Rate, molecular spectrum, and consequences of human mutation

Exploring Mitonuclear Discordance: Ghost Introgression From an Ancient Extinction Lineage in the Odorrana swinhoana Complex

Mitonuclear discordance, the incongruence between mitochondrial DNA (mtDNA) and nuclear DNA (nuDNA), is a well-documented phenomenon with various potential explanations. One emerging hypothesis, ghost introgression, refers to the genetic contribution of an ancient, extinct or unsampled lineage and can now be tested using modern genomic data and demographic models. In this study, we investigated the evolutionary history of the Odorrana swinhoana complex (Anura: Ranidae), which includes O. swinhoana, O. utsunomiyaorum and an unidentified population with highly divergent mtDNA. While mitochondrial phylogeny suggested this population as a basal lineage, nuclear data from ddRADseq revealed it as a mixture of the most derived O. swinhoana nuclear sequences combined with ancient mtDNA. Demographic modelling further supported ghost introgression, as all models incorporating a ghost population outperformed those without it. These findings suggest that an eastward expansion of western O. swinhoana replaced an ancient Odorrana lineage, leaving only its mtDNA and fragments of its nuclear genome in the hybrid population. Our results provide one of the first documented cases of ghost introgression in amphibians and highlight its potential as a widespread evolutionary process. This study also underscores the risks of relying solely on mtDNA for phylogenetic reconstruction and species delimitation.

Efficient Detection and Characterization of Targets of Natural Selection Using Transfer Learning

Natural selection leaves detectable patterns of altered spatial diversity within genomes, and identifying affected regions is crucial for understanding species evolution. Recently, machine learning approaches applied to raw population genomic data have been developed to uncover these adaptive signatures. Convolutional neural networks (CNNs) are particularly effective for this task, as they handle large data arrays while maintaining element correlations. However, shallow CNNs may miss complex patterns due to their limited capacity, while deep CNNs can capture these patterns but require extensive data and computational power. Transfer learning addresses these challenges by utilizing a deep CNN pretrained on a large dataset as a feature extraction tool for downstream classification and evolutionary parameter prediction. This approach reduces extensive training data generation requirements and computational needs while maintaining high performance. In this study, we developed TrIdent, a tool that uses transfer learning to enhance detection of adaptive genomic regions from image representations of multilocus variation. We evaluated TrIdent across various genetic, demographic, and adaptive settings, in addition to unphased data and other confounding factors. TrIdent demonstrated improved detection of adaptive regions compared to recent methods using similar data representations. We further explored model interpretability through class activation maps and adapted TrIdent to infer selection parameters for identified adaptive candidates. Using whole-genome haplotype data from European and African populations, TrIdent effectively recapitulated known sweep candidates and identified novel cancer, and other disease-associated genes as potential sweeps.

Human deleterious mutation rate slows adaptation and implies high fitness variance

Each new human has an expectedU d = 2 - 10 new deleterious mutations. Using a novel approach to capture complex linkage disequilibria from highU d using genome-wide simulations, we confirm that fitness decline due to the fixation of many slightly deleterious mutations can be compensated by rarer beneficial mutations of larger effect. The evolution of increased genome size and complexity have previously been attributed to a similarly asymmetric pattern of fixations, but we propose that the cause might be highU d rather than the small population size posited as causal by drift barrier theory. High within-population variance in relative fitness is an inevitable consequence of highU d ∼ 2 - 10 combined with inferred human deleterious effect sizes; two individuals will typically differ in fitness by 15-40%. The need to compensate for the deluge of deleterious mutations slows net adaptation (i.e. to the external environment) by ~13%-55%. The rate of beneficial fixations is more sensitive to changes in the mutation rate than the rate of deleterious fixations is. As a surprising consequence of this, an increase (e.g. 10%) in overall mutation rate leads to faster adaptation; this puts to rest dysgenic fears about increasing mutation rates due to rising paternal age.

Intratumoral heterogeneity and drug resistance in cancer

Intratumoral heterogeneity is the main cause of tumor treatment failure, varying across disease sites (spatial heterogeneity) and polyclonal properties of tumors that evolve over time (temporal heterogeneity). As our understanding of intratumoral heterogeneity, the formation of which is mainly related to the genomic instability, epigenetic modifications, plastic gene expression, and different microenvironments, plays a substantial role in drug-resistant as far as tumor metastasis and recurrence. Understanding the role of intratumoral heterogeneity, it becomes clear that a single therapeutic agent or regimen may only be effective for subsets of cells with certain features, but not for others. This necessitates a shift from our current, unchanging treatment approach to one that is tailored against the killing patterns of cancer cells in different clones. In this review, we discuss recent evidence concerning global perturbations of intratumoral heterogeneity, associations of specific intratumoral heterogeneity in lung cancer, the underlying mechanisms of intratumoral heterogeneity potentially leading to formation, and how it drives drug resistance. Our findings highlight the most up-to-date progress in intratumoral heterogeneity and its role in mediating tumor drug resistance, which could support the development of future treatment strategies.

Stable hypermutators revealed by the genomic landscape of DNA repair genes among yeast species

Mutator phenotypes are short-lived due to the rapid accumulation of deleterious mutations. Yet, recent observations reveal that certain fungi can undergo prolonged accelerated evolution after losing DNA repair genes. Here, we surveyed 1,154 yeast genomes representing nearly all known yeast species of the subphylum Saccharomycotina to examine the relationship between reduced DNA repair repertoires and elevated evolutionary rates. We identified three distantly related lineages-encompassing 12% of species-with substantially reduced sets of DNA repair genes and the highest evolutionary rates in the entire subphylum. Two of these "faster-evolving lineages" (FELs)-a subclade within the order Pichiales and the Wickerhamiella/Starmerella (W/S) clade (order Dipodascales)-are described here for the first time, while the third corresponds to a previously documented Hanseniaspora FEL. Examination of DNA repair gene repertoires revealed a set of genes predominantly absent in these three FELs, suggesting a potential role in the observed acceleration of evolutionary rates. Genomic signatures in the W/S clade are consistent with a substantial mutational burden, including pronounced A|T bias and signatures of endogenous DNA damage. The W/S clade appears to mitigate UV-induced damage through horizontal acquisition of a bacterial photolyase gene, underscoring how gene loss may be offset by nonvertical evolution. These findings highlight how the loss of DNA repair genes gave rise to hypermutators that persist across macroevolutionary timescales, with horizontal gene transfer as an avenue for partial functional compensation.

Efficient detection and characterization of targets of natural selection using transfer learning

Natural selection leaves detectable patterns of altered spatial diversity within genomes, and identifying affected regions is crucial for understanding species evolution. Recently, machine learning approaches applied to raw population genomic data have been developed to uncover these adaptive signatures. Convolutional neural networks (CNNs) are particularly effective for this task, as they handle large data arrays while maintaining element correlations. However, shallow CNNs may miss complex patterns due to their limited capacity, while deep CNNs can capture these patterns but require extensive data and computational power. Transfer learning addresses these challenges by utilizing a deep CNN pre-trained on a large dataset as a feature extraction tool for downstream classification and evolutionary parameter prediction. This approach reduces extensive training data generation requirements and computational needs while maintaining high performance. In this study, we developed TrIdent, a tool that uses transfer learning to enhance detection of adaptive genomic regions from image representations of multilocus variation. We evaluated TrIdent across various genetic, demographic, and adaptive settings, in addition to unphased data and other confounding factors. TrIdent demonstrated improved detection of adaptive regions compared to recent methods using similar data representations. We further explored model interpretability through class activation maps and adapted TrIdent to infer selection parameters for identified adaptive candidates. Using whole-genome haplotype data from European and African populations, TrIdent effectively recapitulated known sweep candidates and identified novel cancer, and other disease-associated genes as potential sweeps.

