Biology subjects

Li, B.

Publications and source records attributed to Li, B..

641 records · Page 36Linked to original sources

bioRxiv2017

Unravelling the genomic basis and evolution of the pea aphid male wing dimorphism

Wing dimorphisms have long served as models for examining the ecological and evolutionary tradeoffs associated with alternative morphologies [1], yet the mechanistic basis of morph determination remains largely unknown. Here we investigate the genetic basis of the pea aphid (Acyrthosiphon pisum) wing dimorphism, wherein males exhibit one of two alternative morphologies that differ dramatically in a set of correlated traits that inclused the presence or absence of wings [2-4]. Unlike the environmentally-induced asexual female aphid wing polyphenism [5], the male wing polymorphism is genetically determined by a single uncharacterized locus on the X chromosome called aphicarus (\"aphid\" plus \"Icarus\", api) [6, 7]. Using recombination and association mapping, we localized api to a 130kb region of the pea aphid genome. No nonsynonymous variation in coding sequences strongly associated with the winged and wingless phenotypes, indicating that api is likely a regulatory change. Gene expression level profiling revealed an aphid-specific gene from the region expressed at higher levels in winged male embryos, coinciding with the expected stage of api action. Comparison of the api region across biotypes (pea aphid populations specialized to different host plants that began diverging ~16,000 years ago [8, 9]) revealed that the two alleles were likely present prior to biotype diversification. Moreover, we find evidence for a recent selective sweep of a wingless allele since the biotypes diversified. In sum, this study provides insight into how adaptive, complex traits evolve within and across natural populations.

evolutionary biology↗

bioRxiv2017

An insula-central amygdala circuit for behavioral inhibition

Predicting which substances are suitable for consumption during foraging is critical for animals to survive. While food-seeking behavior is extensively studied, the neural circuit mechanisms underlying avoidance of potentially poisonous substances remain poorly understood. Here we examined the role of the insular cortex (IC) to central amygdala (CeA) circuit in the establishment of such avoidance behavior. Using anatomic tracing approaches combined with optogenetics-assisted circuit mapping, we found that the gustatory region of the IC sends direct excitatory projections to the lateral division of the CeA (CeL), making monosynaptic excitatory connections with distinct populations of CeL neurons. Specific inhibition of neurotransmitter release from the CeL-projecting IC neurons prevented mice from acquiring the \"no-go\" response, while leaving the \"go\" response largely unaffected in a tastant (sucrose/quinine)-reinforced \"go/no-go\" task. Furthermore, selective activation of the IC-CeL pathway with optogenetics drove unconditioned lick suppression in thirsty animals, induced aversive responses, and was sufficient to instruct conditioned action suppression in response to a cue predicting the optogenetic activation. These results indicate that activity in the IC-CeL circuit is necessary for establishing anticipatory avoidance responses to an aversive tastant, and is also sufficient to drive learning of such anticipatory avoidance. This function of the IC-CeL circuit is likely important for guiding avoidance of substances with unpleasant tastes during foraging in order to minimize the chance of being poisoned.\n\nSignificance StatementThe ability to predict which substances are suitable for consumption is critical for survival. Here we found that activity in the insular cortex (IC) to central amygdala (CeA) circuit is necessary for establishing avoidance responses to an unpleasant tastant, and is also sufficient to drive learning of such avoidance responses. These results suggest that the IC-CeA circuit is critical for behavioral inhibition in anticipation of potentially poisonous substances during foraging.

neuroscience↗

bioRxiv2017

Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration

Transcriptomic deconvolution in cancer and other heterogeneous tissues remains challenging. Available methods lack the ability to estimate both component-specific proportions and expression profiles for individual samples. We present DeMixT, a new tool to deconvolve high dimensional data from mixtures of more than two components. DeMixT implements an iterated conditional mode algorithm and a novel gene-set-based component merging approach to improve accuracy. In a series of experimental validation studies and application to TCGA data, DeMixT showed high accuracy. Improved deconvolution is an important step towards linking tumor transcriptomic data with clinical outcomes. An R package, scripts and data are available: https://github.com/wwylab/DeMixT/.

bioinformatics↗

bioRxiv2017

Specific Virus-Host Genome Interactions Revealed By Tethered Chromosome Conformation Capture

