Secondary structure of the human mitochondrial genome affects formation of deletions.

BACKGROUND: Aging in postmitotic tissues is associated with clonal expansion of somatic mitochondrial deletions, the origin of which is not well understood. Such deletions are often flanked by direct nucleotide repeats, but this alone does not fully explain their distribution. Here, we hypothesized that the close proximity of direct repeats on single-stranded mitochondrial DNA (mtDNA) might play a role in the formation of deletions. RESULTS: By analyzing human mtDNA deletions in the major arc of mtDNA, which is single-stranded during replication and is characterized by a high number of deletions, we found a non-uniform distribution with a "hot spot" where one deletion breakpoint occurred within the region of 6-9 kb and another within 13-16 kb of the mtDNA. This distribution was not explained by the presence of direct repeats, suggesting that other factors, such as the spatial proximity of these two regions, can be the cause. In silico analyses revealed that the single-stranded major arc may be organized as a large-scale hairpin-like loop with a center close to 11 kb and contacting regions between 6-9 kb and 13-16 kb, which would explain the high deletion activity in this contact zone. The direct repeats located within the contact zone, such as the well-known common repeat with a first arm at 8470-8482 bp (base pair) and a second arm at 13,447-13,459 bp, are three times more likely to cause deletions compared to direct repeats located outside of the contact zone. A comparison of age- and disease-associated deletions demonstrated that the contact zone plays a crucial role in explaining the age-associated deletions, emphasizing its importance in the rate of healthy aging. CONCLUSIONS: Overall, we provide topological insights into the mechanism of age-associated deletion formation in human mtDNA, which could be used to predict somatic deletion burden and maximum lifespan in different human haplogroups and mammalian species.

A single-cell transcriptome atlas of the adult human retina.

The retina is a specialized neural tissue that senses light and initiates image processing. Although the functional organization of specific retina cells has been well studied, the molecular profile of many cell types remains unclear in humans. To comprehensively profile the human retina, we performed single-cell RNA sequencing on 20,009 cells from three donors and compiled a reference transcriptome atlas. Using unsupervised clustering analysis, we identified 18 transcriptionally distinct cell populations representing all known neural retinal cells: rod photoreceptors, cone photoreceptors, Müller glia, bipolar cells, amacrine cells, retinal ganglion cells, horizontal cells, astrocytes, and microglia. Our data captured molecular profiles for healthy and putative early degenerating rod photoreceptors, and revealed the loss of MALAT1 expression with longer post-mortem time, which potentially suggested a novel role of MALAT1 in rod photoreceptor degeneration. We have demonstrated the use of this retina transcriptome atlas to benchmark pluripotent stem cell-derived cone photoreceptors and an adult Müller glia cell line. This work provides an important reference with unprecedented insights into the transcriptional landscape of human retinal cells, which is fundamental to understanding retinal biology and disease.

Slightly deleterious genomic variants and transcriptome perturbations in Down syndrome embryonic selection.

The majority of aneuploid fetuses are spontaneously miscarried. Nevertheless, some aneuploid individuals survive despite the strong genetic insult. Here, we investigate if the survival probability of aneuploid fetuses is affected by the genome-wide burden of slightly deleterious variants. We analyzed two cohorts of live-born Down syndrome individuals (388 genotyped samples and 16 fibroblast transcriptomes) and observed a deficit of slightly deleterious variants on Chromosome 21 and decreased transcriptome-wide variation in the expression level of highly constrained genes. We interpret these results as signatures of embryonic selection, and propose a genetic handicap model whereby an individual bearing an extremely severe deleterious variant (such as aneuploidy) could escape embryonic lethality if the genome-wide burden of slightly deleterious variants is sufficiently low. This approach can be used to study the composition and effect of the numerous slightly deleterious variants in humans and model organisms.

Single-cell RNA-seq of human induced pluripotent stem cells reveals cellular heterogeneity and cell state transitions between subpopulations.

