Graduation Date

Fall 2022

Document Type

Thesis

Program

Master of Science degree with a major in Biology

Committee Chair Name

Amy Sprowles

Committee Chair Affiliation

HSU Faculty or Staff

Second Committee Member Name

Kyle Fink

Second Committee Member Affiliation

Community Member or Outside Professional

Third Committee Member Name

Brigitte Blackman

Third Committee Member Affiliation

HSU Faculty or Staff

Fourth Committee Member Name

Catalina Cuellar Gempeler

Fourth Committee Member Affiliation

HSU Faculty or Staff

Keywords

Epigenetics, X chromosome, Bioinformatics, Stem cells

Subject Categories

Biology

Abstract

Females with heterozygous X-linked mutations are prone to pseudo-haploinsufficiency because random X chromosome inactivation (XCI) silences one of their two X chromosomes. A prior study explored the theory that reactivating the silenced healthy allele could be a treatment for pseudo-haploinsufficient females. The next step was to evaluate this approach in a clinically relevant stem cell model of the rare neurological disease CDKL5 Deficiency Disorder (CDD). It was necessary to validate X-inactivation state with respect to CDKL5 allele expression in one of these models. We explored CDKL5 allele expression in two populations of CDD female patient-derived induced pluripotent stem cells (iPSCs) by determining whether expression of the CDKL5 allele from the inactive X chromosome was the result of a mixed population or incomplete XCI. To examine incomplete XCI due to naïve cell state, the iPSCs were differentiated into neuronal stem cells (NSCs), but sequencing revealed that NSCs maintained inactive allele expression. By contrast, sequencing of individual clones selected from both iPSC populations revealed clonal expression of CDKL5 alleles. This result indicated that a mixed cell population was the likely cause of "inactive" allele expression. This supports the use of these particular iPSCs as reactivation models. To develop a pipeline to observe epigenetic states on the inactive X, standard bioinformatic analysis of ChIP-seq data was combined with AlleleSeq to assess allele specific activity. This pipeline was used on publicly available ChIP-seq data from GM12878 cells. The results reveal bottlenecks for allele specific epigenetic research. Collectively, this work contains both methods and considerations for researchers studying inactivation of specific X-linked genes in iPSC models and epigenetic features in the female X chromosome.

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