Biology subjects

Manjunath, M.

Publications and source records attributed to Manjunath, M..

10 recordsLinked to original sources

bioRxiv2025

KLF5 controls subtype-independent highly interactive enhancers in pancreatic cancer to regulate cell survival

Pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal cancer with a 5-year survival rate of 13%. Despite recent molecular stratification of tumors into distinct classical and basal-like cell states, most tumors are heterogeneous contain of both subtypes. Therefore, therapeutic approaches targeting one subtype may not be suitable for PDAC therapy. Here, we integrated chromatin accessibility (ATAC-seq), genome-wide occupancy (ChIP-seq) for epigenetic status (H3K27ac) and H3K4me3-anchored chromatin topology (HiChIP) to uncover subtype-independent highly interactive enhancers that interact with essential genes in PDAC. Motif analysis revealed these common enhancers were bound by KLF5 with subsequent depletion leading to decreased cell viability via induction of apoptosis. To elucidate the transcriptional and epigenetic mechanisms by which KLF5 functions in PDAC, we employed rapid depletion of KLF5 with dTAG technology and profiled the effects on the open and active chromatin landscape and transcription with nascent RNA and mRNA-seq over time. Enhancer inactivation via KRAB domain Zim3-dCas9 fusion protein confirmed KLF5-bound enhancers regulate target genes, including the anti-apoptotic gene BCL2L1. Multiplex immunofluorescence confirmed co-staining of KLF5 and Bcl-xL in patient samples and overexpression of Bcl-xL rescued the induction of apoptosis after KLF5 depletion. Taken together, this study provides new insights into common mechanisms to target highly heterogeneous PDAC tumors. TeaserKLF5 controls subtype-independent highly interactive enhancers to regulate cell viability in pancreatic cancer.

cancer biology↗

bioRxiv2025

Unraveling Tyrosine-Kinase Inhibitor Resistance in NSCLC Cells via Same-cell Measurement of RNA, Protein, and Morphological Responses

Non-small cell lung cancer (NSCLC) frequently develops resistance to tyrosine kinase inhibitors (TKIs), limiting the long-term success of targeted therapies. A deeper understanding of resistance mechanisms at the molecular and cellular levels may enable the development of more effective treatment strategies. Here, we applied the Teton detection assay on the AVITI24 platform to measure concurrently RNA, protein, and cellular morphology in NSCLC cell lines treated with the TKIs gefitinib and osimertinib. This single-cell, multiomic analysis revealed distinct expression and morphological profiles between drug-sensitive and resistant cells, including differences in MAPK-related pathway activity. Stratifying responses at the single-cell level uncovered subtle responses not detectable in bulk measurements. We identified CDK4/6 activity as a route of cell survival under TKI treatment and demonstrated that co-treatment with the CDK4/6 inhibitor palbociclib enhanced TKI efficacy. The ability to measure multiomics and cellular morphology in the same cells opens new avenues for future studies aimed at improving personalized treatment strategies in NSCLC and overcoming the obstacles posed by drug resistance.

genomics↗

bioRxiv2024

Genomic prediction of cereal crop architecture traits using models informed by gene regulatory circuitries from maize

Plant architecture is a major determinant of planting density, which enhances productivity potential for crops per unit area. Genomic prediction is well-positioned to expedite genetic gain of plant architecture traits since they are typically highly heritable. Additionally, the adaptation of genomic prediction models to query predictive abilities of markers tagging certain genomic regions could shed light on the genetic architecture of these traits. Here, we leveraged transcriptional networks from a prior study that contextually described developmental progression during tassel and leaf organogenesis in maize (Z. mays) to inform genomic prediction models for architecture traits. Since these developmental processes underlie tassel branching and leaf angle, two important agronomic architecture traits, we tested whether genes prioritized from these networks quantitatively contribute to the genetic architecture of these traits. We used genomic prediction models to evaluate the ability of markers in the vicinity of prioritized network genes to predict breeding values of tassel branching and leaf angle traits for two diversity panels in maize, and diversity panels from sorghum (S. bicolor) and rice (O. sativa). Predictive abilities of markers near these prioritized network genes were similar to those using whole-genome marker sets. Notably, markers near highly connected transcription factors from core network motifs in maize yielded predictive abilities that were significantly greater than expected by chance in not only maize but also closely related sorghum. We expect that these highly connected regulators are key drivers of architectural variation that are conserved across closely related cereal crop species. Article summaryWe used an approach typically used for breeding to infer the contributions of biological gene networks to plant architectural traits. We found that markers near genes belonging to smaller, specialized gene networks from maize could predict breeding values of leaf angle better than expected by chance for both maize and sorghum.

genetics↗

bioRxiv2024

Mechanosensory cephalic bristles mediate rapid flight initiation in endothermic hawkmoths

