Biology subjects

Gao, G.

Publications and source records attributed to Gao, G..

106 records · Page 6Linked to original sources

bioRxiv2019

Computational Assessment of the Regulation-Modulating Potential for Noncoding Variants

Large-scale genome-wide association and expression quantitative trait loci studies have identified multiple noncoding variants associated with genetic diseases via affecting gene expression. However, effectively and efficiently pinpointing causal variants remains a serious challenge. Here, we developed CARMEN, a novel algorithm to identify functional noncoding expression-modulating variants. Multiple evaluations demonstrated CARMENs superior performance over state-of-the-art tools. Its higher sensitivity and low false discovery rate enable CARMEN to identify multiple causal expression-modulating variants that other tools simply missed. Meanwhile, benefitting from extensive annotations generated, CARMEN provides mechanism hints on predicted expression-modulating variants, enabling effectively characterizing functional variants involved in gene expression and disease-related phenotypes. CARMEN scales well with the massive datasets and is available online as a Web server at http://carmen.gao-lab.org.

genomics↗

bioRxiv2019

Multiple features within Sed5p mediate it’s COPI-independent trafficking and Golgi localization

Protein retention and the transport of proteins and lipids into and out of the Golgi is intimately linked to the biogenesis and homeostasis of this sorting hub of eukaryotic cells. Of particular importance are membrane proteins that mediate membrane fusion events with and within the Golgi - the Soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs). In the Golgi of budding yeast cells a single syntaxin - the SNARE Sed5p - oversees membrane fusion within the Golgi. Determining how Sed5p is localized to and trafficked within the Golgi is critical to informing our understanding of the mechanism(s) of biogenesis and homeostasis of this organelle. Here we establish that the Golgi retention and trafficking of Sed5p between the Golgi and the ER is independent of COPI function, the composition of the transmembrane domain, and binding of the Sec1-Munc18 (SM) protein Sly1p. Rather, the steady state localization of Sed5p to the Golgi appears to be primarily conformation-based relying on intra-molecular associations between the Habc domain and SNARE-motif.

cell biology↗

bioRxiv2019

Expectation pooling: An effective and interpretable pooling method for predicting DNA-protein binding

MotivationConvolutional neural networks (CNNs) have outperformed conventional methods in modeling the sequence specificity of DNA-protein binding. While previous studies have built a connection between CNNs and probabilistic models, simple models of CNNs cannot achieve sufficient accuracy on this problem. Recently, some methods of neural networks have increased performance using complex neural networks whose results cannot be directly interpreted. However, it is difficult to combine probabilistic models and CNNs effectively to improve DNA-protein binding predictions.\n\nResultsIn this paper, we present a novel global pooling method: expectation pooling for predicting DNA-protein binding. Our pooling method stems naturally from the EM algorithm, and its benefits can be interpreted both statistically and via deep learning theory. Through experiments, we demonstrate that our pooling method improves the prediction performance DNA-protein binding. Our interpretable pooling method combines probabilistic ideas with global pooling by taking the expectations of inputs without increasing the number of parameters. We also analyze the hyperparameters in our method and propose optional structures to help fit different datasets. We explore how to effectively utilize these novel pooling methods and show that combining statistical methods with deep learning is highly beneficial, which is promising and meaningful for future studies in this field.\n\nContactdengmh@pku.edu.cn, gaog@mail.cbi.pku.edu.cn\n\nSupplementary informationAll code is public in https://github.com/gao-lab/ePooling

bioinformatics↗

bioRxiv2019

Conditional, inducible gene silencing in dopamine neurons reveals a sex-specific role for Rit2 GTPase in acute cocaine response and striatal function

