Mean Mutation Rate Research Articles

Estimating mutation rates under heterogeneous stress responses.

Exposure to environmental stressors, including certain antibiotics, induces stress responses in bacteria. Some of these responses increase mutagenesis and thus potentially accelerate resistance evolution. Many studies report increased mutation rates under stress, often using the standard experimental approach of fluctuation assays. However, single-cell studies have revealed that many stress responses are heterogeneously expressed in bacterial populations, which existing estimation methods have not yet addressed. We develop a population dynamic model that considers heterogeneous stress responses (subpopulations of cells with the response off or on) that impact both mutation rate and cell division rate, inspired by the DNA-damage response in Escherichia coli (SOS response). We derive the mutant count distribution arising in fluctuation assays under this model and then implement maximum likelihood estimation of the mutation-rate increase specifically associated with the expression of the stress response. Using simulated mutant count data, we show that our inference method allows for accurate and precise estimation of the mutation-rate increase, provided that this increase is sufficiently large and the induction of the response also reduces the division rate. Moreover, we find that in many cases, either heterogeneity in stress responses or mutant fitness costs could explain similar patterns in fluctuation assay data, suggesting that separate experiments would be required to identify the true underlying process. In cases where stress responses and mutation rates are heterogeneous, current methods still correctly infer the effective increase in population mean mutation rate, but we provide a novel method to infer distinct stress-induced mutation rates, which could be important for parameterising evolutionary models.

Genomic Surveillance and Mutation Analysis of SARS-CoV-2 Variants among Patients in Saudi Arabia.

The genome of severe acute respiratory coronavirus-2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19), has undergone a rapid evolution, resulting in the emergence of multiple SARS-CoV-2 variants with amino acid changes. This study aimed to sequence the whole genome of SARS-CoV-2 and detect the variants present in specimens from Saudi Arabia. Furthermore, we sought to analyze and characterize the amino acid changes in the various proteins of the identified SARS-CoV-2 variants. A total of 1161 samples from patients diagnosed with COVID-19 in Saudi Arabia, between 1 April 2021 and 31 July 2023, were analyzed. Whole genome sequencing was employed for variant identification and mutation analysis. The statistical analysis was performed using the Statistical Analytical Software SAS, version 9.4, and GraphPad, version 9.0. This study identified twenty-three variants and subvariants of SARS-CoV-2 within the population, with the Omicron BA.1 (21K) variant (37.0%) and the Delta (21J) variant (12%) being the most frequently detected. Notably, the Omicron subvariants exhibited a higher mean mutation rate. Amino acid mutations were observed in twelve proteins. Among these, the spike (S), ORF1a, nucleocapsid (N), and ORF1b proteins showed a higher frequency of amino acid mutations compared to other the viral proteins. The S protein exhibited the highest incidence of amino acid mutations (47.6%). Conversely, the ORF3a, ORF8, ORF7a, ORF6, and ORF7b proteins appeared more conserved, demonstrating the lowest percentage and frequency of amino acid mutations. The investigation of structural protein regions revealed the N-terminal S1 subunit of the S protein to frequently harbor mutations, while the N-terminal domain of the envelope (E) protein displayed the lowest mutation frequency. This study provides insights into the variants and genetic diversity of SARS-CoV-2, underscoring the need for further research to comprehend its genome evolution and the occurrence of mutations. These findings are pertinent to the development of testing approaches, therapeutics, and vaccine strategies.

Modeling SARS-CoV-2 nucleotide mutations as a stochastic process.

This study analyzes the SARS-CoV-2 genome sequence mutations by modeling its nucleotide mutations as a stochastic process in both the time-series and spatial domain of the gene sequence. In the time-series model, a Markov Chain embedded Poisson random process characterizes the mutation rate matrix, while the spatial gene sequence model delineates the distribution of mutation inter-occurrence distances. Our experiment focuses on five key variants of concern that had become a global concern due to their high transmissibility and virulence. The time-series results reveal distinct asymmetries in mutation rate and propensities among different nucleotides and across different strains, with a mean mutation rate of approximately 2 mutations per month. In particular, our spatial gene sequence results reveal some novel biological insights on the characteristic distribution of mutation inter-occurrence distances, which display a notable pattern similar to other natural diseases. Our findings contribute interesting insights to the underlying biological mechanism of SARS-CoV-2 mutations, bringing us one step closer to improving the accuracy of existing mutation prediction models. This research could also potentially pave the way for future work in adopting similar spatial random process models and advanced spatial pattern recognition algorithms in order to characterize mutations on other different kinds of virus families.

