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Book: Regulatory RNomics and gene expression

Ghosh, Zhumur

(Journal of biomedicine and biotechnology ; 2009, Spec. iss.)

2009

Author's details	guest ed.: Zhumur Ghosh
Series title	Journal of biomedicine and biotechnology ; 2009, Spec. iss. Journal of biomedicine & biotechnology
Collection	Journal of biomedicine & biotechnology
Language	English
Size	Getr. Zählung : Ill., graph. Darst.
Publisher	Hindawi
Publishing place	S.l.
Publishing country	United States
Document type	Book
HBZ-ID	HT016289383
Database	Catalogue ZB MED Medicine, Health

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Article: Defense Surveillance System at the Interface: Response of Rice Towards

Acharya, Udita / Das, Troyee / Ghosh, Zhumur / Ghosh, Anupama

Molecular plant-microbe interactions : MPMI

2022 , Page(s) MPMI07220153R

Abstract: Sheath blight of rice caused by necrotrophic plant ... ...

Abstract	Sheath blight of rice caused by necrotrophic plant pathogen
Language	English
Publishing date	2022-12-12
Publishing country	United States
Document type	Journal Article
ZDB-ID	743331-1
ISSN	1943-7706 ; 0894-0282
ISSN (online)	1943-7706
ISSN	0894-0282
DOI	10.1094/MPMI-07-22-0153-R
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: LncRTPred: Predicting RNA-RNA mode of interaction mediated by lncRNA.

Das, Gourab / Das, Troyee / Parida, Sibun / Ghosh, Zhumur

IUBMB life

2023 Volume 76, Issue 1, Page(s) 53–68

Abstract: ... versions of LncRTPred are available. Web server link: http://bicresources.jcbose.ac.in/zhumur/lncrtpred ...

Abstract	Long non-coding RNAs (lncRNAs) play a significant role in various biological processes. Hence, it is utmost important to elucidate their functions in order to understand the molecular mechanism of a complex biological system. This versatile RNA molecule has diverse modes of interaction, one of which constitutes lncRNA-mRNA interaction. Hence, identifying its target mRNA is essential to understand the function of an lncRNA explicitly. Existing lncRNA target prediction tools mainly adopt thermodynamics approach. Large execution time and inability to perform real-time prediction limit their usage. Further, lack of negative training dataset has been a hindrance in the path of developing machine learning (ML) based lncRNA target prediction tools. In this work, we have developed a ML-based lncRNA-mRNA target prediction model- 'LncRTPred'. Here we have addressed the existing problems by generating reliable negative dataset and creating robust ML models. We have identified the non-interacting lncRNA and mRNAs from the unlabelled dataset using BLAT. It is further filtered to get a reliable set of outliers. LncRTPred provides a cumulative_model_score as the final output against each query. In terms of prediction accuracy, LncRTPred outperforms other popular target prediction protocols like LncTar. Further, we have tested its performance against experimentally validated disease-specific lncRNA-mRNA interactions. Overall, performance of LncRTPred is heavily dependent on the size of the training dataset, which is highly reflected by the difference in its performance for human and mouse species. Its performance for human species shows better as compared to that for mouse when applied on an unknown data due to smaller size of the training dataset in case of mouse compared to that of human. Availability of increased number of lncRNA-mRNA interaction data for mouse will improve the performance of LncRTPred in future. Both webserver and standalone versions of LncRTPred are available. Web server link: http://bicresources.jcbose.ac.in/zhumur/lncrtpred/index.html. Github Link: https://github.com/zglabDIB/LncRTPred.
MeSH term(s)	Humans ; Animals ; Mice ; RNA, Long Noncoding/genetics ; RNA, Messenger/genetics ; Computational Biology/methods
Chemical Substances	RNA, Long Noncoding ; RNA, Messenger
Language	English
Publishing date	2023-08-22
Publishing country	England
Document type	Journal Article
ZDB-ID	1492141-8
ISSN	1521-6551 ; 1521-6543
ISSN (online)	1521-6551
ISSN	1521-6543
DOI	10.1002/iub.2778
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: MicroRNA mediated gene regulatory circuits leads to machine learning based preliminary detection of acute myeloid leukemia.

