Biology subjects

Huang, Y.

Publications and source records attributed to Huang, Y..

At least 829 records · Page 46Linked to original sources

bioRxiv2020

A body map of somatic mutagenesis in morphologically normal human tissues

Somatic mutations accumulated in normal tissues are associated with aging and disease. Here, we performed a comprehensive genomic analysis of 1,737 morphologically normal tissue biopsies (~ 600 cells each), mostly from the epithelia, of nine organs from five donors. We found that somatic mutation accumulations and clonal expansions are widespread, although with variable extent, in morphologically normal human tissues. Somatic copy number alterations were rarely detected, except for tissues from esophagus and cardia. Endogenous mutational processes like SBS1 and SBS5 are ubiquitous among normal tissues though exhibiting different relative activities. Exogenous mutational processes like SBS22 were found in different tissues from the same donor. We reconstructed the spatial somatic clonal architecture with sub-millimeter resolution. In epithelial tissues from esophagus and cardia, macroscopic somatic clones expanded to several millimeters were frequently seen, whereas in tissues from colon, rectum, and duodenum somatic clones were microscopic in size and evolved independently. Our study depicted a body map of somatic mutations and clonal expansions from the same individuals, and it revealed that the degree of somatic clonal expansion and enrichment of driver mutations are highly organ specific.

genomics↗

bioRxiv2020

A fish-specific new gene evolves new functions in cichlid fishes

Deciphering why some lineages produce spectacular radiations while others do not provides important insights into biodiversity, but the molecular basis underlying this process remains largely unknown. Here, we identified a lineage-restricted gene, which we named lg. Combined omics analyses showed that lg is under positive selection in the most species-rich lineage of cichlid fishes, the modern haplochromine (MH) lineage, indicating its evolutionary advantage. Using transgenic zebrafish, we functionally showed that a cichlid fish-specific upstream insertion of lg can drive new and strong eGFP expression in tissues noted for adaptation in the MH lineage, but not in other lineages. Furthermore, the deletion of three MH-specific SNPs within this region can reconstitute weak and limited expression patterns similar to those in non-MH lineages. We thus demonstrated that a series of cis-regulatory changes in an advantageous gene are linked with a gain of expression that is related to an astonishingly adaptive radiative lineage.

evolutionary biology↗

bioRxiv2020

Sparse Epistatic Regularization of Deep Neural Networks for Inferring Fitness Functions

Despite recent advances in high-throughput combinatorial mutagenesis assays, the number of labeled sequences available to predict molecular functions has remained small for the vastness of the sequence space combined with the ruggedness of many fitness functions. Expressive models in machine learning (ML), such as deep neural networks (DNNs), can model the nonlinearities in rugged fitness functions, which manifest as high-order epistatic interactions among the mutational sites. However, in the absence of an inductive bias, DNNs overfit to the small number of labeled sequences available for training. Herein, we exploit the recent biological evidence that epistatic interactions in many fitness functions are sparse; this knowledge can be used as an inductive bias to regularize DNNs. We have developed a method for sparse epistatic regularization of DNNs, called the epistatic net (EN), which constrains the number of non-zero coefficients in the spectral representation of DNNs. For larger sequences, where finding the spectral transform becomes computationally intractable, we have developed a scalable extension of EN, which subsamples the combinatorial sequence space uniformly inducing a sparse-graph-code structure, and regularizes DNNs using the resulting greedy optimization method. Results on several biological landscapes, from bacterial to protein fitness functions, show that EN consistently improves the prediction accuracy of DNNs and enables them to outperform competing models which assume other forms of inductive biases. EN estimates all the higher-order epistatic interactions of DNNs trained on massive sequence spaces--a computational problem that takes years to solve without leveraging the epistatic sparsity in the fitness functions.

