Biology subjects

Huang, Y.

Publications and source records attributed to Huang, Y..

At least 613 records · Page 34Linked to original sources

bioRxiv2023

A syntelog-based pan-genome provides insights into rice domestication and de-domestication

Asian rice is one of the worlds most widely cultivated crops. Large-scale resequencing analyses have been undertaken to explore the domestication and de-domestication genomic history of Asian rice, but the evolution of rice is still under debate. Here, we construct a syntelog-based rice pan-genome by integrating and merging 74 high-accuracy genomes based on long-read sequencing, encompassing all ecotypes and taxa of Oryza sativa and Oryza rufipogon. Analyses of syntelog groups illustrate subspecies divergence in gene presence-and-absence and haplotype composition and identify massive genomic regions putatively introgressed from ancient Geng/japonica to ancient Xian/indica or its wild ancestor, including almost all well-known domestication genes and a 4.5-Mb centromere-spanning block, supporting a single domestication event in rice. Genomic comparisons between weedy and cultivated rice highlight the contribution from wild introgression to the emergence of de-domestication syndromes in weedy rice. This work highlights the significance of inter-taxa introgression in shaping diversification and divergence in rice evolution and provides an exploratory attempt by utilizing the advantages of pan-genomes in evolutionary studies.

evolutionary biology↗

bioRxiv2023

Plant diversity stabilizes soil temperature

Extreme weather events are occurring more frequently, and research has shown that plant diversity can help mitigate impacts of climate change by increasing plant productivity and ecosystem stability1,2. Although soil temperature and its stability are key determinants of essential ecosystem processes related to water and nutrient uptake3 as well as soil respiration and microbial activity4, no study has yet investigated whether plant diversity can buffer soil temperature fluctuations. Using 18 years of a continuous dataset with a resolution of 1 minute ([~]795,312,000 individual measurements) from a large-scale grassland biodiversity experiment, we show that plant diversity buffers soil temperature throughout the year. Plant diversity helped to prevent soil heating in hot weather, and cooling in cold weather. Moreover, this effect of plant diversity increased over the 18-year observation period with the aging of experimental communities and was even stronger under extreme conditions, i.e., on hot days or in dry years. Using structural equation modelling, we found that plant diversity stabilized soil temperature by increasing soil organic carbon concentrations and, to a lesser extent, by increasing the plant leaf area index. We suggest that the diversity-induced stabilization of soil temperature may help to mitigate the negative effects of extreme climatic events such as soil carbon release, thus slow global warming.

ecology↗

bioRxiv2023

ancIBD - Screening for identity by descent segments in human ancient DNA

Long DNA sequences shared between two individuals, known as Identical by descent (IBD) segments, are a powerful signal for identifying close and distant biological relatives because they only arise when the pair shares a recent common ancestor. Existing methods to call IBD segments between present-day genomes cannot be straightforwardly applied to ancient DNA data (aDNA) due to typically low coverage and high genotyping error rates. We present ancIBD, a method to identify IBD segments for human aDNA data implemented as a Python package. Our approach is based on a Hidden Markov Model, using as input genotype probabilities imputed based on a modern reference panel of genomic variation. Through simulation and downsampling experiments, we demonstrate that ancIBD robustly identifies IBD segments longer than 8 centimorgan for aDNA data with at least either 0.25x average whole-genome sequencing (WGS) coverage depth or at least 1x average depth for in-solution enrichment experiments targeting a widely used aDNA SNP set ( 1240k). This application range allows us to screen a substantial fraction of the aDNA record for IBD segments and we showcase two downstream applications. First, leveraging the fact that biological relatives up to the sixth degree are expected to share multiple long IBD segments, we identify relatives between 10,156 ancient Eurasian individuals and document evidence of long-distance migration, for example by identifying a pair of two approximately fifth-degree relatives who were buried 1410km apart in Central Asia 5000 years ago. Second, by applying ancIBD, we reveal new details regarding the spread of ancestry related to Steppe pastoralists into Europe starting 5000 years ago. We find that the first individuals in Central and Northern Europe carrying high amounts of Steppe-ancestry, associated with the Corded Ware culture, share high rates of long IBD (12-25 cM) with Yamnaya herders of the Pontic-Caspian steppe, signaling a strong bottleneck and a recent biological connection on the order of only few hundred years, providing evidence that the Yamnaya themselves are a main source of Steppe ancestry in Corded Ware people. We also detect elevated sharing of long IBD segments between Corded Ware individuals and people associated with the Globular Amphora culture (GAC) from Poland and Ukraine, who were Copper Age farmers not yet carrying Steppe-like ancestry. These IBD links appear for all Corded Ware groups in our analysis, indicating that individuals related to GAC contexts must have had a major demographic impact early on in the genetic admixtures giving rise to various Corded Ware groups across Europe. These results show that detecting IBD segments in aDNA can generate new insights both on a small scale, relevant to understanding the life stories of people, and on the macroscale, relevant to large-scale cultural-historical events.