Sarkar, Arijita / Das, Troyee / Das, Gourab / Ghosh, Zhumur

Computational biology and chemistry

2023 Volume 104, Page(s) 107859

Abstract: Acute Myeloid Leukemia (AML) can be detected based on morphology, cytochemistry, immunological markers, and cytogenetics. MicroRNAs (miRNAs) influence key biological pathways in multiple haematological malignancies including AML. In this work, we have ... ...

Abstract	Acute Myeloid Leukemia (AML) can be detected based on morphology, cytochemistry, immunological markers, and cytogenetics. MicroRNAs (miRNAs) influence key biological pathways in multiple haematological malignancies including AML. In this work, we have analysed the miRNome and the transcriptome of normal and AML samples and have identified the significant set of miRNA-target mRNA pairs present within AML- Peripheral Blood and AML- Bone Marrow samples from both tissue and cell lines. The miRNA target genes are further filtered based on their functional significance in AML system. These filtered genes constitute the set of selected miRNA target features, which have been finally used for developing machine learning based prediction tool, 'TbAMLPred' for preliminary detection of AML. This model implements both unsupervised clustering and supervised classification algorithms that would increase the reliability of prediction. Our results show that the selected miRNA target-based features can separate the control and disease samples linearly. Overall, we put forward 'TbAMLPred' for a non-invasive mode of preliminary AML diagnosis in future. Github link for accessing TbAMLPred: https://github.com/zglabDIB/TbAMLPred.
MeSH term(s)	Humans ; MicroRNAs/genetics ; MicroRNAs/metabolism ; Reproducibility of Results ; Leukemia, Myeloid, Acute/diagnosis ; Leukemia, Myeloid, Acute/genetics ; Cell Line ; Gene Regulatory Networks/genetics
Chemical Substances	MicroRNAs
Language	English
Publishing date	2023-03-31
Publishing country	England
Document type	Journal Article
ISSN	1476-928X
ISSN (online)	1476-928X
DOI	10.1016/j.compbiolchem.2023.107859
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: TarpiD, a database of putative and validated targets of piRNAs.

Gupta, Pooja / Das, Gourab / Chattopadhyay, Trisha / Ghosh, Zhumur / Mallick, Bibekanand

Molecular omics

2023 Volume 19, Issue 9, Page(s) 706–713

Abstract: Piwi-interacting RNAs (piRNAs) are a novel class of 18-36 nts long small non-coding single-stranded RNAs that play crucial roles in a wide array of critical biological activities besides maintaining genome integrity by transposon silencing. piRNAs ... ...

Abstract	Piwi-interacting RNAs (piRNAs) are a novel class of 18-36 nts long small non-coding single-stranded RNAs that play crucial roles in a wide array of critical biological activities besides maintaining genome integrity by transposon silencing. piRNAs influence biological processes and pathways by regulating gene expression at transcriptional and post-transcriptional level. Studies have reported that piRNAs silence various endogenous genes post-transcriptionally by binding to respective mRNAs through interaction with the PIWI proteins. Several thousands of piRNAs have been discovered in animals, but their functions remain largely undiscovered owing to a lack of proper guiding principles of piRNA targeting or diversity in targeting patterns amongst piRNAs from the same or different species. Identification of piRNA targets is essential for deciphering their functions. There are a few tools and databases on piRNAs, but there are no systematic and exclusive repositories to obtain information on target genes regulated by piRNAs and other related information. Hence, we developed a user-friendly database named TarpiD (Targets of piRNA Database) that offers comprehensive information on piRNA and its targets, including their expression, methodologies (high-throughput or low-throughput) for target identification/validation, cells/tissue types, diseases, target gene regulation types, target binding regions, and key functions driven by piRNAs through target gene interactions. The contents of TarpiD are curated from the published literature and enable users to search and download the targets of a particular piRNA or the piRNAs that target a specific gene for use in their research. This database harbours 28 682 entries of piRNA-target interactions supported by 15 methodologies reported in hundreds of cell types/tissues from 9 species. TarpiD will be a valuable resource for a better understanding of the functions and gene-regulatory mechanisms mediated by piRNAs. TarpiD is freely accessible for academic use at https://tarpid.nitrkl.ac.in/tarpid_db/.
MeSH term(s)	Animals ; RNA, Small Interfering/genetics ; RNA, Small Interfering/metabolism ; Piwi-Interacting RNA ; Gene Expression Regulation ; Proteins/metabolism
Chemical Substances	RNA, Small Interfering ; Piwi-Interacting RNA ; Proteins
Language	English
Publishing date	2023-10-30
Publishing country	England
Document type	Journal Article
ISSN	2515-4184
ISSN (online)	2515-4184
DOI	10.1039/d3mo00098b
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: piRNAQuest V.2: an updated resource for searching through the piRNAome of multiple species

