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Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases. A catalogue of predicted loss-of-function variants in 125,748 whole-exome and 15,708 whole-genome sequencing datasets from the Genome Aggregation Database (gnomAD) reveals the spectrum of mutational constraints that affect these human protein-coding genes.

Since the first half of the twentieth century, evolutionary theory has been dominated by the idea that mutations occur randomly with respect to their consequences 1 . Here we test this assumption with large surveys of de novo mutations in the plant Arabidopsis thaliana . In contrast to expectations, we find that mutations occur less often in functionally constrained regions of the genome—mutation frequency is reduced by half inside gene bodies and by two-thirds in essential genes. With independent genomic mutation datasets, including from the largest Arabidopsis mutation accumulation experiment conducted to date, we demonstrate that epigenomic and physical features explain over 90% of variance in the genome-wide pattern of mutation bias surrounding genes. Observed mutation frequencies around genes in turn accurately predict patterns of genetic polymorphisms in natural Arabidopsis accessions ( r  = 0.96). That mutation bias is the primary force behind patterns of sequence evolution around genes in natural accessions is supported by analyses of allele frequencies. Finally, we find that genes subject to stronger purifying selection have a lower mutation rate. We conclude that epigenome-associated mutation bias 2 reduces the occurrence of deleterious mutations in Arabidopsis , challenging the prevailing paradigm that mutation is a directionless force in evolution. Data on de novo mutations in Arabidopsis thaliana reveal that mutations do not occur randomly; instead, epigenome-associated mutation bias reduces the occurrence of deleterious mutations.

Background SARS-CoV-2 is a RNA coronavirus responsible for the pandemic of the Severe Acute Respiratory Syndrome (COVID-19). RNA viruses are characterized by a high mutation rate, up to a million times higher than that of their hosts. Virus mutagenic capability depends upon several factors, including the fidelity of viral enzymes that replicate nucleic acids, as SARS-CoV-2 RNA dependent RNA polymerase (RdRp). Mutation rate drives viral evolution and genome variability, thereby enabling viruses to escape host immunity and to develop drug resistance. Methods We analyzed 220 genomic sequences from the GISAID database derived from patients infected by SARS-CoV-2 worldwide from December 2019 to mid-March 2020. SARS-CoV-2 reference genome was obtained from the GenBank database. Genomes alignment was performed using Clustal Omega. Mann–Whitney and Fisher-Exact tests were used to assess statistical significance. Results We characterized 8 novel recurrent mutations of SARS-CoV-2, located at positions 1397, 2891, 14408, 17746, 17857, 18060, 23403 and 28881. Mutations in 2891, 3036, 14408, 23403 and 28881 positions are predominantly observed in Europe, whereas those located at positions 17746, 17857 and 18060 are exclusively present in North America. We noticed for the first time a silent mutation in RdRp gene in England (UK) on February 9th, 2020 while a different mutation in RdRp changing its amino acid composition emerged on February 20th, 2020 in Italy (Lombardy). Viruses with RdRp mutation have a median of 3 point mutations [range: 2–5], otherwise they have a median of 1 mutation [range: 0–3] (p value < 0.001). Conclusions These findings suggest that the virus is evolving and European, North American and Asian strains might coexist, each of them characterized by a different mutation pattern. The contribution of the mutated RdRp to this phenomenon needs to be investigated. To date, several drugs targeting RdRp enzymes are being employed for SARS-CoV-2 infection treatment. Some of them have a predicted binding moiety in a SARS-CoV-2 RdRp hydrophobic cleft, which is adjacent to the 14408 mutation we identified. Consequently, it is important to study and characterize SARS-CoV-2 RdRp mutation in order to assess possible drug-resistance viral phenotypes. It is also important to recognize whether the presence of some mutations might correlate with different SARS-CoV-2 mortality rates.