Characterizing the Rates and Patterns of De Novo Germline Mutations in the Aye-Aye (Daubentonia madagascariensis)

Given the many levels of biological variation in mutation rates observed to date in primates-spanning from species to individuals to genomic regions-future steps in our understanding of mutation rate evolution will not only be aided by a greater breadth of species coverage across the primate clade but also by a greater depth as afforded by an evaluation of multiple trios within individual species. In order to help bridge these gaps, we here present an analysis of a species representing one of the most basal splits on the primate tree (aye-ayes), combining whole-genome sequencing of seven parent-offspring trios from a three-generation pedigree with a novel computational pipeline that takes advantage of recently developed pan-genome graphs, thereby circumventing the application of (highly subjective) quality metrics that has previously been shown to result in notable differences in the detection of de novo mutations and ultimately estimates of mutation rates. This deep sampling has enabled both a detailed picture of parental age effects and sex dependency in mutation rates, which we here compare with previously studied primates, but has also provided unique insights into the nature of genetic variation in one of the most endangered primates on the planet.

Gene therapy for intracranial aneurysms: systemic review

Treatment of intracranial aneurysms is currently limited to invasive surgical and endovascular modalities, and some aneurysms are not treatable with these methods. Identification and targeting of specific molecular pathways involved in the pathogenesis of aneurysms may improve outcomes. Low frequency somatic variants found in cancer related genes have been linked to intracranial aneurysm development. In particular, mutations in the PDGFRB gene lead to constitutively activated ERK and nuclear factor κB signaling pathways, which can be targeted with tyrosine kinase inhibitors. In this review, we describe how low frequency somatic variants in oncogenic and other genes affect the pathogenesis of aneurysm development, with a focus on gene therapy applications, such as endovascular in situ delivery of chemotherapeutics.

Landscape of human protein-coding somatic mutations across tissues and individuals

Although somatic mutations are fundamentally important to human biology, disease, and aging, many outstanding questions remain about their rates, spectrum, and determinants in apparently healthy tissues. Here, we performed high-coverage exome sequencing on 265 samples from 14 GTEx donors sampled for a median of 17.5 tissues per donor (spanning 46 total tissues). Using a novel probabilistic method tailored to the unique structure of our data, we identified 8,470 somatic variants. We leverage our compendium of somatic mutations to quantify the burden of deleterious somatic variants among tissues and individuals, identify molecular features such as chromatin accessibility that exhibit significantly elevated somatic mutation rates, provide novel biological insights into mutational mechanisms, and infer developmental trajectories based on patterns of multi-tissue somatic mosaicism. Our data provides a high-resolution portrait of somatic mutations across genes, tissues, and individuals.

HBV DNA integration and somatic mutations in HCC patients with HBV-HCV dual infection reveals profiles intermediate between HBV- and HCV-related HCC

BACKGROUND

In regions with a high prevalence of chronic hepatitis B virus (HBV) and hepatitis C virus (HCV) infections, coinfected patients face a heightened risk of developing hepatocellular carcinoma (HCC), termed HBV/HCV-related HCC (HBCV-HCC). We aimed to investigate the contribution of preexisting chronic hepatitis B (CHB) and subsequent chronic hepatitis C (CHC) to the development of HBCV-HCC.

METHODS

We examined HBV's involvement in 93 HBCV-HCC cases by analyzing HBV DNA integration as an indicator of HCC originating from HBV-infected hepatocytes, compared with 164 HBV-HCCs and 56 HCV-HCCs as controls.

RESULTS

Next generation sequencing revealed that 55% of HBCV-HCCs exhibited clonal HBV integration, which falls between the rates observed in HBV-HCCs (88%) and HCV-HCCs (7%), with similar integration patterns to HBV-HCCs. Common HCC somatic mutation analysis indicated HCV superinfection in HBCV-HCCs correlated with increased mutation rates in the telomerase reverse transcriptase (TERT) promoter and beta-catenin genes. Transcriptome analysis showed a prevalence of replicating HCV over HBV in HBCV-HCCs, with preexisting HBV exerting a proliferative role. The comparison of clinical characteristics revealed similarities between HBCV-HCC and HCV-HCC patients, including later onset for HBCV-HCC, possibly due to HCV superinfection slowing carcinogenesis. Notably, HBCV-HCCs with the same driver mutation, HBV integration at the TERT promoter, tended to develop later and showed a better prognosis post-tumor resection than HBV-HCCs.

CONCLUSIONS

Our findings shed light on the interplay between preexisting CHB and subsequent CHC in elevating the risk of HBCV-HCC. These insights are crucial for understanding viral etiology-specific carcinogenesis and guiding surveillance policies for HBCV-HCC post-antiviral therapy.

Genetic and epigenetic alterations in aging and rejuvenation of human

All the information essential for life is encoded within our genome and epigenome, which orchestrates diverse cellular states spatially and temporally. In particular, the epigenome interacts with internal and external stimuli, encoding and preserving cellular experiences, and it serves as the regulatory base of the transcriptome across diverse cell types. The emergence of single-cell transcriptomic and epigenomic data collection has revealed unique omics signatures in diverse tissues, highlighting cellular heterogeneity. Recent research has documented age-related epigenetic changes at the single-cell level, alongside the validation of cellular rejuvenation through partial reprogramming, which involves simultaneous epigenetic modifications. These dynamic shifts, primarily fueled by stem cell plasticity, have catalyzed significant interest and cross-disciplinary research endeavors. This review explores the genomic and epigenomic alterations with aging, elucidating their reciprocal interactions. Additionally, it seeks to discuss the evolving landscape of rejuvenation research, with a particular emphasis on dissecting stem cell behavior through the lens of single-cell analysis. Moreover, it proposes potential research methodologies for future studies.

Characterizing the rates and patterns of de novo germline mutations in the aye-aye (Daubentonia madagascariensis)

Given the many levels of biological variation in mutation rates observed to date in primates - spanning from species to individuals to genomic regions - future steps in our understanding of mutation rate evolution will be aided by both a greater breadth of species coverage across the primate clade, but also by a greater depth as afforded by an evaluation of multiple trios within individual species. In order to help bridge these gaps, we here present an analysis of a species representing one of the most basal splits on the primate tree (aye-ayes), combining whole-genome sequencing of seven parent-offspring trios from a three-generation pedigree with a novel computational pipeline that takes advantage of recently developed pan-genome graphs, thereby circumventing the application of (highly subjective) quality metrics that has previously been shown to result in notable differences in the detection of de novo mutations, and ultimately estimates of mutation rates. This deep sampling has enabled both a detailed picture of parental age effects as well as sex dependency in mutation rates which we here compare with previously studied primates, but has also provided unique insights into the nature of genetic variation in one of the most endangered primates on the planet.