genetics↗

bioRxiv2023

Identification of mobile element insertion from whole genome sequencing data using deep neural network model

Mobile element insertions (MEIs) are a major contributor to genome evolution and play an essential role in the regulation of gene expression, as well as being implicated in various human diseases. This study introduces DeepMEI, a tool based on a convolutional neural network model that transforms the MEI identification process into an image recognition problem and automatically learns complex and abstract representations of MEI features in whole genome sequencing data. DeepMEI outperformed existing tools in the benchmark dataset from the Genome in a Bottle consortium, with a precision of 0.90 and recall of 0.70. Moreover, factors such as sequencing depth, ME integrity, and genome mappability can affect MEI identification accuracy. Using DeepMEI, we reanalyzed 3,202 high-coverage whole-genome sequencing samples from the 1000 Genome Project (1kGP) phase 4 release, discovering 1.71-fold more non-reference MEIs, totaling 6,218,088, with 92.2% of the increase coming from rare MEIs (allele frequency <1%). This enhances our understanding of MEIs role in human disease and evolution. The DeepMEI tool and the updated 1kGP MEI dataset can be accessed at https://github.com/xuxif/DeepMEI.

bioinformatics↗

bioRxiv2023

Long noncoding RNA-mediated epigenetic regulation of auxin-related genes controlling shade avoidance syndrome in Arabidopsis thaliana

The long noncoding RNA (lncRNA) AUXIN-REGULATED PROMOTER LOOP (APOLO) recognizes a subset of target loci across the Arabidopsis thaliana genome by forming RNA-DNA hybrids (R-loop) and modulating local three-dimensional chromatin conformation. Here we show that APOLO is involved in regulating the shade avoidance syndrome (SAS) by dynamically modulating the expression of key factors. In response to far-red (FR) light, the expression of APOLO anticorrelates with its target BRANCHED1 (BRC1), a master regulator of shoot branching in Arabidopsis thaliana. APOLO deregulation results in BRC1 transcriptional repression and an increase in the number of branches. APOLO transcriptional accumulation fine-tunes the formation of a repressive chromatin loop encompassing the BRC1 promoter, which normally occurs only in leaves as well as in a late response to FR treatment in axillary buds. In addition, our data reveal that APOLO participates in leaf hyponasty, in agreement with its previously reported role in the control of auxin homeostasis through direct modulation of YUCCA2 (auxin synthesis), PID and WAG2 (auxin efflux). We found that direct application of APOLO RNA to leaves results in a rapid increase in auxin accumulation that is associated with changes in the response of the plants to FR light. Collectively, our data support the view that lncRNAs coordinate the shade avoidance syndrome in Arabidopsis thaliana and shed light on the potential of lncRNAs as bioactive exogenous molecules. Deploying exogenous RNAs that modulate plant-environment interactions are important new tools for sustainable agriculture.

plant biology↗

bioRxiv2023

Social Behavior Atlas: A computational framework for tracking and mapping 3D close interactions of free-moving animals

The study of social behaviors in animals is essential for understanding their survival and reproductive strategies. However, accurately tracking and analyzing the social interactions of free-moving animals has remained a challenge. Existing multi-animal pose estimation techniques suffer from drawbacks such as the need for extensive manual annotation and difficulty in discriminating between similar-looking animals in close social interactions. In this paper, we present the Social Behavior Atlas (SBeA), a novel computational framework that solves these challenges by employing a deep learning-based video instance segmentation model, 3D pose reconstruction, and unsupervised dynamic behavioral clustering. SBeA framework also involves a multi-camera setup to prevent occlusion, and a novel approach to identify individual animals in close social interactions. We demonstrate the effectiveness of SBeA in tracking and mapping the 3D close interactions of free-moving animals using the example of genetic mutant mice, birds, and dogs. Our results show that SBeA is capable of identifying subtle social interaction abnormalities, and the models and frameworks developed can be applied to a wide range of animal species. SBeA is a powerful tool for researchers in the fields of neuroscience and ecology to study animal social behaviors with a high degree of accuracy and reliability.

