The MLH1 ATPase domain is needed for suppressing aberrant formation of interstitial telomeric sequences

Classification of MLH1 Missense VUS Using Protein Structure-Based Deep Learning-Ramachandran Plot-Molecular Dynamics Simulations Method

Pathogenic variation in DNA mismatch repair (MMR) gene MLH1 is associated with Lynch syndrome (LS), an autosomal dominant hereditary cancer. Of the 3798 MLH1 germline variants collected in the ClinVar database, 38.7% (1469) were missense variants, of which 81.6% (1199) were classified as Variants of Uncertain Significance (VUS) due to the lack of functional evidence. Further determination of the impact of VUS on MLH1 function is important for the VUS carriers to take preventive action. We recently developed a protein structure-based method named "Deep Learning-Ramachandran Plot-Molecular Dynamics Simulation (DL-RP-MDS)" to evaluate the deleteriousness of MLH1 missense VUS. The method extracts protein structural information by using the Ramachandran plot-molecular dynamics simulation (RP-MDS) method, then combines the variation data with an unsupervised learning model composed of auto-encoder and neural network classifier to identify the variants causing significant change in protein structure. In this report, we applied the method to classify 447 MLH1 missense VUS. We predicted 126/447 (28.2%) MLH1 missense VUS were deleterious. Our study demonstrates that DL-RP-MDS is able to classify the missense VUS based solely on their impact on protein structure.

Integration of deep learning with Ramachandran plot molecular dynamics simulation for genetic variant classification

Functional classification of genetic variants is a key for their clinical applications in patient care. However, abundant variant data generated by the next-generation DNA sequencing technologies limit the use of experimental methods for their classification. Here, we developed a protein structure and deep learning (DL)-based system for genetic variant classification, DL-RP-MDS, which comprises two principles: 1) Extracting protein structural and thermodynamics information using the Ramachandran plot-molecular dynamics simulation (RP-MDS) method, 2) combining those data with an unsupervised learning model of auto-encoder and a neural network classifier to identify the statistical significance patterns of the structural changes. We observed that DL-RP-MDS provided higher specificity than over 20 widely used in silico methods in classifying the variants of three DNA damage repair genes: TP53, MLH1, and MSH2. DL-RP-MDS offers a powerful platform for high-throughput genetic variant classification. The software and online application are available at https://genemutation.fhs.um.edu.mo/DL-RP-MDS/.

Telomerase subunit Est2 marks internal sites that are prone to accumulate DNA damage

Background

The main function of telomerase is at the telomeres but under adverse conditions telomerase can bind to internal regions causing deleterious effects as observed in cancer cells.

Results

By mapping the global occupancy of the catalytic subunit of telomerase (Est2) in the budding yeast Saccharomyces cerevisiae, we reveal that it binds to multiple guanine-rich genomic loci, which we termed “non-telomeric binding sites” (NTBS). We characterize Est2 binding to NTBS. Contrary to telomeres, Est2 binds to NTBS in G1 and G2 phase independently of Est1 and Est3. The absence of Est1 and Est3 renders telomerase inactive at NTBS. However, upon global DNA damage, Est1 and Est3 join Est2 at NTBS and telomere addition can be observed indicating that Est2 occupancy marks NTBS regions as particular risks for genome stability.

Conclusions

Our results provide a novel model of telomerase regulation in the cell cycle using internal regions as “parking spots” of Est2 but marking them as hotspots for telomere addition.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01167-1.

At the Beginning of the End and in the Middle of the Beginning: Structure and Maintenance of Telomeric DNA Repeats and Interstitial Telomeric Sequences

Tandem DNA repeats derived from the ancestral (TTAGGG)n run were first detected at chromosome ends of the majority of living organisms, hence the name telomeric DNA repeats. Subsequently, it has become clear that telomeric motifs are also present within chromosomes, and they were suitably called interstitial telomeric sequences (ITSs). It is well known that telomeric DNA repeats play a key role in chromosome stability, preventing end-to-end fusions and precluding the recurrent DNA loss during replication. Recent data suggest that ITSs are also important genomic elements as they confer its karyotype plasticity. In fact, ITSs appeared to be among the most unstable microsatellite sequences as they are highly length polymorphic and can trigger chromosomal fragility and gross chromosomal rearrangements. Importantly, mechanisms responsible for their instability appear to be similar to the mechanisms that maintain the length of genuine telomeres. This review compares the mechanisms of maintenance and dynamic properties of telomeric repeats and ITSs and discusses the implications of these dynamics on genome stability.