation density in the protein-coding regions was reduced, resulting in the decrease of phenotypically detected mutants. We propose that the induction of clustered mutations by deaminases involves: a) the exposure of ssDNA strands during transcription and loss of protection of ssDNA due to the depletion of ssDNA-binding proteins, such as Sub1, and b) attainment of conditions favorable for APOBEC action in subpopulation of cells, leading to enzymatic deamination within the currently expressed genes. This model is applicable to both the initial and the later stages of oncogenic transformation and explains variations in the distribution of mutations and kataegis events in different tumor cells.

Scytalidium candidum 3C is a new name for the Geotrichum candidum Link 3C strain.

In the 1970s, the strain Geotrichum candidum Link 3C was isolated from rotting rope and since then has been extensively studied as a source of cellulose and xylan-degrading enzymes. The original identification of the strain was based only on morphological characters of the fungal mycelium in culture. Recent comparison of the internal transcribed spacer (ITS) fragments derived from the draft genome published in 2015 did not show its similarity to G. candidum species. Given the value of the strain 3C in lignocellulosic biomass degradation, we performed morphological and molecular studies to find the appropriate taxonomic placement for this fungal strain within the Ascomycota phylum. ITS, 18S rDNA, 28S rDNA sequences, and RPB2 encoding genes were used to construct phylogenetic trees with Maximum likelihood and Bayesian inference methods. Based on sequence comparison and multiple gene sequencing, we conclude that the fungal strain designated as Geotrichum candidum Link 3C should be placed into the genus Scytalidium (Pezizomycotina, Leotiomycetes) and is redescribed herein as Scytalidium candidum 3C comb. nov.

Nicotiana noctiflora Hook. Genome Contains Two Cellular T-DNAs with Functional Genes.

Agrobacterium (Rhizobium)-mediated transformation leads to the formation of crown galls or hairy roots on infected plants. These effects develop due to the activity of T-DNA genes, gathered on a big plasmid, acquired from agrobacteria during horizontal gene transfer. However, a lot of plant species are known to contain such sequences, called cellular T-DNAs (cT-DNAs), and maintain normal phenotypes. Some of the genes remain intact, which leads to the conclusion of their functional role in plants. In this study, we present a comprehensive analysis of the cT-DNAs in the Nicotiana noctiflora Hook. genome, including gene expression and opine identification. Deep sequencing of the Nicotiana noctiflora genome revealed the presence of two different cT-DNAs, NnT-DNA1 and NnT-DNA2, which contain the intact genes iaaM, iaaH, acs, orf13, orf13a, and orf14. According to the expression analysis results, all these genes are most active in roots in comparison with other organs, which is consistent with data on cT-DNA gene expression in other plant species. We also used genetic engineering approaches and HPTLC and HPLC-MS methods to investigate the product of the acs gene (agrocinopine synthase), which turned out to be similar to agrocinopine A. Overall, this study expands our knowledge of cT-DNAs in plants and brings us closer to understanding their possible functions. Further research of cT-DNAs in different species and their functional implications could contribute to advancements in plant genetics and potentially unveil novel traits with practical applications in agriculture and other fields.

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.

RNA Sequencing of Whole Blood Defines the Signature of High Intensity Exercise at Altitude in Elite Speed Skaters.

Although high altitude training has been increasingly popular among endurance athletes, the molecular and cellular bases of this adaptation remain poorly understood. We aimed to define the underlying physiological changes and screen for potential biomarkers of adaptation using transcriptional profiling of whole blood. Seven elite female speed skaters were profiled on the 18th day of high-altitude adaptation. Whole blood RNA-seq before and after an intense 1 h skating bout was used to measure gene expression changes associated with exercise. In order to identify the genes specifically regulated at high altitudes, we have leveraged the data from eight previously published microarray datasets studying blood expression changes after exercise at sea level. Using cell type-specific signatures, we were able to deconvolute changes of cell type abundance from individual gene expression changes. Among these were PHOSPHO1, with a known role in erythropoiesis, and MARC1 with a role in endogenic NO metabolism. We find that platelet and erythrocyte counts uniquely respond to altitude exercise, while changes in neutrophils represent a more generic marker of intense exercise. Publicly available data from both single cell atlases and exercise-related blood profiling dramatically increases the value of whole blood RNA-seq for the dynamic evaluation of physiological changes in an athlete's body.

Identification of Genetic Risk Factors of Severe COVID-19 Using Extensive Phenotypic Data: A Proof-of-Concept Study in a Cohort of Russian Patients.