Estimating the Number of Polygenic Diseases Among Six Mutually Exclusive Entities of Non-Tumors and Cancer

In the era of precision medicine with increasing amounts of sequenced cancer and non-cancer genomes of different ancestries, we here enumerate the resulting polygenic disease entities. Based on the cell number status, we first identified six fundamental types of polygenic illnesses, five of which are non-cancerous. Like complex, non-tumor disorders, neoplasms normally carry alterations in multiple genes, including in 'Drivers' and 'Passengers'. However, tumors also lack certain genetic alterations/epigenetic changes, recently named 'Goners', which are toxic for the neoplasm and potentially constitute therapeutic targets. Drivers are considered essential for malignant transformation, whereas environmental influences vary considerably among both types of polygenic diseases. For each form, hyper-rare disorders, defined as affecting <1/108 individuals, likely represent the largest number of disease entities. Loss of redundant tumor-suppressor genes exemplifies such a profoundly rare mutational event. For non-tumor, polygenic diseases, pathway-centered taxonomies seem preferable. This classification is not readily feasible in cancer, but the inclusion of Drivers and possibly also of epigenetic changes to the existing nomenclature might serve as initial steps in this direction. Based on the detailed genetic alterations, the number of polygenic diseases is essentially countless, but different forms of nosologies may be used to restrict the number.

Characterization and distribution of de novo mutations in the zebra finch

Germline de novo mutations (DNMs) provide the raw material for evolution. The DNM rate varies considerably between species, sexes and chromosomes. Here, we identify DNMs in the zebra finch (Taeniopygia guttata) across 16 parent-offspring trios using two genome assemblies of different quality. Using an independent genotyping assay, we validate 82% of the 150 candidate DNMs. DNM rates are consistent between both assemblies, with estimates of 6.14 × 10-9 and 6.36 × 10-9 per site per generation. We observe a strong paternal bias in DNM rates (male-to-female ratio ɑ ≈ 4), but this bias is in transition mutations only, leading to a transition-to-transversion ratio of 3.18 and 3.57. Finally, we find that DNMs tend to be randomly distributed across chromosomes, not associated with recombination hotspots or genic regions. However, the sex chromosome chrZ shows a roughly fourfold increased DNM rate compared to autosomes, which is more than the expected increase due to chrZ spending two-thirds of its time in males. Overall, our results further enhance our understanding of DNMs in passerine songbirds.

Genome-wide patterns of selection-drift variation strongly associate with organismal traits across the green plant lineage

There are many gaps in our knowledge of how life cycle variation and organismal body architecture associate with molecular evolution. Using the diverse range of green algal body architectures and life cycle types as a test case, we hypothesize that increases in cytomorphological complexity are likely to be associated with a decrease in the effective population size, because larger-bodied organisms typically have smaller populations, resulting in increased drift. For life cycles, we expect haploid-dominant lineages to evolve under stronger selection intensity relative to diploid-dominant life cycles owing to masking of deleterious alleles in heterozygotes. We use a genome-scale data set spanning the phylogenetic diversity of green algae and phylogenetic comparative approaches to measure the relative selection intensity across different trait categories. We show stronger signatures of drift in lineages with more complex body architectures compared with unicellular lineages, which we consider to be a consequence of smaller effective population sizes of the more complex algae. Significantly higher rates of synonymous as well as nonsynonymous substitutions relative to other algal body architectures highlight that siphonous and siphonocladous body architectures, characteristic of many green seaweeds, form an interesting test case to study the potential impacts of genome redundancy on molecular evolution. Contrary to expectations, we show that levels of selection efficacy do not show a strong association with life cycle types in green algae. Taken together, our results underline the prominent impact of body architecture on the molecular evolution of green algal genomes.

An estimate of fitness reduction from mutation accumulation in a mammal allows assessment of the consequences of relaxed selection

Each generation, spontaneous mutations introduce heritable changes that tend to reduce fitness in populations of highly adapted living organisms. This erosion of fitness is countered by natural selection, which keeps deleterious mutations at low frequencies and ultimately removes most of them from the population. The classical way of studying the impact of spontaneous mutations is via mutation accumulation (MA) experiments, where lines of small effective population size are bred for many generations in conditions where natural selection is largely removed. Such experiments in microbes, invertebrates, and plants have generally demonstrated that fitness decays as a result of MA. However, the phenotypic consequences of MA in vertebrates are largely unknown, because no replicated MA experiment has previously been carried out. This gap in our knowledge is relevant for human populations, where societal changes have reduced the strength of natural selection, potentially allowing deleterious mutations to accumulate. Here, we study the impact of spontaneous MA on the mean and genetic variation for quantitative and fitness-related traits in the house mouse using the MA experimental design, with a cryopreserved control to account for environmental influences. We show that variation for morphological and life history traits accumulates at a sufficiently high rate to maintain genetic variation and selection response. Weight and tail length measures decrease significantly between 0.04% and 0.3% per generation with narrow confidence intervals. Fitness proxy measures (litter size and surviving offspring) decrease on average by about 0.2% per generation, but with confidence intervals overlapping zero. When extrapolated to humans, our results imply that the rate of fitness loss should not be of concern in the foreseeable future.

Utilizing biological experimental data and molecular dynamics for the classification of mutational hotspots through machine learning

Motivation

Benzo[a]pyrene, a notorious DNA-damaging carcinogen, belongs to the family of polycyclic aromatic hydrocarbons commonly found in tobacco smoke. Surprisingly, nucleotide excision repair (NER) machinery exhibits inefficiency in recognizing specific bulky DNA adducts including Benzo[a]pyrene Diol-Epoxide (BPDE), a Benzo[a]pyrene metabolite. While sequence context is emerging as the leading factor linking the inadequate NER response to BPDE adducts, the precise structural attributes governing these disparities remain inadequately understood. We therefore combined the domains of molecular dynamics and machine learning to conduct a comprehensive assessment of helical distortion caused by BPDE-Guanine adducts in multiple gene contexts. Specifically, we implemented a dual approach involving a random forest classification-based analysis and subsequent feature selection to identify precise topological features that may distinguish adduct sites of variable repair capacity. Our models were trained using helical data extracted from duplexes representing both BPDE hotspot and nonhotspot sites within the TP53 gene, then applied to sites within TP53, cII, and lacZ genes.

Results

We show our optimized model consistently achieved exceptional performance, with accuracy, precision, and f1 scores exceeding 91%. Our feature selection approach uncovered that discernible variance in regional base pair rotation played a pivotal role in informing the decisions of our model. Notably, these disparities were highly conserved among TP53 and lacZ duplexes and appeared to be influenced by the regional GC content. As such, our findings suggest that there are indeed conserved topological features distinguishing hotspots and nonhotpot sites, highlighting regional GC content as a potential biomarker for mutation.

Availability and implementation

Code for comparing machine learning classifiers and evaluating their performance is available at https://github.com/jdavies24/ML-Classifier-Comparison, and code for analysing DNA structure with Curves+ and Canal using Random Forest is available at https://github.com/jdavies24/ML-classification-of-DNA-trajectories.

Mutation accumulation in H. sapiens F508del CFTR countermands dN/dS type genomic analysis

Understanding the mechanisms that underlie de novo mutations (DNMs) can be essential for interpreting human evolution, including aspects such as rapidly diverging genes, conservation of non-coding regulatory elements, and somatic DNA adaptation, among others. DNM accumulation in Homo sapiens is often limited to evaluation of human trios or quads across a single generation. Moreover, human SNPs in exons, pseudogenes, or other non-coding elements can be ancient and difficult to date, including polymorphisms attributable to founder effects and identity by descent. In this report, we describe multigenerational evolution of a human coding locus devoid of natural selection, and delineate patterns and principles by which DNMs have accumulated over the past few thousand years. We apply a data set comprising cystic fibrosis transmembrane conductance regulator (CFTR) alleles from 2,393 individuals homozygous for the F508del defect. Additional polymorphism on the F508del background diversified subsequent to a single mutational event during recent human history. Because F508del CFTR is without function, SNPs observed on this haplotype are effectively attributable to factors that govern accumulating de novo mutations. We show profound enhancement of transition, synonymous, and positionally repetitive polymorphisms, indicating appearance of DNMs in a manner evolutionarily designed to protect protein coding DNA against mutational attrition while promoting diversity.

