Papers by Subhashree Nayak
Canadian Journal of Biotechnology
Panicle number is directly associated with grain number in rice. As the panicle number increases,... more Panicle number is directly associated with grain number in rice. As the panicle number increases, it affects the total yield of rice. We examined the evolution of genes associated with panicle number formation in Oryza sativa. Intramural program written in JAVA script and fastPHASE software used for the generation of genotype and haplotype file of SNPs of 11 individual genes associated with panicle number formation utilizing VCF file obtained from RiceCAP project (USDA/CSREES http://www.uark.edu/ua/ricecap/).Tests for natural selection executed on these genes using the Haplotype data. Tajima's D and Fu Li's D* analysis were performed using DNASP v4.0. Rates of non-synonymous Vs synonymous changes were calculated according to the dN/dS algorithm of Nei and Gojobori.dN/dS calculation compared with the ancestral (Oryza meridionalis) sequence individually showed that out of 11, almost all genes responsible for grain number formation, Os01g0746400,
Scientific Reports
Fusion transcripts can contribute to diversity of molecular networks in the human cortex. In this... more Fusion transcripts can contribute to diversity of molecular networks in the human cortex. In this study, we explored the occurrence of fusion transcripts in normal human cortex along with single neurons and astrocytes. We identified 1305 non-redundant fusion events from 388 transcriptomes representing 59 human cortices and 329 single cells. Our results indicate while the majority of fusion transcripts in human cortex are intra-chromosomal (85%), events found in single neurons and astrocytes were primarily inter-chromosomal (80%). The number of fusions in single neurons was significantly higher than that in single astrocytes (p
Journal of Investigative Dermatology
International Journal of Current Microbiology and Applied Sciences
Biology Direct, 2013
Background: MicroRNAs (miRNAs) are non-uniformly distributed in genomes and~30% of the miRNAs in ... more Background: MicroRNAs (miRNAs) are non-uniformly distributed in genomes and~30% of the miRNAs in the human genome are clustered. In this study we have focused on the imprinted miRNA cluster miR-379/miR-656 on 14q32.31 (hereafter C14) to test their coordinated function. We have analyzed expression profile of >1000 human miRNAs in >1400 samples representing seven different human tissue types obtained from cancer patients along with matched and unmatched controls. Results: We found 68% of the miRNAs in this cluster to be significantly downregulated in glioblastoma multiforme (GBM), 61% downregulated in kidney renal clear cell carcinoma (KIRC), 46% in breast invasive carcinoma (BRCA) and 14% in ovarian serous cystadenocarcinoma (OV). On a genome-wide scale C14 miRNAs accounted for 12-30% of the total downregulated miRNAs in different cancers. Pathway enrichment for the predicted targets of C14 miRNA was significant for cancer pathways, especially Glioma (p< 3.77x10-6 , FDR<0.005). The observed downregulation was confirmed in GBM patients by real-time PCR, where 79% of C14 miRNAs (34/43) showed downregulation. In GBM samples, hypermethylation at C14 locus (p<0.003) and downregulation of MEF2, a crucial transcription factor for the cluster was observed which likely contribute to the observed downregulation of the entire miRNA cluster. Conclusion: We provide compelling evidence that the entire C14 miRNA cluster is a tumor suppressor locus involved in multiple cancers, especially in GBM, and points toward a general mechanism of coordinated function for clustered miRNAs.
Haemophilia A (HA) is an X-linked recessive bleeding disorder, primarily because of defects in th... more Haemophilia A (HA) is an X-linked recessive bleeding disorder, primarily because of defects in the 186-kb long factor VIII gene (F8) affecting 1-2 men per 10 000 worldwide. Available markers for carrier detection are not effective in all populations, especially in India. In this study, we have chosen a set of five microsatellite markers, namely, DSX9897, DSX1073, intron 1 (GT) n , intron 22 (CA) n and intron 25 (CA) n , in and around the F8 gene to achieve better sensitivity for carrier detection. Each marker locus has been PCR amplified in the individual DNA samples using fluorescent markers followed by genotyping experiment in automated sequencer. Genotype calls have been made by GeneMapper Software (version 4). Allele frequency of each microsatellite marker was calculated manually. Heterozygosity was determined by counting the hetero-zygotes in the female subset. We have shown that in 253 normal individuals from 20 different ethnic groups of India, the heterozygosity for the markers ranged from 0.25 to 0.54; and for the entire subset of 102 female samples we could successfully discriminate between the two X-chromosomes using these five markers. These markers could also discriminate between the two X-chromosomes for each of 39 obligate carriers included in this study. In conclusion, this panel of five markers around the F8 locus can be used for carrier detection of HA with higher sensitivity across India for families affected with the disease.
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Papers by Subhashree Nayak