Endothermic insects including bees, butterflies, and moths need to warm up their flight muscles before taking flight. For instance, diurnal butterflies bask in the sun to heat their flight muscles, whereas nocturnal hawkmoths display a pre-flight shivering behavior in which small-amplitude wing movements cause flight muscles to warm up, eventually generating large-amplitude wing motion for flight. The time required for warm-up puts such insects at a considerable risk if they need to rapidly escape from predators. Here, we show that upon experiencing a sudden air-puff on the head, hawkmoths rapidly initiate flight bypassing the pre-flight shivering phase. This response is mediated by mechanosensory cephalic bristles that are buried under the scales on their head. Cephalic bristle mediated flight entails a stereotypic triggering of various flight-related reflexes including antennal positioning, foreleg extension, wing movement, and abdominal flexion. Some mechanosensory neurons underlying cephalic bristles arborize in the subesophageal zone (SEZ) and antennal motor and mechanonsensory center (AMMC), whereas most arborize in pro-, meso- and meta-thoracic ganglia which contain the motor circuitry for foreleg motion, flight, and abdominal flexion. Thermal recordings revealed that large-amplitude wing motion following cephalic bristle-stimulation occurs at lower thoracic temperatures than required for voluntary flight. Electromyogram recordings from steering and indirect flight muscles show significant variability in activation latency in response to cephalic bristle stimulus. The range of latency values among different muscles overlaps, suggesting that cephalic bristle stimulation activates steering muscles, thereby generating high-amplitude wing movement at lower thoracic temperatures. Concomitant activation of the indirect flight muscles initiates thoracic warm-up in preparation for longer flight. Thus, akin to locusts, the cephalic bristle system in hawkmoths rapidly triggers flight upon sensing danger, ensuring swift escape from potential threats.

neuroscience↗

bioRxiv2022

A comprehensive study of mRNA and long noncoding RNAs in Indian Breast cancer patients using transcriptomics approach

BackgroundBreast cancer (BC) is one of the leading causes of cancer-associated death in women. Despite the progress in therapeutic regimen, resistance and recurrence of Breast cancer have impacted Overall Survival. Transcriptomic profiling of tumour samples has led to identifying subtype-specific differences, identifying biomarkers, and designing therapeutic strategies. Although there are multiple transcriptomic studies on breast cancer patients from different geographical regions, a comprehensive study on long noncoding RNA (lncRNA) and mRNA in Indian Breast cancer patients in multiple subtypes are very limited. This study aims to understand the subtype-specific alterations and mRNA-lncRNA gene sets. MethodWe have performed transcriptome analysis of 17 Indian breast cancer patients and matched normal belonging to 6 different subtypes, i.e., four patients in triple positive, three patients in estrogen receptor-positive (ER+ve), three patients in estrogen and progesterone receptor-positive (ER+ve, PR+ve), two patients in Human epidermal growth factor receptor (Her2+ve), three patients in triple-negative and one patient in ER+ve and Her2 +ve subtypes. Hierarchical clustering and principal component analysis were performed using R packages to derive gene sets. Univariate and multivariate Cox analyses were performed for survival analysis. ResultsmRNA and lncRNA expression profiles segregated Indian Breast cancer subtypes with minimum overlap. We have identified a 25mRNA-27 lncRNA gene set, which displayed proper segregation of the subtypes in our data. The same gene set also segregated premenopausal women samples in The Cancer Genome Atlas (TCGA) data. Pathway analysis of the differentially expressed genes revealed unique pathways for premenopausal and postmenopausal women. Kaplan-Meier survival analysis revealed menopausal status, grade of the tumour, and hormonal status displayed statistically significant effects (p < 0.05) on the risk of mortality due to breast cancer. Her2+ve patients showed low overall survival ConclusionThis is the first study describing subtype-specific mRNA and lncRNA gene expression in Indian Breast Cancer patients with unique pathway signatures for premenopausal and postmenopausal breast cancer patients. Additionally, our data identified an mRNA-lncRNA gene set that could segregate pre and postmenopausal women with Breast Cancer. Although the sample size is small, results from this study could be a foundation that could be validated further in a larger dataset to establish an mRNA-lncRNA signature specific to the Indian population which might, in turn, improve therapeutic decisions.

bioinformatics↗

bioRxiv2021

Leveraging epigenomes and three-dimensional genome organization for interpreting regulatory variation

Understanding the impact of regulatory variants on complex phenotypes is a significant challenge because the genes and pathways that are targeted by such variants are typically unknown. Furthermore, a regulatory variant might influence a particular genes expression in a cell type or tissue-specific manner. Cell-type specific long-range regulatory interactions that occur between a distal regulatory sequence and a gene offers a powerful framework for understanding the impact of regulatory variants on complex phenotypes. However, high-resolution maps of such long-range interactions are available only for a handful of model cell lines. To address this challenge, we have developed L-HiC-Reg, a Random Forests based regression method to predict high- resolution contact counts in new cell lines, and a network-based framework to identify candidate cell line-specific gene networks targeted by a set of variants from a Genome-wide association study (GWAS). We applied our approach to predict interactions in 55 Roadmap Epigenome Consortium cell lines, which we used to interpret regulatory SNPs in the NHGRI GWAS catalogue. Using our approach, we performed an in-depth characterization of fifteen different phenotypes including Schizophrenia, Coronary Artery Disease (CAD) and Crohns disease. In CAD, we found differentially wired subnetworks consisting of known as well as novel gene targets of regulatory SNPs. Taken together, our compendium of interactions and associated network-based analysis pipeline offers a powerful resource to leverage long-range regulatory interactions to examine the context-specific impact of regulatory variation in complex phenotypes.

