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We present Bisque, a tool for estimating cell type proportions in bulk expression. Bisque implements a regression-based approach that utilizes single-cell RNA-seq (scRNA-seq) or single-nucleus RNA-seq (snRNA-seq) data to generate a reference expression profile and learn gene-specific bulk expression transformations to robustly decompose RNA-seq data. These transformations significantly improve decomposition performance compared to existing methods when there is significant technical variation in the generation of the reference profile and observed bulk expression. Importantly, compared to existing methods, our approach is extremely efficient, making it suitable for the analysis of large genomic datasets that are becoming ubiquitous. When applied to subcutaneous adipose and dorsolateral prefrontal cortex expression datasets with both bulk RNA-seq and snRNA-seq data, Bisque replicates previously reported associations between cell type proportions and measured phenotypes across abundant and rare cell types. We further propose an additional mode of operation that merely requires a set of known marker genes. Traditional methods for determining cell type composition lack scalability, while single-cell technologies remain costly and noisy compared to bulk RNA-seq. Here, the authors present a highly efficient tool to measure cellular heterogeneity in bulk expression through robust integration of single-cell information.

Background Bees are the most important group of pollinators worldwide and their populations are declining. In natural conditions, Apis mellifera depends exclusively on food from the field to meet its physiological demands. In the period of scarcity, available resources are insufficient and artificial supplementation becomes essential for maintaining the levels of vitamins, proteins, carbohydrates, and minerals of colonies. Among these minerals, zinc is essential in all living systems, particularly for the regulation of cell division and protein synthesis, and is a component of more than 200 metalloenzymes. Results The total RNA extracted from the brain tissue of nurse bees exposed to different sources and concentrations of zinc was sequenced. A total of 1,172 genes in the treatment that received an inorganic source of zinc and 502 genes that received an organic source of zinc were found to be differentially expressed among the control group. Gene ontology enrichment showed that zinc can modulate important biological processes such as nutrient metabolism and the molting process. Conclusions Our results indicate that zinc supplementation modulates the expression of many differentially expressed genes and plays an important role in the development of Apis mellifera bees. All the information obtained in this study can contribute to future research in the field of bee nutrigenomics.

Purpose Immunotherapy, such as checkpoint inhibitors against anti-programmed death-ligand 1 (PD-L1), has not been successful in treating patients with pancreatic ductal adenocarcinoma (PDAC). Tumor-associated macrophages (TAMs), myeloid-derived suppressor cells (MDSCs), dendritic cells (DCs), and the TGF-β cytokine are critical in anti-cancer immunity. We hypothesized that TGF-β enhances the immunosuppressive effects of TAM, MDSC, and DC presence in tumors. Methods Using a murine PDAC cell line derived from a genetically engineered mouse model, we orthotopically implanted treated cells plus drug embedded in Matrigel into immunocompetent mice. Treatments included saline control, TGF-β1, or a TGF-β receptor 1 small molecule inhibitor, galunisertib. We investigated TAM, MDSC, DC, and TAM PD-L1 expression with flow cytometry in tumors. Separately, we used the TIMER2.0 database to analyze TAM and PD-L1 gene expression in human PDAC tumors in TCGA database. Results TGF-β did not alter MDSC or DC frequencies in the primary tumors. However, in PDAC metastases to the liver, TGF-β decreased the proportion of MDSCs ( P =0.022) and DCs ( P =0.005). TGF-β significantly increased the percent of high PD-L1 expressing TAMs (32 ± 6 % vs. 12 ± 5%, P =0.013) but not the proportion of TAMs in primary and metastatic tumors. TAM PD-L1 gene expression in TCGA PDAC database was significantly correlated with tgb1 and tgfbr1 gene expression ( P <0.01). Conclusions TGF-β is important in PDAC anti-tumor immunity, demonstrating context-dependent impact on immune cells. TGF-β has an overall immunosuppressive effect mediated by TAM PD-L1 expression and decreased presence of DCs. Future investigations will focus on enhancing anti-cancer immune effects of TGF-β receptor inhibition.