Ghosh, Byapti / Sarkar, Arijita / Mondal, Sudip / Bhattacharya, Namrata / Khatua, Sunirmal / Ghosh, Zhumur

RNA Biology. 2022 Dec. 31, v. 19, no. 1 p.12-25

2022

Abstract: ... is available at http://dibresources.jcbose.ac.in/zhumur/pirnaquest2. ...

Abstract	PIWI interacting RNAs (piRNAs) have emerged as important gene regulators in recent times. Since the release of our first version of piRNAQuest in 2014, lots of novel piRNAs have been annotated in different species other than human, mouse and rat. Such new developments in piRNA research have led us to develop an updated database piRNAQuest V.2. It consists of 92,77,689 piRNA entries for 25 new species of different phylum along with human, mouse and rat. Besides providing primary piRNA features which include their genomic location, with further information on piRNAs overlapping with repeat elements, pseudogenes and syntenic regions, etc., the novel features of this version includes (i) density based cluster prediction, (ii) piRNA expression profile across various healthy and disease systems and (iii) piRNA target prediction. The concept of density-based piRNA cluster identification is robust as it does not consider parametric distribution in its model. The piRNA expression profile for 21 disease systems including cancer have been hosted in addition to 32 tissue specific piRNA expression profile for various species. Further, the piRNA target prediction section includes both predicted and curated piRNA targets within eight disease systems and developmental stages of mouse testis. Further, users can visualize the piRNA-target duplex structure and the ping-pong signature pattern for all the ping-pong piRNA partners in different species. Overall, piRNAQuest V.2 is an updated user-friendly database which will serve as a useful resource to survey, search and retrieve information on piRNAs for multiple species. This freely accessible database is available at http://dibresources.jcbose.ac.in/zhumur/pirnaquest2.
Keywords	RNA ; databases ; genomics ; humans ; mice ; models ; new species ; prediction ; pseudogenes ; rats ; surveys ; testes ; PIWI interacting RNAs ; piRNA cluster ; ping-pong piRNAs ; piRNA target ; piRNA profile
Language	English
Dates of publication	2022-1231
Size	p. 12-25.
Publishing place	Taylor & Francis
Document type	Article ; Online
ZDB-ID	2159587-2
ISSN	1555-8584
ISSN	1555-8584
DOI	10.1080/15476286.2021.2010960
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: NSAID targets SIRT3 to trigger mitochondrial dysfunction and gastric cancer cell death.

Debsharma, Subhashis / Pramanik, Saikat / Bindu, Samik / Mazumder, Somnath / Das, Troyee / Pal, Uttam / Saha, Debanjan / De, Rudranil / Nag, Shiladitya / Banerjee, Chinmoy / Chandra Maiti, Nakul / Ghosh, Zhumur / Bandyopadhyay, Uday

iScience

2024 Volume 27, Issue 4, Page(s) 109384

Abstract: Gastric cancer (GC) is a deadly malignancy that demands effective therapeutic intervention capitalizing unique drug target/s. Here, we report that indomethacin, a cyclooxygenase non-selective non-steroidal anti-inflammatory drug, arrests GC cell growth ... ...

