Biology subjects

Harlapur, P.

Publications and source records attributed to Harlapur, P..

4 recordsLinked to original sources

bioRxiv2023

Comparative Analysis of TG/CA Repeats in Sixteen Primate Genomes Reveals the Dynamics and Role of TG/CA Repeats in the Human Genome

Among the different microsatellite sequences found in the human genome, the dinucleotide TG/CA repeats are one of the most abundant, exhibiting multifaceted functional roles. Availability of several primate genomes offers relevant datasets for studying the evolution and function of these repeats in non-human primates and human genome. Using pairwise genomic alignments, genome-wide analysis of these repeats was performed in human and sixteen other primate genomes. The total number of these repeats and expansion of medium (12[≤] n< 23) and long (n[≥]23) (TG/CA)n repeats was significantly higher in human than other primates. Further, other dinucleotide repeats like TA were found in the orthologous genomic regions in other primates. Thus, selection, elongation and a selective process of conversion of other dinucleotide repeats in primates to TG/CA repeats in humans was apparent and presented in this study as a comprehensive model for the dynamics and role of TG/CA repeats in the human genome.

genomics↗

bioRxiv2023

Low dimensionality of phenotypic space as an emergent property of coordinated teams in biological regulatory networks

Biological networks driving cell-fate decisions involve complex interactions, but they often give rise to only a few phenotypes, thus exhibiting low-dimensional dynamics. The network design principles that govern such cell-fate canalization remain unclear. Here, we investigate networks across diverse biological contexts- Epithelial-Mesenchymal Transition, Small Cell Lung Cancer, and Gonadal cell-fate determination - to reveal that the presence of two mutually antagonistic, well-coordinated teams of nodes leads to low-dimensional phenotypic space such that the first principal component (PC1) axis can capture most of the variance. Further analysis of artificial team-based networks and random counterparts of biological networks reveals that the principal component decomposition is determined by the team strength within these networks, demonstrating how the underlying network structure governs PC1 variance. The presence of low dimensionality in corresponding transcriptomic data confirms the applicability of our observations. We propose that team-based topology in biological networks are critical for generating a cell-fate canalization landscape.

systems biology↗

bioRxiv2022

Functional resilience of mutually repressing motifs embedded in larger regulatory networks

Elucidating the design principles of regulatory networks driving cellular decision-making has important implications in understanding cell differentiation and guiding the design of synthetic circuits. Mutually repressing feedback loops between master regulators of cell-fates can exhibit multistable dynamics, thus enabling multiple "single-positive" phenotypes: (high A, low B) and (low A, high B) for a toggle switch, and (high A, low B, low C), (low A, high B, low C) and (low A, low B, high C) for a toggle triad. However, the dynamics of these two network motifs has been interrogated in isolation in silico, but in vitro and in vivo, they often operate while embedded in larger regulatory networks. Here, we embed these network motifs in complex larger networks of varying sizes and connectivity and identify conditions under which these motifs maintain their canonical dynamical behavior, thus identifying hallmarks of their functional resilience. We show that an increased number of incoming edges onto a motif leads to a decay in their canonical stand-alone behaviors, as measured by multiple metrics based on pairwise correlation among nodes, bimodality of individual nodes, and the fraction of "single-positive" states. We also show that this decay can be exacerbated by adding self-inhibition, but not self-activation, loops on the master regulators. These observations offer insights into the design principles of biological networks containing these motifs, and can help devise optimal strategies for integration of these motifs into larger synthetic networks.

systems biology↗

bioRxiv2021

Emergent properties of coupled bistable switches

Understanding the dynamical hallmarks of network motifs is one of the fundamental aspects of systems biology. Positive feedback loops constituting one or two nodes - self-activation, toggle switch, and double activation loops - are commonly observed motifs in regulatory networks underlying cell-fate decision systems. Their individual dynamics are well-studied; they are capable of exhibiting bistability. However, studies across various biological systems suggest that such positive feedback loops are interconnected with one another, and design principles of coupled bistable motifs remain unclear. We wanted to ask what happens to bistability or multistability traits and the phenotypic space (collection of phenotypes exhibited by a system) due to the couplings. In this study, we explore a set of such interactions using discrete and continuous simulation methods. Our results suggest that couplings that do not connect the bistable switches in a way that contradicts the connections within individual bistable switches lead to a steady state space that is strictly a subset of the set of possible combinations of steady states of bistable switches. Furthermore, adding direct and indirect self-activations to these coupled networks can increase the frequency of multistability. Thus, our observations reveal specific dynamical traits exhibited by various coupled bistable motifs.

systems biology↗