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Chang, T.-W.

Publications and source records attributed to Chang, T.-W..

2 recordsLinked to original sources

The phosphorylation of Pak1 by Erk1/2 for cell migration requires Arl4D acting as a scaffolding protein

Activation of extracellular signal-regulated kinases 1 and 2 (Erk1/2) at the plasma membrane typically results in their translocation to other intracellular sites for substrate targeting. This targeting requires scaffolding proteins to bring Erk1/2 and their substrates together. In the case of platelet-derived growth factor (PDGF)-induced signaling that activates Erk1/2 to phosphorylate Pak1 for cell migration, Erk1/2 remain at the plasma membrane. Thus, it has been unclear in this case whether a scaffolding protein is needed for substrate targeting by Erk1/2. The small GTPase Arf-like protein (Arl) 4D also promotes cell migration by targeting Pak1 to the plasma membrane. However, as this recruitment also results in the phosphorylation of Pak1, it has been unclear how this phosphorylation is achieved. Furthermore, because both Erk1/2 and Arl4D promote the role of Pak1 in cell migration, the relationship between these two processes has also been unclear. Addressing these outstanding questions, we show that Arl4D acts as a scaffolding protein by recruiting Erk1/2 and Pak1 to the plasma membrane for their assembly into a protein complex. Our findings identify Arl4D as a novel regulator of Erk1/2, reveal a conserved role for scaffolding proteins in substrate targeting by Erk1/2, as well as uncovering a previously unknown interplay among Arl4D, Erk1/2, and Pak1. Moreover, as all these factors are known to be involved in cell migration, we have shed new mechanistic insights into how this fundamental cellular process occurs.

cell biology↗

powerEQTL: An R package and shiny application for sample size and power calculation of bulk tissue and single-cell eQTL analysis

SummaryGenome-wide association studies (GWAS) have revealed thousands of genetic loci for common diseases. One of the main challenges in the post-GWAS era is to understand the causality of the genetic variants. Expression quantitative trait locus (eQTL) analysis has been proven to be an effective way to address this question by examining the relationship between gene expression and genetic variation in a sufficiently powered cohort. However, it is often tricky to determine the sample size at which a variant with a specific allele frequency will be detected to associate with gene expression with sufficient power. This is particularly demanding with single-cell RNAseq studies. Therefore, a user-friendly tool to perform power analysis for eQTL at both bulk tissue and single-cell level will be critical. Here, we presented an R package called powerEQTL with flexible functions to calculate power, minimal sample size, or detectable minor allele frequency in both bulk tissue and single-cell eQTL analysis. A user-friendly, program-free web application is also provided, allowing customers to calculate and visualize the parameters interactively. Availability and implementationThe powerEQTL R package source code and online tutorial are freely available at CRAN: https://cran.r-project.org/web/packages/powerEQTL/. The R shiny application is publicly hosted at https://bwhbioinfo.shinyapps.io/powerEQTL/. ContactXianjun Dong (xdong@rics.bwh.harvard.edu), Weiliang Qiu (weiliang.qiu@sanofi.com) Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