Genomic Surveillance of SARS-CoV-2 Variants in the Dominican Republic and Emergence of a Local Lineage.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an RNA virus that evolves over time, leading to new variants. In the current study, we assessed the genomic epidemiology of SARS-CoV-2 in the Dominican Republic. A total of 1149 SARS-CoV-2 complete genome nucleotide sequences from samples collected between March 2020 and mid-February 2022 in the Dominican Republic were obtained from the Global Initiative on Sharing All Influenza Data (GISAID) database. Phylogenetic relationships and evolution rates were analyzed using the maximum likelihood method and the Bayesian Markov chain Monte Carlo (MCMC) approach. The genotyping details (lineages) were obtained using the Pangolin web application. In addition, the web tools Coronapp, and Genome Detective Viral Tools, among others, were used to monitor epidemiological characteristics. Our results show that the most frequent non-synonymous mutation over the study period was D614G. Of the 1149 samples, 870 (75.74%) were classified into 8 relevant variants according to Pangolin/Scorpio. The first Variants Being Monitored (VBM) were detected in December 2020. Meanwhile, in 2021, the variants of concern Delta and Omicron were identified. The mean mutation rate was estimated to be 1.5523 × 10-3 (95% HPD: 1.2358 × 10-3, 1.8635 × 10-3) nucleotide substitutions per site. We also report the emergence of an autochthonous SARS-CoV-2 lineage, B.1.575.2, that circulated from October 2021 to January 2022, in co-circulation with the variants of concern Delta and Omicron. The impact of B.1.575.2 in the Dominican Republic was minimal, but it then expanded rapidly in Spain. A better understanding of viral evolution and genomic surveillance data will help to inform strategies to mitigate the impact on public health.

Pleiotropy facilitates parallel adaptation in sticklebacks.

Highly pleiotropic genes are predicted to be used less often during adaptation, as mutations in these loci are more likely to have negative fitness consequences. Following this logic, we tested whether pleiotropy impacts the probability that a locus will be used repeatedly in adaptation. We used two proxies to estimate pleiotropy: number of phenotypic traits affected by a given genomic region and gene connectivity. We first surveyed 16 independent stream‐lake and three independent benthic‐limnetic ecotype pairs of threespine stickleback to estimate genome‐wide patterns in parallel genomic differentiation. Our analysis revealed parallel divergence across the genome; 30%–37% of outlier regions were shared between at least two independent pairs in either the stream‐lake or benthic‐limnetic comparisons. We then tested whether parallel genomic regions are less pleiotropic than nonparallel regions. Counter to our a priori prediction, parallel genomic regions contained genes with significantly more pleiotropy; that is, influencing a greater number of traits and more highly connected. The increased pleiotropy of parallel regions could not be explained by other genomic factors, as there was no significant difference in mean gene count, mutation or recombination rates between parallel and nonparallel regions. Interestingly, although nonparallel regions contained genes that were less connected and influenced fewer mapped traits on average than parallel regions, they also tended to contain the genes that were predicted to be the most pleiotropic. Taken together, our findings are consistent with the idea that pleiotropy only becomes constraining at high levels and that low or intermediate levels of pleiotropy may be beneficial for adaptation.

Seeing is believing: a visualization toolbox to enhance selection efficiency in maize genome editing.

The emerging and promising biotechnology methodology of CRISPR/Cas9 gene-editing is revolutionizing crop improvement. However, the low-efficiency, time-consuming, and labor-intensive nature of positive or/and negative selections during or after transformation and subsequent identification of mutations are major challenges for its agricultural application, from upstream (high-throughput) mutant screening to downstream commercial production (He and Zhao, 2020). Although visual markers, and in particular fluorescent markers including green fluorescent protein (GFP) and red fluorescent protein (RFP), have been employed for the rapid visualization of transgenic material (Qi et al., 2020), the integration of cost-effective and non-invasive CRISPR-separation gene-editing tools is still in its infancy but remains critical for crop genetics and breeding (Callaway, 2018). Furthermore, special light sources are required to visualize fluorescent signals, which increases the cost and inconvenience of the application of fluorescence markers, especially in field conditions. We have developed a visualization toolbox, ViMeBox (VIsual Maize Editing toolBox), for the selection of positive transformants in maize (Zea mays). In the ViMeBox system, the vector expressing Cas9 includes a gene cassette containing a visible marker expressed from a tissue-specific promoter; Cas9-free kernels that are easy to separate by the visible marker are also undergoing gene editing. ViMeBox offers two advantages: 1) It enables enhanced expression of DsRED2, which makes seeds containing Cas9 visible to the naked eye in natural light, and does not affect genome editing efficiency or plant development. 2) It is effective for different seed tissues, for example, using embryo-specific promoters or promoters preferentially expressed in the embryo or aleurone. Furthermore, ViMeBox has potential applications in diverse additional scenarios.

