Biology subjects

Siddharthan, R.

Publications and source records attributed to Siddharthan, R..

9 recordsLinked to original sources

bioRxiv2023

Position-specific evolution in transcription factor binding sites, and a fast likelihood calculation for the F81 model

Transcription factor binding sites (TFBS), like other DNA sequence, evolve via mutation and selection relating to their function. Models of nucleotide evolution describe DNA evolution via single-nucleotide mutation. A stationary vector of such a model is the long-term distribution of nucleotides, unchanging under the model. Neutrally evolving sites may have uniform stationary vectors, but one expects that sites within a TFBS instead have stationary vectors reflective of the fitness of various nucleotides at those positions. We introduce "position-specific stationary vectors" (PSSVs), the collection of stationary vectors at each site in a TFBS locus, analogous to the position weight matrix (PWM) commonly used to describe TFBS. We infer PSSVs for human TFs using two evolutionary models (Felsenstein 1981 and Hasegawa-Kishino-Yano 1985). We find that PSSVs reflect the nucleotide distribution from PWMs, but with reduced specificity. We infer ancestral nucleotide distributions at individual positions and calculate "conditional PSSVs" conditioned on specific choices of majority ancestral nucleotide. We find that certain ancestral nucleotides exert a strong evolutionary pressure on neighbouring sequence while others have a negligible effect. Finally, we present a fast likelihood calculation for the F81 model on moderate-sized trees that makes this approach feasible for large-scale studies along these lines.

evolutionary biology↗

bioRxiv2022

Transcription factors organize into functional groups on the linear genome and in 3D chromatin

Transcription factors (TFs) and their binding sites have evolved to interact cooperatively or competitively with each other. Here we examine in detail, across multiple cell lines, such cooperation or competition among TFs both in sequential and spatial proximity (using chromatin conformation capture assays) on one hand, and based on both in vivo binding as well as TF binding motifs on the other. We ascertain significantly co-occurring ("attractive") or avoiding ("repulsive") TF pairs using robust randomized models that retain the essential characteristics of the experimental data. Across human cell lines TFs organize into two groups, with intra-group attraction and inter-group repulsion. This is true for both sequential and spatial proximity, as well as for both in vivo binding and motifs. Attractive TF pairs exhibit significantly more physical interactions suggesting an underlying mechanism. The two TF groups differ significantly in their genomic and network properties, as well in their function--while one group regulates housekeeping function, the other potentially regulates lineage-specific functions, that are disrupted in cancer. We also show that weaker binding sites tend to occur in spatially interacting regions of the genome. Our results suggest a complex pattern of spatial cooperativity of TFs that has evolved along with the genome to support housekeeping and lineage-specific functions.

genomics↗

bioRxiv2021

Functional and comparative genome analysis reveals clade-specific genome innovations in the killer fungus Candida auris

The thermotolerant multidrug-resistant ascomycete Candida auris rapidly emerged since 2009 and simultaneously evolved in different geographical zones worldwide, causing superficial as well as systemic infections. The molecular events that orchestrated this sudden emergence of the killer fungus remain mostly elusive. Here, we identify centromeres in C. auris and related species, using a combined approach of chromatin immunoprecipitation and comparative genomic analyses. We find that C. auris and multiple other species in the Clavispora/Candida clade shared a conserved small regional centromere landscape lacking pericentromeres. Further, a centromere inactivation event led to karyotypic alterations in this species complex. Inter-species genome analysis identified several structural chromosomal changes around centromeres. In addition, centromeres are found to be rapidly evolving loci among the different geographical clades of the same species of C. auris. Finally, we reveal an evolutionary trajectory of the unique karyotype associated with clade 2 that consists of the drug susceptible isolates of C. auris.

genomics↗

bioRxiv2020

Altered kinetics of circulating progenitor cells in cardiopulmonary bypass (CPB) associated vasoplegic patients: An observational study

