Biology subjects

Xue, H.

Publications and source records attributed to Xue, H..

At least 73 records · Page 4Linked to original sources

bioRxiv2021

The contribution of uncharted RNA sequences to tumor identity in lung adenocarcinoma

BackgroundTranscriptome analysis of cancer tissues has been instrumental in defining tumor subtypes, diagnostic signatures and cancer regulatory networks. Cancer transcriptomes are still predominantly analyzed at the level of gene expression. Few studies have addressed transcript-level variations, and most of these only looked at splice variants. Previously we introduced a k-mer based, reference-free method, DE-kupl, that performs differential analysis of RNA-seq data at the k-mer level, which enables distinguishing RNAs differing by a single nucleotide. Here we evaluate the significance of differential events discovered by this method in two independent lung adenocarcinoma RNA-seq datasets (N=583 and N=154). ResultsFocusing on differential events in a tumor vs normal setting, we found events in endogenous repeats, alternative splicing and polyadenylation sites, long non-coding RNAs, retained introns and unmapped RNAs. Replicability was highly significant for most event classes (assessed by comparing to events shared between unrelated tumors). Overall about 160,000 differential k-mer contigs were shared between datasets, including a large set of sequences from hypervariable genes such as immunoglobulins, SFTP and mucin genes. Most interestingly, we identified a set of novel tumor-specific long non-coding RNAs in intergenic and intronic regions. We found that expressed endogenous transposons defined two major groups of patients (high/low repeat expression) with distinct clinical characteristic. A number of repeats, intronic RNAs and lincRNA achieved strong patient stratification in univariate or multivariate survival models. Finally, using antigen presentation prediction, we identified 55 contigs predicted to produce recurrent tumor-specific antigens. ConclusionsK-mer based RNA-seq analysis enables description of cancer transcriptomes at nucleotide precision, independently of prior transcript annotation. Application to lung cancer data uncovered events stemming from a wide variety of transcriptional and postranscriptional mechanisms. Among those events, a significant subset was replicable between cohorts, thus constituting novel RNA hallmarks of cancer. The code is available at: https://github.com/Transipedia/dekupl-lung-cancer-inter-cohort.

bioinformatics↗

bioRxiv2021

Kmerator Suite: design of specific k-mer signatures andautomatic metadata discovery in large RNA-Seq datasets.

The huge body of publicly available RNA-seq libraries is a treasure of functional information allowing to quantify the expression of known or novel transcripts in tissues. However, transcript quantification commonly relies on alignment methods requiring a lot of computational resources and processing time, which does not scale easily to large datasets. K-mer decomposition constitutes a new way to process RNA-seq data for the identification of transcriptional signatures, as k-mers can be used to quantify accurately gene expression in a less resource-consuming way. We present the Kmerator Suite, a set of three tools designed to extract specific k-mer signatures, quantify these k-mers into RNA-seq datasets and quickly visualize large datasets characteristics. The core tool, Kmerator, produces specific k-mers for 97% of human genes, enabling the measure of gene expression with high accuracy in simulated datasets. KmerExploR, a direct application of Kmerator, uses a set of predictor genes specific k-mers to infer metadata including library protocol, sample features or contaminations from RNA-seq datasets. KmerExploR results are visualised through a user-friendly interface. Moreover, we demonstrate that the Kmerator Suite can be used for advanced queries targeting known or new biomarkers such as mutations, gene fusions or long non coding-RNAs for human health applications.

bioinformatics↗

bioRxiv2021

Transcriptomic Insights into the Responses in Leaves Storing Lipid Organelles under Different Irradiances

