Biology subjects

Cheng, H.

Publications and source records attributed to Cheng, H..

At least 127 records · Page 7Linked to original sources

bioRxiv2021

Extend Mixed Models to Multi-layer Neural Networks for Genomic Prediction Including Intermediate Omics Data

With the growing amount and diversity of intermediate omics data complementary to genomics (e.g., DNA methylation, gene expression, and protein abundance), there is a need to develop methods to incorporate intermediate omics data into conventional genomic evaluation. The omics data helps decode the multiple layers of regulation from genotypes to phenotypes, thus forms a connected multi-layer network naturally. We developed a new method named NN-LMM to model the multiple layers of regulation from genotypes to intermediate omics features, then to phenotypes, by extending conventional linear mixed models ("LMM") to multi-layer artificial neural networks ("NN"). NN-LMM incorporates intermediate omics features by adding middle layers between genotypes and phenotypes. Linear mixed models (e.g., pedigree-based BLUP, GBLUP, Bayesian Alphabet, single-step GBLUP, or single-step Bayesian Alphabet) can be used to sample marker effects or genetic values on intermediate omics features, and activation functions in neural networks are used to capture the nonlinear relationships between intermediate omics features and phenotypes. NN-LMM had significantly better prediction performance than the recently proposed single-step approach for genomic prediction with intermediate omics data. Compared to the single-step approach, NN-LMM can handle various patterns of missing omics measures, and allows nonlinear relationships between intermediate omics features and phenotypes. NN-LMM has been implemented in an open-source package called "JWAS".

genetics↗

bioRxiv2021

Smart3-ATAC: a highly sensitive method for joint accessibility and full-length transcriptome analysis in single cells

Joint single-cell measurements of gene expression and DNA regulatory element activity holds great promise as a tool to understand transcriptional regulation. Towards this goal we have developed Smart3-ATAC, a highly sensitive method which allows joint mRNA and chromatin accessibility analysis genome wide in single cells. With Smart3-ATAC, we are able to obtain the highest possible quality measurements per cell. The method combines transcriptomic profiling based on the highly sensitive Smart-seq3 protocol on cytosolic mRNA, with a novel low-loss single-cell ATAC (scATAC) protocol to measure chromatin accessibility. Compared to current droplet multiome methods, the yield of both the scATAC protocol and mRNA-seq protocol is markedly higher.

systems biology↗

bioRxiv2021

Hoxb5 reprograms murine multipotent blood progenitors into hematopoietic stem cell-like cells

The expression of transcription factor Hoxb5 specifically marks the functional hematopoietic stem cells (HSC) in mice. However, our recent work demonstrated that ectopic expression of Hoxb5 exerted little effect on HSC but could convert B cell progenitors into functional T cells in vivo. Thus, cell type- and development stage-specific roles of Hoxb5 in hematopoietic hierarchy await more extensive exploration. Here, with a mouse strain engineered with conditional expression of Hoxb5, we unveiled that induced expression of Hoxb5 in mouse multipotent progenitor cells (MPP) led to the generation of a de novo Sca1+cKit+Mac1+CD48+ (Mac1+CD48+SK) cell type, which has the ability to repopulate long-term multi-lineage hematopoiesis in serial transplant recipients. RNA-seq analyses showed that Mac1+CD48+SK cells exhibited an acquired machinery of DNA replication and cell division, which resembled nature fetal liver HSC cells (FL HSC). In short, our current study uncovers that Hoxb5 is able to empower MPP with self-renewal potential, thereby providing new strategies to reprogram blood progenitor cells into HSC-like cells.

cell biology↗

bioRxiv2021

Actin filaments act as a size-dependent diffusion barrier around centrosomes

The centrosome, a non-membranous organelle, constrains various soluble molecules locally to execute its functions. As the centrosome is surrounded by various dense components, we hypothesized that the centrosome may be bordered by a putative diffusion barrier. After quantitatively measuring the trapping kinetics of soluble proteins of varying size at centrosomes by a chemically inducible diffusion trapping assay, we found that centrosomes were highly accessible to soluble molecules with a Stokes radius of [≤] 5.1 nm, whereas larger molecules rarely reach centrosomes, indicating the existence of a size-dependent diffusion barrier at centrosomes. The permeability of barriers was tightly regulated by branched actin filaments outside of centrosomes. Such barrier gated the microtubule nucleation. We propose that actin filaments spatiotemporally constrain the distribution of molecules at centrosomes in a size-dependent manner. Significance StatementCentrosome maintains its microenvironment without membrane. Whether the dense protein complexes outside centrosomes including pericentriolar matrix, microtubules, and branched actin filaments provide physical obstruction is unclear yet. We here established a series of new tools for quantitative evaluation of the diffusion rates of varisized soluble proteins in different sub-compartments of centrosomes. Our results demonstrated that branched actin filaments, but not pericentriolar matrix or microtubules, around centrosome have acted as a size-dependent diffusion barrier and physically constrain centrosome microtubule nucleation.