Post-implantation analysis of genomic variations in the progeny from developing fetus to birth

The analysis of genomic variations in offspring after implantation has been infrequently studied. In this study, we aim to investigate the extent of de novo mutations in humans from developing fetus to birth. Using high-depth whole-genome sequencing, 443 parent-offspring trios were studied to compare the results of de novo mutations (DNMs) between different groups. The focus was on fetuses and newborns, with DNA samples obtained from the families' blood and the aspirated embryonic tissues subjected to deep sequencing. It was observed that the average number of total DNMs in the newborns group was 56.26 (54.17-58.35), which appeared to be lower than that the multifetal reduction group, which was 76.05 (69.70-82.40) (F = 2.42, P = 0.12). However, after adjusting for parental age and maternal pre-pregnancy body mass index (BMI), significant differences were found between the two groups. The analysis was further divided into single nucleotide variants (SNVs) and insertion/deletion of a small number of bases (indels), and it was discovered that the average number of de novo SNVs associated with the multifetal reduction group and the newborn group was 49.89 (45.59-54.20) and 51.09 (49.22-52.96), respectively. No significant differences were noted between the groups (F = 1.01, P = 0.32). However, a significant difference was observed for de novo indels, with a higher average number found in the multifetal reduction group compared to the newborn group (F = 194.17, P < 0.001). The average number of de novo indels among the multifetal reduction group and the newborn group was 26.26 (23.27-29.05) and 5.17 (4.82-5.52), respectively. To conclude, it has been observed that the quantity of de novo indels in the newborns experiences a significant decrease when compared to that in the aspirated embryonic tissues (7-9 weeks). This phenomenon is evident across all genomic regions, highlighting the adverse effects of de novo indels on the fetus and emphasizing the significance of embryonic implantation and intrauterine growth in human genetic selection mechanisms.

The effectiveness of selection in a species affects the direction of amino acid frequency evolution

Nearly neutral theory predicts that species with higher effective population size (N e ) are better able to purge slightly deleterious mutations. We compare evolution in high-N e vs. low-N e vertebrates to reveal which amino acid frequencies are subject to subtle selective preferences. We take three complementary approaches, two measuring flux and one measuring outcomes. First, we fit non-stationary substitution models of amino acid flux using maximum likelihood, comparing the high-N e clade of rodents and lagomorphs to its low-N e sister clade of primates and colugos. Second, we compare evolutionary outcomes across a wider range of vertebrates, via correlations between amino acid frequencies and N e . Third, we dissect the details of flux in human, chimpanzee, mouse, and rat, as scored by parsimony - this also enables comparison to a historical paper. All three methods agree on which amino acids are preferred under more effective selection. Preferred amino acids tend to be smaller, less costly to synthesize, and to promote intrinsic structural disorder. Parsimony-induced bias in the historical study produces an apparent reduction in structural disorder, perhaps driven by slightly deleterious substitutions. Within highly exchangeable pairs of amino acids, arginine is strongly preferred over lysine, and valine over isoleucine, consistent with more effective selection preferring a marginally larger free energy of folding. These two preferences match differences between thermophiles and mesophilic relatives. These results reveal the biophysical consequences of mutation-selection-drift balance, and demonstrate the utility of nearly neutral theory for understanding protein evolution.

Pathogenic variants in human DNA damage repair genes mostly arose after the latest human out-of-Africa migration

Introduction

The DNA damage repair (DDR) system in human genome is pivotal in maintaining genomic integrity. Pathogenic variation (PV) in DDR genes impairs their function, leading to genome instability and increased susceptibility to diseases, especially cancer. Understanding the evolution origin and arising time of DDR PV is crucial for comprehending disease susceptibility in modern humans.

Methods

We used big data approach to identify the PVs in DDR genes in modern humans. We mined multiple genomic databases derived from 251,214 modern humans of African and non-Africans. We compared the DDR PVs between African and non-African. We also mined the DDR PVs in the genomic data derived from 5,031 ancient humans. We used the DDR PVs from ancient humans as the intermediate to further the DDR PVs between African and non-African.

Results and discussion

We identified 1,060 single-base DDR PVs across 77 DDR genes in modern humans of African and non-African. Direct comparison of the DDR PVs between African and non-African showed that 82.1% of the non-African PVs were not present in African. We further identified 397 single-base DDR PVs in 56 DDR genes in the 5,031 ancient humans dated between 45,045 and 100 years before present (BP) lived in Eurasian continent therefore the descendants of the latest out-of-Africa human migrants occurred 50,000-60,000 years ago. By referring to the ancient DDR PVs, we observed that 276 of the 397 (70.3%) ancient DDR PVs were exclusive in non-African, 106 (26.7%) were shared between non-African and African, and only 15 (3.8%) were exclusive in African. We further validated the distribution pattern by testing the PVs in BRCA and TP53, two of the important genes in genome stability maintenance, in African, non-African, and Ancient humans. Our study revealed that DDR PVs in modern humans mostly emerged after the latest out-of-Africa migration. The data provides a foundation to understand the evolutionary basis of disease susceptibility, in particular cancer, in modern humans.

Haploinsufficiency underlies the neurodevelopmental consequences of SLC6A1 variants

Heterozygous variants in SLC6A1, encoding the GAT-1 GABA transporter, are associated with seizures, developmental delay, and autism. The majority of affected individuals carry missense variants, many of which are recurrent germline de novo mutations, raising the possibility of gain-of-function or dominant-negative effects. To understand the functional consequences, we performed an in vitro GABA uptake assay for 213 unique variants, including 24 control variants. De novo variants consistently resulted in a decrease in GABA uptake, in keeping with haploinsufficiency underlying all neurodevelopmental phenotypes. Where present, ClinVar pathogenicity reports correlated well with GABA uptake data; the functional data can inform future reports for the remaining 72% of unscored variants. Surface localization was assessed for 86 variants; two-thirds of loss-of-function missense variants prevented GAT-1 from being present on the membrane while GAT-1 was on the surface but with reduced activity for the remaining third. Surprisingly, recurrent de novo missense variants showed moderate loss-of-function effects that reduced GABA uptake with no evidence for dominant-negative or gain-of-function effects. Using linear regression across multiple missense severity scores to extrapolate the functional data to all potential SLC6A1 missense variants, we observe an abundance of GAT-1 residues that are sensitive to substitution. The extent of this missense vulnerability accounts for the clinically observed missense enrichment; overlap with hypermutable CpG sites accounts for the recurrent missense variants. Strategies to increase the expression of the wild-type SLC6A1 allele are likely to be beneficial across neurodevelopmental disorders, though the developmental stage and extent of required rescue remain unknown.

Relationships between genomic dissipation and de novo SNP evolution

Patterns of single nucleotide polymorphisms (SNPs) in eukaryotic DNA are traditionally attributed to selective pressure, drift, identity descent, or related factors-without accounting for ways in which bias during de novo SNP formation, itself, might contribute. A functional and phenotypic analysis based on evolutionary resilience of DNA points to decreased numbers of non-synonymous SNPs in human and other genomes, with a predominant component of SNP depletion in the human gene pool caused by robust preferences during de novo SNP formation (rather than selective constraint). Ramifications of these findings are broad, belie a number of concepts regarding human evolution, and point to a novel interpretation of evolving DNA across diverse species.