Minimal Residual Disease Monitoring from Liquid Biopsy By Next Generation Sequencing in Follicular Lymphoma Patients

Minimal Residual Disease Monitoring from Liquid Biopsy By Next Generation Sequencing in Follicular Lymphoma Patients

Primary orthologs from local sequence context

BackgroundThe evolutionary history of genes serves as a cornerstone of contemporary biology. Most conserved sequences in mammalian genomes don’t code for proteins, yielding a need to infer evolutionary history of sequences irrespective of what kind of functional element they may encode. Thus, sequence-, as opposed to gene-, centric modes of inferring paths of sequence evolution are increasingly relevant. Customarily, homologous sequences derived from the same direct ancestor, whose ancestral position in two genomes is usually conserved, are termed “primary” (or “positional”) orthologs. Methods based solely on similarity don’t reliably distinguish primary orthologs from other homologs; for this, genomic context is often essential. Context-dependent identification of orthologs traditionally relies on genomic context over length scales characteristic of conserved gene order or whole-genome sequence alignment, and can be computationally intensive.ResultsWe demonstrate that short-range sequence context—as short as a single “maximal” match— distinguishes primary orthologs from other homologs across whole genomes. On mammalian whole genomes not preprocessed by repeat-masker, potential orthologs are extracted by genome intersection as “non-nested maximal matches:” maximal matches that are not nested into other maximal matches. It emerges that on both nucleotide and gene scales, non-nested maximal matches recapitulate primary or positional orthologs with high precision and high recall, while the corresponding computation consumes less than one thirtieth of the computation time required by commonly applied whole-genome alignment methods. In regions of genomes that would be masked by repeat-masker, non-nested maximal matches recover orthologs that are inaccessible to Lastz net alignment, for which repeat-masking is a prerequisite. mmRBHs, reciprocal best hits of genes containing non-nested maximal matches, yield novel putative orthologs, e.g. around 1000 pairs of genes for human-chimpanzee.ConclusionsWe describe an intersection-based method that requires neither repeat-masking nor alignment to infer evolutionary history of sequences based on short-range genomic sequence context. Ortholog identification based on non-nested maximal matches is parameter-free, and less computationally intensive than many alignment-based methods. It is especially suitable for genome-wide identification of orthologs, and may be applicable to unassembled genomes. We are agnostic as to the reasons for its effectiveness, which may reflect local variation of mean mutation rate.

Generation of semi-dwarf rice (Oryza sativa L.) lines by CRISPR/Cas9-directed mutagenesis of OsGA20ox2 and proteomic analysis of unveiled changes caused by mutations.

Plant height (PH) is one of the most important agronomic traits of rice, as it directly affects the yield potential and lodging resistance. Here, semi-dwarf mutant lines were developed through CRISPR/Cas9-based editing of OsGA20ox2 in an indica rice cultivar. Total 24 independent lines were obtained in T0 generation with the mean mutation rate of 73.5% including biallelic (29.16%), homozygous (47.91%) and heterozygous (16.66%) mutations, and 16 T-DNA-free lines (50%) were obtained in T1 generation without off-target effect in four most likely sites. Mutations resulted in a changed amino acid sequence of mutant plants and reduced gibberellins (GA) level and PH (22.2%), flag leaf length (FLL) and increased yield per plant (YPP) (6.0%), while there was no effect on other agronomic traits. Mutants restored their PH to normal by exogenous GA3 treatment. The expression of the OsGA20ox2 gene was significantly suppressed in mutant plants, while the expression level was not affected for other GA biosynthesis (OsGA2ox3 and OsGA3ox2) and signaling (D1, GIDI and SLR1) genes. The mutant lines showed decreased cell length and width, abnormal cell elongation, while increased cell numbers in the second internode sections at mature stage. Total 30 protein spots were exercised, and 24 proteins were identified, and results showed that OsGA20ox2 editing altered protein expression. Five proteins including, glyceraldehyde-3-phosphate dehydrogenase, putative ATP synthase, fructose-bisphosphate aldolase 1, S-adenosyl methionine synthetase 1 and gibberellin 20 oxidase 2, were downregulated in dwarf mutant lines which may affect the plant growth. Collectively, our results provide the insights into the role of OsGA20ox2 in PH and confirmed that CRISPR-Cas9 is a powerful tool to understand the gene functions.