Dopamine (DA) signaling is critical for movement, motivation, and addictive behavior. The neuronal GTPase, Rit2, is enriched in DA neurons (DANs), binds directly to the DA transporter (DAT), and is implicated in several DA-related neuropsychiatric disorders. However, it remains unknown whether Rit2 plays a role in either DAergic signaling and/or DA-dependent behaviors. Here, we leveraged the TET-OFF system to conditionally silence Rit2 in Pitx3IRES2-tTA mouse DANs. Following DAergic Rit2 knockdown (Rit2-KD), mice displayed an anxiolytic phenotype, with no change in baseline locomotion. Further, males exhibited increased acute cocaine sensitivity, whereas DAergic Rit2-KD suppressed acute cocaine sensitivity in females. DAergic Rit2-KD did not affect presynaptic TH and DAT protein levels in females, nor was TH was affected in males; however, DAT was significantly diminished in males. Paradoxically, despite decreased DAT levels in males, striatal DA uptake was enhanced, but was not due to enhanced DAT surface expression in either dorsal or ventral striatum. Finally, patch recordings in nucleus accumbens (NAcc) medium spiny neurons (MSNs) revealed reciprocal changes in spontaneous EPSP (sEPSP) frequency in male and female D1+ and D2+ MSNs following DAergic Rit2-KD. In males, sEPSP frequency was decreased in D1+, but not D2+, MSNs, whereas in females sEPSP frequency decreased in D2+, but not D1+, MSNs. Moreover, DAergic Rit2-KD abolished the ability of cocaine to reduce sEPSP frequency in D1+, but not D2+, male MSNs. Taken together, our studies are among the first to acheive AAV-mediated, conditional and inducible DAergic knockdown in vivo. Importantly, our results provide the first evidence that DAergic Rit2 expression differentially impacts striatal function and DA-dependent behaviors in males and females.

neuroscience↗

bioRxiv2019

Cell BLAST: Searching large-scale scRNA-seq database via unbiased cell embedding

An effective and efficient cell-querying method is critical for integrating existing scRNA-seq data and annotating new data. Herein, we present Cell BLAST, an accurate and robust cell-querying method. Powered by a well-curated reference database and a user-friendly Web server, Cell BLAST (http://cblast.gao-lab.org) provides a one-stop solution for real-world scRNA-seq cell querying and annotation.

bioinformatics↗

bioRxiv2019

Reticulon and CLIMP-63 control nanodomain organization of peripheral ER tubules

The endoplasmic reticulum (ER) is an expansive, membrane-enclosed organelle composed of smooth peripheral tubules and rough, ribosome-studded central ER sheets whose morphology is determined, in part, by the ER-shaping proteins, reticulon and CLIMP-63, respectively. Here, STimulated Emission Depletion (STED) super-resolution microscopy shows that reticulon and CLIMP-63 also control the organization and dynamics of peripheral ER tubule nanodomains. STED imaging shows that lumenal ERmoxGFP, membrane Sec61{beta}GFP, knock-in calreticulin-GFP and antibody-labeled ER resident proteins calnexin and derlin-1 are all localized to periodic puncta along the length of peripheral ER tubules that are not readily observable by diffraction limited confocal microscopy. Reticulon segregates away from and restricts lumenal blob length while CLIMP-63 associates with and increases lumenal blob length. Reticulon and CLIMP-63 also regulate the nanodomain distribution of ER resident proteins, being required for the preferential segregation of calnexin and derlin-1 puncta away from lumenal ERmoxGFP blobs. High-speed (40 ms/frame) live cell STED imaging shows that reticulon and CLIMP-63 control nanoscale compartmentalization of lumenal flow in peripheral ER tubules. Reticulon enhances and CLIMP-63 disrupts the local accumulation of lumenal ERmoxGFP at spatially defined sites along ER tubules. The ER shaping proteins reticulon and CLIMP-63 therefore control lumenal ER nanodomain dynamics, heterogeneity and interaction with ER resident proteins in peripheral ER tubules.

cell biology↗

bioRxiv2019

Geographic Patterns of Bacterioplankton among Lakes of the Middle and Lower Reaches of the Yangtze River Basin, China

