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TPP1 mutagenesis screens unravel shelterin interfaces and functions in hematopoiesis.

ABSTRACT: Telomerase catalyzes chromosome end replication in stem cells and other long-lived cells. Mutations in telomerase or telomere-related genes result in diseases known as telomeropathies. Telomerase is recruited to chromosome ends by the ACD/TPP1 protein (TPP1 hereafter), a component of the shelterin complex that protects chromosome ends from unwanted end joining. TPP1 facilitates end protection by binding shelterin proteins POT1 and TIN2. TPP1 variants have been associated with telomeropathies but remain poorly characterized in vivo. Disease variants and mutagenesis scans provide efficient avenues to interrogate the distinct physiological roles of TPP1. Here, we conduct mutagenesis in the TIN2- and POT1-binding domains of TPP1 to discover mutations that dissect TPP1's functions. Our results extend current structural data to reveal that the TPP1-TIN2 interface is more extensive than previously thought and highlight the robustness of the POT1-TPP1 interface. Introduction of separation-of-function mutants alongside known TPP1 telomeropathy mutations in mouse hematopoietic stem cells (mHSCs) lacking endogenous TPP1 demonstrated a clear phenotypic demarcation. TIN2- and POT1-binding mutants were unable to rescue mHSC failure resulting from end deprotection. In contrast, TPP1 telomeropathy mutations sustained mHSC viability, consistent with their selectively impacting end replication. These results highlight the power of scanning mutagenesis in revealing structural interfaces and dissecting multifunctional genes.

SUBMITTER: Grill S

PROVIDER: S-EPMC8262337 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Retroviral insertional mutagenesis screens, which identify genes involved in tumor development in mice, have yielded a substantial number of retroviral integration sites, and this number is expected to grow substantially due to the introduction of high-throughput screening techniques. The data of various retroviral insertional mutagenesis screens are compiled in the publicly available Retroviral Tagged Cancer Gene Database (RTCGD). Integrally analyzing these screens for the presence of common insertion sites (CISs, i.e., regions in the genome that have been hit by viral insertions in multiple independent tumors significantly more than expected by chance) requires an approach that corrects for the increased probability of finding false CISs as the amount of available data increases. Moreover, significance estimates of CISs should be established taking into account both the noise, arising from the random nature of the insertion process, as well as the bias, stemming from preferential insertion sites present in the genome and the data retrieval methodology. We introduce a framework, the kernel convolution (KC) framework, to find CISs in a noisy and biased environment using a predefined significance level while controlling the family-wise error (FWE) (the probability of detecting false CISs). Where previous methods use one, two, or three predetermined fixed scales, our method is capable of operating at any biologically relevant scale. This creates the possibility to analyze the CISs in a scale space by varying the width of the CISs, providing new insights in the behavior of CISs across multiple scales. Our method also features the possibility of including models for background bias. Using simulated data, we evaluate the KC framework using three kernel functions, the Gaussian, triangular, and rectangular kernel function. We applied the Gaussian KC to the data from the combined set of screens in the RTCGD and found that 53% of the CISs do not reach the significance threshold in this combined setting. Still, with the FWE under control, application of our method resulted in the discovery of eight novel CISs, which each have a probability less than 5% of being false detections.

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TPP1 mutagenesis screens unravel shelterin interfaces and functions in hematopoiesis.

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