Biology subjects

Frasca, M.

Publications and source records attributed to Frasca, M..

3 recordsLinked to original sources

bioRxiv2026

ZCWPW1 organizes telomeric architecture to drive meiotic chromosome movements

Meiotic homolog pairing relies on programmed DNA recombination and large-scale chromosome movements, yet, how these genetic and mechanical events are coordinated remains unclear. ZCWPW1 is a histone reader that recognizes PRDM9-deposited chromatin marks. We identify an unexpected role for ZCWPW1 as a regulator of rapid prophase movements (RPMs). Using super-resolution imaging, we show that ZCWPW1 is strongly enriched at subtelomeric regions of mouse spermatocytes, where it stabilizes TRF1, LINC complex components, dynein, and meiosis-specific cohesin (STAG3). Loss of ZCWPW1 disrupts telomere architecture, weakens telomere-LINC- motor coupling, and abolishes chromosome movement, leading to defective synapsis and pairing, and persistence of DSBs. These defects are more severe than, and mechanistically independent of, those observed in Prdm9-/- spermatocytes. Together, our findings reveal that ZCWPW1 acts independently of PRDM9 as a chromatin-based intranuclear regulator of telomere architecture and telomere-led chromosome movements, thereby linking telomeric chromatin state to nuclear force transmission required for faithful meiotic progression. Significance StatementMeiotic pairing requires recombination and telomere-led chromosome movements, yet no chromatin factor has been shown to regulate both. We identify ZCWPW1 as the first chromatin-based regulator of rapid prophase movements. ZCWPW1 organizes telomeric chromatin and promotes cohesin and motor assembly at telomeres that for force transmission across the nuclear envelope. Loss of ZCWPW1 disrupts the telomere-nuclear envelope mechanical coupling, impairing motion and altering recombination. This function doesnt rely on PRDM9 despite their co-evolution and co-expression, challenging the prevailing view that ZCWPW1 only acts downstream of PRDM9 in DNA repair. Our findings show that chromatin readers can function as structural regulators of genome organization, revealing a conserved mechanism integrating chromosome structure, motion, and repair to ensure proper pairing and fertility.

cell biology↗

bioRxiv2022

Genetic dissection of crossover mutants defines discrete intermediates in mouse meiosis

Crossovers, the exchange of homolog arms, are required for accurate segregation during meiosis. Studies in yeast have established that the single end invasion intermediate is highly regulated to ensure crossover distribution. Single end invasions are thought to differentiate into double Holliday junctions that are resolved by MutLgamma (MLH1/3) into crossovers. Currently, we lack knowledge of early steps of mammalian crossover recombination or how intermediates are differentiated in any organism. Using comprehensive analysis of recombination and cytology, we infer that polymerized single-end invasion intermediates and nicked double Holliday junctions are crossover precursors in mouse spermatocytes. In marked contrast to yeast, MLH3 plays a structural role to differentiate single end invasions into double Holliday junctions with differentially polymerized 3 ends. Therefore, we show independent genetic requirements for precursor formation and asymmetry with regard to 3 end processing, providing mechanistic insight into crossover formation and patterning.

genetics↗

bioRxiv2020

parSMURF, a High Performance Computing tool for the genome-wide detection of pathogenic variants

Several prediction problems in Computational Biology and Genomic Medicine are characterized by both big data as well as a high imbalance between examples to be learned, whereby positive examples can represent a tiny minority with respect to negative examples. For instance, deleterious or pathogenic variants are overwhelmed by the sea of neutral variants in the non-coding regions of the genome: as a consequence the prediction of deleterious variants is a very challenging highly imbalanced classification problem, and classical prediction tools fail to detect the rare pathogenic examples among the huge amount of neutral variants or undergo severe restrictions in managing big genomic data. To overcome these limitations we propose parSMURF, a method that adopts a hyper-ensemble approach and oversampling and undersampling techniques to deal with imbalanced data, and parallel computational techniques to both manage big genomic data and significantly speed-up the computation. The synergy between Bayesian optimization techniques and the parallel nature of parSMURF enables efficient and user-friendly automatic tuning of the hyper-parameters of the algorithm, and allows specific learning problems in Genomic Medicine to be easily fit. Moreover, by using MPI parallel and machine learning ensemble techniques, parSMURF can manage big data by partitioning them across the nodes of a High Performance Computing cluster. Results with synthetic data and with single nucleotide variants associated with Mendelian diseases and with GWAS hits in the non-coding regions of the human genome, involving millions of examples, show that parSMURF achieves state-of-the-art results and a speed-up of 80x with respect to the sequential version. In conclusion parSMURF is a parallel machine learning tool that can be trained to learn different genomic problems, and its multiple levels of parallelization and its high scalability allow us to efficiently fit problems characterized by big and imbalanced genomic data. Availability and ImplementationThe C++ OpenMP multi-core version tailored to a single workstation and the C++ MPI/OpenMP hybrid multi-core and multi-node parSMURF version tailored to a High Performance Computing cluster are both available from github: https://github.com/AnacletoLAB/parSMURF

bioinformatics↗