In aquatic ecosystems, microbial biogeography research is critical for unveiling the mechanisms of microbial community succession. However, little is known about the microbial biogeography among interconnected lakes. To address this deficit, we used high-throughput sequencing to explore geographic patterns and the relative importance of ecological processes that shape these patterns in abundant and rare bacterial subcommunities from 25 lakes across the middle and lower reaches of Yangtze River basin (MLYB, located in southeast China), where most of the lakes are interconnected by river networks. We found that there were significant differences in both abundant and rare bacterial subcommunities between the two lake groups that were far from each other, while were no difference among the nearby lakes in each group. Both abundant and rare bacteria followed a strong distance-decay relationship, especially for rare bacteria. These findings suggest that although the interconnectivity between lakes breaks the geographical isolation of bacteria, the dispersal capability of bacterial taxa was still limited by geographic distance. We also found that although deterministic processes and stochastic processes together drive the bacterial subcommunities assembly, the stochastic processes (based on adjusted R2 in redundancy analysis) exhibited a greater influence on bacterial subcommunities. Our results implied that bacterial dispersal among interconnected lakes was more stochastically. ImportanceUnraveling the relative importance of ecological processes regulating microbial community structure is a central goal in microbial ecology. In aquatic ecosystems, microbial communities often occur in spatially structured habitats, where connectivity directly affects dispersal and metacommunity processes. Recent theoretical work suggests that directional dispersal among connected habitats leads to higher variability in local diversity and among-community composition. However, the study of microbial biogeography among natural interconnected habitats is still lacking. The findings of this study revealed interesting phenomena of microbial biogeography among natural interconnected habitats, suggested that the high interconnectivity reduced the spatial heterogeneity of bacteria, and caused the dispersal of bacteria to be more stochastically. This study has provided a deeper understanding of the biogeographic patterns of rare and abundant bacterial taxa and their determined processes among interconnected aquatic habitats.

microbiology↗

bioRxiv2019

Dissection and validation of minor quantitative trait loci (QTLs) conferring grain size and weight in rice

Grain size and weight contribute greatly to the grain yield of rice. In order to identify minor QTLs conferring grain size and weight, an F2 population derived from a cross between two indica rice lines showing small difference on grain size, Guangzhan 63-4S (GZ63-4S) and Dodda, and its derived F2:3 population were developed and used for QTL analysis. Totally, 36 QTLs for grain size and weight were detected, and 7 were repeatedly detected, of which the number of beneficial alleles was contributed roughly equally by the two parents. In order to further validate effects of QTLs detected, a BC1F2 population derived from a backcross of a mixture of F2 lines with GZ63-4S was developed and subjected to QTL selection. Heterozygous regions of 3 QTLs, qGS3, qTGW6.2 and qGT7 were identified, and corresponding near-isogenic lines (NILs) of each QTL were constructed with three rounds of self-crosses. In the background of NILs, qGS3 was responsible for GL, LWR, GT and TGW, qTGW6.2 was for GL and TGW, and qGT7 was for GT and TGW. These results have laid the foundation of further fine mapping and cloning of underlying genes, and could be of great use in breeding and improvement of rice lines with desirable size and yield.

genetics↗

bioRxiv2018

A new convolution model for effective bio-motif detection via rationally design the \"black box\"

Motif identification is among the most common and essential computational tasks for bioinformatics and genomics. Here we proposed a novel convolutional layer for deep neural network, named Variable Convolutional (vConv) layer, for effective motif identification in high-throughput omics data by learning kernel length from data adaptively. Empirical evaluations on DNA-protein binding and DNase footprinting cases well demonstrated that vConv-based networks have superior performance to their convolutional counterparts regardless of model complexity. Meanwhile, vConv could be readily integrated into multi-layer neural networks as an "in-place replacement" of canonical convolutional layer. All source codes are freely available on GitHub for academic usage.

bioinformatics↗

bioRxiv2018

Sex-dependent dominance maintains migration supergene in rainbow trout

Traits with different fitness optima in males and females cause sexual conflict when they have a shared genetic basis. Heteromorphic sex chromosomes can resolve this conflict and protect sexually antagonistic polymorphisms but accumulate deleterious mutations. However, many taxa lack differentiated sex chromosomes, and how sexual conflict is resolved in these species is largely unknown. Here we present a chromosome-anchored genome assembly for rainbow trout (Oncorhynchus mykiss) and characterize a 56 Mb double-inversion supergene that mediates sex-specific migration through sex-dependent dominance, a mechanism that reduces sexual conflict. The double-inversion contains key photosensory, circadian rhythm, adiposity, and sexual differentiation genes and displays frequency clines associated with latitude and temperature, revealing environmental dependence. Our results constitute the first example of sex-dependent dominance across a large autosomal supergene, a novel mechanism for sexual conflict resolution capable of protecting polygenic sexually antagonistic variation while avoiding the homozygous lethality and deleterious mutation load of heteromorphic sex chromosomes.

