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                                GENOME   ANALYSIS











      Genome analysis entails the prediction of genes or gnome in uncharacterized genomic sequences. The twenty one century has seen the announcement of the draft version of the human genome sequence (HGS). Model organisms have been sequenced in both the animal and plant kingdoms. However, the pace of genome annotation is not matching the pace of genome sequencing.  all experimental genome annotation is slow and time consuming. The demand is to be able to develop computational or computerized tools for gene prediction. Computational Gene prediction is relatively simple for the all prokaryotes where all the genes are converted into the corresponding mRNA (messnger RNA)  and then into proteins. The process is more complex for eukaryotic cells where the coding DNA (Deoxyribonucleic acid) sequence is interrupted by random sequences called introns.



Some of the questions which biologists want to answer today are:


 1.Divide a newly sequenced genome into the genes (coding regions) and the non-coding regions.


 2. Given a DNA sequence, what part of it codes for a protein and what part of it is junk DNA.


 3. Classify the junk DNA as intron, regulatory elements,  transposons, untranslated region, dead genes etc.



Defination- Genomic analysis are the techniques needed to compare and determine the genetic sequence (e.g. DNA in the chromosomes). This includes DNA sequencing, routine use of DNA microarray technology for the analysis of gene expression profiles at the mRNA (messnger RNA) level and improved informatic tools to analyze and organize such data. At the same time, new developments in chip-based analysis of samples and the emergence of models of gene networks.Genome refers to haploid set of chromosomes or genes in a gamete or microorganisms, or in each cell of a multicellular organism. It is determined either by DNA or for many types of virus, in RNA.


Computational genomics- computational gnomics is the use of computational analysis to decipher biology from genome sequences and related data, including both RNA and DNA sequence as well as other "post-genomic" data (i.e. experimental data obtained with technologies that require the genome sequence ). As such, computational genomics may be regarded as a subset of bioinformatics, but with a focus on using whole genomes ( than individual genes) to understand the principles of how the DNA of a species controls its biology at the molecular level. With the current abundance of massive biological datasets, computational studies have become one of the most important means to biological discovery and research.


The significance of genome analysis can be understood by comparing the chimpanzee and human genomes. The chimp and human genomes vary by an average of just 2%  i.e. just about 150 enzymes. An complete genome analysis of the two genomes would give a strong and havey insight into the various mechanisms responsible for the differences.








Genome VoyagerTM-


Research tells that the keys to understanding both disease and good health are hidden inside the about three billion base pairs of each human being’s genome. Genome Voyager makes the mass of data that explain the human genome more intelligible and accessible to the genomics research community.


CGATM Tools-


 The CGA Tools (Complete Genomics Analysis Tools) are a set of free open source software tools for downstream analysis of sequencing data produced by Complete Genomics or genes. These tools focus on multi-genome comparisons and format conversion, and can be used to conduct various analyses including case-control analysis or family-based analysis.


Complete Genomics Tool Repository


That tool contains automated workflows and scripts created by Complete Genomics experts or researchers to help you analyze Complete Genomics data. Included in the Tool Repository are scripts and programs for format conversion, genome analysis and comparison, and visualization of data that found.


Compatible Third-Party Tools-


There are many open source and commercial software packages that complement Complete Genomics sequencing services to allow you to further explore and visualize your data. These type of tools can assist with annotation, format conversion, filtering, visualization, and data storage etc.



Complete Genomics Analysis Tools


 CGA™ Tools witch called (Complete Genomics Analysis Tools) are a set of open source software tools for downstream analysis of sequencing data produced by Complete Genomics. These tools workes on multi-genome comparisons and format conversion, for eg. to SAM and VCF formats. Customers or user can use these tools to conduct various analyses including family-based analysis or case-control analysis.



Analysis functionality includes:


·         Genome comparison tools – compare many types of variant calls between genomes

·         Format conversion tools – export data into other standard formats for further analysis.