To increase the nutritional value of forage, transgenic ryegrass known as High Metabolizable Energy (HME) were previously generated that co-express cysteine-oleosin and diacylglycerol O-acyltransferase. HME not only accumulate lipids in the leaf but also has elevated CO2 assimilation and increased biomass. Shading is one of the most influencing factors for ryegrass growth environments particularly in swards. The aim of this study, therefore, was to determine the influence of irradiance levels on photosynthesis and gene expression in the HME leaves when compared with their corresponding non-transformant (NT). Under low light (150-250 {micro}mol m-2 s-1) and standard light (600-1000 {micro}mol m-2 s-1), the HME accumulated more lipid than NT. The previously reported elevated photosynthesis and increased biomass was observed when the HME were grown under standard light but not under low light. Under both light conditions, compared to NT, the HME had upregulated a number of transcripts involved in lipid metabolism, light capturing, photosynthesis, and sugar signalling network while downregulated genes participated in sugar and fructan biosynthesis. We further discuss how the HME differentially manipulated several genes other metabolic pathways including maintenance of redox homeostasis. Combined, the data suggests that the increased photosynthesis capacity in the HME likely corresponds to an increase of micro-lipid sink strength; these are influenced by available light energy and may be related to diffusional and biochemical activities of stomata. Overall, this work provides a clearly understanding of the changes in molecular and biochemical mechanisms underlying the carbon storing as leaf lipid sink of the HME ryegrass. One sentence summaryShading led to increase leaf lipid accumulation but limit the greater photosynthesis trait of high lipid ryegrass which may be related to limitation of biochemical activities of stomata.

molecular biology↗

bioRxiv2021

Locally restricted glucose availability in the embryonic hypocotyl determines seed germination under ABA treatment

O_LIAbiotic stresses directly affect seed germination, plant growth, and reproduction. Seed germination is a complex and energy-demanding process, involving diverse physical, metabolic and cellular events, and is controlled by intrinsic and environmental cues. Abiotic stresses involving abscisic acid (ABA) inhibit seed germination by suppressing physiological processes essential for completion of germination. It remains unclear whether the component tissues of an embryo respond to stress, and are suppressed differentially. C_LIO_LIHere we used a genetically engineered FRET sensor to show that ABA significantly affected the spatiotemporal distribution of glucose (Glc) in lower hypocotyl region. Transcriptome analysis and 14C-Glc uptake assay suggested that Glc limitation in the embryonic hypocotyl was largely due to suppressed sugar partitioning along with enhanced sugar metabolism. The loss-of-function mutants of ABA-induced sucrose-phosphate synthase (SPS) genes accumulated more Glc, leading to ABA insensitivity during germination. In addition, we identified molecular signatures that Glc antagonizes ABA by globally counteracting the ABA influence on gene expression, including expansin (EXP) family genes that are inhibited by ABA. C_LIO_LIThis study presents a new perspective on the interaction between ABA and Glc in response to external stimuli, which restricts Glc availability and thereby controls the transition from seed to seedling. C_LI

plant biology↗

bioRxiv2021

Copy number variation profile-based genomic subtyping of premenstrual dysphoric disorder in Chinese

Premenstrual dysphoric disorder (PMDD) affects nearly 5% women of reproductive age. The symptomatic heterogeneity, along with largely unknown genetics, of PMDD have greatly hindered its effective treatment. In the present study, 127 Chinese PMDD patients of the invasion and depression subtypes clinically differentiated by us earlier were analyzed together with 108 non-PMDD controls for genome-wide copy number variations (CNVs). Germline genomic DNA samples from white blood cells were subjected to AluScan sequencing-based CNV profiling, which enabled clustering of patient samples readily into the V and D groups, dominated by the "invasion" and "depression" clinical subtypes, respectively; the CNVs obtained with 100-kb windows yielded two clusters that were correlated with these subtypes with a consistency of up to 89.8%. Diagnostic correlation- and frequency-based CNV features of either CNV-gain (CNVG) or CNV-loss (CNVL) that could differentiate between V and D subtypes were selected and analyzed. CNVG features located preferentially in S2-phase replicating regions and enriched with steroid hormone biosynthesis pathway of genes were found protective against PMDD. Moreover, machine learning employing the correlation-based CNV features could predict with >80% accuracy whether a genomic sample was D-type, V-type or control. In terms of their CNV profiles, the D- and V-types differed more from one another than from the controls, thereby providing a genomic basis for the clinical D-V subtyping of PMDD. Genome-wide profiling of CNVs, as a new approach to complex disease genetics, has revealed recurrent CNVs and genomic features beyond individual genes and mutations underlying PMDD clinical diversity.

