Biology subjects

Fang, L.

Publications and source records attributed to Fang, L..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

FarmGTEx TWAS-server: an interactive web server for customized TWAS analysis in both human and farm animals

Transcriptome-wide association study (TWAS) is a powerful strategy for elucidating the molecular mechanisms behind the genetic loci of complex phenotypes. However, TWAS analysis is still daunting in many species due to the complication of the TWAS analysis pipeline, including the construction of the gene expression reference panel, gene expression prediction, and the subsequent association analysis in the large cohorts of genome-wide association study (GWAS). Farm animals are major protein sources and biomedical models for humans. To facilitate the translation of genetic findings across species, here we provide an interactive and easy-to-use multi-species TWAS web server for the entire community, called the FarmGTEx TWAS-server (http://twas.farmgtex.org), which is based on the GTEx and FarmGTEx projects. It includes gene expression data from 49, 34, and 23 tissues in 838 humans, 5,457 pigs, and 4,889 cattle, representing 38,180, 21,037, and 17,942 distinct eGenes in prediction models for humans, pigs, and cattle, respectively. It allows users to conduct gene expression prediction for any individuals with genotypes, GWAS summary statistics imputation, customized TWAS, and popular downstream functional annotation. It also provides 479,203, 1,208, and 657 tissue-gene-trait association trios for the research community, representing 1,129 human traits, 41 cattle traits, and 11 pig traits. In summary, the FarmGTEx TWAS-server is a one-stop solution for performing TWAS analysis for researchers without programming skills in both human and farm animal research communities. It will be maintained and updated timely within the FarmGTEx project to facilitate gene mapping and phenotype prediction within and across species.

bioinformatics↗

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↗

bioRxiv2022

Transforming inert cycloalkanes into alpha-omega-diamines through designed enzymatic cascade catalysis

Aliphatic ,{omega}-diamines (DAs) are important monomer precursors in polyamide plastic manufacturing. However, the dominant industrial process for DA synthesis involves energy-intensive, multistage chemical reactions that are harmful to the environment. For instance, 1,6-hexanediamine (HMD), one of most prominent monomers in nylon-66 synthesis, is mainly synthesized with currently high technological control by butadiene hydrocyanation, which suffers from the use of highly toxic hydrogen cyanide, unsatisfactory selectivity and a complex separation process. Thus, the development of sustainable green DA synthetic routes is highly desired. Herein, we report an efficient one-pot in vivo biocatalytic cascade for the transformation of cycloalkanes into DAs with the aid of advanced techniques, including the RetroBioCat tool for biocatalytic route design, enzyme mining for finding appropriate enzymes and microbial consortia construction for efficient pathway assembly. As a result, DAs are successfully produced by the developed microbial consortia-based biocatalytic system, especially HMD, and product concentrations as high as 16.5 mM and 7.6 mM are achieved when using cyclohexanol (CHOL) or cyclohexane (CH) as substrates, respectively. This also represents the highest HMD biosynthesis productivity to date. Other cycloalkanes also serve as substrates, indicating the generality of our approach.

synthetic biology↗

bioRxiv2022

Born with intronless ERF transcriptional factors: C4 photosynthesis inherits a legacy dating back 450 million years

The genus Flaveria, containing species at different evolutionary stages of the progression from C3 to C4 photosynthesis, is used as a model system to study the evolution of C4 photosynthesis. Here, we report chromosome-scale genome sequences for five Flaveria species, including C3, C4, and intermediate species. Our analyses revealed that both acquiring additional gene copies and recruiting ethylene responsive factor (ERF) cis-regulatory elements (CREs) contributed to the emergence of C4 photosynthesis. ERF transcriptional factors (TFs), especially intronless ERF TFs, were co-opted in dicotyledonous C4 species and monocotyledonous C4 species in parallel. These C4 species co-opted intronless ERF TFs originated from the Late Ordovician mass extinction that occurred [~]450 million years ago in coping with environmental stress. Therefore, this study demonstrated that intronless ERF TFs were acquired during the early evolution of plants and provided the molecular toolbox facilitating multiple subsequent independent evolutions of C4 photosynthesis.

evolutionary biology↗

bioRxiv2022

Atypical NMDA Receptors Limit Synaptic Plasticity in the Adult Ventral Hippocampus

