Effects of urban-induced mutations on ecology, evolution and health

Increasing evidence suggests that urbanization is associated with higher mutation rates, which can affect the health and evolution of organisms that inhabit cities. Elevated pollution levels in urban areas can induce DNA damage, leading to de novo mutations. Studies on mutations induced by urban pollution are most prevalent in humans and microorganisms, whereas studies of non-human eukaryotes are rare, even though increased mutation rates have the potential to affect organisms and their populations in contemporary time. Our Perspective explores how higher mutation rates in urban environments could impact the fitness, ecology and evolution of populations. Most mutations will be neutral or deleterious, and higher mutation rates associated with elevated pollution in urban populations can increase the risk of cancer in humans and potentially other species. We highlight the potential for urban-driven increased deleterious mutational loads in some organisms, which could lead to a decline in population growth of a wide diversity of organisms. Although beneficial mutations are expected to be rare, we argue that higher mutation rates in urban areas could influence adaptive evolution, especially in organisms with short generation times. Finally, we explore avenues for future research to better understand the effects of urban-induced mutations on the fitness, ecology and evolution of city-dwelling organisms.

A regulatory variant impacting TBX1 expression contributes to basicranial morphology in Homo sapiens

Changes in gene regulatory elements play critical roles in human phenotypic divergence. However, identifying the base-pair changes responsible for the distinctive morphology of Homo sapiens remains challenging. Here, we report a noncoding single-nucleotide polymorphism (SNP), rs41298798, as a potential causal variant contributing to the morphology of the skull base and vertebral structures found in Homo sapiens. Screening for differentially regulated genes between Homo sapiens and extinct relatives revealed 13 candidate genes associated with basicranial development, with TBX1, implicated in DiGeorge syndrome, playing a pivotal role. Epigenetic markers and in silico analyses prioritized rs41298798 within a TBX1 intron for functional validation. CRISPR editing revealed that the 41-base-pair region surrounding rs41298798 modulates gene expression at 22q11.21. The derived allele of rs41298798 acts as an allele-specific enhancer mediated by E2F1, resulting in increased TBX1 expression levels compared to the ancestral allele. Tbx1-knockout mice exhibited skull base and vertebral abnormalities similar to those seen in DiGeorge syndrome. Phenotypic differences associated with TBX1 deficiency are observed between Homo sapiens and Neanderthals (Homo neanderthalensis). In conclusion, the regulatory divergence of TBX1 contributes to the formation of skull base and vertebral structures found in Homo sapiens.

Multiplex generation and single cell analysis of structural variants in a mammalian genome

The functional consequences of structural variants (SVs) in mammalian genomes are challenging to study. This is due to several factors, including: 1) their numerical paucity relative to other forms of standing genetic variation such as single nucleotide variants (SNVs) and short insertions or deletions (indels); 2) the fact that a single SV can involve and potentially impact the function of more than one gene and/or cis regulatory element; and 3) the relative immaturity of methods to generate and map SVs, either randomly or in targeted fashion, in in vitro or in vivo model systems. Towards addressing these challenges, we developed Genome-Shuffle-seq, a straightforward method that enables the multiplex generation and mapping of several major forms of SVs (deletions, inversions, translocations) throughout a mammalian genome. Genome-Shuffle-seq is based on the integration of "shuffle cassettes" to the genome, wherein each shuffle cassette contains components that facilitate its site-specific recombination (SSR) with other integrated shuffle cassettes (via Cre-loxP), its mapping to a specific genomic location (via T7-mediated in vitro transcription or IVT), and its identification in single-cell RNA-seq (scRNA-seq) data (via T7-mediated in situ transcription or IST). In this proof-of-concept, we apply Genome-Shuffle-seq to induce and map thousands of genomic SVs in mouse embryonic stem cells (mESCs) in a single experiment. Induced SVs are rapidly depleted from the cellular population over time, possibly due to Cre-mediated toxicity and/or negative selection on the rearrangements themselves. Leveraging T7 IST of barcodes whose positions are already mapped, we further demonstrate that we can efficiently genotype which SVs are present in association with each of many single cell transcriptomes in scRNA-seq data. Finally, preliminary evidence suggests our method may be a powerful means of generating extrachromosomal circular DNAs (ecDNAs). Looking forward, we anticipate that Genome-Shuffle-seq may be broadly useful for the systematic exploration of the functional consequences of SVs on gene expression, the chromatin landscape, and 3D nuclear architecture. We further anticipate potential uses for in vitro modeling of ecDNAs, as well as in paving the path to a minimal mammalian genome.

Identification and in silico structural analysis for the first de novo mutation in the cystic fibrosis transmembrane conductance regulator protein in Iran: case report and developmental insight using microsatellite markers

Cystic fibrosis (CF) is an autosomal recessive disease caused by the inheritance of two mutant cystic fibrosis transmembrane conductance regulator (CFTR) alleles, one from each parent. Autosomal recessive disorders are rarely associated with germline mutations or mosaicism. Here, we propose a case of paternal germline mutation causing CF. The subject also had an identifiable maternal mutant allele. We identified the compound heterozygous variants in the proband through Sanger sequencing, and in silico studies predicted functional effects on the protein. Also, short tandem repeat markers revealed the de novo nature of the mutation. The maternal mutation in the CFTR gene was c.1000C > T. The de novo mutation was c.178G > A, p.Glu60Lys. This mutation is located in the lasso motif of the CFTR protein and, according to in silico structural analysis, disrupts the interaction of the lasso motif and R-domain, thus influencing protein function. This first reported case of de novo mutation in Asia has notable implications for molecular diagnostics, genetic counseling, and understanding the genetic etiology of recessive disorders in the Iranian population.

Dynamic basis for dA•dGTP and dA•d8OGTP misincorporation via Hoogsteen base pairs

Replicative errors contribute to the genetic diversity needed for evolution but in high frequency can lead to genomic instability. Here, we show that DNA dynamics determine the frequency of misincorporating the A•G mismatch, and altered dynamics explain the high frequency of 8-oxoguanine (8OG) A•8OG misincorporation. NMR measurements revealed that Aanti•Ganti (population (pop.) of >91%) transiently forms sparsely populated and short-lived Aanti+•Gsyn (pop. of ~2% and kex = kforward + kreverse of ~137 s-1) and Asyn•Ganti (pop. of ~6% and kex of ~2,200 s-1) Hoogsteen conformations. 8OG redistributed the ensemble, rendering Aanti•8OGsyn the dominant state. A kinetic model in which Aanti+•Gsyn is misincorporated quantitatively predicted the dA•dGTP misincorporation kinetics by human polymerase β, the pH dependence of misincorporation and the impact of the 8OG lesion. Thus, 8OG increases replicative errors relative to G because oxidation of guanine redistributes the ensemble in favor of the mutagenic Aanti•8OGsyn Hoogsteen state, which exists transiently and in low abundance in the A•G mismatch.