Responses to commentaries on "The gene: An appraisal"

The central conclusions of "The Gene: An Appraisal" are that genetic variance does not underpin biological evolution, and, therefore, that genes are not Mendel's units of inheritance. In this response, I will address the criticisms I have received via commentaries on that paper by defending the following statements: 1. Epistasis does not explain the power-law fitness profile of the Long-Term Evolution Experiment (LTEE). The data from the evolution of natural systems displays the power-law form ubiquitously. Epistasis plays no role in evolution. 2. The common characteristics of living things (natural systems) are described by the principle of least action in de Maupertuis's original form, which is synonymous with the 2nd law of thermodynamics and Newton's 2nd law of motion in its complete form, i.e., F = dp/dt. Organisms strive to achieve free energy balance with their environments. 3. Based on an appraisal of the scientific environment between 1880 and 1911, I conclude that Johannsen's genotype conception was perhaps, the only option available to him. 4. The power-law fitness profile of the LTEE falsifies Fisher's Genetical Theory of Natural Selection, Johannsen's genotype conception, and the idea that 'Darwinian evolution' is an exception to the generic thermodynamic process of evolution in natural systems. 5. The use of the technique of genome-wide association to identify the causes and the likelihoods of inherited common diseases and behavioural traits is a 'wild goose chase' because genes are not the units of inheritance.

Bridging horizons beyond CIRCULATE-Japan: a new paradigm in molecular residual disease detection via whole genome sequencing-based circulating tumor DNA assay

Circulating tumor DNA (ctDNA) is the fraction of cell-free DNA in patient blood that originates from a tumor. Advances in DNA sequencing technologies and our understanding of the molecular biology of tumors have increased interest in exploiting ctDNA to facilitate detection of molecular residual disease (MRD). Analysis of ctDNA as a promising MRD biomarker of solid malignancies has a central role in precision medicine initiatives exemplified by our CIRCULATE-Japan project involving patients with resectable colorectal cancer. Notably, the project underscores the prognostic significance of the ctDNA status at 4 weeks post-surgery and its correlation to adjuvant therapy efficacy at interim analysis. This substantiates the hypothesis that MRD is a critical prognostic indicator of relapse in patients with colorectal cancer. Despite remarkable advancements, challenges endure, primarily attributable to the exceedingly low ctDNA concentration in peripheral blood, particularly in scenarios involving low tumor shedding and the intrinsic error rates of current sequencing technologies. These complications necessitate more sensitive and sophisticated assays to verify the clinical utility of MRD across all solid tumors. Whole genome sequencing (WGS)-based tumor-informed MRD assays have recently demonstrated the ability to detect ctDNA in the parts-per-million range. This review delineates the current landscape of MRD assays, highlighting WGS-based approaches as the forefront technique in ctDNA analysis. Additionally, it introduces our upcoming endeavor, WGS-based pan-cancer MRD detection via ctDNA, in our forthcoming project, SCRUM-Japan MONSTAR-SCREEN-3.

Statistical methods for assessing the effects of de novo variants on birth defects

With the development of next-generation sequencing technology, de novo variants (DNVs) with deleterious effects can be identified and investigated for their effects on birth defects such as congenital heart disease (CHD). However, statistical power is still limited for such studies because of the small sample size due to the high cost of recruiting and sequencing samples and the low occurrence of DNVs. DNV analysis is further complicated by genetic heterogeneity across diseased individuals. Therefore, it is critical to jointly analyze DNVs with other types of genomic/biological information to improve statistical power to identify genes associated with birth defects. In this review, we discuss the general workflow, recent developments in statistical methods, and future directions for DNV analysis.

Phenotypic Heterogeneity, Bidirectionality, Universal Cues, Plasticity, Mechanics, and the Tumor Microenvironment Drive Cancer Metastasis

Tumor diseases become a huge problem when they embark on a path that advances to malignancy, such as the process of metastasis. Cancer metastasis has been thoroughly investigated from a biological perspective in the past, whereas it has still been less explored from a physical perspective. Until now, the intraluminal pathway of cancer metastasis has received the most attention, while the interaction of cancer cells with macrophages has received little attention. Apart from the biochemical characteristics, tumor treatments also rely on the tumor microenvironment, which is recognized to be immunosuppressive and, as has recently been found, mechanically stimulates cancer cells and thus alters their functions. The review article highlights the interaction of cancer cells with other cells in the vascular metastatic route and discusses the impact of this intercellular interplay on the mechanical characteristics and subsequently on the functionality of cancer cells. For instance, macrophages can guide cancer cells on their intravascular route of cancer metastasis, whereby they can help to circumvent the adverse conditions within blood or lymphatic vessels. Macrophages induce microchannel tunneling that can possibly avoid mechanical forces during extra- and intravasation and reduce the forces within the vascular lumen due to vascular flow. The review article highlights the vascular route of cancer metastasis and discusses the key players in this traditional route. Moreover, the effects of flows during the process of metastasis are presented, and the effects of the microenvironment, such as mechanical influences, are characterized. Finally, the increased knowledge of cancer metastasis opens up new perspectives for cancer treatment.

Germline and somatic testing for ovarian Cancer: An SGO clinical practice statement

Germline and somatic genetic testing have become critical components of care for people with ovarian cancer. The identification of germline and somatic pathogenic variants as well as homologous recombination deficiency can contribute to the prediction of treatment response, prognostic outcome, and suitability for targeted agents (e.g. poly (ADP-ribose) polymerase (PARP) inhibitors). Furthermore, identifying germline pathogenic variants can prompt cascade genetic testing for at-risk relatives. Despite the clinical benefits and consensus recommendations from several organizations calling for universal genetic testing in ovarian cancer, only about one third of patients complete germline or somatic genetic testing. The members of the Society of Gynecologic Oncology (SGO) Clinical Practice Committee have composed this statement to provide an overview of germline and somatic genetic testing for patients with epithelial ovarian cancer, focusing on available testing modalities and options for care delivery.

Inferring compound heterozygosity from large-scale exome sequencing data

Recessive diseases arise when both copies of a gene are impacted by a damaging genetic variant. When a patient carries two potentially causal variants in a gene, accurate diagnosis requires determining that these variants occur on different copies of the chromosome (that is, are in trans) rather than on the same copy (that is, in cis). However, current approaches for determining phase, beyond parental testing, are limited in clinical settings. Here we developed a strategy for inferring phase for rare variant pairs within genes, leveraging genotypes observed in the Genome Aggregation Database (v2, n = 125,748 exomes). Our approach estimates phase with 96% accuracy, both in trio data and in patients with Mendelian conditions and presumed causal compound heterozygous variants. We provide a public resource of phasing estimates for coding variants and counts per gene of rare variants in trans that can aid interpretation of rare co-occurring variants in the context of recessive disease.

The Gene: An appraisal

The gene can be described as the foundational concept of modern biology. As such, it has spilled over into daily discourse, yet it is acknowledged among biologists to be ill-defined. Here, following a short history of the gene, I analyse critically its role in inheritance, evolution, development, and morphogenesis. Wilhelm Johannsen's genotype-conception, formulated in 1910, has been adopted as the foundation stone of genetics, giving the gene a higher degree of prominence than is justified by the evidence. An analysis of the results of the Long-Term Evolution Experiment (LTEE) with E. coli bacteria, grown over 60,000 generations, does not support spontaneous gene mutation as the source of variance for natural selection. From this it follows that the gene is not Mendel's unit of inheritance: that must be Johannsen's transmission-conception at the gamete phenotype level, a form of inheritance that Johannsen did not consider. Alternatively, I contend that biology viewed on the bases of thermodynamics, complex system dynamics, and self-organisation, provides a new framework for the foundations of biology. In this framework, the gene plays a passive role as a vital information store: it is the phenotype that plays the active role in inheritance, evolution, development, and morphogenesis.