genomics↗

bioRxiv2020

Genetic-variant hotspots and hotspot clusters in the human genome facilitating adaptation while increasing instability

BackgroundGenetic variants, underlining phenotypic diversity, are known to distribute unevenly in the human genome. A comprehensive understanding of the distributions of different genetic variants is important for insights into genetic functions and disorders. MethodsHerein, a sliding-window scan of regional densities of eight kinds of germline genetic variants, including single-nucleotide-polymorphisms (SNPs) and four size-classes of copy-number-variations (CNVs) in the human genome has been performed. ResultsThe study has identified 44,379 hotspots with high genetic-variant densities, and 1,135 hotspot clusters comprising more than one type of hotspots, accounting for 3.1% and 0.2% of the genome respectively. The hotspots and clusters are found to co-localize with different functional genomic features, as exemplified by the associations of hotspots of middle-size CNVs with histone-modification sites, work with balancing and positive selections to meet the need for diversity in immune proteins, and facilitate the development of sensory-perception and neuroactive ligand-receptor interaction pathways in the function-sparse late-replicating genomic sequences. Genetic variants of different lengths co-localize with retrotransposons of different ages on a long-with-young and short-with-all basis. Hotspots and clusters are highly associated with tumour suppressor genes and oncogenes (p < 10-10), and enriched with somatic tumour CNVs and the trait- and disease-associated SNPs identified by genome-wise association studies, exceeding tenfold enrichment in clusters comprising SNPs and extra-long CNVs. ConclusionsIn conclusion, the genetic-variant hotspots and clusters represent two-edged swords that spearhead both positive and negative genomic changes. Their strong associations with complex traits and diseases also open up a potential Common Disease-Hotspot Variant approach to the missing heritability problem.

genomics↗

bioRxiv2020

A bacterial effector uncovers a metabolic pathway involved in resistance to bacterial wilt disease

Bacterial wilt caused by the soil-borne pathogen Ralstonia solanacearum is a devastating disease worldwide. Upon plant colonization, R. solanacearum replicates massively, causing plant wilting and death; collapsed infected tissues then serve as a source of inoculum. In this work, we show that the metabolic pathway mediated by pyruvate decarboxylases (PDCs), activated in response to low oxygen and involved in drought stress tolerance, contributes to resistance against bacterial wilt disease. Arabidopsis and tomato plants with deficient PDC activity are more susceptible to bacterial wilt, and treatment with either pyruvic acid or acetic acid (substrate and product of the PDC pathway, respectively) enhances resistance. An effector protein secreted by R. solanacearum, RipAK, interacts with PDCs and inhibits their oligomerisation and enzymatic activity. This work reveals a metabolic pathway involved in resistance to biotic and abiotic stresses, and a bacterial virulence strategy to promote disease and the completion of the pathogenic life cycle.

plant biology↗

bioRxiv2020

Telmisartan potentiates insulin secretion via ion channels, independent of the AT1 receptor and PPARγ

