Pathogenic mitochondrial DNA mutations are common in the general population

Mitochondrial DNA (mtDNA) mutations are a major cause of genetic disease, but their prevalence in the general population is not known. We determined the frequency of ten mitochondrial point mutations in 3168 neonatal-cord-blood samples from sequential live births, analyzing matched maternal-blood samples to estimate the de novo mutation rate. mtDNA mutations were detected in 15 offspring (0.54%, 95% CI = 0.30–0.89%). Of these live births, 0.00107% (95% CI = 0.00087–0.0127) harbored a mutation not detected in the mother's blood, providing an estimate of the de novo mutation rate. The most common mutation was m.3243A→G. m.14484T→C was only found on sub-branches of mtDNA haplogroup J. In conclusion, at least one in 200 healthy humans harbors a pathogenic mtDNA mutation that potentially causes disease in the offspring of female carriers. The exclusive detection of m.14484T→C on haplogroup J implicates the background mtDNA haplotype in mutagenesis. These findings emphasize the importance of developing new approaches to prevent transmission.     

Next‐generation sequencing (NGS)‐based identification of induced mutations in a doubly mutagenized tomato (Solanum lycopersicum) population

The identification of mutations in targeted genes has been significantly simplified by the advent of TILLING (Targeting Induced Local Lesions In Genomes), speeding up the functional genomic analysis of animals and plants. Next‐generation sequencing (NGS) is gradually replacing classical TILLING for mutation detection, as it allows the analysis of a large number of amplicons in short durations. The NGS approach was used to identify mutations in a population of Solanum lycopersicum (tomato) that was doubly mutagenized by ethylmethane sulphonate (EMS). Twenty‐five genes belonging to carotenoids and folate metabolism were PCR‐amplified and screened to identify potentially beneficial alleles. To augment efficiency, the 600‐bp amplicons were directly sequenced in a non‐overlapping manner in Illumina MiSeq, obviating the need for a fragmentation step before library preparation. A comparison of the different pooling depths revealed that heterozygous mutations could be identified up to 128‐fold pooling. An evaluation of six different software programs (camba , crisp , gatk unified genotyper , lofreq , snver and vipr ) revealed that no software program was robust enough to predict mutations with high fidelity. Among these, crisp and camba predicted mutations with lower false discovery rates. The false positives were largely eliminated by considering only mutations commonly predicted by two different software programs. The screening of 23.47 Mb of tomato genome yielded 75 predicted mutations, 64 of which were confirmed by Sanger sequencing with an average mutation density of 1/367 Kb. Our results indicate that NGS combined with multiple variant detection tools can reduce false positives and significantly speed up the mutation discovery rate.     

Direct Measure of the De Novo Mutation Rate in Autism and Schizophrenia Cohorts

The role of de novo mutations (DNMs) in common diseases remains largely unknown. Nonetheless, the rate of de novo deleterious mutations and the strength of selection against de novo mutations are critical to understanding the genetic architecture of a disease. Discovery of high-impact DNMs requires substantial high-resolution interrogation of partial or complete genomes of families via resequencing. We hypothesized that deleterious DNMs may play a role in cases of autism spectrum disorders (ASD) and schizophrenia (SCZ), two etiologically heterogeneous disorders with significantly reduced reproductive fitness. We present a direct measure of the de novo mutation rate (μ) and selective constraints from DNMs estimated from a deep resequencing data set generated from a large cohort of ASD and SCZ cases (n = 285) and population control individuals (n = 285) with available parental DNA. A survey of ∼430 Mb of DNA from 401 synapse-expressed genes across all cases and 25 Mb of DNA in controls found 28 candidate DNMs, 13 of which were cell line artifacts. Our calculated direct neutral mutation rate (1.36 × 10⁻⁸) is similar to previous indirect estimates, but we observed a significant excess of potentially deleterious DNMs in ASD and SCZ individuals. Our results emphasize the importance of DNMs as genetic mechanisms in ASD and SCZ and the limitations of using DNA from archived cell lines to identify functional variants.     

