Biology subjects

Hu, L.

Publications and source records attributed to Hu, L..

At least 109 records · Page 6Linked to original sources

bioRxiv2023

OmicVerse: A single pipeline for exploring the entire transcriptome universe

Single-cell sequencing is frequently marred by "interruptions" due to limitations in sequencing throughput, yet bulk RNA-seq may harbor these ostensibly "interrupted" cells. In response, we introduce the single cell trajectory blending from Bulk RNA-seq (BulkTrajBlend) algorithm, a component of the OmicVerse suite that leverages a Beta-Variational AutoEncoder for data deconvolution and graph neural networks for the discovery of overlapping community. This approach proficiently interpolates and restores the continuity of "interrupted" cells within single-cell RNA sequencing dataset. Furthermore, OmicVerse provides an extensive toolkit for bulk and single cell RNA-seq analysis, offering uniform access to diverse methodologies, streamlining computational processes, fostering exquisite data visualization, and facilitating the extraction of novel biological insights to advance scientific research.

bioinformatics↗

bioRxiv2023

Chromatin and Gene Regulatory Dynamics of Optic Nerve Invasion in Retinoblastoma at Single-Cell Resolution

Retinoblastoma (RB), the most aggressive pediatric intraocular malignancy, urgently requires mechanistic insights to overcome limitations of current clinical interventions. Through integrated single-cell multi-omics analysis, we constructed a comprehensive epigenetic-transcriptomic atlas of photoreceptor subpopulations in RB. Pseudotemporal trajectory analysis revealed the differentiation cascade from retinal progenitor cells (RPCs) to malignant cone-like tumor cells (Cone-T), orchestrated by dynamic regulation of tumor suppressors (FEZ1) and oncogenic drivers (CITED2) within the MAPK pathway. Notably, we identified three photoreceptor subtype-specific transcription factors (EBF1, SOX15, NFIL3) exhibiting concordant overexpression and chromatin accessibility. Cell-cell communication analysis uncovered PPIA-BSG ligand-receptor interactions potentially driving tumor progression, while drug screening prioritized nine therapeutic candidates targeting transitional proliferative photoreceptors (P-p). Our findings establish a mechanistic framework for photoreceptor transformation and provide actionable targets for precision therapies.

cancer biology↗

bioRxiv2023

Protein Engineering for Thermostability through Deep Evolution

Protein engineering for increased thermostability through iterative mutagenesis and high throughput screening is labor-intensive, expensive and inefficient. Here, we developed a deep evolution (DeepEvo) strategy to engineer protein thermostability through global sequence generation and selection using deep learning models. We firstly constructed a thermostability selector based on a protein language model to extract thermostability-related features in high-dimensional latent spaces of protein sequences with high temperature tolerance. Subsequently, we constructed a variant generator based on a generative adversarial network to create protein sequences containing the desirable function with more than 50% accuracy. Finally, the generator and selector were utilized to iteratively improve the performance of DeepEvo on the model protein glyceraldehyde-3-phosphate dehydrogenase (G3PDH), whereby 8 highly thermostable variants were obtained from only 30 generated sequences, demonstrating the high efficiency of DeepEvo for the engineering of protein thermostability.

bioinformatics↗

bioRxiv2023

A novel method for sampling subgingival microbiome - a comparative metatranscriptomic study

The subgingival microbiome has been implicated in several oral and systemic diseases, such as periodontitis, arthritis, and Alzheimers disease. However, subgingival sampling is challenging and cannot be readily performed outside of primary care facilities. In order to support global, diverse, direct-to-participant clinical research studies, we developed a novel method of sampling the subgingival microbiome by rotationally swabbing the supragingival area, which we named subgingival-P (for proxy) samples. To validate this method, we sampled and metatranscriptomically analyzed subgingival and subgingival-P samples of three different teeth in 20 individuals. The subgingival-P samples were comparable to the subgingival samples in the relative abundances of microorganisms and microbial gene expression levels. Our data demonstrate that the novel method of collecting and analyzing the subgingival-P samples can act as a proxy for the subgingiva, paving the way for large and diverse studies investigating the role of the subgingival microbiome in health and disease.

microbiology↗

bioRxiv2023

Whole-genome sequencing of ethnolinguistic diverse northwestern Chinese Hexi Corridor people from the 10K_CPGDP project suggested the differentiated East-West genetic admixture along the Silk Road and their biological adaptations