N-methyl-D-aspartate receptors (NMDARs) assemble as functionally diverse heterotetramers. Incorporation of the GluN3A subunit into NMDARs alters conventional NMDAR properties by reducing both magnesium sensitivity and calcium permeability. GluN1 together with GluN3A can also form functional receptors that lack a glutamate binding site and instead serve as excitatory glycine receptors (eGlyRs). GluN3A expression is high in early development but naturally declines to low levels in most brain regions by adulthood. Interestingly, GluN3A expression remains elevated in the CA1 of the adult ventral hippocampus (VH), but not in the dorsal hippocampus (DH). The DH and VH are now well-understood to play very different functional roles, with the DH being primarily involved in cognitive functions and the VH in emotional processing. Why GluN3A persists in the adult VH, and the impact its presence has on glutamatergic neurotransmission in the VH is currently unknown. Here, we show that GluN3A remains elevated both at synaptic and extrasynaptic locations in the adult VH, assembling as GluN1/GluN2/GluN3A NMDARs with reduced magnesium sensitivity, as well as GluN1/GluN3A eGlyRs. By comparing various synaptic properties in the DH and VH of wild-type (WT) and GluN3A knockout (KO) mice, we demonstrate that GluN3A persistence in the VH attenuates glutamate release, limits postsynaptic calcium influx through NMDARs, and reduces the magnitude of NMDAR-dependent long-term potentiation. In comparison, GluN3A KO had relatively little effect on these same properties in the DH. In all, our data demonstrate that GluN3A persistence in the VH represents a key modulator of VH excitability and therefore may play a central role in emotional processing.

neuroscience↗

bioRxiv2022

Depletion of collagen IX alpha2 interferes osteochondral homeostasis of the knee joint which ultimately causing osteoarthritis-like articular cartilage damage

As one of the branched chains of Type IX collagen (Col9), Collagen IX alpha2 (Col92) has been reported to be associated with several orthopedic conditions. To probe the relationship between Col92 and knee osteoarthritis (KOA), we performed a systematic analysis of Col92-deficient (Col9-/-) mice using whole-mount skeletal staining, Micro-CT (CT), biomechanics, histomorphometry, immunohistochemistry (IHC), immunofluorescence (IF) and Enzyme-linked immunosorbent (Elisa). Although whole-mount skeletal staining displayed no difference in bone length and ossification between Col9-/- mice and wild-type (Col92+/+) mice at mid-gestation and adult stages, the knee joint exhibited dramatic discrepancies. Specifically, the subchondral bone (SCB) in the knee joint of Col9-/- mice became sparse and deformed in the early stage, with altered bone morphometric parameters, reduced load-bearing capacity, dysfunctional bone homeostasis (decreased osteogenesis capacity and elevated bone resorption capacity), diminished cartilage proteoglycans and disrupted cartilage extracellular matrix (ECM) anabolism and catabolism compared with the Col92+/+ mice. In the late stage, the cartilage degeneration in Col92-/- mice were particularly pronounced compared to Col92+/+ mice, as evidenced by severe cartilage destruction and a marked reduction in cartilage thickness and area. Overall, Col92 is essential for maintaining osteochondral homeostasis in the knee joint of mice, and the absence of this gene is accompanied by distinct sclerosis of the SCB and a reduction in load-bearing capacity; in the late stage, in the lack of SCB stress inhibition, excessive load is consistently exerted on the cartilage, ultimately leading to osteoarthritic-like articular cartilage damage. Hence, Col92 may serve as a potential candidate biomarker associated with KOA.

physiology↗

bioRxiv2022

Pervasive Transcriptome Interactions of Protein-Targeted Drugs

The off-target toxicity of drugs targeted to proteins imparts substantial health and economic costs. Proteome interaction studies can reveal off-target effects with unintended proteins; however, little attention has been paid to intracellular RNAs as potential off targets that may contribute to toxicity. To begin to assess this, we developed a reactivity-based RNA profiling (RBRP) methodology, and applied it to uncover transcriptome interactions of a set of FDA-approved small-molecule drugs in vivo. We show that these protein-targeted drugs pervasively interact with the human transcriptome and can exert unintended biological effects on RNA function. In addition, we show that many off-target interactions occur at RNA loci associated with protein binding and structural changes, allowing us to generate hypotheses to infer the biological consequences of RNA off-target binding. The results suggest that rigorous characterization of drugs' transcriptome interactions may help assess target specificity and potentially avoid toxicity and clinical failures.

pharmacology and toxicology↗

bioRxiv2022

Genetic score omics regression and multi-trait meta-analysis detect widespread cis-regulatory effects shaping bovine complex traits