Background Hepatocellular carcinoma (HCC) is a common primary liver cancer with poor overall survival. We hypothesized that there are HCC-associated cell-types that impact patient survival. Methods We combined liver single nucleus (snRNA-seq), single cell (scRNA-seq), and bulk RNA-sequencing (RNA-seq) data to search for cell-type differences in HCC. To first identify cell-types in HCC, adjacent non-tumor tissue, and normal liver, we integrated single-cell level data from a healthy liver cohort ( n  = 9 non-HCC samples) collected in the Strasbourg University Hospital; an HCC cohort ( n  = 1 non-HCC, n  = 14 HCC-tumor, and n  = 14 adjacent non-tumor samples) collected in the Singapore General Hospital and National University; and another HCC cohort ( n  = 3 HCC-tumor and n  = 3 adjacent non-tumor samples) collected in the Dumont-UCLA Liver Cancer Center. We then leveraged these single cell level data to decompose the cell-types in liver bulk RNA-seq data from HCC patients’ tumor ( n  = 361) and adjacent non-tumor tissue ( n  = 49) from the Cancer Genome Atlas (TCGA) multi-center cohort. For replication, we decomposed 221 HCC and 209 adjacent non-tumor liver microarray samples from the Liver Cancer Institute (LCI) cohort collected by the Liver Cancer Institute and Zhongshan Hospital of Fudan University. Results We discovered a tumor-associated proliferative cell-type, Prol (80.4% tumor cells), enriched for cell cycle and mitosis genes. In the liver bulk tissue from the TCGA cohort, the proportion of the Prol cell-type is significantly increased in HCC and associates with a worse overall survival. Independently from our decomposition analysis, we reciprocally show that Prol nuclei/cells significantly over-express both tumor-elevated and survival-decreasing genes obtained from the bulk tissue. Our replication analysis in the LCI cohort confirmed that an increased estimated proportion of the Prol cell-type in HCC is a significant marker for a shorter overall survival. Finally, we show that somatic mutations in the tumor suppressor genes TP53 and RB1 are linked to an increase of the Prol cell-type in HCC. Conclusions By integrating liver single cell, single nucleus, and bulk expression data from multiple cohorts we identified a proliferating cell-type (Prol) enriched in HCC tumors, associated with a decreased overall survival, and linked to TP53 and RB1 somatic mutations.

Reverse causality has made it difficult to establish the causal directions between obesity and prediabetes and obesity and insulin resistance. To disentangle whether obesity causally drives prediabetes and insulin resistance already in non-diabetic individuals, we utilized the UK Biobank and METSIM cohort to perform a Mendelian randomization (MR) analyses in the non-diabetic individuals. Our results suggest that both prediabetes and systemic insulin resistance are caused by obesity (p = 1.2×10-3 and p = 3.1×10-24). As obesity reflects the amount of body fat, we next studied how adipose tissue affects insulin resistance. We performed both bulk RNA-sequencing and single nucleus RNA sequencing on frozen human subcutaneous adipose biopsies to assess adipose cell-type heterogeneity and mitochondrial (MT) gene expression in insulin resistance. We discovered that the adipose MT gene expression and body fat percent are both independently associated with insulin resistance (p≤0.05 for each) when adjusting for the decomposed adipose cell-type proportions. Next, we showed that these 3 factors, adipose MT gene expression, body fat percent, and adipose cell types, explain a substantial amount (44.39%) of variance in insulin resistance and can be used to predict it (p≤2.64×10-5 in 3 independent human cohorts). In summary, we demonstrated that obesity is a strong determinant of both prediabetes and insulin resistance, and discovered that individuals' adipose cell-type composition, adipose MT gene expression, and body fat percent predict their insulin resistance, emphasizing the critical role of adipose tissue in systemic insulin resistance.

Ae. aegypti mosquitoes are considered a global threat to public health due to its ability to transmit arboviruses such as yellow fever, dengue, Zika and Chikungunya to humans. The lack of effective arboviral vaccines and etiological treatments make vector control strategies fundamental in interrupting the transmission cycle of these pathogens. This study evaluated Ae. aegypti mosquito populations pre- and post-intervention period with disseminating stations of the larvicide pyriproxyfen to understand its potential influence on the genetic structure and population diversity of these vectors. This study was conducted in Manacapuru city, Amazonas, Brazil, where 1,000 pyriproxyfen dissemination stations were deployed and monitored from FEB/2014 to FEB/2015 (pre-intervention) and AUG/2015 to JAN/2016 (post-intervention). Low-coverage whole genome sequencing of 36 individuals was performed, revealing significant stratification between pre- and post-intervention groups (pairwise FST estimate of 0.1126; p-value < 0.033). Tajima's D estimates were -3.25 and -3.07 (both p-value < 0.01) for pre- and post-intervention groups, respectively. Molecular diversity estimates (Theta(S) and Theta(Pi)) also showed divergences between pre- and post-intervention groups. PCA and K-means analysis showed clustering for SNP frequency matrix and SNP genotype matrix, respectively, being both mainly represented by the first principal component. PCA and K-means clustering also showed significant results that corroborate the impact of pyriproxyfen intervention on genetic structure populations of Ae. aegypti mosquitoes. The results revealed a bottleneck effect and reduced mosquito populations during intervention, followed by reintroduction from adjacent and unaffected populations by this vector. We highlighted that low-coverage whole genome sequencing can contribute to genetic and structure population data, and also generate important information to aid in genomic and epidemiological surveillance.

Increased adiposity is a hallmark of obesity and overweight, which affect 2.2 billion people world-wide. Understanding the genetic and molecular mechanisms that underlie obesity-related phenotypes can help to improve treatment options and drug development. Here we perform promoter Capture Hi–C in human adipocytes to investigate interactions between gene promoters and distal elements as a transcription-regulating mechanism contributing to these phenotypes. We find that promoter-interacting elements in human adipocytes are enriched for adipose-related transcription factor motifs, such as PPARG and CEBPB, and contribute to heritability of cis -regulated gene expression. We further intersect these data with published genome-wide association studies for BMI and BMI-related metabolic traits to identify the genes that are under genetic cis regulation in human adipocytes via chromosomal interactions. This integrative genomics approach identifies four cis -eQTL-eGene relationships associated with BMI or obesity-related traits, including rs4776984 and MAP2K5 , which we further confirm by EMSA, and highlights 38 additional candidate genes. GWAS have identified numerous genetic loci for BMI and related traits. Here, Pan et al. generate Promoter Capture Hi-C data for human white adipocytes and integrate these with data of transcription factor motifs, RNA-seq and GWAS to identify eQTL-eGene relationships mediated by chromosomal interactions.