Viruses have evolved a variety of mechanisms to interact with host cells for their adaptive benefits, including subverting host immune responses and hijacking host DNA replication/transcription machineries [1-3]. Although interactions between viral and host proteins have been studied extensively, little is known about how the vial genome may interact with the host genome and how such interactions could affect the activities of both the virus and the host cell. Since the three-dimensional organization of a genome can have significant impact on genomic activities such as transcription and replication, we hypothesize that such structure-based regulation of genomic functions also applies to viral genomes depending on their association with host genomic regions and their spatial locations inside the nucleus. Here, we used Tethered Chromosome Conformation Capture (TCC) to investigate viral-host genome interactions between the adenovirus and human lung fibroblast cells. We found viral-host genome interactions were enriched in certain active chromatin regions and chromatin domains marked by H3K27me3. The contacts by viral DNA seems to impact the structure and function of the host genome, leading to remodeling of the fibroblast epigenome. Our study represents the first comprehensive analysis of viral-host interactions at the genome structure level, revealing unexpectedly specific virus-host genome interactions. The non-random nature of such interactions indicates a deliberate but poorly understood mechanism for targeting of host DNA by foreign genomes.

microbiology↗

bioRxiv2017

Transcriptomic Correlates Of Neuron Electrophysiological Diversity

How neuronal diversity emerges from complex patterns of gene expression remains poorly understood. Here we present an approach to understand electrophysiological diversity through gene expression by integrating transcriptomics with intracellular electrophysiology. Using a brain-wide dataset of 34 neuron types, we identified 420 genes whose expression levels significantly correlated with variability in one or more of 11 electrophysiological parameters. The majority of these correlations were consistent in an independent sample of 12 visual cortex cell types. Many associations reported here have the potential to provide new insights into how neurons generate functional diversity, and correlations of ion channel genes like Gabrd and Scn1a (Nav1.1) with resting potential and spiking frequency are consistent with known causal mechanisms. These results suggest that despite the complexity linking gene expression to electrophysiology, there are likely some general principles that govern how individual genes establish phenotypic diversity across very different cell types.

neuroscience↗

bioRxiv2017

The central amygdala controls learning in the lateral amygdala

Both the lateral and the central nuclei of the amygdala are required for adaptive behavioral responses to environmental cues predicting threats. While experience-driven synaptic plasticity in the lateral amygdala is thought to underlie the formation of association between a sensory stimulus and an ensuing threat, how the central amygdala participates in such learning process remains unclear. Here we show that a specific class of central amygdala neurons, the protein kinase C-{delta}-expressing neurons, is essential for the synaptic plasticity underlying learning in the lateral amygdala, as it is required for lateral amygdala neurons to respond to unconditioned stimulus, and furthermore carries information about the unconditioned stimulus to instruct learning. Our results uncover an amygdala functional organization that may play a key role in diverse learning processes.

neuroscience↗

bioRxiv2017

STAR-Fusion: Fast and Accurate Fusion Transcript Detection from RNA-Seq

MotivationFusion genes created by genomic rearrangements can be potent drivers of tumorigenesis. However, accurate identification of functionally fusion genes from genomic sequencing requires whole genome sequencing, since exonic sequencing alone is often insufficient. Transcriptome sequencing provides a direct, highly effective alternative for capturing molecular evidence of expressed fusions in the precision medicine pipeline, but current methods tend to be inefficient or insufficiently accurate, lacking in sensitivity or predicting large numbers of false positives. Here, we describe STAR-Fusion, a method that is both fast and accurate in identifying fusion transcripts from RNA-Seq data.\n\nResultsWe benchmarked STAR-Fusions fusion detection accuracy using both simulated and genuine Illumina paired-end RNA-Seq data, and show that it has superior performance compared to popular alternative fusion detection methods.\n\nAvailability and implementationSTAR-Fusion is implemented in Perl, freely available as open source software at http://star-fusion.github.io, and supported on Linux.\n\nContactbhaas@broadinstitute.org

bioinformatics↗

bioRxiv2017

Preservation of Chromatin Organization after Acute Loss of CTCF in Mouse Embryonic Stem Cells

The CCCTC-binding factor (CTCF) is widely regarded as a key player in chromosome organization in mammalian cells, yet direct assessment of the impact of loss of CTCF on genome architecture has been difficult due to its essential role in cell proliferation and early embryogenesis. Here, using auxin-inducible degron techniques to acutely deplete CTCF in mouse embryonic stem cells, we show that cell growth is severely slowed yet chromatin organization remains largely intact after loss of CTCF. Depletion of CTCF reduces interactions between chromatin loop anchors, diminishes occupancy of cohesin complex genome-wide, and slightly weakens topologically associating domain (TAD) structure, but the active and inactive chromatin compartments are maintained and the vast majority of TAD boundaries persist. Furthermore, transcriptional regulation and histone marks associated with enhancers are broadly unchanged upon CTCF depletion. Our results suggest CTCF-independent mechanisms in maintenance of chromatin organization.