Vasoplegia observed post cardiopulmonary bypass (CPB) is associated with substantial morbidity, multiple organ failure and mortality. Circulating counts of hematopoietic stem cells (HSCs) and endothelial progenitor cells (EPC) are potential markers of neo-vascularization and vascular repair. However, the significance of changes in the circulating levels of these progenitors in perioperative CPB, and their association with post-CPB vasoplegia, are currently unexplored. We enumerated HSC and EPC counts, via flow cytometry, at different time-points during CPB in 19 individuals who underwent elective cardiac surgery. These 19 individuals were categorized into two groups based on severity of post-operative vasoplegia, a clinically insignificant vasoplegic Group 1 (G1) and a clinically significant vasoplegic Group 2 (G2). Differential changes in progenitor cell counts during different stages of surgery were compared across these two groups. Machine-learning classifiers (logistic regression and gradient boosting) were employed to determine if differential changes in progenitor counts could aid the classification of individuals into these groups. Enumerating progenitor cells revealed an early and significant increase in the circulating counts of CD34+ and CD34+CD133+ hematopoietic stem cells (HSC) in G1 individuals, while these counts were attenuated in G2 individuals. Additionally, EPCs (CD34+VEGFR2+) were lower in G2 individuals compared to G1. Gradient boosting outperformed logistic regression in assessing the vasoplegia grouping based on the fold change in circulating CD 34+ levels. Our findings indicate that a lack of early response of CD34+ cells and CD34+CD133+ HSCs might serve as an early marker for development of clinically significant vasoplegia after CPB.

physiology↗

bioRxiv2019

Centromere-mediated chromosome break drives karyotype evolution in closely related Malassezia species

Intra-chromosomal or inter-chromosomal genomic rearrangements often lead to speciation (1). Loss or gain of a centromere leads to alterations in chromosome number in closely related species. Thus, centromeres can enable tracing the path of evolution from the ancestral to a derived state (2). The Malassezia species complex of the phylum Basiodiomycota shows remarkable diversity in chromosome number ranging between six and nine chromosomes (3-5). To understand these transitions, we experimentally identified all eight centromeres as binding sites of an evolutionarily conserved outer kinetochore protein Mis12/Mtw1 in M. sympodialis. The 3 to 5 kb centromere regions share an AT-rich, poorly transcribed core region enriched with a 12 bp consensus motif. We also mapped nine such AT-rich centromeres in M. globosa and the related species Malassezia restricta and Malassezia slooffiae. While eight predicted centromeres were found within conserved synteny blocks between these species and M. sympodialis, the remaining centromere in M. globosa (MgCEN2) or its orthologous centromere in M. slooffiae (MslCEN4) and M. restricta (MreCEN8) mapped to a synteny breakpoint compared with M. sympodialis. Taken together, we provide evidence that breakage and loss of a centromere (CEN2) in an ancestral Malassezia species possessing nine chromosomes resulted in fewer chromosomes in M. sympodialis. Strikingly, the predicted centromeres of all closely related Malassezia species map to an AT-rich core on each chromosome that also shows enrichment of the 12 bp sequence motif. We propose that centromeres are fragile AT-rich sites driving karyotype diversity through breakage and inactivation in these and other species. Significance statementThe number of chromosomes can vary between closely related species. Centromere loss destabilizes chromosomes and results in reduced number of chromosomes to drive speciation. A series of evidence from studies on various cancers suggest that an imbalance in kinetochore-microtubule attachments results in breaks at the centromeres. To understand if such events can cause chromosome number changes in nature, we studied six species of Malassezia, of which three possess eight chromosomes and others have nine chromosomes each. We find signatures of chromosome breakage at the centromeres in organisms having nine chromosomes. We propose that the break at the centromere followed by fusions of acentric chromosomes to other chromosomes could be a plausible mechanism shaping the karyotype of Malassezia and related organisms. ClassificationBiological sciences, Genetics

genomics↗

bioRxiv2018

ChIPulate : A comprehensive ChIP-seq simulation pipeline

ChIP-seq (Chromatin Immunoprecipitation followed by sequencing) is a high-throughput technique to identify genomic regions that are bound in vivo by a particular protein, e.g., a transcription factor (TF). Biological factors, such as chromatin state, indirect and cooperative binding, as well as experimental factors, such as antibody quality, cross-linking, and PCR biases, are known to affect the outcome of ChIP-seq experiments. However, the relative impact of these factors on inferences made from ChIP-seq data is not entirely clear. Here, via a detailed ChIP-seq simulation pipeline, ChIPulate, we assess the impact of various biological and experimental sources of variation on several outcomes of a ChIP-seq experiment, viz., the recoverability of the TF binding motif, accuracy of TF-DNA binding detection, the sensitivity of inferred TF-DNA binding strength, and number of replicates needed to confidently infer binding strength. We find that the TF motif can be recovered despite poor and non-uniform extraction and PCR amplification efficiencies. The recovery of the motif is however affected to a larger extent by the fraction of sites that are either cooperatively or indirectly bound. Importantly, our simulations reveal that the number of ChIP-seq replicates needed to accurately measure in vivo occupancy at high-affinity sites is larger than the recommended community standards. Our results establish statistical limits on the accuracy of inferences of protein-DNA binding from ChIP-seq and suggest that increasing the mean extraction efficiency, rather than amplification efficiency, would better improve sensitivity. The source code and instructions for running ChIPulate can be found at https://github.com/vishakad/chipulate.