The adaptive evolution of cancer driver genes

BACKGROUND

Cancer is a life-threatening disease in humans; yet, cancer genes are frequently reported to be under positive selection. This suggests an evolutionary-genetic paradox in which cancer evolves as a secondary product of selection in human beings. However, systematic investigation of the evolution of cancer driver genes is sparse.

RESULTS

Using comparative genomics analysis, population genetics analysis and computational molecular evolutionary analysis, the evolution of 568 cancer driver genes of 66 cancer types were evaluated at two levels, selection on the early evolution of humans (long timescale selection in the human lineage during primate evolution, i.e., millions of years), and recent selection in modern human populations (~ 100,000 years). Results showed that eight cancer genes covering 11 cancer types were under positive selection in the human lineage (long timescale selection). And 35 cancer genes covering 47 cancer types were under positive selection in modern human populations (recent selection). Moreover, SNPs associated with thyroid cancer in three thyroid cancer driver genes (CUX1, HERC2 and RGPD3) were under positive selection in East Asian and European populations, consistent with the high incidence of thyroid cancer in these populations.

CONCLUSIONS

These findings suggest that cancer can be evolved, in part, as a by-product of adaptive changes in humans. Different SNPs at the same locus can be under different selection pressures in different populations, and thus should be under consideration during precision medicine, especially for targeted medicine in specific populations.

Transcription factor binding site orientation and order are major drivers of gene regulatory activity

The gene regulatory code and grammar remain largely unknown, precluding our ability to link phenotype to genotype in regulatory sequences. Here, using a massively parallel reporter assay (MPRA) of 209,440 sequences, we examine all possible pair and triplet combinations, permutations and orientations of eighteen liver-associated transcription factor binding sites (TFBS). We find that TFBS orientation and order have a major effect on gene regulatory activity. Corroborating these results with genomic analyses, we find clear human promoter TFBS orientation biases and similar TFBS orientation and order transcriptional effects in an MPRA that tested 164,307 liver candidate regulatory elements. Additionally, by adding TFBS orientation to a model that predicts expression from sequence we improve performance by 7.7%. Collectively, our results show that TFBS orientation and order have a significant effect on gene regulatory activity and need to be considered when analyzing the functional effect of variants on the activity of these sequences.

Phenotypic Modulation of Cancer-Associated Antioxidant NQO1 Activity by Post-Translational Modifications and the Natural Diversity of the Human Genome

Human NAD(P)H:quinone oxidoreductase 1 (hNQO1) is a multifunctional and antioxidant stress protein whose expression is controlled by the Nrf2 signaling pathway. hNQO1 dysregulation is associated with cancer and neurological disorders. Recent works have shown that its activity is also modulated by different post-translational modifications (PTMs), such as phosphorylation, acetylation and ubiquitination, and these may synergize with naturally-occurring and inactivating polymorphisms and mutations. Herein, I describe recent advances in the study of the effect of PTMs and genetic variations on the structure and function of hNQO1 and their relationship with disease development in different genetic backgrounds, as well as the physiological roles of these modifications. I pay particular attention to the long-range allosteric effects exerted by PTMs and natural variation on the multiple functions of hNQO1.

De novo variants are a common cause of genetic hearing loss

PURPOSE

De novo variants (DNVs) are a well-recognized cause of genetic disorders. The contribution of DNVs to hearing loss (HL) is poorly characterized. We aimed to evaluate the rate of DNVs in HL-associated genes and assess their contribution to HL.

METHODS

Targeted genomic enrichment and massively parallel sequencing were used for molecular testing of all exons and flanking intronic sequences of known HL-associated genes, with no exclusions on the basis of type of HL or clinical features. Segregation analysis was performed, and previous reports of DNVs in PubMed and ClinVar were reviewed to characterize the rate, distribution, and spectrum of DNVs in HL.

RESULTS

DNVs were detected in 10% (24/238) of trios for whom segregation analysis was performed. Overall, DNVs were causative in at least ∼1% of probands for whom a genetic diagnosis was resolved, with marked variability based on inheritance mode and phenotype. DNVs of MITF were most common (21% of DNVs), followed by GATA3 (13%), STRC (13%), and ACTG1 (8%). Review of reported DNVs revealed gene-specific variability in contribution of DNV to the mutational spectrum of HL-associated genes.

CONCLUSION

DNVs are a relatively common cause of genetic HL and must be considered in all cases of sporadic HL.

Loss of stability and unfolding cooperativity in hPGK1 upon gradual structural perturbation of its N-terminal domain hydrophobic core

Phosphoglycerate kinase has been a model for the stability, folding cooperativity and catalysis of a two-domain protein. The human isoform 1 (hPGK1) is associated with cancer development and rare genetic diseases that affect several of its features. To investigate how mutations affect hPGK1 folding landscape and interaction networks, we have introduced mutations at a buried site in the N-terminal domain (F25 mutants) that either created cavities (F25L, F25V, F25A), enhanced conformational entropy (F25G) or introduced structural strain (F25W) and evaluated their effects using biophysical experimental and theoretical methods. All F25 mutants folded well, but showed reduced unfolding cooperativity, kinetic stability and altered activation energetics according to the results from thermal and chemical denaturation analyses. These alterations correlated well with the structural perturbation caused by mutations in the N-terminal domain and the destabilization caused in the interdomain interface as revealed by H/D exchange under native conditions. Importantly, experimental and theoretical analyses showed that these effects are significant even when the perturbation is mild and local. Our approach will be useful to establish the molecular basis of hPGK1 genotype-phenotype correlations due to phosphorylation events and single amino acid substitutions associated with disease.

Construction of a trio-based structural variation panel utilizing activated T lymphocytes and long-read sequencing technology

Long-read sequencing technology enable better characterization of structural variants (SVs). To adapt the technology to population-scale analyses, one critical issue is to obtain sufficient amount of high-molecular-weight genomic DNA. Here, we propose utilizing activated T lymphocytes, which can be established efficiently in a biobank to stably supply high-grade genomic DNA sufficiently. We conducted nanopore sequencing of 333 individuals constituting 111 trios with high-coverage long-read sequencing data (depth 22.2x, N50 of 25.8 kb) and identified 74,201 SVs. Our trio-based analysis revealed that more than 95% of the SVs were concordant with Mendelian inheritance. We also identified SVs associated with clinical phenotypes, all of which appear to be stably transmitted from parents to offspring. Our data provide a catalog of SVs in the general Japanese population, and the applied approach using the activated T-lymphocyte resource will contribute to biobank-based human genetic studies focusing on SVs at the population scale.

