Biology subjects

Sandhu, R.

Publications and source records attributed to Sandhu, R..

6 recordsLinked to original sources

bioRxiv2025

Conserved and Unique Features of Terminal Telomeric Sequences in ALT-Positive Cancer Cells

A significant portion of human cancers utilize a recombination-based pathway, Alternative Lengthening of Telomeres (ALT), to maintain telomere length. Targeting the ALT is of growing interest as a cancer therapy, yet a substantial knowledge gap remains regarding the basic features of telomeres in ALT-positive cells. To address this, we adopted END-seq, an unbiased sequencing-based approach, to define the identity and regulation of the terminal sequences of chromosomes in ALT cells. Our data reveal that the terminal portions of chromosomes in ALT cells contain canonical telomeric sequences with the same 5 terminus bias (-ATC) observed in non-ALT cells. Furthermore, as reported for non-ALT cells, POT1 is required to preserve the precise regulation of the 5 end in cells that maintain telomere length using the ALT pathway. Thus, the regulation of the terminal 5 of chromosomes occurs independently of the mechanism of telomere elongation. Additionally, we employed an S1 endonuclease-based sequencing method to determine the presence and origin of single-stranded regions within ALT telomeres. These data shed light on conserved and unique features of ALT telomeres.

molecular biology↗

bioRxiv2024

Temporal and Functional Relationship between Synaptonemal Complex Morphogenesis and Recombination during Meiosis

During prophase of meiosis I, programmed double strand breaks (DSBs) are processed into crossovers, a critical requirement for segregation of homologous chromosomes (homologs) and genome haploidization in sexually reproducing organisms. Crossovers form via homologous recombination in close temporospatial association with morphogenesis of the synaptonemal complex (SC), a proteinaceous structure that connects paired homologs along their length during the pachytene stage. Synapsis and recombination are a paradigm for the interplay between higher order chromosome structure and DNA metabolism, yet their temporal and functional relationship remains poorly understood. Probing linkage between these processes in budding yeast, we show that SC assembly is associated with a distinct threshold number of unstable D-loops. The transition from bona fide paranemic D-loops to plectonemic DSB single end invasions (SEIs) is completed during midpachynema, when the SC is fully assembled. Double Holliday junctions (dHJs) form at the time of desynapsis and are resolved into crossovers during diplonema. The SC central element component Zip1 shepherds recombination through three transitions, including DSB first end strand exchange and second end capture, as well as dHJ resolution. Zip1 mediates SEI formation independent of its polymerization whereas precocious Zip1 assembly interferes with double Holliday junction resolution. Together, our findings indicate that the synaptonemal complex controls recombination while assembled but also beyond its disassembly, possibly by establishing spatial constraints at recombination sites.

genetics↗

bioRxiv2022

Emergent low-frequency activity in cortico-cerebellar networks with motor skill learning

The motor cortex controls skilled arm movement by recruiting a variety of targets in the nervous system, and it is important to understand the emergent activity in these regions as refinement of a motor skill occurs. One fundamental projection of the motor cortex is to the cerebellum. However, the emergent activity in the motor cortex and the cerebellum that appears as a dexterous motor skill is consolidated is incompletely understood. Here, we report on low-frequency oscillatory (LFO) activity that emerges in cortico-cerebellar networks with learning the reach-to-grasp motor skill. We chronically recorded the motor and the cerebellar cortices in rats which revealed the emergence of coordinated movement-related activity in the local-field potentials (LFPs) as the reaching skill consolidated. We found that the local and cross-area spiking activity was coordinated with LFOs. Finally, we also found that these neural dynamics were more prominently expressed during accurate behavior. This work furthers our understanding on emergent dynamics in the cortico-cerebellar loop that underlie learning and execution of precise skilled movement.

neuroscience↗

bioRxiv2022

Beyond Pairwise Interactions: Higher-Order Dynamics in Protein Interaction Networks

Protein interactions form a complex dynamic system that shapes cell phenotype and function; in this regard, network analysis is a powerful tool for studying the dynamics of cellular processes. Graph-based models are limited, however, in that these models consider only pairwise relationships. Higher-order interactions are well-characterized in biology, including protein complex formation and feedback or feedforward loops. These higher-order relationships are better represented by a hypergraph as a generalized network model. Here, we present an approach to analyzing dynamic gene expression data using a hypergraph model and quantify network heterogeneity via Forman-Ricci curvature. We observe, on a global level, increased network curvature in pluripotent stem cells and cancer cells. Further, we use local curvature to conduct pathway analysis in a melanoma dataset, finding increased curvature in several oncogenic pathways and decreased curvature in tumor suppressor pathways. We compare this approach to a graph-based model and a differential gene expression approach.

systems biology↗

bioRxiv2021

Quantifying Cellular Pluripotency and Pathway Robustness through Forman-Ricci Curvature

In stem cell biology, cellular pluripotency describes the capacity of a given cell to differentiate into multiple cell types. From a statistical physics perspective, entropy provides a statistical measure of randomness and has been demonstrated as a way to quantitate pluripotency when considering biological gene networks. Furthermore, recent theoretical work has established a relationship between Ricci curvature (a geometric measure of "flatness") and entropy (also related to robustness), which one can exploit to link the geometric quantity of curvature to the statistical quantity of entropy. Therefore, this study seeks to explore Ricci curvature in biological gene networks as a descriptor of pluripotency and robustness among gene pathways. Here, we investigate Forman-Ricci curvature, a combinatorial discretization of Ricci curvature, along with network entropy, to explore the relationship of the two quantities as they occur in gene networks. First, we demonstrate our approach on an experiment of stem cell gene expression data. As expected, we find Ricci curvature directly correlates with network entropy, suggesting Ricci curvature could serve as an indicator for cellular pluripotency much like entropy. Second, we measure Forman-Ricci curvature in a dataset of cancer and non-cancer cells from melanoma patients. We again find Ricci curvature is increased in the cancer state, reflecting increased pluripotency or "stemness". Further, we locally examine curvature on the gene level to identify several genes and gene pathways with known relevance to melanoma. In turn, we conclude Forman-Ricci curvature provides valuable biological information related to pluripotency and pathway functionality. In particular, the advantages of this geometric approach are promising for extension to higher-order topological structures in order to represent more complex features of biological systems.

systems biology↗

bioRxiv2017

Pediatric Sarcoma Data Forms a Unique Cluster Measured via the Earth Mover’s Distance

In this note, we combined pediatric sarcoma data from Columbia University with adult sarcoma data collected from TCGA, in order to see if one can automatically discern a unique pediatric cluster in the combined data set. Using a novel clustering pipeline based on optimal transport theory, this turned out to be the case. The overall methodology may find uses for the classification of data from other biological networking problems.

cancer biology↗