A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Cross-Tissue Single-Nucleus RNA Sequencing Discovers Tissue-Resident Adipocytes Involved in Propanoate Metabolism in the Human Heart.

BACKGROUND: Adipocytes are crucial regulators of cardiovascular health. However, not much is known about gene expression profiles of adipocytes residing in nonfat cardiovascular tissues, their genetic regulation, and contribution to coronary artery disease. Here, we investigated whether and how the gene expression profiles of adipocytes in the subcutaneous adipose tissue differ from adipocytes residing in the heart. METHODS: We used single-nucleus RNA-sequencing data sets of subcutaneous adipose tissue and heart and performed in-depth analysis of tissue-resident adipocytes and their cell-cell interactions. RESULTS: We first discovered tissue-specific features of tissue-resident adipocytes, identified functional pathways involved in their tissue specificity, and found genes with cell type-specific expression enrichment in tissue-resident adipocytes. By following up these results, we discovered the propanoate metabolism pathway as a novel distinct characteristic of the heart-resident adipocytes and found a significant enrichment of coronary artery disease genome-wide association study risk variants among the right atrium-specific adipocyte marker genes. Our cell-cell communication analysis identified 22 specific heart adipocyte-associated ligand-receptor pairs and signaling pathways, including THBS (thrombospondin) and EPHA (ephrin type-A), further supporting the distinct tissue-resident role of heart adipocytes. Our results also suggest chamber-level coordination of heart adipocyte expression profiles as we observed a consistently larger number of adipocyte-associated ligand-receptor interactions and functional pathways in the atriums than ventricles. CONCLUSIONS: Overall, we introduce a new function and genetic link to coronary artery disease for the previously unexplored heart-resident adipocytes.

The causal effect of obesity on prediabetes and insulin resistance reveals the important role of adipose tissue in insulin resistance.

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.

Zinc supplementation modifies brain tissue transcriptome of Apis mellifera honeybees.

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.

ASElux: an ultra-fast and accurate allelic reads counter.

Motivation: Mapping bias causes preferential alignment to the reference allele, forming a major obstacle in allele-specific expression (ASE) analysis. The existing methods, such as simulation and SNP-aware alignment, are either inaccurate or relatively slow. To fast and accurately count allelic reads for ASE analysis, we developed a novel approach, ASElux, which utilizes the personal SNP information and counts allelic reads directly from unmapped RNA-sequence (RNA-seq) data. ASElux significantly reduces runtime by disregarding reads outside single nucleotide polymorphisms (SNPs) during the alignment. Results: When compared to other tools on simulated and experimental data, ASElux achieves a higher accuracy on ASE estimation than non-SNP-aware aligners and requires a much shorter time than the benchmark SNP-aware aligner, GSNAP with just a slight loss in performance. ASElux can process 40 million read-pairs from an RNA-sequence (RNA-seq) sample and count allelic reads within 10 min, which is comparable to directly counting the allelic reads from alignments based on other tools. Furthermore, processing an RNA-seq sample using ASElux in conjunction with a general aligner, such as STAR, is more accurate and still ∼4× faster than STAR + WASP, and ∼33× faster than the lead SNP-aware aligner, GSNAP, making ASElux ideal for ASE analysis of large-scale transcriptomic studies. We applied ASElux to 273 lung RNA-seq samples from GTEx and identified a splice-QTL rs11078928 in lung which explains the mechanism underlying an asthma GWAS SNP rs11078927. Thus, our analysis demonstrated ASE as a highly powerful complementary tool to cis-expression quantitative trait locus (eQTL) analysis. Availability and implementation: The software can be downloaded from https://github.com/abl0719/ASElux. Contact: zmiao@ucla.edu or a5ko@ucla.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Molecular Characterization of the Lipid Genome-Wide Association Study Signal on Chromosome 18q11.2 Implicates HNF4A-Mediated Regulation of the TMEM241 Gene.