Heterogeneity of cell states represented in pluripotent cultures has not been described at the transcriptional level. Since gene expression is highly heterogeneous between cells, single-cell RNA sequencing can be used to identify how individual pluripotent cells function. Here, we present results from the analysis of single-cell RNA sequencing data from 18,787 individual WTC-CRISPRi human induced pluripotent stem cells. We developed an unsupervised clustering method and, through this, identified four subpopulations distinguishable on the basis of their pluripotent state, including a core pluripotent population (48.3%), proliferative (47.8%), early primed for differentiation (2.8%), and late primed for differentiation (1.1%). For each subpopulation, we were able to identify the genes and pathways that define differences in pluripotent cell states. Our method identified four transcriptionally distinct predictor gene sets composed of 165 unique genes that denote the specific pluripotency states; using these sets, we developed a multigenic machine learning prediction method to accurately classify single cells into each of the subpopulations. Compared against a set of established pluripotency markers, our method increases prediction accuracy by 10%, specificity by 20%, and explains a substantially larger proportion of deviance (up to threefold) from the prediction model. Finally, we developed an innovative method to predict cells transitioning between subpopulations and support our conclusions with results from two orthogonal pseudotime trajectory methods.

Tissue specific regulation of transcription in endometrium and association with disease.

STUDY QUESTION: Are genetic effects on endometrial gene expression tissue specific and/or associated with reproductive traits and diseases? SUMMARY ANSWER: Analyses of RNA-sequence data and individual genotype data from the endometrium identified novel and disease associated, genetic mechanisms regulating gene expression in the endometrium and showed evidence that these mechanisms are shared across biologically similar tissues. WHAT IS KNOWN ALREADY: The endometrium is a complex tissue vital for female reproduction and is a hypothesized source of cells initiating endometriosis. Understanding genetic regulation specific to, and shared between, tissue types can aid the identification of genes involved in complex genetic diseases. STUDY DESIGN, SIZE, DURATION: RNA-sequence and genotype data from 206 individuals was analysed and results were compared with large publicly available datasets. PARTICIPANTS/MATERIALS, SETTING, METHODS: RNA-sequencing and genotype data from 206 endometrial samples was used to identify the influence of genetic variants on gene expression, via expression quantitative trait loci (eQTL) analysis and to compare these endometrial eQTLs with those in other tissues. To investigate the association between endometrial gene expression regulation and reproductive traits and diseases, we conducted a tissue enrichment analysis, transcriptome-wide association study (TWAS) and summary data-based Mendelian randomisation (SMR) analyses. Transcriptomic data was used to test differential gene expression between women with and without endometriosis. MAIN RESULTS AND THE ROLE OF CHANCE: A tissue enrichment analysis with endometriosis genome-wide association study summary statistics showed that genes surrounding endometriosis risk loci were significantly enriched in reproductive tissues. A total of 444 sentinel cis-eQTLs (P < 2.57 × 10-9) and 30 trans-eQTLs (P < 4.65 × 10-13) were detected, including 327 novel cis-eQTLs in endometrium. A large proportion (85%) of endometrial eQTLs are present in other tissues. Genetic effects on endometrial gene expression were highly correlated with the genetic effects on reproductive (e.g. uterus, ovary) and digestive tissues (e.g. salivary gland, stomach), supporting a shared genetic regulation of gene expression in biologically similar tissues. The TWAS analysis indicated that gene expression at 39 loci is associated with endometriosis, including five known endometriosis risk loci. SMR analyses identified potential target genes pleiotropically or causally associated with reproductive traits and diseases including endometriosis. However, without taking account of genetic variants, a direct comparison between women with and without endometriosis showed no significant difference in endometrial gene expression. LARGE SCALE DATA: The eQTL dataset generated in this study is available at http://reproductivegenomics.com.au/shiny/endo_eqtl_rna/. Additional datasets supporting the conclusions of this article are included within the article and the supplementary information files, or are available on reasonable request. LIMITATIONS, REASONS FOR CAUTION: Data are derived from fresh tissue samples and expression levels are an average of expression from different cell types within the endometrium. Subtle cell-specifc expression changes may not be detected and differences in cell composition between samples and across the menstrual cycle will contribute to sample variability. Power to detect tissue specific eQTLs and differences between women with and without endometriosis was limited by the sample size in this study. The statistical approaches used in this study identify the likely gene targets for specific genetic risk factors, but not the functional mechanism by which changes in gene expression may influence disease risk. WIDER IMPLICATIONS OF THE FINDINGS: Our results identify novel genetic variants that regulate gene expression in endometrium and the majority of these are shared across tissues. This allows analysis with large publicly available datasets to identify targets for female reproductive traits and diseases. Much larger studies will be required to identify genetic regulation of gene expression that will be specific to endometrium. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the National Health and Medical Research Council (NHMRC) under project grants GNT1026033, GNT1049472, GNT1046880, GNT1050208, GNT1105321, GNT1083405 and GNT1107258. G.W.M is supported by a NHMRC Fellowship (GNT1078399). J.Y is supported by an ARC Fellowship (FT180100186). There are no competing interests.