Long-read sequencing on activated T-cells from a sample of 333 Japanese individuals (representing 111 parent-offspring trios) provides a useful reference dataset of structural variation in the Japanese population.

Genomic mapping of copy number variations influencing immune response in breast cancer

Identification of genomic alterations that influence the immune response within the tumor microenvironment is mandatory in order to identify druggable vulnerabilities. In this article, by interrogating public genomic datasets we describe copy number variations (CNV) present in breast cancer (BC) tumors and corresponding subtypes, associated with different immune populations. We identified regulatory T-cells associated with the Basal-like subtype, and type 2 T-helper cells with HER2 positive and the luminal subtype. Using gene set enrichment analysis (GSEA) for the Type 2 T-helper cells, the most relevant processes included the ERBB2 signaling pathway and the Fibroblast Growth Factor Receptor (FGFR) signaling pathway, and for CD8+ T-cells, cellular response to growth hormone stimulus or the JAK-STAT signaling pathway. Amplification of ERBB2, GRB2, GRB7, and FGF receptor genes strongly correlated with the presence of type 2 T helper cells. Finally, only 8 genes were highly upregulated and present in the cellular membrane: MILR1, ACE, DCSTAMP, SLAMF8, CD160, IL2RA, ICAM2, and SLAMF6. In summary, we described immune populations associated with genomic alterations with different BC subtypes. We observed a clear presence of inhibitory cells, like Tregs or Th2 when specific chromosomic regions were amplified in basal-like or HER2 and luminal groups. Our data support further evaluation of specific therapeutic strategies in specific BC subtypes, like those targeting Tregs in the basal-like subtype.

The hidden (degron) truth behind the degradation of DHFR disease-associated variants

In this issue of Structure, Kampmeyer et al. provide detailed mechanistic insights into how structural changes in disease-associated dihydrofolate reductase (DHFR) missense variants affect their cellular protein abundance and discuss implications for hereditary megaloblastic anemia disease.

Computational and experimental methods for classifying variants of unknown clinical significance

The increase in sequencing capacity, reduction in costs, and national and international coordinated efforts have led to the widespread introduction of next-generation sequencing (NGS) technologies in patient care. More generally, human genetics and genomic medicine are gaining importance for more and more patients. Some communities are already discussing the prospect of sequencing each individual's genome at time of birth. Together with digital health records, this shall enable individualized treatments and preventive measures, so-called precision medicine. A central step in this process is the identification of disease causal mutations or variant combinations that make us more susceptible for diseases. Although various technological advances have improved the identification of genetic alterations, the interpretation and ranking of the identified variants remains a major challenge. Based on our knowledge of molecular processes or previously identified disease variants, we can identify potentially functional genetic variants and, using different lines of evidence, we are sometimes able to demonstrate their pathogenicity directly. However, the vast majority of variants are classified as variants of uncertain clinical significance (VUSs) with not enough experimental evidence to determine their pathogenicity. In these cases, computational methods may be used to improve the prioritization and an increasing toolbox of experimental methods is emerging that can be used to assay the molecular effects of VUSs. Here, we discuss how computational and experimental methods can be used to create catalogs of variant effects for a variety of molecular and cellular phenotypes. We discuss the prospects of integrating large-scale functional data with machine learning and clinical knowledge for the development of accurate pathogenicity predictions for clinical applications.

Unusual clinical manifestations and predominant stopgain ATM gene variants in a single centre cohort of ataxia telangiectasia from North India

Germline ATM gene variations result in phenotypic heterogeneity characterized by a variable degree of disease severity. We retrospectively collected clinical, genetic, and immunological data of 26 cases with A-T. Clinical manifestations included oculocutaneous telangiectasia (100%), ataxia (100%), fever, loose stools or infection (67%), cerebellar atrophy (50%), nystagmus (8%), dysarthria (15.38%), and visual impairment (8%). Genetic analysis confirmed ATM gene variations in 16 unrelated cases. The most common type of variation was stopgain variants (56%). Immunoglobulin profile indicated reduced IgA, IgG, and IgM in 94%, 50%, and 20% cases, respectively. T cell lymphopenia was observed in 80% of cases among those investigated. Unusual presentations included an EBV-associated smooth muscle tumour located in the liver in one case and Hyper IgM syndrome-like presentation in two cases. Increased immunosenescence was observed in T-cell subsets (CD4+CD57+ and CD8+CD57+). T-cell receptor excision circles (TRECs) were reduced in 3/8 (37.50%) cases.

Assessing Autosomal InDel Loci With Multiple Insertions or Deletions of Random DNA Sequences in Human Genome

Multiple mutational events of insertion/deletion occurring at or around InDel sites could form multi-allelic InDels and multi-InDels (abbreviated as MM-InDels), while InDels with random DNA sequences could imply a unique mutation event at these loci. In this study, preliminary investigation of MM-InDels with random sequences was conducted using high-throughput phased data from the 1000 Genomes Project. A total of 3,599 multi-allelic InDels and 6,375 multi-InDels were filtered with multiple alleles. A vast majority of the obtained MM-InDels (85.59%) presented 3 alleles, which implies that only one secondary insertion or deletion mutation event occurred at these loci. The more frequent presence of two adjacent InDel loci was observed within 20 bp. MM-InDels with random sequences presented an uneven distribution across the genome and showed a correlation with InDels, SNPs, recombination rate, and GC content. The average allelic frequencies and prevalence of multi-allelic InDels and multi-InDels presented similar distribution patterns in different populations. Altogether, MM-InDels with random sequences can provide useful information for population resolution.

De novo mutation rates at the single-mutation resolution in a human HBB gene-region associated with adaptation and genetic disease

Although it is known that the mutation rate varies across the genome, previous estimates were based on averaging across various numbers of positions. Here, we describe a method to measure the origination rates of target mutations at target base positions and apply it to a 6-bp region in the human hemoglobin subunit beta (HBB) gene and to the identical, paralogous hemoglobin subunit delta (HBD) region in sperm cells from both African and European donors. The HBB region of interest (ROI) includes the site of the hemoglobin S (HbS) mutation, which protects against malaria, is common in Africa, and has served as a classic example of adaptation by random mutation and natural selection. We found a significant correspondence between de novo mutation rates and past observations of alleles in carriers, showing that mutation rates vary substantially in a mutation-specific manner that contributes to the site frequency spectrum. We also found that the overall point mutation rate is significantly higher in Africans than in Europeans in the HBB region studied. Finally, the rate of the 20A→T mutation, called the “HbS mutation” when it appears in HBB, is significantly higher than expected from the genome-wide average for this mutation type. Nine instances were observed in the African HBB ROI, where it is of adaptive significance, representing at least three independent originations; no instances were observed elsewhere. Further studies will be needed to examine mutation rates at the single-mutation resolution across these and other loci and organisms and to uncover the molecular mechanisms responsible.

