A) Expressed Sequence Tag (EST) Analysis
There are huge numbers of genes in our genome yet only few of them express to synthesis mRNAs which encode different proteins. These mRNAs are collectively called as transcriptome and mRNA can be reverse transcribed into cDNA, which provides evidence for all mRNA transcripts. Hence, mRNA and cDNA are crucial for gene expression profiling and transcriptome study.
Expressed sequence tags (ESTs) are short, unverified nucleotide fragment usually of 200-800 nucleotide bases. It is randomly selected by single-pass sequencing of either the 5’- or 3’-end of cDNA derived from cDNA libraries that constructed based on mRNA of specific gene. EST data sets has been recognized as the ‘poor man’s genome’ because EST data are widely used as a substitute to the genome sequencing.
There are several steps involved in EST generation. First, mRNAs isolated from specific cell line will be reverse transcribed to double-stranded cDNAs by using reverse transcriptase enzyme. cDNAs are then ligated into plasmid vector and cloned in order to get multiple copies of the cDNA for libraries construction. After then, ESTs can be generated by random sequencing of the cDNA clones with single-pass run from both 5’- and 3’-end directions, with no full-length read. The redundancies of the ESTs set can be reduced by normalization. EST data can be retrieved from different network interface such as UniGene from NCBI, TIGR, Cancer Genome Anatomy Project, ESTree, and dbEST at NCBI.
There are 5 stages involved in EST sequence analysis as described below:
Stage Explanation
1st: EST pre-processing • Lessen overall noise in EST data and enhance efficiency of downstream analysis.
• Identify and remove vector-sequence contaminan...
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...ion of Next Generation Sequencing is definitely a better approach to make genes sequencing more efficient. EST and SAGE has similarity that they require no prior understanding of the sequences to be analyzed since they are both sequencing-based gene expression profiling approaches (Pationo et al. as cited in Yamamoto et al., 2001).
Works Cited
Nagaraj, S. H., Gasser, R. B., & Ranganathan, S. (2006). A hitchhiker’s guide to expressed sequence tag (EST) analysis. Briefing in Bioinformatics, 8(1), 6-21.
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Yamamoto, M., Wakatsuki, T., Hada, A., & Ryo, A. (2001). Use of serial analysis of gene expression (SAGE) technology. Journal of Immunological Methods, 250, 45-66.
...It allowed access to virtually annotate sequences freely, build and visualize maps, design primers, and restriction analysis. First, the pEGFP-N1 plasmid nucleotide sequence was found by using the NCBI nucleotide database program. SnapGene viewer illustrated the restriction enzyme cut sites used to cut EGFP gene from the pEGFP-N1 source plasmid. Then the pET-41a (+) vector sequence was found by using the AddGene Vector Database. A new DNA file representing the recombinant pET-41a (+)-EGFP plasmid was built by virtually cloning the EGFP gene insert into the pET-41a (+) vector sequence. The plasmid was virtually cut utilizing the pAD1 sense primer and pAD1 anti primer from the PCR procedure. A restriction digest experiment was designed to confirm the identity of the PCR product. The two restriction endonucleases that cut the PCR product at least once was HgaI and XspI.
