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Discovering functional DNA elements using population genomic information: a proof of concept using human mtDNA.

ABSTRACT: Identifying the complete set of functional elements within the human genome would be a windfall for multiple areas of biological research including medicine, molecular biology, and evolution. Complete knowledge of function would aid in the prioritization of loci when searching for the genetic bases of disease or adaptive phenotypes. Because mutations that disrupt function are disfavored by natural selection, purifying selection leaves a detectable signature within functional elements; accordingly, this signal has been exploited for over a decade through the use of genomic comparisons of distantly related species. While this is so, the functional complement of the genome changes extensively across time and between lineages; therefore, evidence of the current action of purifying selection in humans is essential. Because the removal of deleterious mutations by natural selection also reduces within-species genetic diversity within functional loci, dense population genetic data have the potential to reveal genomic elements that are currently functional. Here, we assess the potential of this approach by examining an ultradeep sample of human mitochondrial genomes (n = 16,411). We show that the high density of polymorphism in this data set precisely delineates regions experiencing purifying selection. Furthermore, we show that the number of segregating alleles at a site is strongly correlated with its divergence across species after accounting for known mutational biases in human mitochondrial DNA (ρ = 0.51; P < 2.2 × 10(-16)). These two measures track one another at a remarkably fine scale across many loci-a correlation that is purely the result of natural selection. Our results demonstrate that genetic variation has the potential to reveal with surprising precision which regions in the genome are currently performing important functions and likely to have deleterious fitness effects when mutated. As more complete human genomes are sequenced, similar power to reveal purifying selection may be achievable in the human nuclear genome.

SUBMITTER: Schrider DR

PROVIDER: S-EPMC4122919 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:OBJECTIVE:We have previously found that acute psychological stress may affect mitochondria and trigger an increase in serum mitochondrial DNA, known as circulating cell-free mtDNA (ccf-mtDNA). Similar to other stress reactivity measures, there are substantial unexplained inter-individual differences in the magnitude of ccf-mtDNA reactivity, as well as within-person differences across different occasions of testing. Here, we sought to identify psychological and physiological predictors of ccf-mtDNA reactivity using machine learning-based multivariate classifiers. METHOD:We used data from serum ccf-mtDNA concentration measured pre- and post-stress in 46 healthy midlife adults tested on two separate occasions. To identify variables predicting the magnitude of ccf-mtDNA reactivity, two multivariate classification models, partial least-squares discriminant analysis (PLS-DA) and random forest (RF), were trained to discriminate between high and low ccf-mtDNA responders. Potential predictors used in the models included state variables such as physiological measures and affective states, and trait variables such as sex and personality measures. Variables identified across both models were considered to be predictors of ccf-mtDNA reactivity and selected for downstream analyses. RESULTS:Identified predictors were significantly enriched for state over trait measures (X2?=?7.03; p?=?0.008) and for physiological over psychological measures (X2?=?4.36; p?=?0.04). High responders were more likely to be male (X2?=?26.95; p?<?0.001) and differed from low-responders on baseline cardiovascular and autonomic measures, and on stress-induced reduction in fatigue (Cohen's d?=?0.38-0.73). These group-level findings also accurately accounted for within-person differences in 90% of cases. CONCLUSION:These results suggest that acute cardiovascular and psychological indices, rather than stable individual traits, predict stress-induced ccf-mtDNA reactivity. This work provides a proof-of-concept that machine learning approaches can be used to explore determinants of inter-individual and within-person differences in stress psychophysiology.

Project description:BackgroundGenome-wide analysis of sequence divergence among species offers profound insights into the evolutionary processes that shape lineages. When full-genome sequencing is not feasible for a broad comparative study, we propose the use of array-based comparative genomic hybridization (aCGH) in order to identify orthologous genes with high sequence divergence. Here we discuss experimental design, statistical power, success rate, sources of variation and potential confounding factors. We used a spotted PCR product microarray platform from Drosophila melanogaster to assess sequence divergence on a gene-by-gene basis in three fully sequenced heterologous species (D. sechellia, D. simulans, and D. yakuba). Because complete genome assemblies are available for these species this study presents a powerful test for the use of aCGH as a tool to measure sequence divergence.ResultsWe found a consistent and linear relationship between hybridization ratio and sequence divergence of the sample to the platform species. At higher levels of sequence divergence (< 92% sequence identity to D. melanogaster) approximately 84% of features had significantly less hybridization to the array in the heterologous species than the platform species, and thus could be identified as "diverged". At lower levels of divergence (>or= 97% identity), only 13% of genes were identified as diverged. While approximately 40% of the variation in hybridization ratio can be accounted for by variation in sequence identity of the heterologous sample relative to D. melanogaster, other individual characteristics of the DNA sequences, such as GC content, also contribute to variation in hybridization ratio, as does technical variation.ConclusionsHere we demonstrate that aCGH can accurately be used as a proxy to estimate genome-wide divergence, thus providing an efficient way to evaluate how evolutionary processes and genomic architecture can shape species diversity in non-model systems. Given the increased number of species for which microarray platforms are available, comparative studies can be conducted for many interesting lineages in order to identify highly diverged genes that may be the target of natural selection.

