Biology subjects

Cheng, H.

Publications and source records attributed to Cheng, H..

At least 91 records · Page 5Linked to original sources

bioRxiv2023

Using encrypted genotypes and phenotypes for collaborative genomic analyses to maintain data confidentiality

To adhere to and capitalize on the benefits of the FAIR (Findable, Accessible, Interoperable and Reusable) principles in agricultural genome-to-phenome studies, it is crucial to address privacy and intellectual property issues that prevent sharing and reuse of data in research and industry. Direct sharing of genotype and phenotype data is often prohibited due to intellectual property and privacy concerns. Thus there is a pressing need for encryption methods that obscure confidential aspects of the data, without affecting the outcomes of certain statistical analyses. A homomorphic encryption method for genotypes and phenotypes (HEGP) has been proposed for single-marker regression in genome-wide association studies using linear mixed models with Gaussian errors. This methodology permits frequentist likelihood-based parameter estimation and inference. In this paper, we extend HEGP to broader applications in genome-to-phenome analyses. We show that HEGP is suited to commonly used linear mixed models for genetic analyses of quantitative traits including GBLUP and RR-BLUP, as well as Bayesian variable selection methods (e.g., those in Bayesian Alphabet), for genetic parameter estimation, genomic prediction, and genome-wide association studies. By advancing the capabilities of HEGP, we offer researchers and industry professionals a secure and efficient approach for collaborative genomic analyses while preserving data confidentiality.

genetics↗

bioRxiv2023

Harnessing Landrace Diversity Empowers Wheat Breeding for Climate Resilience

Breeding crops resilient to climate change is urgently needed to help ensure food security. A key challenge is to harness genetic diversity to optimise adaptation, yield, stress resilience and nutrition. We examined the genetic and phenotypic diversity of the A.E. Watkins landrace collection of bread wheat (Triticum aestivum), a major global cereal, through whole-genome re-sequencing (827 Watkins landraces and 208 modern cultivars) and in-depth field evaluation spanning a decade. We discovered that modern cultivars are derived from just two of the seven ancestral groups of wheat, leaving five groups as previously untapped sources for breeding. This provides access to landrace-specific functional variations using structured germplasm, genotyping and informatics resources. Employing complementary genetic populations and approaches, we identified thousands of high-resolution quantitative trait loci (QTL) and significant marker-trait associations for major traits, revealing many Watkins-unique loci that can confer superior traits in modern wheat. Furthermore, we identified and functionally verified causative genes for climate-change adaptation, nutritional enhancement and resistance to wheat blast. Finally, we assessed the phenotypic effects of 44,338 Watkins-unique haplotypes, introgressed from 143 prioritised QTL in the context of modern cultivars, bridging the gap between landrace diversity and current breeding. This study establishes a framework for systematically utilising genetic diversity in crop improvement to achieve sustainable food security.

plant biology↗

bioRxiv2023

Direct serotonin release in humans shapes decision computations within aversive environments

The role of serotonin in human behaviour is critically informed by approaches which allow in vivo modification of synaptic serotonin. However, characterising the effects of increased serotonin signalling in human models of behaviour is challenging given the limitations of available experimental probes (e.g., SSRIs). Here we use a now accessible approach to directly increase synaptic serotonin in humans - a selective serotonin releasing agent - and examine its influence on domains of behaviour historically considered core functions of serotonin. Computational techniques including reinforcement learning and drift diffusion modelling were fit to observed behaviour. Reinforcement learning models revealed that increased synaptic serotonin reduced sensitivity specifically for outcomes in aversive but not appetitive contexts. Furthermore, increasing synaptic serotonin enhanced behavioural inhibition, and shifted bias towards impulse control during exposure to aversive emotional probes. These effects were seen in the context of overall improvements in memory for neutral verbal information. Our findings highlight the direct effects of increased synaptic serotonin on human behaviour, underlining its critical role in guiding decision-making within aversive and neutral contexts, and offering broad implications for longstanding theories of central serotonin function.

neuroscience↗

bioRxiv2023

A role for LGI1 in regulating pain sensitivity.

