Reference based assembly of genomic reads of the elite indica rice cultivar RP Bio-226 was carried out against 2101 reference bacterial genomes using Bowtie-2 genome assembly tool. Five types of ...data: Number of paired end reads concordantly aligned exactly only once, number of paired end reads concordantly aligned more than once, number of mates that make the pairs aligned exactly only once, number of mates that make the pairs aligned more than once and overall percentage of alignment were collected. Interpretation of the results and identification of endophytes based on these alignment statistics are described in detail in our research article “L.Battu, M.M. Reddy, B.S.Goud, K.Ulaganathan, K.Ulaganathan, Genome inside genome:NGS based identification and assembly of endophytic Sphingopyxis granuli and Pseudomonas aeruginosa genomes from rice genomic reads, Genomics (in press)”.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Lignocellulosic biomass, though available in massive volumes, is not used for production of bioethanol due to existence of several barriers which escalate the cost of production. Microorganisms ...possess different proteins associated with different stages of lignocellulosic bioethanol production. Though a large number of such proteins have been identified, their specificities and expression levels are not suitable for lignocellulosic bioethanol production. Additionally, the host organism used for bioethanol production may not be tolerant to temperature, pH and ethanol stresses. Hence, the host organisms and the proteins used for bioethanol production needs to be engineered to suit the conditions for ethanol production. Engineering the host strain and altering specificities of proteins employed for bioethanol production can be achieved by genetic engineering techniques, where the gene of interest is isolated first, manipulated in vitro and introduced back into the host organism. Recently, a number of precision genome engineering techniques have been developed which facilitate modification of genes / genomic regions directly in the organism of interest without the need for isolating the genes/genomic regions. These techniques include (a). The bacterial immunity based CRISPR/Cas system, (b). Xanthomonas transcription-activator-like effector nuclease based TALEN system, (c). Zinc finger domain based ZFN system, (d). Long region recognizing-nuclease based meganuclease system and (e). Oligonucleotide based YOGE system. Protein engineering studies and whole genome sequencing of bioethanol producing strains have shown that alteration of one or more nucleotides can bring out large changes that facilitate increased production of cellulosic bioethanol. These precision engineering techniques can supplement genetic engineering to bring out alteration in specificities of enzymes and change the host's tolerance to various stress levels by specific alteration of genomic regions. In this review, various methods of genome engineering available and their possible application for breaking barriers in lignocellulosic bioethanol production are discussed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Purpose
In this study, we aimed at profiling of luminal B breast cancer specific gene expression pattern in Indian women using mRNA-seq and validation based on TCGA expression data.
Methods
RNA ...isolated from luminal B tumor and adjacent normal tissues was used for library construction and sequencing. Reference-based assemblies of these reads were used for differential gene expression analysis using DeSeq2. The DEGs were evaluated using TCGA expression data. Kaplan–Meier survival method was used to evaluate association between genes showing luminal B specific differential expression pattern and breast cancer prognosis and statistical significance was assessed using log-rank test. Alternate splicing analysis was done using rmats.
Results
Differential expression analysis identified 2371 differentially expressed genes (DEGs) in luminal B breast tumors in comparison with adjacent normal tissues of Indian Women. Of them, 1692 DEGs were validated using TCGA luminal B paired samples. Integration of this data with the DEGs obtained by comparative analysis of unpaired luminal B with luminal A unpaired samples from TCGA resulted in 291 DEGs showing luminal B specific expression pattern. Further, 26 genes of prognostic value were identified. Differential splicing analysis between luminal B tumors and adjacent normal tissues in our cohort led to the identification of 687 genes showing significant differential alternate splicing events.
Conclusion
This study profiled gene expression pattern of luminal B tumors of Indian women and identified 26 key genes of prognostic value for luminal B breast cancer. This study also profiled differential alternate splicing and identified important alternate splicing events in luminal B breast cancer.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
miRNAs have been found to play a major role in cardiomyopathy, a heart muscle disorder characterized by cardiac dysfunction. Several miRNAs including those involved in heart development are found to ...be dysregulated in cardiomyopathy. These miRNAs act either directly or indirectly by controlling the genes involved in normal development and functioning of the heart. Indirectly it also targets modifier genes and genes involved in signaling pathways. In this review, miRNAs involved in heart development, including dysregulation of miRNA which regulate various genes, modifiers and notch signaling pathway genes leading to cardiomyopathy are discussed. A study of these miRNAs would give an insight into the mechanisms involved in the processes of heart development and disease. Apart from this, information gathered from these studies would also generate suitable therapeutic targets in the form of antagomirs which are chemically engineered oligonucleotides used for silencing miRNAs.
Genetic control of root development in rice is complex and the underlying mechanisms (constitutive and adaptive) are poorly understood. Lowland and upland varieties of indica and japonica rice with ...contrasting root development characteristics have been crossed, mapping populations developed and a number of QTLs in different chromosomes were identified. As these studies have used different sets of markers and many of the QTLs identified are long, it is difficult to exploit the varietal difference for improved root traits by marker assisted selection and for identification of concerned alleles. Intensive data mining of literature resulted in the identification 861 root development QTLs and associated microsatellite markers located on different chromosomes. The QTL and marker data generated and the genome sequence of rice were used for construction of a relational database, Rootbrowse, using MySQL relational database management system and Bio::DB::GFF schema. The data is viewed using GBrowse visualization tool. It graphically displays a section of the genome and all features annotated on it including the QTLs. The QTLs can be displayed along with SSR markers, protein coding genes and/or known root development genes for prediction of probable candidate genes.
Rootbrowse is freely available at http://www.ricebrowse.org.
Genetic control of root development in rice is complex and the underlying mechanisms (constitutive and adaptive) are poorly understood. Lowland and upland varieties of indica and japonica rice with ...contrasting root development characteristics have been crossed, mapping populations developed and a number of QTLs in different chromosomes were identified. As these studies have used different sets of markers and many of the QTLs Identified are long, it is difficult to exploit the varietal difference for improved root traits by marker assisted selection and for identification of concerned alleles. Intensive data mining of literature resulted in the identification 861 root development QTLs and associated microsatellite markers bcated on different chromosomes. The QTL and marker data generated and the genome sequence of rice were used for construction of a relational database, Rootbrowse, using MySQL relational database management system and Bio::DB::GFF schema. The data is viewed using GBrowse visualization tool. It graphically displays a section of the genome and all features annotated on it including the QTLs. The QTLs can be displayed along with SSR markers, protein coding genes and/or known root development genes for prediction of probable candidate genes.
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