Biocontrol Strains Differentially Shift the Genetic Structure of Indigenous Soil Populations of Aspergillus flavus.

Biocontrol using non-aflatoxigenic strains of Aspergillus flavus has the greatest potential to mitigate aflatoxin contamination in agricultural produce. However, factors that influence the efficacy of biocontrol agents in reducing aflatoxin accumulation under field conditions are not well-understood. Shifts in the genetic structure of indigenous soil populations of A. flavus following application of biocontrol products Afla-Guard and AF36 were investigated to determine how these changes can influence the efficacy of biocontrol strains in reducing aflatoxin contamination. Soil samples were collected from maize fields in Alabama, Georgia, and North Carolina in 2012 and 2013 to determine changes in the population genetic structure of A. flavus in the soil following application of the biocontrol strains. A. flavus L was the most dominant species of Aspergillus section Flavi with a frequency ranging from 61 to 100%, followed by Aspergillus parasiticus that had a frequency of <35%. The frequency of A. flavus L increased, while that of A. parasiticus decreased after application of biocontrol strains. A total of 112 multilocus haplotypes (MLHs) were inferred from 1,282 isolates of A. flavus L using multilocus sequence typing of the trpC, mfs, and AF17 loci. A. flavus individuals belonging to the Afla-Guard MLH in the IB lineage were the most dominant before and after application of biocontrol strains, while individuals of the AF36 MLH in the IC lineage were either recovered in very low frequencies or not recovered at harvest. There were no significant (P > 0.05) differences in the frequency of individuals with MAT1-1 and MAT1-2 for clone-corrected MLH data, an indication of a recombining population resulting from sexual reproduction. Population mean mutation rates were not different across temporal and spatial scales indicating that mutation alone is not a driving force in observed multilocus sequence diversity. Clustering based on principal component analysis identified two distinct evolutionary lineages (IB and IC) across all three states. Additionally, patristic distance analysis revealed phylogenetic incongruency among single locus phylogenies which suggests ongoing genetic exchange and recombination. Levels of aflatoxin accumulation were very low except in North Carolina in 2012, where aflatoxin levels were significantly (P < 0.05) lower in grain from treated compared to untreated plots. Phylogenetic analysis showed that Afla-Guard was more effective than AF36 in shifting the indigenous soil populations of A. flavus toward the non-toxigenic or low aflatoxin producing IB lineage. These results suggest that Afla-Guard, which matches the genetic and ecological structure of indigenous soil populations of A. flavus in Alabama, Georgia, and North Carolina, is likely to be more effective in reducing aflatoxin accumulation and will also persist longer in the soil than AF36 in the southeastern United States.

Mcr-1 facilitated selection of high-level colistin-resistant mutants in Escherichia coli

ObjectivesThe mcr-1 gene is the first reported plasmid-mediated colistin resistance gene. It has caused worldwide concern about the colistin resistance in Gram-negative bacteria. The aim of this research was to study the impact of mcr-1 on the selection of high-level colistin resistance (HLCR) mutations in Escherichia coli and Klebsiella pneumoniae. MethodsWe detected the HLCR mutation rates of Enterobacteriaceae strains (K. pneumoniae XH209, KP10, and E. coli Q3, ATCC 25922) and their transformants harbouring the mcr-1 gene. Further analysis of the HLCR mutants was conducted by sequencing, plasmid elimination experiment, and real-time quantitative PCR. ResultsFor XH209, mean mutation rate of XH209-pMCR was 1.7 (95% confidence interval (CI) 0.76–2.54) × 10−8, while XH209 and XH209-pCR2.1 showed mutation rates of 2.0 (95% CI, 1.32–2.67) × 10−8 and 2.3 (95% CI 1.47–3.13) × 10−8. For KP10 and its derived strains KP10-pCR2.1, KP10-pMCR, the mutation rates were 3.5 (95% CI 0.77–6.13) × 10−8, 4.8 (95% CI 0.69–8.94) × 10−8 and 4.2 (95% CI 0.95–7.54) × 10−8 respectively. The mutation rates of E. coli strains Q3-pMCR and ATCC25922-pMCR were 3.4 (95% CI 0.19–7.47) × 10−8 and 1.54 (95% CI 0.27–2.8) × 10−9, which were significantly higher than their corresponding non-mcr-1-carrying strains (p < 0.05). ConclusionsBeside the knowledge that mcr-1 mediates low-level colistin resistance, this gene also facilitates selection of HLCR mutants in E. coli, but does not affect K. pneumoniae.