cell biology↗

bioRxiv2021

iHypoxia: an integrative database of the expression dynamics of proteins in response to hypoxia in animals

Decreased oxygen concentrations (hypoxia) outside of the physiological range may severely subvert cell, tissue, and organism survival. Mammals have evolved mechanisms to sense hypoxia and induce a series of hypoxic responses. In recent years, high-throughput techniques have greatly promoted global perturbation studies of protein expression during hypoxia, and these studies have contributed to the understanding of the complex regulatory networks of hypoxia. In this study, we developed an integrated resource for the expression dynamics of proteins in response to hypoxia (iHypoxia), which contains 1,629 expression events of 1,215 proteins identified by low-throughput experiments (LTEs) and 154,953 quantitative expression events of 36,194 proteins identified by high-throughput experiments (HTEs) from five mammals that exhibit a response to hypoxia. Various experimental details such as the hypoxic experimental conditions, expression patterns, and samples were carefully collected and integrated. In addition, we conducted an orthologous search and identified 581,763 proteins that may respond to hypoxia among 50 animals. An enrichment analysis of human proteins identified from LTEs showed that these proteins were enriched in certain drug targets and cancer genes. The annotation of known posttranslational modification (PTM) sites to proteins identified by LTEs revealed that these proteins underwent extensive PTMs, particularly phosphorylation, ubiquitination and acetylation. Based on the results, iHypoxia provides a convenient and user-friendly method for users to obtain hypoxia-related information of interest. We anticipate that iHypoxia, which is freely accessible at http://ihypoxia.omicsbio.info, will advance the understanding of hypoxia and serve as a valuable data resource.

bioinformatics↗

bioRxiv2021

Video-evoked fMRI BOLD responses are highly consistent across different data acquisition sites

Naturalistic imaging paradigms, in which participants view complex videos in the scanner, are increasingly used in human cognitive neuroscience. Videos evoke temporally synchronized brain responses that are similar across subjects as well as within subjects, but the reproducibility of these brain responses across different data acquisition sites has not yet been quantified. Here we characterize the consistency of brain responses across independent samples of participants viewing the same videos in fMRI scanners at different sites (Indiana University and Caltech). We compared brain responses collected at these different sites for two carefully matched datasets with identical scanner models, acquisition, and preprocessing details, along with a third unmatched dataset in which these details varied. Our overall conclusion is that for matched and unmatched datasets alike, video-evoked brain responses have high consistency across these different sites, both when compared across groups and across pairs of individuals. As one might expect, differences between sites were larger for unmatched datasets than matched datasets. Residual differences between datasets could in part reflect participant-level variability rather than scanner- or data-related effects. Altogether our results indicate promise for the development and, critically, generalization of video fMRI studies of individual differences in healthy and clinical populations alike.

neuroscience↗

bioRxiv2021

Functional network topography of the medial entorhinal cortex

The medial entorhinal cortex (MEC) creates a map of local space, based on the firing patterns of grid, head direction (HD), border, and object-vector (OV) cells. How these cell types are organized anatomically is debated. In-depth analysis of this question requires collection of precise anatomical and activity data across large populations of neurons during unrestrained behavior, which neither electrophysiological nor previous imaging methods fully afford. Here we examined the topographic arrangement of spatially modulated neurons in MEC and adjacent parasubiculum using miniaturized, portable two-photon microscopes, which allow mice to roam freely in open fields. Grid cells exhibited low levels of co-occurrence with OV cells and clustered anatomically, while border, HD and OV cells tended to intermingle. These data suggest that grid-cell networks might be largely distinct from those of border, HD and OV cells and that grid cells exhibit strong coupling among themselves but weaker links to other cell types. Highlights- Grid and object vector cells show low levels of regional co-occurrence - Grid cells exhibit the strongest tendency to cluster among all spatial cell types - Grid cells stay separate from border, head direction and object vector cells - The territories of grid, head direction and border cells remain stable over weeks

neuroscience↗

bioRxiv2021

A low-cost greenhouse-based high-throughput phenotyping platform for genetic studies: a case study in maize under inoculation with plant growth-promoting bacteria