Chronic pain represents a major unmet clinical need. Neuropathic pain, that is pain arising due to damage or disease of the somatosensory nervous system, represents a sizeable proportion of chronic pain cases, affecting around 8% of the general population. Neuronal hyperexcitability is a key driver of neuropathic pain. Leucine glioma inactivated 1 (LGI1), is a secreted protein known to regulate excitability within the nervous system and is the target of autoantibodies from neuropathic pain patients. Therapies that block or reduce antibody levels are highly effective at relieving pain in these patients, suggesting that LGI1 has an important role in clinical pain. Here we have studied the role of LGI1 in regulating pain using mouse models to specifically ablate LGI1 in neuron populations. LGI1 has been well studied at the level of the brain. Here we show that LGI1 is highly expressed in dorsal root ganglion (DRG) neurons and in dorsal horn neurons of the spinal cord. Using transgenic mice, we ablated LGI1, either specifically in nociceptors (LGI1fl/Nav1.8(+/-)), or in all DRG and spinal neurons (LGI1fl/Hoxb8(+/-)). On acute pain assays, mild phenotypes were observed when compared to littermate controls with limited changes in DRG neuron excitability. No differences were seen in the first phase of the formalin test, however LGI1fl/Hoxb8(+/-) mice displayed a significant increase in nocifensive behaviours in the second phase compared to littermate controls. Using the spared nerve injury model, we assessed the impact of LGI1 ablation on neuropathic pain-like behaviours. LGI1fl/Nav1.8(+/-) mice showed no differences in nerve injury induced mechanical hypersensitivity, brush-evoked allodynia or spontaneous pain behaviour compared to controls. However, LGI1fl/Hoxb8(+/-) mice showed a significant exacerbation of mechanical hypersensitivity and allodynia. These data show that LGI1 has a role in regulating pain sensitivity particularly in the context of nerve injury. We suggest this effect is likely mediated at the spinal level since no differences were observed following specific ablation of LGI1 in nociceptors. Neurons in dorsal horn of the spinal cord are important in gating nerve injury induced mechanical pain and our findings suggest that LGI1 plays an important role in this process.

neuroscience↗

bioRxiv2023

Deep Whole-Genome Resequencing of Marek's Disease Virus Strains Reveals Intrastrain Variation

Current strategies to understand the molecular basis of Mareks disease virus (MDV) virulence primarily consist of cataloguing divergent nucleotides between strains with different phenotypes. However, each MDV strain is typically represented by a single consensus genome despite the confirmed existence of mixed viral populations. To assess the reliability of single-consensus interstrain genomic comparisons, we obtained two additional consensus genomes of vaccine strain CVI988 (Rispens) and two additional consensus genomes of the very virulent strain Md5 by sequencing viral stocks and cultured field isolates. In conjunction with the published genomes of CVI988 and Md5, this allowed us to perform 3-way comparisons between consensus genomes of the same strain. We found that consensus genomes of CVI988 can vary in as many as 236 positions involving 13 open reading frames (ORFs). In contrast, we found that Md5 genomes varied only in 11 positions involving a single ORF. Phylogenomic analyses showed all three Md5 consensus genomes clustered closely together, while also showing that CVI988GenBank.BAC diverged from CVI988Pirbright.lab and CVI988USDA.PA.field. Comparison of CVI988 consensus genomes revealed 19 SNPs in the unique regions of CVI988GenBank.BAC that were not present in either CVI988Pirbright.lab or CVI988USDA.PA.field. Finally, we evaluated the genomic heterogeneity of CVI988 and Md5 populations by identifying positions with >2% read support for alternative alleles in two ultra-deeply sequenced samples. We were able to confirm that both populations of CVI988 and Md5 were mixed, exhibiting a total of 29 and 27 high-confidence minor variant positions, respectively. We did not find any evidence of minor variants in the positions corresponding to the 19 SNPs in the unique regions of CVI988GenBank.BAC. Taken together, our findings confirm that consensus genomes of the same strain of MDV can vary and suggest that multiple consensus genomes per strain are needed in order to maximize the accuracy of interstrain genomic comparisons.

