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Flowering plants possess an unrivaled diversity of mechanisms for achieving sexual and asexual reproduction, often simultaneously. The commonest type of asexual reproduction is clonal growth (vegetative propagation) in which parental genotypes (genets) produce vegetative modules (ramets) that are capable of independent growth, reproduction, and often dispersal. Clonal growth leads to an expansion in the size of genets and increased fitness because large floral displays increase fertility and opportunities for outcrossing. Moreover, the clonal dispersal of vegetative propagules can assist “mate finding,” particularly in aquatic plants. However, there are ecological circumstances in which functional antagonism between sexual and asexual reproductive modes can negatively affect the fitness of clonal plants. Populations of heterostylous and dioecious species have a small number of mating groups (two or three), which should occur at equal frequency in equilibrium populations. Extensive clonal growth and vegetative dispersal can disrupt the functioning of these sexual polymorphisms, resulting in biased morph ratios and populations with a single mating group, with consequences for fertility and mating. In populations in which clonal propagation predominates, mutations reducing fertility may lead to sexual dysfunction and even the loss of sex. Recent evidence suggests that somatic mutations can play a significant role in influencing fitness in clonal plants and may also help explain the occurrence of genetic diversity in sterile clonal populations. Highly polymorphic genetic markers offer outstanding opportunities for gaining novel insights into functional interactions between sexual and clonal reproduction in flowering plants.

Background The lifelong accumulation of somatic mutations underlies age-related phenotypes and cancer. Mutagenic forces are thought to shape the genome of aging cells in a tissue-specific way. Whole genome analyses of somatic mutation patterns, based on both types and genomic distribution of variants, can shed light on specific processes active in different human tissues and their effect on the transition to cancer. Results To analyze somatic mutation patterns, we compile a comprehensive genetic atlas of somatic mutations in healthy human cells. High-confidence variants are obtained from newly generated and publicly available whole genome DNA sequencing data from single non-cancer cells, clonally expanded in vitro. To enable a well-controlled comparison of different cell types, we obtain single genome data (92% mean coverage) from multi-organ biopsies from the same donors. These data show multiple cell types that are protected from mutagens and display a stereotyped mutation profile, despite their origin from different tissues. Conversely, the same tissue harbors cells with distinct mutation profiles associated to different differentiation states. Analyses of mutation rate in the coding and non-coding portions of the genome identify a cell type bearing a unique mutation pattern characterized by mutation enrichment in active chromatin, regulatory, and transcribed regions. Conclusions Our analysis of normal cells from healthy donors identifies a somatic mutation landscape that enhances the risk of tumor transformation in a specific cell population from the kidney proximal tubule. This unique pattern is characterized by high rate of mutation accumulation during adult life and specific targeting of expressed genes and regulatory regions.

ObjectiveA new adult-onset autoinflammatory syndrome has been described, named VEXAS (Vacuoles, E1 Enzyme, X-linked, Autoinflammatory, Somatic). We aimed to compare the clinical characteristics, the laboratory features and the outcomes between idiopathic-relapsing polychondritis (I-RP) and VEXAS-relapsing polychondritis (VEXAS-RP).MethodsPatients from French retrospective multicentre cohort of RP were separated into two groups: a VEXAS-RP and an I-RP.ResultsCompared with patients with I-RP (n=40), patients with VEXAS-RP (n=55) were men (96% vs 30%, p<0.001) and were older at diagnosis (66 vs 44 years, p<0.001). They had a greater prevalence of fever (60% vs 10%, p<0.001), of skin lesions (82% vs 20%, p<0.001), of ocular involvement (57% vs 28%, p=0.01), of pulmonary infiltrates (46% vs 0%, p<0.001), of heart involvement (11% vs 0%, p=0.0336) and with higher median C-reactive protein levels (64 mg/L vs 10 mg/L, p<0.001). Seventy-five per cent of the patients with VEXAS-RP had myelodysplastic syndrome (MDS) versus none in I-RP group. The glucocorticoids use, and the number of steroid sparing agents were similar in both groups, but patients with VEXAS-RP had more frequent refractory disease (remission obtained in 27% vs 90%, p<0001). VEXAS-RP was associated with higher risk of death: six patients (11%) died in the VEXAS-RP group after a median follow-up of 37 months and none in the I-RP group after a median follow-up of 92 months (p<0.05).ConclusionWe report the largest cohort of VEXAS-RP, characterised by high prevalence of male sex, fever, skin lesion, ocular involvement, pulmonary infiltration, heart involvement, older age and MDS association.