The ancient Silk Road served as the main connection between East and West Eurasia for several centuries. At any rate, the genetic exchange between populations along the ancient Silk Road was likely to leave traces on the contemporary gene pool of local people in Northwest China, which was the passage of the Northern Silk Road. However, genetic sources from northwestern China are under-represented in the current population-scale genomic database. To characterize the genetic architecture and adaptative history of the Northern Silk Road ethnic populations, we performed whole-genome sequencing on 126 individuals from six ethnolinguistic groups (Tibeto-Burman (TB)-speaking Tibetan, Mongolic (MG)-speaking Dongxiang/Tu/eastern Yugur, and Turkic (TK)-speaking Salar/western Yugur) living in Gansu and Qinghai in the 10K Chinese people Genomic Diversity Project (10K_CPGDP). We observed ethnicity-related differentiated population structures among these geographically close Northwest Chinese populations, that is, Salar and Tu people showed a close affinity with southwestern TB groups, and other studied populations shared more alleles with MG and Tungusic groups. Overall, the patterns of genetic clustering were not consistent with linguistic classifications. We estimated that Dongxiang, Tibetan, and Yugur people inherited more than 10% West Eurasian ancestry, much higher than that of Salar and Tu people (<7%). Hence, the difference in the proportion of West Eurasian ancestry has primarily contributed to the genetic divergence of geographically close Northwest Chinese populations. The signatures of natural selection were identified in genes associated with cardiovascular system diseases or lipid metabolism related to triglyceride levels (e.g., PRIM2, PDE4DIP, NOTCH2, DDAH1, GALNT2, and MLIP) and developmental and neurogenetic diseases (e.g., NBPFs 8/9/20/25P, etc.). Moreover, the EPAS1 gene, a transcription factor regulating hypoxia response, showed relatively high PBS values in our studied groups. The sex-biased admixture history, in which the West Eurasian ancestry was introduced primarily by males, was identified in Dongxiang, Tibetan, and Yugur populations. We determined that the eastern-western admixture occurred [~]783-1131 years ago, coinciding with the intensive economic and cultural exchanges during the historic Trans-Eurasian cultural exchange era.

genomics↗

bioRxiv2023

Shoot maturation strengthens FLS2-mediated resistance to Pseudomonas syringae

A temporal-spatial regulation of immunity components is essential for properly activating plant defense response. Flagellin-sensing 2 (FLS2) is a surface-localized receptor that recognizes bacterial flagellin. The immune function of FLS2 is compromised in early stages of shoot development. However, the underlying mechanism for the age-dependent FLS2 signaling is not clear. Here, we show that the reduced basal immunity of juvenile leaves against Pseudomonas syringae pv. tomato DC3000 is independent of FLS2. The flg22-induced marker gene expression and ROS activation were comparable in juvenile and adult stage, but callose deposition was more evident in the adult stage than that of juvenile stage. We further demonstrated that microRNA156, a master regulator of plant aging, suppressed callose deposition in juvenile leaves in response to flg22 but not the expression of FLS2 and FRK1 (Flg22-induced receptor-like kinase 1). Altogether, we revealed an intrinsic mechanism that regulates the amplitude of FLS2-mediated resistance during aging.

plant biology↗

bioRxiv2023

Single-cell transcriptomic landscape deciphers novel olfactory neuroblastoma subtypes and intratumoral heterogeneity

Olfactory neuroblastoma (ONB) is an uncommon malignant tumor known to originate from the olfactory epithelial. The complex tumor ecosystem of this pathology remained unclear. Here, we explored the cellular components with ONB tumors based on scRNA profiles of 96,325 single-cells derived from 10 tumors and 1 olfactory mucosa sample. We discovered 11 major cell types, including 6 immune cell, 3 stromal cell subtypes and epithelial cluster in the tumor microenvironment (TME), and identified 5 common expression programs from malignant epithelial cells. We analyzed subclusters of TME and the interactions among different cell types in the TME. An innovative three-classification of ONB was established via scRNA analysis. Markers for categorizing tumor samples into new subtypes were elucidated. Different responses towards certain chemotherapy regimens could be inferred according to the molecular features of three tumor types. Relative abundance of immunosuppressive TAMs indicated the benefits of immunotherapies targeting myeloid cells.

cancer biology↗

bioRxiv2023

Differentiated genomic footprints and connections inferred from 440 Hmong-Mien genomes suggest their isolation and long-distance migration