·         Filtering and annotation tools – manipulation of  variant files

·         Reference tools – help build a xerox of the reference genome for other CGA Tools analyses.



The CGA Tools package is freely available as pre-compiled binary distributions for 64-bit Linux and Mac OS X platforms. Installing from the provided source code provides access to the CGA Tools C++ APIs. The most uses CGA Tools commands are also published in Mac and Linux repositories in the Galaxy Tool Shed, allowing consumers  to harness the graphical interface provided by Galaxy to develop workflows that incorporate the tools.












      The analysis technique witch is known as "next generation sequencing," a powerful way capable of decoding entire genomes. Vast quantities of DNA data are produced from each sample tested, simultaneously revealing information on the inheritance of genetic disorders, mitochondrial mutations and chromosome abnormalitiesNGS (Next generation sequencing) is already revolutionising many areas of genetic research and diagnostics, and, when applied to the assessment of embryos, will allow the concurrent analysis of serious lethal chromosome abnormalities and inherited disorders. "Next generation sequencing provides an unprecedented insight into the biology of embryos.


Shotgun sequencing-


    Shotgun sequencing  is an sequencing method designed for analysis of DNA sequences longer than about 1000 base pairs, up to and including entire chromosomes or genome. It is named by analogy with the rapidly expanding, quasi-random firing pattern of a shotgun. Since the chain termination method of DNA sequencing can only be used for fairly short strands (about 100 to 1000 basepairs), large DNA sequences must be pieces into random small segments which are then sequenced to obtain reads. multiple overlapping reads for the target DNA are obtained by performing many rounds of this sequencing and fragmentation. Computer programs then use the overlapping ends of different reads to assemble them into in a continuous sequence.  that type of sequencing is a random sampling process, requiring over-sampling to ensure a given nucleotide is represented in the reconstructed sequence.



High-throughput sequencing-


  The high demand for chepest sequencing has driven the development of high-throughput sequencing NGS (or next-generation sequencing) technologies that parallelize the sequencing process, creating thousands or millions of sequences at once. High-throughput sequencing technologies are intended to lower the cost of DNA sequencing beyond what is possible with standard dye-terminator process. In ultra-high-throughput sequencing as many as 500,000 sequencing-by-synthesis operations may be run in parallel way.


While NGS methods' high throughput are associated with the sequencing of bigest eukaryotic genomes, their scalability gives them applications in the sequencing of smaller prokaryotic genomes. In a December 2012 comparison of NGS technologies, experts from the Integrated Microbial Genomesproject found comparison.



Illumina (Solexa) sequencing-


   Solexa, witch now part of Illumina, developed a sequencing method based on reversible dye-terminators technology acquired from Manteia Predictive Medicine. This method had been invented and developed in late 1996 at GBRI (Glaxo-Welcome's Geneva Biomedical Research Institute), by Dr Laurent Farinelli and Dr. Pascal Mayer. In this method, DNA molecules and primers are first attached on a slide and amplified with polymerase enzyme so that local clonal colonies, initially coined "DNA colonies", are formed. To determine the sequence, four types of reversible terminator bases (RT-bases) are added and non-incorporated nucleotides are washed away. Unlike pyrosequencing, the DNA chains are extended one nucleotide at a time and image acquisition can be performed at a delayed moment, allowing for very large arrays of DNA colonies to be captured by sequential photo taken from a single camera.



New Genome Analysis Technique-


      July 8, 2013 — The first birth has been gained following the analysis of embryos using a new genome sequencing technique which promises to revolutionise embryo selection for IVF. The technique, which has never before been applied in the screening of embryos, is reported today at the annual meeting of ESHRE of the NIHR Biomedical Research Centre at the University of Oxford, UK.