OBJECTIVE: We recently identified a locus on chromosome 18q11.2 for high serum triglycerides in Mexicans. We hypothesize that the lead genome-wide association study single-nucleotide polymorphism rs9949617, or its linkage disequilibrium proxies, regulates 1 of the 5 genes in the triglyceride-associated region. APPROACH AND RESULTS: We performed a linkage disequilibrium analysis and found 9 additional variants in linkage disequilibrium (r(2)>0.7) with the lead single-nucleotide polymorphism. To select the variants for functional analyses, we annotated the 10 variants using DNase I hypersensitive sites, transcription factor and chromatin states and identified rs17259126 as the lead candidate variant for functional in vitro validation. Using luciferase transcriptional reporter assay in liver HepG2 cells, we found that the G allele exhibits a significantly lower effect on transcription (P<0.05). The electrophoretic mobility shift and ChIPqPCR (chromatin immunoprecipitation coupled with quantitative polymerase chain reaction) assays confirmed that the minor G allele of rs17259126 disrupts an hepatocyte nuclear factor 4 α-binding site. To find the regional candidate gene, we performed a local expression quantitative trait locus analysis and found that rs17259126 and its linkage disequilibrium proxies alter expression of the regional transmembrane protein 241 (TMEM241) gene in 795 adipose RNAs from the Metabolic Syndrome In Men (METSIM) cohort (P=6.11×10(-07)-5.80×10(-04)). These results were replicated in expression profiles of TMEM241 from the Multiple Tissue Human Expression Resource (MuTHER; n=856). CONCLUSIONS: The Mexican genome-wide association study signal for high serum triglycerides on chromosome 18q11.2 harbors a regulatory single-nucleotide polymorphism, rs17259126, which disrupts normal hepatocyte nuclear factor 4 α binding and decreases the expression of the regional TMEM241 gene. Our data suggest that decreased transcript levels of TMEM241 contribute to increased triglyceride levels in Mexicans.

Remote Ischemic Conditioning Alters Methylation and Expression of Cell Cycle Genes in Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND AND PURPOSE: Remote ischemic conditioning (RIC) is a phenomenon in which short periods of nonfatal ischemia in 1 tissue confers protection to distant tissues. Here we performed a longitudinal human pilot study in patients with aneurysmal subarachnoid hemorrhage undergoing RIC by limb ischemia to compare changes in DNA methylation and transcriptome profiles before and after RIC. METHODS: Thirteen patients underwent 4 RIC sessions over 2 to 12 days after rupture of an intracranial aneurysm. We analyzed whole blood transcriptomes using RNA sequencing and genome-wide DNA methylomes using reduced representation bisulfite sequencing, both before and after RIC. We tested differential expression and differential methylation using an intraindividual paired study design and then overlapped the differential expression and differential methylation results for analyses of functional categories and protein-protein interactions. RESULTS: We observed 164 differential expression genes and 3493 differential methylation CpG sites after RIC, of which 204 CpG sites overlapped with 103 genes, enriched for pathways of cell cycle (P<3.8×10(-4)) and inflammatory responses (P<1.4×10(-4)). The cell cycle pathway genes form a significant protein-protein interaction network of tightly coexpressed genes (P<0.00001). CONCLUSIONS: Gene expression and DNA methylation changes in aneurysmal subarachnoid hemorrhage patients undergoing RIC are involved in coordinated cell cycle and inflammatory responses.

Impact of Long-Term Pyriproxyfen Exposure on the Genetic Structure and Diversity of Aedes aegypti and Aedes albopictus in Manaus, Amazonas, Brazil.

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.

Evaluation of Aedes aegypti control intervention with pyriproxyfen by lcWGS in Manacapuru, Amazonas, Brazil.

BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS/SIGNIFICANCE: 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.

Food contamination with fipronil alters gene expression associated with foraging in Africanized honey bees.

Taking into consideration that bees can be contaminated by pesticides through the ingestion of contaminated floral resources, we can utilize genetic techniques to assess effects that are scarcely observed in behavioral studies. This study aimed to investigate the genetic effects of ingesting lethal and sublethal doses of the insecticide fipronil in foraging honey bees during two periods of acute exposure. Bees were exposed to fipronil through contaminated honey syrup at two dosages (LD50 = 0.19 µg/bee; LD50/100 = 0.0019 µg/bee) and for two durations (1 and 4 h). Following exposure, we measured syrup consumption per bee, analyzed the transcriptome of bee brain tissue, and identified differentially expressed genes (DEGs), categorizing them functionally based on gene ontology (GO). The results revealed a significant genetic response in honey bees after exposure to fipronil, regardless of the dosage used. Fipronil affected various metabolic, transport, and cellular regulation pathways, as well as detoxification processes and xenobiotic substance detection. Additionally, the downregulation of several DEGs belonging to the olfactory-binding protein (OBP) family was observed, suggesting potential physiological alterations in bees that may lead to disoriented behaviors and reduced foraging efficiency.

Age-dependent genes in adipose stem and precursor cells affect regulation of fat cell differentiation and link aging to obesity via cellular and genetic interactions.

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.

Intake of imidacloprid in lethal and sublethal doses alters gene expression in Apis mellifera bees.