ConVarT: a search engine for matching human genetic variants with variants from non-human species

The availability of genetic variants, together with phenotypic annotations from model organisms, facilitates comparing these variants with equivalent variants in humans. However, existing databases and search tools do not make it easy to scan for equivalent variants, namely 'matching variants' (MatchVars) between humans and other organisms. Therefore, we developed an integrated search engine called ConVarT (http://www.convart.org/) for matching variants between humans, mice, and Caenorhabditis elegans. ConVarT incorporates annotations (including phenotypic and pathogenic) into variants, and these previously unexploited phenotypic MatchVars from mice and C. elegans can give clues about the functional consequence of human genetic variants. Our analysis shows that many phenotypic variants in different genes from mice and C. elegans, so far, have no counterparts in humans, and thus, can be useful resources when evaluating a relationship between a new human mutation and a disease.

Analysis of the Batch Effect Due to Sequencing Center in Population Statistics Quantifying Rare Events in the 1000 Genomes Project

The 1000 Genomes Project (1000G) is one of the most popular whole genome sequencing datasets used in different genomics fields and has boosting our knowledge in medical and population genomics, among other fields. Recent studies have reported the presence of ghost mutation signals in the 1000G. Furthermore, studies have shown that these mutations can influence the outcomes of follow-up studies based on the genetic variation of 1000G, such as single nucleotide variants (SNV) imputation. While the overall effect of these ghost mutations can be considered negligible for common genetic variants in many populations, the potential bias remains unclear when studying low frequency genetic variants in the population. In this study, we analyze the effect of the sequencing center in predicted loss of function (LoF) alleles, the number of singletons, and the patterns of archaic introgression in the 1000G. Our results support previous studies showing that the sequencing center is associated with LoF and singletons independent of the population that is considered. Furthermore, we observed that patterns of archaic introgression were distorted for some populations depending on the sequencing center. When analyzing the frequency of SNPs showing extreme patterns of genotype differentiation among centers for CEU, YRI, CHB, and JPT, we observed that the magnitude of the sequencing batch effect was stronger at MAF < 0.2 and showed different profiles between CHB and the other populations. All these results suggest that data from 1000G must be interpreted with caution when considering statistics using variants at low frequency.

Comparison of the frequencies of ENU-induced point mutations in male germ cells and inherited germline mutations in their offspring

Background

Gene mutations induced in germ cells may be transmitted to the next generation and cause adverse effects such as genetic diseases. Certain mutations may result in infertility or death in early development. Thus, the mutations may not be inheritable. However, the extent to which point mutations in male germ cells are transmitted to the next generation or eliminated during transmission is largely unknown. This study compared mutation frequencies (MFs) in sperm of N-ethyl-N-nitrosourea (ENU)-treated gpt delta mice and de novo MFs in the whole exome/genome of their offspring.

Results

Male gpt delta mice were treated with 10, 30, and 85 mg/kg of ENU (i.p., weekly × 2) and mated with untreated females to generate offspring. We previously reported a dose-dependent increase in de novo MFs in the offspring estimated by whole exome sequencing (WES) (Mutat. Res., 810, 30–39, 2016). In this study, gpt MFs in the sperm of ENU-treated mice were estimated, and the MFs per reporter gene were converted to MFs per base pair. The inherited de novo MFs in the offspring (9, 26 and 133 × 10^− 8/bp for 10, 30, and 85 mg/kg ENU-treated groups, respectively) were comparable to those of the converted gpt MFs in the sperm of ENU-treated fathers (6, 16, and 69 × 10^− 8/bp). It indicated that the gpt MFs in the ENU-treated father’s sperm were comparable to the inherited de novo MFs in the offspring as estimated by WES. In addition, de novo MFs in the offspring of 10 mg/kg ENU-treated and control fathers were estimated by whole genome sequencing (WGS), because WES was not sufficiently sensitive to detect low background MF. The de novo MF in the offspring of the ENU-treated fathers was 6 × 10^− 8/bp and significantly higher than that of the control (2 × 10^− 8/bp). There were no significant differences in de novo MFs between gene-coding and non-coding regions. WGS analysis was able to detect ENU-induced characteristic de novo base substitutions at a low dose group.

Conclusions

Despite a difference between exome/genome and exogenous reporter genes, the results indicated that ENU-induced point mutations in male germ cells could be transmitted to the next generation without severe selection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41021-021-00216-z.

Sex chromosome transformation and the origin of a male-specific X chromosome in the creeping vole

The mammalian sex chromosome system (XX female/XY male) is ancient and highly conserved. The sex chromosome karyotype of the creeping vole (Microtus oregoni) represents a long-standing anomaly, with an X chromosome that is unpaired in females (X0) and exclusively maternally transmitted. We produced a highly contiguous male genome assembly, together with short-read genomes and transcriptomes for both sexes. We show that M. oregoni has lost an independently segregating Y chromosome and that the male-specific sex chromosome is a second X chromosome that is largely homologous to the maternally transmitted X. Both maternally inherited and male-specific sex chromosomes carry fragments of the ancestral Y chromosome. Consequences of this recently transformed sex chromosome system include Y-like degeneration and gene amplification on the male-specific X, expression of ancestral Y-linked genes in females, and X inactivation of the male-specific chromosome in male somatic cells. The genome of M. oregoni elucidates the processes that shape the gene content and dosage of mammalian sex chromosomes and exemplifies a rare case of plasticity in an ancient sex chromosome system.

Rising incidence of early-onset colorectal cancer - a call to action

The incidence of early-onset colorectal cancer (CRC), which occurs in individuals <50 years of age, has been increasing worldwide and particularly in high-income countries. The reasons for this increase remain unknown but plausible hypotheses include greater exposure to potential risk factors, such as a Western-style diet, obesity, physical inactivity and antibiotic use, especially during the early prenatal to adolescent periods of life. These exposures can not only cause genetic and epigenetic alterations in colorectal epithelial cells but also affect the gut microbiota and host immunity. Early-onset CRCs have differential clinical, pathological and molecular features compared with later-onset CRCs. Certain existing resources can be utilized to elucidate the aetiology of early-onset CRC and inform the development of effective prevention, early detection and therapeutic strategies; however, additional life-course cohort studies spanning childhood and young adulthood, integrated with prospective biospecimen collections, omics biomarker analyses and a molecular pathological epidemiology approach, are needed to better understand and manage this disease entity. In this Perspective, we summarize our current understanding of early-onset CRC and discuss how we should strategize future research to improve its prevention and clinical management.

