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Article: Analysis of H3K4me3-ChIP-Seq and RNA-Seq data to understand the putative role of miRNAs and their target genes in breast cancer cell lines.

Kotipalli, Aneesh / Banerjee, Ruma / Kasibhatla, Sunitha Manjari / Joshi, Rajendra

2021 Volume 19, Issue 2, Page(s) e17

Abstract: Breast cancer is one of the leading causes of cancer in women all over the world and accounts for ~25% of newly observed cancers in women. Epigenetic modifications influence differential expression of genes through non-coding RNA and play a crucial role ... ...

Abstract	Breast cancer is one of the leading causes of cancer in women all over the world and accounts for ~25% of newly observed cancers in women. Epigenetic modifications influence differential expression of genes through non-coding RNA and play a crucial role in cancer regulation. In the present study, epigenetic regulation of gene expression by in-silico analysis of histone modifications using chromatin immunoprecipitation sequencing (ChIP-Seq) has been carried out. Histone modification data of H3K4me3 from one normal-like and four breast cancer cell lines were used to predict miRNA expression at the promoter level. Predicted miRNA promoters (based on ChIP-Seq) were used as a probe to identify gene targets. Five triple-negative breast cancer (TNBC)-specific miRNAs (miR153-1, miR4767, miR4487, miR6720, and miR-LET7I) were identified and corresponding 13 gene targets were predicted. Eight miRNA promoter peaks were predicted to be differentially expressed in at least three breast cancer cell lines (miR4512, miR6791, miR330, miR3180-3, miR6080, miR5787, miR6733, and miR3613). A total of 44 gene targets were identified based on the 3'-untranslated regions of downregulated mRNA genes that contain putative binding targets to these eight miRNAs. These include 17 and 15 genes in luminal-A type and TNBC respectively, that have been reported to be associated with breast cancer regulation. Of the remaining 12 genes, seven (A4GALT, C2ORF74, HRCT1, ZC4H2, ZNF512, ZNF655, and ZNF608) show similar relative expression profiles in large patient samples and other breast cancer cell lines thereby giving insight into predicted role of H3K4me3 mediated gene regulation via the miRNA-mRNA axis.
Language	English
Publishing date	2021-06-30
Publishing country	Korea (South)
Document type	Journal Article
ZDB-ID	2802682-2
ISSN	2234-0742 ; 1598-866X
ISSN (online)	2234-0742
ISSN	1598-866X
DOI	10.5808/gi.21020
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Understanding the Genetic Diversity of

Balamurugan, Muthukumar / Banerjee, Ruma / Kasibhatla, Sunitha Manjari / Achalere, Archana / Joshi, Rajendra

Frontiers in genetics

2022 Volume 13, Page(s) 800083

Abstract: A total of two lineages ... ...

Abstract	A total of two lineages of
Language	English
Publishing date	2022-04-13
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2606823-0
ISSN	1664-8021
ISSN	1664-8021
DOI	10.3389/fgene.2022.800083
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Article: Genetic diversity of 'Very Important Pharmacogenes' in two South-Asian populations.

Bharti, Neeraj / Banerjee, Ruma / Achalere, Archana / Kasibhatla, Sunitha Manjari / Joshi, Rajendra

PeerJ

2021 Volume 9, Page(s) e12294

Abstract: Objectives: Reliable identification of population-specific variants is important for building the single nucleotide polymorphism (SNP) profile. In this study, genomic variation using allele frequency differences of pharmacologically important genes for ... ...