Mutation rates and the evolution of germline structure

Genome sequencing studies of de novo mutations in humans have revealed surprising incongruities in our understanding of human germline mutation. In particular, the mutation rate observed in modern humans is substantially lower than that estimated from calibration against the fossil record, and the paternal age effect in mutations transmitted to offspring is much weaker than expected from our long-standing model of spermatogenesis. I consider possible explanations for these discrepancies, including evolutionary changes in life-history parameters such as generation time and the age of puberty, a possible contribution from undetected post-zygotic mutations early in embryo development, and changes in cellular mutation processes at different stages of the germline. I suggest a revised model of stem-cell state transitions during spermatogenesis, in which ‘dark’ gonial stem cells play a more active role than hitherto envisaged, with a long cycle time undetected in experimental observations. More generally, I argue that the mutation rate and its evolution depend intimately on the structure of the germline in humans and other primates.This article is part of the themed issue ‘Dating species divergences using rocks and clocks''.     

Pedigree-based and phylogenetic methods support surprising patterns of mutation rate and spectrum in the gray mouse lemur

Mutations are the raw material on which evolution acts, and knowledge of their frequency and genomic distribution is crucial for understanding how evolution operates at both long and short timescales. At present, the rate and spectrum of de novo mutations have been directly characterized in relatively few lineages. Our study provides the first direct mutation-rate estimate for a strepsirrhine (i.e., the lemurs and lorises), which comprises nearly half of the primate clade. Using high-coverage linked-read sequencing for a focal quartet of gray mouse lemurs (Microcebus murinus), we estimated the mutation rate to be among the highest calculated for a mammal at 1.52 × 10^–8 (95% credible interval: 1.28 × 10⁻⁸–1.78 × 10⁻⁸) mutations/site/generation. Further, we found an unexpectedly low count of paternal mutations, and only a modest overrepresentation of mutations at CpG sites. Despite the surprising nature of these results, we found both the rate and spectrum to be robust to the manipulation of a wide range of computational filtering criteria. We also sequenced a technical replicate to estimate a false-negative and false-positive rate for our data and show that any point estimate of a de novo mutation rate should be considered with a large degree of uncertainty. For validation, we conducted an independent analysis of context-dependent substitution types for gray mouse lemur and five additional primate species for which de novo mutation rates have also been estimated. These comparisons revealed general consistency of the mutation spectrum between the pedigree-based and the substitution-rate analyses for all species compared.Subject terms: Evolution, Molecular evolution     

Recent advances in gene structure prediction

De novo gene predictors are programs that predict the exon-intron structures of genes using the sequences of one or more genomes as their only input. In the past two years, dual-genome de novo predictors, which exploit local rates and patterns of mutation inferred from alignments between two genomes, have led to significant improvements in accuracy. Systems that exploit more than two genomes simultaneously have only recently begun to appear and are not yet competitive on practical tasks, but offer the greatest hope for near-term improvements. Dual-genome de novo prediction for compact eukaryotic genomes such as those of Arabidopsis thaliana and Caenorhabditis elegans is already quite accurate. Although mammalian gene prediction lags behind in accuracy, it is yielding ever more useful results. Coupled with significant improvements in pseudogene detection methods, which have eliminated many false positives, we have reached the point where de novo gene predictions are being used as hypotheses to drive experimental annotation via systematic RT-PCR and sequencing.     

De novo mutations producing unstable Hbs or Hbs M.

Summary Cases of unstable hemoglobin and hemoglobin M disease that have appeared as de novo mutants over a span of approximately 50 years were used in derivingminimal, direct estimates of mutation rates per nucleotide per generation in man. The estimates are based upon analysis of data related to 40 cases of unstable Hbs and 15 of Hbs M that arose in 13 countries. The estimated rate calculated using all de novo -gene mutants is 7.4×10^-9 per nucleotide per generation; that derived using de novo -gene mutants is 10.0×10^-9. Subsequent calculations of mutation rates per - and -chain gene and extrapolation of these rates to a hypothetical gene of 1000 nucleotides yield an estimated mutation rate of 8.6×10^-6 per 1000 nucleotides per generation. Even though some instances of false paternity may have biased these estimates in an upward direction, underreporting of Hb M cases, and particularly of unstable hemoglobins, makes it likely that the cited values are minimal estimates of mutation rates at the molecular level.     