evolutionary biology↗

bioRxiv2018

Decoding functional regulatory maps via genomic evolutionary footprints in 63 green plants

Systematic identification of functional transcriptional regulatory interactions is essential for understanding regulatory systems. Here, we firstly established genome-wide conservation landscapes for 63 green plants of seven lineages and then developed an algorithm FunTFBS to screen for functional regulatory elements and interactions by coupling base-varied binding affinities of transcription factors with the evolutionary footprints on their binding sites. Using the FunTFBS and the conservation landscapes, we further identified over two million functional interactions for 21,346 TFs, charting functional regulatory maps of these 63 plants. Our work provides plant community with valuable resources to decode plant transcriptional regulatory system and genome sequences.

bioinformatics↗

bioRxiv2018

IL-25 induces beige fat to improve metabolic homeostasis via macrophage and innervation

Beige fat dissipates energy and functions as a defense against cold and obesity, but the underlying mechanisms remain unclear. We found that the signaling of interleukin (IL)-25 including its cognate receptor, IL-17 receptor B (IL-17RB), increased in adipose tissue upon cold and {beta}3-adrenoceptor agonist stimulation. IL-25 induced the browning effect in white adipose tissue (WAT) by releasing IL-4, 13 and promoting alternative activation of macrophages to regulate innervation, which characterized as tyrosine hydroxylase (TH) up-regulation to produce more catecholamine including norepinephrine. Blockade of IL-4R and depletion of macrophages with clodronate-loaded liposomes in vivo significantly impaired the browning of WAT. Obese mice administered with IL-25 were protected from obesity on a high-fat diet and the subsequent metabolic disorders, and the process involved the uncoupling protein 1 (UCP1)-mediated thermogenesis. In conclusion, the activation of IL-25 signaling on beige fat might play a therapeutic potential for obesity and its associated metabolic disorders.

biochemistry↗

bioRxiv2018

Gp78 E3 ubiquitin ligase mediates both basal and damage-induced mitophagy

Mitophagy, the elimination of mitochondria by the autophagy machinery, evolved to monitor mitochondrial health and maintain mitochondrial integrity. PINK1 is a sensor of mitochondrial health that recruits Parkin and other mitophagy-inducing ubiquitin ligases to depolarized mitochondria. However, mechanisms underlying mitophagic control of mitochondrial homeostasis, basal mitophagy, remain poorly understood. The Gp78 E3 ubiquitin ligase, an endoplasmic reticulum membrane protein, induces mitochondrial fission, endoplasmic reticulum-mitochondria contacts and mitophagy of depolarized mitochondria. CRISPR/Cas9 knockout of Gp78 in HT-1080 fibrosarcoma cells results in reduced ER-mitochondria contacts, increased mitochondrial volume and resistance to CCCP-induced mitophagy. Knockdown (KD) of the essential autophagy protein ATG5 increased mitochondrial volume of wild-type cells but did not impact mitochondrial volume of Gp78 knockout cells. This suggests that endogenous Gp78 actively eliminates mitochondria by autophagy in wild-type HT-1080 cells. Damage-induced mitophagy of depolarized mitochondria, in the presence of CCCP, but not basal mitophagy was prevented by knockdown of PINK1. This suggests that endogenous Gp78 plays dual roles in mitophagy induction: 1) control of mitochondrial homeostasis through mitophagy of undamaged mitochondria; and 2) elimination of damaged mitochondria through PINK1.

cell biology↗

bioRxiv2018

Genome-wide association analysis with a 50K transcribed gene SNP-chip identifies QTL affecting muscle yield in rainbow trout