A major challenge for distinguishing cancer-causing driver mutations from inconsequential passenger mutations is the long-tail of infrequently mutated genes in cancer genomes. Here, we present and evaluate a method for prioritizing cancer genes accounting not only for mutations in individual genes but also in their neighbors in functional networks, MUFFINN (MUtations For Functional Impact on Network Neighbors). This pathway-centric method shows high sensitivity compared with gene-centric analyses of mutation data. Notably, only a marginal decrease in performance is observed when using 10 % of TCGA patient samples, suggesting the method may potentiate cancer genome projects with small patient populations.

Abstract Long-lived perennial plants accumulate numerous somatic mutations with age. Mutations originating in stem cells at the shoot apex often become fixed in large sectors of the plant body due to cell lineage drift during repeated branching. Understanding the somatic evolution of such mutations requires knowledge of the effective stem cell population size, the cellular bottleneck strength during branch initiation, and the mutation rate. Here, we show that these parameters can be estimated directly from cell-layer-enriched DNA sequencing data, thus filling a gap where no other in vivo method exists.

Background The phenotypes of cancer cells are driven in part by somatic structural variants. Structural variants can initiate tumors, enhance their aggressiveness, and provide unique therapeutic opportunities. Whole-genome sequencing of tumors can allow exhaustive identification of the specific structural variants present in an individual cancer, facilitating both clinical diagnostics and the discovery of novel mutagenic mechanisms. A plethora of somatic structural variant detection algorithms have been created to enable these discoveries; however, there are no systematic benchmarks of them. Rigorous performance evaluation of somatic structural variant detection methods has been challenged by the lack of gold standards, extensive resource requirements, and difficulties arising from the need to share personal genomic information. Results To facilitate structural variant detection algorithm evaluations, we create a robust simulation framework for somatic structural variants by extending the BAMSurgeon algorithm. We then organize and enable a crowdsourced benchmarking within the ICGC-TCGA DREAM Somatic Mutation Calling Challenge (SMC-DNA). We report here the results of structural variant benchmarking on three different tumors, comprising 204 submissions from 15 teams. In addition to ranking methods, we identify characteristic error profiles of individual algorithms and general trends across them. Surprisingly, we find that ensembles of analysis pipelines do not always outperform the best individual method, indicating a need for new ways to aggregate somatic structural variant detection approaches. Conclusions The synthetic tumors and somatic structural variant detection leaderboards remain available as a community benchmarking resource, and BAMSurgeon is available at https://github.com/adamewing/bamsurgeon .

The unique life form of plants promotes the accumulation of somatic mutations that can be passed to offspring in the next generation, because the same meristem cells responsible for vegetative growth also generate gametes for sexual reproduction. However, little is known about the consequences of somatic mutation accumulation for offspring fitness. We evaluate the fitness effects of somatic mutations in Mimulus guttatus by comparing progeny from self-pollinations made within the same flower (autogamy) to progeny from self-pollinations made between stems on the same plant (geitonogamy). The effects of somatic mutations are evident from this comparison, as autogamy leads to homozygosity of a proportion of somatic mutations, but progeny from geitonogamy remain heterozygous for mutations unique to each stem. In two different experiments, we find consistent fitness effects of somatic mutations from individual stems. Surprisingly, several progeny groups from autogamous crosses displayed increases in fitness compared to progeny from geitonogamy crosses, likely indicating that beneficial somatic mutations occurred in some stems. These results support the hypothesis that somatic mutations accumulate during vegetative growth, but they are filtered by different forms of selection that occur throughout development, resulting in the culling of expressed deleterious mutations and the retention of beneficial mutations.