Mutation is the ultimate source of genetic variation. The most direct and unbiased method of studying spontaneous mutations is via mutation accumulation (MA) lines. Until recently, MA experiments were limited by the cost of sequencing and thus provided us with small numbers of mutational events and therefore imprecise estimates of rates and patterns of mutation. We used whole-genome sequencing to identify nearly 1,000 spontaneous mutation events accumulated over ∼311,000 generations in 145 diploid MA lines of the budding yeast Saccharomyces cerevisiae . MA experiments are usually assumed to have negligible levels of selection, but even mild selection will remove strongly deleterious events. We take advantage of such patterns of selection and show that mutation classes such as indels and aneuploidies (especially monosomies) are proportionately much more likely to contribute mutations of large effect. We also provide conservative estimates of indel, aneuploidy, environment-dependent dominant lethal, and recessive lethal mutation rates. To our knowledge, for the first time in yeast MA data, we identified a sufficiently large number of single-nucleotide mutations to measure context-dependent mutation rates and were able to (i) confirm strong AT bias of mutation in yeast driven by high rate of mutations from C/G to T/A and (ii) detect a higher rate of mutation at C/G nucleotides in two specific contexts consistent with cytosine methylation in S. cerevisiae .

The CRISPR/Cas9 system has been implemented in a variety of model organisms to mediate site-directed mutagenesis. A wide range of mutation rates has been reported, but at a limited number of genomic target sites. To uncover the rules that govern effective Cas9-mediated mutagenesis in zebrafish, we targeted over a hundred genomic loci for mutagenesis using a streamlined and cloning-free method. We generated mutations in 85% of target genes with mutation rates varying across several orders of magnitude, and identified sequence composition rules that influence mutagenesis. We increased rates of mutagenesis by implementing several novel approaches. The activities of poor or unsuccessful single-guide RNAs (sgRNAs) initiating with a 5' adenine were improved by rescuing 5' end homogeneity of the sgRNA. In some cases, direct injection of Cas9 protein/sgRNA complex further increased mutagenic activity. We also observed that low diversity of mutant alleles led to repeated failure to obtain frame-shift mutations. This limitation was overcome by knock-in of a stop codon cassette that ensured coding frame truncation. Our improved methods and detailed protocols make Cas9-mediated mutagenesis an attractive approach for labs of all sizes.

Generation time varies widely across organisms and is an important factor in the life cycle, life history and evolution of organisms. Although the doubling time (DT) has been estimated for many bacteria in the laboratory, it is nearly impossible to directly measure it in the natural environment. However, an estimate can be obtained by measuring the rate at which bacteria accumulate mutations per year in the wild and the rate at which they mutate per generation in the laboratory. If we assume the mutation rate per generation is the same in the wild and in the laboratory, and that all mutations in the wild are neutral, an assumption that we show is not very important, then an estimate of the DT can be obtained by dividing the latter by the former. We estimate the DT for five species of bacteria for which we have both an accumulation and a mutation rate estimate. We also infer the distribution of DTs across all bacteria from the distribution of the accumulation and mutation rates. Both analyses suggest that DTs for bacteria in the wild are substantially greater than those in the laboratory, that they vary by orders of magnitude between different species of bacteria and that a substantial fraction of bacteria double very slowly in the wild.