Project description:BackgroundPrevious work has indicated that post-traumatic stress disorder (PTSD) symptoms, measured by the Clinician-Administered PTSD Scale (CAPS) within 60 days of trauma exposure, can reliably produce likelihood estimates of chronic PTSD among trauma survivors admitted to acute care centers. Administering the CAPS is burdensome, requires skilled professionals, and relies on symptoms that are not fully expressed upon acute care admission. Predicting chronic PTSD from peritraumatic responses, which are obtainable upon acute care admission, has yielded conflicting results, hence the rationale for a stepwise screening-and-prediction practice. This work explores the ability of peritraumatic responses to produce risk likelihood estimates of early CAPS-based PTSD symptoms indicative of chronic PTSD risk. It specifically evaluates the Peritraumatic Dissociative Experiences Questionnaire (PDEQ) as a risk-likelihood estimator.MethodsWe used individual participant data (IPD) from five acute care studies that used both the PDEQ and the CAPS (n = 647). Logistic regression calculated the probability of having CAPS scores ≥ 40 between 30 and 60 days after trauma exposure across the range of initial PDEQ scores, and evaluated the added contribution of age, sex, trauma type, and prior trauma exposure. Brier scores, area under the receiver-operating characteristic curve (AUC), and the mean slope of the calibration line evaluated the accuracy and precision of the predicted probabilities.ResultsTwenty percent of the sample had CAPS ≥ 40. PDEQ severity significantly predicted having CAPS ≥ 40 symptoms (p < 0.001). Incremental PDEQ scores produced a reliable estimator of CAPS ≥ 40 likelihood. An individual risk estimation tool incorporating PDEQ and other significant risk indicators is provided.ConclusionPeritraumatic reactions, measured here by the PDEQ, can reliably quantify the likelihood of acute PTSD symptoms predictive of chronic PTSD and requiring clinical attention. Using them as a screener in a stepwise chronic PTSD prediction strategy may reduce the burden of later CAPS-based assessments. Other peritraumatic metrics may perform similarly and their use requires similar validation.Trial registrationJerusalem Trauma Outreach and Prevention Study (J-TOPS): NCT00146900.

Project description:Failure of corneal endothelium cell monolayer is the main cause leading to corneal transplantation. Autologous cell-based therapies are required to reconstruct in vitro the cell monolayer. Several strategies have been proposed using embryonic stem cells and induced pluripotent stem cells, although their use has ethical issues as well as limited clinical applications. For this purpose, we propose the use of dental pulp stem cells isolated from the third molars to form the corneal endothelium cell monolayer. We hypothesize that using dental pulp stem cells that share an embryological origin with corneal endothelial cells, as they both arise from the neural crest, may allow a direct differentiation process avoiding the use of reprogramming techniques, such as induced pluripotent stem cells. In this work, we report a two-step differentiation protocol, where dental pulp stem cells are derived into neural crest stem-like cells and, then, into corneal endothelial-like cells. Initially, for the first-step we used an adhesion culture and compared two initial cell sources: a direct formation from dental pulp stem cells with the differentiation from induced pluripotent stem cells. Results showed significantly higher levels of early stage marker AP2 for the dental pulp stem cells compared to induced pluripotent stem cells. In order to provide a better environment for neural crest stem cells generation, we performed a suspension method, which induced the formation of neurospheres. Results showed that neurosphere formation obtained the peak of neural crest stem cell markers expression after 4 days, showing overexpression of AP2, Nestin, and p75 markers, confirming the formation of neural crest stem-like cells. Furthermore, pluripotent markers Oct4, Nanog, and Sox2 were as well-upregulated in suspension culture. Neurospheres were then directly cultured in corneal endothelial conditioned medium for the second differentiation into corneal endothelial-like cells. Results showed the conversion of dental pulp stem cells into polygonal-like cells expressing higher levels of ZO-1, ATP1A1, COL4A2, and COL8A2 markers, providing a proof of the conversion into corneal endothelial-like cells. Therefore, our findings demonstrate that patient-derived dental pulp stem cells may represent an autologous cell source for corneal endothelial therapies that avoids actual transplantation limitations as well as reprogramming techniques.

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Discovering functional DNA elements using population genomic information: a proof of concept using human mtDNA.

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