microbiology↗

bioRxiv2023

BNIP3-mediated mitophagy boosts the competitive dominant growth of lenvatinib resistant cells via reprogramming energy metabolism in HCC

Although increasing studies has demonstrated that cell competition widely involved in the growth and homeostasis of multicellular organisms is closely linked to tumorigenesis and development, the mechanistic contributions to the association between tumor cell competition-driven heterogeneity and drug resistance remains ill-defined. In our study, lenvitinib-resistant hepatocellular carcinoma (HCC) cells display obviously competitive growth dominance against sensitive cells through reprogramming energy metabolism. Mechanistically, when BCL2 interacting protein3 (BNIP3) overexpression activates mitophagy activity in lenvatinib-resistant HCC cells, energy imbalance signal caused by reduced mitochondrial oxidative phosphorylation levels provokes the phosphorylation of AMP-activated protein kinase (AMPK) sensor; subsequently, enabled AMPK specifically targets enolase 2 (ENO2) to enhance glycolysis and eventually promots the competitive capacity and dominant growth. Of note, BNIP3 deficiency shows certain inhibition of cell competition outcome. Our findings emphasize a vital role for BNIP3-AMPK-ENO2 signaling in maintaining the competitive outcome of lenvitinib-resistant HCC cells via regulating energy metabolism; meanwhile this work recognaizes BNIP3 as a promising target to overcome HCC drug resistance.

cell biology↗

bioRxiv2023

Scalable, accessible, and reproducible reference genome assembly and evaluation in Galaxy

Improvements in genome sequencing and assembly are enabling high-quality reference genomes for all species. However, the assembly process is still laborious, computationally and technically demanding, lacks standards for reproducibility, and is not readily scalable. Here we present the latest Vertebrate Genomes Project assembly pipeline and demonstrate that it delivers high-quality reference genomes at scale across a set of vertebrate species arising over the last [~]500 million years. The pipeline is versatile and combines PacBio HiFi long-reads and Hi-C-based haplotype phasing in a new graph-based paradigm. Standardized quality control is performed automatically to troubleshoot assembly issues and assess biological complexities. We make the pipeline freely accessible through Galaxy, accommodating researchers even without local computational resources and enhanced reproducibility by democratizing the training and assembly process. We demonstrate the flexibility and reliability of the pipeline by assembling reference genomes for 51 vertebrate species from major taxonomic groups (fish, amphibians, reptiles, birds, and mammals).

bioinformatics↗

bioRxiv2023

The ChickenGTEx pilot analysis: a reference of regulatory variants across 28 chicken tissues

Chicken is a valuable model for understanding fundamental biology, vertebrate evolution and diseases, as well as a major source of nutrient-dense and lean-protein-enriched food globally. Although it is the first non-mammalian amniote genome to be sequenced, the chicken genome still lacks a systematic characterization of functional impacts of genetic variants. Here, through integrating 7,015 RNA-Seq and 2,869 whole-genome sequence data, the Chicken Genotype- Tissue Expression (ChickenGTEx) project presents the pilot reference of regulatory variants in 28 chicken tissue transcriptomes, including millions of regulatory effects on primary expression (including protein-coding genes, lncRNA and exon) and post-transcriptional modifications (alternative splicing and 3 untranslated region alternative polyadenylation). We explored the tissue-sharing and context-specificity of these regulatory variants, their underlying molecular mechanisms of action, and their utility in interpreting adaptation and genome-wide associations of 108 chicken complex traits. Finally, we illustrated shared and lineage-specific features of gene regulation between chickens and mammals, and demonstrated how the ChickenGTEx resource can further assist with translating genetic findings across species. One-Sentence SummaryThe ChickenGTEx provides a multi-tissue reference of regulatory variants for chicken genetics and genomics, functional genomics, precision breeding, veterinary medicine, vertebrate evolution and even human biomedicine.

genetics↗

bioRxiv2023

Exploring the Landscape of Spatial Transcriptome Analysis: Introducing STASH, a Database of Spatial Transcriptome Tools