bioinformatics↗

bioRxiv2020

STAT3 inhibits Myocardin induced cardiac hypertrophy

BackgroundIn order to explore the molecular mechanism of cardiomyocyte-dependent myocardial gene expression and cardiomyocyte differentiation in cardiac hypertrophy, and to provide new insights for cardiac hypertrophy. MethodsCardiac myocytes were isolated from day 1-3 Sprague-Dawley rat pups. Real time quantitative PCR, western blot and immunocytochemistry Assay were used to detect the expression and localization of related genes. CO-IP was used to detect direct protein interactions between Myocardin and STAT3. Luciferase reporter assay and chromatin immunoprecipitation were used to detect the binding of Myocardin to the promoter of a downstream target gene. Microinjection of zebrafish embryos was used to examine the effects of STAT3 and Myocardin interactions on cardiac development in vivo ResultsThe N-terminus of STAT3 directly binds to the basic domain of myocardin and inhibits the transcriptional activity of Myocardin-mediated cardiac-specific genes ANF and -actinin, thereby inhibiting their expression, and further inhibit myocardin-mediated cardiac hypertrophy in vivo. ConclusionsIn summary, our report states that signal transduction and transcriptional activation factor 3 (STAT3) are inhibitors of the major cardiac hypertrophic transcription factor Myocardiin, which is required for cardiomyocyte differentiation. The STAT3-cardiacin interaction identified nuclear hormone receptor-mediated and cardiac-specific gene-regulated convergence sites and suggested a possible mechanism for cardioprotective effects.

cell biology↗

bioRxiv2020

GEMC1-MCIDAS transcriptional program regulates multiciliogenesis in the choroid plexus and acts as a barrier to tumorigenesis

Multiciliated cells (MCCs) in the brain include the ependymal cells and choroid plexus (CP) epithelial cells. The CP secretes cerebrospinal fluid that circulates within the ventricular system, driven by ependymal cilia movement. However, the mechanisms and functional significance of multiciliogenesis in the CP remain unknown. Deregulated oncogenic signals cause CP carcinoma (CPC), a rare but aggressive pediatric brain cancer. Here we show that aberrant NOTCH and Sonic Hedgehog signaling in mice drive tumors that resemble CPC in humans. NOTCH-driven CP tumors were monociliated, whereas disruption of the NOTCH complex restored multiciliation and decreased tumor growth. NOTCH suppressed multiciliation in tumor cells by inhibiting the expression of GEMC1 and MCIDAS, early regulators of multiciliogenesis. Consistently, GEMC1-MCIDAS function is essential for multiciliation in the CP, and is critical for correcting multiciliation defect in tumor cells by a NOTCH inhibitor. Disturbances to the GEMC1 program are commonly observed in human CPCs characterized by solitary cilia. Consistently, CPC driven by deletion of Trp53 and Rb1 in mice exhibits a cilia deficit consequent to loss of Gemc1-Mcidas expression. Taken together, these findings reveal a GEMC1-MCIDAS multiciliation program in the CP critical for inhibiting tumorigenesis, and it may have therapeutic implications for the treatment of CPC.

cancer biology↗

bioRxiv2020

Surfaceome CRISPR Screen Identifies OLFML3 as a Rhinovirus-inducible IFN Antagonist

BackgroundRhinoviruses (RVs) cause more than half of common cold and, in some cases, more severe diseases. Functional genomics analyses of RVs using siRNA or genome-wide CRISPR screen uncovered a limited set of host factors, few of which has proven clinical relevance. ResultsHerein, we systematically compared genome-wide CRISPR screen and surface protein-focused CRISPR screen, referred to as surfaceome CRISPR screen, for their efficiencies in identifying RV host factors. It was found that surfaceome screen outperformed genome-wide screen in the success rate of hit identification. Importantly, using surfaceome screen we have identified olfactomedin like 3 (OLFML3) as a novel host factor of RV serotypes A and B including a clinical isolate. We found that OLFML3 was a RV-inducible suppressor of the innate immune response and that OLFML3 antagonized type I interferon (IFN) signaling in a SOCS3-dependent manner. ConclusionOur study has suggested that RV-induced OLFML3expression is an important mechanism for RV to hijack the immune system and underscored surfaceome CRISPR screen in identifying viral host factors.

molecular biology↗

bioRxiv2020

Computational identification of splicing phenotypes from single cell transcriptomic experiments

RNA splicing is an important driver of heterogeneity in single cells, both through the expression of alternative transcripts and as a major determinant of transcriptional kinetics. However, the intrinsic coverage limitations of scRNA-seq technologies make it challenging to associate specific splicing events to cell-level phenotypes. Here, we present BRIE2, a scalable computational method that resolves these issues by regressing single-cell transcriptomic data against cell-level features. We show that BRIE2 effectively identifies differential alternative splicing events that are associated with a disease. Additionally, BRIE2 allows a principled selection of genes (differential momentum genes) that capture heterogeneity in transcriptional kinetics and improve quantitatively RNA velocity analyses. BRIE2, therefore, extends the scope of single-cell transcriptomic experiments towards the identification of splicing phenotypes associated with biological changes at the single-cell level.