The identification of an embryo destined to implant in the uterus and form a pregnancy remains the holy grail of IVF (in vitro fertilization) on average, only around 30% of embryos currently selected for transfer actually implant. The reason for this high failure rate is unknown, but the prime suspects are unidentified chromosomal defects. Several genetic screening methods have been introduced over the past decade, but all have been shown to have limitations or drawbacks (and have not realised their potential) when tested in randomised clinical trials.



This new NGS (next generation sequencing)technique however, seems to overcome the major drawbacks of current methods:


1.Serious gene defects can be identified at the same time.


2.The test could greatly reduce the costs of embryo screening, which is currently an expensive add-on to IVF.


3.Complete chromosome information can be produced revealing abnormalities often responsible for miscarriage.


4.The analysis can be completed rapidly (around 16 hours), thus avoiding the need for embryo freezing while awaiting results.



     The study witch described today was designed to test the predictability and accuracy of NGS in embryo selection. The validation was performed on multiple cells from cell-lines with known  gene defects (cystic fibrosis) or mitochondrial DNA mutations,and chromosome abnormalities .Additionally, cells from 45 embryos, previously shown to be abnormal with another testing technique, were reanalysed by NGS in a blinded fashion. After high accuracy had been demonstrated, the method was applied clinically, with cells sampled from seven five-day-old embryos (blastocysts) produced by two couples undergoing IVF. The mothers were 35 and 39 years of age and one couple had a history of miscarriage.


"In the last few years, results from randomised clinical trials have suggested that most IVF (in vitro fertilization) patients would benefit from embryo chromosome screening, with some studies reporting a 50% boost in pregnancy rates. However, the costs of these genetic tests are relatively high, putting them beyond the reach of many patients. Next generation sequencing is a process which could make chromosome testing more widely available to a greater number of patients, improving access by cutting the costs.






      The current explosion in available genome sequence data has ushered in an era in which analysis of a complete genome can be performed in a experiment. While DNA microarrays have long been the established strategy for measuring gene expression levels, standard expression arrays use relatively some probes for each gene and are typically biased toward known and predicted gene structures. currently, with the availability of complete genome sequences for many organisms, very-high-density oligonucleotide-based microarrays that span the complete genome have emerged as the preferred platform for genomic analysis. Whole-genome tiling microarrays can be employed for a myriad of aim, including empirical annotation of the transcriptome, chromatin immunoprecipitation-chip studies, analysis of alternative RNA splicing, characterization of the methylation state of cytosine bases throughout a genome (methylome), and DNA polymorphism discovery.



plant species exhibit a wide range of values for each of the components. The genome of Arabidopsis plant is essentially entirely one copy sequences (the repetitive sequences have been determined to be essentially all chloroplast DNA). At the other extreme, wheat and pea genomes have only 10-20% single copy sequences. Reassociation kinetic experiments of polyploid species, such as bread wheat (witch scintific name is Triticum aestivium ) were unable to derive a component that displayed true single copy kinetics. Instead the lowest component appeared to act as if it consisted of xerox represented three times. This result is consistent with the current hypothesis that bread wheat was developed from the introgression of three diploid wheat species. Genomic analysis suggest that this hypothesis is right since the slowest component appears to made up of sequences represented three times.



Molecular Markers in palnt genome analysis-


    Always plant have been looked upon as a key source of energy for evolution and survival of the animal kingdom, thus forming a base for every ecological pyramid. Over the last few decades plant genomics has been studied extensively bringing approx a revolution in this area. Molecular markers, useful for plant genome or DNA analysis, have now become an good tool in this revolution. most of the available DNA markers that can be routinely employed in various aspects of plant genome analysis such as  phylogeny, taxonomy, ecology,plant breeding, and geneticsGenetic polymorphism is  defined as the simultaneous occurrence of a trait in the same population of two or more discontinuous variants or genotypes. Although DNA sequencing is a straightforward strategy for identifying variations at a locus, it is expensive and laborious. A wide variety of techniques have, therefore, been developed in the last few years for visualizing DNA sequence polymorphism.











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