Bees are important pollinators for ecosystems and agriculture; however, populations have suffered a decline that may be associated with several factors, including habitat loss, climate change, increased vulnerability to diseases and parasites and use of pesticides. The extensive use of neonicotinoids, including imidacloprid, as agricultural pesticides, leads to their persistence in the environment and accumulation in bees, pollen, nectar, and honey, thereby inducing deleterious effects. Forager honey bees face significant exposure to pesticide residues while searching for resources outside the hive, particularly systemic pesticides like imidacloprid. In this study, 360 Apis mellifera bees, twenty-one days old (supposed to be in the forager phase) previously marked were fed syrup (honey and water, 1:1 m/v) containing a lethal dose (0.081 µg/bee) or sublethal dose (0.00081 µg/bee) of imidacloprid. The syrup was provided in plastic troughs, with 250 µL added per trough onto each plastic Petri dish containing 5 bees (50 µL per bee). The bees were kept in the plastic Petri dishes inside an incubator, and after 1 and 4 h of ingestion, the bees were euthanised and stored in an ultra-freezer (-80 °C) for transcriptome analysis. Following the 1-h ingestion of imidacloprid, 1516 genes (73 from lethal dose; 1509 from sublethal dose) showed differential expression compared to the control, while after 4 h, 758 genes (733 from lethal dose; 25 from sublethal) exhibited differential expression compared to the control. All differentially expressed genes found in the brain tissue transcripts of forager bees were categorised based on gene ontology into functional groups encompassing biological processes, molecular functions, and cellular components. These analyses revealed that sublethal doses might be capable of altering more genes than lethal doses, potentially associated with a phenomenon known as insecticide-induced hormesis. Alterations in genes related to areas such as the immune system, nutritional metabolism, detoxification system, circadian rhythm, odour detection, foraging activity, and memory in bees were present after exposure to the pesticide. These findings underscore the detrimental effects of both lethal and sublethal doses of imidacloprid, thereby providing valuable insights for establishing public policies regarding the use of neonicotinoids, which are directly implicated in the compromised health of Apis mellifera bees.

Partitioned polygenic risk scores identify distinct types of metabolic dysfunction-associated steatotic liver disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses an excess of triglycerides in the liver, which can lead to cirrhosis and liver cancer. While there is solid epidemiological evidence of MASLD coexisting with cardiometabolic disease, several leading genetic risk factors for MASLD do not increase the risk of cardiovascular disease, suggesting no causal relationship between MASLD and cardiometabolic derangement. In this work, we leveraged measurements of visceral adiposity and identified 27 novel genetic loci associated with MASLD. Among these loci, we replicated 6 in several independent cohorts. Next, we generated two partitioned polygenic risk scores (PRS) based on the mechanism of genetic association with MASLD encompassing intra-hepatic lipoprotein retention. The two PRS suggest the presence of at least two distinct types of MASLD, one confined to the liver resulting in a more aggressive liver disease and one that is systemic and results in a higher risk of cardiometabolic disease.

Maternal protein restriction combined with postnatal sugar consumption alters liver proteomic profile and metabolic pathways in adult male offspring rats.

This study investigated the impact of maternal protein restriction (MPR) and early postnatal sugar consumption (SUG) on the liver health of adult male descendant rats. Male offspring of mothers fed a normal protein diet (NPD) or a low protein diet (LPD) were divided into four groups: Control (CTR), Sugar Control (CTR + SUG), LPD during gestation and lactation (GLLP), and LPD with sugar (GLLP + SUG). Sugar consumption (10% glucose diluted in water) began after weaning on day 21 (PND 21), and at 90 days (PND 90), rats were sacrificed for analysis. Sugar intake reduced food intake and increased water consumption in CTR + SUG and GLLP + SUG compared to CTR and GLLP. GLLP and GLLP + SUG groups showed lower body weight and total and retroperitoneal fat compared to CTR and CTR + SUG. CTR + SUG and GLLP + SUG groups exhibited hepatocyte vacuolization associated with increased hepatic glycogen content compared to CTR and GLLP. Hepatic catalase activity increased in GLLP compared to CTR. Proteomic analysis identified 223 differentially expressed proteins (DEPs) among experimental groups. While in the GLLP group, the DEPs enriched molecular pathways related to cellular stress, glycogen metabolic pathways were enriched in the GLLP + SUG and CTR + SUG groups. The association of sugar consumption amplifies the effects of MPR, deregulating molecular mechanisms related to metabolism and the antioxidant system.

Single nucleus RNA-sequencing integrated into risk variant colocalization discovers 17 cell-type-specific abdominal obesity genes for metabolic dysfunction-associated steatotic liver disease.

