LTMG: a novel statistical modeling of transcriptional expression states in single-cell RNA-Seq data

A key challenge in modeling single-cell RNA-seq data is to capture the diversity of gene expression states regulated by different transcriptional regulatory inputs across individual cells, which is further complicated by largely observed zero and low expressions. We developed a left truncated mixture Gaussian (LTMG) model, from the kinetic relationships of the transcriptional regulatory inputs, mRNA metabolism and abundance in single cells. LTMG infers the expression multi-modalities across single cells, meanwhile, the dropouts and low expressions are treated as left truncated. We demonstrated that LTMG has significantly better goodness of fitting on an extensive number of scRNA-seq data, comparing to three other state-of-the-art models. Our biological assumption of the low non-zero expressions, rationality of the multimodality setting, and the capability of LTMG in extracting expression states specific to cell types or functions, are validated on independent experimental data sets. A differential gene expression test and a co-regulation module identification method are further developed. We experimentally validated that our differential expression test has higher sensitivity and specificity, compared with other five popular methods. The co-regulation analysis is capable of retrieving gene co-regulation modules corresponding to perturbed transcriptional regulations. A user-friendly R package with all the analysis power is available at https://github.com/zy26/LTMGSCA

Retroviral intasomes search for a target DNA by 1D diffusion which rarely results in integration

Retroviruses must integrate their linear viral cDNA into the host genome for a productive infection. Integration is catalysed by the retrovirus-encoded integrase (IN), which forms a tetramer or octamer complex with the viral cDNA long terminal repeat (LTR) ends termed an intasome. IN removes two 3'-nucleotides from both LTR ends and catalyses strand transfer of the recessed 3'-hydroxyls into the target DNA separated by 4-6 bp. Host DNA repair restores the resulting 5'-Flap and single-stranded DNA (ssDNA) gap. Here we have used multiple single molecule imaging tools to determine that the prototype foamy virus (PFV) retroviral intasome searches for an integration site by one-dimensional (1D) rotation-coupled diffusion along DNA. Once a target site is identified, the time between PFV strand transfer events is 470 ms. The majority of PFV intasome search events were non-productive. These observations identify new dynamic IN functions and suggest that target site-selection limits retroviral integration.open1196sciescopu

Ovulation-stimulation drugs and cancer risks: a long-term follow-up of a British cohort

To assess long-term health effects of ovarian-stimulation drugs we followed-up for over 20 years a British cohort of 7355 women with ovulatory disorders, 43% of whom were prescribed ovarian-stimulation drugs, and identified a total of 274 deaths and 367 incident cancers. Relative to the general population, the cohort experienced lower mortality from most causes, including from all neoplasms combined, and lower incidence of cervical cancer, but higher incidence of cancers of the breast (relative risk: 1.13; 95% CI 0.97, 1.30) and corpus uteri (2.02; 1.37, 2.87). There were, however, no significant differences in the risk of cancers of the breast, corpus uteri, ovary, or of any other site, between women who had been prescribed ovarian-stimulation drugs and those who had not. Further analyses by type of drug and dose revealed a dose–response gradient in the risk of cancer of the corpus uteri (P for linear trend=0.03), with women given ⩾2250 mg of clomiphene having a 2.6-fold (2.62; 0.94, 6.82) increase in risk relative to those who were not treated. These findings do not support strong associations between ovulation-stimulation drugs and cancer risks, but they indicate the need for continued monitoring to establish whether risks are elevated in certain subgroups of users

Cancer risk in MLH1, MSH2 and MSH6 mutation carriers; different risk profiles may influence clinical management

Background: Lynch syndrome (LS) is associated with a high risk for colorectal cancer (CRC) and extracolonic malignancies, such as endometrial carcinoma (EC). The risk is dependent of the affected mismatch repair gene. The aim of the present study was to calculate the cumulative risk of LS related cancers in proven MLH1, MSH2 and MSH6 mutation carriers.Methods: The studypopulation consisted out of 67 proven LS families. Clinical information including mutation status and tumour diagnosis was collected. Cumulative risks were calculated and compared using Kaplan Meier survival analysis.Results: MSH6 mutation carriers, both males and females had the lowest risk for developing CRC at age 70 years, 54% and 30% respectively and the age of onset was delayed by 3-5 years in males. With respect to endometrial carcinoma, female MSH6 mutation carriers had the highest risk at age 70 years (61%) compared to MLH1 (25%) and MSH2 (49%). Also, the age of EC onset was delayed by 5-10 years in comparison with MLH1 and MSH2.Conclusions: Although the cumulative lifetime risk of LS related cancer is similar, MLH1, MSH2 and MSH6 mutations seem to cause distinguishable cancer risk profiles. Female MSH6 mutation carriers have a lower CRC risk and a higher risk for developing endometrial carcinoma. As a consequence, surveillance colonoscopy starting at age 30 years instead of 20-25 years is more suitable. Also, prophylactic hysterectomy may be more indicated in female MSH6 mutation carriers compared to MLH1 and MSH2 mutation carriers

The DNA mismatch repair gene hMSH2 is a potent coactivator of oestrogen receptor α