Angiotensin II type 1 receptor blockers (ARBs), as antihypertensive drugs, have drawn attention for their benefits to individuals with diabetes and prediabetes. However, the effects of ARBs on insulin secretion remain unclear. Here, we investigated the insulinotropic effects of ARBs (telmisartan, valsartan, and irbesartan) and the underlying electrophysiological mechanism in rat islets. We found that only telmisartan among the three ARBs exhibited an insulin secretagogue role. Distinct from other ARBs, telmisartan exerted effects on ion channels including voltage-gated potassium (Kv) channels and voltage-gated Ca2+ channels to promote extracellular Ca2+ influx, thereby potentiating insulin secretion in a glucose-dependent manner. We observed that the peroxisome proliferator-activated receptor {gamma} pathway was not involved in these telmisartan-induced effects. Furthermore, we identified that telmisartan at least directly inhibited Kv2.1 channel through construction of a Chinese hamster ovary cell line with Kv2.1 channel overexpression. Acute exposure of type 2 diabetes model (db/db) mice to a telmisartan dose equivalent to therapeutic doses in humans resulted in lower blood glucose and increased plasma insulin concentration in the oral glucose tolerance test. We further observed the telmisartan-induced insulinotropic and electrophysiological effects on pathological pancreatic islets isolated from db/db mice. Collectively, our results establish an important function of telmisartan distinct from other ARBs in the treatment of diabetes.

cell biology↗

bioRxiv2020

Inferring Causal Direction Between Two Traits in the Presence of Horizontal Pleiotropy with GWAS Summary Data

Orienting the causal relationship between pairs of traits is a fundamental task in scientific research with significant implications in practice, such as in prioritizing molecular targets and modifiable risk factors for developing therapeutic and interventional strategies for complex diseases. A recent method, called Steigers method, using a single SNP as an instrument variable (IV) in the framework of Mendelian randomization (MR), has since been widely applied. We report the following new contributions. First, we propose a single SNP-based alternative, overcoming a severe limitation of Steigers method in simply assuming, instead of inferring, the existence of a causal relationship. We also clarify a condition necessary for the validity of the methods in the presence of hidden confounding. Second, to improve statistical power, we propose combining the results from multiple, and possibly correlated, SNPs. as multiple instruments. Third, we develop three goodness-of-fit tests to check modeling assumptions, including those required for valid IVs. Fourth, by relaxing one of the three IV assumptions in MR, we propose methods, including one Egger regression-like approach and its multivariable version (analogous to multivariable MR), to account for horizontal pleiotropy of the SNPs/IVs, which is often unavoidable in practice. All our methods can simultaneously infer both the existence and (if so) the direction of a causal relationship, largely expanding their applicability over that of Steigers method. Although we focus on uni-directional causal relationships, we also briefly discuss an extension to bi-directional relationships. Through extensive simulations and an application to infer the causal directions between low density lipoprotein (LDL) cholesterol, or high density lipoprotein (HDL) cholesterol, and coronary artery disease (CAD), we demonstrate the superior performance and advantage of our proposed methods over Steigers method and bi-directional MR. In particular, after accounting for horizontal pleiotropy, our method confirmed the well known causal direction from LDL to CAD, while other methods, including bi-directional MR, failed. Author SummaryIn spite of its importance, due to technical challenges, orienting causal relationships between pairs of traits has been largely under-studied. Mendelian randomization (MR) Steigers method has become increasingly used in the last two years. Here we point out several limitations with MR Steigers method and propose alternative approaches. First, MR Steigers method is based on using only one single SNP as the instrument variable (IV), for which we propose a correlation ratio-based method, called Causal Direction-Ratio, or simply CD-Ratio. An advantage of CD-Ratio is its inference of both the existence and (if so) the direction of a causal relationship, in contrast to MR Steigers prior assumption of the existence and its poor performance if the assumption is violated. Furthermore, CD-Ratio can be extended to combine the results from multiple, possibly correlated, SNPs with improved statistical power. Second, we propose two methods, called CD-Egger and CD-GLS, for multiple and possibly correlated SNPs while allowing horizontal pleiotropy. Third, we propose three goodness-of-fit tests to check modeling assumptions for the three proposed methods. Finally, we introduce multivariable CD-Egger, analogous to multivariable MR, as a more robust approach, and an extension of CD-Ratio to cases with possibly bi-directional causal relationships. Our numerical studies demonstrated superior performance of our proposed methods over MR Steiger and bi-directional MR. Our proposed methods, along with freely available software, are expected to be useful in practice for causal inference.

genetics↗

bioRxiv2020

The effect of autophagy and mitochondrial fission on Harderian gland is greater than apoptosis in male hamsters during different photoperiods