De novo structural mutation rates and gamete-of-origin biases revealed through genome sequencing of 2,396 families

Each human genome includes de novo mutations that arose during gametogenesis. While these germline mutations represent a fundamental source of new genetic diversity, they can also create deleterious alleles that impact fitness. Whereas the rate and patterns of point mutations in the human germline are now well understood, far less is known about the frequency and features that impact de novo structural variants (dnSVs). We report a family-based study of germline mutations among 9,599 human genomes from 33 multigenerational CEPH-Utah families and 2,384 families from the Simons Foundation Autism Research Initiative. We find that de novo structural mutations detected by alignment-based, short-read WGS occur at an overall rate of at least 0.160 events per genome in unaffected individuals, and we observe a significantly higher rate (0.206 per genome) in ASD-affected individuals. In both probands and unaffected samples, nearly 73% of de novo structural mutations arose in paternal gametes, and we predict most de novo structural mutations to be caused by mutational mechanisms that do not require sequence homology. After multiple testing correction, we did not observe a statistically significant correlation between parental age and the rate of de novo structural variation in offspring. These results highlight that a spectrum of mutational mechanisms contribute to germline structural mutations and that these mechanisms most likely have markedly different rates and selective pressures than those leading to point mutations.

e-MutPath: computational modeling reveals the functional landscape of genetic mutations rewiring interactome networks

Understanding the functional impact of cancer somatic mutations represents a critical knowledge gap for implementing precision oncology. It has been increasingly appreciated that the interaction profile mediated by a genomic mutation provides a fundamental link between genotype and phenotype. However, specific effects on biological signaling networks for the majority of mutations are largely unknown by experimental approaches. To resolve this challenge, we developed e-MutPath (edgetic Mutation-mediated Pathway perturbations), a network-based computational method to identify candidate ‘edgetic’ mutations that perturb functional pathways. e-MutPath identifies informative paths that could be used to distinguish disease risk factors from neutral elements and to stratify disease subtypes with clinical relevance. The predicted targets are enriched in cancer vulnerability genes, known drug targets but depleted for proteins associated with side effects, demonstrating the power of network-based strategies to investigate the functional impact and perturbation profiles of genomic mutations. Together, e-MutPath represents a robust computational tool to systematically assign functions to genetic mutations, especially in the context of their specific pathway perturbation effect.

Brain circuits at risk in psychiatric diseases and pharmacological pathways

The multiple brain circuits involved in psychiatric diseases may appear daunting, but we prefer to concentrate on a select few, with a particular sensitivity to stress and neurodevelopmental issues, with a clear pharmacotherapy. This review is structured around 1. the key circuits, their role in health and disease, and the neurotransmitters maintaining them, 2. The influence of upbringing, stress, chronobiology, inflammation and infection, 3. The genetic and epigenetic influence on these circuits, particularly regarding copy number variants and neuronal plasticity, 4. The use and abuse of pharmacological agents with the particular risks of stress and chronobiology at critical periods. A major emphasis is placed on the links between hippocampus, prefrontal cortex and amygdala/periaqueductal grey which control specific aspects of cognition, mood, pain and even violence. Some of the research findings were from the innovative medicine initiative (IMI) NEWMEDS, a 22M€ academic/industrial consortium on the brain circuits critical for psychiatric disease.

Genomic signatures of recombination in a natural population of the bdelloid rotifer Adineta vaga

Sexual reproduction is almost ubiquitous among extant eukaryotes. As most asexual lineages are short-lived, abandoning sex is commonly regarded as an evolutionary dead end. Still, putative anciently asexual lineages challenge this view. One of the most striking examples are bdelloid rotifers, microscopic freshwater invertebrates believed to have completely abandoned sexual reproduction tens of Myr ago. Here, we compare whole genomes of 11 wild-caught individuals of the bdelloid rotifer Adineta vaga and present evidence that some patterns in its genetic variation are incompatible with strict clonality and lack of genetic exchange. These patterns include genotype proportions close to Hardy-Weinberg expectations within loci, lack of linkage disequilibrium between distant loci, incongruent haplotype phylogenies across the genome, and evidence for hybridization between divergent lineages. Analysis of triallelic sites independently corroborates these findings. Our results provide evidence for interindividual genetic exchange and recombination in A. vaga, a species previously thought to be anciently asexual.

Hotspots of Human Mutation

Mutation of the human genome results in three classes of genomic variation: single nucleotide variants; short insertions or deletions; and large structural variants (SVs). Some mutations occur during normal processes, such as meiotic recombination or B cell development, and others result from DNA replication or aberrant repair of breaks in sequence-specific contexts. Regardless of mechanism, mutations are subject to selection, and some hotspots can manifest in disease. Here, we discuss genomic regions prone to mutation, mechanisms contributing to mutation susceptibility, and the processes leading to their accumulation in normal and somatic genomes. With further, more accurate human genome sequencing, additional mutation hotspots, mechanistic details of their formation, and the relevance of hotspots to evolution and disease are likely to be discovered.

Naturally-Occurring Rare Mutations Cause Mild to Catastrophic Effects in the Multifunctional and Cancer-Associated NQO1 Protein

The functional and pathological implications of the enormous genetic diversity of the human genome are mostly unknown, primarily due to our unability to predict pathogenicity in a high-throughput manner. In this work, we characterized the phenotypic consequences of eight naturally-occurring missense variants on the multifunctional and disease-associated NQO1 protein using biophysical and structural analyses on several protein traits. Mutations found in both exome-sequencing initiatives and in cancer cell lines cause mild to catastrophic effects on NQO1 stability and function. Importantly, some mutations perturb functional features located structurally far from the mutated site. These effects are well rationalized by considering the nature of the mutation, its location in protein structure and the local stability of its environment. Using a set of 22 experimentally characterized mutations in NQO1, we generated experimental scores for pathogenicity that correlate reasonably well with bioinformatic scores derived from a set of commonly used algorithms, although the latter fail to semiquantitatively predict the phenotypic alterations caused by a significant fraction of mutations individually. These results provide insight into the propagation of mutational effects on multifunctional proteins, the implementation of in silico approaches for establishing genotype-phenotype correlations and the molecular determinants underlying loss-of-function in genetic diseases.