Species-specific mutation rates for ampC derepression in Enterobacterales with chromosomally encoded inducible AmpC β-lactamase.

AmpC β-lactamases are encoded on the chromosomes of certain Enterobacterales and lead to clinical resistance to various β-lactams in case of high-level expression. In WT bacteria with inducible AmpC, the expression is low, but selection of stably ampC-derepressed mutants may occur during β-lactam therapy. Thus, for Enterobacter spp., Citrobacter freundii complex, Serratia spp. and Morganella morganii that test susceptible in vitro to oxyimino-cephalosporins, the EUCAST expert rules recommend suppressing susceptibility testing results for these agents or noting that their use in monotherapy should be discouraged, owing to the risk of selecting resistance. However, clinical observations suggest that emergence of resistance is not equally common in all species with inducible AmpC. To determine species-specific mutation rates, which are more accurate and reproducible than previously described mutant frequencies, for ampC derepression in Enterobacterales with inducible AmpC. Mutation rates were determined using a protocol based on Luria-Delbrück fluctuation analyses. Overall, 237 isolates were analysed. Mutation rates were high in Enterobacter cloacae complex, Enterobacter aerogenes, C. freundii complex and Hafnia alvei isolates, with a mean mutation rate of 3 × 10-8. In contrast, mean mutation rates were considerably lower in Providencia spp., Serratia spp. and especially M. morganii isolates. Furthermore, we observed species-specific variations in the resistance patterns of ampC-derepressed mutants. Our data might help to predict the risk of treatment failure with oxyimino-cephalosporins in infections by different Enterobacterales with inducible AmpC. Moreover, we make a proposal for optimization of the current EUCAST expert rule.

Mutations in LRP5,FZD4, TSPAN12, NDP, ZNF408, or KIF11 Genes Account for 38.7% of Chinese Patients With Familial Exudative Vitreoretinopathy.

Familial exudative vitreoretinopathy (FEVR) is a severe hereditary retinal disorder characterized by defects in retinal vascular development. To date, six genes have been reported to be responsible for this disease, including LRP5, FZD4, TSPAN12, NDP, ZNF408, and KIF11. The purpose of our study was to investigate the genetic defects in Chinese patients with FEVR through mutational analyses of 31 pedigrees. Clinical data and peripheral blood were collected from 31 pedigrees with FEVR. All coding sequences and intron/exon junctions were amplified and sequenced comprehensively, followed by cosegregation testing to verify suspected variants in the family members. Finally, we assessed clinical relevance of the identified mutations, according to the standards and guidelines from the American College of Medical Genetics and Genomics. Twelve index cases (12/31, 38.7%) were confirmed to harbor mutations in the known genes, including one previously reported mutation and 11 novel mutations. Among the detected mutations, LRP5 accounted for the largest proportion with a mean mutation rate of 16.1% (5/31, 16.1%), followed by NDP (3/31, 9.7%), FZD4 (2/31, 6.5%), TSPAN12 (1/31, 3.2%), and KIF11 (1/31, 3.2%). All the novel changes were predicted to be pathogenic by a series of bioinformatics analyses. We comprehensively screened six known disease-causing genes in 31 pedigrees with FEVR and achieved a clear picture of the mutation spectrum in Chinese patients with FEVR, which highlights the importance and utility of clinical genetic diagnosis.

Dynamic process of circulating tumour DNA (ctDNA) profiling as a predictor of efficacy of pemetrexed combined platinum chemotherapy in advanced lung adenocarcinoma.