Transcriptomics and single-cell RNA-sequencing.

The past four decades have yielded advances in molecular biology allowing detailed characterization of the cellular genome and the transcriptome: the complete set of RNA species transcribed by a cell or tissue. Through transcriptomics and next-generation sequencing, we can now attain an unprecedented level of detail in understanding cellular phenotypes through examining the genes expressed in specific physiological and pathological states. In this review, we provide an overview of transcriptomics and RNA-sequencing in the analysis of whole tissue and single cells. We describe the techniques and pitfalls involved in the isolation and sequencing of single cells, and what additional benefits this application can provide. Finally, we look to how these technologies are being applied in pulmonary research, and how they may translate in the near future into clinical practice.

CFTR mRNA expression is regulated by an upstream open reading frame and RNA secondary structure in its 5' untranslated region.

Post-transcriptional regulation of gene expression through 5' untranslated region (5'UTR)-encoded cis-acting elements is an important mechanism for the control of protein expression levels. Through controlling specific aspects of translation initiation, expression can be tightly regulated while remaining responsive to cellular requirements. With respect to cystic fibrosis (CF), the overexpression of cystic fibrosis transmembrane conductance regulator (CFTR) protein trafficking mutants, such as delta-F508, is of great biological and clinical interest. By understanding the post-transcriptional mechanisms that regulate CFTR expression, new procedures can be developed to enhance CFTR expression in homozygous delta-F508 CF patients. We have identified the key elements of a complex negative regulatory mechanism that is encoded within the human CFTR 5'UTR and show how these elements act in combination to restrict CFTR gene expression to a consistently low level in a transcript-specific manner. This study shows, for the first time, that endogenous human CFTR expression is post-transcriptionally regulated through a 5'UTR-mediated mechanism. We show that the very low levels of endogenous CFTR expression, compared with other low expression genes, are maintained through the co-operative inhibitory effects of an upstream open reading frame and a thermodynamically stable RNA secondary structure.

Gene age predicts the strength of purifying selection acting on gene expression variation in humans.

Gene expression levels can be subject to selection. We hypothesized that the age of gene origin is associated with expression constraints, given that it affects the level of gene integration into the functional cellular environment. By studying the genetic variation affecting gene expression levels (cis expression quantitative trait loci [cis-eQTLs]) and protein levels (cis protein QTLs [cis-pQTLs]), we determined that young, primate-specific genes are enriched in cis-eQTLs and cis-pQTLs. Compared to cis-eQTLs of old genes originating before the zebrafish divergence, cis-eQTLs of young genes have a higher effect size, are located closer to the transcription start site, are more significant, and tend to influence genes in multiple tissues and populations. These results suggest that the expression constraint of each gene increases throughout its lifespan. We also detected a positive correlation between expression constraints (approximated by cis-eQTL properties) and coding constraints (approximated by Ka/Ks) and observed that this correlation might be driven by gene age. To uncover factors associated with the increase in gene-age-related expression constraints, we demonstrated that gene connectivity, gene involvement in complex regulatory networks, gene haploinsufficiency, and the strength of posttranscriptional regulation increase with gene age. We also observed an increase in heritability of gene expression levels with age, implying a reduction of the environmental component. In summary, we show that gene age shapes key gene properties during evolution and is therefore an important component of genome function.

The genetic regulation of transcription in human endometrial tissue.

