Mechanisms and Measurement of Changes in Gene Expression

Abstract

Research on gene expression (GE) provides insights into the physiology of a cell or group of cells at a given point in time. Studies of changes in GE can be used to identify patients at higher risk for various medical conditions, a higher symptom burden, and/or the adverse consequences associated with various treatments. The aims of this article are as follows: (1) to describe the different types of RNA transcripts, (2) to describe the processes involved in GE (i.e., RNA transcription, epigenetics, and posttranscriptional modifications), (3) to describe common sources of variation in GE, (4) to describe the most common methods used to measure GE, and (5) to discuss factors to consider when choosing tissue for a GE study. This article begins with an overview of the mechanisms involved in GE. Then, the factors that can influence the findings from GE experiments (e.g., tissue specificity, host age, host gender, and time of sample collection) are described and potential solutions are presented. This article concludes with a discussion of how the types of tissue used in GE studies can affect study findings. Given that the costs associated with the measurement of changes in GE are decreasing and the methods to analyze GE data are becoming easier to use, nurse scientists need to understand the basic principles that underlie any GE study.

Two evolutionarily duplicated domains individually and post‐transcriptionally control SWEET expression for phloem transport

“…However, we know nothing about the mechanism governing this PP‐specific accumulation. A promoter is essential for gene expression and is the main contributor to tissue‐ or cell‐specific gene expression if it contains a specific regulatory element (Ramírez‐Clavijo & Montoya‐Ortíz, 2013; Singh et al ., 2018). To examine if the SWEET11 promoter including 5′ UTR (we simplified it as the promoter hereafter, pSWEET11 ) alone is sufficient to confer PP expression, we generated transgenic lines carrying the SWEET11 promoter driving GUS and did histochemical GUS staining (Fig.…”

Down-regulation of BCL2L13 renders poor prognosis in clear cell and papillary renal cell carcinoma

“…Somatic mutations and gene CNAs could also influence the prognosis of cancer patients [ 36 ]. Through analysis using data from TCGA, BCL2L13 copy number altered only 0.2% in ccRCC with deep deletion, and 1.1% in pRCC with deep deletion and missense mutations (Additional file 5 ).…”

Lost in translation. The quest for definitions of treatment-resistant depression with a focus on inflammation-related gene expression

“…Through the analysis of mRNA transcripts, it is possible to identify expression levels of the products of every single gene of the genome ( Stransky and Souza, 2013 ). Notably, gene expression is a dynamic process and can change under a variety of conditions ( Singh et al., 2018 ). Changes in gene expression may help to identify differences between clinical phenotypes.…”