Towards Accurate Genotype-Phenotype Correlations in the CYP2D6 Gene

Establishing accurate and large-scale genotype-phenotype correlations and predictions of individual response to pharmacological treatments are two of the holy grails of Personalized Medicine. These tasks are challenging and require an integrated knowledge of the complex processes that regulate gene expression and, ultimately, protein functionality in vivo, the effects of mutations/polymorphisms and the different sources of interindividual phenotypic variability. A remarkable example of our advances in these challenging tasks is the highly polymorphic CYP2D6 gene, which encodes a cytochrome P450 enzyme involved in the metabolization of many of the most marketed drugs (including SARS-Cov-2 therapies such as hydroxychloroquine). Since the introduction of simple activity scores (AS) over 10 years ago, its ability to establish genotype-phenotype correlations on the drug metabolizing capacity of this enzyme in human population has provided lessons that will help to improve this type of score for this, and likely many other human genes and proteins. Multidisciplinary research emerges as the best approach to incorporate additional concepts to refine and improve such functional/activity scores for the CYP2D6 gene, as well as for many other human genes associated with simple and complex genetic diseases.

Biophysical ambiguities prevent accurate genetic prediction

A goal of biology is to predict how mutations combine to alter phenotypes, fitness and disease. It is often assumed that mutations combine additively or with interactions that can be predicted. Here, we show using simulations that, even for the simple example of the lambda phage transcription factor CI repressing a gene, this assumption is incorrect and that perfect measurements of the effects of mutations on a trait and mechanistic understanding can be insufficient to predict what happens when two mutations are combined. This apparent paradox arises because mutations can have different biophysical effects to cause the same change in a phenotype and the outcome in a double mutant depends upon what these hidden biophysical changes actually are. Pleiotropy and non-monotonic functions further confound prediction of how mutations interact. Accurate prediction of phenotypes and disease will sometimes not be possible unless these biophysical ambiguities can be resolved using additional measurements.

The Impact of DNA Methylation Dynamics on the Mutation Rate During Human Germline Development

DNA methylation is a dynamic epigenetic modification found in most eukaryotic genomes. It is known to lead to a high CpG to TpG mutation rate. However, the relationship between the methylation dynamics in germline development and the germline mutation rate remains unexplored. In this study, we used whole genome bisulfite sequencing (WGBS) data of cells at 13 stages of human germline development and rare variants from the 1000 Genome Project as proxies for germline mutations to investigate the correlation between dynamic methylation levels and germline mutation rates at different scales. At the single-site level, we found a significant correlation between methylation and the germline point mutation rate at CpG sites during germline developmental stages. Then we explored the mutability of methylation dynamics in all stages. Our results also showed a broad correlation between the regional methylation level and the rate of C > T mutation at CpG sites in all genomic regions, especially in intronic regions; a similar link was also seen at all chromosomal levels. Our findings indicate that the dynamic DNA methylome during human germline development has a broader mutational impact than is commonly assumed.

A catalogue of new incidence estimates of monogenic neurodevelopmental disorders caused by de novo variants

A large fraction of rare and severe neurodevelopmental disorders are caused by sporadic de novo variants. Epidemiological disease estimates are not available for the vast majority of these de novo monogenic neurodevelopmental disorders because of phenotypic heterogeneity and the absence of large-scale genomic screens. Yet, knowledge of disease incidence is important for clinicians and researchers to guide health policy planning. Here, we adjusted a statistical method based on genetic data to predict, for the first time, the incidences of 101 known de novo variant-associated neurodevelopmental disorders as well as 3106 putative monogenic disorders. Two corroboration analyses supported the validity of the calculated estimates. First, greater predicted gene-disorder incidences positively correlated with larger numbers of pathogenic variants collected from patient variant databases (Kendall’s τ = 0.093, P-value = 6.9 × 10⁻⁶). Second, for six of seven (86%) de novo variant associated monogenic disorders for which epidemiological estimates were available (SCN1A, SLC2A1, SALL1, TBX5, KCNQ2, and CDKL5), the predicted incidence estimates matched the reported estimates. We conclude that in the absence of epidemiological data, our catalogue of 3207 incidence estimates for disorders caused by de novo variants can guide patient advocacy groups, clinicians, researchers, and policymakers in strategic decision-making.

Evolution of the mutation rate across primates

Germline mutations are the source of all heritable variation. In the past few years, whole genome sequencing has allowed direct and comprehensive surveys of mutation patterns in humans and other species. These studies have documented substantial variation in both mutation rates and spectra across primates, the causes of which remain unclear. Here, we review what is currently known about mutation rates in primates, highlight the factors proposed to explain the variation across species, and discuss some implications of these findings on our understanding of the chronology of primate evolution and the process of mutagenesis.

TLmutation: Predicting the Effects of Mutations Using Transfer Learning

A reccurring challenge in bioinformatics is predicting the phenotypic consequence of amino acid variation in proteins. With the recent advancements in sequencing techniques, sufficient genomic data has become available to train models that predict the evolutionary statistical energies, but there is still inadequate experimental data to directly predict functional effects. One approach to overcome this data scarcity is to apply transfer learning and train more models with available data sets. In this study, we propose a set of transfer learning algorithms we call TLmutation, which implements a supervised transfer learning algorithm that transfers knowledge from survival data of a protein to a particular function of that protein. This is followed by an unsupervised transfer learning algorithm that extends the knowledge to a homologous protein. We explore the application of our algorithms in three cases. First, we test the supervised transfer on 17 previously published deep mutagenesis data sets to complete and refine missing data points. We further investigate these data sets to identify which mutations build better predictors of variant functions. In the second case, we apply the algorithm to predict higher-order mutations solely from single point mutagenesis data. Finally, we perform the unsupervised transfer learning algorithm to predict mutational effects of homologous proteins from experimental data sets. These algorithms are generalized to transfer knowledge between Markov random field models. We show the benefit of our transfer learning algorithms to utilize informative deep mutational data and provide new insights into protein variant functions. As these algorithms are generalized to transfer knowledge between Markov random field models, we expect these algorithms to be applicable to other disciplines.

