Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism, bioRxiv, 2018-12-01
SummaryWe present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n=35,584 total samples, 11,986 with ASD). Using an enhanced Bayesian framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate ≤ 0.1. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained for severe neurodevelopmental delay, while 53 show higher frequencies in individuals ascertained for ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most of the risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In human cortex single-cell gene expression data, expression of risk genes is enriched in both excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatoryinhibitory imbalance underlying ASD.
biorxiv genetics 200-500-users 2018Linked-read sequencing of gametes allows efficient genome-wide analysis of meiotic recombination, bioRxiv, 2018-12-01
ABSTRACTMeiotic crossovers (COs) ensure proper chromosome segregation and redistribute the genetic variation that is transmitted to the next generation. Existing methods for CO identification are challenged by large populations and the demand for genome-wide and fine-scale resolution. Taking advantage of linked-read sequencing, we developed a highly efficient method for genome-wide identification of COs at kilobase resolution in pooled recombinants. We first tested this method using a pool of Arabidopsis F2 recombinants, and obtained results that recapitulated those identified from the same plants using individual whole-genome sequencing. By applying this method to a pool of pollen DNA from a single F1 plant, we established a highly accurate CO landscape without generating or sequencing a single recombinant plant. The simplicity of this approach now enables the simultaneous generation and analysis of multiple CO landscapes and thereby allows for efficient comparison of genotypic and environmental effects on recombination, accelerating the pace at which the mechanisms for the regulation of recombination can be elucidated.
biorxiv bioinformatics 100-200-users 2018Generative modeling and latent space arithmetics predict single-cell perturbation response across cell types, studies and species, bioRxiv, 2018-11-30
AbstractAccurately modeling cellular response to perturbations is a central goal of computational biology. While such modeling has been proposed based on statistical, mechanistic and machine learning models in specific settings, no generalization of predictions to phenomena absent from training data (‘out-of-sample’) has yet been demonstrated. Here, we present scGen, a model combining variational autoencoders and latent space vector arithmetics for high-dimensional single-cell gene expression data. In benchmarks across a broad range of examples, we show that scGen accurately models dose and infection response of cells across cell types, studies and species. In particular, we demonstrate that scGen learns cell type and species specific response implying that it captures features that distinguish responding from non-responding genes and cells. With the upcoming availability of large-scale atlases of organs in healthy state, we envision scGen to become a tool for experimental design through in silico screening of perturbation response in the context of disease and drug treatment.
biorxiv bioinformatics 0-100-users 2018Intelligible speech synthesis from neural decoding of spoken sentences, bioRxiv, 2018-11-30
The ability to read out, or decode, mental content from brain activity has significant practical and scientific implications. For example, technology that translates cortical activity into speech would be transformative for people unable to communicate as a result of neurological impairment. Decoding speech from neural activity is challenging because speaking requires extremely precise and dynamic control of multiple vocal tract articulators on the order of milliseconds. Here, we designed a neural decoder that explicitly leverages the continuous kinematic and sound representations encoded in cortical activity to generate fluent and intelligible speech. A recurrent neural network first decoded vocal tract physiological signals from direct cortical recordings, and then transformed them to acoustic speech output. Robust decoding performance was achieved with as little as 25 minutes of training data. Naive listeners were able to accurately identify these decoded sentences. Additionally, speech decoding was not only effective for audibly produced speech, but also when participants silently mimed speech. These results advance the development of speech neuroprosthetic technology to restore spoken communication in patients with disabling neurological disorders.
biorxiv neuroscience 200-500-users 2018Sex differences in gene expression in the human fetal brain, bioRxiv, 2018-11-30
ABSTRACTWidespread structural, chemical and molecular differences have been reported between the male and female human brain. Although several neurodevelopmental disorders are more commonly diagnosed in males, little is known regarding sex differences in early human brain development. Here, we used RNA sequencing data from a large collection of human brain samples from the second trimester of gestation (N = 120) to assess sex biases in gene expression within the human fetal brain. In addition to 43 genes (102 Ensembl transcripts) transcribed from the Y-chromosome in males, we detected sex differences in the expression of 2558 autosomal genes (2723 Ensembl transcripts) and 155 genes on the X-chromosome (207 Ensembl transcripts) at a false discovery rate (FDR) < 0.1. Genes exhibiting sex-biased expression in human fetal brain are enriched for high-confidence risk genes for autism and other developmental disorders. Male-biased genes are enriched for expression in neural progenitor cells, whereas female-biased genes are enriched for expression in Cajal-Retzius cells and glia. All gene- and transcript-level data are provided as an online resource (available at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpfgen.psycm.cf.ac.ukFBSeq1>httpfgen.psycm.cf.ac.ukFBSeq1<jatsext-link>) through which researchers can search, download and visualize data pertaining to sex biases in gene expression during early human brain development.
biorxiv genomics 200-500-users 2018E-ChRPs Engineered Chromatin Remodeling Proteins for Precise Nucleosome Positioning, bioRxiv, 2018-11-29
SummaryRegulation of chromatin structure is essential for controlling the access of DNA to factors that require association with specific DNA sequences. The ability to alter chromatin organization in a targeted manner would provide a mechanism for directly manipulating DNA-dependent processes and should provide a means to study direct consequences of chromatin structural changes. Here we describe the development and validation of engineered chromatin remodeling proteins (E-ChRPs) for inducing programmable changes in nucleosome positioning by design. We demonstrate that E-ChRPs function both in vivo and in vitro to specifically reposition target nucleosomes and entire nucleosomal arrays, and possess the ability to evict native DNA-binding proteins through their action. E-ChRPs can be designed with a range of targeting modalities, including the SpyCatcher and dCas9 moieties, resulting in high versatility and enabling diverse future applications. Thus, engineered chromatin remodeling proteins represent a simple and robust means to probe regulation of DNA-dependent processes in different chromatin contexts.
biorxiv genetics 100-200-users 2018