Massively parallel sequencing of the mouse exome to accurately identify rare, induced mutations: an immediate source for thousands of new mouse models

Accurate identification of sparse heterozygous single-nucleotide variants (SNVs) is a critical challenge for identifying the causative mutations in mouse genetic screens, human genetic diseases and cancer. When seeking to identify causal DNA variants that occur at such low rates, they are overwhelmed by false-positive calls that arise from a range of technical and biological sources. We describe a strategy using whole-exome capture, massively parallel DNA sequencing and computational analysis, which identifies with a low false-positive rate the majority of heterozygous and homozygous SNVs arising de novo with a frequency of one nucleotide substitution per megabase in progeny of N-ethyl-N-nitrosourea (ENU)-mutated C57BL/6j mice. We found that by applying a strategy of filtering raw SNV calls against known and platform-specific variants we could call true SNVs with a false-positive rate of 19.4 per cent and an estimated false-negative rate of 21.3 per cent. These error rates are small enough to enable calling a causative mutation from both homozygous and heterozygous candidate mutation lists with little or no further experimental validation. The efficacy of this approach is demonstrated by identifying the causative mutation in the Ptprc gene in a lymphocyte-deficient strain and in 11 other strains with immune disorders or obesity, without the need for meiotic mapping. Exome sequencing of first-generation mutant mice revealed hundreds of unphenotyped protein-changing mutations, 52 per cent of which are predicted to be deleterious, which now become available for breeding and experimental analysis. We show that exome sequencing data alone are sufficient to identify induced mutations. This approach transforms genetic screens in mice, establishes a general strategy for analysing rare DNA variants and opens up a large new source for experimental models of human disease.     

Direct estimate of the spontaneous germ line mutation rate in African green monkeys

Here, I provide the first direct estimate of the spontaneous mutation rate in an Old World monkey, using a seven individual, three‐generation pedigree of African green monkeys. Eight de novo mutations were identified within ～1.5 Gbp of accessible genome, corresponding to an estimated point mutation rate of 0.94 × 10^?8 per site per generation, suggesting an effective population size of ～12000 for the species. This estimation represents a significant improvement in our knowledge of the population genetics of the African green monkey, one of the most important nonhuman primate models in biomedical research. Furthermore, by comparing mutation rates in Old World monkeys with the only other direct estimates in primates to date–humans and chimpanzees–it is possible to uniquely address how mutation rates have evolved over longer time scales. While the estimated spontaneous mutation rate for African green monkeys is slightly lower than the rate of 1.2 × 10^?8 per base pair per generation reported in chimpanzees, it is similar to the lower range of rates of 0.96 × 10^?8–1.28 × 10^?8 per base pair per generation recently estimated from whole genome pedigrees in humans. This result suggests a long‐term constraint on mutation rate that is quite different from similar evidence pertaining to recombination rate evolution in primates.     

Estimation of the Spontaneous Mutation Rate per Nucleotide Site in a Drosophila melanogaster Full-Sib Family

We employed deep genome sequencing of two parents and 12 of their offspring to estimate the mutation rate per site per generation in a full-sib family of Drosophila melanogaster recently sampled from a natural population. Sites that were homozygous for the same allele in the parents and heterozygous in one or more offspring were categorized as candidate mutations and subjected to detailed analysis. In 1.23 × 10⁹ callable sites from 12 individuals, we confirmed six single nucleotide mutations. We estimated the false negative rate in the experiment by generating synthetic mutations using the empirical distributions of numbers of nonreference bases at heterozygous sites in the offspring. The proportion of synthetic mutations at callable sites that we failed to detect was <1%, implying that the false negative rate was extremely low. Our estimate of the point mutation rate is 2.8 × 10⁻⁹ (95% confidence interval = 1.0 × 10⁻⁹ − 6.1 × 10⁻⁹) per site per generation, which is at the low end of the range of previous estimates, and suggests an effective population size for the species of ∼1.4 × 10⁶. At one site, point mutations were present in two individuals, indicating that there had been a premeiotic mutation cluster, although surprisingly one individual had a G→A transition and the other a G→T transversion, possibly associated with error-prone mismatch repair. We also detected three short deletion mutations and no insertions, giving a deletion mutation rate of 1.2 × 10⁻⁹ (95% confidence interval = 0.7 × 10⁻⁹ − 11 × 10⁻⁹).     