To complete the genome-to-phenome map, transcriptome-wide association studies (TWAS) are performed to correlate genetically predicted gene expression with observed phenotypic measurements. However, the relatively small training population assayed with gene expression could limit the accuracy of TWAS. We propose Genetic Score Omics Regression (GSOR) correlating observed gene expression with genetically predicted phenotype, i.e., genetic score. The score, calculated using variants near genes with assayed expression, provides a powerful association test between cis-effects on gene expression and the trait. In simulated and real data, GSOR outperforms TWAS in detecting causal/informative genes. Applying GSOR to transcriptomes of 16 tissue (N[~]5000) and 37 traits in [~]120,000 cattle, multi-trait meta-analyses of omics-associations (MTAO) found that, on average, each significant gene expression and splicing mediates cis-genetic effects on 8[~]10 traits. Supported by Mendelian Randomisation, MTAO prioritised genes/splicing show increased evolutionary constraints. Many newly discovered genes/splicing regions underlie previously thought single-gene loci to influence multiple traits.

genomics↗

bioRxiv2022

Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle

Many quantitative trait loci (QTL) are located in non-coding genomic regions. Therefore, QTL are assumed to affect gene regulation. Gene expression and RNA splicing are primary steps of transcription so QTL changing gene expression (eQTL) or RNA splicing (sQTL) are expected to significantly contribute to phenotypic variations. Here, we quantify the contribution of eQTL and sQTL detected from 16 tissues (N~5,000) to 37 complex traits of ~120k cattle. Using Bayesian methods, we show that including more regulatory variants in the model explains larger proportions of heritability. Across traits, cis and trans eQTL and sQTL detected from 16 tissues jointly explain ~70% (SE=0.5%) of heritability, 44% more than expected from the same number of random variants, where trans e/sQTL contribute 24% (14% more than expected). Multi-tissue cis and trans e/sQTL also explain 71% (SE=0.3%) of heritability for the metabolome, demonstrating the essential role of proximal and distal regulatory variants in shaping mammalian phenotypes.

genomics↗

bioRxiv2022

A genotoxic antibody drug conjugate targeting CD276/B7H3 demonstrates efficacy across multiple biomarker defined classes of treatment refractory metastatic prostate cancer

Antibody-drug conjugates (ADCs) are promising targeted cancer therapy; however, patient selection based solely on target antigen expression without consideration for cytotoxic payload vulnerabilities has plateaued clinical benefits. Biomarkers to capture patients who might benefit from specific ADCs have not been systematically determined for any cancer. We present a comprehensive therapeutic and biomarker analysis of a B7H3-ADC with pyrrolobenzodiazepine(PBD) payload in 26 treatment-resistant, metastatic prostate cancer(mPC) models. B7H3 is a tumor-specific surface protein widely expressed in mPC, and PBD is a DNA cross-linking agent. B7H3 expression was necessary but not sufficient for B7H3-PBD-ADC responsiveness. RB1 deficiency and/or replication stress, characteristics of poor prognosis, conferred sensitivity and were associated with complete tumor regression in both neuroendocrine (NEPC) and androgen receptor positive(ARPC) prostate cancer models, even with low B7H3 levels. Non-ARPC models, which are currently lacking efficacious treatment, demonstrated the highest replication stress and were most sensitive to treatment. In RB1 wild-type ARPC tumors, SLFN11 expression or select DNA repair mutations in SLFN11 non-expressors governed response. Significantly, wild-type TP53 predicted non-responsiveness (7/8 models). Overall, biomarker-focused selection of models led to high efficacy of in vivo treatment. These data enable a paradigm shift to biomarker-driven trial designs for maximizing clinical benefit of ADC therapies.

cancer biology↗

bioRxiv2022

The conservation of human functional variants and their effects across mammals

Despite the clear potential of livestock models of human functional variants to provide important insights into the biological mechanisms driving human diseases and traits, their use to date has been limited. Generating such models via genome editing is costly and time consuming, and it is unclear which variants will have conserved effects across species. In this study we address these issues by studying naturally occurring livestock models of human functional variants. We show that orthologues of over 1.6 million human variants are already segregating in domesticated mammalian species, including several hundred previously directly linked to human traits and diseases. Models of variants linked to particular phenotypes, including metabolomic disorders and height, have been preferentially maintained across species, meaning studying the genetic basis of these phenotypes is particularly tractable in livestock. Using machine learning we demonstrate it is possible to identify human variants that are more likely to have an existing livestock orthologue, and, importantly, we show that the effects of functional variants are often conserved in livestock, acting on orthologous genes with the same direction of effect. Consequently, this work demonstrates the substantial potential of naturally occurring livestock carriers of orthologues of human functional variants to disentangle their functional impacts.

genetics↗

bioRxiv2022

Real-time denoising of fluorescence time-lapse imaging enables high-sensitivity observations of biological dynamics beyond the shot-noise limit