bioinformatics↗

bioRxiv2020

Aberrant peripheral immune responses in acute Kawasaki disease with single-cell sequencing

Kawasaki disease (KD) is the most common cause of acquired heart disease in children in developed countries. Although diverse immune aberrance was reported, a global understanding of immune responses underlying acute KD was lacking. Based on single-cell sequencing, we profiled peripheral blood mononuclear cells from patients with acute KD before and after intravenous immunoglobulin therapy and from healthy controls. Most differentially expressed genes were derived from monocytes, with upregulation of immunoglobulin receptors, complement and receptors and downregulation of MHC class II receptors before therapy. The percentage of B cells was significantly increased before therapy and rapidly returned to normal after therapy. There was also an increased abundance of B-cell receptors with IGHA and IGHG after therapy, accompanied by massive oligoclonal expansion. The percentage of CD8 T cells was remarkably decreased during acute KD, especially the subset of effector memory CD8 T cells. All lymphocyte compartments were characterized by underexpressed interferon response pathways before therapy. The identification of unique innate and adaptive immune responses suggests potential mechanisms underlying pathogenesis and progression of KD.

immunology↗

bioRxiv2020

Pairwise genetic interactions modulate lipid plasma levels and cellular uptake

Genetic interactions (GIs), the joint impact of different genes or variants on a phenotype, are foundational to the genetic architecture of complex traits. However, identifying GIs through human genetics is challenging since it necessitates very large population sizes, while findings from model systems not always translate to humans. Here, we combined exome-sequencing and genotyping in the UK Biobank with combinatorial RNA-interference (coRNAi) screening to systematically test for pairwise GIs between 30 lipid GWAS genes. Gene-based protein-truncating variant (PTV) burden analyses from 240,970 exomes revealed additive GIs for APOB with PCSK9 and LPL, respectively. Both, genetics and coRNAi identified additive GIs for 12 additional gene pairs. Overlapping non-additive GIs were detected only for TOMM40 at the APOE locus with SORT1 and NCAN. Our study identifies distinct gene pairs that modulate both, plasma and cellular lipid levels via additive and non-additive effects and nominates drug target pairs for improved lipid-lowering combination therapies.

genetics↗

bioRxiv2020

Disruption of a GATA2, TAL1, ERG regulatory circuit promotes erythroid transition in healthy and leukemic stem cells

Changes in gene regulation and expression govern orderly transitions from hematopoietic stem cells to terminally differentiated blood cell types. These transitions are disrupted during leukemic transformation but knowledge of the gene regulatory changes underpinning this process is elusive. We hypothesised that identifying core gene regulatory networks in healthy hematopoietic and leukemic cells could provide insights into network alterations that perturb cell state transitions. A heptad of transcription factors (LYL1, TAL1, LMO2, FLI1, ERG, GATA2, RUNX1) bind key hematopoietic genes in human CD34+ haematopoietic stem and progenitor cells (HSPCs) and have prognostic significance in acute myeloid leukemia (AML). These factors also form a densely interconnected circuit by binding combinatorially at their own, and each others, regulatory elements. However, their mutual regulation during normal haematopoiesis and in AML cells, and how perturbation of their expression levels influences cell fate decisions remains unclear. Here, we integrated bulk and single cell data and found that the fully connected heptad circuit identified in healthy HSPCs persists with only minor alterations in AML, and that chromatin accessibility at key heptad regulatory elements was predictive of cell identity in both healthy progenitors and in leukemic cells. The heptad factors GATA2, TAL1 and ERG formed an integrated sub-circuit that regulates stem cell to erythroid transition in both healthy and leukemic cells. Components of this triad could be manipulated to facilitate erythroid transition providing a proof of concept that such regulatory circuits could be harnessed to promote specific cell type transitions and overcome dysregulated haematopoiesis.

cancer biology↗

bioRxiv2020

Complete and haplotype-specific sequence assembly of segmental duplication-mediated genome rearrangements using targeted CRISPR-targeted ultra-long read sequencing (CTLR-Seq)

