Biology subjects

Roberts, A. L.

Publications and source records attributed to Roberts, A. L..

8 recordsLinked to original sources

bioRxiv2025

Genetic regulation of fatty acid content in adipose tissue

Fatty acids are important as structural components, energy sources, and signaling mediators. While studies have extensively explored genetic regulation of fatty acids in serum and other bodily fluids, their regulation within adipose tissue, a crucial regulator of cardiovascular and metabolic health remains unclear. Here, we investigated the genetic regulation of 18 fatty acids in subcutaneous adipose tissue from 569 female twins from TwinsUK. Using twin models, the heritability of fatty acids ranged from 5% to 59%, indicating a substantial genetic regulation of fatty acid levels within adipose tissue, which was also tissue-specific in many cases. Genome-wide association studies identified ten significant loci, in SCD, ADAMTSL1, ZBTB41, SNTB1, EXOC6B, ACSL3, LINC02055, MKRN2/TSEN2, FADS1 and HAPLN across 13 fatty acids or fatty acid product-to-precursor ratios. Using adipose gene expression and methylation, which were concurrently measured in these samples, we detected five fatty acid-associated signals that colocalized with eQTL and meQTL signals, highlighting fatty acids that are regulated by molecular processes within adipose tissue. We identified strong associations of adipose fatty acids-associated loci with type 2 diabetes, body fat percentage, and cardiovascular disease. We explored links between polygenic scores of common metabolic traits and adipose fatty acid levels, and identified associations between polygenic scores of BMI, body-fat distribution and triglycerides and several fatty acids, indicating these risk scores impact local adipose tissue content. Overall, our results identified local genetic regulation of fatty acids within adipose tissue and highlighted their links with renal and cardio-metabolic health.

genetics↗

bioRxiv2025

Inducible estrogen receptor alpha in normal breast epithelial cells demonstrate estrogen receptor-dependent DNA damage

BackgroundSignaling by estrogen-receptor alpha (ER) plays a major role in breast cancer initiation Investigations of the mechanism of DNA damage mediated by ER signaling are carried out in breast cancer cell lines due to the lack of ER+ normal human breast epithelial cells lines (HBEC). Defining the mechanisms by which ER induces DNA damage and initiates tumorigenesis requires normal HBECs that express ER, demonstrate estrogenic responses, and are amenable to long term propagation in culture. MethodsWe utilized lentiviral expression of an inducible ER construct to generate four HBEC lines (HBEC-ESR1). We studied these cells for ER-dependent responses using a luciferase reporter, endogenous gene expression and proliferation assays. RNA-Seq was performed to characterize the ER-mediated transcriptomic patterns in the four HBEC lines. ER mediated DNA double strand breaks (DSBs) were analyzed using {gamma}H2AX immunofluorescence. ResultsExpression and functional activation of ER were observed in all HBEC-ESR1 lines, whereas proliferation in response to 17{beta}-estradiol (E2) was observed in 3 of the cell lines. Proliferative responses were due to intrinsic signaling within the HBECs as conditioned media from the cells failed to cause proliferation. A total of 682 genes were differentially expressed at 24h following treatment with 10nM E2 with 43% of these genes were also observed in ER+ breast cancer cell lines (MCF7 or T47D). Gene-set enrichment analysis identified differential expression of genes in ER signaling pathways and DNA repair pathways in E2-treated cells. E2-induced ER signaling also increased {gamma}H2AX foci in 3 of the 4 cell lines. Levels of DSBs were increased by inhibition of the non-homologous end-joining (NHEJ) and homologous recombination (HR) pathways. DSBs were also increased in MCF10A-ESR1 cells heterozygous for the BRCA1185delAG mutation causing a truncated protein. ConclusionsInducible expression of ER in immortalized HBECs recapitulate transcriptional, replicative and DNA damage responses. Increased DSBs in MCF10A-ESR1 cells with heterozygous mutation of BRCA1 indicate haploinsufficiency and the potential for increased genetic instability due to ER signaling.

