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26 results on '"Sahadevan, Sudeep"'

1. Systematic analysis of RNA-binding proteins identifies targetable therapeutic vulnerabilities in osteosarcoma

Author

Zhou, Yang, Ray, Partho Sarothi, Zhu, Jianguo, Stein, Frank, Rettel, Mandy, Sekaran, Thileepan, Sahadevan, Sudeep, Perez-Perri, Joel I., Roth, Eva K., Myklebost, Ola, Meza-Zepeda, Leonardo A., von Deimling, Andreas, Fu, Chuli, Brosig, Annika N., Boye, Kjetil, Nathrath, Michaela, Blattmann, Claudia, Lehner, Burkhard, Hentze, Matthias W., and Kulozik, Andreas E.

Published
2024
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10. Small noncoding RNA interactome capture reveals pervasive, carbon source–dependent tRNA engagement of yeast glycolytic enzymes

Author

Asencio, Claudio, Schwarzl, Thomas, Sahadevan, Sudeep, and Hentze, Matthias W.

Abstract

Small noncoding RNAs fulfill key functions in cellular and organismal biology, typically working in concert with RNA-binding proteins (RBPs). While proteome-wide methodologies have enormously expanded the repertoire of known RBPs, these methods do not distinguish RBPs binding to small noncoding RNAs from the rest. To specifically identify this relevant subclass of RBPs, we developed small noncoding RNA interactome capture (snRIC2C) based on the differential RNA-binding capacity of silica matrices (2C). We define the S. cerevisiaeproteome of nearly 300 proteins that specifically binds to RNAs smaller than 200 nt in length (snRBPs), identifying informative distinctions from the total RNA-binding proteome determined in parallel. Strikingly, the snRBPs include most glycolytic enzymes from yeast. With further methodological developments using silica matrices, 12 tRNAs were identified as specific binders of the glycolytic enzyme GAPDH. We show that tRNA engagement of GAPDH is carbon source–dependent and regulated by the RNA polymerase III repressor Maf1, suggesting a regulatory interaction between glycolysis and RNA polymerase III activity. We conclude that snRIC2Cand other 2C-derived methods greatly facilitate the study of RBPs, revealing previously unrecognized interactions.

Published
2023
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12. Transcriptome profile of lung dendritic cells after in vitro porcine reproductive and respiratory syndrome virus (PRRSV) infection

Author

Pröll, Maren Julia, primary, Neuhoff, Christiane, additional, Schellander, Karl, additional, Uddin, Muhammad Jasim, additional, Cinar, Mehmet Ulas, additional, Sahadevan, Sudeep, additional, Qu, Xueqi, additional, Islam, Md. Aminul, additional, Poirier, Mikhael, additional, Müller, Marcel A., additional, Drosten, Christian, additional, Tesfaye, Dawit, additional, Tholen, Ernst, additional, and Große-Brinkhaus, Christine, additional

Published
2017
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13. Transcriptome profile of lung dendritic cells after in vitro porcine reproductive and respiratory syndrome virus (PRRSV) infection

Author

Pröll, Maren Julia, Neuhoff, Christiane, Schellander, Karl, Uddin, Muhammad Jasim, Cinar, Mehmet Ulas, Sahadevan, Sudeep, Qu, Xueqi, Islam, Aminul, Poirier, Mikhael, Müller, Marcel A., Drosten, Christian, Tesfaye, Dawit, Tholen, Ernst, Große-Brinkhaus, Christine, Pröll, Maren Julia, Neuhoff, Christiane, Schellander, Karl, Uddin, Muhammad Jasim, Cinar, Mehmet Ulas, Sahadevan, Sudeep, Qu, Xueqi, Islam, Aminul, Poirier, Mikhael, Müller, Marcel A., Drosten, Christian, Tesfaye, Dawit, Tholen, Ernst, and Große-Brinkhaus, Christine