bioinformatics↗

bioRxiv2018

DNA replication initiator proteins facilitate CENPA loading on early replicating compact chromatin

Spatiotemporal regulation in DNA replication maintains kinetochore stability. The epigenetically regulated centromeres (CENs) in the budding yeast Candida albicans have unique DNA sequences, replicate early and are clustered throughout the cell cycle. In this study, the genome-wide occupancy of replication initiation protein Orc4 reveals its abundance at all CENs in C. albicans. Orc4 associates with four different DNA motifs, one of which coincides with tRNA genes. Hi-C combined with genome-wide replication timing analyses identify enriched interactions among early or late replicating Orc4-bound regions. A simulated polymer model of chromosomes reveals that early replicating and strongly enriched Orc4-bound sites localize towards the kinetochores. Orc4 is constitutively localized to CENs, and both Orc4 and Mcm2 stabilize CENPA. CENPA chaperone Scm3 localizes at the kinetochore during anaphase, coinciding with the loading time of CENPA. We propose that this spatiotemporal nuclear localization of Orc4, with Mcm2 and Scm3, recruits CENPA and stabilizes centromeric chromatin.

molecular biology↗

bioRxiv2017

Detection Of Cooperatively Bound Transcription Factor Pairs Using ChIP-seq Peak Intensities And Expectation Maximization

Transcription factors (TFs) often work cooperatively, where the binding of one TF to DNA enhances the binding affinity of a second TF to a nearby location. Such cooperative binding is important for activating gene expression from promoters and enhancers in both prokaryotic and eukaryotic cells. Existing methods to detect cooperative binding of a TF pair rely on analyzing the sequence that is bound. We propose a method that uses, instead, only ChIP-seq peak intensities and an expectation maximization (CPI-EM) algorithm. We validate our method using ChIP-seq data from cells where one of a pair of TFs under consideration has been genetically knocked out. Our algorithm relies on our observation that cooperative TF-TF binding is correlated with weak binding of one of the TFs, which we demonstrate in a variety of cell types, including E. coli, S. cerevisiae and M. musculus cells. We show that this method performs significantly better than a predictor based only on the ChIP-seq peak distance of the TFs under consideration. This suggests that peak intensities contain information that can help detect the cooperative binding of a TF pair. CPI-EM also outperforms an existing sequence-based algorithm in detecting cooperative binding. The CPI-EM algorithm is available at https://github.com/vishakad/cpi-em.

genomics↗

bioRxiv2017

THiCweed: fast, sensitive motif finding by clustering big data sets

We present THiCweed, a new approach to analyzing transcription factor binding data from high-throughput chromatin-immunoprecipitation-sequencing (ChIP-seq) experiments. THiCweed clusters bound regions based on sequence similarity using a divisive hierarchical clustering approach based on sequence similarity within sliding windows, while exploring both strands. ThiCweed is specially geared towards data containing mixtures of motifs, which present a challenge to traditional motif-finders. Our implementation is significantly faster than standard motif-finding programs, able to process 30,000 peaks in 1-2 hours, on a single CPU core of a desktop computer. On synthetic data containing mixtures of motifs it is as accurate or more accurate than all other tested programs.\n\nTHiCweed performs best with large \"window\" sizes ([≥] 50bp), much longer than typical binding sites (7-15 base pairs). On real data it successfully recovers literature motifs, but also uncovers complex sequence characteristics in flanking DNA, variant motifs, and secondary motifs even when they occur in < 5% of the input, all of which appear biologically relevant. We also find recurring sequence patterns across diverse ChIP-seq data sets, possibly related to chromatin architecture and looping. THiCweed thus goes beyond traditional motif-finding to give new insights into genomic TF binding complexity.

bioinformatics↗