Study question: Do genetic effects regulate gene expression in human endometrium? Summary answer: This study demonstrated strong genetic effects on endometrial gene expression and some evidence for genetic regulation of gene expression in a menstrual cycle stage-specific manner. What is known already: Genetic effects on expression levels for many genes are tissue specific. Endometrial gene expression varies across menstrual cycle stages and between individuals, but there are limited data on genetic control of expression in endometrium. Study design, size, duration: We analysed genome-wide genotype and gene expression data to map cis expression quantitative trait loci (eQTL) in endometrium. Participants/materials, setting, methods: We recruited 123 women of European ancestry. DNA samples from blood were genotyped on Illumina HumanCoreExome chips. Total RNA was extracted from endometrial tissues. Whole-transcriptome profiles were characterized using Illumina Human HT-12 v4.0 Expression Beadchips. We performed eQTL mapping with ~8 000 000 genotyped and imputed single nucleotide polymorphisms (SNPs) and 12 329 genes. Main results and the role of chance: We identified a total of 18 595 cis SNP-probe associations at a study-wide level of significance (P < 1 × 10-7), which correspond to independent eQTLs for 198 unique genes. The eQTLs with the largest effect in endometrial tissue were rs4902335 for CHURC1 (P = 1.05 × 10-32) and rs147253019 for ZP3 (P = 8.22 × 10-30). We further performed a context-specific eQTL analysis to investigate if genetic effects on gene expression regulation act in a menstrual cycle-specific manner. Interestingly, five cis-eQTLs were identified with a significant stage-by-genotype interaction. The strongest stage interaction was the eQTL for C10ORF33 (PYROXD2) with SNP rs2296438 (P = 2.0 × 10-4), where we observe a 2-fold difference in the average expression levels of heterozygous samples depending on the stage of the menstrual cycle. Large scale data: The summary eQTL results are publicly available to browse or download. Limitations, reasons for caution: A limitation of the present study was the relatively modest sample size. It was not powered to identify trans-eQTLs and larger sample sizes will also be needed to provide better power to detect cis-eQTLs and cycle stage-specific effects, given the substantial changes in expression across the menstrual cycle for many genes. Wider implications of the findings: Identification of endometrial eQTLs provides a platform for better understanding genetic effects on endometriosis risk and other endometrial-related pathologies. Study funding/competing interest(s): Funding for this work was provided by NHMRC Project Grants GNT1026033, GNT1049472, GNT1046880, GNT1050208, GNT1105321 and APP1083405. There are no competing interests.

The serum resistome of a globally disseminated multidrug resistant uropathogenic Escherichia coli clone.

Escherichia coli ST131 is a globally disseminated, multidrug resistant clone responsible for a high proportion of urinary tract and bloodstream infections. The rapid emergence and successful spread of E. coli ST131 is strongly associated with antibiotic resistance; however, this phenotype alone is unlikely to explain its dominance amongst multidrug resistant uropathogens circulating worldwide in hospitals and the community. Thus, a greater understanding of the molecular mechanisms that underpin the fitness of E. coli ST131 is required. In this study, we employed hyper-saturated transposon mutagenesis in combination with multiplexed transposon directed insertion-site sequencing to define the essential genes required for in vitro growth and the serum resistome (i.e. genes required for resistance to human serum) of E. coli EC958, a representative of the predominant E. coli ST131 clonal lineage. We identified 315 essential genes in E. coli EC958, 231 (73%) of which were also essential in E. coli K-12. The serum resistome comprised 56 genes, the majority of which encode membrane proteins or factors involved in lipopolysaccharide (LPS) biosynthesis. Targeted mutagenesis confirmed a role in serum resistance for 46 (82%) of these genes. The murein lipoprotein Lpp, along with two lipid A-core biosynthesis enzymes WaaP and WaaG, were most strongly associated with serum resistance. While LPS was the main resistance mechanism defined for E. coli EC958 in serum, the enterobacterial common antigen and colanic acid also impacted on this phenotype. Our analysis also identified a novel function for two genes, hyxA and hyxR, as minor regulators of O-antigen chain length. This study offers novel insight into the genetic make-up of E. coli ST131, and provides a framework for future research on E. coli and other Gram-negative pathogens to define their essential gene repertoire and to dissect the molecular mechanisms that enable them to survive in the bloodstream and cause disease.