Background Understanding the molecular basis of sport mutations in fruit trees has the potential to accelerate generation of improved cultivars. Results For this, we analyzed the genome of the apple tree that developed the RubyMac phenotype through a sport mutation that led to the characteristic fruit coloring of this variety. Overall, we found 46 somatic mutations that distinguished the mutant and wild-type branches of the tree. In addition, we found 54 somatic gene conversions (i.e., loss-of-heterozygosity mutations) that also distinguished the two parts of the tree. Approximately 20% of the mutations were specific to individual cell lineages, suggesting that they originated from the corresponding meristematic layers. Interestingly, the de novo mutations were enriched for GC =  > AT transitions while the gene conversions showed the opposite bias for AT =  > GC transitions, suggesting that GC-biased gene conversions have the potential to counteract the AT-bias of de novo mutations. By comparing the gene expression patterns in fruit skins from mutant and wild-type branches, we found 56 differentially expressed genes including 18 involved in anthocyanin biosynthesis. While none of the differently expressed genes harbored a somatic mutation, we found that some of them in regions of the genome that were recently associated with natural variation in fruit coloration. Conclusion Our analysis revealed insights in the characteristics of somatic change, which not only included de novo mutations but also gene conversions. Some of these somatic changes displayed strong candidate mutations for the change in fruit coloration in RubyMac .

Background Because driver mutations provide selective advantage to the mutant clone, they tend to occur at a higher frequency in tumor samples compared to selectively neutral (passenger) mutations. However, mutation frequency alone is insufficient to identify cancer genes because mutability is influenced by many gene characteristics, such as size, nucleotide composition, etc. The goal of this study was to identify gene characteristics associated with the frequency of somatic mutations in the gene in tumor samples. Results We used data on somatic mutations detected by genome wide screens from the Catalog of Somatic Mutations in Cancer (COSMIC). Gene size, nucleotide composition, expression level of the gene, relative replication time in the cell cycle, level of evolutionary conservation and other gene characteristics (totaling 11) were used as predictors of the number of somatic mutations. We applied stepwise multiple linear regression to predict the number of mutations per gene. Because missense, nonsense, and frameshift mutations are associated with different sets of gene characteristics, they were modeled separately. Gene characteristics explain 88% of the variation in the number of missense, 40% of nonsense, and 23% of frameshift mutations. Comparisons of the observed and expected numbers of mutations identified genes with a higher than expected number of mutations– positive outliers. Many of these are known driver genes. A number of novel candidate driver genes was also identified. Conclusions By comparing the observed and predicted number of mutations in a gene, we have identified known cancer-associated genes as well as 111 novel cancer associated genes. We also showed that adding the number of silent mutations per gene reported by genome/exome wide screens across all cancer type (COSMIC data) as a predictor substantially exceeds predicting accuracy of the most popular cancer gene predicting tool - MutsigCV.

Although somatic mutations in exon 2 of the mediator complex subunit 12 ( MED12 ) gene have been reported previously in uterine fibroids in women from Finland, South Africa, and North America, the status of these mutations was not reported in the Southern United States women. The aim of this study is to determine the MED12 somatic mutations in uterine fibroids of women from Southern Unites States, which will help to better understand the contribution of MED12 mutations in fibroid tumor biology. Herein, we determined the frequency of MED12 gene exon 2 somatic mutations in 143 fibroid tumors from a total of 135 women from the Southern United States and in 50 samples of the adjacent myometrium using PCR amplification and Sanger sequencing. We observed that the MED12 gene is mutated in 64.33 % (92/143) of uterine fibroid cases in the exon 2 (including deletion mutations). These mutations include 107T > G (4.3 %), 130G > C (2.8 %), 130G > A (7.0 %), 130G > T (2.8 %), 131G > C (2.1 %), 131G > A (20.2 %), and 131G > T (2.1 %). Interestingly, we identified four novel mutations in these patients: 107 T > C (12.8 %), 105A > T (2.1 %), 122T > A (2.1 %), and 92T > A (2.1 %). As expected, we did not observe any mutations in the normal myometrium. Moreover, we found a higher rate of deletion mutations (17.5 %, 25/143) in the above fibroid tumors. Our results clearly demonstrate that the MED12 gene exon 2 is frequently mutated in human uterine fibroids in Southern United States women. These results highlight the molecular pathogenesis of human uterine fibroids with the central role of MED12 somatic mutations.