e23048 Background: Pemetrexed combined platinum is recommended as first line chemotherapy regimen for non-squamous non-small cell lung cancer. However, the efficacy is variable for individuals. Methods: We conducted a prospective study with 52 consecutive patients enrolled who were histologically confirmed advanced or metastatic lung adenocarcinoma, of whom, 32 had their plasma samples collected both baseline and follow-up when efficacy evaluation. We used a next-generation sequencing to assess the dynamic change of ctDNA across 87 plasma samples. Results: 34 blood samples from 61.5% of patients demonstrated smoking status is an infavorable factor to drug efficacy ( p= 0.02, fisher’s exact test, two-sided). Simultaneously, we found positive correlation between decreased mutation burden and chemotherapy sensitivity (the mean mutation rates of pre chemotherapy, PD, PR, SD and SDA were 4.5, 6.3, 2.1, 1.6 and 2.4, respectively, p= 0.004, one way ANOVA test, two-sided).The mean mutation rates with T &gt; G substitution mutation of pre and post chemotherapy were 1.5 and 0.6 ( p= 0.014, Mann-Whitney U test, two-sided). 34.4% (11/32) individuals harbor those mutation pre chemotherapy, 6 out of them were characterized by DNA repair signatures, of which 83.3% (5/6) cases were positively related to platinum sensitivity. In addition, T &gt; G substitution was still detected from 5 patients at cycle 2, 60% (3/5) individuals were characterized by DNA repair signatures and 2 out of them had better platinum-based chemotherapy response.Neoplastic cells carrying a specific set of somatic mutations were sensitive to platinum treatment, including USP9X (pre vs post chemotherapy: 10.3% vs 0%), ZRSR2 (pre vs post chemotherapy: 6.9% vs 0%) and PIK3C2G (pre vs post chemotherapy: 10.3% vs 0%). Nonetheless, persistence of gene ROBO2 (pre vs post chemotherapy: 10.3% vs 4.6%) may be correlated with tumorigenesis. Conclusions: Dynamic monitoring of ctDNA mutation status may be contributed to advanced or metastatic lung adenocarcinoma patients stratification and prediction for pemetrexed combined platinum as first line chemotherapy regimen.

Using circulating tumor DNA analysis to depict genomic profiles and predict survival outcomes in patients with small-cell lung cancer.

8567 Background: Small-cell lung cancer (SCLC) accounts for approximately 15% of lung cancers. Most patients have extensive-stage disease with widespread metastases and poor survival. Understanding the molecular mutation profile of each SCLC patient would allow precision treatment and improved clinical outcome. However, tumor tissues from surgery are not available for most SCLC patients and biopsy specimens are often have limited quantities. Several studies have provided evidence of circulating tumor DNA (ctDNA) in detecting somatic variants of multiple solid tumors. This study evaluated utility of ctDNA to depict genomic profiles and predict survival outcomes in SCLC patients. Methods: 22 Plasma samples were obtained before initial treatment from 22 patients with SCLC enrolled between 2012 and 2016. Targeted-capture deep sequencing was performed to identify somatic variants in 465 cancer-related genes. Genomic mutation profiles were described and the clinical implications were further analyzed. Results: Tumor DNA can be detected in all 22 plasma samples collected from patients with SCLC. In total, 340 variants were identified, and the mean and median mutation rate were 6.3 and 6.6 per Mb. TP53 and RB1 are the most frequently mutated genes, detected in 90.9% (20/22) and 59.1% (13/22) patients, respectively. Further analysis showed that high ctDNA fraction in cell-free DNA (cfDNA) was associated with heavy tumor burden (R = 0.7, p = 0.0017). Moreover, patients with high ctDNA fractions (ctDNA fraction &gt; = 18.3%) had poor progression free survival (PFS) (HR, 17.2; p = 0.0019). The median PFS of patients with high versus low ctDNA fractions was 5.2 months (95% CI 4.6 to 5.8 months) versus 10.0 months (95% CI 9.3 to 10.7 months), respectively. Conclusions: In this study, ctDNA analysis offers a promising way to depict the molecular profile in patients with SCLC. Moreover, these findings highlight the potential clinical utility of ctDNA to predicate clinical outcome in SCLC.

Landscape genetics indicate recently increased habitat fragmentation in African forest-associated chafers.

Today, indigenous forests cover less than 0.6% of South Africa's land surface and are highly fragmented. Most forest relicts are very small and typically occur in fire-protected gorges along the eastern Great Escarpment. Yet, they hold a unique and valuable fauna with high endemism and ancient phylogenetic lineages, fostered by long-term climatic stability and complex microclimates. Despite numerous studies on southern African vegetation cover, the current state of knowledge about the natural extension of indigenous forests is rather fragmentary. We use an integrated approach of population-level phylogeography and climatic niche modeling of forest-associated chafer species to assess connectivity and extent of forest habitats since the last glacial maximum. Current and past species distribution models ascertained potential fluctuations of forest distribution and supported a much wider potential current extension of forests based on climatic data. Considerable genetic admixture of mitochondrial and nuclear DNA among many populations and an increase in mean population mutation rate in Extended Bayesian Skyline Plots of all species indicated more extended or better connected forests in the recent past (<5kya). Genetic isolation of certain populations, as revealed by population differentiation statistics (GST'), as well as landscape connectivity statistics and habitat succession scenarios suggests considerable loss of habitat connectivity. As major anthropogenic influence is likely, conservational actions need to be considered.

TERT promoter mutations and chromosome 8p loss are characteristic of nonalcoholic fatty liver disease-related hepatocellular carcinoma.