We have developed a generally applicable method based on CRISPR/Cas9-targeted ultra-long read sequencing (CTLR-Seq) to completely and haplotype-specifically resolve, at base-pair resolution, large, complex, and highly repetitive genomic regions that had been previously impenetrable to next-generation sequencing analysis such as large segmental duplication (SegDup) regions and their associated genome rearrangements that stretch hundreds of kilobases. Our method combines in vitro Cas9-mediated cutting of the genome and pulse-field gel electrophoresis to haplotype-specifically isolate intact large (200-550 kb) target regions that encompass previously unresolvable genomic sequences. These target fragments are then sequenced (amplification-free) to produce ultra-long reads at up to 40x on-target coverage using Oxford nanopore technology, allowing for the complete assembly of the complex genomic regions of interest at single base-pair resolution. We applied CTLR-Seq to resolve the exact sequence of SegDup rearrangements that constitute the boundary regions of the 22q11.2 deletion CNV and of the 16p11.2 deletion and duplication CNVs. These CNVs are among the strongest known risk factors for schizophrenia and autism. We then perform de novo assembly to resolve, for the first time, at single base-pair resolution, the sequence rearrangements of the 22q11.2 and 16p11.2 CNVs, mapping out exactly the genes and non-coding regions that are affected by the CNV for different carriers.

genomics↗

bioRxiv2020

Resolving a Systematic Error in STARR-seq for QuantitativeEnhancer Activity Mapping

STARR-seq assesses millions of fragments in parallel measuring enhancer activity quantitatively. Here we show that STARR-seq is critically flawed with a systematic error in the cells of Arabidopsis thaliana (A. thaliana). Large amount of self-transcripts (STs) is lost during reverse transcription because these STs are polyadenylated after alternative polyadenylation sites (APAS) inside the test sequences. We solved this problem by using specially designed primer and recovered self-transcribed sequences independent from the PAS usage. In A. thaliana, we identified active enhancers and also enhancers quiescent in their endogenous genomic loci. Different from traditional STARR-seq identified enhancers, enhancers identified by new method are highly enriched in sequences proximal to the 5 and 3 ends of genes, and their epigenetic states correlate with gene expression levels. Our solution applies to methods based on self-transcript quantification. In addition, our results provide an invaluable functional enhancer activity map and insights into the functional complexity of enhancers in A. thaliana.

genetics↗

bioRxiv2020

ATPIF1 inactivation promotes antitumor immunity through metabolic reprogramming of CD8+ T cells

Induction of CD8+ T cell activity is a promising strategy in the cancer immunotherapy. In this study, we identified ATP synthase inhibitory factor 1 (ATPIF1) as a potential target in the induction of CD8+ T cell immunity against tumor. Inactivation of ATPIF1 gene in mice promoted the antitumor activity of CD8+ T cells leading to suppression of tumor growth of B16 melanoma and Lewis lung cancer. The phenotype was abolished by deletion of CD8+ T cells in the ATPIF1-KO mice. The tumor infiltrating CD8+ T cells exhibited strong activities in the proliferation, effector and memory as revealed by the single cell RNA sequencing results of CD45+ tumor infiltrating lymphocytes (TILs) isolated from the tumors. The CD8+ T cells expressed more antitumor makers in the tumor microenvironment and in coculture with the tumor cells. The cells had a higher level of glycolysis after the T cell receptor-mediated activation as revealed by the targeted metabolomics assay. The cells exhibited an extra activity of oxidative phosphorylation before the activation as indicated by the oxygen consumption rate. The cells gained capacities in the proliferation, apoptosis resistance and mitophagy in the glucose-limiting environment. These data suggest that inhibition of ATPIF1 activity by gene inactivation rewired the energy metabolism of CD8+ T cells to enhance their immune activities to the tumors. ATPIF1 is a potential molecular target in the induction of antitumor immunity through metabolic reprogramming of CD8+ T cells for the cancer immunotherapy.

immunology↗

bioRxiv2020

Multimodal single-cell/nucleus RNA-sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer's disease

