Author ORCID Identifier

https://orcid.org/0000-0001-9356-4339

Date Available

9-23-2021

Year of Publication

2021

Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation

College

Medicine

Department/School/Program

Pharmacology and Nutritional Sciences

First Advisor

Dr. Eric Blalock

Abstract

Transcriptional profiling (TP) is a common tool to determine RNA expression levels. It allows for thousands of genes to be analyzed simultaneously, and determines differences in gene expression levels due to various pathologies. RNA quality also impacts the reported expression level. One of the most common approaches for assessing RNA quality is Agilent Technology’s RNA integrity number (RIN). The use of RINs allowed scientists to standardize the assessment and reporting of RNA quality by predominantly using rRNA traits to assign a quantitative value. Recent work provided evidence that RINs are associated with transcriptional profiles, and possibly has a stronger connection to some pathologies. Because of the effect RIN has on gene expression, many have tried to correct for its influence using techniques such as multiple regression. Despite this, there has been relatively little work done on determining 1) how RNA quality impacts TP results, 2) when RNA degradation begins to impact gene expression, and 3) the relationship between RINs and gene expression. To investigate this, individual profiles from human, control, brain tissue with disambiguated RINs were analyzed. A robust set of mRNA species, particularly related to neurons, were significantly correlated with RINs, indicating that neurons are more susceptible to the effects of RNA degradation in brain tissue. Most of the decline in mRNA expression occurs within a narrow RIN range of 7.2 to 8.6, with values greater than 8.6 not needing RIN-correction and values less than 7.2 being too degraded to give accurate readings. This non-linear relationship between RINs and mRNA expression may be important to consider for RIN-correction procedures. Also, it was confirmed that RINs appear to be confounded with certain pathologies. RNA quality is possibly influenced by ante-mortem factors that occur during life and may exacerbate post-mortem effects.

Post-mortem variables are a key focus for RNA quality, while ante-mortem factors such as stress and neuropathology are less understood. During stress, glucocorticoids (GCs) released from the adrenal glands are associated with neurotoxic and RNA degrading effects in brain that may contribute to ante-mortem influences on RNA quality. Recent evidence has shown that progesterone (P4) may counter GC’s effects during stress. To determine if acute psychosocial stress impacts RNA quality and whether P4 protects against the effects of this stress, male and female rats were administered a vehicle or P4 daily during water maze training, and then underwent an acute stress (restraint) before the probe trial. Female, P4-stressed animals had improved probe trial performance compared to their vehicle-stressed counterparts, and neither stress nor P4 influenced RNA quality. Stressed animals had higher blood plasma GC levels, as expected. In the hippocampus, acute stress and P4 did not alter Sgk1 protein levels between sexes, but Sgk1 mRNA was significantly increased in male vehicle-stressed subjects, and this stress effect was blocked by P4. Based on prior work showing both age and stress sensitivity, we also assessed microglial-myelin fragment co-labeling, and found that this was increased in males, particularly the progesterone groups. Taken together, this indicates that acute behavioral stress does not appreciably impact RNA quality from brain tissue, and that the behavioral and molecular effects of acute stress are partially disrupted by P4.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2021.384

Funding Information

National Institute of Aging R01 (no. AG037868) in 2017

General Funds Pharmacology and Nutritional Sciences 2017-2021

Enrichment-Pharmacology 2017-2021

Supp. Data 2.1.xlsx (78 kB)
Supplemental Data 2.1. Common significant RIN-sensitive genes from GSE25219, GSE45878, and GSE71620

Supp. Data 2.2.xlsx (42 kB)
Supplemental Data 2.2. Independent validation of correlation direction in RIN-sensitive genes

Supp. Data 2.3.xlsx (415 kB)
Supplemental Data 2.3. RNA degradation templates and associated genes

Supp. Data 2.4.xlsx (2079 kB)
Supplemental Data 2.4. Genes common to Miller et al. and significant genes from individual study analysis

Supp. Data 2.5.xlsx (3111 kB)
Supplemental Data 2.5. Genes common to Hargis & Blalock and significant genes from individual study analysis

Supp. Data 2.6.xlsx (5216 kB)
Supplemental Data 2.6. RMA data for GSE22521

Supp. Data 2.7.xlsx (4748 kB)
Supplemental Data 2.7. RMA data for GSE25219

Supp. Data 2.8.xlsx (6067 kB)
Supplemental Data 2.8. RMA data for GSE45878

Supp. Data 2.9.xlsx (28303 kB)
Supplemental Data 2.9. RMA data for GSE46706

Supp. Data 2.10.xlsx (7536 kB)
Supplemental Data 2.10. RMA data for GSE53987

Supp. Data 2.11.xlsx (53709 kB)
Supplemental Data 2.11. RMA data for GSE71620

Supp. Data 4.1.xlsx (133 kB)
Supplemental Data 4.1. Information for individual subjects

Share

COinS