Negative selection on complex traits limits genetic risk prediction accuracy between populations, bioRxiv, 2019-08-02
Accurate genetic risk prediction is a key goal for medical genetics and great progress has been made toward identifying individuals with extreme risk across several traits and diseases (Collins and Varmus, 2015). However, many of these studies are done in predominantly European populations (Bustamante et al., 2011; Popejoy and Fullerton, 2016). Although GWAS effect sizes correlate across ancestries (Wojcik et al., 2019), risk scores show substantial reductions in accuracy when applied to non-European populations (Kim et al., 2018; Martin et al., 2019; Scutari et al., 2016). We use simulations to show that human demographic history and negative selection on complex traits result in population specific genetic architectures. For traits under moderate negative selection, ~50% of the heritability can be accounted for by variants in Europe that are absent from Africa. We show that this directly leads to poor performance in risk prediction when using variants discovered in Europe to predict risk in African populations, especially in the tails of the risk distribution. To evaluate the impact of this effect in genomic data, we built a Bayesian model to stratify heritability between European-specific and shared variants and applied it to 43 traits and diseases in the UK Biobank. Across these phenotypes, we find ~50% of the heritability comes from European-specific variants, setting an upper bound on the accuracy of genetic risk prediction in non-European populations using effect sizes discovered in European populations. We conclude that genetic association studies need to include more diverse populations to enable to utility of genetic risk prediction in all populations.
biorxiv genetics 100-200-users 2019Phylogenies of extant species are consistent with an infinite array of diversification histories, bioRxiv, 2019-08-01
AbstractTime-calibrated molecular phylogenies of extant species (extant timetrees) are widely used for estimating the dynamics of diversification rates (1–6) and testing for associations between these rates and environmental factors (5, 7) or species traits (8). However, there has been considerable debate surrounding the reliability of these inferences in the absence of fossil data (9–13), and to date this critical question remains unresolved. Here we mathematically clarify the precise information that can be extracted from extant timetrees under the generalized birth-death model, which underlies the majority of existing estimation methods. We prove that for a given extant timetree and a candidate diversification scenario, there exists an infinite number of alternative diversification scenarios that are equally likely to have generated a given tree. These “congruent” scenarios cannot possibly be distinguished using extant timetrees alone, even in the presence of infinite data. Importantly, congruent diversification scenarios can exhibit markedly different and yet plausible diversification dynamics, suggesting that many previous studies may have over-interpreted phylogenetic evidence. We show that sets of congruent models can be uniquely described using composite variables, which contain all available information about past dynamics of diversification (14); this suggests an alternative paradigm for learning about the past from extant timetrees.
biorxiv evolutionary-biology 100-200-users 2019Precision of Tissue Patterning is Controlled by Dynamical Properties of Gene Regulatory Networks, bioRxiv, 2019-08-01
AbstractDuring development, gene regulatory networks allocate cell fates by partitioning tissues into spatially organised domains of gene expression. How the sharp boundaries that delineate these gene expression patterns arise, despite the stochasticity associated with gene regulation, is poorly understood. We show, in the vertebrate neural tube, using perturbations of coding and regulatory regions, that the structure of the regulatory network contributes to boundary precision. This is achieved, not by reducing noise in individual genes, but by the configuration of the network modulating the ability of stochastic fluctuations to initiate gene expression changes. We use a computational screen to identify the properties of a network that influence boundary precision, revealing two dynamical mechanisms by which small gene circuits attenuate the effect of noise to increase patterning precision. These results establish design principles of gene regulatory networks that produce precise patterns of gene expression.
biorxiv developmental-biology 0-100-users 2019Cross-species transcriptomic and epigenomic analysis reveals key regulators of injury response and neuronal regeneration in vertebrate retinas, bioRxiv, 2019-07-31
AbstractInjury induces retinal Müller glia of cold-blooded, but not mammalian, vertebrates to generate neurons. To identify gene regulatory networks that control neuronal reprogramming in retinal glia, we comprehensively profiled injury-dependent changes in gene expression and chromatin conformation in Müller glia from zebrafish, chick and mice using bulk RNA and ATAC-Seq, as well as single-cell RNA-Seq. Cross-species integrative analysis of these data, together with functional validation of candidate genes, identified evolutionarily conserved and species-specific gene networks controlling glial quiescence, gliosis and neurogenesis. In zebrafish and chick, transition from quiescence to gliosis is a critical stage in acquisition of neurogenic competence, while in mice a dedicated network suppresses this transition and rapidly restores quiescence. Selective disruption of NFI family transcription factors, which maintain and restore quiescence, enables Müller glia to proliferate and robustly generate neurons in adult mice after retinal injury. These comprehensive resources and findings will facilitate the design of cell-based therapies aimed at restoring retinal neurons lost to degenerative disease.
biorxiv neuroscience 100-200-users 2019Graphmap2 - splice-aware RNA-seq mapper for long reads, bioRxiv, 2019-07-31
AbstractIn this paper we present Graphmap2, a splice-aware mapper built on our previously developed DNA mapper Graphmap. Graphmap2 is tailored for long reads produced by Pacific Biosciences and Oxford Nanopore devices. It uses several newly developed algorithms which enable higher precision and recall of correctly detected transcripts and exon boundaries. We compared its performance with the state-of-the-art tools Minimap2 and Gmap. On both simulated and real datasets Graphmap2 achieves higher mappability and more correctly recognized exons and their ends. In addition we present an analysis of potential of splice aware mappers and long reads for the identification of previously unknown isoforms and even genes. The Graphmap2 tool is publicly available at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpsgithub.comlbcb-scigraphmap2>httpsgithub.comlbcb-scigraphmap2<jatsext-link>.
biorxiv bioinformatics 0-100-users 2019Reversal of ageing- and injury-induced vision loss by Tet-dependent epigenetic reprogramming, bioRxiv, 2019-07-31
Ageing is a degenerative process leading to tissue dysfunction and death. A proposed cause of ageing is the accumulation of epigenetic noise, which disrupts youthful gene expression patterns that are required for cells to function optimally and recover from damage1–3. Changes to DNA methylation patterns over time form the basis of an ‘ageing clock’4, 5, but whether old individuals retain information to reset the clock and, if so, whether this would improve tissue function is not known. Of all the tissues in the body, the central nervous system (CNS) is one of the first to lose regenerative capacity6, 7. Using the eye as a model tissue, we show that expression of Oct4, Sox2, and Klf4 genes (OSK) in mice resets youthful gene expression patterns and the DNA methylation age of retinal ganglion cells, promotes axon regeneration after optic nerve crush injury, and restores vision in a mouse model of glaucoma and in normal old mice. This process, which we call recovery of information via epigenetic reprogramming or REVIVER, requires the DNA demethylases Tet1 and Tet2, indicating that DNA methylation patterns don’t just indicate age, they participate in ageing. Thus, old tissues retain a faithful record of youthful epigenetic information that can be accessed for functional age reversal.
biorxiv molecular-biology 500+-users 2019