Photoperiod is an important factor of mammalian seasonal rhythm. We studied the morphological differences in HG which is a vital photosensitive organ of male striped dwarf hamsters (Cricetulus barabensis), under different photoperiods (short photoperiod, SP; moderate photoperiod, MP; long photoperiod, LP), and further investigated the molecular mechanisms related to these morphological differences. Results showed that body weight, carcass weight, and HG weight were lower in SP and LP. Protein expression of bax/bcl2 and Cytochrome C showed no significant differences, indicating that the level of apoptosis remained stable. Protein aggregation of LC3 and protein expression of LC3II/LC3I were higher in SP than. Furthermore, comparison of changes in the HG ultrastructure demonstrated autolysosome formation in the LP, which suggesting the lowest autophagy level in MP. Protein expression levels of ATP synthase and mitochondrial fission factor were highest in the MP, whereas citrate synthase, dynamin-related protein1, and fission1 remained unchanged in three groups. In summary, the significant up-regulation of autophagy under short and long photoperiod may be the main factor leading to the loss of HG weight and reduced mitochondrial energy supply.

cell biology↗

bioRxiv2020

Studies on trans-sutural distraction osteogenesis-related genes based on transcriptome sequencing

Trans-sutural distraction osteogenesis (TSDO) is an important approach to improve mid-face hypoplasia. In recent years, many studies have been carried out on physical mechanisms of TSDO; however, its specific cytological and molecular mechanisms are still unclear. In this study, we performed transcriptome sequencing analysis in Sprague Dawley rats at 1 and 2 weeks after suture osteogenesis and compared RNA expression levels between experimental and control groups. At one week, enrichment pathways were mainly up-regulated in muscle- and bone-related pathways. By contrast, pathways of the immune system showed a state of inhibition and down-regulation, especially for B cells; the main immune pathways showed significant down-regulation. However, two weeks later, the experimental group showed positive up-regulation of the pathways related to DNA synthesis and replication, cell cycle, and chromosome replication. At the same time, the immune pathways that were down-regulated in the first week were up-regulated in the second week. In other words, the up-regulated muscle- and bone-related pathways show opposite trends. The expression of bone- and myogenesis-related transcriptome was up-regulated and the immune-related pathways were down-regulated in the experimental group at 1 week. At 2 weeks, the pathways related to bone- and muscle were down-regulated, while those related to cell cycle regulation and DNA replication were up-regulated. These results suggest that musculoskeletal-related molecules may play an important role during suture osteogenesis at 1 week, and immune regulation may be involved in this process; however, at 2 weeks, molecules related to cell proliferation and replication may be a major role.

bioinformatics↗

bioRxiv2020

An ectosymbiosis-based mechanism of eukaryogenesis

The mechanisms proposed for eukaryogenesis are divisible into mitochondria-early and mitochondria-late ones, where the mitochondriate-eukaryotes (MTEs) were evolutionary precursors or products of the amitochondriate-eukaryotes (AMIs) respectively. Analysis of prokaryote-to-eukaryote gene transfers in eukaryogenesis showed two tranches of high-intensity transfers from prokaryotes to eukaryotes mediated by endosymbioses that gave rise to mitochondria and chloroplasts, and hundreds of medium-intensity transfers which included the transfer of hydrogenase and pyruvate: ferredoxin oxidoreductase genes from the Thermoanaerobacter-Hungateiclostridium-Sporanaerobacter group to the AMIs. Since 94.5% of these medium-intensity transfers generated more than 100 inter-proteome similarity hits between each donor-recipient pair, they were not readily explicable by horizontal gene transfers (HGTs) or endosymbioses, pointing instead to the participation of a large number of ectosymbiotic transfers. The euryarchaeon Aciduliprofundum boonei (Abo) and the gammaproteobacterium Escherichia coli (Eco) were the foremost contributors of archaeal and bacterial genes for the eukaryotic DNA-apparatus respectively, and the Abo/Eco ratios for the prokaryote-derived genes in eukaryotes decreased from Microsporidia to other AMIs, and even more so in the MTEs. These findings supported an ectosymbiosis-based mechanism of eukaryogenesis with Abo as the Archaeal Parent of Eukarya, and Microsporidia as the eukaryotes phylogenetically closest to the Last Eukaryotic Common Ancestor (LECA).