neuroscience↗

bioRxiv2023

Multifunctional Materials Strategies for Enhanced Safety of Wireless, Skin-Interfaced Bioelectronic Devices

Many recently developed classes of wireless, skin-interfaced bioelectronic devices rely on conventional thermoset silicone elastomer materials, such as poly(dimethylsiloxane) (PDMS), as soft encapsulating structures around collections of electronic components, radio frequency antennas and, commonly, rechargeable batteries. In optimized layouts and device designs, these materials provide attractive features, most prominently in their gentle, noninvasive interfaces to the skin even at regions of high curvature and large natural deformations. Past work, however, overlooks opportunities for developing variants of these materials for multimodal means to enhance the safety of the devices against failure modes that range from mechanical damage to thermal runaway. This paper presents a self-healing PDMS dynamic covalent matrix embedded with chemistries that provide thermochromism, mechanochromism, strain-adaptive stiffening, and thermal insulation, as a collection of attributes relevant to safety. Demonstrations of this materials system and associated encapsulation strategy involve a wireless, skin-interfaced device that captures mechanoacoustic signatures of health status. The concepts introduced here can apply immediately to many other related bioelectronic devices.

bioengineering↗

bioRxiv2023

CD99 Promotes Self-renewal in Hematopoietic Stem Cells and Leukemia Stem Cells by Regulating Protein Synthesis

Blood production is sustained by hematopoietic stem cells (HSCs), which are typically the only blood cells capable of long-term self-renewal. Acute myeloid leukemia (AML) is initiated by aberrantly self-renewing malignant stem cells termed leukemia stem cells (LSCs). HSCs exhibit and depend on low levels of protein synthesis to self-renew. However, the mechanisms by which HSCs regulate protein synthesis to maintain their capacity for self-renewal in the setting of proliferative stress and leukemogenesis remain unknown. Here we show CD99, a cell surface protein upregulated in LSCs, is required for self-renewal of proliferating HSCs and LSCs. We found that loss of CD99 in HSCs and LSCs leads to increased protein synthesis and that their self-renewal capacity can be restored by translation inhibition. These data demonstrate a functional role for CD99 in constraining protein synthesis, which may promote the clonal expansion of HSCs and LSCs that leads to AML. Furthermore, they show that similar to HSCs, LSCs depend on regulated protein synthesis.

cancer biology↗

bioRxiv2023

CRACD, a gatekeeper restricting proliferation, heterogeneity, and immune evasion of small cell lung cancer

Small cell lung cancer (SCLC) is aggressive with limited therapeutic options. Despite recent advances in targeted therapies and immunotherapies, therapy resistance is a recurring issue, which might be partly due to tumor cell plasticity, a change in cell fate. Nonetheless, the mechanisms underlying tumor cell plasticity and immune evasion in SCLC remain elusive. CRACD, a capping protein inhibitor that promotes actin polymerization, is frequently inactivated in SCLC. Cracd knockout (KO) transforms preneoplastic cells into SCLC tumor-like cells and promotes in vivo SCLC development driven by Rb1, Trp53, and Rbl2 triple KO. Cracd KO induces neuroendocrine (NE) plasticity and increases tumor cell heterogeneity of SCLC tumor cells via dysregulated NOTCH1 signaling by actin cytoskeleton disruption. CRACD depletion also reduces nuclear actin and induces EZH2-mediated H3K27 methylation. This nuclear event suppresses the MHC-I genes and thereby depletes intratumoral CD8+ T cells for accelerated SCLC tumorigenesis. Pharmacological blockade of EZH2 inhibits CRACD-negative SCLC tumorigenesis by restoring MHC-I expression and immune surveillance. Unsupervised single-cell transcriptomics identifies SCLC patient tumors with concomitant inactivation of CRACD and downregulated MHC-I pathway. This study defines CRACD, an actin regulator, as a tumor suppressor that limits cell plasticity and immune evasion and proposes EZH2 blockade as a viable therapeutic option for CRACD-negative SCLC.