The number of patients with nonalcoholic fatty liver disease (NAFLD)-related hepatocellular carcinoma (HCC) is increasing. To understand the molecular features of the tumor phenotype, we aimed to clarify the overall landscape of genetic aberrations accumulated in NAFLD-related HCC. Of 247 HCC patients who underwent hepatectomy during 2010 to 2014 at a single center in Japan, 10 were diagnosed with NAFLD-HCC based on strict clinical and pathologic criteria. We analyzed the genetic aberrations of 11 NAFLD-HCC tumor samples from these 10 patients by whole-exome sequencing, targeted sequencing of the selected genes, and copy number variation studies. Whole-exome sequencing revealed a mean somatic mutation rate of 1.86 per megabase, and 12 genes were recurrently mutated in NAFLD-HCCs. Targeted sequencing of the 26 selected genes (12 recurrently mutated genes in whole-exome sequencing and 14 representative HCC-associated genes) revealed that TERT promoter mutations occurred in 9 of 11 HCCs (82%), followed by CTNNB1 (45%) and TP53 (36%) mutations. Array-based copy number variation studies identified recurrent gains at 1q and 8q, and recurrent losses at 1p, 4q, 6q, 8p, 13q, 16p, 17p, and 18q. Notably, chromosome 8p loss occurred in all of the NAFLD-HCC samples. The current study provided the characteristics of genetic aberrations in NAFLD-HCC and suggested that TERT promoter mutations and chromosome 8p loss mainly contribute to NAFLD-related liver carcinogenesis.

Abstract LB-323: The genomic landscape of non-muscle-invasive bladder cancer: implications for molecular classification and treatment

Abstract Non-muscle-invasive bladder cancers (NMIBC) and muscle-invasive bladder cancers (MIBC) show distinct molecular and clinical features and are considered to follow different pathogenesis pathways. MIBC commonly metastasise (&amp;gt;50%) and have poor prognosis whereas NMIBC, particularly low-stage low-grade tumors, rarely progress to invade muscle (&amp;lt;5%). Patients diagnosed with NMIBC frequently suffer disease recurrence, demanding long-term disease monitoring and repeated resection of recurrences. Large MIBC cohorts have been extensively interrogated on a genome-wide scale but relatively few NMIBC have been studied at this level. To address this we determined the mutational landscape of 82 non-muscle-invasive tumors (stage Ta grade 2) using whole-exome and targeted deep sequencing. Whole-exome sequencing identified an average of 124±79 synonymous and non-synonymous somatic mutations (single nucleotide substitutions and indels) per sample, giving mean and median somatic mutation rates of 2.41 and 1.64 per megabase, respectively. Overall, 47% of nucleotide substitutions were C&amp;gt;T transitions, followed by C&amp;gt;G transversions (24.8%). Similar to MIBC, APOBEC mutagenesis was the strongest source of mutation in NMIBC with 75% of samples showing up to 5-fold enrichment of the APOBEC mutation signature. Significantly mutated genes included genes implicated in epigenetic regulation and several genes that have not previously been reported as significantly mutated in bladder cancer. Comparison of mutation frequencies in NMIBC with those found in MIBC revealed both known differences (absence of TP53 mutations and high frequency of FGFR3, PIK3CA and STAG2 mutations in NMIBC) and novel findings including a higher frequency of mutations in chromatin-state regulators in NMIBC. Notably CDKN1A, RB1, ERCC2, ERBB3 and FBXW7, which are mutated in &amp;gt;10% of MIBC were not significantly mutated in TaG2 tumors, further delineating the distinct pathogenesis pathways of NMIBC and MIBC. Whole-genome expression array profiling and immunohistochemistry using a panel of markers were carried out to further examine the molecular features of NMIBC samples and define potentially clinically relevant subtypes. These data provide a detailed view of the genomic landscape of NMIBC that highlights chromatin modification as a key area for consideration in the development of potential future therapeutic approaches to the treatment of patients with non-muscle-invasive disease. Citation Format: Carolyn D. Hurst, Olivia Alder, Fiona M. Platt, Alastair Droop, Lucy F. Stead, Julie E. Burns, George J. Burghel, Sunjay Jain, Leszek J. Klimczak, Helen Lindsay, Jo-An Roulson, Claire F. Taylor, Helene Thygesen, Angus J. Cameron, Anne J. Ridley, Helene R. Mott, Dmitry A. Gordenin, Margaret A. Knowles. The genomic landscape of non-muscle-invasive bladder cancer: implications for molecular classification and treatment. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-323.

Microsatellite evolutionary rate and pattern in Schistocerca gregaria inferred from direct observation of germline mutations.