bioinformatics↗

bioRxiv2021

Unleashing a Novel Function of Endonuclease G in Mitochondrial Genome Instability

Having its own genome makes mitochondria a unique and semiautonomous organelle within cells. Mammalian mitochondrial DNA (mtDNA) is double-stranded closed circular molecule of about 16 kb coding 37 genes. Mutations, including deletions in the mitochondrial genome can culminate in different human diseases. Mapping of the deletion junctions suggests that the breakpoints are generally seen at hotspots. 9-bp deletion (8271-8281), seen in the intergenic region of cytochrome c oxidase II/tRNALys, is the most common mitochondrial deletion. While it is associated with several diseases like myopathy, dystonia, and hepatocellular carcinoma, it has also been used as an evolutionary marker. However, the mechanism responsible for its fragility is unclear. In the current study, we show that Endonuclease G, a mitochondrial nuclease responsible for nonspecific cleavage of nuclear DNA during apoptosis, can induce breaks at sequences associated with 9-bp deletion, when it is present on a plasmid or in the mitochondrial genome. Through a series of in vitro and intracellular studies, we show that Endonuclease G binds to G-quadruplex structures formed at the hotspot and induces DNA breaks. Besides, we reconstitute the whole process of 9-bp deletion using purified Endonuclease G to induce breaks in mtDNA, followed by mitochondrial extract-mediated DSB repair and establish that microhomology-mediated end joining is responsible for the generation of mtDNA deletion. Finally, we show that the whole process is regulated by different stress conditions, which may modulate release of Endonuclease G to the mitochondrial matrix. Therefore, we uncover a new role for Endonuclease G in generating deletions, which is dependent on the formation of G4 DNA within the mitochondrial genome. Thus, in this study we identify a novel property of Endonuclease G, besides its role in apoptosis, and the recently described elimination of paternal mitochondria during fertilization.

molecular biology↗

bioRxiv2018

Can cancer GWAS variants modulate immune cells in the tumor microenvironment?

Genome-wide association studies (GWAS) have hitherto identified several genetic variants associated with cancer susceptibility, but the molecular functions of these risk modulators remain largely uncharacterized. Recent studies have begun to uncover the regulatory potential of non-coding GWAS SNPs by using epigenetic information in corresponding cancer cell types and matched normal tissues. However, this approach does not explore the potential effect of risk germline variants on other important cell types that constitute the microenvironment of tumor or its precursor. This paper presents evidence that the breast cancer-associated variant rs3903072 may regulate the expression of CTSW in tumor infiltrating lymphocytes. CTSW is a candidate tumor-suppressor gene, with expression highly specific to immune cells and also positively correlated with breast cancer patient survival. Integrative analyses suggest a putative causative variant in a GWAS-linked enhancer in lymphocytes that loops to the 3 end of CTSW through three-dimensional chromatin interaction. Our work thus poses the possibility that a cancer-associated genetic variant might regulate a gene not only in the cell of cancer origin, but also in immune cells in the microenvironment, thereby modulating the immune surveillance by T lymphocytes and natural killer cells and affecting the clearing of early cancer initiating cells.

cancer biology↗

bioRxiv2018

SequencEnG: an Interactive Knowledge Base of Sequencing Techniques

Next-generation sequencing (NGS) techniques are revolutionizing biomedical research by providing powerful methods for generating genomic and epigenomic profiles. The rapid progress is posing an acute challenge to students and researchers to stay acquainted with the numerous available methods. We have developed an interactive online educational resource called SequencEnG (acronym for Sequencing Techniques Engine for Genomics) to provide a tree-structured knowledge base of 66 different sequencing techniques and step-by-step NGS data analysis pipelines comparing popular tools. SequencEnG is designed to facilitate barrier-free learning of current NGS techniques and provides a user-friendly interface for searching through experimental and analysis methods. SequencEnG is part of the project KnowEnG (Knowledge Engine for Genomics) and is freely available at http://education.knoweng.org/sequenceng/.

bioinformatics↗

bioRxiv2017

ClusterEnG: An interactive educational web resource for clustering big data

SummaryClustering is one of the most common techniques used in data analysis to discover hidden structures by grouping together data points that are similar in some measure into clusters. Although there are many programs available for performing clustering, a single web resource that provides both state-of-the-art clustering methods and interactive visualizations is lacking. ClusterEnG (acronym for Clustering Engine for Genomics) provides an interface for clustering big data and interactive visualizations including 3D views, cluster selection and zoom features. ClusterEnG also aims at educating the user about the similarities and differences between various clustering algorithms and provides clustering tutorials that demonstrate potential pitfalls of each algorithm. The web resource will be particularly useful to scientists who are not conversant with computing but want to understand the structure of their data in an intuitive manner.\n\nAvailabilityClusterEnG is part of a bigger project called KnowEnG (Knowledge Engine for Genomics) and is available at http://education.knoweng.org/clustereng.\n\nContactsongi@illinois.edu

bioinformatics↗