Biomedical subjects

Mehdi Pirooznia

Publications and source records attributed to Mehdi Pirooznia.

5 recordsLinked to original sources

PubMed2025

Subtelomeric elements provide stability to short telomeres in telomerase-negative cells of the budding yeast Naumovozyma castellii.

Telomerase plays an important role in sustaining eukaryotic linear chromosomes, as elongation of telomeres is needed to counterbalance the shortening occurring in each replication round. Nevertheless, in telomerase-deficient cells, Alternative Lengthening of Telomeres (ALT) pathways can maintain telomeres by employing recombination-based mechanisms. In the budding yeast Naumovozyma castellii, effective activation of the ALT pathway leads to bypass of senescence and supports long-term growth. We found that telomere structures in N. castellii ALT cells are stably maintained at a shortened uniform length over extensive numbers of generations. This is correlated to the spreading of a subtelomeric sequence, TelKO element, to all telomeres. Genome sequencing of the wild-type strain revealed variants of the TelKO element, differing in their lengths, and separate ALT strains are maintained by spreading of distinct TelKO element variants. Although short uniform telomere structures are predominant, sporadic telomere lengthening events occur by addition of long repeated arrays of TelKO elements. The telomere-binding protein Rap1 can bind to TelKO sequences in vitro, indicating a functional role of TelKO elements in providing stability to shortened ALT telomeres. Our results suggest that stable maintenance and telomere functionality may be achieved by incorporating the distal subtelomeric TelKO sequences into the telomeric chromatin cap.

Telomerase↗

PubMed2025

AncestryGeni: a novel genetic ancestry classification pipeline for small and noisy sequence data.

MOTIVATION: Efforts to address health disparities are often limited by the lack of robust computational tools for inferring genetic ancestry by calculating an individual's genetic similarity to continental groups. We have already shown that a preferred alternative to self-described race is using ancestry-informative markers (AIMs) that can be classified into ancestral components and used to estimate their similarity to those of known populations to identify continental groups. However, real-world genomic data can present challenges, including limited availability of germline DNA, a small number of AIMs for each sample, and the use of different variant calling software, limiting the application of existing solutions. RESULTS: Here, we describe a novel supervised machine-learning tool AncestryGeni, which infers genetic ancestry for samples with even a hundred markers and is applicable to any genomic data, including whole exome sequencing (WES) and RNA sequencing (RNA-Seq) data. Applying AncestryGeni to a real-world genomic dataset obtained from the Multiple Myeloma Research Foundation (MMRF) CoMMpass study, we show that it is more accurate than the commonly used FastNGSadmix when using nonstandard genomic material. We also demonstrate that when using AncestryGeni, the tumor-derived sequence obtained from WES and RNA-Seq can be a robust data source to accurately estimate an individual's genetic similarity to a continental group. AVAILABILITY AND IMPLEMENTATION: AncestryGeni pipeline is available at https://github.com/eelhaik/AncestryGeni/tree/main.

Humans↗

PubMed2021

Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology.

Circulating tumor DNA (ctDNA) sequencing is being rapidly adopted in precision oncology, but the accuracy, sensitivity and reproducibility of ctDNA assays is poorly understood. Here we report the findings of a multi-site, cross-platform evaluation of the analytical performance of five industry-leading ctDNA assays. We evaluated each stage of the ctDNA sequencing workflow with simulations, synthetic DNA spike-in experiments and proficiency testing on standardized, cell-line-derived reference samples. Above 0.5% variant allele frequency, ctDNA mutations were detected with high sensitivity, precision and reproducibility by all five assays, whereas, below this limit, detection became unreliable and varied widely between assays, especially when input material was limited. Missed mutations (false negatives) were more common than erroneous candidates (false positives), indicating that the reliable sampling of rare ctDNA fragments is the key challenge for ctDNA assays. This comprehensive evaluation of the analytical performance of ctDNA assays serves to inform best practice guidelines and provides a resource for precision oncology.

Circulating Tumor DNA↗

PubMed2006

SVM Classifier - a comprehensive java interface for support vector machine classification of microarray data.

MOTIVATION: Graphical user interface (GUI) software promotes novelty by allowing users to extend the functionality. SVM Classifier is a cross-platform graphical application that handles very large datasets well. The purpose of this study is to create a GUI application that allows SVM users to perform SVM training, classification and prediction. RESULTS: The GUI provides user-friendly access to state-of-the-art SVM methods embodied in the LIBSVM implementation of Support Vector Machine. We implemented the java interface using standard swing libraries. We used a sample data from a breast cancer study for testing classification accuracy. We achieved 100% accuracy in classification among the BRCA1-BRCA2 samples with RBF kernel of SVM. CONCLUSION: We have developed a java GUI application that allows SVM users to perform SVM training, classification and prediction. We have demonstrated that support vector machines can accurately classify genes into functional categories based upon expression data from DNA microarray hybridization experiments. Among the different kernel functions that we examined, the SVM that uses a radial basis kernel function provides the best performance. The SVM Classifier is available at http://mfgn.usm.edu/ebl/svm/.

Cluster Analysis↗

PubMed2006

RiboaptDB: a comprehensive database of ribozymes and aptamers.

BACKGROUND: Catalytic RNA molecules are called ribozymes. The aptamers are DNA or RNA molecules that have been selected from vast populations of random sequences, through a combinatorial approach known as SELEX. The selected oligo-nucleotide sequences (~200 bp in length) have the ability to recognize broad range of specific ligands by forming binding pockets. These novel aptamer sequences can bind to nucleic acids, proteins or small organic and inorganic chemical compounds and have many potential uses in medicine and technology. RESULTS: The comprehensive sequence information on aptamers and ribozymes that have been generated by in vitro selection methods are included in this RiboaptDB database. Such types of unnatural data generated by in vitro methods are not available in the public 'natural' sequence databases such as GenBank and EMBL. The amount of sequence data generated by in vitro selection experiments has been accumulating exponentially. There are 370 artificial ribozyme sequences and 3842 aptamer sequences in the total 4212 sequences from 423 citations in this RiboaptDB. We included general search feature, and individual feature wise search, user submission form for new data through online and also local BLAST search. CONCLUSION: This database, besides serving as a storehouse of sequences that may have diagnostic or therapeutic utility in medicine, provides valuable information for computational and theoretical biologists. The RiboaptDB is extremely useful for garnering information about in vitro selection experiments as a whole and for better understanding the distribution of functional nucleic acids in sequence space. The database is updated regularly and is publicly available at http://mfgn.usm.edu/ebl/riboapt/.

Aptamers, Nucleotide↗