A fundamental challenge in fluorescence microscopy is the inherent photon shot noise caused by the inevitable stochasticity of photon detection. Noise increases measurement uncertainty, degrades image quality, and limits imaging resolution, speed, and sensitivity. To achieve high-sensitivity imaging beyond the shot-noise limit, we provide DeepCAD-RT, a versatile self-supervised method for effective noise suppression of fluorescence time-lapse imaging. We made comprehensive optimizations to reduce its data dependency, processing time, and memory consumption, finally allowing real-time processing on a two-photon microscope. High imaging signal-to-noise ratio (SNR) can be acquired with 10-fold fewer fluorescence photons. Meanwhile, the self-supervised superiority makes it a practical tool in fluorescence microscopy where ground-truth images for training are hard to obtain. We demonstrated the utility of DeepCAD-RT in extensive experiments, including in vivo calcium imaging of various model organisms (mouse, zebrafish larva, fruit fly), 3D migration of neutrophils after acute brain injury, and 3D dynamics of cortical ATP (adenosine 5-triphosphate) release. DeepCAD-RT will facilitate the morphological and functional interrogation of biological dynamics with minimal photon budget.

biophysics↗

bioRxiv2022

Building an atlas of transposable elements reveals the extensive roles of young SINE in gene regulation, genetic diversity, and complex traits in pigs

Transposable elements (TEs) are an extensive source of genetic polymorphisms and play an indispensable role in chromatin architecture, transcriptional regulatory networks, and genomic evolution. The pig is an important source of animal protein and serves as a biomedical model for humans, yet the functional role of TEs in pigs and their contributions to complex traits are largely unknown. Here, we built a comprehensive catalog of TEs (n = 3,087,929) in pigs by a newly developed pipeline. Through integrating multi-omics data from 21 tissues, we found that SINEs with different ages were significantly associated with genomic regions with distinct functions across tissues. The majority of young SINEs were predominantly silenced by histone modifications, DNA methylation, and decreased accessibility. However, the expression of transcripts that were derived from the remaining active young SINEs exhibited strong tissue specificity through cross-examining 3,570 RNA-seq from 79 tissues and cell types. Furthermore, we detected 211,067 polymorphic SINEs (polySINEs) in 374 individuals genome-wide and found that they clearly recapitulated known patterns of population admixture in pigs. Out of them, 340 population-specific polySINEs were associated with local adaptation. Mapping these polySINEs to genome-wide associations of 97 complex traits in pigs, we found 54 candidate genes (e.g., ANK2 and VRTN) that might be mediated by TEs. Our findings highlight the important roles of young SINEs in functional genomics and provide a supplement for genotype-to-phenotype associations and modern breeding in pigs.

genomics↗

bioRxiv2022

Rapid deep widefield neuron finder driven by virtual calcium imaging data

Widefield microscope provides optical access to multi-millimeter fields of view and thousands of neurons in mammalian brains at video rate. However, calcium imaging at cellular resolution has been mostly contaminated by tissue scattering and background signals, making neuronal activities extraction challenging and time-consuming. Here we present a deep widefield neuron finder (DeepWonder), which is fueled by simulated calcium recordings but effectively works on experimental data with an order of magnitude faster speed and improved inference accuracy than traditional approaches. The efficient DeepWonder accomplished fifty-fold signal-to-background ratio enhancement in processing terabytes-scale cortex-wide recording, with over 14000 neurons extracted in 17 hours in workstation-grade computing resources compared to nearly week-long processing time with previous methods. DeepWonder circumvented the numerous computational resources and could serve as a guideline to massive data processing in widefield neuronal imaging.

bioengineering↗

bioRxiv2021

Neural stemness unifies cell tumorigenicity and pluripotent differentiation potential

Tumorigenicity and pluripotent differentiation potential are kernel cell properties for tumorgenesis and embryogenesis. A growing number of studies have demonstrated that neural stemness is the source of the two cell properties, because neural stem cells and cancer cells share cell features and regulatory networks and neural stemness has an evolutionary advantage. However, it needs to validate whether neural stemness is a cell property that would unify tumorigenicity and pluripotent differentiation potential. SETDB1/Setdb1 is an epigenetic factor that is upregulated in cancer cells and promotes cancers, and correspondingly, is enriched in embryonic neural cells during vertebrate embryogenesis. We show that knockdown of SETDB1/Setdb1 led to neuronal differentiation in neural stem and cancer cells, concomitant with reduced tumorigenicity and pluripotent differentiation potential in these cells; whereas overexpression caused an opposite effect. On one hand, SETDB1 maintains a regulatory network comprised of proteins involved in developmental programs and basic cellular functional machineries, including epigenetic modifications (EZH2), ribosome biogenesis (RPS3), translation initiation (EIF4G), spliceosome assembly (SF3B1), etc., all of which play active roles in cancers. On the other, it represses transcription of genes promoting differentiation and cell cycle and growth arrest. Moreover, neural stemness, tumorigenicity and pluripotent differentiation potential were simultaneously enhanced during serial transplantation of cancer cells. Expression of proteins involved in developmental programs and basic cellular functional machineries, including SETDB1 and other proteins above, was gradually increased. In agreement with increased expression of spliceosome proteins, alternative splicing events also increased in tumor cells derived from later transplantations, suggesting that different machineries should work concertedly to match the status of high proliferation and pluripotent differentiation potential. The study presents the evidence that neural stemness unifies tumorigenicity and differentiation potential. Tumorigenesis represents a process of gradual loss of original cell identity and gain of neural stemness in somatic cells, which might be a distorted replay of neural induction during normal embryogenesis.