Unravelling variation among taxonomic orders regarding the rate of evolution in microsatellites is crucial for evolutionary biology and population genetics research. The mean mutation rate of microsatellites tends to be lower in arthropods than in vertebrates, but data are scarce and mostly concern accumulation of mutations in model species. Based on parent-offspring segregations and a hierarchical Bayesian model, the mean rate of mutation in the orthopteran insect Schistocerca gregaria was estimated at 2.1e(-4) per generation per untranscribed dinucleotide locus. This is close to vertebrate estimates and one order of magnitude higher than estimates from species of other arthropod orders, such as Drosophila melanogaster and Daphnia pulex. We also found evidence of a directional bias towards expansions even for long alleles and exceptionally large ranges of allele sizes. Finally, at transcribed microsatellites, the mean rate of mutation was half the rate found at untranscribed loci and the mutational model deviated from that usually considered, with most mutations involving multistep changes that avoid disrupting the reading frame. Our direct estimates of mutation rate were discussed in the light of peculiar biological and genomic features of S. gregaria, including specificities in mismatch repair and the dependence of its activity to allele length. Shedding new light on the mutational dynamics of grasshopper microsatellites is of critical importance for a number of research fields. As an illustration, we showed how our findings improve microsatellite application in population genetics, by obtaining a more precise estimation of S. gregaria effective population size from a published data set based on the same microsatellites.

Abstract LB-315: Comprehensive genomic characterization of cutaneous melanoma

Abstract Melanoma has emerged as the latest success story for both immuno- and genomics-guided targeted therapy following the advent of both monoclonal antibodies directed toward the inhibitory immune receptors CTLA-4, PD-1, and PD-L1, as well as BRAF inhibitors targeting mutant BRAF found in over 50% of melanoma patients. To characterize the genomic alterations in cutaneous melanoma, The Cancer Genome Atlas Project (TCGA) analyzed exome sequence, DNA structural variations (copy number and translocations), promoter methylation, mRNA, miRNA, and protein expression in primary and metastatic melanoma samples originating from non-glabrous skin in up to 336 samples. Interestingly, clustering analysis of RNA-seq data demonstrated 3 expression module subgroups of melanomas, categorized by elevated lymphocytic, keratin, and melanocyte differentiation markers. Consistent with previous findings, the high lymphocytic expression subgroup was found to possess a better overall survival. Mutation analysis from exome sequencing identified a broad spectrum of samples possessing a signature of UV mutagenesis dominated by C &amp;gt; T transitions at dipyrimidines. We observed a mean somatic mutation rate of 17 mutations per megabase (Mb), almost doubling the highest mutation rate reported previously for a cancer type analyzed by TCGA. The InVEx algorithm identified 13 significantly mutated genes (P. Bonferroni &amp;lt;0.05, Q &amp;lt;0.1), which included: known melanoma oncogenes and tumor suppressors (BRAF, NRAS, CDKN2A, TP53, and PTEN); genes previously implicated in melanoma, but found here for the first time to be significantly mutated (including the RAS-GAP NF1, IDH1 and RB1); recently implicated melanoma genes possessing either characteristic hotspot or loss of function mutations (RAC1, MAP2K1, PPP6C, and ARID2); and finally, a gene not previously implicated in melanoma, the RNA helicase DDX3X. Over 80% of samples possessed at least one mutation in the significantly mutated genes BRAF, NRAS, or NF1 involved in the MAPK pathway. Importantly, hotspot mutations in BRAF were found to be anti-correlated with both NRAS (Fisher's exact test p-value = 6.461e-16) and NF1 mutations (p-value 1.888e-06). Given this finding, we propose melanoma can be categorized into four genetic subgroups distinguished by MAPK driver mutations: BRAF, NRAS, NF1, and triple-wild type melanomas. Integrative analysis with additional platforms revealed enrichment of copy number gains in KIT, PDGFRA, KDR (VEGFR2), CCND1,CDK4, MDM2, and TERT in the triple wild-type melanomas. Integration of reverse phase protein array data also revealed differentially downstream signaling of the MAPK pathway in these four genetic subgroups. In summary, insights provided by this analysis have shed light on the different genetic mechanisms leading to cutaneous melanoma. Citation Format: Ian R. Watson, Chang-Jiun Wu, Jeffrey E. Gershenwald, Lynda Chin, On Behalf of the Melanoma Analysis Working Group and The Cancer Genome Analysis Research Network. Comprehensive genomic characterization of cutaneous melanoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-315. doi:10.1158/1538-7445.AM2014-LB-315