cancer biology↗

bioRxiv2023

Tumor Niche Network-Defined Subtypes Predict Immunotherapy Response of Esophageal Squamous Cell Cancer

Despite the promising outcomes of immune checkpoint blockade (ICB), resistance to ICB presents a new challenge. Therefore, selecting patients for specific ICB applications is crucial for maximizing therapeutic efficacy. Herein we curated 69 human esophageal squamous cell cancer (ESCC) patients tumor microenvironment (TME) single-cell transcriptomic datasets to subtype ESCC. Integrative analyses of the cellular network transcriptional signatures of T cells, myeloid cells, and fibroblasts define distinct ESCC subtypes characterized by T cell exhaustion, Interferon (IFN) a/b signaling, TIGIT enrichment, and specific marker genes. Furthermore, this approach classifies ESCC patients into ICB responders and non-responders, as validated by liquid biopsy single-cell transcriptomics. Our study stratifies ESCC patients based on TME transcriptional network, providing novel insights into tumor niche remodeling and predicting ICB responses in ESCC patients.

cancer biology↗

bioRxiv2023

Cell type-specific Interaction Analysis using Doublets in scRNA-seq (CIcADA)

MotivationDoublets are usually considered an unwanted artifact of single-cell RNA-sequencing (scRNA-seq) and are only identified in datasets for the sake of removal. However, if cells have a juxtacrine attachment to one another in situ and maintain this association through an scRNA-seq processing pipeline that only partially dissociates the tissue, these doublets can provide meaningful biological information regarding the interactions and cell processes occurring in the analyzed tissue. This is especially true for cases such as the immune compartment of the tumor microenvironment, where the frequency and type of immune cell juxtacrine interactions can be a prognostic indicator. ResultsWe developed Cell type-specific Interaction Analysis using Doublets in scRNA-seq (CIcADA) as a pipeline for identifying and analyzing biological doublets in scRNA-seq data. CIcADA identifies putative doublets using multi-label cell type scores and characterizes interaction dynamics through a comparison against synthetic doublets of the same cell type composition. In performing CIcADA on several scRNA-seq tumor datasets, we found that the identified doublets were consistently upregulating expression of immune response genes. ContactCourtney.T.Schiebout.GR@Dartmouth.edu, Hildreth.R.Frost@Dartmouth.edu

bioinformatics↗

bioRxiv2023

A closer look at high-energy X-ray-induced bubble formation during soft tissue imaging

Improving the scalability of tissue imaging throughput with bright, coherent X-rays requires identifying and mitigating artifacts resulting from the interactions between X-rays and matter. At synchrotron sources, long-term imaging of soft tissues in solution can result in gas bubble formation or cavitation, which dramatically compromises image quality and integrity of the samples. By combining in-line phase-contrast cineradiography with operando gas chromatography, we were able to track the onset and evolution of high-energy X-ray-induced gas bubbles in ethanol-embedded soft tissue samples for tens of minutes (2 to 3 times the typical scan times). We demonstrate quantitatively that vacuum degassing of the sample during preparation can significantly delay bubble formation, offering up to a twofold improvement in dose tolerance, depending on the tissue type. However, once nucleated, bubble growth is faster in degassed than undegassed samples, indicating their distinct metastable states at bubble onset. Gas chromatography analysis shows increased solvent vaporization concurrent with bubble formation, yet the quantities of dissolved gases remain unchanged. Coupling features extracted from the radiographs with computational analysis of bubble characteristics, we uncover dose-controlled kinetics and nucleation site-specific growth. These hallmark signatures provide quantitative constraints on the driving mechanisms of bubble formation and growth. Overall, the observations highlight bubble formation as a critical, yet often overlooked hurdle in upscaling X-ray imaging for biological tissues and soft materials and we offer an empirical foundation for their understanding and imaging protocol optimization. More importantly, our approaches establish a top-down scheme to decipher the complex, multiscale radiation-matter interactions in these applications. Significance statementBetter probing the X-ray radiation dose limit of bubble formation in biological tissue and developing mitigation methods is essential for improving imaging techniques involving X-ray, such as synchrotron X-ray tomography or crystallography. Here, we combined operando gas chromatography with in-line X-ray phase-contrast radiography on human lung and brain tissue to investigate bubble formation under high-energy X-ray irradiation. We demonstrate that vacuum degassing delays bubble nucleation up to a factor two, depending on the tissue type. Gas chromatography analysis showed increased solvent vaporization during bubble formation; however, the quantities of dissolved gases remained unchanged. Moreover, depending on the nucleation site, bubble growth can be geometrically constrained by sample microstructure, which influence its dynamics.