Polymorphic short tandem repeats make widespread contributions to blood and serum traits

Short tandem repeats (STRs) are genomic regions consisting of repeated sequences of 1-6 bp in succession. Single-nucleotide polymorphism (SNP)-based genome-wide association studies (GWASs) do not fully capture STR effects. To study these effects, we imputed 445,720 STRs into genotype arrays from 408,153 White British UK Biobank participants and tested for association with 44 blood phenotypes. Using two fine-mapping methods, we identify 119 candidate causal STR-trait associations and estimate that STRs account for 5.2%-7.6% of causal variants identifiable from GWASs for these traits. These are among the strongest associations for multiple phenotypes, including a coding CTG repeat associated with apolipoprotein B levels, a promoter CGG repeat with platelet traits, and an intronic poly(A) repeat with mean platelet volume. Our study suggests that STRs make widespread contributions to complex traits, provides stringently selected candidate causal STRs, and demonstrates the need to consider a more complete view of genetic variation in GWASs.

Ultra-high static magnetic field induces a change in the spectrum but not frequency of DNA spontaneous mutations in Arabidopsis thaliana

Biological effects of magnetic fields have been extensively studied in plants, microorganisms and animals, and applications of magnetic fields in regulation of plant growth and phytoprotection is a promising field in sustainable agriculture. However, the effect of magnetic fields especially ultra-high static magnetic field (UHSMF) on genomic stability is largely unclear. Here, we investigated the mutagenicity of 24.5, 30.5 and 33.0 T UHSMFs with the gradient of 150, 95 and 0 T/m, respectively, via whole genome sequencing. Our results showed that 1 h exposure of Arabidopsis dried seeds to UHSMFs has no significant effect on the average rate of DNA mutations including single nucleotide variations and InDels (insertions and deletions) in comparison with the control, but 33.0 T and 24.5 T treatments lead to a significant change in the rate of nucleotide transitions and InDels longer than 3 bp, respectively, suggesting that both strength and gradient of UHSMF impact molecular spectrum of DNA mutations. We also found that the decreased transition rate in UHSMF groups is correlated with the upstream flanking sequences of G and C mutation sites. Furthermore, the germination rate of seeds exposed to 24.5 T SMF with -150 T/m gradient showed a significant decrease at 24 hours after sowing. Overall, our data lay a basis for precisely assessing the potential risk of UHSMF on DNA stability, and for elucidating molecular mechanism underlying gradient SMF-regulated biological processes in the future.

Background radiation and cancer risks: A major intellectual confrontation within the domain of radiation genetics with multiple converging biological disciplines

This paper assesses the judgments of leading radiation geneticists and cancer risk assessment scientists from the mid-1950s to mid-1970s that background radiation has a significant effect on human genetic disease and cancer incidence. This assumption was adopted by the National Academy of Sciences (NAS) Biological Effects of Atomic Radiation (BEAR) I Genetics Panel for genetic diseases and subsequently applied to cancer risk assessment by other leading individuals/advisory groups (e.g., International Commission on Radiation Protection-ICRP). These recommendations assumed that a sizeable proportion of human mutations originated from background radiation due to cumulative exposure over prolonged reproductive periods and the linear nature of the dose-response. This paper shows that the assumption that background radiation is a significant cause of spontaneous mutation, genetic diseases, and cancer incidence is not supported by experimental and epidemiological findings, and discredits erroneous risk assessments that improperly influenced the recommendations of national and international advisory committees, risk assessment policies, and beliefs worldwide.

MitoTracer facilitates the identification of informative mitochondrial mutations for precise lineage reconstruction

Mitochondrial (MT) mutations serve as natural genetic markers for inferring clonal relationships using single cell sequencing data. However, the fundamental challenge of MT mutation-based lineage tracing is automated identification of informative MT mutations. Here, we introduced an open-source computational algorithm called "MitoTracer", which accurately identified clonally informative MT mutations and inferred evolutionary lineage from scRNA-seq or scATAC-seq samples. We benchmarked MitoTracer using the ground-truth experimental lineage sequencing data and demonstrated its superior performance over the existing methods measured by high sensitivity and specificity. MitoTracer is compatible with multiple single cell sequencing platforms. Its application to a cancer evolution dataset revealed the genes related to primary BRAF-inhibitor resistance from scRNA-seq data of BRAF-mutated cancer cells. Overall, our work provided a valuable tool for capturing real informative MT mutations and tracing the lineages among cells.

Teaser

MitoTracer enables automatically and accurately discover informative mitochondrial mutations for lineage tracing.

The divergence of mutation rates and spectra across the Tree of Life

Owing to advances in genome sequencing, genome stability has become one of the most scrutinized cellular traits across the Tree of Life. Despite its centrality to all things biological, the mutation rate (per nucleotide site per generation) ranges over three orders of magnitude among species and several-fold within individual phylogenetic lineages. Within all major organismal groups, mutation rates scale negatively with the effective population size of a species and with the amount of functional DNA in the genome. This relationship is most parsimoniously explained by the drift-barrier hypothesis, which postulates that natural selection typically operates to reduce mutation rates until further improvement is thwarted by the power of random genetic drift. Despite this constraint, the molecular mechanisms underlying DNA replication fidelity and repair are free to wander, provided the performance of the entire system is maintained at the prevailing level. The evolutionary flexibility of the mutation rate bears on the resolution of several prior conundrums in phylogenetic and population-genetic analysis and raises challenges for future applications in these areas.

A Catalog of Coding Sequence Variations in Salivary Proteins' Genes Occurring during Recent Human Evolution

Saliva houses over 2000 proteins and peptides with poorly clarified functions, including proline-rich proteins, statherin, P-B peptides, histatins, cystatins, and amylases. Their genes are poorly conserved across related species, reflecting an evolutionary adaptation. We searched the nucleotide substitutions fixed in these salivary proteins' gene loci in modern humans compared with ancient hominins. We mapped 3472 sequence variants/nucleotide substitutions in coding, noncoding, and 5'-3' untranslated regions. Despite most of the detected variations being within noncoding regions, the frequency of coding variations was far higher than the general rate found throughout the genome. Among the various missense substitutions, specific substitutions detected in PRB1 and PRB2 genes were responsible for the introduction/abrogation of consensus sequences recognized by convertase enzymes that cleave the protein precursors. Overall, these changes that occurred during the recent human evolution might have generated novel functional features and/or different expression ratios among the various components of the salivary proteome. This may have influenced the homeostasis of the oral cavity environment, possibly conditioning the eating habits of modern humans. However, fixed nucleotide changes in modern humans represented only 7.3% of all the substitutions reported in this study, and no signs of evolutionary pressure or adaptative introgression from archaic hominins were found on the tested genes.