Abstract	Objectives: Reliable identification of population-specific variants is important for building the single nucleotide polymorphism (SNP) profile. In this study, genomic variation using allele frequency differences of pharmacologically important genes for Gujarati Indians in Houston (GIH) and Indian Telugu in the U.K. (ITU) from the 1000 Genomes Project vis-à-vis global population data was studied to understand its role in drug response. Methods: Joint genotyping approach was used to derive variants of GIH and ITU independently. SNPs of both these populations with significant allele frequency variation (minor allele frequency ≥ 0.05) with super-populations from the 1000 Genomes Project and gnomAD based on Chi-square distribution with Results: Population stratification of VIP genes revealed four clusters viz., single cluster of GIH and ITU, one cluster each of East Asian, European, African populations and Admixed American was found to be admixed. A total of 13 SNPs belonging to ten pharmacogenes were identified to have significant allele frequency variation in both GIH and ITU populations as compared to one or more super-populations. These SNPs belong to VKORC1 (rs17708472, rs2359612, rs8050894) involved in Vitamin K cycle, cytochrome P450 isoforms CYP2C9 (rs1057910), CYP2B6 (rs3211371), CYP2A2 (rs4646425) and CYP2A4 (rs4646440); ATP-binding cassette (ABC) transporter ABCB1 (rs12720067), DPYD1 (rs12119882, rs56160474) involved in pyrimidine metabolism, methyltransferase COMT (rs9332377) and transcriptional factor NR1I2 (rs6785049). SNPs rs1544410 (VDR), rs2725264 (ABCG2), rs5215 and rs5219 (KCNJ11) share high fixation index (≥ 0.5) with either EAS/AFR populations. Missense variants rs1057910 (CYP2C9), rs1801028 (DRD2) and rs1138272 (GSTP1), rs116855232 (NUDT15); intronic variants rs1131341 (NQO1) and rs115349832 (DPYD) are identified to be 'deleterious'. Conclusions: Analysis of SNPs pertaining to pharmacogenes in GIH and ITU populations using population structure, fixation index and allele frequency variation provides a premise for understanding the role of genetic diversity in drug response in Asian Indians.
Language	English
Publishing date	2021-11-10
Publishing country	United States
Document type	Journal Article
ZDB-ID	2703241-3
ISSN	2167-8359
ISSN	2167-8359
DOI	10.7717/peerj.12294
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Article ; Online: Phylogenetic Analysis of Spread of Hepatitis C Virus Identified during HIV Outbreak Investigation, Unnao, India.

Mane, Arati / Kasibhatla, Sunitha Manjari / Vidhate, Pallavi / Saxena, Vandana / Patil, Sandip / Rao, Amrita / Nirmalkar, Amit / Kulkarni-Kale, Urmila / Panda, Samiran

Emerging infectious diseases

2022 Volume 28, Issue 4, Page(s) 725–733

Abstract: An HIV outbreak investigation during 2017-2018 in Unnao District, Uttar Pradesh, India, unearthed high prevalence of hepatitis C virus (HCV) antibodies among the study participants. We investigated these HCV infections by analyzing NS5B and core regions. ...

Abstract	An HIV outbreak investigation during 2017-2018 in Unnao District, Uttar Pradesh, India, unearthed high prevalence of hepatitis C virus (HCV) antibodies among the study participants. We investigated these HCV infections by analyzing NS5B and core regions. We observed no correlation between HIV-HCV viral loads and clustering of HCV sequences, regardless of HIV serostatus. All HCV isolates belonged to genotype 3a. Monophyletic clustering of isolates in NS5B phylogeny indicates emergence of the outbreak from a single isolate or its closely related descendants. The nucleotide substitution rate for NS5B was 6 × 10
MeSH term(s)	Disease Outbreaks ; HIV Infections/epidemiology ; Hepacivirus ; Hepatitis C/epidemiology ; Humans ; India/epidemiology ; Phylogeny
Language	English
Publishing date	2022-03-23
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	1380686-5
ISSN	1080-6059 ; 1080-6040
ISSN (online)	1080-6059
ISSN	1080-6040
DOI	10.3201/eid2804.211845
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Article ; Online: MC1R diversity and its role in skin pigmentation variation in West Maharashtra, India.

Jonnalagadda, Manjari / Bharti, Neeraj / Kasibhatla, Sunitha Manjari / Wagh, Mayur A / Joshi, Rajendra / Ozarkar, Shantanu / Ashma, Richa

American journal of human biology : the official journal of the Human Biology Council

2022 Volume 34, Issue 7, Page(s) e23734

Abstract: Objectives: MC1R polymorphisms have been reported to be under a selective constraint in populations inhabiting high UVR regions such as Africans; however, these patterns are not consistent. Here we analyze the MC1R gene in West Maharashtra, India to see ...