Systematic identification of molecular networks in disease relevant immune cells of the nervous system is critical for elucidating the underlying pathophysiology of Alzheimers disease (AD). Two key immune cell types, disease-associated microglia (DAM) and disease-associated astrocytes (DAA), are biologically involved in AD pathobiology. Therefore, uncovering molecular determinants of DAM and DAA will enhance our understanding of AD biology, potentially identifying novel therapeutic targets for AD treatment. Here, we present an integrative, network-based methodology to uncover conserved molecular networks between DAM and DAA. Specifically, we leverage single-cell and single-nucleus RNA sequencing data from both AD transgenic mouse models and AD patient brains, drug-target networks, metabolite-enzyme associations, and the human protein-protein interactome, along with large-scale patient data validation from the MarketScan Medicare Supplemental Database. We find that common and unique molecular network regulators between DAM (i.e, PAK1, MAPK14, and SYK) and DAA (i.e., NFKB1, FOS, and JUN) are significantly enriched by multiple neuro-inflammatory pathways and well-known genetic variants (i.e., BIN1) from genome-wide association studies. Further network analysis reveal shared immune pathways between DAM and DAA, including Fc gamma R-mediated phagocytosis, Th17 cell differentiation, and chemokine signaling. Furthermore, integrative metabolite-enzyme network analyses imply that fatty acids (i.e., elaidic acid) and amino acids (i.e., glutamate, serine, and phenylalanine) may trigger molecular alterations between DAM and DAA. Finally, we prioritize repurposed drug candidates for potential treatment of AD by agents that specifically reverse dysregulated gene expression of DAM or DAA, including an antithrombotic anticoagulant triflusal, a beta2-adrenergic receptor agonist salbutamol, and the steroid medications (fluticasone and mometasone). Individuals taking fluticasone (an approved anti-inflammatory and inhaled corticosteroid) displayed a significantly decreased incidence of AD (hazard ratio (HR) = 0.858, 95% confidence interval [CI] 0.829-0.888, P < 0.0001) in retrospective case-control validation. Furthermore, propensity score matching cohort studies also confirmed an association of mometasone with reduced incidence of AD in comparison to fluticasone (HR =0.921, 95% CI 0.862-0.984, P < 0.0001).

neuroscience↗

bioRxiv2020

Multivariate GWAS elucidates the genetic architecture of alcohol consumption and misuse, corrects biases, and reveals novel associations with disease

Genome-wide association studies (GWASs) of the Alcohol Use Disorder Identification Test (AUDIT), a ten-item screener for alcohol use disorder (AUD), have elucidated novel loci for alcohol consumption and misuse. However, these studies also revealed that GWASs can be influenced by numerous biases (e.g., measurement error, selection bias), which have led to inconsistent genetic correlations between alcohol involvement and AUD, as well as paradoxically negative genetic correlations between alcohol involvement and psychiatric disorders/medical conditions. To explore these unexpected differences in genetic correlations, we conducted the first item-level and largest GWAS of AUDIT items (N=160,824), and applied a multivariate framework to mitigate previous biases. In doing so, we identified novel patterns of similarity (and dissimilarity) among the AUDIT items, and found evidence of a correlated two-factor structure at the genetic level (Consumption and Problems, rg=.80). Moreover, by applying empirically-derived weights to each of the AUDIT items, we constructed an aggregate measure of alcohol consumption that is strongly associated with alcohol dependence (rg=.67) and several other psychiatric disorders, and no longer positively associated with health and positive socioeconomic outcomes. Lastly, by performing polygenic analyses in three independent cohorts that differed in their ascertainment and prevalence of AUD, we identified novel genetic associations between alcohol consumption, alcohol misuse, and human health. Our work further emphasizes the value of AUDIT for both clinical and genetic studies of AUD, and the importance of using multivariate methods to study genetic associations that are more closely related to AUD.

genetics↗

bioRxiv2020

Shared and distinct genetic influences between cognitive domains and psychiatric disorder risk based on genome-wide data

Group-level cognitive performance differences are found in psychiatric disorders ranging from depression to autism to schizophrenia. To investigate the genetics of individual differences in fluid and crystallized cognitive abilities and their associations with psychiatric disorder risk, we conducted genome-wide association studies (GWAS) of a total of 335,227 consented 23andMe customers of European descent between the ages of 50 and 85, who completed at least one online test of crystallized cognitive ability (vocabulary knowledge, N=188,434) and/or fluid cognitive ability (visual change detection, N=158 888; digit-symbol substitution, N=132,807). All cognitive measures were significantly heritable (h2=0.10-0.16), and GWAS identified 25 novel genome-wide significant loci. Genetic correlation analyses highlight variable profiles of genetic relationships across tasks and disorders. While schizophrenia had moderate negative genetic correlations with tests of fluid cognition (visual change detection rg=-0.27, p<9.2e-24; digit-symbol substitution rg=-0.26, p<5.2e-27), it was only weakly negatively associated with crystalized cognition (vocabulary knowledge rg=-0.07, p<0.004). Autism, in contrast, showed a robust positive genetic correlation with vocabulary knowledge (rg=0.30, p<5.6e-13) and little to no genetic correlation with either fluid cognition task (rgs<0.08, ps>0.005). Crystalized and fluid cognitive abilities thus have correlated but distinct genetic architectures that relate to those of psychiatric disorders. Understanding the genetic underpinnings of specific cognitive abilities, and their relationships to psychiatric disorder risk, can inform the understanding of disease biology nosology and etiology.