Spatial transcriptomics (ST) has emerged as a powerful tool for unravelling tissue structure and function. However, the continuous development of ST has made it challenging to select and effectively use appropriate analysis tools. To address this issue, we have developed the Spatial Transcriptome Analysis Hub (STASH, http://cailab.labshare.cn:7004), a comprehensive, systematic, and user-friendly database of ST analysis tools. STASH collects and categorizes most of the tools currently available and provides insight into their current status and trends. This can help researchers quickly locate the appropriate tool for their needs, or even guide researchers in the development of better tools.

bioinformatics↗

bioRxiv2023

Engineering Nme2Cas9 Adenine Base Editors with Improved Activity and Targeting Scope

Nme2Cas9 has been established as a genome editing platform with compact size, high accuracy, and broad targeting range, including single-AAV-deliverable adenine base editors. Here, we have engineered Nme2Cas9 to further increase the activity and targeting scope of compact Nme2Cas9 base editors. We first used domain insertion to position the deaminase domain nearer the displaced DNA strand in the target-bound complex. These domain-inlaid Nme2Cas9 variants exhibited shifted editing windows and increased activity in comparison to the N-terminally fused Nme2-ABE. We next expanded the editing scope by swapping the Nme2Cas9 PAM-interacting domain with that of SmuCas9, which we had previously defined as recognizing a single-cytidine PAM. We used these enhancements to correct two common MECP2 mutations associated with Rett syndrome with little or no bystander editing. Finally, we validated domain-inlaid Nme2-ABEs for single-AAV delivery in vivo.

molecular biology↗

bioRxiv2023

Microbiome-enabled genomic selection improves prediction accuracy for nitrogen-related traits in maize

Root-associated microbiomes in the rhizosphere (rhizobiomes) are increasingly known to play an important role in nutrient acquisition, stress tolerance, and disease resistance of plants. However, it remains largely unclear to what extent these rhizobiomes contribute to trait variation for different genotypes and if their inclusion in the genomic selection (GS) protocol can enhance prediction accuracy. To address these questions, we developed a microbiome-enabled GS (MEGS) method that incorporated host SNPs and ASVs (amplicon sequence variants) from plant rhizobiomes in a maize diversity panel under high and low nitrogen (N) field conditions. Our cross-validation results showed that the MEGS model significantly outperformed the conventional GS model for nearly all time-series traits related to plant growth and N responses, with an average relative improvement of 3.7%. The improvement was more pronounced under low N conditions (8.4% -- 40.2% of relative improvement), consistent with the view that some beneficial microbes can enhance N nutrient uptake, particularly in low N fields. However, our study could not definitively rule out the possibility that the observed improvement is partially due to the ASVs being influenced by microenvironments. Using a high-dimensional mediation analysis method, our study has also identified microbial mediators that establish a link between plant genotype and phenotype. Some of the detected mediator microbes were previously reported to promote plant growth. The enhanced prediction accuracy of the MEGS models, demonstrated in a single environment, serves as a proof-of-concept for the potential application of microbiome-enabled plant breeding for sustainable agriculture.

genetics↗

bioRxiv2023

Replay as a basis for backpropagation through time in the brain

How episodic memories are formed in the brain is an outstanding puzzle for the neuroscience community. The brain areas that are critical for episodic learning (e.g., the hippocampus) are characterized by recurrent connectivity and generate frequent offline replay events. The function of the replay events is a subject of active debate. Recurrent connectivity, computational simulations show, enables sequence learning when combined with a suitable learning algorithm such as Backpropagation through time (BPTT). BPTT, however, is not biologically plausible. We describe here, for the first time, a biologically plausible variant of BPTT in a reversible recurrent neural network, R2N2, that critically leverages offline-replay to support episodic learning. The model uses forwards and backwards offline replay to transfer information between two recurrent neural networks, a cache and a consolidator,that perform rapid one-shot learning and statistical learning, respectively. Un-like replay in standard BPTT, this architecture requires no artificial external memory store. This architecture and approach outperform existing solutions and account for the functional significance to hippocampal replay events. We demonstrate the R2N2 network properties using benchmark tests from computer science and simulate the rodent delayed alternation T-maze task.

