2-D Photonic Crystal based Bio-chip for DNA Analysis of Breast Cancer

The work is basically focused on the Design and simulation of Bio-chip based Optical Sensor for the DNA analysis. In medical science it has been observed that the physical agents or errors in DNA replication alter the usual DNA sequence causing cancer and other genetic diseases. It takes 5-7 years for a normal cell to become cancerous. 70% of the cancer conditions that are detected are at the advanced stage. In this paper we have demonstrated a Nano-platform based chip which is highly sensitive for the change in refractive index and thus can easily differentiate the normal and cancerous DNA. Computation has been done by using the tool of MEEP & MPB by using FDTD algorithm. An analysis of normal cell breast DNA and Breast Cancer cell DNA has been done. The obtained spectral behavior shows the maximum amplitude for normal breast DNA is 0.1802 where as for benign DNA and malignant DNA is 0.1791 and 0.1795 respectively. The wavelength shifts were also observed for normal breast DNA at 1.845 um and benign DNA at1.846 um and malignant DNA at 1.8447 um. The quality factor of the proposed design is 118563 and a sensitivity of 10-6. Further the proposed chip design for the fabrication is possible by doing the layout GDSII file format and IMEC IPKISS tool

Isolation and characterization of microsatellite markers from Garcinia indica and cross species amplification

Garcinia indica popularly known as ‘Kokum’ or Murugalu”, is a medium-sized evergreen tree found in the western-ghats of India. This tree species is highly exploited to produce anti-obesity drugs and culinary purposes. Its population is threatened by overexploitation and loss of habitat. The development of microsatellite markers would help in understanding the genetic structure and further to develop appropriate conservation strategies. In this study, using next generation sequencing platform Illumina Hiseq 2000, we have sequenced the partial genome of G. indica and identified 3725 microsatellites. Forty-eight microsatellite markers were analyzed using 30 accessions. Polymorphism information content (PIC) values ranged from 0.718 to 0.968 with a mean value of 0.922. Allele per locus ranged from 3 to 33 per locus. The probability of identity values ranged from 0.00329 to 0.30489. Cross-species amplification SSR primers in the related species showed a moderate transferability from 12.5 % (for G. morella) to 18.7%(for G. gummigutta

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Not AvailableMango is one of the most important fruits of tropical ecological region of the world, well known for its nutritive value, aroma and taste. Its world production is >45MT worth >200 billion US dollars. Genomic resources are required for improvement in productivity and management of mango germplasm. There is no web-based genomic resources available for mango. Hence rapid and cost-effective high throughput putative marker discovery is required to develop such resources. RAD-based marker discovery can cater this urgent need till whole genome sequence of mango becomes available. Using a panel of 84 mango varieties, a total of 28.6 Gb data was generated by ddRAD-Seq approach on Illumina HiSeq 2000 platform. A total of 1.25 million SNPs were discovered. Phylogenetic tree using 749 common SNPs across these varieties revealed three major lineages which was compared with geographical locations. A web genomic resources MiSNPDb, available at http://webtom.cabgrid.res.in/mangosnps/ is based on 3-tier architecture, developed using PHP, MySQL and Javascript. This web genomic resources can be of immense use in the development of high density linkage map, QTL discovery, varietal differentiation, traceability, genome finishing and SNP chip development for future GWAS in genomic selection program. We report here world’s first web-based genomic resources for genetic improvement and germplasm management of mango.Not Availabl

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Not AvailableMango is one of the most important fruits of tropical ecological region of the world, well known for its nutritive value, aroma and taste. Its world production is >45MT worth >200 billion US dollars. Genomic resources are required for improvement in productivity and management of mango germplasm. There is no web-based genomic resources available for mango. Hence rapid and cost-efective high throughput putative marker discovery is required to develop such resources. RAD-based marker discovery can cater this urgent need till whole genome sequence of mango becomes available. Using a panel of 84 mango varieties, a total of 28.6 Gb data was generated by ddRAD-Seq approach on Illumina HiSeq 2000 platform. A total of 1.25 million SNPs were discovered. Phylogenetic tree using 749 common SNPs across these varieties revealed three major lineages which was compared with geographical locations. A web genomic resources MiSNPDb, available at http://webtom.cabgrid.res.in/mangosnps/ is based on 3-tier architecture, developed using PHP, MySQL and Javascript. This web genomic resources can be of immense use in the development of high density linkage map, QTL discovery, varietal diferentiation, traceability, genome fnishing and SNP chip development for future GWAS in genomic selection program. We report here world’s frst web-based genomic resources for genetic improvement and germplasm management of mango.Not Availabl

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Not AvailableMango (Mangifera indica L.) is known as the ‘king of fruits’ for its rich taste, flavor, color, production volume and diverse end usage. It belongs to plant family Anacardiaceae and has a small genome size of 439 Mb (2n = 40). Ancient literature indicates origin of cultivated mango in India. Although wild species of genus Mangifera are distributed throughout South and South-East Asia, recovery of Paleocene mango leaf fossils near Damalgiri, West Garo Hills, Meghalaya point to the origin of genus in peninsular India before joining of the Indian and Asian continental plates. India produces more than fifty percent of the world’s mango and grows more than thousand varieties. Despite its huge economic significance genomic resources for mango are limited and genetics of useful horticultural traits are poorly understood. Here we present a brief account of our recent efforts to generate genomic resources for mango and its use in the analysis of genetic diversity and population structure of mango cultivars. Sequencing of leaf RNA from mango cultivars ‘Neelam’, ‘Dashehari’ and their hybrid ‘Amrapali’ revealed substantially higher level of heterozygosity in ‘Amrapali’ over its parents and helped develop genic simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers. Sequencing of double digested restriction-site-associated genomic DNA (ddRAD) of 84 diverse mango cultivars identified 1.67 million high quality SNPs and two major sub-populations. We have assembled 323 Mb of the highly heterozygous ‘Amrapali’ genome using long sequence reads of PacBio single molecule real time (SMRT) sequencing chemistry and predicted 43,247 protein coding genes. We identified in the mango genome 122,332 SSR loci and developed 8,451 Type1 SSR and 835 HSSR markers for high level of polymorphism. Among the published genomes, mango showed highest similarity with sweet orange (Citrus sinensis). These genomic resources will fast track the mango varietal improvement for high productivity, disease resistance and superior end use qualityNot Availabl