BACKGROUND: Abdominal obesity increases the risk for non-alcoholic fatty liver disease (NAFLD), now known as metabolic dysfunction-associated steatotic liver disease (MASLD). METHODS: To elucidate the directional cell-type level biological mechanisms underlying the association between abdominal obesity and MASLD, we integrated adipose and liver single nucleus RNA-sequencing and bulk cis-expression quantitative trait locus (eQTL) data with the UK Biobank genome-wide association study (GWAS) data using colocalization. Then we used colocalized cis-eQTL variants as instrumental variables in Mendelian randomization (MR) analyses, followed by functional validation experiments on the target genes of the cis-eQTL variants. FINDINGS: We identified 17 colocalized abdominal obesity GWAS variants, regulating 17 adipose cell-type marker genes. Incorporating these 17 variants into MR discovers a putative tissue-of-origin, cell-type-aware causal effect of abdominal obesity on MASLD consistently with multiple MR methods without significant evidence for pleiotropy or heterogeneity. Single cell data confirm the adipocyte-enriched mean expression of the 17 genes. Our cellular experiments across human adipogenesis identify risk variant -specific epigenetic and transcriptional mechanisms. Knocking down two of the 17 genes, PPP2R5A and SH3PXD2B, shows a marked decrease in adipocyte lipidation and significantly alters adipocyte function and adipogenesis regulator genes, including DGAT2, LPL, ADIPOQ, PPARG, and SREBF1. Furthermore, the 17 genes capture a characteristic MASLD expression signature in subcutaneous adipose tissue. INTERPRETATION: Overall, we discover a significant cell-type level effect of abdominal obesity on MASLD and trace its biological effect to adipogenesis. FUNDING: NIH grants R01HG010505, R01DK132775, and R01HL170604; the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (Grant No. 802825), Academy of Finland (Grants Nos. 333021), the Finnish Foundation for Cardiovascular Research the Sigrid Jusélius Foundation and the Jane and Aatos Erkko Foundation; American Association for the Study of Liver Diseases (AASLD) Advanced Transplant Hepatology award and NIH/NIDDK (P30DK41301) Pilot and Feasibility award; NIH/NIEHS F32 award (F32ES034668); Finnish Diabetes Research Foundation, Kuopio University Hospital Project grant (EVO/VTR grants 2005-2021), the Academy of Finland grant (Contract no. 138006); Academy of Finland (Grant Nos 335443, 314383, 272376 and 266286), Sigrid Jusélius Foundation, Finnish Medical Foundation, Finnish Diabetes Research Foundation, Novo Nordisk Foundation (#NNF20OC0060547, NNF17OC0027232, NNF10OC1013354) and Government Research Funds to Helsinki University Hospital; Orion Research Foundation, Maud Kuistila Foundation, Finish Medical Foundation, and University of Helsinki.

Isolation of Nuclei from Human Snap-frozen Liver Tissue for Single-nucleus RNA Sequencing.

Single-nucleus RNA sequencing (snRNA-seq) provides a powerful tool for studying cell type composition in heterogenous tissues. The liver is a vital organ composed of a diverse set of cell types; thus, single-cell technologies could greatly facilitate the deconvolution of liver tissue composition and various downstream omics analyses at the cell-type level. Applying single-cell technologies to fresh liver biopsies can, however, be very challenging, and snRNA-seq of snap-frozen liver biopsies requires some optimization given the high nucleic acid content of the solid liver tissue. Therefore, an optimized protocol for snRNA-seq specifically targeted for the use of frozen liver samples is needed to improve our understanding of human liver gene expression at the cell-type resolution. We present a protocol for performing nuclei isolation from snap-frozen liver tissues, as well as guidance on the application of snRNA-seq. We also provide guidance on optimizing the protocol to different tissue and sample types.

Genetic Structuring of One of the Main Vectors of Sylvatic Yellow Fever: Haemagogus (Conopostegus) leucocelaenus (Diptera: Culicidae).

Genetic diversity and population structuring for the species Haemogogus leucocelaenus, a sylvatic vector of yellow fever virus, were found to vary with the degree of agricultural land use and isolation of fragments of Atlantic Forest in municipalities in the state of São Paulo where specimens were collected. Genotyping of 115 mitochondrial SNPs showed that the populations with the highest indices of genetic diversity (polymorphic loci and mean pairwise differences between the sequences) are found in areas with high levels of agricultural land use (northeast of the State). Most populations exhibited statistically significant negative values for the Tajima D and Fu FS neutrality tests, suggesting recent expansion. The results show an association between genetic diversity in this species and the degree of agricultural land use in the sampled sites, as well as signs of population expansion of this species in most areas, particularly those with the highest forest edge densities. A clear association between population structuring and the distance between the sampled fragments (isolation by distance) was observed: samples from a large fragment of Atlantic Forest extending along the coast of the state of São Paulo exhibited greater similarity with each other than with populations in the northwest of the state.

