Retinal outputs depend on behavioural state, bioRxiv, 2019-05-14
AbstractThe operating mode of the visual system depends on behavioural states such as arousal1,2. This dependence is seen both in primary visual cortex3–7 (V1) and in subcortical brain structures receiving direct retinal input4,8. Here we show that this effect arises as early as in the output of the retina. We first measured activity in a region that receives retinal projections9, the superficial superior colliculus (sSC), and found that this activity strongly depended on behavioural state. This modulation was not mediated by feedback inputs from V1 as it was immune to V1 inactivation. We then used Neuropixels probes10 to record activity in the optic tract, and we found some retinal axons whose activity significantly varied with arousal, even in darkness. To characterize these effects on a larger sample of retinal outputs, we imaged the activity of retinal boutons11,12 in sSC during behaviour using a calcium indicator. The activity of these boutons correlated with arousal as strongly as that of sSC neurons, and this correlation persisted also during darkness. These results reveal a novel property of retinal function in mice, which could be observed only during behaviour retinal outputs are modulated by behavioural state before they reach the rest of the brain.
biorxiv neuroscience 100-200-users 2019A large-scale resource for tissue-specific CRISPR mutagenesis in Drosophila, bioRxiv, 2019-05-13
SUMMARYGenetic screens are powerful tools for the functional annotation of genomes. In the context of multicellular organisms, interrogation of gene function is greatly facilitated by methods that allow spatial and temporal control of gene abrogation. Here, we describe a large-scale transgenic short guide (sg) RNA library for efficient CRISPR-based disruption of specific target genes in a constitutive or conditional manner. The library consists currently of more than 2600 plasmids and 1400 fly lines with a focus on targeting kinases, phosphatases and transcription factors, each expressing two sgRNAs under control of the Gal4UAS system. We show that conditional CRISPR mutagenesis is robust across many target genes and can be efficiently employed in various somatic tissues, as well as the germline. In order to prevent artefacts commonly associated with excessive amounts of Cas9 protein, we have developed a series of novel UAS-Cas9 transgenes, which allow fine tuning of Cas9 expression to achieve high gene editing activity without detectable toxicity. Functional assays, as well as direct sequencing of genomic sgRNA target sites, indicates that the vast majority of transgenic sgRNA lines mediate efficient gene disruption. Furthermore, we conducted the so far largest fully transgenic CRISPR screen in any metazoan organism, which further supported the high efficiency and accuracy of our library and revealed many so far uncharacterized genes essential for development.
biorxiv genetics 100-200-users 2019Determining sufficient sequencing depth in RNA-Seq differential expression studies, bioRxiv, 2019-05-13
AbstractRNA-Seq studies require a sufficient read depth to detect biologically important genes. Sequencing below this threshold will reduce statistical power while sequencing above will provide only marginal improvements in power and incur unnecessary sequencing costs. Although existing methodologies can help assess whether there is sufficient read depth, they are unable to guide how many additional reads should be sequenced to reach this threshold. We provide a new method called superSeq that models the relationship between statistical power and read depth. We apply the superSeq framework to 393 RNA-Seq experiments (1,021 total contrasts) in the Expression Atlas and find the model accurately predicts the increase in statistical power gained by increasing the read depth. Based on our analysis, we find that most published studies (> 70%) are undersequenced, i.e., their statistical power can be improved by increasing the sequencing read depth. In addition, the extent of saturation is highly dependent on statistical methodology only 9.5%, 29.5%, and 26.6% of contrasts are saturated when using DESeq2, edgeR, and limma, respectively. Finally, we also find that there is no clear minimum per-transcript read depth to guarantee saturation for an entire technology. Therefore, our framework not only delineates key differences among methods and their impact on determining saturation, but will also be needed even as technology improves and the read depth of experiments increases. Researchers can thus use superSeq to calculate the read depth to achieve required statistical power while avoiding unnecessary sequencing costs.
biorxiv genomics 100-200-users 2019Logomaker Beautiful sequence logos in python, bioRxiv, 2019-05-13
AbstractSequence logos are visually compelling ways of illustrating the biological properties of DNA, RNA, and protein sequences, yet it is currently difficult to generate such logos within the Python programming environment. Here we introduce Logomaker, a Python API for creating publication-quality sequence logos. Logomaker can produce both standard and highly customized logos from any matrix-like array of numbers. Logos are rendered as vector graphics that are easy to stylize using standard matplotlib functions. Methods for creating logos from multiple-sequence alignments are also included.Availability and ImplementationLogomaker can be installed using the pip package manager and is compatible with both Python 2.7 and Python 3.6. Source code is available at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpgithub.comjbkinneylogomaker>httpgithub.comjbkinneylogomaker<jatsext-link>.Supplemental InformationDocumentation is provided at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httplogomaker.readthedocs.io>httplogomaker.readthedocs.io<jatsext-link>.Contactjkinney@cshl.edu.
biorxiv bioinformatics 100-200-users 2019Proximity labeling of protein complexes and cell type-specific organellar proteomes in Arabidopsis enabled by TurboID, bioRxiv, 2019-05-13
AbstractDefining specific protein interactions and spatially or temporally restricted local proteomes improves our understanding of all cellular processes, but obtaining such data is challenging, especially for rare proteins, cell types, or events. Proximity labeling enables discovery of protein neighborhoods defining functional complexes andor organellar protein compositions. Recent technological improvements, namely two highly active biotin ligase variants (TurboID and miniTurboID), allowed us to address two challenging questions in plants (1) what are in vivo partners of a low abundant key developmental transcription factor and (2) what is the nuclear proteome of a rare cell type? Proteins identified with FAMA-TurboID include known interactors of this stomatal transcription factor and novel proteins that could facilitate its activator and repressor functions. Directing TurboID to stomatal nuclei enabled purification of cell type- and subcellular compartment-specific proteins. Broad tests of TurboID and miniTurboID in Arabidopsis and N. benthamiana and versatile vectors enable customization by plant researchers.
biorxiv plant-biology 100-200-users 2019Paragraph A graph-based structural variant genotyper for short-read sequence data, bioRxiv, 2019-05-11
AbstractAccurate detection and genotyping of structural variations (SVs) from short-read data is a long-standing area of development in genomics research and clinical sequencing pipelines. We introduce Paragraph, a fast and accurate genotyper that models SVs using sequence graphs and SV annotations produced by a range of methods and technologies. We demonstrate the accuracy of Paragraph on whole genome sequence data from a control sample with both short and long read sequencing data available, and then apply it at scale to a cohort of 100 samples of diverse ancestry sequenced with short-reads. Comparative analyses indicate that Paragraph has better accuracy than other existing genotypers. The Paragraph software is open-source and available at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpsgithub.comIlluminaparagraph>httpsgithub.comIlluminaparagraph<jatsext-link>
biorxiv genomics 100-200-users 2019