Significance The number of driver events required for human tumorigenesis has remained one of the fundamental issues in cancer research since the seminal studies of Armitage and Doll. This question has become even more important with the recent genome-wide sequencing studies of cancer, whose major goal is the identification of the driver genes responsible for tumor initiation and progression. By using a novel approach that combines conventional epidemiologic studies with genome-wide sequencing data, we show that only three sequential mutations are required to develop lung and colon adenocarcinomas, a number that is lower than what is typically thought to be required for the formation of cancers of these and other organs. This finding has important implications for the design of future cancer genome-sequencing efforts. Cancer arises through the sequential accumulation of mutations in oncogenes and tumor suppressor genes. However, how many such mutations are required for a normal human cell to progress to an advanced cancer? The best estimates for this number have been provided by mathematical models based on the relation between age and incidence. For example, the classic studies of Nordling [Nordling CO (1953) Br J Cancer 7(1):68–72] and Armitage and Doll [Armitage P, Doll R (1954) Br J Cancer 8(1):1–12] suggest that six or seven sequential mutations are required. Here, we describe a different approach to derive this estimate that combines conventional epidemiologic studies with genome-wide sequencing data: incidence data for different groups of patients with the same cancer type were compared with respect to their somatic mutation rates. In two well-documented cancer types (lung and colon adenocarcinomas), we find that only three sequential mutations are required to develop cancer. This conclusion deepens our understanding of the process of carcinogenesis and has important implications for the design of future cancer genome-sequencing efforts.

The high mutation rate of RNA viruses is credited with their evolvability and virulence. This Primer, however, discusses recent evidence that this is, in part, a byproduct of selection for faster genomic replication.

It is commonly assumed that mitochondrial DNA (mtDNA) evolves at a faster rate than nuclear DNA (nuDNA) in animals. This has contributed to the popularity of mtDNA as a molecular marker in evolutionary studies. Analyzing 121 multilocus data sets and four phylogenomic data sets encompassing 4,676 species of animals, we demonstrate that the ratio of mitochondrial over nuclear mutation rate is highly variable among animal taxa. In nonvertebrates, such as insects and arachnids, the ratio of mtDNA over nuDNA mutation rate varies between 2 and 6, whereas it is above 20, on average, in vertebrates such as scaled reptiles and birds. Interestingly, this variation is sufficient to explain the previous report of a similar level of mitochondrial polymorphism, on average, between vertebrates and nonvertebrates, which was originally interpreted as reflecting the effect of pervasive positive selection. Our analysis rather indicates that the among-phyla homogeneity in within-species mtDNA diversity is due to a negative correlation between mtDNA per-generation mutation rate and effective population size, irrespective of the action of natural selection. Finally, we explore the variation in the absolute per-year mutation rate of both mtDNA and nuDNA using a reduced data set for which fossil calibration is available, and discuss the potential determinants of mutation rate variation across genomes and taxa. This study has important implications regarding DNA-based identification methods in predicting that mtDNA barcoding should be less reliable in nonvertebrates than in vertebrates.

Background Elevated temperatures can cause physiological, biochemical, and molecular responses in plants that can greatly affect their growth and development. Mutations are the most fundamental force driving biological evolution. However, how long-term elevations in temperature influence the accumulation of mutations in plants remains unknown. Results Multigenerational exposure of Arabidopsis MA (mutation accumulation) lines and MA populations to extreme heat and moderate warming results in significantly increased mutation rates in single-nucleotide variants (SNVs) and small indels. We observe distinctive mutational spectra under extreme and moderately elevated temperatures, with significant increases in transition and transversion frequencies. Mutation occurs more frequently in intergenic regions, coding regions, and transposable elements in plants grown under elevated temperatures. At elevated temperatures, more mutations accumulate in genes associated with defense responses, DNA repair, and signaling. Notably, the distribution patterns of mutations among all progeny differ between MA populations and MA lines, suggesting that stronger selection effects occurred in populations. Methylation is observed more frequently at mutation sites, indicating its contribution to the mutation process at elevated temperatures. Mutations occurring within the same genome under elevated temperatures are significantly biased toward low gene density regions, special trinucleotides, tandem repeats, and adjacent simple repeats. Additionally, mutations found in all progeny overlap significantly with genetic variations reported in 1001 Genomes, suggesting non-uniform distribution of de novo mutations through the genome. Conclusion Collectively, our results suggest that elevated temperatures can accelerate the accumulation, and alter the molecular profiles, of DNA mutations in plants, thus providing significant insight into how environmental temperatures fuel plant evolution.