Abstract	Gastric cancer (GC) is a deadly malignancy that demands effective therapeutic intervention capitalizing unique drug target/s. Here, we report that indomethacin, a cyclooxygenase non-selective non-steroidal anti-inflammatory drug, arrests GC cell growth by targeting mitochondrial deacetylase Sirtuin 3 (SIRT3). Interaction study revealed that indomethacin competitively inhibited SIRT3 by binding to nicotinamide adenine dinucleotide (NAD)-binding site. The Cancer Genome Atlas data meta-analysis indicated poor prognosis associated with high SIRT3 expression in GC. Further, transcriptome sequencing data of human gastric adenocarcinoma cells revealed that indomethacin treatment severely downregulated SIRT3. Indomethacin-induced SIRT3 downregulation augmented SOD2 and OGG1 acetylation, leading to mitochondrial redox dyshomeostasis, mtDNA damage, respiratory chain failure, bioenergetic crisis, mitochondrial fragmentation, and apoptosis via blocking the AMPK/PGC1α/SIRT3 axis. Indomethacin also downregulated SIRT3 regulators ERRα and PGC1α. Further, SIRT3 knockdown aggravated indomethacin-induced mitochondrial dysfunction as well as blocked cell-cycle progression to increase cell death. Thus, we reveal how indomethacin induces GC cell death by disrupting SIRT3 signaling.
Language	English
Publishing date	2024-03-01
Publishing country	United States
Document type	Journal Article
ISSN	2589-0042
ISSN (online)	2589-0042
DOI	10.1016/j.isci.2024.109384
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Heightened miR6024-NLR interactions facilitate necrotrophic pathogenesis in tomato.

Dey, Sayani / Sarkar, Arijita / Chowdhury, Shreya / Singh, Raghuvir / Mukherjee, Ananya / Ghosh, Zhumur / Kundu, Pallob

Plant molecular biology

2022 Volume 109, Issue 6, Page(s) 717–739

Abstract: Key message: miR6024 acts as a negative regulator of R genes, hence of Tomato plant immunity, and facilitates disease by the necrotrophic pathogen A. solani. Plant resistance genes or Nucleotide-binding leucine-rich repeat (NLR) genes, integral ... ...

Abstract	Key message: miR6024 acts as a negative regulator of R genes, hence of Tomato plant immunity, and facilitates disease by the necrotrophic pathogen A. solani. Plant resistance genes or Nucleotide-binding leucine-rich repeat (NLR) genes, integral components of plant disease stress-signaling are targeted by variable groups of miRNAs. However, the significance of miRNA-mediated regulation of NLRs during a pathogen stress response, specifically for necrotrophic fungus, is poorly understood. A thorough examination of Tomato NLRs and miRNAs could map substantial interactions of which half the annotated NLRs were targets of Solanaceae-specific and conserved miRNAs, at the NB subdomain. The Solanaceae-specific miR6024 and its NLR targets analysed in different phytopathogenic stresses revealed differential and mutually antagonistic regulation. Interestingly, miR6024-targeted cleavage of a target NLR also triggered the generation of secondary phased siRNAs which could potentially amplify the defense signal. RNA-seq analysis of leaf tissues from miR6024 overexpressing Tomato plants evidenced a perturbation in the defense transcriptome with the transgenics showing unwarranted immune response-related genes' expression with or without infection with necrotrophic Alternaria solani, though no adverse effect could be observed in the growth and development of the transgenic plants. Transgenic plants exhibited constitutive downregulation of the target NLRs, aggravated disease phenotype with an enhanced lesion, greater ROS generation and hypersusceptibility to A. solani infection, thus establishing that miR6024 negatively impacts plant immune response during necrotrophic pathogenesis. Limited knowledge about the outcome of NLR-miRNA interaction during necrotrophic pathogenesis is a hindrance to the deployment of miRNAs in crop improvement programs. With the elucidation of the necrotrophic disease-synergistic role played by miR6024, it becomes a potent candidate for biotechnological manipulation for the rapid development of pathogen-tolerant solanaceous plants.
MeSH term(s)	Lycopersicon esculentum/microbiology ; MicroRNAs/genetics ; MicroRNAs/metabolism ; Plant Diseases/genetics ; Plant Diseases/microbiology ; Plant Immunity ; Plants, Genetically Modified/genetics
Chemical Substances	MicroRNAs
Language	English
Publishing date	2022-05-02
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	778032-1
ISSN	1573-5028 ; 0167-4412
ISSN (online)	1573-5028
ISSN	0167-4412
DOI	10.1007/s11103-022-01270-z
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: PSCRIdb: A database of regulatory interactions and networks of pluripotent stem cell lines.

Banerjee, Krishnendu / Jana, Tanmoy / Ghosh, Zhumur / Saha, Sudipto

Journal of biosciences

2020 Volume 45

Abstract: Pluripotency in stem cells is regulated by a complex network between the transcription factors, signaling molecules, mRNAs, and epigenetic regulators like non-coding RNAs. Different pluripotent stem cell (PSC) lines were isolated and characterized to ... ...