Deep learning-based phenotype imputation on population-scale biobank data increases genetic discoveries.

Biobanks that collect deep phenotypic and genomic data across many individuals have emerged as a key resource in human genetics. However, phenotypes in biobanks are often missing across many individuals, limiting their utility. We propose AutoComplete, a deep learning-based imputation method to impute or 'fill-in' missing phenotypes in population-scale biobank datasets. When applied to collections of phenotypes measured across ~300,000 individuals from the UK Biobank, AutoComplete substantially improved imputation accuracy over existing methods. On three traits with notable amounts of missingness, we show that AutoComplete yields imputed phenotypes that are genetically similar to the originally observed phenotypes while increasing the effective sample size by about twofold on average. Further, genome-wide association analyses on the resulting imputed phenotypes led to a substantial increase in the number of associated loci. Our results demonstrate the utility of deep learning-based phenotype imputation to increase power for genetic discoveries in existing biobank datasets.

Impaired Adipocyte SLC7A10 Promotes Lipid Storage in Association With Insulin Resistance and Altered BCAA Metabolism.

CONTEXT: The neutral amino acid transporter SLC7A10/ASC-1 is an adipocyte-expressed gene with reduced expression in insulin resistance and obesity. Inhibition of SLC7A10 in adipocytes was shown to increase lipid accumulation despite decreasing insulin-stimulated uptake of glucose, a key substrate for de novo lipogenesis. These data imply that alternative lipogenic substrates to glucose fuel continued lipid accumulation during insulin resistance in obesity. OBJECTIVE: We examined whether increased lipid accumulation during insulin resistance in adipocytes may involve alter flux of lipogenic amino acids dependent on SLC7A10 expression and activity, and whether this is reflected by extracellular and circulating concentrations of marker metabolites. METHODS: In adipocyte cultures with impaired SLC7A10, we performed RNA sequencing and relevant functional assays. By targeted metabolite analyses (GC-MS/MS), flux of all amino acids and selected metabolites were measured in human and mouse adipose cultures. Additionally, SLC7A10 mRNA levels in human subcutaneous adipose tissue (SAT) were correlated to candidate metabolites and adiposity phenotypes in 2 independent cohorts. RESULTS: SLC7A10 impairment altered expression of genes related to metabolic processes, including branched-chain amino acid (BCAA) catabolism, lipogenesis, and glyceroneogenesis. In 3T3-L1 adipocytes, SLC7A10 inhibition increased fatty acid uptake and cellular content of glycerol and cholesterol. SLC7A10 impairment in SAT cultures altered uptake of aspartate and glutamate, and increased net uptake of BCAAs, while increasing the net release of the valine catabolite 3- hydroxyisobutyrate (3-HIB). In human cohorts, SLC7A10 mRNA correlated inversely with total fat mass, circulating triacylglycerols, BCAAs, and 3-HIB. CONCLUSION: Reduced SLC7A10 activity strongly affects flux of BCAAs in adipocytes, which may fuel continued lipogenesis during insulin resistance, and be reflected in increased circulating levels of the valine-derived catabolite 3-HIB.

Cell-Type Composition Affects Adipose Gene Expression Associations With Cardiometabolic Traits.

Understanding differences in adipose gene expression between individuals with different levels of clinical traits may reveal the genes and mechanisms leading to cardiometabolic diseases. However, adipose is a heterogeneous tissue. To account for cell-type heterogeneity, we estimated cell-type proportions in 859 subcutaneous adipose tissue samples with bulk RNA sequencing (RNA-seq) using a reference single-nuclear RNA-seq data set. Cell-type proportions were associated with cardiometabolic traits; for example, higher macrophage and adipocyte proportions were associated with higher and lower BMI, respectively. We evaluated cell-type proportions and BMI as covariates in tests of association between >25,000 gene expression levels and 22 cardiometabolic traits. For >95% of genes, the optimal, or best-fit, models included BMI as a covariate, and for 79% of associations, the optimal models also included cell type. After adjusting for the optimal covariates, we identified 2,664 significant associations (P ≤ 2e-6) for 1,252 genes and 14 traits. Among genes proposed to affect cardiometabolic traits based on colocalized genome-wide association study and adipose expression quantitative trait locus signals, 25 showed a corresponding association between trait and gene expression levels. Overall, these results suggest the importance of modeling cell-type proportion when identifying gene expression associations with cardiometabolic traits.