Abstract	Objectives: MC1R polymorphisms have been reported to be under a selective constraint in populations inhabiting high UVR regions such as Africans; however, these patterns are not consistent. Here we analyze the MC1R gene in West Maharashtra, India to see if sequence diversity corresponds to their diverse pigmentary profiles and if MC1R is constrained in dark skinned tribal as compared to lighter skinned caste populations. Methods: A 2648 bp region of this gene was sequenced in 102 individuals and the data was compared for π, ϴ diversity indices. Tajima's D was assessed for signatures of purifying selection and MC1R variants were associated with MI measures using the additive, dominant, and recessive models. Pairwise F Results: MC1R diversity was not uniquely patterned among castes and tribes. Non-synonymous variants rs2228479A, rs1805007_T, and rs885479_A showed low variability in these populations. Selection tests did not indicate any constraint on MC1R and pairwise F Conclusions: We do not find evidence of a selective constraint on MC1R. The presence of a large number of unique haplotypes and low F
MeSH term(s)	Haplotypes ; Humans ; India ; Polymorphism, Genetic ; Receptor, Melanocortin, Type 1/genetics ; Skin Pigmentation/genetics
Chemical Substances	MC1R protein, human ; Receptor, Melanocortin, Type 1
Language	English
Publishing date	2022-02-21
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1025339-7
ISSN	1520-6300 ; 1042-0533
ISSN (online)	1520-6300
ISSN	1042-0533
DOI	10.1002/ajhb.23734
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Article: GAMUT: A genomics big data management tool

Ramakrishnan, E P / Gupta, Saurabh / Gadhari, Renu / Bharti, Neeraj / Malviya, Sandeep / Kasibhatla, Sunitha Manjari / Kim, Jan / Joshi, Rajendra

Journal of biosciences. 2021 Dec., v. 46, no. 4

2021

Abstract: Efficient analysis of Single Nucleotide Polymorphisms (SNPs) across genomic samples enable in deciphering the relationship between genotype and phenotype. The core principle behind SNP comparison is to arrive at a probable list of variants that can ... ...

Abstract	Efficient analysis of Single Nucleotide Polymorphisms (SNPs) across genomic samples enable in deciphering the relationship between genotype and phenotype. The core principle behind SNP comparison is to arrive at a probable list of variants that can differentiate two sets of data (populations). Such SNPs have direct applications in array design, genotype imputation and in cataloging of variants in regions of interest. We have developed GAMUT (Genomics bigdAta Management Tool), a big data-based solution for efficient run-time comparison of SNPs across large datasets based on partition of samples belonging to different populations taking into account user-defined splits. The tool is based on client-server architecture with MongoDB at the back-end and JSF with PrimeFaces as the front-end. It is readily deployable on wild-fly server as well as a docker container. Spark-based parallel data uploader enables optimal loading times. GAMUT enables dynamic querying of the large datasets consisting of multiple samples using text-based, chromosome position-based as well as gene-name based options. Various charting options like bar and pie charts along with tabular formats are available to ease the analysis of the queried data. The resultant data pertaining to comparison of genome-wide SNPs can also be downloaded in different formats like text, html, json for further stand-alone analysis. GAMUT is available for download at: https://github.com/bioinformatics-cdac/gamut
Keywords	chromosomes ; data collection ; genomics ; genotype ; information management ; phenotype
Language	English
Dates of publication	2021-12
Size	p. 89.
Publishing place	Springer India
Document type	Article
ZDB-ID	756157-x
ISSN	0973-7138 ; 0250-5991
ISSN (online)	0973-7138
ISSN	0250-5991
DOI	10.1007/s12038-021-00213-y
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Article: GenoVault: a cloud based genomics repository.