Detection of coding/functional SNPs that change the biological function of a gene may lead to identification of putative causative alleles within QTL regions and discovery of genetic markers with large effects on phenotypes. Two bioinformatics pipelines, GATK and SAMtools, were used to identify ~21K transcribed SNPs with allelic imbalances associated with important aquaculture production traits including body weight, muscle yield, muscle fat content, shear force, and whiteness in addition to resistance/susceptibility to bacterial cold-water disease (BCWD). SNPs were identified from pooled RNA-Seq data collected from ~620 fish, representing 98 families from growth- and 54 families from BCWD-selected lines with divergent phenotypes. In addition, ~29K transcribed SNPs without allelic-imbalances were strategically added to build a 50K Affymetrix SNP-chip. SNPs selected included two SNPs per gene from 14K genes and ~5K non-synonymous SNPs. The SNP-chip was used to genotype 1728 fish. The average SNP calling-rate for samples passing quality control (QC; 1,641 fish) was [≥] 98.5%. Genome-wide association (GWA) study on 878 fish (representing 197 families from 2 consecutive generations) with muscle yield phenotypes and genotyped for 35K polymorphic markers (passing QC) identified several QTL regions explaining together up to 28.40% of the additive genetic variance for muscle yield in this rainbow trout population. The most significant QTLs were on chromosomes 14 and 16 with 12.71% and 10.49% of the genetic variance, respectively. Many of the annotated genes in the QTL regions were previously reported as important regulators of muscle development and cell signaling. No major QTLs were identified in a previous GWA study using a 57K genomic SNP chip on the same fish population. These results indicate improved detection power of the transcribed gene SNP-chip in the target trait and population, allowing identification of large-effect QTLs for important traits in rainbow trout.

genomics↗

bioRxiv2017

Genome-wide Association Studies Reveal Similar Genetic Architecture with Shared and Unique QTL for Bacterial Cold Water Disease Resistance in Two Rainbow Trout Breeding Populations

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. In previous studies, we identified moderate-large effect QTL for BCWD resistance in rainbow trout (Oncorhynchus mykiss). However, the recent availability of a 57K SNP array and a genome physical map have enabled us to conduct genome-wide association studies (GWAS) that overcome several experimental limitations from our previous work. In the current study, we conducted GWAS for BCWD resistance in two rainbow trout breeding populations using two genotyping platforms, the 57K Affymetrix SNP array and restriction-associated DNA (RAD) sequencing. Overall, we identified 14 moderate-large effect QTL that explained up to 60.8% of the genetic variance in one of the two populations and 27.7% in the other. Four of these QTL were found in both populations explaining a substantial proportion of the variance, although major differences were also detected between the two populations. Our results confirm that BCWD resistance is controlled by the oligogenic inheritance of few moderate-large effect loci and a large-unknown number of loci each having a small effect on BCWD resistance. We detected differences in QTL number and genome location between two GWAS models (weighted single-step GBLUP and Bayes B), which highlights the utility of using different models to uncover QTL. The RAD-SNPs detected a greater number of QTL than the 57K SNP array in one population, suggesting that the RAD-SNPs may uncover polymorphisms that are more unique and informative for the specific population in which they were discovered.

genetics↗

bioRxiv2017

An exact transformation of convolutional kernels applied directly to DNA/RNA sequences

MotivationConvolutional neural network (CNN) has been widely used in functional motifs identification for large-scale DNA/RNA sequences. Currently, however, the only way to interpret such a convolutional kernel is a heuristic construction of a position weight matrix (PWM) from fragments scored highly by that kernel.\n\nResultsInstead of using heuristics, we developed a novel, exact kernel-to-PWM transformation whose equivalency is theoretically proven: the log-likelihood of the resulting PWM generating any DNA/RNA sequence is exactly the sum of a constant and the convolution of the original kernel on the same sequence. Importantly, we further proved that the resulting PWMs performance on sequence classification/regression can be exactly the same as the original kernels under popular CNN frame-works. In simulation, the exact transformation rivals or outperforms the heuristic PWMs in terms of classifying sequences with sequence- or structure-motifs. The exact transformation also faithfully reproduces the output of CNN models on real-world cases, while the heuristic one fails, especially on the case with little prior knowledge on the form of underlying true motifs. Of note, the time complexity of the novel exact transformation is independent on the number of input sequences, enabling it to scale well for massive training sequences.\n\nAvailabilityPython scripts for the transformation from kernel to PWM, the inverted transformation from PWM to kernel, and a proof-of-concept for the maximum likelihood estimation of optimal PWM are available through https://github.com/gao-lab/kernel-to-PWM.\n\nContactgaog@mail.cbi.pku.edu.cn

bioinformatics↗