A Law of Redundancy Compounds the Problem of Cancer and Precision Medicine

Genetics and molecular biology research have progressed for over a century; however, no laws of biology resembling those of physics have been identified, despite the expectations of some physicists. It may be that it is not the properties of matter alone but evolved properties of matter in combination with atomic physics and chemistry that gave rise to the origin and complexity of life. It is proposed that any law of biology must also be a product of evolution that co-evolved with the origin and progression of life. It was suggested that molecular complexity and redundancy exponentially increase over time and have the following relationship: DNA sequence complexity (Cd) < molecular complexity (Cm) < phenotypic complexity (Cp). This study presents a law of redundancy, which together with the law of complexity, is proposed as an evolutionary law of biology. Molecular complexity and redundancy are inseparable aspects of biochemical pathways, and molecular redundancy provides the first line of defense against environmental challenges, including those of deleterious mutations. Redundancy can create problems for precision medicine because in addition to the issues arising from the involvement of multiple genes, redundancy arising from alternate pathways between genotypes and phenotypes can complicate gene detection for complex diseases and mental disorders. This study uses cancer as an example to show how cellular complexity, molecular redundancy, and hidden variation affect the ability of cancer cells to evolve and evade detection and elimination. Characterization of alternate biochemical pathways or "escape routes" can provide a step in the fight against cancer.

Model of neural development by differentiating human induced pluripotent stem cells into neural progenitor cells to study the neurodevelopmental toxicity of lead

Lead (Pb) exposure causes immeasurable damage to multiple human systems, particularly the central nervous system (CNS). In this study, human induced pluripotent stem cells (hiPSCs) were differentiated into neural progenitor cells (NPCs) to investigate the neurotoxic effects of Pb. The hiPSCs were treated with 0, 0.5, 1.0, 2.5, 5.0 and 10.0 μmol/L Pb for 7 days, whereas embryoid bodies (EBs) and NPCs were treated with 0, 0.1, 0.5, and 1.0 μmol/L Pb for 7 days. Pb exposure disrupted the cell cycle and caused apoptosis in hiPSCs, EBs, and NPCs. Besides, Pb inhibited the differentiation of NPCs and EBs. Whole exome sequencing revealed 2509, 2413, and 1984 single nucleotide variants (SNVs) caused by Pb in hiPSCs, EBs, and NPCs, respectively. The common mutation sites in the exon region were mostly nonsynonymous mutations. We identified 18, 19, and 18 common deleterious mutations in hiPSCs, EBs, and NPCs, respectively. Additionally, Online Mendelian Inheritance in Man database analysis revealed 30, 20, and 13 genes related to CNS disorders in hiPSCs, EBs, and NPCs, respectively. Our findings suggest that this in vitro model may supplement animal models and be applied to the study of neurodevelopmental toxicity in the future.

A Poisson distribution-based general model of cancer rates and a cancer risk-dependent theory of aging

This article presents a formula for modeling the lifetime incidence of cancer in humans. The formula utilizes a Poisson distribution-based "np" model to predict cancer incidence, with "n" representing the effective number of cell turnover and "p" representing the probability of single-cell transformation. The model accurately predicts the observed incidence of cancer in humans when a reduction in cell turnover due to aging is taken into account. The model also suggests that cancer development is ultimately inevitable. The article proposes a theory of aging based on this concept, called the "np" theory. According to this theory, an organism maintains its order by balancing cellular entropy through continuous proliferation. However, cellular "information entropy" in the form of accumulated DNA mutations increases irreversibly over time, restricting the total number of cells an organism can generate throughout its lifetime. When cell division slows down and fails to compensate for the increased entropy in the system, aging occurs. Essentially, aging is the phenomenon of running out of predetermined cell resources. Different species have evolved separate strategies to utilize their limited cell resources throughout their life cycle.

Emergence and influence of sequence bias in evolutionarily malleable, mammalian tandem arrays

BACKGROUND

The radiation of mammals at the extinction of the dinosaurs produced a plethora of new forms-as diverse as bats, dolphins, and elephants-in only 10-20 million years. Behind the scenes, adaptation to new niches is accompanied by extensive innovation in large families of genes that allow animals to contact the environment, including chemosensors, xenobiotic enzymes, and immune and barrier proteins. Genes in these "outward-looking" families are allelically diverse among humans and exhibit tissue-specific and sometimes stochastic expression.

RESULTS

Here, we show that these tandem arrays of outward-looking genes occupy AT-biased isochores and comprise the "tissue-specific" gene class that lack CpG islands in their promoters. Models of mammalian genome evolution have not incorporated the sharply different functions and transcriptional patterns of genes in AT- versus GC-biased regions. To examine the relationship between gene family expansion, sequence content, and allelic diversity, we use population genetic data and comparative analysis. First, we find that AT bias can emerge during evolutionary expansion of gene families in cis. Second, human genes in AT-biased isochores or with GC-poor promoters experience relatively low rates of de novo point mutation today but are enriched for non-synonymous variants. Finally, we find that isochores containing gene clusters exhibit low rates of recombination.

CONCLUSIONS

Our analyses suggest that tolerance of non-synonymous variation and low recombination are two forces that have produced the depletion of GC bases in outward-facing gene arrays. In turn, high AT content exerts a profound effect on their chromatin organization and transcriptional regulation.

Inferring compound heterozygosity from large-scale exome sequencing data

Recessive diseases arise when both the maternal and the paternal copies of a gene are impacted by a damaging genetic variant in the affected individual. When a patient carries two different potentially causal variants in a gene for a given disorder, accurate diagnosis requires determining that these two variants occur on different copies of the chromosome (i.e., are in trans) rather than on the same copy (i.e. in cis). However, current approaches for determining phase, beyond parental testing, are limited in clinical settings. We developed a strategy for inferring phase for rare variant pairs within genes, leveraging genotypes observed in exome sequencing data from the Genome Aggregation Database (gnomAD v2, n=125,748). When applied to trio data where phase can be determined by transmission, our approach estimates phase with 95.7% accuracy and remains accurate even for very rare variants (allele frequency < 1×10-4). We also correctly phase 95.9% of variant pairs in a set of 293 patients with Mendelian conditions carrying presumed causal compound heterozygous variants. We provide a public resource of phasing estimates from gnomAD, including phasing estimates for coding variants across the genome and counts per gene of rare variants in trans, that can aid interpretation of rare co-occurring variants in the context of recessive disease.

Generalised interrelations among mutation rates drive the genomic compliance of Chargaff's second parity rule

Chargaff's second parity rule (PR-2), where the complementary base and k-mer contents are matching within the same strand of a double stranded DNA (dsDNA), is a phenomenon that invited many explanations. The strict compliance of nearly all nuclear dsDNA to PR-2 implies that the explanation should also be similarly adamant. In this work, we revisited the possibility of mutation rates driving PR-2 compliance. Starting from the assumption-free approach, we constructed kinetic equations for unconstrained simulations. The results were analysed for their PR-2 compliance by employing symbolic regression and machine learning techniques. We arrived to a generalised set of mutation rate interrelations in place in most species that allow for their full PR-2 compliance. Importantly, our constraints explain PR-2 in genomes out of the scope of the prior explanations based on the equilibration under mutation rates with simpler no-strand-bias constraints. We thus reinstate the role of mutation rates in PR-2 through its molecular core, now shown, under our formulation, to be tolerant to previously noted strand biases and incomplete compositional equilibration. We further investigate the time for any genome to reach PR-2, showing that it is generally earlier than the compositional equilibrium, and well within the age of life on Earth.