Greenhouse-based high-throughput phenotyping (HTP) presents a useful approach for studying novel plant growth-promoting bacteria (PGPB). Despite the potential of this approach to leverage genetic variability for breeding new maize cultivars exhibiting highly stable symbiosis with PGPB, greenhouse-based HTP platforms are not yet widely used because they are highly expensive; hence, it is challenging to perform HTP studies under a limited budget. In this study, we built a low-cost greenhouse-based HTP platform to collect growth-related image-derived phenotypes. We assessed 360 inbred maize lines with or without PGPB inoculation under nitrogen-limited conditions. Plant height, canopy coverage, and canopy volume obtained from photogrammetry were evaluated five times during early maize development. A plant biomass index was constructed as a function of plant height and canopy coverage. Inoculation with PGPB promoted plant growth. Phenotypic correlations between the image-derived phenotypes and manual measurements were at least 0.6. The genomic heritability estimates of the image-derived phenotypes ranged from 0.23 to 0.54. Moderate-to-strong genomic correlations between the plant biomass index and shoot dry mass (0.24-0.47) and between HTP-based plant height and manually measured plant height (0.55-0.68) across the developmental stages showed the utility of our HTP platform. Collectively, our results demonstrate the usefulness of the low-cost HTP platform for large-scale genetic and management studies to capture plant growth. Core ideasO_LIA low-cost greenhouse-based HTP platform was developed. C_LIO_LIImage-derived phenotypes presented moderate to high genomic heritabilities and correlations. C_LIO_LIPlant growth-promoting bacteria can improve plant resilience under nitrogen-limited conditions. C_LI

genetics↗

bioRxiv2021

Early megakaryocyte lineage-committed progenitors in adult mouse bone marrow

Hematopoietic stem cells (HSCs) have been considered to progressively lose their self-renewal and differentiation potentials prior to the commitment to each blood lineage. However, recent studies have suggested that megakaryocyte progenitors are generated at the level of HSCs. In this study, we newly identified early megakaryocyte lineage-committed progenitors (MgPs) in CD201-CD48- cells and CD48+ cells separated from the CD150+CD34-Kit+Sca-1+Lin- HSC population of the bone marrow in C57BL/6 mice. Single-cell transplantation and single-cell colony assay showed that MgPs, unlike platelet-biased HSCs, had little repopulating potential in vivo, but formed larger megakaryocyte colonies in vitro (on average eight megakaryocytes per colony) than did previously reported megakaryocyte progenitors (MkPs). Single-cell RNA-sequencing supported that these MgPs lie between HSCs and MkPs along the megakaryocyte differentiation pathway. Single-cell colony assay and single-cell RT-PCR analysis suggested the coexpression of CD41 and Pf4 is associated with megakaryocyte colony-forming activity. Single-cell colony assay of a small number of cells generated from single HSCs in culture suggested that MgPs are not direct progeny of HSCs. In this study, we propose a differentiation model in which HSCs give rise to MkPs through MgPs.

cell biology↗

bioRxiv2021

Previously unrecognized non-reproducible antibody-antigen interactions and their implications for diagnosis of viral infections including COVID-19

Antibody-antigen (Ab-Ag) interactions are canonically described by a model which exclusively accommodates non-interaction (0) or reproducible-interaction (RI) states, yet this model is inadequate to explain often-encountered non-reproducible signals. Here, by monitoring diverse experimental systems and confirmed COVID-19 clinical sera using a peptide microarray, we observed that non-specific interactions (NSI) comprise a substantial proportion of non-reproducible antibody-based results. This enabled our discovery and capacity to reliably identify non-reproducible Ab-Ag interactions (NRI), as well as our development of a powerful explanatory model ("0-RI-NRI-Hook four-state model") that is [mAb]-dependent, regardless of specificity, which ultimately shows that both NSI and NRI are not predictable yet certain-to-happen. In experiments using seven FDA-approved mAb drugs, we demonstrated the use of NSI counts in predicting epitope type. Beyond challenging the centrality of Ab-Ag interaction specificity data in serology and immunology, our discoveries also facilitated the rapid development of a serological test with uniquely informative COVID-19 diagnosis performance.

immunology↗

bioRxiv2021

Allele-resolved single-cell multi-omics uncovers the dynamics and transcriptional kinetics of X-chromosome upregulation