evolutionary biology↗

bioRxiv2019

Some Statistical Consideration in Transcriptome-Wide Association Studies

Transcriptome-wide association study (TWAS) has become popular in integrating a reference eQTL dataset with an independent main GWAS dataset to identify (putatively) causal genes, shedding mechanistic insights to biological pathways from genetic variants to a GWAS trait mediated by gene expression. Statistically TWAS is a (two-sample) 2-stage least squares (2SLS) method in the framework of instrumental variables analysis for causal inference: in Stage 1 it uses the reference eQTL data to impute a genes expression for the main GWAS data, then in Stage 2 it tests for association between the imputed gene expression and the GWAS trait; if an association is detected in Stage 2, a (putatively) causal relationship between the gene and the GWAS trait is claimed. If a non-linear model or a generalized linear model (GLM) is fitted in Stage 2 (e.g. for a binary GWAS trait), it is known that using only imputed gene expression, as in standard TWAS, in general does not lead to a consistent (i.e. asymptotically unbiased) estimate for the causal effect; accordingly, a variation of 2SLS, called two-stage residual inclusion (2SRI), has been proposed to yield better estimates (e.g. being consistent under suitable conditions). Our main goal is to investigate whether it is necessary or even better to apply 2SRI, instead of the standard 2SLS. In addition, due to the use of imputed gene expression (i.e. with measurement errors), it is known that in general some correction to the standard error estimate of the causal effect estimate has to be applied, while in the standard TWAS no correction is applied. Is this an issue? We also compare one-sample 2SLS with two-sample 2SLS (i.e. the standard TWAS). We used the ADNI data and simulated data mimicking the ADNI data to address the above questions. At the end, we conclude that, in practice with the large sample sizes and small effect sizes of genetic variants, the standard TWAS performs well and is recommended.

genetics↗

bioRxiv2019

Descent of Bacteria and Eukarya from an archaeal root of life

The three biological domains delineated based on SSU rRNAs are confronted by uncertainties regarding the relationship between Archaea and Bacteria, and the origin of Eukarya. Herein the homologies between the paralogous valyl-tRNA and isoleucyl-tRNA synthetases in a wide spectrum of species revealed vertical gene transmission from an archaeal root of life through a Primitive Archaea Cluster to an Ancestral Bacteria Cluster of species. The higher homologies of the ribosomal proteins (rProts) of eukaryotic Giardia toward archaeal relative to bacterial rProts established that an archaeal-parent rather than a bacterial-parent underwent genome merger with an alphaproteobacterium to generate Eukarya. Moreover, based on the top-ranked homology of the proteins of Aciduliprofundum among archaea toward the Giardia and Trichomonas proteomes and the pyruvate phosphate dikinase of Giardia, together with their active acquisition of exogenous bacterial genes plausibly through foodchain gene adoption, the Aciduliprofundum archaea were identified as leading candidates for the archaeal-parent of Eukarya.

evolutionary biology↗

bioRxiv2019

A bacterial effector protein prevents MAPK-mediated phosphorylation of SGT1 to suppress plant immunity

