Biology subjects

Maric, M.

Publications and source records attributed to Maric, M..

4 recordsLinked to original sources

bioRxiv2025

Distinct ATRX functions cooperate with 9-1-1 and CST complexesto safeguard replication and telomere integrity

Mutations in the ATRX chromatin remodeller predispose to a developmental genetic disorder and cancer, but how it safeguards genome and telomere stability remains unresolved. Here, we uncover critical dependencies for the CTC1-STN1-TEN1 (CST) complex and RAD9A-HUS1-RAD1 (9-1-1) clamp in ATRX deficient cells. ATRX:CST synthetic lethality manifests following accumulation of telomeric G-rich ssDNA, which results in telomere loss and cell death. Conversely, we attribute ATRX:9-1-1 synthetic lethality to genome-wide ssDNA lesions, which compromise DNA replication. We further show ATRX suppresses DNA damage during replication stress by counteracting the activity of the FAM111A protease. We demonstrate that roles of ATRX in telomere maintenance and replication are genetically separable requiring its ATPase activity and PIP-box, respectively, and independently of its DAXX interaction. Collectively, functions of ATRX in suppressing toxic ssDNA lesions are context-dependent and are key to global DNA replication and telomere integrity.

molecular biology↗

bioRxiv2025

SLFN11 restricts escape from telomere crisis to prevent alternative lengthening of telomeres

The tRNA nuclease SLFN11 is epigenetically silenced in [~]50% of treatment-naive tumours and is the strongest predictor of chemoresistance but why it is frequently inactivated in cancer is unknown. To acquire immortality, cancer cells can activate alternative lengthening of telomeres (ALT), typically accompanied by ATRX loss. Here, we implicate SLFN11 in sensing telomere replication stress, triggering eradication of ATRX deficient cells prior to ALT establishment. Whereas progressive telomere shortening of cells lacking telomerase and ATRX leads to telomere crisis and cell death, SLFN11 loss confers tolerance to PML-BLM dependent ALT intermediates, permitting emergence of ALT survivors. We propose that during tumorigenesis SLFN11 inactivation is selected as means to tolerate endogenous replication stress following telomere crisis, leading to the development of therapy resistant tumours before treatment.

molecular biology↗

bioRxiv2025

Parabricks: GPU Accelerated Universal Pan-Instrument Genomics Analysis Software Suite

Next-generation sequencing (NGS) has transformed genomics, enabling breakthroughs in biotechnology, healthcare, and pharmaceuticals. However, exponential data growth-outpacing Moores Law-presents critical computational challenges for secondary analysis. We introduce Parabricks, a freely accessible, GPU-accelerated software suite supporting diverse workflows, including wholegenome, exome, transcriptome, and methylation analysis. Compatible across major short read and long read sequencing platforms, it reduces processing time from hours to minutes while maintaining concordance with established standards, this acceleration translates to significant cost savings. Deployable on-premises or through cloud platforms, Parabricks ensures scalable, genomic processing. Integrated AI-driven workflows and deep learning models further enhance precision, offering a universal solution for high-throughput genomic research and clinical diagnostics.

bioinformatics↗

bioRxiv2022

Accelerating Minimap2 for accurate long read alignment on GPUs

Long read sequencing technology is becoming increasingly popular for Precision Medicine applications like Whole Genome Sequencing (WGS) and microbial abundance estimation. Minimap2 is the state-of-the-art aligner and mapper used by the leading long read sequencing technologies, today. However, Minimap2 on CPUs is very slow for long noisy reads. [~]60-70% of the run-time on a CPU comes from the highly sequential chaining step in Minimap2. On the other hand, most Point-of-Care computational workflows in long read sequencing use Graphics Processing Units (GPUs). We present minimap2-accelerated (mm2-ax), a heterogeneous design for sequence mapping and alignment where minimap2s compute intensive chaining step is sped up on the GPU and demonstrate its time and cost benefits. We extract better intra-read parallelism from chaining without loosing mapping accuracy by forward transforming Minimap2s chaining algorithm. Moreover, we better utilize the high memory available on modern cloud instances apart from better workload balancing, data locality and minimal branch divergence on the GPU. We show mm2-ax on an NVIDIA A100 GPU improves the chaining step with 5.41 - 2.57X speedup and 4.07 - 1.93X speedup : costup over the fastest version of Minimap2, mm2-fast, benchmarked on a Google Cloud Platform instance of 30 SIMD cores.

genomics↗