Aedes aegypti and Aedes albopictus are responsible for transmitting major human arboviruses such as Dengue, Zika, and Chikungunya, posing a global threat to public health. The lack of etiological treatments and efficient vaccines makes vector control strategies essential for reducing vector population density and interrupting the pathogen transmission cycle. This study evaluated the impact of long-term pyriproxyfen exposure on the genetic structure and diversity of Ae. aegypti and Ae. albopictus mosquito populations. The study was conducted in Manaus, Amazonas, Brazil, where pyriproxyfen dissemination stations have been monitored since 2014 up to the present day. Double digest restriction-site associated DNA sequencing was performed, revealing that despite significant local population reductions by dissemination stations with pyriproxyfen in various locations in Brazil, focal intervention has no significant impact on the population stratification of these vectors in urban scenarios. The genetic structuring level of Ae. aegypti suggests it is more stratified and directly affected by pyriproxyfen intervention, while for Ae. albopictus exhibits a more homogeneous and less structured population. The results suggest that although slight differences are observed among mosquito subpopulations, intervention focused on neighborhoods in a capital city is not efficient in terms of genetic structuring, indicating that larger-scale pyriproxyfen interventions should be considered for more effective urban mosquito control.

Background Age and obesity are dominant risk factors for several common cardiometabolic disorders, and both are known to impair adipose tissue function. However, the underlying cellular and genetic factors linking aging and obesity on adipose tissue function have remained elusive. Adipose stem and precursor cells (ASPCs) are an understudied, yet crucial adipose cell type due to their deterministic adipocyte differentiation potential, which impacts the capacity to store fat in a metabolically healthy manner. Methods We integrated subcutaneous adipose tissue (SAT) bulk ( n =435) and large single-nucleus RNA sequencing ( n =105) data with the UK Biobank (UKB) ( n =391,701) data to study age-obesity interactions originating from ASPCs by performing cell-type decomposition, differential expression testing, cell-cell communication analyses, and construction of polygenic risk scores for body mass index (BMI). Results We found that the SAT ASPC proportions significantly decrease with age in an obesity-dependent way consistently in two independent cohorts, both showing that the age dependency of ASPC proportions is abolished by obesity. We further identified 76 genes (72 SAT ASPC marker genes and 4 transcription factors regulating ASPC marker genes) that are differentially expressed by age in SAT and functionally enriched for developmental processes and adipocyte differentiation (i.e., adipogenesis). The 76 age-perturbed ASPC genes include multiple negative regulators of adipogenesis, such as RORA, SMAD3, TWIST2, and ZNF521 , form tight clusters of longitudinally co-expressed genes during human adipogenesis, and show age-based differences in cellular interactions between ASPCs and adipose cell types. Finally, our genetic data demonstrate that cis -regional variants of these genes interact with age as predictors of BMI in an obesity-dependent way in the large UKB, while no such gene-age interaction on BMI is observed with non-age-dependent ASPC marker genes, thus independently confirming our cellular ASPC results at the biobank level. Conclusions Overall, we discover that obesity prematurely induces a decrease in ASPC proportions and identify 76 developmentally important ASPC genes that implicate altered negative regulation of fat cell differentiation as a mechanism for aging and directly link aging to obesity via significant cellular and genetic interactions.

In Brazil, Nyssorhynchus darlingi stands out as the primary malaria vector. Chromosome inversions have long been recognized as critical evolutionary mechanisms in diverse organisms. In this study, we used biallelic SNPs to show that it is possible to detect chromosome inversions reliably with low coverage sequence data. We estimated chromosome inversions in an Amazon Basin sample of Ny. darlingi and compared them with Anopheles gambiae and Anopheles albimanus genomes in synteny analysis. The An. gambiae dataset benchmarked the inversion detection pipeline with known inversions. Genotyping by sequencing was performed using the LCSeqTools workflow for the lcWGS dataset with an average sequencing depth of 2x. A synteny analysis was performed for Ny. darlingi inversions regions with An. gambiae and An. albimanus genomes. The sliding window analysis of PCA components revealed 10 high-confidence candidate regions for chromosome inversions in Ny. darlingi genome and two known inversions for An. gambiae with possible identification of breakpoints and adjacent regions at lower resolution. We demonstrate that lcWGS is a cost-effective and accurate method for detecting chromosome inversions. We reliably detected chromosome inversions in Ny. darlingi from the Brazilian Amazon that does not share similar inversion arrangements in An. gambiae or An. albimanus genomes.