genetics↗

bioRxiv2020

Ubiquitylome Analysis Reveals a Central Role for the Ubiquitin-Proteasome System in Plant Innate Immunity

Protein ubiquitylation profoundly expands proteome functionality and diversifies cellular signaling processes, with recent studies providing ample evidence for its importance to plant immunity. To gain a proteome-wide appreciation of ubiquitylome dynamics during immune recognition, we employed a two-step affinity enrichment protocol based on a 6His-tagged ubiquitin (Ub) variant coupled with high sensitivity mass spectrometry to identify Arabidopsis proteins rapidly ubiquitylated upon plant perception of the microbe-associated molecular pattern (MAMP) peptide flg22. The catalog from two-week-old seedlings treated for only 30 minutes with flg22 contained nearly 1,000 conjugates, 150 Ub footprints, and all seven types of Ub linkages, and included previously uncharacterized conjugates of immune components, such as RECEPTOR-LIKE KINASE 1 (RKL1) shown to negatively regulate plant immunity. In vivo ubiquitylation assays confirmed modification of several candidates upon immune elicitation, and revealed distinct modification patterns and dynamics for key immune components, including poly- and monoubiquitylation, as well as induced or reduced levels of ubiquitylation. Gene ontology and network analyses of the collection also uncovered rapid modification of the Ub-proteasome system itself, suggesting a critical auto-regulatory loop necessary for an effective MAMP-triggered immune response and subsequent disease resistance. Included targets were UBIQUITIN-CONJUGATING ENZYME 13 (UBC13) and proteasome component REGULATORY PARTICLE NON-ATPASE SUBUNIT 8b (RPN8b), whose subsequent biochemical and genetic analyses implied negative roles in immune elicitation. Collectively, our proteomic analyses further strengthened the connection between ubiquitylation and flg22-based immune signaling, identified novel components and pathways regulating plant immunity, and increased the database of ubiquitylated substrates in plants. One-sentence summaryProteome-wide catalogs of ubiquitylated proteins revealed a rapid engagement of the ubiquitin-proteasome system in Arabidopsis innate immunity.

plant biology↗

bioRxiv2020

Contrasting impacts of urban and farmland cover on flying insect biomass

Recent studies report declines in biomass, abundance and diversity of terrestrial insect groups. While anthropogenic land use is one likely contributor to this decline, studies assessing land cover as a driver of insect dynamics are rare and mostly restricted in spatial scale and types of land cover. In this study, we used rooftop-mounted car nets in a citizen science project ( InsectMobile) to allow for large-scale geographic sampling of flying insects across Denmark and parts of Germany. Citizen scientists sampled insects along 278 10 km routes in urban, farmland and semi-natural (grassland, wetland and forest) landscapes in the summer of 2018. We assessed the importance of local to landscape-scale effects and land use intensity by relating insect biomass to land cover in buffers of 50, 250, 500 and 1000 m along the routes. We found a negative association of urban cover and a positive association of farmland on insect biomass at a landscape-scale (1000 m buffer) in both countries. In Denmark, we also found positive effects of all semi-natural land covers, i.e. grassland (largest at the landscape-scale, 1000 m), forests (largest at intermediate scales, 250 m), and wetlands (largest at the local-scale, 50 m). The negative association of insect biomass with urban land cover and positive association with farmland were not clearly modified by any variable associated with land use intensity. Our results show that land cover has an impact on flying insect biomass with the magnitude of this effect varying across spatial scales. Since we consistently found negative effects of urban land cover, our findings highlight the need for the conservation of semi-natural areas, such as wetlands, grasslands and forests, in Europe.

ecology↗