Nucleotide-binding domain and leucine-rich repeat-containing (NLR) proteins function as sensors that perceive pathogen molecules and activate immunity. In plants, the accumulation and activation of NLRs is regulated by SUPPRESSOR OF G2 ALLELE OF skp1 (SGT1). In this work, we found that an effector protein named RipAC, secreted by the plant pathogen Ralstonia solanacearum, associates with SGT1 to suppress NLR-mediated SGT1-dependent immune responses, including those triggered by another R. solanacearum effector, RipE1. RipAC does not affect the accumulation of SGT1 or NLRs, or their interaction. However, RipAC inhibits the interaction between SGT1 and MAP kinases, and the phosphorylation of a MAPK target motif in the C-terminal domain of SGT1. Such phosphorylation is enhanced upon activation of immune signaling, leads to the release of the interaction between SGT1 and NLRs, and contributes to the activation of NLR-mediated responses. Additionally, SGT1 phosphorylation contributes to resistance against R. solanacearum, and this is particularly evident in the absence of RipAC. Our results shed light onto the mechanism of activation of NLR-mediated immunity, and suggest a positive feedback loop between MAPK activation and SGT1-dependent NLR activation.

plant biology↗

bioRxiv2019

The receptor-like kinases BAM1 and BAM2 promote the cell-to-cell movement of miRNA in the root stele to regulate xylem patterning

Xylem patterning in the root is established through the creation of opposing gradients of miRNAs and their targets, enabled by the cell-to-cell spread of the former. The miRNAs involved in xylem patterning, miR165/6, move through plasmodesmata, but how their trafficking is regulated remains elusive. Here, we describe that the receptor-like kinases BAM1/2 are required for the intercellular movement of miR165/6 in the stele and hence proper xylem patterning in the root.

plant biology↗

bioRxiv2019

Integrating multi-network topology for gene function prediction using deep neural networks

MotivationThe emerging of abundant biological networks, which benefit from the development of advanced high-throughput techniques, contribute to describing and modeling complex internal interactions among biological entities such as genes and proteins. Multiple networks provide rich information for inferring the function of genes or proteins. To extract functional patterns of genes based on multiple heterogeneous networks, network embedding-based methods, aiming to capture non-linear and low-dimensional feature representation based on network biology, have recently achieved remarkable performance in gene function prediction. However, existing methods mainly do not consider the shared information among different networks during the feature learning process. Thus, we propose a novel multi-networks embedding-based function prediction method based on semi-supervised autoencoder and feature convolution neural network, named DeepMNE-CNN, which captures complex topological structures of multi-networks and takes the correlation among multi-networks into account. ResultsWe design a novel semi-supervised autoencoder method to integrate multiple networks and generate a low-dimensional feature representation. Then we utilize a convolutional neural network based on the integrated feature embedding to annotate unlabeled gene functions. We test our method on both yeast and human dataset and compare with four state-of-the-art methods. The results demonstrate the superior performance of our method over four state-of-the-art algorithms. From the future explorations, we find that semi-supervised autoencoder based multi-networks integration method and CNN-based feature learning methods both contribute to the task of function prediction. AvailabilityDeepMNE-CNN is freely available at https://github.com/xuehansheng/DeepMNE-CNN

bioinformatics↗

bioRxiv2018

Reversing Abnormal Neural Development by Inhibiting OLIG2 in Down Syndrome Human iPSC Brain Organoids and Neuronal Mouse Chimeras

Down syndrome (DS) is a common neurodevelopmental disorder, and cognitive defects in DS patients may arise form imbalances in excitatory and inhibitory neurotransmission. Understanding the mechanisms underlying such imbalances may provide opportunities for therapeutic intervention. Here, we show that human induced pluripotent stem cells (hiPSCs) derived from DS patients overproduce OLIG2+ ventral forebrain neural progenitors. As a result, DS hiPSC-derived cerebral organoids excessively produce specific subclasses of GABAergic interneurons and cause impaired recognition memory in neuronal chimeric mice. Increased OLIG2 expression in DS cells directly upregulates interneuron lineage-determining transcription factors. shRNA-mediated knockdown of OLIG2 largely reverses abnormal gene expression in early-stage DS neural progenitors, reduces interneuron production in DS organoids and chimeric mouse brains, and improves behavioral deficits in DS chimeric mice. Thus, altered OLIG2 expression may underlie neurodevelopmental abnormalities and cognitive defects in DS patients.

neuroscience↗