BackgroundThe underrepresentation of Hmong-Mien (HM) people in Asian genomic studies has hindered our comprehensive understanding of population history and human health. South China is an ethnolinguistically diverse region and indigenously settled by ethnolinguistically diverse HM, Austroasiatic (AA), Tai-Kadai (TK), Austronesian (AN), and Sino-Tibetan (ST) people, which is regarded as East Asias initial cradle of biodiversity. However, previous fragmented genetic studies have only presented a fraction of the landscape of genetic diversity in this region, especially the lack of haplotype-based genomic resources. The deep characterization of demographic history and natural-selection-relevant architecture in HM people was necessary. ResultsWe comprehensively reported the population-specific genomic resources and explored the fine-scale genetic structure and adaptative features inferred from the high-density SNP data in 440 individuals from 34 ethnolinguistic populations, including previously unreported She. We identified solid genetic differentiation between inland (Miao/Yao) and coastal (She) southern Chinese HM people, and the latter obtained more gene flow from northern East Asians. Multiple admixture models further confirmed that extensive gene flow from surrounding ST, TK, and AN people entangled in forming the gene pool of coastal southeastern East Asian HM people. Population genetic findings of isolated shared unique ancestral components based on the sharing alleles and haplotypes deconstructed that HM people from Yungui Plateau carried the breadth of genomic diversity and previously unknown genetic features. We identified a direct and recent genetic connection between Chinese and Southeast Asian HM people as they shared the most extended IBD fragments, supporting the long-distance migration hypothesis. Uniparental phylogenetic topology and Network relationship reconstruction found ancient uniparental lineages in southwestern HM people. Finally, the population-specific biological adaptation study identified the shared and differentiated natural-selection signatures among inland and coastal HM people associated with physical features and immune function. The allele frequency spectrum (AFS) of clinical cancer susceptibility alleles and pharmacogenomic genes showed significant differences between HM and northern Chinese people. ConclusionsOur extensive genetic evidence combined with the historic documents supported the view that ancient HM people originated in Yungui regions associated with ancient Three-Miao tribes descended from the ancient Daxi-Qujialing-Shijiahe people. And then, some recently rapidly migrated to Southeast Asia, and some culturally dispersed eastward and mixed respectively with Southeast Asian indigenes, coastal Liangzhu-related ancient populations, and incoming southward Sino-Tibetan people. Generally, complex population migration, admixture, and adaptation history contributed to their specific patterns of non-coding or disease-related genetic variations.

genetics↗

bioRxiv2022

Lower socioeconomic status is associated with greater neural responses to deviance in the ambient environment

Humans early life experience varies by socioeconomic status, raising the question of how this difference is reflected in the adult brain. An important aspect of brain function is the ability to detect salient ambient changes while focusing on a task. Here we ask whether perceived childhood social standing is reflected by the way young adults brain signals correlate with detecting changes in irrelevant information. In two studies (total N = 58), we examine electrical brain responses in the frontocentral region to a series of auditory tones, consisting of "standard" stimuli (80%) and "deviant" stimuli (20%) interspersed randomly, while participants were engaged in various visual tasks. Both studies showed stronger automatic change detection indexed by mismatch negativity (MMN) in lower-SES individuals, regardless of the sounds features, emotional content, or study type. Moreover, we observed a larger MMN in lower-SES participants, even though they did not show differences in brain and behavior responses to the attended task and did not involuntarily orient more attention to deviance, as indexed by the P3a. The study indicates that individuals with lower subjective social status may have an increased ability to automatically detect changes in their environment, which may suggest their adaptation to their childhood environments.