cancer biology↗

bioRxiv2021

Profiling of the drug resistance of thousands of Src tyrosine kinase mutants uncovers a regulatory network that couples autoinhibition to the dynamics of the catalytic domain

Kinase inhibitors are effective cancer therapies but resistance often limits clinical efficacy. Despite the cataloguing of numerous resistance mutations, our understanding of kinase inhibitor resistance is still incomplete. Here, we comprehensively profiled the resistance of [~]3500 Src tyrosine kinase mutants to four different ATP-competitive inhibitors. We found that ATP-competitive inhibitor resistance mutations are distributed throughout Srcs catalytic domain. In addition to inhibitor contact residues, residues that participate in regulating Srcs phosphotransferase activity were prone to the development of resistance. Unexpectedly, we found that a resistance-prone cluster of residues located on the top face of the N-terminal lobe of Srcs catalytic domain contributes to autoinhibition by reducing catalytic domain dynamics, and mutations in this cluster led to resistance by lowering inhibitor affinity and promoting kinase hyperactivation. Together, our studies demonstrate how drug resistance profiling can be used to define potential resistance pathways and uncover new mechanisms of kinase regulation.

biochemistry↗

bioRxiv2021

Deep-BGCpred: A unified deep learning genome-mining framework for biosynthetic gene cluster prediction

Natural products produced by microorganisms constitute an important source of essential pharmaceuticals, including antimicrobial and anti-tumor drugs. These bioactive molecules are microbial secondary metabolites synthesized by co-localized genes termed Biosynthetic Gene Clusters (BGCs). The rapid increase of microbial genomics resources, due to the availability of high-throughput sequencing technologies, has spurred the development of computational methods for microbial genome mining for BGC discovery. Current machine learning methods, however, have limited successes in uncovering novel BGCs due to an excessive number of false positives in their predictions. To this end, we propose Deep-BGCpred, a framework that effectively addresses the aforementioned issue by improving a deep learning model termed DeepBGC. The new model embeds multi-source protein family domains and employs a stacked Bidirectional Long Short-Term Memory model to boost accuracy for BGC identifications. In particular, it integrates two customized strategies, sliding window strategy and dual-model serial screening, to improve the models performance stability and reduce the number of false positive in BGC predictions. We compare the proposed model against other well-established methods on common benchmarks and achieve new state-of-the-art results with convincing evidences. We expect that researchers working on genome mining for natural products may be greatly benefited from our newly proposed method, Deep-BGCpred.

bioinformatics↗

bioRxiv2021

DEAD-box RNA helicase 18 disrupts IRF3-binding to the interferon-β promoter

The production of type I interferons (IFN-/{beta}) requires strict control to avoid excessive activation during viral infections. The binding of interferon regulatory factor 3 (IRF3) to the IFN-{beta} promoter region in the nucleus is essential for IFN-{beta} transcription; however, whether nuclear factors have important negative-regulatory roles in this process is largely unknown. By screening for IRF3-interacting partners in the nucleus, we identified DEAD-box RNA helicase 18 (DDX18) as an important negative regulator of intranuclear IRF3. Overexpression of DDX18 suppressed virus- and IRF3-induced IFN-{beta} production, whereas knockdown of DDX18 expression or knockout of the DDX18 gene had opposite effects. Mechanistically, DDX18 interacts with IRF3 and decreases the binding of IRF3 to the IFN-{beta} promoter after viral infection. DDX18 knockdown mice (Ddx18+/-) further demonstrated that DDX18 suppressed antiviral innate immunity in vivo. Thus, despite many members of the DDX family act as important positive regulators in the cytoplasm, DDX18 plays a unique "braking" role in balancing virus-induced type I IFN production.

immunology↗