Unexpected Inheritance Patterns in a Large Cohort of Patients with a Suspected Ciliopathy

Ciliopathies are rare genetic disorders caused by dysfunction of the primary or motile cilia. Their mode of inheritance is mostly autosomal recessive with biallelic pathogenic variants inherited from the parents. However, exceptions exist such as uniparental disomy (UPD) or the appearance of a de novo pathogenic variant in trans of an inherited pathogenic variant. These two genetic mechanisms are expected to be extremely rare, and few data are available in the literature, especially regarding ciliopathies. In this study, we investigated 940 individuals (812 families) with a suspected ciliopathy by Sanger sequencing, high-throughput sequencing and/or SNP array analysis and performed a literature review of UPD and de novo variants in ciliopathies. In a large cohort of 623 individuals (511 families) with a molecular diagnosis of ciliopathy (mainly Bardet-Biedl syndrome and Alström syndrome), we identified five UPD, revealing an inherited pathogenic variant and five pathogenic variants of de novo appearance (in trans of another pathogenic variant). Moreover, from these ten cases, we reported 15 different pathogenic variants of which five are novel. We demonstrated a relatively high prevalence of UPD and de novo variants in a large cohort of ciliopathies and highlighted the importance of identifying such rare genetic events, especially for genetic counseling.

The Degradation and Aging of Biological Systems as a Process of Information Loss and Entropy Increase

The problem of the degradation and aging of bioorganisms is herein considered from the viewpoint of statistical physics. Two typical timescales in biological systems-the time of metabolic processes and the time of the life cycle-are used. A kinetic equation describing the small timescales of the systems' characteristic processes in is proposed. Maintaining a biosystem in a time-stable state requires a constant inflow of negative entropy (negentropy). Ratios are proposed to evaluate the aging and degradation of systems in terms of entropy. As an example, the aging of the epithelium is studied. The connection of our approach to the information theory of aging is discussed, as well as theoretical constructions related to the concept of cooperon and its changing with time.

In silico methods for predicting functional synonymous variants

Single nucleotide variants (SNVs) contribute to human genomic diversity. Synonymous SNVs are previously considered to be "silent," but mounting evidence has revealed that these variants can cause RNA and protein changes and are implicated in over 85 human diseases and cancers. Recent improvements in computational platforms have led to the development of numerous machine-learning tools, which can be used to advance synonymous SNV research. In this review, we discuss tools that should be used to investigate synonymous variants. We provide supportive examples from seminal studies that demonstrate how these tools have driven new discoveries of functional synonymous SNVs.

Cancer driver mutations: predictions and reality

Cancer cells accumulate many genetic alterations throughout their lifetime, but only a few of them drive cancer progression, termed driver mutations. Driver mutations may vary between cancer types and patients, can remain latent for a long time and become drivers at particular cancer stages, or may drive oncogenesis only in conjunction with other mutations. The high mutational, biochemical, and histological tumor heterogeneity makes driver mutation identification very challenging. In this review we summarize recent efforts to identify driver mutations in cancer and annotate their effects. We underline the success of computational methods to predict driver mutations in finding novel cancer biomarkers, including in circulating tumor DNA (ctDNA). We also report on the boundaries of their applicability in clinical research.

Large-scale analysis of de novo mutations identifies risk genes for female infertility characterized by oocyte and early embryo defects

BACKGROUND

Oocyte maturation arrest and early embryonic arrest are important reproductive phenotypes resulting in female infertility and cause the recurrent failure of assisted reproductive technology (ART). However, the genetic etiologies of these female infertility-related phenotypes are poorly understood. Previous studies have mainly focused on inherited mutations based on large pedigrees or consanguineous patients. However, the role of de novo mutations (DNMs) in these phenotypes remains to be elucidated.

RESULTS

To decipher the role of DNMs in ART failure and female infertility with oocyte and embryo defects, we explore the landscape of DNMs in 473 infertile parent-child trios and identify a set of 481 confident DNMs distributed in 474 genes. Gene ontology analysis reveals that the identified genes with DNMs are enriched in signaling pathways associated with female reproductive processes such as meiosis, embryonic development, and reproductive structure development. We perform functional assays on the effects of DNMs in a representative gene Tubulin Alpha 4a (TUBA4A), which shows the most significant enrichment of DNMs in the infertile parent-child trios. DNMs in TUBA4A disrupt the normal assembly of the microtubule network in HeLa cells, and microinjection of DNM TUBA4A cRNAs causes abnormalities in mouse oocyte maturation or embryo development, suggesting the pathogenic role of these DNMs in TUBA4A.

CONCLUSIONS

Our findings suggest novel genetic insights that DNMs contribute to female infertility with oocyte and embryo defects. This study also provides potential genetic markers and facilitates the genetic diagnosis of recurrent ART failure and female infertility.

Interplay Between Polymorphic Short Tandem Repeats and Gene Expression Variation in Caenorhabditis elegans

Short tandem repeats (STRs) have orders of magnitude higher mutation rates than single nucleotide variants (SNVs) and have been proposed to accelerate evolution in many organisms. However, only few studies have addressed the impact of STR variation on phenotypic variation at both the organismal and molecular levels. Potential driving forces underlying the high mutation rates of STRs also remain largely unknown. Here, we leverage the recently generated expression and STR variation data among wild Caenorhabditis elegans strains to conduct a genome-wide analysis of how STRs affect gene expression variation. We identify thousands of expression STRs (eSTRs) showing regulatory effects and demonstrate that they explain missing heritability beyond SNV-based expression quantitative trait loci. We illustrate specific regulatory mechanisms such as how eSTRs affect splicing sites and alternative splicing efficiency. We also show that differential expression of antioxidant genes and oxidative stresses might affect STR mutations systematically using both wild strains and mutation accumulation lines. Overall, we reveal the interplay between STRs and gene expression variation by providing novel insights into regulatory mechanisms of STRs and highlighting that oxidative stress could lead to higher STR mutation rates.

Grave-to-cradle: human embryonic lineage tracing from the postmortem body

Curiosity concerning the process of human creation has been around for a long time. Relevant questions seemed to be resolved with the knowledge of how cells divide after fertilization obtained through in vitro fertilization experiments. However, we still do not know how human life is created at the cellular level. Recently, the value of cadavers as a resource from which to obtain "normal" cells and tissues has been established, and human research using postmortem bodies has attracted growing scientific attention. As the human genome can be analyzed at the level of nucleotides through whole-genome sequencing, individual cells in a postmortem body can be traced back to determine what developmental processes have transpired from fertilization. These retrospective lineage tracing studies have answered several unsolved questions on how humans are created. This review covers the methodologies utilized in lineage tracing research in a historical context and the conceptual basis for reconstructing the division history of cells in a retrospective manner using postzygotic somatic variants in postmortem tissue. We further highlight answers that postmortem research could potentially address and discuss issues that wait to be solved in the future.

Clonal hematopoiesis, somatic mosaicism, and age-associated disease

Somatic mosaicism, the occurrence of multiple genetically distinct cell clones within the same tissue, is an evitable consequence of human aging. The hematopoietic system is no exception to this, where studies have revealed the presence of expanded blood cell clones carrying mutations in preleukemic driver genes and/or genetic alterations in chromosomes. This phenomenon is referred to as clonal hematopoiesis and is remarkably prevalent in elderly individuals. While clonal hematopoiesis represents an early step toward a hematological malignancy, most individuals will never develop blood cancer. Somewhat unexpectedly, epidemiological studies have found that clonal hematopoiesis is associated with an increase in the risk of all-cause mortality and age-related disease, particularly in the cardiovascular system. Studies using murine models of clonal hematopoiesis have begun to shed light on this relationship, suggesting that driver mutations in mature blood cells can causally contribute to aging and disease by augmenting inflammatory processes. Here we provide an up-to-date review of clonal hematopoiesis within the context of somatic mosaicism and aging and describe recent epidemiological studies that have reported associations with age-related disease. We will also discuss the experimental studies that have provided important mechanistic insight into how driver mutations promote age-related disease and how this knowledge could be leveraged to treat individuals with clonal hematopoiesis.