Simultaneous Isolation of High-Quality RNA and DNA From Postmortem Human Central Nervous System Tissues for Omics Studies. Issue 2 (22nd December 2021)

• Record Type: Journal Article
• Authors: Grima, Natalie; Henden, Lyndal; Watson, Owen; Blair, Ian P; Williams, Kelly L
• Is Part Of: Journal of neuropathology and experimental neurology. Volume 81:Issue 2(2022)
• Page Start: 135
• Page End: 145
• Publication Date: 2021-12-22
• Subjects: Brain -- Neurodegenerative disease -- Nucleotide extraction -- Postmortem tissue -- RNA sequencing -- Simultaneous DNA/RNA isolation -- Spinal cord; Neurology -- Diseases -- Periodicals; Neurology -- Diseases -- Physiopathology -- Periodicals; 616.8047
• DOI: 10.1093/jnen/nlab129
• Languages: English
• ISSNs: 0022-3069

Abstract

Abstract: Multi-omics approaches are increasingly being adopted to understand the complex networks underlying disease. The coisolation of high-quality nucleotides from affected tissues is paramount for the parallel analysis of transcriptomic, genomic, and epigenomic data sets. Although nucleotides extracted from postmortem central nervous system (CNS) tissue are widely used in the study of neurodegenerative disease, assessment of methods for the simultaneous isolation of DNA and RNA is limited. Herein, we describe a strategy for the isolation of high-quality DNA and RNA from postmortem human tissue from 7 CNS regions. Motor cortex, frontal cortex, hippocampus, occipital cortex, anterior cingulate cortex, cerebellum, and spinal cord tissues were obtained from 22 individuals diagnosed with motor neuron disease (MND) and 13 neurologically normal controls (n = 245 tissues). We demonstrated that the Qiagen AllPrep DNA/RNA kit consistently isolated DNA and RNA of high yield and quality from all 6 brain regions. Importantly, phenol-chloroform-based extraction was required to isolate high-yield RNA from spinal cord. RNA sequencing using RNA extracted from 6 CNS regions (n = 60) generated high-quality transcriptomes. Hierarchical clustering of data from motor cortex, using an MND susceptibility gene panel and marker genes of disease-associated microglia, demonstrated that MND-specific gene expression signatures could be detected in the transcriptome data.