X-chromosome inactivation (XCI) and upregulation (XCU) are the major opposing chromosome-wide modes of gene regulation that collectively achieve dosage compensation in mammals, but the regulatory link between the two remains elusive. Here, we use allele-resolved single-cell RNA-seq combined with chromatin accessibility profiling to finely dissect the separate effects of XCI and XCU on RNA levels during mouse development. We uncover that balanced X dosage is flexibly attained through expression tuning by XCU in a sex- and lineage-specific manner along varying degrees of XCI and across developmental and cellular states. Male blastomeres achieve XCU upon zygotic genome activation while females experience two distinct waves of XCU, upon imprinted- and random XCI, and ablation of Xist impedes female XCU. Contrary to widely established models of mammalian dosage compensation, naive female embryonic cells carrying two active X chromosomes do not exhibit upregulation but express both alleles at basal level, yet collectively exceeding the RNA output of a single hyperactive allele. We show, in vivo and in vitro, that XCU is kinetically driven by X-specific modulation of transcriptional burst frequency, coinciding with increased compartmentalization of the hyperactive allele. Altogether, our data provide unprecedented insights into the dynamics of mammalian XCU, prompting a revised model of the chain in events of allelic regulation by XCU and XCI in unitedly achieving stable cellular levels of X-chromosome transcripts.

genomics↗

bioRxiv2021

WDR82-binding long non-coding RNA lncEry controls mouse erythroid differentiation and maturation

Hematopoietic differentiation is controlled by both genetic and epigenetic regulators. Long non-coding RNAs (lncRNAs) have been demonstrated to be important for normal hematopoiesis, but their function in erythropoiesis needs to be further explored. We profiled the transcriptomes of 16 murine hematopoietic cell populations by deep RNA-sequencing and identified a novel lncRNA, Gm15915, that was highly expressed in erythroid-related progenitors and erythrocytes. For this reason, we named it lncEry. We also identified a novel lncEry isoform, which was also the principal transcript that has not been reported before. LncEry depletion impaired erythropoiesis, indicating the important role of the lncRNA in regulating erythroid differentiation and maturation. Mechanistically, we found that lncEry interacted with WD repeat-containing protein 82 (WDR82) to promote the transcription of Klf1 and globin genes and thus control the early and late stages of erythropoiesis, respectively. These findings identified lncEry as an important player in the transcriptional regulation of erythropoiesis.

cell biology↗

bioRxiv2021

Fast alignment and preprocessing of chromatin profiles with Chromap

We present Chromap, an ultrafast method for aligning and preprocessing high throughput chromatin profiles. Chromap is comparable to BWA-MEM and Bowtie2 in alignment accuracy and is over 10 times faster than traditional workflows on bulk ChIP-seq / Hi-C profiles and than 10x Genomics CellRanger v2.0.0 pipeline on single-cell ATAC-seq profiles.

bioinformatics↗

bioRxiv2021

Towards a Comprehensive Variation Benchmark for Challenging Medically-Relevant Autosomal Genes

The repetitive nature and complexity of multiple medically important genes make them intractable to accurate analysis, despite the maturity of short-read sequencing, resulting in a gap in clinical applications of genome sequencing. The Genome in a Bottle Consortium has provided benchmark variant sets, but these excluded some medically relevant genes due to their repetitiveness or polymorphic complexity. In this study, we characterize 273 of these 395 challenging autosomal genes that have multiple implications for medical sequencing. This extended, curated benchmark reports over 17,000 SNVs, 3,600 INDELs, and 200 SVs each for GRCh37 and GRCh38 across HG002. We show that false duplications in either GRCh37 or GRCh38 result in reference-specific, missed variants for short- and long-read technologies in medically important genes including CBS, CRYAA, and KCNE1. Our proposed solution improves variant recall in these genes from 8% to 100%. This benchmark will significantly improve the comprehensive characterization of these medically relevant genes and guide new method development.

genomics↗

bioRxiv2021

The complete sequence of a human genome

In 2001, Celera Genomics and the International Human Genome Sequencing Consortium published their initial drafts of the human genome, which revolutionized the field of genomics. While these drafts and the updates that followed effectively covered the euchromatic fraction of the genome, the heterochromatin and many other complex regions were left unfinished or erroneous. Addressing this remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium has finished the first truly complete 3.055 billion base pair (bp) sequence of a human genome, representing the largest improvement to the human reference genome since its initial release. The new T2T-CHM13 reference includes gapless assemblies for all 22 autosomes plus Chromosome X, corrects numerous errors, and introduces nearly 200 million bp of novel sequence containing 2,226 paralogous gene copies, 115 of which are predicted to be protein coding. The newly completed regions include all centromeric satellite arrays and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies for the first time.