Abstract

The porcine reproductive and respiratory syndrome (PRRS) is an infectious disease that leads to high financial and production losses in the global swine industry. The pathogenesis of this disease is dependent on a multitude of factors, and its control remains problematic. The immune system generally defends against infectious diseases, especially dendritic cells (DCs), which play a crucial role in the activation of the immune response after viral infections. However, the understanding of the immune response and the genetic impact on the immune response to PRRS virus (PRRSV) remains incomplete. In light of this, we investigated the regulation of the host immune response to PRRSV in porcine lung DCs using RNA-sequencing (RNA-Seq). Lung DCs from two different pig breeds (Pietrain and Duroc) were collected before (0 hours) and during various periods of infection (3, 6, 9, 12, and 24 hours post infection (hpi)). RNA-Seq analysis revealed a total of 20,396 predicted porcine genes, which included breed-specific differentially expressed immune genes. Pietrain and Duroc infected lung DCs showed opposite gene expression courses during the first time points post infection. Duroc lung DCs reacted more strongly and distinctly than Pietrain lung DCs during these periods (3, 6, 9, 12 hpi). Additionally, cluster analysis revealed time-dependent co-expressed groups of genes that were involved in immune-relevant pathways. Key clusters and pathways were identified, which help to explain the biological and functional background of lung DCs post PRRSV infection and suggest IL-1β1 as an important candidate gene. RNA-Seq was also used to characterize the viral replication of PRRSV for each breed. PRRSV was able to infect and to replicate differently in lung DCs between the two mentioned breeds. These results could be useful in investigations on immunity traits in pig breeding and enhancing the health of pigs.

Published
2017

15. Sahadevan, Sudeep

Author

Sahadevan, Sudeep and Sahadevan, Sudeep

Published
2016

16. Genomic analysis of water holding capacity of meat in a porcine resource population

Author

Becker, Astrid, Zimmer, Andreas, ÇINAR, Mehmet Ulaş, Tesfaye, Dawit, Tholen, Ernst, Heidt, Hanna, Sahadevan, Sudeep, Schellander, K., Grosse-Brinkhaus, Christine, and Looft, Christian

Abstract

In this study lean meat water-holding capacity (WHC) of a Duroc × Pietrain (DuPi) resource populations withcorresponding genotypes and transcriptomes were investigated using the approaches of genetical genomics.WHC was characterized by drip loss measured in M. long. dorsi. Genotypes of 169 F2 DuPi animals wereidentified by the 60k Illumina SNP chips. Whole genome tanscriptomes of muscle were available for 132F2 animals using the 24k Affymetrix expression microarray. Performing genome wide associations studies(GWAS) of transcriptional profiles which are correlated with phenotypes allows elucidating cis- and trans-regulation. Expression levels of 1,228 genes were significantly correlated with drip loss and were furtheranalyzed for enrichment of functional annotation groups as defined by gene ontology and KEGG pathways.A hyper geometric gene set enrichment test was performed and revealed glycolysis/glyconeogenesis, pentosephosphate pathway and pyruvat metabolism as most promising pathways. For 267 selected transcripts eQTLanalysis was performed and revealed 78,576 significant (Paccordance of the gene underlying transcript and the eQTL location it was possible to identify 59 eQTL thatcan be assumed to be cis-regulated. Comparing the results of gene set enrichment and the eQTL detectiontests molecular networks and potential candidate genes which seem to play key roles in the expression ofwater holding capacity were detected. One gene was the glucose-6-phosphate transporter SLC37A4 whichwas assumed to be cis-regulated and involved in the glucose metabolic process. This approach supports toidentify trait-associated SNPs and to understand the biology of complex traits.

Published
2013

17. Preliminary study of FMO1, FMO5, CYP21, ESR1, PLIN2 and SULT2A1 as candidate gene for compounds related to boar taint

Author

Neuhoff, Christiane, primary, Gunawan, Asep, additional, Farooq, Malik Omar, additional, Cinar, Mehmet Ulas, additional, Große-Brinkhaus, Christine, additional, Sahadevan, Sudeep, additional, Frieden, Luc, additional, Tesfaye, Dawit, additional, Tholen, Ernst, additional, Looft, Christian, additional, Schellander, Karl, additional, and Uddin, Muhammad Jasim, additional

Published
2015
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19. MicroRNA Expression Profile in Bovine Granulosa Cells of Preovulatory Dominant and Subordinate Follicles during the Late Follicular Phase of the Estrous Cycle

Author

Gebremedhn, Samuel, primary, Salilew-Wondim, Dessie, additional, Ahmad, Ijaz, additional, Sahadevan, Sudeep, additional, Hossain, Md Munir, additional, Hoelker, Michael, additional, Rings, Franca, additional, Neuhoff, Christiane, additional, Tholen, Ernst, additional, Looft, Christian, additional, Schellander, Karl, additional, and Tesfaye, Dawit, additional

Published
2015
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20. Identification of gene co-expression clusters in liver tissues from multiple porcine populations with high and low backfat androstenone phenotype