cancer biology↗

bioRxiv2023

Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits

Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. Here, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34K conditionally distinct expression quantitative trait locus (eQTL) signals in 18K genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared to primary signals, non-primary signals had lower effect sizes, lower minor allele frequencies, and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTL with conditionally distinct genome-wide association study signals for 28 cardiometabolic traits identified 3,605 eQTL signals for 1,861 genes. Inclusion of non-primary eQTL signals increased colocalized signals by 46%. Among 30 genes with [≥]2 pairs of colocalized signals, 21 showed a mediating gene dosage effect on the trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation.

genomics↗

bioRxiv2021

Escape from X-inactivation in twins exhibits intra- and inter-individual variability across tissues and is heritable

X-chromosome inactivation (XCI) silences one X-chromosome in female cells to balance sex-differences in X-dosage. A subset of X-linked genes escape XCI, but the extent to which this phenomenon occurs and how it varies across tissues and in a population is as yet unclear. In order to characterize the incidence and variability of escape across individuals and tissues, we conducted a large scale transcriptomic study of XCI escape in adipose, skin, lymphoblastoid cell lines (LCLs) and immune cells in 248 twins drawn from a healthy population cohort. We identify 159 X-linked genes with detectable escape, of which 54 genes, including 19 lncRNAs, were not previously known to escape XCI. Across tissues we find a range of tissue-specificity, with 11% of genes escaping XCI constitutively across tissues and 24% demonstrating tissue-restricted escape, including genes with cell-type specific escape between immune cell types (B, T-CD4+, T-CD8+ and NK cells) of the same individual. Escape genes interact with autosomal-encoded proteins and are involved in varied biological processes such as gene regulation. We find substantial variability in escape between individuals. 49% of genes show inter-individual variability in escape, indicating escape from XCI is an under-appreciated source of gene expression differences. We utilized twin models to investigate the role of genetics in variable escape. Overall, monozygotic (MZ) twin pairs share more similar escape than dizygotic twin pairs, indicating that genetic factors underlie differences in escape across individuals. However, we also identify instances of discordant XCI within MZ co-twin pairs, suggesting that environmental factors also influence escape. Thus, XCI escape may be shaped by an interplay of genetic factors with tissue- and cell type-specificity, and environment. These results illuminate an intricate phenotype whose characterization aids understanding the basis of variable trait expressivity in females.

genetics↗

bioRxiv2019

Cell type specific genetic regulation of gene expression across human tissues

The Genotype-Tissue Expression (GTEx) project has identified expression and splicing quantitative trait loci (cis-QTLs) for the majority of genes across a wide range of human tissues. However, the interpretation of these QTLs has been limited by the heterogeneous cellular composition of GTEx tissue samples. Here, we map interactions between computational estimates of cell type abundance and genotype to identify cell type interaction QTLs for seven cell types and show that cell type interaction eQTLs provide finer resolution to tissue specificity than bulk tissue cis-eQTLs. Analyses of genetic associations to 87 complex traits show a contribution from cell type interaction QTLs and enables the discovery of hundreds of previously unidentified colocalized loci that are masked in bulk tissue.\n\nOne Sentence SummaryEstimated cell type abundances from bulk RNA-seq across tissues reveal the cellular specificity of quantitative trait loci.

genomics↗

bioRxiv2019

Genetic risk loadings influence the susceptibility and severity of systemic lupus erythematosus