The DNA mismatch repair gene is a key regulator in the elimination of base–base mismatches and insertion/deletion loops (IDLs). Human MutS homologue 2 (hMSH2), originally identified as a human homologue of the bacterial MutS, is a tumour suppressor gene frequently mutated in hereditary nonpolyposis colorectal cancer. Hereditary nonpolyposis colorectal cancer is characterised by the early onset of colorectal cancer and the development of extracolonic cancers such as endometrial, ovarian, and urological cancers. Oestrogen receptor (ER) α and β are members of a nuclear receptor (NR) superfamily. Ligand-dependent transcription of ER is regulated by the p160 steroid receptor coactivator family, the thyroid hormone receptor-associated proteins/the vitamin D receptor-interacting proteins (TRAP/DRIP) mediator complex, and the TATA box-binding protein (TBP)-free TBP associated factor complex (TFTC) type histone acetyltransferase complex. Here, we report the interaction between ER α/β and hMSH2. Immunoprecipitation and glutathione-S-transferase pulldown assay revealed that ER α and hMSH2 interacted in a ligand-dependent manner, whereas ER β and hMSH2 interacted in a ligand-independent manner. Oestrogen receptor α/β bound to hMSH2 through the hMSH3/hMSH6 interaction domain of hMSH2. In a transient expression assay, hMSH2 potentiated the transactivation function of liganded ER α, but not that of ER β. These results suggest that hMSH2 may play an important role as a putative coactivator in ER α dependent gene expression

Development and evaluation of human AP endonuclease inhibitors in melanoma and glioma cell lines

AimsModulation of DNA base excision repair (BER) has the potential to enhance response to chemotherapy and improve outcomes in tumours such as melanoma and glioma. APE1, a critical protein in BER that processes potentially cytotoxic abasic sites (AP sites), is a promising new target in cancer. In the current study, we aimed to develop small molecule inhibitors of APE1 for cancer therapy.MethodsAn industry-standard high throughput virtual screening strategy was adopted. The Sybyl8.0 (Tripos, St Louis, MO, USA) molecular modelling software suite was used to build inhibitor templates. Similarity searching strategies were then applied using ROCS 2.3 (Open Eye Scientific, Santa Fe, NM, USA) to extract pharmacophorically related subsets of compounds from a chemically diverse database of 2.6 million compounds. The compounds in these subsets were subjected to docking against the active site of the APE1 model, using the genetic algorithm-based programme GOLD2.7 (CCDC, Cambridge, UK). Predicted ligand poses were ranked on the basis of several scoring functions. The top virtual hits with promising pharmaceutical properties underwent detailed in vitro analyses using fluorescence-based APE1 cleavage assays and counter screened using endonuclease IV cleavage assays, fluorescence quenching assays and radiolabelled oligonucleotide assays. Biochemical APE1 inhibitors were then subjected to detailed cytotoxicity analyses.ResultsSeveral specific APE1 inhibitors were isolated by this approach. The IC(50) for APE1 inhibition ranged between 30 nM and 50 μM. We demonstrated that APE1 inhibitors lead to accumulation of AP sites in genomic DNA and potentiated the cytotoxicity of alkylating agents in melanoma and glioma cell lines.ConclusionsOur study provides evidence that APE1 is an emerging drug target and could have therapeutic application in patients with melanoma and glioma

Evolution of Mutational Robustness in the Yeast Genome: A Link to Essential Genes and Meiotic Recombination Hotspots

Deleterious mutations inevitably emerge in any evolutionary process and are speculated to decisively influence the structure of the genome. Meiosis, which is thought to play a major role in handling mutations on the population level, recombines chromosomes via non-randomly distributed hot spots for meiotic recombination. In many genomes, various types of genetic elements are distributed in patterns that are currently not well understood. In particular, important (essential) genes are arranged in clusters, which often cannot be explained by a functional relationship of the involved genes. Here we show by computer simulation that essential gene (EG) clustering provides a fitness benefit in handling deleterious mutations in sexual populations with variable levels of inbreeding and outbreeding. We find that recessive lethal mutations enforce a selective pressure towards clustered genome architectures. Our simulations correctly predict (i) the evolution of non-random distributions of meiotic crossovers, (ii) the genome-wide anti-correlation of meiotic crossovers and EG clustering, (iii) the evolution of EG enrichment in pericentromeric regions and (iv) the associated absence of meiotic crossovers (cold centromeres). Our results furthermore predict optimal crossover rates for yeast chromosomes, which match the experimentally determined rates. Using a Saccharomyces cerevisiae conditional mutator strain, we show that haploid lethal phenotypes result predominantly from mutation of single loci and generally do not impair mating, which leads to an accumulation of mutational load following meiosis and mating. We hypothesize that purging of deleterious mutations in essential genes constitutes an important factor driving meiotic crossover. Therefore, the increased robustness of populations to deleterious mutations, which arises from clustered genome architectures, may provide a significant selective force shaping crossover distribution. Our analysis reveals a new aspect of the evolution of genome architectures that complements insights about molecular constraints, such as the interference of pericentromeric crossovers with chromosome segregation

Methods for comprehensive chromosome screening of oocytes and embryos: capabilities, limitations, and evidence of validity

Preimplantation aneuploidy screening of cleavage stage embryos using fluorescence in situ hybridization (FISH) may no longer be considered the standard of care in reproductive medicine. Over the last few years, there has been considerable development of novel technologies for comprehensive chromosome screening (CCS) of the human genome. Among the notable methodologies that have been incorporated are whole genome amplification, metaphase and array based comparative genomic hybridization, single nucleotide polymorphism microarrays, and quantitative real-time PCR. As these methods become more integral to treating patients with infertility, it is critical that clinicians and scientists obtain a better understanding of their capabilities and limitations. This article will focus on reviewing these technologies and the evidence of their validity