neuroscience↗

bioRxiv2022

Distinct function of SPL genes in age-related resistance in Arabidopsis

In plants, age-related resistance (ARR) refers to a gain of disease resistance during shoot or organ maturation. ARR associated with vegetative phase change, a transition from juvenile to adult stage, is a widespread agronomic trait affecting resistance against multiple pathogens. How innate immunity in a plant is differentially regulated during successive stages of shoot maturation is unclear. In this work, we found that Arabidopsis thaliana showed ARR against its bacterial pathogen Pseudomonas syringae pv. tomato DC3000 during vegetative phase change. The timing of the ARR activation was associated with a temporal drop of miR156 level. A systematic inspection of the loss- and gain-of-function mutants of 11 SPL genes revealed that a subset of SPL genes, notably SPL2, SPL10, and SPL11, activated ARR in adult stage. The immune function of SPL10 was independent of its role in morphogenesis. Furthermore, the SPL10 mediated an age-dependent augmentation of the salicylic acid (SA) pathway partially by direct activation of PAD4. Disrupting SA biosynthesis or signaling abolished the ARR against Pto DC3000. Our work demonstrated that the miR156-SPL10 module in Arabidopsis is deployed to operate immune outputs over developmental timing. SignificanceAge-associated change of immunity is a widespread phenomenon in animals and plants. How organisms integrate immune maturation into a developmental clock is a fundamental question. Heterochronic microRNAs are key regulators of developmental timing. We found that a conserved heterochronic microRNA (miRNA) in Arabidopsis, microRNA156, regulates the timing of age-related resistance associated with a transition from the juvenile to the adult vegetative phase. The coordination between developmental maturation and gain of disease resistance is achieved through miR156-controlled SPL transcription factors with distinct functions. A subset of SPL transcription factors promoted resistance by directly activating key genes in defense signaling. This work bridges the knowledge gap between vegetative development and age-related resistance. Pinpointing mechanisms of the developmental regulation on immunity may pave a way for unlocking the age limit on plant immunity and lay a foundation to applications in the precision agriculture.

plant biology↗

bioRxiv2022

Biologically-informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post-treatment glioblastoma

Intratumoral heterogeneity poses a significant challenge to the diagnosis and treatment of glioblastoma (GBM). This heterogeneity is further exacerbated during GBM recurrence, as treatment-induced reactive changes produce additional intratumoral heterogeneity that is ambiguous to differentiate on clinical imaging. There is an urgent need to develop non-invasive approaches to map the heterogeneous landscape of histopathological alterations throughout the entire lesion for each patient. We propose to predictively fuse Magnetic Resonance Imaging (MRI) with the underlying intratumoral heterogeneity in recurrent GBM using machine learning (ML) by leveraging image-localized biopsies with their associated locoregional MRI features. To this end, we develop BioNet, a biologically-informed neural network model, to predict regional distributions of three tissue-specific gene modules: proliferating tumor, reactive/inflammatory cells, and infiltrated brain tissue. BioNet offers valuable insights into the integration of multiple implicit and qualitative biological domain knowledge, which are challenging to describe in mathematical formulations. BioNet performs significantly better than a range of existing methods on cross-validation and blind test datasets. Voxel-level prediction maps of the gene modules by BioNet help reveal intratumoral heterogeneity, which can improve surgical targeting of confirmatory biopsies and evaluation of neuro-oncological treatment effectiveness. The non-invasive nature of the approach can potentially facilitate regular monitoring of the gene modules over time, and making timely therapeutic adjustment. These results also highlight the emerging role of ML in precision medicine.

cancer biology↗

bioRxiv2022

Machine learning prediction of cancer cell metabolism from autofluorescence lifetime images

Metabolic reprogramming at a cellular level contributes to many diseases including cancer, yet few assays are capable of measuring metabolic pathway usage by individual cells within living samples. Here, we combine autofluorescence lifetime imaging with single-cell segmentation and machine-learning models to predict the metabolic pathway usage of cancer cells. The metabolic activities of MCF7 breast cancer cells and HepG2 liver cancer cells were controlled by growing the cells in culture media with specific substrates and metabolic inhibitors. Fluorescence lifetime images of two endogenous metabolic coenzymes, reduced nicotinamide adenine dinucleotide (NADH) and oxidized flavin adenine dinucleotide (FAD), were acquired by a multi-photon fluorescence lifetime microscope and analyzed at the cellular level. Quantitative changes of NADH and FAD lifetime components were observed for cells using glycolysis, oxidative phosphorylation, and glutaminolysis. Conventional machine learning models trained with the autofluorescence features classified cells as dependent on glycolytic or oxidative metabolism with 90 - 92% accuracy. Furthermore, adapting convolutional neural networks to predict cancer cell metabolic perturbations from the autofluorescence lifetime images provided improved performance, 95% accuracy, over traditional models trained via extracted features. In summary, autofluorescence lifetime imaging combined with machine learning models can detect metabolic perturbations between glycolysis and oxidative metabolism of living samples at a cellular level, providing a label-free technology to study cellular metabolism and metabolic heterogeneity.

bioengineering↗

bioRxiv2022

The direct interaction with transcriptional factor TEAD4 implied a straightforward regulation mechanism of tumor suppressor NF2