genomics↗

bioRxiv2017

Discovering the Interactions between Circular RNAs and RNA-binding Proteins from CLIP-seq Data using circScan

Although tens of thousands of circular RNAs (circRNAs) have been identified in mammalian genomes, only few of them have been characterized with biological functions. Here, we report a new approach, circScan, to identify regulatory interactions between circRNAs and RNA-binding proteins (RBPs) by discovering back-splicing reads from Cross-Linking and Immunoprecipitation followed by high-throughput sequencing (CLIP-seq) data. By using our method, we have systematically scanned ~1500 CLIP-seq datasets, and identified ~12540 and ~1090 novel circRNA-RBP interactions in human and mouse genomes, respectively, which include all known interactions between circRNAs and Argonaute (AGO) proteins. More than twenty novel interactions were further experimentally confirmed by RNA Immunoprecipitation quantitative PCR (RIP-qPCR). Importantly, we uncovered that some natural circRNAs interacted with cap-independent translation factors eukaryotic initiation factor 3 (eIF3) and N6-Methyladenosine (m6A), indicating they can be translated into proteins. These findings demonstrate that circRNAs are regulated by various RBPs, suggesting they may play important roles in diverse biological processes.

molecular biology↗

bioRxiv2017

A powerful approach to estimating annotation-stratified genetic covariance using GWAS summary statistics

Despite the success of large-scale genome-wide association studies (GWASs) on complex traits, our understanding of their genetic architecture is far from complete. Jointly modeling multiple traits genetic profiles has provided insights into the shared genetic basis of many complex traits. However, large-scale inference sets a high bar for both statistical power and biological interpretability. Here we introduce a principled framework to estimate annotation-stratified genetic covariance between traits using GWAS summary statistics. Through theoretical and numerical analyses we demonstrate that our method provides accurate covariance estimates, thus enabling researchers to dissect both the shared and distinct genetic architecture across traits to better understand their etiologies. Among 50 complex traits with publicly accessible GWAS summary statistics (Ntotal {approx} 4.5 million), we identified more than 170 pairs with statistically significant genetic covariance. In particular, we found strong genetic covariance between late-onset Alzheimers disease (LOAD) and amyotrophic lateral sclerosis (ALS), two major neurodegenerative diseases, in single-nucleotide polymorphisms (SNPs) with high minor allele frequencies and in SNPs located in the predicted functional genome. Joint analysis of LOAD, ALS, and other traits highlights LOADs correlation with cognitive traits and hints at an autoimmune component for ALS.

genetics↗

bioRxiv2016

NeuroExpresso: A cross-laboratory database of brain cell-type expression profiles with applications to marker gene identification and bulk brain tissue transcriptome interpretation

The identification of cell type marker genes, genes highly enriched in specific cell types, plays an important role in the study of the nervous system. In particular, marker genes can be used to identify cell types to enable studies of their properties. Marker genes can also aid the interpretation of bulk tissue expression profiles by revealing cell type specific changes.\n\nWe assembled a database, NeuroExpresso, of publicly available mouse brain cell type-specific gene expression datasets. We then used stringent criteria to select marker genes highly expressed in individual cell types. We found a substantial number of novel markers previously unknown in the literature and validated a subset of them using in silico analyses and in situ hybridization. We next demonstrate the use of marker genes in analysis of whole tissue data by summarizing their expression into \"cell type profiles\" that can be thought of as surrogates for the relative abundance of the cell types across the samples studied.\n\nFurther analysis of our cell type-specific expression database confirms some recent findings about brain cell types along with revealing novel properties, such as Ddc expression in oligodendrocytes. To facilitate further use of this expanding database, we provide a user-friendly web interface for the visualization of expression data.\n\nSignificance StatementCell type markers are powerful tools in the study of the nervous system that help reveal properties of cell types and acquire additional information from large scale expression experiments. Despite their usefulness in the field, known marker genes for brain cell types are few in number. We present NeuroExpresso, a database of brain cell type specific gene expression profiles, and demonstrate the use of marker genes for acquiring cell type specific information from whole tissue expression. The database will prove itself as a useful resource for researchers aiming to reveal novel properties of the cell types and aid both laboratory and computational scientists to unravel the cell type specific components of brain disorders.

neuroscience↗