Jain, Sankalp / Saxena, Amit / Hesarur, Suprit / Bhadhadhara, Kirti / Bharti, Neeraj / Kasibhatla, Sunitha Manjari / Sonavane, Uddhavesh / Joshi, Rajendra

BioData mining

2021 Volume 14, Issue 1, Page(s) 36

Abstract: GenoVault is a cloud-based repository for handling Next Generation Sequencing (NGS) data. It is developed using OpenStack-based private cloud with various services like keystone for authentication, cinder for block storage, neutron for networking and ... ...

Abstract	GenoVault is a cloud-based repository for handling Next Generation Sequencing (NGS) data. It is developed using OpenStack-based private cloud with various services like keystone for authentication, cinder for block storage, neutron for networking and nova for managing compute instances for the Cloud. GenoVault uses object-based storage, which enables data to be stored as objects instead of files or blocks for faster retrieval from different distributed object nodes. Along with a web-based interface, a JavaFX-based desktop client has also been developed to meet the requirements of large file uploads that are usually seen in NGS datasets. Users can store files in their respective object-based storage areas and the metadata provided by the user during file uploads is used for querying the database. GenoVault repository is designed taking into account future needs and hence can scale both vertically and horizontally using OpenStack-based cloud features. Users have an option to make the data shareable to the public or restrict the access as private. Data security is ensured as every container is a separate entity in object-based storage architecture which is also supported by Secure File Transfer Protocol (SFTP) for data upload and download. The data is uploaded by the user in individual containers that include raw read files (fastq), processed alignment files (bam, sam, bed) and the output of variation detection (vcf). GenoVault architecture allows verification of the data in terms of integrity and authentication before making it available to collaborators as per the user's permissions. GenoVault is useful for maintaining the organization-wide NGS data generated in various labs which is not yet published and submitted to public repositories like NCBI. GenoVault also provides support to share NGS data among the collaborating institutions. GenoVault can thus manage vast volumes of NGS data on any OpenStack-based private cloud.
Language	English
Publishing date	2021-07-29
Publishing country	England
Document type	Journal Article
ZDB-ID	2438773-3
ISSN	1756-0381
ISSN	1756-0381
DOI	10.1186/s13040-021-00268-5
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Article ; Online: GAMUT: A genomics big data management tool.

Ramakrishnan, E P / Gupta, Saurabh / Gadhari, Renu / Bharti, Neeraj / Malviya, Sandeep / Kasibhatla, Sunitha Manjari / Kim, Jan / Joshi, Rajendra

Journal of biosciences

2021 Volume 46

Abstract	Efficient analysis of Single Nucleotide Polymorphisms (SNPs) across genomic samples enable in deciphering the relationship between genotype and phenotype. The core principle behind SNP comparison is to arrive at a probable list of variants that can differentiate two sets of data (populations). Such SNPs have direct applications in array design, genotype imputation and in cataloging of variants in regions of interest. We have developed GAMUT (Genomics bigdAta Management Tool), a big data-based solution for efficient run-time comparison of SNPs across large datasets based on partition of samples belonging to different populations taking into account user-defined splits. The tool is based on client-server architecture with MongoDB at the back-end and JSF with PrimeFaces as the front-end. It is readily deployable on wild-fly server as well as a docker container. Spark-based parallel data uploader enables optimal loading times. GAMUT enables dynamic querying of the large datasets consisting of multiple samples using text-based, chromosome position-based as well as gene-name based options. Various charting options like bar and pie charts along with tabular formats are available to ease the analysis of the queried data. The resultant data pertaining to comparison of genomewide SNPs can also be downloaded in different formats like text, html, json for further stand-alone analysis. GAMUT is available for download at: https://github.com/bioinformatics-cdac/gamut.
MeSH term(s)	Big Data ; Data Management ; Databases, Factual ; Genomics ; Genotype ; Humans ; Polymorphism, Single Nucleotide ; Software
Language	English
Publishing date	2021-09-08
Publishing country	India
Document type	Journal Article
ZDB-ID	756157-x
ISSN	0973-7138 ; 0250-5991
ISSN (online)	0973-7138
ISSN	0250-5991
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Article ; Online: Population genomics of dengue virus serotype 4: insights into genetic structure and evolution.