biochemistry↗

bioRxiv2023

Neuromuscular Basis of Drosophila larval escape behavior

When threatened by dangerous or harmful stimuli, animals engage in diverse forms of rapid escape behaviors. In Drosophila larvae, one type of escape response involves C-shaped bending and lateral rolling followed by rapid forward crawling. The sensory circuitry that promotes larval escape has been extensively characterized; however, the motor programs underlying rolling are unknown. Here, we characterize the neuromuscular basis of rolling escape behavior. We used high-speed, volumetric, Swept Confocally-Aligned Planar Excitation (SCAPE) microscopy to image muscle activity during larval rolling. Unlike sequential peristaltic muscle contractions that progress from segment to segment during forward and backward crawling, the muscle activity progresses circumferentially during bending and rolling escape behavior. We propose that progression of muscular contraction around the larvas circumference results in a transient misalignment between weight and the ground support forces, which generates a torque that induces stabilizing body rotation. Therefore, successive cycles of slight misalignment followed by reactive aligning rotation lead to continuous rolling motion. Supporting our biomechanical model, we found that disrupting the activity of muscle groups undergoing circumferential contraction progression lead to rolling defects. We use EM connectome data to identify premotor to motor connectivity patterns that could drive rolling behavior, and perform neural silencing approaches to demonstrate the crucial role of a group of glutamatergic premotor neurons in rolling. Our data reveal body-wide muscle activity patterns and putative premotor circuit organization for execution of the rolling escape response. Significance StatementTo escape from dangerous stimuli, animals execute escape behaviors that are fundamentally different from normal locomotion. The rolling escape behavior of Drosophila larvae consists of C-shaped bending and rolling. However, the muscle contraction patterns that lead to rolling are poorly understood. We find that following the initial body bending, muscles contract in a circumferential wave around the larva as they enter the bend, maintaining unidirectional rolling that resembles cylinder rolling on a surface. We study the structure of motor circuits for rolling, inhibit different motor neurons to determine which muscles are essential for rolling, and propose circuit and biomechanical models for roll generation. Our findings provide insights into how motor circuits produce diverse motor behaviors.

neuroscience↗

bioRxiv2023

Utility of long-read sequencing for All of Us

The All of Us (AoU) initiative aims to sequence the genomes of over one million Americans from diverse ethnic backgrounds to improve personalized medical care. In a recent technical pilot, we compared the performance of traditional short-read sequencing with long-read sequencing in a small cohort of samples from the HapMap project and two AoU control samples representing eight datasets. Our analysis revealed substantial differences in the ability of these technologies to accurately sequence complex medically relevant genes, particularly in terms of gene coverage and pathogenic variant identification. We also considered the advantages and challenges of using low coverage sequencing to increase sample numbers in large cohort analysis. Our results show that HiFi reads produced the most accurate results for both small and large variants. Further, we present a cloud-based pipeline to optimize SNV, indel and SV calling at scale for long-reads analysis. These results will lead to widespread improvements across AoU.

bioinformatics↗

bioRxiv2023

Towards a reliable spatial analysis of missing features via spatially-regularized imputation

AO_SCPLOWBSTRACTC_SCPLOWImputation of missing features in spatial transcriptomics is urgently demanded due to technology limitations, while most existing computational methods suffer from moderate accuracy and cannot estimate the reliability of the imputation. To fill the research gaps, we introduce a computational model, TransImp, that imputes the missing feature modality in spatial transcriptomics by mapping it from single-cell reference. Uniquely, we derived a set of attributes that can accurately predict imputation uncertainty, hence enabling us to select reliably imputed genes. Also, we introduced a spatial auto-correlation metric as a regularization to avoid overestimating spatial patterns. Multiple datasets from various platforms have demonstrated that our approach significantly improves the reliability of downstream analyses in detecting spatial variable genes and interacting ligand-receptor pairs. Therefore, TransImp offers a way towards a reliable spatial analysis of missing features for both matched and unseen modalities, e.g., nascent RNAs.

