RNA Sequencing from Laser Capture Microdissected Brain Tissue to Study Normal Aging and Alzheimer’s Disease

Abstract

The next-generation sequencing (NGS) of RNA, or RNA-Seq, has significantly changed the way that the transcriptional content of a biological sample is investigated. RNA-Seq is a major advance for the field due to its largely unbiased and digital nature, its ability to empower RNA splice form construction at a genomic level, and its improved dynamic range when compared to a microarray technology. Investigating the healthy or diseased brain presents unique problems from the standpoint of transcriptional analysis as each cell type, and perhaps even each individual cell, is in a unique state of transcription. The organ is a complex mixture of main cell types (neuronal, glial, vascular, etc.), and within each of those types, there are a multitude of subtypes (specific neuronal populations, different classes of glial cells, etc.) that could each be targeted for investigation and could each respond to health and disease in distinct and functionally important ways. Here, we discuss the approach of using laser capture microdissection (LCM) to specifically select cell types of interest for transcriptional dissection. We highlight approaches to couple this with RNA-Seq to generate highly specific transcriptional profiles from the brain. Sample inputs into RNA-Seq protocols continue to be pushed lower, including several reports of single-cell transcriptome profiles; therefore, the combination of cell selection approaches, like LCM, with RNA-Seq is well poised to provide a researcher with the cell-specific digital whole transcriptome information that has been desired since transcriptomic profiling became feasible during the earliest days of the microarray.