Waman, Vaishali P / Kasibhatla, Sunitha Manjari / Kale, Mohan M / Kulkarni-Kale, Urmila

Archives of virology

2016 Volume 161, Issue 8, Page(s) 2133–2148

Abstract: The spread of dengue disease has become a global public health concern. Dengue is caused by dengue virus, which is a mosquito-borne arbovirus of the genus Flavivirus, family Flaviviridae. There are four dengue virus serotypes (1-4), each of which is ... ...

Abstract	The spread of dengue disease has become a global public health concern. Dengue is caused by dengue virus, which is a mosquito-borne arbovirus of the genus Flavivirus, family Flaviviridae. There are four dengue virus serotypes (1-4), each of which is known to trigger mild to severe disease. Dengue virus serotype 4 (DENV-4) has four genotypes and is increasingly being reported to be re-emerging in various parts of the world. Therefore, the population structure and factors shaping the evolution of DENV-4 strains across the world were studied using genome-based population genetic, phylogenetic and selection pressure analysis methods. The population genomics study helped to reveal the spatiotemporal structure of the DENV-4 population and its primary division into two spatially distinct clusters: American and Asian. These spatial clusters show further time-dependent subdivisions within genotypes I and II. Thus, the DENV-4 population is observed to be stratified into eight genetically distinct lineages, two of which are formed by American strains and six of which are formed by Asian strains. Episodic positive selection was observed in the structural (E) and non-structural (NS2A and NS3) genes, which appears to be responsible for diversification of Asian lineages in general and that of modern lineages of genotype I and II in particular. In summary, the global DENV-4 population is stratified into eight genetically distinct lineages, in a spatiotemporal manner with limited recombination. The significant role of adaptive evolution in causing diversification of DENV-4 lineages is discussed. The evolution of DENV-4 appears to be governed by interplay between spatiotemporal distribution, episodic positive selection and intra/inter-genotype recombination.
MeSH term(s)	Dengue/virology ; Dengue Virus/classification ; Dengue Virus/genetics ; Dengue Virus/isolation & purification ; Evolution, Molecular ; Genetic Variation ; Genome, Viral ; Genomics ; Genotype ; Humans ; Phylogeny ; Viral Proteins/genetics ; Viral Proteins/metabolism
Chemical Substances	Viral Proteins
Language	English
Publishing date	2016-08
Publishing country	Austria
Document type	Journal Article
ZDB-ID	7491-3
ISSN	1432-8798 ; 0304-8608
ISSN (online)	1432-8798
ISSN	0304-8608
DOI	10.1007/s00705-016-2886-8
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Article: Complete Genome Sequences of Four Bovine Coronavirus Isolates from Pennsylvania.

Byukusenge, Maurice / Nissly, Ruth Helmus / Kasibhatla, Sunitha Manjari / Li, Lingling / Russell, Rebekah / Springer, Hayley / Barry, Rhiannon / Van Saun, Robert / Wolfgang, David / Hovingh, Ernest / Kulkarni-Kale, Urmila / Kuchipudi, Suresh V

Genome announcements

2018 Volume 6, Issue 22

Abstract: We report four full-genome sequences of bovine coronavirus (BCoV) isolates from dairy calves in Pennsylvania obtained in 2016 and 2017. BCoV is a pathogen of great importance to cattle health, and this is the first report of full-genome sequences of BCoV ...

Abstract	We report four full-genome sequences of bovine coronavirus (BCoV) isolates from dairy calves in Pennsylvania obtained in 2016 and 2017. BCoV is a pathogen of great importance to cattle health, and this is the first report of full-genome sequences of BCoV from PA cattle.
Keywords	covid19
Language	English
Publishing date	2018-05-31
Publishing country	United States
Document type	Journal Article
ZDB-ID	2704277-7
ISSN	2169-8287
ISSN	2169-8287
DOI	10.1128/genomeA.00467-18
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