The COVID-19 pandemic has drawn the attention of many researchers to the interaction between pathogen and host genomes. Over the last two years, numerous studies have been conducted to identify the genetic risk factors that predict COVID-19 severity and outcome. However, such an analysis might be complicated in cohorts of limited size and/or in case of limited breadth of genome coverage. In this work, we tried to circumvent these challenges by searching for candidate genes and genetic variants associated with a variety of quantitative and binary traits in a cohort of 840 COVID-19 patients from Russia. While we found no gene- or pathway-level associations with the disease severity and outcome, we discovered eleven independent candidate loci associated with quantitative traits in COVID-19 patients. Out of these, the most significant associations correspond to rs1651553 in MYH14p = 1.4 × 10-7), rs11243705 in SETX (p = 8.2 × 10-6), and rs16885 in ATXN1 (p = 1.3 × 10-5). One of the identified variants, rs33985936 in SCN11A, was successfully replicated in an independent study, and three of the variants were found to be associated with blood-related quantitative traits according to the UK Biobank data (rs33985936 in SCN11A, rs16885 in ATXN1, and rs4747194 in CDH23). Moreover, we show that a risk score based on these variants can predict the severity and outcome of hospitalization in our cohort of patients. Given these findings, we believe that our work may serve as proof-of-concept study demonstrating the utility of quantitative traits and extensive phenotyping for identification of genetic risk factors of severe COVID-19.

Compensation for the absence of the catalytically active half of DNA polymerase ε in yeast by positively selected mutations in CDC28.

Current eukaryotic replication models postulate that leading and lagging DNA strands are replicated predominantly by dedicated DNA polymerases. The catalytic subunit of the leading strand DNA polymerase ε, Pol2, consists of two halves made of two different ancestral B-family DNA polymerases. Counterintuitively, the catalytically active N-terminal half is dispensable, while the inactive C-terminal part is required for viability. Despite extensive studies of yeast Saccharomyces cerevisiae strains lacking the active N-terminal half, it is still unclear how these strains survive and recover. We designed a robust method for constructing mutants with only the C-terminal part of Pol2. Strains without the active polymerase part show severe growth defects, sensitivity to replication inhibitors, chromosomal instability, and elevated spontaneous mutagenesis. Intriguingly, the slow-growing mutant strains rapidly accumulate fast-growing clones. Analysis of genomic DNA sequences of these clones revealed that the adaptation to the loss of the catalytic N-terminal part of Pol2 occurs by a positive selection of mutants with improved growth. Elevated mutation rates help generate sufficient numbers of these variants. Single nucleotide changes in the cell cycle-dependent kinase gene, CDC28, improve the growth of strains lacking the N-terminal part of Pol2, and rescue their sensitivity to replication inhibitors and, in parallel, lower mutation rates. Our study predicts that changes in mammalian homologs of cyclin-dependent kinases may contribute to cellular responses to the leading strand polymerase defects.

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.

Genomic Variations in Drug Resistant Mycobacterium tuberculosis Strains Collected from Patients with Different Localization of Infection.

Mycobacterium tuberculosis is a highly studied pathogen due to public health importance. Despite this, problems like early drug resistance, diagnostics and treatment success prediction are still not fully resolved. Here, we analyze the incidence of point mutations widely used for drug resistance detection in laboratory practice and conduct comparative analysis of whole-genome sequence (WGS) for clinical M. tuberculosis strains collected from patients with pulmonary tuberculosis (PTB) and extra-pulmonary tuberculosis (XPTB) localization. A total of 72 pulmonary and 73 extrapulmonary microbiologically characterized M. tuberculosis isolates were collected from patients from 2007 to 2014 in Russia. Genomic DNA was used for WGS and obtained data allowed identifying major mutations known to be associated with drug resistance to first-line and second-line antituberculous drugs. In some cases previously described mutations were not identified. Using genome-based phylogenetic analysis we identified M. tuberculosis substrains associated with distinctions in the occurrence in PTB vs. XPTB cases. Phylogenetic analyses did reveal M. tuberculosis genetic substrains associated with TB localization. XPTB was associated with Beijing sublineages Central Asia (Beijing CAO), Central Asia Clade A (Beijing A) and 4.8 groups, while PTB localization was associated with group LAM (4.3). Further, the XPTB strain in some cases showed elevated drug resistance patterns relative to PTB isolates. HIV was significantly associated with the development of XPTB in the Beijing B0/W148 group and among unclustered Beijing isolates.

LMNA Mutations G232E and R482L Cause Dysregulation of Skeletal Muscle Differentiation, Bioenergetics, and Metabolic Gene Expression Profile.