genomics↗

bioRxiv2021

Reduced graphene oxide membrane as supporting film for high-resolution cryo-EM

Although single-particle cryogenic electron microscopy (cryo-EM) has been applied extensively for elucidating many crucial biological mechanisms at the molecular level, this technique still faces critical challenges, the major one of which is to prepare the high-quality cryo-EM specimen. Aiming to achieve a more reproducible and efficient cryo-EM specimen preparation, novel supporting films including graphene-based two-dimensional materials have been explored in recent years. Here we report a robust and simple method to fabricate EM grids coated with single- or few-layer reduced graphene oxide (RGO) membrane in large batch for high-resolution cryo-EM structural determination. The RGO membrane has decreased interlayer space and enhanced electrical conductivity in comparison to regular graphene oxide (GO) membrane. Moreover, we found that the RGO supporting film exhibited nice particle-absorption ability, thus avoiding the air-water interface problem. More importantly, we found that the RGO supporting film is particularly useful in cryo-EM reconstruction of sub-100 kDa biomolecules at near-atomic resolution, as exemplified by the study of RBD-ACE2 complex and other small protein molecules. We envision that the RGO membranes can be used as a robust graphene-based supporting film in cryo-EM specimen preparation.

biophysics↗

bioRxiv2021

Interpretable Artificial Neural Networks incorporating Bayesian Alphabet Models for Genome-wide Prediction and Association Studies

In conventional linear models for whole-genome prediction and genome-wide association studies (GWAS), it is usually assumed that the relationship between genotypes and phenotypes is linear. Bayesian neural networks have been used to account for non-linearity such as complex genetic architectures. Here, we introduce a method named NN-Bayes, where "NN" stands for neural networks, and "Bayes" stands for Bayesian Alphabet models, including a collection of Bayesian regression models such as BayesA, BayesB, BayesC, Bayesian LASSO, and BayesR. NN-Bayes incorporates Bayesian Alphabet models into non-linear neural networks via hidden layers between SNPs and observed traits. Thus, NN-Bayes attempts to improve the performance of genome-wide prediction and GWAS by accommodating non-linear relationships between the hidden nodes and the observed trait, while maintaining genomic interpretability through the Bayesian regression models that connect the SNPs to the hidden nodes. For genomic interpretability, the posterior distribution of marker effects in NN-Bayes is inferred by Markov chain Monte Carlo (MCMC) approaches and used for inference of association through posterior inclusion probabilities (PIPs) and window posterior probability of association (WPPA). In simulation studies with dominance and epistatic effects, performance of NN-Bayes was significantly better than conventional linear models for both GWAS and whole-genome prediction, and the differences on prediction accuracy were substantial in magnitude. In real data analyses, for the soy dataset, NN-Bayes achieved significantly higher prediction accuracies than conventional linear models, and results from other four different species showed that NN-Bayes had similar prediction performance to linear models, which is potentially due to the small sample size. Our NN-Bayes is optimized for high-dimensional genomic data and implemented in an open-source package called "JWAS". NN-Bayes can lead to greater use of Bayesian neural networks to account for non-linear relationships due to its interpretability and computational performance.

genetics↗

bioRxiv2021

BTBD9 is a novel component of IGF signaling and regulates manganese-induced dopaminergic dysfunction

Restless legs syndrome (RLS) is a common neurological disorder associated with iron deficiency and dopaminergic (DAergic) neuronal dysfunction. BTBD9 is a genetic risk factor for RLS. However, its molecular function remains largely unknown. Here, we report the interaction between BTBD9, manganese (Mn) and insulin/insulin-like growth factor (IGF) signaling in Caenorhabditis elegans, mouse Neuro2a cells and humans. We found that elevated Mn downregulated BTBD9 mRNA levels; in turn, BTBD9 expression attenuated Mn-induced cellular stress and dopaminergic neurodegeneration. As Mn is a known co-factor for insulin receptor and IGF-1 receptor, which activates IGF signaling, we posited that BTBD9 negatively regulates IGF signaling. Our results showed that the protective effects of BTBD9 against Mn toxicity were dependent on the forkhead box O (FOXO) protein. Furthermore, BTBD9 overexpression significantly elevated FOXO level and decreased PKB level, while phosphoinositide-dependent kinase-1 (PDK1) level remained unchanged. We conclude that BTBD9 acts as a key component in the IGF signaling pathway. Meanwhile, the roles of Mn in DAergic neurotoxicity and regulating BTBD9 shed new light on the etiology of RLS.

neuroscience↗