In order to do this a polymer of DNA “unzips” into its two strands, a coding strand (left strand) and a template strand (right strand). Nucleotides of a molecule known as mRNA (messenger RNA) then temporarily bonds to the template strand and join together in the same way as nucleotides of DNA. Messenger RNA has a similar structure to that of DNA only it is single stranded. Like DNA, mRNA is made up of nucleotides again consisting of a phosphate, a sugar, and an organic nitrogenous base. However, unlike in DNA, the sugar in a nucleotide of mRNA is different (Ribose) and the nitrogenous base Thymine is replaced by a new base found in RNA known as Uracil (U)3b and like Thymine can only bond to its complimentary base Adenine. As a result of how it bonds to the DNA’s template strand, the mRNA strand formed is almost identical to the coding strand of DNA apart from these
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Proteogenomics is a kind of science field that includes proteomics and genomics. Proteomic consists of protein sequence information and genomic consists of genome sequence information. It is used to annotate whole genome and protein coding genes. Proteomic data provides genome analysis by showing genome annotation and using of peptides that is gained from expressed proteins and it can be used to correct coding regions.Identities of protein coding regions in terms of function and sequence is more important than nucleotide sequences because protein coding genes have more function in a cell than other nucleotide sequences. Genome annotation process includes all experimental and computational stages.These stages can be identification of a gene ,function and structure of a gene and coding region locations.To carry out these processes, ab initio gene prediction methods can be used to predict exon and splice sites. Annotation of protein coding genes is very time consuming process ,therefore gene prediction methods are used for genome annotations. Some web site programs provides these genome annotations such as NCBI and Ensembl. These tools shows sequenced genomes and gives more accurate gene annotations. However, these tools may not explain the presence of a protein. Main idea of proteogenomic methods is to identify peptides in samples by using these tools and also with the help of mass spectrometry.Mass spectrometry searches translation of genome sequences rather than protein database searching. This method also annotate protein protein interactions.MS/MS data searching against translation of genome can determine and identify peptide sequences.Thus genome data can be understood by using genomic and transcriptomic information with this proteogenomic methods and tools. Many of proteomic information can be achieved by gene prediction algorithms, cDNA sequences and comparative genomics. Large proteomic datasets can be gained by peptide mass spectrophotometry for proteogenomics because it uses proteomic data to annotate genome. If there is genome sequence data for an organism or closely related genomes are present,proteogenomic tools can be used. Gained proteogenomic data provides comparing of these data between many related species and shows homology relationships among many species proteins to make annotations with high accuracy.From these studies, proteogenomic data demonstrates frame shifts regions, gene start sites and exon and intron boundaries , alternative splicing sites and its detection , proteolytic sites that is found in proteins, prediction of genes and post translational modification sites for protein.
... susceptibility. Patients who subsequently needed further treatment for coronary heart disease displayed significantly different protein expression as opposed to patients who needed no further treatment. This revolutionary study provides a new way of detecting coronary artery disease that is both cost effective and less dangerous for patients.
Proteins called transcription factors, however, play a particularly central role in regulating transcription. These important proteins help determine which genes are active in each cell of your body.
This data is used in DESeq66, which is an R Bioconductor package, to calculate differentially expressed genes between HPC and PFC. DESeq provides various statistical tests for determining differentially expressed genes in gene expression data67 The inputs for DESeq are raw counts obtained from HTSeq. DESeq takes into account the total size of each library to perform calculations on fold change as well as significance based on p-value and adjusted p-value. The transcript biotypes were obtained from the Ensembl GTF annotation file (Mus musculus genome build NCBIM37). Using the annotation file, we identified 34,379 transcripts from HPC and 32,909 transcripts from PFC. Analysis of this dataset by blasting against the EMBL database containing 2,057 lncRNAs led to the identification of 1,982 lncRNAs from HPC and 1,936 lncRNAs from PFC (Fig 1, from Kadakkuzha et al., submitted to Genome
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The cells/stain solution was loaded into a Countess™ cell counting chamber slide which was inserted into the Countess™ Automated Cell Counter. If the live cell count was above 1 x 106 cells/mL, then the 1mL of cells, previously taken from the culture flask, was washed 1x with 14mL PBS and centrifuged for 8 minutes at 1200 rpm. The supernatant was aspirated off. The pellet was resuspended in 1mL PBS and then placed on ice. The following reagents were thawed while the cell count was performed: yellow fluorescent chemiluminescent probe (CLP), activator solution and
Many gene transcription is either elevator or decrease in expression as adaptive response to contamination, in order to maintain the homeostasis. For example, one such is the response
Distinct characteristics are not only an end result of the DNA sequence but also of the cell’s internal system of expression orchestrated by different proteins and RNAs present at a given time. DNA encodes for many possible characteristics, but different types of RNA aided by specialized proteins sometimes with external signals express the needed genes. Control of gene expression is of vital importance for an eukaryote’s survival such as the ability of switching genes on/off in accordance with the changes in the environment (Campbell and Reece, 2008). Of a cell’s entire genome, only 15% will be expressed, and in multicellular organisms the genes active will vary according to their specialization. (Fletcher, Ivor & Winter, 2007).
By using Messenger RNA- mRNA molecules carrying the code for insulin are common in the cytoplasm of insulin. Or using DNA probes to find the gene required-A probe is a short single strand of DNA carrying the known genetic code we are looking for. So the location of the DNA probe is known, it is labelled with a radioactive fluorescent marker. The aim is for the probe to attach to its complementary base sequence within DNA extracted from human cells.