neuroscience↗

bioRxiv2023

Bovine milk glycoproteins inhibit SARS-CoV-2 and influenza virus co-infection

The attachment of S1 subunit of spike (S) protein to angiotensin-converting enzyme 2 (ACE2) is the first and crucial step of SARS-CoV-2 infection. Although S protein and ACE2 are heavily glycosylated, the precise roles of glycans in their interactions are still unclear. Here, we profiled the glycopatterns of S1 subunit of SARS-CoV-2 and ACE2, and found that the galactosylated glycoforms were dominant in both S1 subunit and ACE2. Interestingly, S1 subunit exhibited the property of glycan-binding protein (GBP) and adhered to the ACE2 via binding to the galactosylated glycans on the ACE2. Our earlier findings demonstrated that the sialylated glycoproteins isolated from bovine milk potently inhibit and neutralize viral activity against influenza A virus (IAV). Importantly, we proved further that the galactosylated glycans on isolated glycoproteins bind to the glycan recognition domains of S1 subunit and competitively inhibit binding of S1 subunit to ACE2 and ultimately impede the entry of SARS-CoV-2 pseudovirus into host cells. We provided a potential protein drug that could be multiple simultaneous inhibitor for coronavirus and IAV co-infection.

microbiology↗

bioRxiv2023

Imaging Microglia Surveillance during Sleep-wake Cycles in Freely Behaving Mice

Microglia surveillance manifests itself as dynamic changes in cell morphology and functional remodeling. Whether and how microglia surveillance is coupled to brain state switches during natural sleep-wake cycles remain unclear. To address this question, we used miniature two-photon microscopy (mTPM) to acquire time-lapse high-resolution microglia images of the somatosensory cortex, along with EEG/EMG recordings and behavioral video, in freely-behaving mice. We uncovered fast and robust brain state-dependent changes in microglia surveillance, occurring in parallel with sleep dynamics and early-onset phagocytic microglial contraction during sleep deprivation stress. We also detected local norepinephrine fluctuation occurring in a sleep state-dependent manner. We showed that the locus coeruleus-norepinephrine system, which is crucial to sleep homeostasis, is required for both sleep state-dependent and stress-induced microglial responses and {beta}2-adrenergic receptor signaling plays a significant role in this process. These results provide direct evidence that microglial surveillance is exquisitely tuned to signals and stressors that regulate sleep dynamics and homeostasis so as to adjust its varied roles to complement those of neurons in the brain. In vivo imaging with mTPM in freely behaving animals, as demonstrated here, opens a new avenue for future investigation of microglia dynamics and sleep biology in freely behaving animals.

neuroscience↗

bioRxiv2023

Three-dimensional genomic mapping of human pancreatic tissue reveals striking multifocality and genetic heterogeneity in precancerous lesions

Pancreatic intraepithelial neoplasia (PanIN) is a precursor to pancreatic cancer and represents a critical opportunity for cancer interception. However, the number, size, shape, and connectivity of PanINs in human pancreatic tissue samples are largely unknown. In this study, we quantitatively assessed human PanINs using CODA, a novel machine-learning pipeline for 3D image analysis that generates quantifiable models of large pieces of human pancreas with single-cell resolution. Using a cohort of 38 large slabs of grossly normal human pancreas from surgical resection specimens, we identified striking multifocality of PanINs, with a mean burden of 13 spatially separate PanINs per cm3 of sampled tissue. Extrapolating this burden to the entire pancreas suggested a median of approximately 1000 PanINs in an entire pancreas. In order to better understand the clonal relationships within and between PanINs, we developed a pipeline for CODA-guided multi-region genomic analysis of PanINs, including targeted and whole exome sequencing. Multi-region assessment of 37 PanINs from eight additional human pancreatic tissue slabs revealed that almost all PanINs contained hotspot mutations in the oncogene KRAS, but no gene other than KRAS was altered in more than 20% of the analyzed PanINs. PanINs contained a mean of 13 somatic mutations per region when analyzed by whole exome sequencing. The majority of analyzed PanINs originated from independent clonal events, with distinct somatic mutation profiles between PanINs in the same tissue slab. A subset of the analyzed PanINs contained multiple KRAS mutations, suggesting a polyclonal origin even in PanINs that are contiguous by rigorous 3D assessment. This study leverages a novel 3D genomic mapping approach to describe, for the first time, the spatial and genetic multifocality of human PanINs, providing important insights into the initiation and progression of pancreatic neoplasia.