bioinformatics↗

bioRxiv2023

Mechanism of an alternative splicing switch mediated by cell-specific and general splicing regulators

Alternative pre-mRNA splicing is regulated by RNA binding proteins (RBPs) that activate or repress regulated splice sites. Repressive RBPs bind stably to target RNAs via multivalent interactions, which can be achieved by both homo-oligomerization and by interactions with other RBPs mediated by intrinsically disordered regions (IDRs). Cell-specific splicing decisions commonly involve the action of widely expressed RBPs that can bind around target exons, but without effect in the absence of a key cell-specific regulator. To address how cell-specific regulators collaborate with constitutive RBPs in alternative splicing regulation we used the smooth-muscle specific regulator RBPMS. Recombinant RBPMS is sufficient to switch cell specific alternative splicing of Tpm1 exon 3 in cell free assays by remodelling ribonucleprotein complexes and preventing assembly of ATP-dependent splicing complexes. This activity depends upon its C-terminal IDR, which facilitates dynamic higher-order self-assembly, cooperative binding to multivalent RNA, and interactions with other splicing co-regulators, including MBNL1 and RBFOX2. Our data show how a cell-specific RBP can co-opt more widely expressed regulatory RBPs to facilitate cooperative assembly of stable cell-specific regulatory complexes.

molecular biology↗

bioRxiv2023

Activation-induced cytidine deaminase-based in vivo continuous evolution system enables rapid protein engineering

Directed evolution is a powerful tool to modify the properties of proteins. However, due to multi-round and stage combinations, directed evolution usually requires time- and labor-intensive manual intervention, which limits the efficiency of protein modification to some extent. Therefore, in vivo continuous evolution system is highly preferred because it can couple the multiple rounds and steps of direction evolution with the host growth cycle, leading to the advantages of effort-saving and accuracy. However, the existing types of this kind of systems can not meet the booming demand. Herein, this paper describes promoted Escherichia coli-assisted continuous evolution (PEACE) that allows for in vivo continuous evolution of target genes. This system polymorphisms the target gene by activation-induced cytidine deaminase-T7 RNA polymerase (AID-T7 PNAP) fusion protein, then it couples the enzymatic properties of desired variants with the expression of antitoxins to achieve efficient growth-coupled screen using the toxin-antitoxin system (TAS). In this study, T7 RNAP was finally employed for validation of PEACE system, and its specificity to the promoter was successfully altered. These results demonstrated the feasibility and further application potential of PEACE.

molecular biology↗

bioRxiv2023

BnIR: a multi-omics collaborative resource and tool platform for Brassica napus biological study

In the post-GWAS era, multi-omics techniques have shown great power and potential for candidate gene mining and functional genomics research. However, due to the lack of effective data integration and multi-omics analysis platforms, such techniques have not still been applied widely in rapeseed, an important oil crop worldwide. Here, we constructed a rapeseed multi-omics database (BnIR; http://yanglab.hzau.edu.cn/BnIR), which provides datasets of six omics including genomics, transcriptomics, variomics, epigenetics, phenomics and metabolomics, as well as numerous "variation-gene expression-phenotype" associations by using multiple statistical methods. In addition, a series of multi-omics search and analysis tools are integrated to facilitate the browsing and application of these datasets. BnIR is the most comprehensive multi-omics database for rapeseed so far, and two case studies demonstrated its power to mine candidate genes associated with specific traits and analyze their potential regulatory mechanisms. Short SummaryIn this study, we developed BnIR (http://yanglab.hzau.edu.cn/BnIR), a multi-omics database for rapeseed that integrates six omics datasets and "variation-gene expression-phenotype" associations. The database is equipped with a range of multi-omics tools for streamlined browsing and analysis. Through multiple case studies, we demonstrated BnIRs potential to identify candidate genes associated with specific traits and investigate their regulatory mechanisms.

bioinformatics↗