Human germline mutation in the factor IX gene

The molecular epidemiology of factor IX germline mutations in patients with hemophilia B has been studied in detail because it is an advantageous model for analyzing recent germline mutations in humans. It is estimated that mutations have been defined in the majority of nucleotides that are the target for mutation. The likelihood that a factor IX missense mutation will cause disease correlates with the degree of evolutionary conservation of the amino acid. Mutation rates per base-pair have been estimated after careful consideration and correction for biases, predicting about 76 de novo mutations per generation per individual resulting in 0.3 deleterious changes. The male-to-female sex ratio of mutation varies with the type of mutation. There is evidence for a maternal age effect and an excess of non-CpG G:C to A:T transitions. The factor IX mutation pattern is similar among geographically, racially and ethnically diverse human populations. The data support primarily endogenous mechanisms of germline mutation in the factor IX gene. Mutations at splice junctions are compatible with simple rules for predicting disease causing mutations.     

Characterization of the factor VIII defect in 147 patients with sporadic hemophilia A: family studies indicate a mutation type-dependent sex ratio of mutation frequencies.

The clinical manifestation of hemophilia A is caused by a wide range of different mutations. In this study the factor VIII genes of 147 severe hemophilia A patients--all exclusively from sporadic families--were screened for mutations by use of the complete panel of modern DNA techniques. The pathogenous defect could be characterized in 126 patients (85.7 percent). Fifty-five patients (37.4 percent) showed a F8A-gene inversion, 47 (32.0 percent) a point mutation, 14 (9.5 percent) a small deletion, 8 (5.4 percent) a large deletion, and 2 (1.4 percent) a small insertion. Further, four (2.7 percent) mutations were localized but could not be sequenced yet. No mutation could be identified in 17 patients (11.6 percent). Sixteen (10.9 percent) of the identified mutations occurred in the B domain. Four of these were located in an adenosine nucleotide stretch at codon 1192, indicating a mutation hotspot. Somatic mosaicisms were detected in 3 (3.9 percent) of 76 patients, mothers, comprising 3 of 16 de novo mutations in the patients mothers. Investigation of family relatives allowed detection of a de novo mutation in 16 of 76 two-generation and 28 of 34 three-generation families. On the basis of these data, the male:female ratio of mutation frequencies (k) was estimated as k = 3.6. By use of the quotients of mutation origin in maternal grandfather to patients mother or to maternal grandmother, k was directly estimated as k = 15 and k = 7.5, respectively. Considering each mutation type separately, we revealed a mutation type-specific sex ratio of mutation frequencies. Point mutations showed a 5-to-10-fold-higher and inversions a >10-fold-higher mutation rate in male germ cells, whereas deletions showed a >5-fold-higher mutation rate in female germ cells. Consequently, and in accordance with the data of other diseases like Duchenne muscular dystrophy, our results indicate that at least for X-chromosomal disorders the male:female mutation rate of a disease is determined by its proportion of the different mutation types.     

Molecular nature of 11 spontaneous de novo mutations in Drosophila melanogaster

To investigate the molecular nature and rate of spontaneous mutation in Drosophila melanogaster, we screened 887,000 individuals for de novo recessive loss-of-function mutations at eight loci that affect eye color. In total, 28 mutants were found in 16 independent events (13 singletons and three clusters). The molecular nature of the 13 events was analyzed. Coding exons of the locus were affected by insertions or deletions >100 nucleotides long (6 events), short frameshift insertions or deletions (4 events), and replacement nucleotide substitutions (1 event). In the case of 2 mutant alleles, coding regions were not affected. Because approximately 70% of spontaneous de novo loss-of-function mutations in Homo sapiens are due to nucleotide substitutions within coding regions, insertions and deletions appear to play a much larger role in spontaneous mutation in D. melanogaster than in H. sapiens. If so, the per nucleotide mutation rate in D. melanogaster may be lower than in H. sapiens, even if their per locus mutation rates are similar.     

Post-zygotic Point Mutations Are an Underrecognized Source of De Novo Genomic Variation

De novo mutations are recognized both as an important source of genetic variation and as a prominent cause of sporadic disease in humans. Mutations identified as de novo are generally assumed to have occurred during gametogenesis and, consequently, to be present as germline events in an individual. Because Sanger sequencing does not provide the sensitivity to reliably distinguish somatic from germline mutations, the proportion of de novo mutations that occur somatically rather than in the germline remains largely unknown. To determine the contribution of post-zygotic events to de novo mutations, we analyzed a set of 107 de novo mutations in 50 parent-offspring trios. Using four different sequencing techniques, we found that 7 (6.5%) of these presumed germline de novo mutations were in fact present as mosaic mutations in the blood of the offspring and were therefore likely to have occurred post-zygotically. Furthermore, genome-wide analysis of “de novo” variants in the proband led to the identification of 4/4,081 variants that were also detectable in the blood of one of the parents, implying parental mosaicism as the origin of these variants. Thus, our results show that an important fraction of de novo mutations presumed to be germline in fact occurred either post-zygotically in the offspring or were inherited as a consequence of low-level mosaicism in one of the parents.     