Laminopathies are a family of monogenic multi-system diseases resulting from mutations in the LMNA gene which include a wide range of neuromuscular disorders. Although lamins are expressed in most types of differentiated cells, LMNA mutations selectively affect only specific tissues by mechanisms that remain largely unknown. We have employed the combination of functional in vitro experiments and transcriptome analysis in order to determine how two LMNA mutations associated with different phenotypes affect skeletal muscle development and metabolism. We used a muscle differentiation model based on C2C12 mouse myoblasts genetically modified with lentivirus constructs bearing wild-type human LMNA (WT-LMNA) or R482L-LMNA/G232E-LMNA mutations, linked to familial partial lipodystrophy of the Dunnigan type and muscular dystrophy phenotype accordingly. We have shown that both G232E/R482L-LMNA mutations cause dysregulation in coordination of pathways that control cell cycle dynamics and muscle differentiation. We have also found that R482/G232E-LMNA mutations induce mitochondrial uncoupling and a decrease in glycolytic activity in differentiated myotubes. Both types of alterations may contribute to mutation-induced muscle tissue pathology.

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 3rd 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.

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.

Whole­exome sequencing in Russian children with non­type 1 diabetes mellitus reveals a wide spectrum of genetic variants in MODY­related and unrelated genes.

The present study reports on the frequency and the spectrum of genetic variants causative of monogenic diabetes in Russian children with non­type 1 diabetes mellitus. The present study included 60 unrelated Russian children with non­type 1 diabetes mellitus diagnosed before the age of 18 years. Genetic variants were screened using whole­exome 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 PCR­direct 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 MODY­related 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 MODY­unrelated 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 non­type 1 diabetes mellitus. The spectrum includes previously known and novel variants in MODY­related 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 non­GCK­MODY cases.

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.

Recombination Is Responsible for the Increased Recovery of Drug-Resistant Mutants with Hypermutated Genomes in Resting Yeast Diploids Expressing APOBEC Deaminases.

DNA editing deaminases (APOBECs) are implicated in generation of mutations in somatic cells during tumorigenesis. APOBEC-dependent mutagenesis is thought to occur during transient exposure of unprotected single-stranded DNA. Mutations frequently occur in clusters (kataegis). We investigated mechanisms of mutant generation in growing and resting diploid yeast expressing APOBEC from sea lamprey, PmCDA1, whose kataegistic effect was previously shown to be associated with transcription. We have found that the frequency of canavanine-resistant mutants kept raising after growth cessation, while the profile of transcription remained unchanged. Surprisingly, the overall number of mutations in the genomes did not elevate in resting cells. Thus, mutations were accumulated during vigorous growth stage with both intense replication and transcription. We found that the elevated recovery of can1 mutant clones in non-growing cells is the result of loss of heterozygosity (LOH) leading to clusters of homozygous mutations in the chromosomal regions distal to the reporter gene. We confirmed that recombination frequency in resting cells was elevated by orders of magnitude, suggesting that cells were transiently committed to meiotic levels of recombination, a process referred to in yeast genetics as return-to-growth. In its extreme, on day 6 of starvation, a few mutant clones were haploid, likely resulting from completed meiosis. Distribution of mutations along chromosomes indicated that PmCDA1 was active during ongoing recombination events and sometimes produced characteristic kataegis near initial breakpoints. AID and APOBEC1 behaved similar to PmCDA1. We conclude that replication, transcription, and mitotic recombination contribute to the recovered APOBEC-induced mutations in resting diploids. The mechanism is relevant to the initial stages of oncogenic transformation in terminally differentiated cells, when recombination may lead to the LOH exposing recessive mutations induced by APOBECs in cell's history and to acquisition of new mutations near original break.

Genome Sequencing and Comparative Analysis of Saccharomyces cerevisiae Strains of the Peterhof Genetic Collection.

The Peterhof genetic collection of Saccharomyces cerevisiae strains (PGC) is a large laboratory stock that has accumulated several thousands of strains for over than half a century. It originated independently of other common laboratory stocks from a distillery lineage (race XII). Several PGC strains have been extensively used in certain fields of yeast research but their genomes have not been thoroughly explored yet. Here we employed whole genome sequencing to characterize five selected PGC strains including one of the closest to the progenitor, 15V-P4, and several strains that have been used to study translation termination and prions in yeast (25-25-2V-P3982, 1B-D1606, 74-D694, and 6P-33G-D373). The genetic distance between the PGC progenitor and S288C is comparable to that between two geographically isolated populations. The PGC seems to be closer to two bakery strains than to S288C-related laboratory stocks or European wine strains. In genomes of the PGC strains, we found several loci which are absent from the S288C genome; 15V-P4 harbors a rare combination of the gene cluster characteristic for wine strains and the RTM1 cluster. We closely examined known and previously uncharacterized gene variants of particular strains and were able to establish the molecular basis for known phenotypes including phenylalanine auxotrophy, clumping behavior and galactose utilization. Finally, we made sequencing data and results of the analysis available for the yeast community. Our data widen the knowledge about genetic variation between Saccharomyces cerevisiae strains and can form the basis for planning future work in PGC-related strains and with PGC-derived alleles.