cancer biology↗

bioRxiv2023

Learning functional conservation between pig and human to decipher evolutionary mechanisms underlying gene expression and complex trait

The assessment of genomic conservation between human and pig at the functional level can help understand and improve the potential of pig as a human biomedical model. To address this, we developed a Deep learning-based approach to learn the Genomic Conservation at the Functional level (DeepGCF) between species by integrating 386 and 374 epigenome and transcriptome profiles from human and pig, respectively. DeepGCF demonstrated a better prediction performance compared to the previous functional conservation prediction method. In addition, we showed that the resulting DeepGCF score captures the functional conservation by examining DeepGCF on chromatin states, sequence ontologies, and regulatory variants. Regions with higher DeepGCF score play a more important role in regulatory activities and show heritability enrichment in human complex traits and diseases. Our DeepGCF approach shows a promising application on the comparison of cross-species functional conservation, and the model framework can be easily adapted to other species. By expanding the model to integrate the functional profiles of multiple species, including human, mouse, pig, cattle, and other livestock animals in the future, the functional conservation information will provide additional insight into the genetic and evolutionary mechanisms behind complex traits and diseases.

genetics↗

bioRxiv2023

ATP-releasing SWELL1 channel in spinal microglia contributes to neuropathic pain

Following peripheral nerve injury, extracellular ATP-mediated purinergic signaling is crucial for spinal cord microglia activation and neuropathic pain. However, the mechanisms of ATP release remain poorly understood. Here, we show that volume-regulated anion channel (VRAC) is an ATP-releasing channel and is activated by inflammatory mediator sphingosine-1-phosphate (S1P) in microglia. Mice with microglia-specific deletion of Swell1 (also known as Lrrc8a), a VRAC essential subunit, had reduced peripheral nerve injury-induced increase in extracellular ATP in spinal cord. The mutant mice also exhibited decreased spinal microgliosis, dorsal horn neuronal hyperactivity, and both evoked and spontaneous neuropathic pain-like behaviors. We further performed high-throughput screens and identified an FDA-approved drug dicumarol as a novel and potent VRAC inhibitor. Intrathecal administration of dicumarol alleviated nerve injury-induced mechanical allodynia in mice. Our findings suggest that ATP-releasing VRAC in microglia is a key spinal cord determinant of neuropathic pain and a potential therapeutic target for this debilitating disease.

physiology↗

bioRxiv2022

Extracellular disintegration of viral proteins as an innovative strategy for developing broad-spectrum antivirals against coronavirus

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed millions of lives worldwide, not to mention innumerable losses in the global economy and disruptions in social relationships. Unfortunately, state-of-the-art treatments still lag behind the fast emergence of new variants of concern. The key to resolve this issue is to develop broad-spectrum antivirals with innovative antiviral mechanisms in which coronaviruses are deactivated regardless of their variant development. Herein, we report a new antiviral strategy involving extracellular disintegration of viral proteins that are indispensable for viral infection with hyperanion-grafted enediyne molecules. The sulfate groups ensure low cellular permeability and rather low cytotoxicity of the molecules, while the core enediyne generates reactive radical species and causes significant damage to the spike (S) protein of coronavirus. The enediyne compounds exhibit antiviral activity at micromolar to nanomolar concentrations, and the selectivity index of up to 20,000 against four kinds of human coronaviruses, including the SARS-CoV-2 omicron variant, suggesting the high potential of this new strategy in combating the COVID-19 pandemic.

biochemistry↗