Skip to main content
eScholarship
Open Access Publications from the University of California

Analysis of the roles of TIN2 splice forms in human telomere regulation and maintenance

  • Author(s): Cimini, Beth
  • Advisor(s): Blackburn, Elizabeth H
  • et al.
Abstract

Mammalian telomeres are protected by a 6-protein unit called the shelterin complex; the scaffold protein, TIN2, regulates the stability and recruitment of all of the other members and additionally controls telomerase access. In humans TIN2 has been shown to have two major isoforms; the shorter, soluble TIN2S isoform and the longer, nuclear matrix-associated TIN2L. To determine whether the isoforms have separate functions we moderately expressed GFP-TIN2S or GFP-TIN2L either alone or alongside an shRNA to knock down the endogenous TIN2. We found that while either isoform supported telomerase access and telomere elongation, GFP-TIN2L showed a significant defect in protecting telomeres from DNA damage and that this defect was likely due to decreased ability to associate with the telomere. Both phenotypes could be modulated by a point mutation of the TIN2L S396 casein kinase II consensus phosphorylation site. We also found that the S270 ATM/ATR consensus phosphorylation site showed no effect when mutated in GFP-TIN2S but had significant effects on GFP-TIN2L’s association with TRF1. TIN2L’s access to the telomere is therefore much more regulated than TIN2S’s and may hint at a role for TIN2L as a factor that can quickly modulate telomere behavior whenever the cell requires.

In the course of this work I began accumulating very large data sets in CellProfiler, running tens of thousands of measurements in each experiment. In order to cope with the analysis I began to write Python scripts with a basic GUI to automate some simpler tasks (selecting parameters to analyze, pulling those columns from the spreadsheet of each image analysis set, and running statistical comparisons), then added the ability to save default parameter sets, generate graphs, to run a few extra analyses not offered by CellProfiler. I found myself wishing such a program had already existed to help me analyze my data and wanting to share these functions with labmates who ran similar experiments but didn’t know how to program. In Chapter 2 I describe the culmination of this work - CellProfilerStats, a free open-source program to parse image analysis data into statistical analyses and high-quality graphs, no programming required.

Main Content
Current View