Abstract	Pluripotency in stem cells is regulated by a complex network between the transcription factors, signaling molecules, mRNAs, and epigenetic regulators like non-coding RNAs. Different pluripotent stem cell (PSC) lines were isolated and characterized to study the regulatory network topology to understand the mechanism that control developmental potential of pluripotent cells. PSCRIdb is a manually curated database of regulatory interactions including protein-protein, protein-DNA, gene-gene, and miRNA-mRNA interactions in mouse and human pluripotent stem cells including embryonic stem cells and embryonic carcinoma cells. At present, 22 different mouse and human pluripotent stem-cell-line-specific regulatory interactions are compiled in the database. Detailed information of the four types of interaction data are presented in tabular format and graphical network view in Cytoscape layout. The database is available at http://bicresources.jcbose.ac.in/ ssaha4/pscridb. The database contains 3037 entries of experimentally validated molecular interactions that can be useful for systematic study of pluripotency integrating multi-omics data. In summary, the database can be a useful resource for identification of regulatory networks present in different pluripotent stem cell lines.
MeSH term(s)	Animals ; Cell Line ; Computational Biology ; Databases, Factual ; Embryonic Stem Cells/metabolism ; Epigenesis, Genetic ; Gene Expression Regulation, Developmental ; Gene Regulatory Networks ; Humans ; Induced Pluripotent Stem Cells/metabolism ; Mice ; MicroRNAs/genetics ; MicroRNAs/metabolism ; Pluripotent Stem Cells/metabolism ; Protein Interaction Mapping ; RNA, Messenger/genetics ; RNA, Messenger/metabolism ; Transcription Factors/genetics
Chemical Substances	MicroRNAs ; RNA, Messenger ; Transcription Factors
Language	English
Publishing date	2020-04-28
Publishing country	India
Document type	Journal Article
ZDB-ID	756157-x
ISSN	0973-7138 ; 0250-5991
ISSN (online)	0973-7138
ISSN	0250-5991
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A systemic insight into astrocytoma biology across different grades.

Chakraborty, Sohini / Ghosh, Zhumur

Journal of cellular physiology

2018 Volume 234, Issue 4, Page(s) 4243–4255

Abstract: Astrocytomas are the most common type of brain tumors, which originate from glial cells, and are classified into specific grades based on their histopathological behavior. To develop precise therapeutic strategies for the disease, it is important to ... ...

Abstract	Astrocytomas are the most common type of brain tumors, which originate from glial cells, and are classified into specific grades based on their histopathological behavior. To develop precise therapeutic strategies for the disease, it is important to identify the molecular signatures specific to each grade as well as the key factors responsible for the transition from one grade to the next. In this study, we have taken a systems approach to investigate the gene expression profiles of each grades of the disease by mapping shortest paths of gene interaction in each grade and also between one grade and the next. Module core genes govern the topology of these networks and serve as important functional players in each grade as well as help in grade transition events. Shortlisted among these module core genes are well-characterized players of glioma as well as novel molecules (32 grade-specific genes and 15 grade transition-specific genes), which influence important prooncogenic functions but have not been linked to glioma biology yet. These module core genes provide interesting insight into the biology of astrocytic tumors and are potential therapeutic targets for astrocytoma.
MeSH term(s)	Astrocytoma/genetics ; Astrocytoma/metabolism ; Astrocytoma/pathology ; Biomarkers, Tumor/genetics ; Brain Neoplasms/genetics ; Brain Neoplasms/metabolism ; Brain Neoplasms/pathology ; Databases, Genetic ; Disease Progression ; Gene Expression Regulation, Neoplastic ; Gene Regulatory Networks ; Humans ; Neoplasm Grading ; Signal Transduction/genetics ; Systems Biology ; Transcriptome
Chemical Substances	Biomarkers, Tumor
Language	English
Publishing date	2018-08-26
Publishing country	United States
Document type	Comparative Study ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	3116-1
ISSN	1097-4652 ; 0021-9541
ISSN (online)	1097-4652
ISSN	0021-9541
DOI	10.1002/jcp.27193
Database	MEDical Literature Analysis and Retrieval System OnLINE

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