Association of a new 99-bp indel of the CEL gene promoter region with phenotypic traits in chickens

Carboxyl ester lipase (CEL) encodes a cholesterol ester hydrolase that is secreted into the duodenum as a component of pancreatic juice. The objective of this study was to characterize the CEL gene, investigate the association between the CEL promoter variants and chicken phenotypic traits, and explore the CEL gene regulatory mechanism. An insertion/deletion (indel) caused by a 99-bp insertion fragment was shown for the first time in the chicken CEL promoter, and large differences in allelic frequency were found among commercial breeds, indigenous and feral birds. Association analysis demonstrated that this indel site had significant effects on shank length, shank girth, chest breadth at 8 weeks (p < 0.01), evisceration weight, sebum weight, breast muscle weight, and leg weight (p < 0.05). Tissue expression profiles showed extremely high levels of the CEL gene in pancreatic tissue. Moreover, the expression levels of the genes APOB, MTTP, APOV1 and SREBF1, which are involved in lipid transport, were significantly reduced by adding a 4% oxidized soybean oil diet treatment at the individual level and transfecting the embryonic primary hepatocytes with a CEL-overexpression vector. Interestingly, the results showed that the expression level of the II homozygous genotype was significantly higher than that of the ID and DD genotypes, while individuals with DD genotypes had higher phenotypic values. Therefore, these data suggested that the CEL gene might affect body growth by participating in hepatic lipoprotein metabolism and that the 99-bp indel polymorphism could be a potentially useful genetic marker for improving the economically important traits of chickens.

Large, three-generation human families reveal post-zygotic mosaicism and variability in germline mutation accumulation

The number of de novo mutations (DNMs) found in an offspring's genome increases with both paternal and maternal age. But does the rate of mutation accumulation in human gametes differ across families? Using sequencing data from 33 large, three-generation CEPH families, we observed significant variability in parental age effects on DNM counts across families, ranging from 0.19 to 3.24 DNMs per year. Additionally, we found that ~3% of DNMs originated following primordial germ cell specification in a parent, and differed from non-mosaic germline DNMs in their mutational spectra. We also discovered that nearly 10% of candidate DNMs in the second generation were post-zygotic, and present in both somatic and germ cells; these gonosomal mutations occurred at equivalent frequencies on both parental haplotypes. Our results demonstrate that rates of germline mutation accumulation vary among families with similar ancestry, and confirm that post-zygotic mosaicism is a substantial source of human DNM.

Molecular function limits divergent protein evolution on planetary timescales

Functional conservation is known to constrain protein evolution. Nevertheless, the long-term divergence patterns of proteins maintaining the same molecular function and the possible limits of this divergence have not been explored in detail. We investigate these fundamental questions by characterizing the divergence between ancient protein orthologs with conserved molecular function. Our results demonstrate that the decline of sequence and structural similarities between such orthologs significantly slows down after ~1-2 billion years of independent evolution. As a result, the sequence and structural similarities between ancient orthologs have not substantially decreased for the past billion years. The effective divergence limit (>25% sequence identity) is not primarily due to protein sites universally conserved in all linages. Instead, less than four amino acid types are accepted, on average, per site across orthologous protein sequences. Our analysis also reveals different divergence patterns for protein sites with experimentally determined small and large fitness effects of mutations.

Editorial note

This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

The living organism: evolutionary design or an accident

The presented work discusses some evolutionary phenomena underlining the complexity of organism creation and surprisingly the short evolutionary time of this process in particular. Uncommonness of this process ensued from the necessary simultaneous combining of highly complicated biological mechanisms, of which some were generated independently before the direct evolutionary demand. This in conclusion points to still not fully understood biological program ensuring superiority of the permanent evolutionary progress over effects of purely random mutational changes as the driving mechanism in evolution.

Harmonious genetic combinations rewire regulatory networks and flip gene essentiality

We lack an understanding of how the full range of genetic variants that occur in individuals can interact. To address this shortcoming, here we combine diverse mutations between genes in a model regulatory network, the galactose (GAL) switch of budding yeast. The effects of thousands of pairs of mutations fall into a limited number of phenotypic classes. While these effects are mostly predictable using simple rules that capture the ‘stereotypical’ genetic interactions of the network, some double mutants have unexpected outcomes including constituting alternative functional switches. Each of these ‘harmonious’ genetic combinations exhibits altered dependency on other regulatory genes. These cases illustrate how both pairwise and higher epistasis determines gene essentiality and how combinations of mutations rewire regulatory networks. Together, our results provide an overview of how broad spectra of mutations interact, how these interactions can be predicted, and how diverse genetic solutions can achieve ‘wild-type’ phenotypic behavior.

Studying how genetic variants in different genes interact and their combinatorial output is experimentally and analytically challenging. Here, the authors quantify the effects of more than 5000 mutation pairs in the yeast GAL regulatory system, finding that many combinations can be predicted with statistical models.

Saturation mutagenesis of twenty disease-associated regulatory elements at single base-pair resolution

The majority of common variants associated with common diseases, as well as an unknown proportion of causal mutations for rare diseases, fall in noncoding regions of the genome. Although catalogs of noncoding regulatory elements are steadily improving, we have a limited understanding of the functional effects of mutations within them. Here, we perform saturation mutagenesis in conjunction with massively parallel reporter assays on 20 disease-associated gene promoters and enhancers, generating functional measurements for over 30,000 single nucleotide substitutions and deletions. We find that the density of putative transcription factor binding sites varies widely between regulatory elements, as does the extent to which evolutionary conservation or integrative scores predict functional effects. These data provide a powerful resource for interpreting the pathogenicity of clinically observed mutations in these disease-associated regulatory elements, and comprise a rich dataset for the further development of algorithms that aim to predict the regulatory effects of noncoding mutations.

Biophysical and Mechanistic Models for Disease-Causing Protein Variants

The rapid decrease in DNA sequencing cost is revolutionizing medicine and science. In medicine, genome sequencing has revealed millions of missense variants that change protein sequences, yet we only understand the molecular and phenotypic consequences of a small fraction. Within protein science, high-throughput deep mutational scanning experiments enable us to probe thousands of variants in a single, multiplexed experiment. We review efforts that bring together these topics via experimental and computational approaches to determine the consequences of missense variants in proteins. We focus on the role of changes in protein stability as a driver for disease, and how experiments, biophysical models, and computation are providing a framework for understanding and predicting how changes in protein sequence affect cellular protein stability.

Redox- and Ligand Binding-Dependent Conformational Ensembles in the Human Apoptosis-Inducing Factor Regulate Its Pro-Life and Cell Death Functions

Aims: The human apoptosis-inducing factor (hAIF) supports OXPHOS biogenesis and programmed cell death, with missense mutations producing neurodegenerative phenotypes. hAIF senses the redox environment of cellular compartments, stabilizing a charge transfer complex (CTC) dimer that modulates the protein interaction network. In this context, we aimed to evaluate the subcellular pH, CTC formation, and pathogenic mutations effects on hAIF stability, and a thermal denaturation high-throughput screening (HTS) assay to discover AIF binders. Results: Apoptotic hAIF_Δ1-101 is not stable at intermembrane mitochondrial space (IMS) pH, but the 77-101 residues confer stability to the mitochondrial isoform. hAIF and its CTC populate different conformational ensembles with redox switch to the CTC producing a less stable and compact protein. The pathogenic G308E, ΔR201, and E493V mutations modulate hAIF stability; particularly, ΔR201 causes a population shift to a less stable conformation that remodels active site structure and dynamics. We have identified new molecules that modulate the hAIF reduced nicotinamide adenine dinucleotide (NADH)/oxidized nicotinamide adenine dinucleotide (NAD⁺) association/dissociation equilibrium and regulate its catalytic efficiency. Innovation: Biophysical methods allow evaluating the regulation of hAIF functional ensembles and to develop an HTS assay to discover small molecules that might modulate hAIF stability and activities. Conclusions: The mitochondrial soluble 54-77 portion stabilizes hAIF at the IMS pH. NADH-redox-linked conformation changes course with strong NAD⁺ binding and protein dimerization, but they produce a negative impact in overall hAIF stability. Loss of functionality in the R201 deletion is due to distortion of the active site architecture. We report molecules that may serve as leads in the development of hAIF bioactive compounds.