As an output effecter of Hippo signaling pathway, the transcription factor TEAD and co-activator YAP play crucial functions in promoting cell proliferation and organ size. The tumor suppressor NF2 has been shown to activate LATS1/2 kinases and interplay with Hippo pathway to suppress YAP-TEAD complex. But, whether and how NF2 could directly regulate TEAD remains unknown. We identified a direct link and physical interaction between NF2 and TEAD4. NF2 interacted with TEAD4 through its FERM domain and the C-terminal tail, and decreased protein stability of TEAD4 independently of LATS1/2 and YAP. Furthermore, NF2 inhibited TEAD4 palmitoylation and retained the cytoplasmic translocation of TEAD4, resulting in ubiquitination and dysfunction of TEAD4. Moreover, the interaction with TEAD4 is required for NF2 function to suppress cell proliferation. These findings revealed a new role of NF2 as a binding partner and inhibitor of the transcription factor TEAD, and would shed light on an alternative mechanism of how NF2 functions as a tumor suppressor through the Hippo signaling cascade.

cell biology↗

bioRxiv2022

Metals and metal isotopes in insect wings: Implications for diet, geolocation and pollution exposure

Anthropogenic activities are exposing insects to abnormal levels of toxic metals, with unknown implications for migratory insects. Simultaneously, metals and metal isotopes have become promising tools for the geolocation of migratory insects. Furthering our understanding of metal cycling in insect tissues is essential, both for the development of metals and metal isotopes as geolocation tools, and for assessing the toxicity risks of metals to insects. We conducted a diet-switching experiment on monarch butterflies (Danaus plexippus) with controlled larval and adult diets to evaluate the dietary and environmental sources of 23 metals and metalloids, strontium isotopes, and lead isotopes to insect wing tissues over a period of 8 weeks. Concentrations of Ca, Co, and Sb differed between the sexes. Ni and Zn bioaccumulated in the insect wing tissues over time, likely from the adult diet, while increases in Al, Cr, Cd, Cu, Fe, and Pb were likely from external sources (i.e., dust aerosols). Bioaccumulation of Pb in the monarch wings was confirmed by Pb isotopes to be from external anthropogenic sources, revealing the potential of Pb isotopes to become an indicator and tracer of metal pollution exposure along migratory paths. Concentrations of Ba, Cs, Mg, Na, Rb, Sr, Ti, Tl, and U appeared to be unaffected by dietary or environmental contamination and should be further developed for geolocation purposes. Strontium isotope ratios remained indicative of the larval diet, at least in males, supporting its potential as a geolocation tool. However, the difference in strontium isotope ratios between sexes, as well as the possibility of external contamination by wetting, requires further investigation. Our results demonstrate the complexity of metal cycling in insects and the need for further investigations, as well as the value of studying metals to develop new tools to quantify pollution exposure, metal toxicity and insect mobility.

ecology↗

bioRxiv2022

Comprehensive cell atlas of the first-trimester developing human brain

The adult human brain likely comprises more than a thousand kinds of neurons, and an unknown number of glial cell types, but how cellular diversity arises during early brain development is not known. Here, in order to reveal the precise sequence of events during early brain development, we used single-cell RNA sequencing and spatial transcriptomics to uncover cell states and trajectories in human brains at 5 - 14 post-conceptional weeks (p.c.w.). We identified twelve major classes and over 600 distinct cell states, which mapped to precise spatial anatomical domains at 5 p.c.w. We uncovered detailed differentiation trajectories of the human forebrain, and a surprisingly large number of region-specific glioblasts maturing into distinct pre-astrocytes and pre-oligodendrocyte precursor cells (pre-OPCs). Our findings reveal the emergence of cell types during the critical first trimester of human brain development.

