Jill M. Recla

Date of Award


Level of Access

Campus-Only Dissertation

Degree Name

Doctor of Philosophy (PhD)


Interdisciplinary Program


Carol J. Bult

Second Committee Member

Gary A. Churchill

Third Committee Member

Keith W. Hutchison


Sensitivity to pain varies widely between subjects, and the significant influence of genetic factors on pain sensitivity variability is now widely appreciated. Animal models are a powerful tool for discovering genes influencing human pain sensitivity. Approximately 350 pain-related genes have been identified in the laboratory mouse to date, along with 14 pain-related quantitative trait loci (QTL) believed to contain genes involved in both acute and chronic pain response. Currently, the field of pain genetics is still heavily focused on the functional characterization of individual genes selected based on a-priori information, narrowing the focus of pain research to specific classes of protein-coding genes. In many cases, known pain genes exert relatively large phenotypic effects and are involved in numerous physiological processes, often limiting their use as therapeutic targets. This thesis had two immediate goals: 1) Identify novel genes whose allelic variants affect sensitivity to acute thermal pain, and 2) Understand the potential relationship of these new genes to existing pain genes and uncover new pathways involved in pain response. In order to accomplish the first goal, phenotypic data from the hot plate assay of thermal nociception were used to conduct two genome-wide in-silico genetic mapping studies – one in a population of emerging Diversity Outbred (DO) mice, and one in a population of Mouse Diversity Panel (MDP) mice. Candidate genes identified through genetic mapping were then assessed for relevance to pain by combining annotation data from a variety of publicly available data sources. Genetic network analysis tools were then used to visualize known and predicted functional relationships between candidate genes and other nervous system genes. This work identified three novel candidate pain genes: 1) the currently unclassified gene RIKEN cDNA C230014O12 (C230014O12Rik), and the protein coding genes 2) glypican 3 (Gpc3) and 3) hydrocephalus inducing (Hydin). Subsequent genetic network analyses revealed that the candidate genes may function in novel pain-related biological pathways. The information generated by this research promises to facilitate the long term goal of developing improved methods of individualized acute, and perhaps chronic, pain prevention and treatment.