The Causes and Consequences of Genetic Interactions (Epistasis)

The same mutation can have different effects in different individuals. One important reason for this is that the outcome of a mutation can depend on the genetic context in which it occurs. This dependency is known as epistasis. In recent years, there has been a concerted effort to quantify the extent of pairwise and higher-order genetic interactions between mutations through deep mutagenesis of proteins and RNAs. This research has revealed two major components of epistasis: nonspecific genetic interactions caused by nonlinearities in genotype-to-phenotype maps, and specific interactions between particular mutations. Here, we provide an overview of our current understanding of the mechanisms causing epistasis at the molecular level, the consequences of genetic interactions for evolution and genetic prediction, and the applications of epistasis for understanding biology and determining macromolecular structures.

NQO1: A target for the treatment of cancer and neurological diseases, and a model to understand loss of function disease mechanisms

NAD(P)H quinone oxidoreductase 1 (NQO1) is a multi-functional protein that catalyses the reduction of quinones (and other molecules), thus playing roles in xenobiotic detoxification and redox balance, and also has roles in stabilising apoptosis regulators such as p53. The structure and enzymology of NQO1 is well-characterised, showing a substituted enzyme mechanism in which NAD(P)H binds first and reduces an FAD cofactor in the active site, assisted by a charge relay system involving Tyr-155 and His-161. Protein dynamics play important role in physio-pathological aspects of this protein. NQO1 is a good target to treat cancer due to its overexpression in cancer cells. A polymorphic form of NQO1 (p.P187S) is associated with increased cancer risk and certain neurological disorders (such as multiple sclerosis and Alzheimer´s disease), possibly due to its roles in the antioxidant defence. p.P187S has greatly reduced FAD affinity and stability, due to destabilization of the flavin binding site and the C-terminal domain, which leading to reduced activity and enhanced degradation. Suppressor mutations partially restore the activity of p.P187S by local stabilization of these regions, and showing long-range allosteric communication within the protein. Consequently, the correction of NQO1 misfolding by pharmacological chaperones is a viable strategy, which may be useful to treat cancer and some neurological conditions, targeting structural spots linked to specific disease-mechanisms. Thus, NQO1 emerges as a good model to investigate loss of function mechanisms in genetic diseases as well as to improve strategies to discriminate between neutral and pathogenic variants in genome-wide sequencing studies.

krCRISPR: an easy and efficient strategy for generating conditional knockout of essential genes in cells

Background

CRISPR/Cas9 system is a powerful tool for knocking out genes in cells. However, genes essential for cell survival cannot be directly knocked out. Traditionally, generation of conditional knockout cells requires multiple steps.

Results

In this study, we developed an easy and efficient strategy to generate conditional knockout cells by using double episomal vectors – one which expresses gRNA and Cas9 nuclease, and the other expresses an inducible rescue gene. Using this system which we named “krCRISPR” (knockout-rescue CRISPR), we showed that essential genes, HDAC3 and DNMT1, can be efficiently knocked out. When cells reach a desired confluency, the exogenous rescue genes can be silenced by the addition of doxycycline. Furthermore, the krCRISPR system enabled us to study the effects of the essential gene mutations on cells. We showed that the P507L mutation in DNMT1 led to downregulation of global DNA methylation in cells, indicating that it is a disease-causing mutation.

Conclusions

The krCRISPR system offers an easy and efficient platform that facilitates the study of essential genes’ function.

Electronic supplementary material

The online version of this article (10.1186/s13036-019-0150-y) contains supplementary material, which is available to authorized users.

Genetic predisposition to colorectal cancer: syndromes, genes, classification of genetic variants and implications for precision medicine

This article reviews genes and syndromes associated with predisposition to colorectal cancer (CRC), with an overview of gene variant classification. We include updates on the application of preventive and therapeutic measures, focusing on the use of non-steroidal anti-inflammatory drugs (NSAIDs) and immunotherapy. Germline pathogenic variants in genes conferring high or moderate risk to cancer are detected in 6-10% of all CRCs and 20% of those diagnosed before age 50. CRC syndromes can be subdivided into nonpolyposis and polyposis entities, the most common of which are Lynch syndrome and familial adenomatous polyposis, respectively. In addition to known and novel genes associated with highly penetrant CRC risk, identification of pathogenic germline variants in genes associated with moderate-penetrance cancer risk and/or hereditary cancer syndromes not traditionally linked to CRC may have an impact on genetic testing, counseling, and surveillance. The use of multigene panels in genetic testing has exposed challenges in the classification of variants of uncertain significance. We provide an overview of the main classification systems and strategies for improving these. Finally, we highlight approaches for integrating chemoprevention in the care of individuals with genetic predisposition to CRC and use of targeted agents and immunotherapy for treatment of mismatch repair-deficient and hypermutant tumors. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Megabase Length Hypermutation Accompanies Human Structural Variation at 17p11.2

DNA rearrangements resulting in human genome structural variants (SVs) are caused by diverse mutational mechanisms. We used long- and short-read sequencing technologies to investigate end products of de novo chromosome 17p11.2 rearrangements and query the molecular mechanisms underlying both recurrent and non-recurrent events. Evidence for an increased rate of clustered single-nucleotide variant (SNV) mutation in cis with non-recurrent rearrangements was found. Indel and SNV formation are associated with both copy-number gains and losses of 17p11.2, occur up to ∼1 Mb away from the breakpoint junctions, and favor C > G transversion substitutions; results suggest that single-stranded DNA is formed during the genesis of the SV and provide compelling support for a microhomology-mediated break-induced replication (MMBIR) mechanism for SV formation. Our data show an additional mutational burden of MMBIR consisting of hypermutation confined to the locus and manifesting as SNVs and indels predominantly within genes.