developmental biology↗

bioRxiv2022

Clustering of CaV1.3 L-type calcium channels by Shank3

Clustering of neuronal L-type voltage-gated Ca2+ channels (LTCC) in the plasma membrane is increasingly implicated in creating highly localized Ca2+ signaling nanodomains. For example, LTCC activation can increase phosphorylation of the nuclear CREB transcription factor by increasing Ca2+ concentrations within a nanodomain close to the channel, without requiring bulk Ca2+ increases in the cytosol or nucleus. However, the molecular basis for LTCC clustering is poorly understood. The postsynaptic scaffolding protein Shank3 specifically associates with one of the major neuronal LTCCs, the CaV1.3 calcium channel, and is required for optimal LTCC-dependent excitation-transcription coupling. Here, we co-expressed CaV1.3 1 subunits with two distinct epitope-tags with or without Shank3 in HEK cells. Co-immunoprecipitation studies using the cell lysates revealed that Shank3 can assemble multiple CaV1.3 1 subunits in a complex under basal conditions. Moreover, CaV1.3 LTCC complex formation was facilitated by CaV{beta} subunits ({beta}3 and {beta}2a), which also interact with Shank3. Shank3 interactions with CaV1.3 LTCCs and multimeric CaV1.3 LTCC complex assembly were disrupted following addition of Ca2+ and calmodulin (Ca2+/CaM) to cell lysates, perhaps simulating conditions within an activated CaV1.3 LTCC nanodomain. In intact HEK293T cells, co-expression of Shank3 enhanced the intensity of membrane-localized CaV1.3 LTCC clusters under basal conditions, but not after Ca2+channel activation. Live cell imaging studies also revealed that Ca2+ influx through LTCCs disassociated Shank3 from CaV1.3 LTCCs clusters and reduced the CaV1.3 cluster intensity. Deletion of the PDZ domain from Shank3 prevented both binding to CaV1.3 and the changes in multimeric CaV1.3 LTCC complex assembly in vitro and in HEK293 cells. Finally, we found that shRNA knock-down of Shank3 expression in cultured rat primary hippocampal neurons reduced the intensity of surface-localized CaV1.3 LTCC clusters in dendrites. Taken together, our findings reveal a novel molecular mechanism contributing to neuronal LTCC clustering under basal conditions.

neuroscience↗

bioRxiv2022

Transcriptomic diversity of cell types across the adult human brain

The human brain directs a wide range of complex behaviors ranging from fine motor skills to abstract intelligence and emotion. However, the diversity of cell types that support these skills has not been fully described. Here we used high-throughput single-nucleus RNA sequencing to systematically survey cells across the entire adult human brain in three postmortem donors. We sampled over three million nuclei from approximately 100 dissections across the forebrain, midbrain, and hindbrain. Our analysis identified 461 clusters and 3313 subclusters organized largely according to developmental origins. We found area-specific cortical neurons, as well as an unexpectedly high diversity of midbrain and hindbrain neurons. Astrocytes also exhibited regional diversity at multiple scales, comprising subtypes specific to the telencephalon and to more precise anatomical locations. Oligodendrocyte precursors comprised two distinct major types specific to the telencephalon and to the rest of the brain. Together, these findings demonstrate the unique cellular composition of the telencephalon with respect to all major brain cell types. As the first single-cell transcriptomic census of the entire human brain, we provide a resource for understanding the molecular diversity of the human brain in health and disease.

neuroscience↗

bioRxiv2022

Host transcriptome and microbiomeinteractions in Holstein cattle under heatstress condition

Climate changes affects animal physiology. In particular, rising ambient temperatures reduce animal vitality due to heat stress and this can be observed at various levels which included genome, transcriptome, and microbiome. In a previous study, microbiota highly associated with changes in cattle physiology were identified under heat stress conditions which included rectal temperature, drooling score, and respiratory score. In the present study, genes differentially expressed between individuals were selected representing different additive genetic effects towards the heat stress response in cattle in their production condition. Moreover, a correlation network analysis was performed to identify interactions between the transcriptome and microbiome for 71 Chinese Holstein cows sequenced for mRNA from blood samples and for 16S rRNA genes from fecal samples. Bioinformatics analysis was performed comprising: i) clustering and classification of 16S rRNA sequence reads, ii) mapping cows transcripts to the reference genome and their expression quantification, and iii) statistical analysis of both data types - including differential gene expression analysis and gene set enrichment analysis. A weighted co-expression network analysis was carried out to assess changes in the association between gene expression and microbiota abundance as well as to find hub genes/microbiota responsible for the regulation of gene expression under heat stress. Results showed 1,851 differentially expressed genes were found that were shared by three heat stress phenotypes. These genes were predominantly associated with the cytokine-cytokine receptor interaction pathway. The interaction analysis revealed three modules of genes and microbiota associated with rectal temperature with which two hubs of those modules were bacterial species, demonstrating the importance of the microbiome in the regulation of gene expression during heat stress. Genes and microbiota from the significant modules can be used as biomarkers of heat stress in cattle.

bioinformatics↗