Biology subjects

Little, P.

Publications and source records attributed to Little, P..

5 recordsLinked to original sources

bioRxiv2024

The clinical antiprotozoal drug halofuginone promotes weight loss by elevating GDF15 and FGF21

Obesity is a debilitating disease with increasing worldwide prevalence. Despite its high prevalence, specific pharmacologic intervention for obesity is challenging. Here, we report that halofuginone, an FDA-approved anti-scleroderma and anti-protozoal drug, is a promising anti-obesity agent in rodent models. Halofuginone suppressed food intake, increased energy expenditure, and resulted in weight loss in preclinical diet-induced obese mouse models, while also decreasing insulin resistance and hepatic steatosis. By combining genetic and pharmacological tools with transcriptomics, we identified that halofuginone increases FGF21 and GDF15 levels via ATF4. Using knockout mice, we show these hormones are both necessary for its anti-obesity effects. Thus, our study first reports the beneficial metabolic effects of halofuginone and underscores its utility to treat obesity and its associated metabolic complications.

pharmacology and toxicology↗

bioRxiv2022

Cell type-specific Expression Quantitative Trait Loci

Mapping cell type-specific gene expression quantitative trait loci (ct-eQTLs) is a powerful way to investigate the genetic basis of complex traits. A popular method for ct-eQTL mapping is to assess the interaction between the genotype of a genetic locus and the abundance of a specific cell type using a linear model. However, this approach requires transforming RNA-seq count data, which distorts the relation between gene expression and cell type proportions and results in reduced power and/or inflated type I error. To address this issue, we have developed a statistical method called CSeQTL that allows for ct-eQTL mapping using bulk RNA-seq count data while taking advantage of allele-specific expression. We validated the results of CSeQTL through simulations and real data analysis, comparing CSeQTL results to those obtained from purified bulk RNA-seq data or single cell RNA-seq data. Using our ct-eQTL findings, we were able to identify cell types relevant to 21 categories of human traits.

genomics↗

bioRxiv2021

ROKET: Associating Somatic Mutation with Clinical Outcomes through Kernel Regression and Optimal Transport

Somatic mutations in cancer patients are inherently sparse and potentially high dimensional. Cancer patients may share the same set of deregulated biological processes perturbed by different sets of somatically mutated genes. Therefore, when assessing the associations between somatic mutations and clinical outcomes, gene-by-gene analyses is often under-powered because it does not capture the complex disease mechanisms shared across cancer patients. Rather than testing genes one by one, an intuitive approach is to aggregate somatic mutation data of multiple genes to assess the joint association. The challenge is how to aggregate such information. Building on the optimal transport method, we propose a principled approach to estimate the similarity of somatic mutation profiles of multiple genes between tumor samples, while accounting for gene-gene similarity defined by gene annotations or empirical mutational patterns. Using such similarities, we can assess the associations between somatic mutations and clinical outcomes by kernel regression. We have applied our method to analyze somatic mutation data of 17 cancer types and identified at least three cancer types harboring associations between somatic mutations and overall survival, progression-free interval or cytolytic activity.

genomics↗

bioRxiv2021

eQTL mapping using allele-specific gene expression

Using information from allele-specific gene expression (ASE) can sub-stantially improve the power to map gene expression quantitative trait loci (eQTLs). However, such practice has been limited, partly due to high computational cost and the requirement to access raw data that can take a large amount of storage space. To address these computational challenges, we have developed a computational framework that uses a statistical method named TReCASE as its computational engine, and it is computationally feasible for large scale analysis. We applied it to map eQTLs in 28 human tissues using the data from the Genotype-Tissue Expression (GTEx) project. Compared with a popular linear regression method that does not use ASE data, TReCASE can double the number of eGenes (i.e., genes with at least one significant eQTL) when sample size is relatively small, e.g., n = 200. We also demonstrated how to use the ASE data that we have collected to study dynamic eQTLs whose effect sizes vary with respect to another variable, such as age. We find the majority of such dynamic eQTLs are due to some underlying latent factors, such as cell type proportions. We further compare TReCASE versus another method RASQUAL. TReCASE is ten times or more faster than RASQUAL and it provides more robust type I error control.

genomics↗

bioRxiv2016

The detection of covariation of mRNA levels of large sets of genes across multiple human populations

In this study, we analyse RNA-Seq data from panels of human lymphoblastoid cell lines (LCLs) to identify covariation in the mRNA levels of large numbers of genes. Such large scale covariation may have biological origin or be due to technical variation in analysis (generally referred to as batch effects). We show that batch effects cannot explain this covariation by demonstrating reproducibility across different human populations and across different methods of analysis. This view is also supported by enrichment of single and combinations of transcription factors (TFs) binding to cognate promoter regions, enrichment of genes shown to be sensitive to the knockdown of individual TFs, enrichment of functional pathways, and finally enrichment of protein-protein interactions in proteins encoded by groups of covarying genes. The properties of the groups of covarying genes are therefore most readily explained by the influence of cumulative variations in the effectors of gene expression that act in trans on cognate genes. We suggest that covariation has functional outcomes by showing that covariation of 83 genes involved in the spliceosome pathway accounts for 8-16% of the variation in the alternative splicing patterns of genes expressed in human LCLs.

genetics↗