Author

Sahadevan, Sudeep, primary, Tholen, Ernst, additional, Große-Brinkhaus, Christine, additional, Schellander, Karl, additional, Tesfaye, Dawit, additional, Hofmann-Apitius, Martin, additional, Cinar, Mehmet Ulas, additional, Gunawan, Asep, additional, Hölker, Michael, additional, and Neuhoff, Christiane, additional

Published
2015
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21. The Expression Pattern of microRNAs in Granulosa Cells of Subordinate and Dominant Follicles during the Early Luteal Phase of the Bovine Estrous Cycle

Author

Salilew-Wondim, Dessie, primary, Ahmad, Ijaz, additional, Gebremedhn, Samuel, additional, Sahadevan, Sudeep, additional, Hossain, MD Munir, additional, Rings, Franca, additional, Hoelker, Michael, additional, Tholen, Ernst, additional, Neuhoff, Christiane, additional, Looft, Christian, additional, Schellander, Karl, additional, and Tesfaye, Dawit, additional

Published
2014
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23. Identification of the Novel Candidate Genes and Variants in Boar Liver Tissues with Divergent Skatole Levels Using RNA Deep Sequencing

Author

Gunawan, Asep, primary, Sahadevan, Sudeep, additional, Cinar, Mehmet Ulas, additional, Neuhoff, Christiane, additional, Große-Brinkhaus, Christine, additional, Frieden, Luc, additional, Tesfaye, Dawit, additional, Tholen, Ernst, additional, Looft, Christian, additional, Wondim, Dessie Salilew, additional, Hölker, Michael, additional, Schellander, Karl, additional, and Uddin, Muhammad Jasim, additional

Published
2013
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24. RNA Deep Sequencing Reveals Novel Candidate Genes and Polymorphisms in Boar Testis and Liver Tissues with Divergent Androstenone Levels

Author

Gunawan, Asep, primary, Sahadevan, Sudeep, additional, Neuhoff, Christiane, additional, Große-Brinkhaus, Christine, additional, Gad, Ahmed, additional, Frieden, Luc, additional, Tesfaye, Dawit, additional, Tholen, Ernst, additional, Looft, Christian, additional, Uddin, Muhammad Jasim, additional, Schellander, Karl, additional, and Cinar, Mehmet Ulas, additional

Published
2013
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25. htseq-clip: a toolset for the preprocessing of eCLIP/iCLIP datasets.

Author

Sahadevan S, Sekaran T, Ashaf N, Fritz M, Hentze MW, Huber W, and Schwarzl T

Subjects
Binding Sites, RNA-Binding Proteins metabolism, Immunoprecipitation, Software, Transcriptome
Abstract

Summary: Transcriptome-wide detection of binding sites of RNA-binding proteins is achieved using Individual-nucleotide crosslinking and immunoprecipitation (iCLIP) and its derivative enhanced CLIP (eCLIP) sequencing methods. Here, we introduce htseq-clip, a python package developed for preprocessing, extracting and summarizing crosslink site counts from i/eCLIP experimental data. The package delivers crosslink site count matrices along with other metrics, which can be directly used for filtering and downstream analyses such as the identification of differential binding sites., Availability and Implementation: The Python package htseq-clip is available via pypi (python package index), bioconda and the Galaxy Tool Shed under the open source MIT License. The code is hosted at https://github.com/EMBL-Hentze-group/htseq-clip and documentation is available under https://htseq-clip.readthedocs.io/en/latest., (© The Author(s) 2022. Published by Oxford University Press.)

Published
2023
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26. A Pipeline for Analyzing eCLIP and iCLIP Data with Htseq-clip and DEWSeq.

Author

Sahadevan S, Sekaran T, and Schwarzl T

Subjects
Binding Sites, Immunoprecipitation, RNA, RNA-Binding Proteins genetics, RNA-Binding Proteins metabolism, Transcriptome, High-Throughput Nucleotide Sequencing
Abstract

Individual-nucleotide crosslinking and immunoprecipitation (iCLIP) sequencing and its derivative enhanced CLIP (eCLIP) sequencing are methods for the transcriptome-wide detection of binding sites of RNA-binding proteins (RBPs). This chapter provides a stepwise tutorial for analyzing iCLIP and eCLIP data with replicates and size-matched input (SMI) controls after read alignment using our open-source tools htseq-clip and DEWSeq. This includes the preparation of gene annotation, extraction, and preprocessing of truncation sites and the detection of significantly enriched binding sites using a sliding window based approach suitable for different binding modes of RBPs., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Published
2022
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