ObjectiveUsing three European and two Chinese genome-wide association studies (GWAS), we investigated the performance of genetic risk scores (GRS) for predicting the susceptibility and severity of Systemic lupus erythematosus (SLE), using renal disease as a proxy for severity. MethodsWe used four GWASs to test the performance of GRS both cross validating within the European population and between European and Chinese populations. The performance of GRS in SLE risk prediction was evaluated by Receiver Operating Characteristic (ROC) curves. We then analyzed the polygenic nature of SLE statistically. We also partitioned patients according to their age-of-onset and evaluated the predictability of GRS in disease severity in each age group. ResultsWe found consistently that the best GRS in the prediction of SLE used SNPs associated at the level of P<1e-05 in all GWAS datasets and that SNPs with P-values above 0.2 were inflated for SLE true positive signals. The GRS results in an area under the ROC curve ranging between 0.64 and 0.72, within European and between the European and Chinese populations. We further showed a significant positive correlation between a GRS and renal disease in two independent European GWAS (Pcohort1=2.44e-08; Pcohort2=0.00205) and a significant negative correlation with age of SLE onset (Pcohort1=1.76e-12; Pcohort2=0.00384). We found that the GRS performed better in prediction of renal disease in the later onset compared to the earlier onset group. ConclusionThe GRS predicts SLE in both European and Chinese populations and correlates with poorer prognostic factors: young age of onset and lupus nephritis.

genetics↗

bioRxiv2018

The neuronal ceroid lipofuscinosis protein, Cln7, regulates neural development from the post-synaptic cell.

The neuronal ceroid lipofuscinoses (NCLs) are a group of fatal, monogenic neurodegenerative disorders with an early onset in infancy or childhood. Despite identification of the genes disrupted in each form of the disease, their normal cellular role and how their deficits lead to disease pathology is not fully understood. Cln7, a major facilitator superfamily domain-containing protein, is affected in a late infantile-onset form of NCL. Using the Drosophila larval neuromuscular junction as a model to study neural development, we demonstrate that Cln7 is required for the normal growth of synapses. In a Cln7 mutant, synapses fail to develop fully leading to reduced function and behavioral changes with dysregulation of TOR activity. Cln7 expression is restricted to the post-synaptic cell and the protein localizes to vesicles immediately adjacent to the post-synaptic membrane. Our data suggest an involvement for Cln7 in regulating trans-synaptic communication.

developmental biology↗

bioRxiv2017

De Novo Mutations Implicate Novel Genes With Burden Of Rare Variants In Systemic Lupus Erythematosus

The omnigenic model of complex diseases stipulates that the majority of the heritability will be explained by the effects of common variation on genes in the periphery of core disease pathways. Rare variant associations, expected to explain far less of the heritability, may be enriched in core disease genes and thus will be instrumental in the understanding of complex disease pathogenesis and their potential therapeutic targets. Here, using complementary whole-exome sequencing (WES), high-density imputation, and in vitro cellular assays, we identify three candidate core genes in the pathogenesis of Systemic Lupus Erythematosus (SLE). Using extreme-phenotype sampling, we sequenced the exomes of 30 SLE parent-affected-offspring trios and identified 14 genes with missense de novo mutations (DNM), none of which are within the >80 SLE susceptibility loci implicated through genome-wide association studies (GWAS). In a follow-up cohort of 10,995 individuals of matched European ancestry, we imputed genotype data to the density of the combined UK10K-1000 genomes Phase III reference panel across the 14 candidate genes. We identify a burden of rare variants across PRKCD associated with SLE risk (P=0.0028), and across DNMT3A associated with two severe disease prognosis sub-phenotypes (P=0.0005 and P=0.0033). Both genes are functional candidates and significantly constrained against missense mutations in gene-level analyses, along with C1QTNF4. We further characterise the TNF-dependent functions of candidate gene C1QTNF4 on NF-{kappa}B activation and apoptosis, which are inhibited by the p.His198Gln DNM. Our results support extreme-phenotype sampling and DNM gene discovery to aid the search for core disease genes implicated through rare variation.\n\nSignificance StatementRare variants, present in <1% in population, are expected to explain little of the heritability of complex diseases, such as Systemic Lupus Erythematosus (SLE), yet are likely to identify core genes crucial to disease mechanisms. Their rarity, however, limits the power to show their statistical association with disease. Through sequencing the exomes of SLE patients and their parents, we identified non-inherited de novo mutations in 14 genes and hypothesised that these are prime candidates for harbouring additional disease-associated rare variants. We demonstrate that two of these genes also carry a significant excess of rare variants in an independent, large cohort of SLE patients. Our findings will influence future study designs in the search for the missing heritability of complex diseases.

genetics↗