Two Birds with One Stone? Possible Dual-Targeting H1N1 Inhibitors from Traditional Chinese Medicine

The H1N1 influenza pandemic of 2009 has claimed over 18,000 lives. During this pandemic, development of drug resistance further complicated efforts to control and treat the widespread illness. This research utilizes traditional Chinese medicine Database@Taiwan (TCM Database@Taiwan) to screen for compounds that simultaneously target H1 and N1 to overcome current difficulties with virus mutations. The top three candidates were de novo derivatives of xylopine and rosmaricine. Bioactivity of the de novo derivatives against N1 were validated by multiple machine learning prediction models. Ability of the de novo compounds to maintain CoMFA/CoMSIA contour and form key interactions implied bioactivity within H1 as well. Addition of a pyridinium fragment was critical to form stable interactions in H1 and N1 as supported by molecular dynamics (MD) simulation. Results from MD, hydrophobic interactions, and torsion angles are consistent and support the findings of docking. Multiple anchors and lack of binding to residues prone to mutation suggest that the TCM de novo derivatives may be resistant to drug resistance and are advantageous over conventional H1N1 treatments such as oseltamivir. These results suggest that the TCM de novo derivatives may be suitable candidates of dual-targeting drugs for influenza.     

Estimation of mutation induction rates in AT-rich sequences using a genome scanning approach after X irradiation of mouse spermatogonia

We have previously used NotI as the marker enzyme (recognizing GCGGCCGC) in a genome scanning approach for detection of mutations induced in mouse spermatogonia and estimated the mutation induction rate as about 0.7 x 10(-5) per locus per Gy. To see whether different parts of the genome have different sensitivities for mutation induction, we used AflII (recognizing CTTAAG) as the marker enzyme in the present study. After the screening of 1,120 spots in each mouse offspring, we found five mutations among 92,655 spots from the unirradiated paternal genome, five mutations among 218,411 spots from the unirradiated maternal genome, and 13 mutations among 92,789 spots from 5 Gy-exposed paternal genome. Among the 23 mutations, 11 involved mouse satellite DNA sequences (AT-rich), and the remaining 12 mutations also involved AT-rich but non-satellite sequences. Both types of sequences were found as multiple, similar-sequence blocks in the genome. Counting each member of cluster mutations separately and excluding results on one hypermutable spot, the spontaneous mutation rates were estimated as 3.2 (+/- 1.9) x 10(-5) and 2.3 (+/- 1.0) x 10(-5) per locus per generation in the male and female genomes, respectively, and the mutation induction rate as 1.1 (+/- 1.2) x 10(-5) per locus per Gy. The induction rate would be reduced to 0.9 x 10(-5) per locus per Gy if satellite sequence mutations were excluded from this analysis. The results indicate that mutation induction rates do not largely differ between GC-rich and AT-rich regions: 1 x 10(-5) per locus per Gy or less, which is close to 1.08 x 10(-5) per locus per Gy, the current estimate for the mean mutation induction rate in mice.     

All2: A tool for selecting mosaic mutations from comprehensive multi-cell comparisons

Accurate discovery of somatic mutations in a cell is a challenge that partially lays in immaturity of dedicated analytical approaches. Approaches comparing a cell’s genome to a control bulk sample miss common mutations, while approaches to find such mutations from bulk suffer from low sensitivity. We developed a tool, All², which enables accurate filtering of mutations in a cell without the need for data from bulk(s). It is based on pair-wise comparisons of all cells to each other where every call for base pair substitution and indel is classified as either a germline variant, mosaic mutation, or false positive. As All² allows for considering dropped-out regions, it is applicable to whole genome and exome analysis of cloned and amplified cells. By applying the approach to a variety of available data, we showed that its application reduces false positives, enables sensitive discovery of high frequency mutations, and is indispensable for conducting high resolution cell lineage tracing.