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Submitted tosubmitted by

MR .PRASHANT RICHABHATIA

SEC K77B1ROLLN

O 18

BTECH BIOTECH INTEGRATED MBA

EXPRESSED SEQUENCE TAGS

BIOINFORMATICS

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Acknowledgement

Gratitude is the hardest emotion to express and often

one doesnot find adequate words to convey that entire

one feels .those who help me to attain some thing better all the time deserve my highest attention

,thankfulness and deep sincere regards.it gives me

tremendous pleasure in acknowledging the valuable

assistance extended to me by various personalities in

success of this term paper.iam indebeted to my teacher

MR. PRASHANTreativeness, interest and enthusiasmgave a new dimension to my work with a motto to

seek ,to strive and not to yield.HE encouraged me to

make project and helped to solve my problems .Also I would like to express my gratitude to parents who were present in this project visiblyall I

cannot be mentioned but none is forgotten.

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INDEX

PAGE NO TOPIC

4 INTRODUCTION

5 SOURCES OF DATA

6 TISSUE INFORMATION

7 HOW EST ARE MADE

10 Hitchhiker's guide

11 EST INDEX

11 ADVANTAGES/DISADVANTAGES OF EST

12 APPLICATIONS

13 CONCLUSION

14 REFRENCES

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INTRODUCTION

The expressed sequence tag (EST) is a short sub-sequence of a transcribed cDNA sequence. It may

be used to identify various gene transcripts, and are important in gene discovery and gene sequence

determination. The identification of ESTs has proceeded rapidly, with approximately 65.9 million

ESTs now available in public databases .

The EST is mainly produced by a one-shot sequencing of a cloned mRNA (i.e. sequencing of

several hundred base pairs from an end of a cDNA clone taken from a cDNA library). The resulting

sequence is a relatively low quality fragment whose length is limited by current technology toapproximately 500 to 800 nucleotides. Because these clones consist of DNA, that is complementary

to mRNA, the ESTs represent actually the portions of an expressed genes. They may be present in

the database as either cDNA/mRNA sequence or as the reverse complement of the mRNA, the

template strand.

The ESTs can be mapped to various specific chromosome locations usingphysical mapping

techniques, such as radiation hybrid mapping, Happy mapping, orFISH.Or, if the genome of the

organism that originated the EST have been sequenced, one can align the EST sequence to that

genome using an computer.

The current understanding of the human set of genes ,includes the existence of thousands of genes

based solely on EST evidence. ESTs has become a important tool to refine the predicted transcripts

for those genes, which leads to the prediction of their protein products and ultimately their function.

Moreover, the situation in which those ESTs are obtained (tissue, organ, disease state - e.g. cancer)

gives information on the conditions in which the corresponding gene is acting. ESTs contain enough

information to permit the design of precise probes forDNA microarrays that then can be used to

determine the gene expression.

Sources of data and annotations

dbEST

The dbEST is an division of Genbank established in 1992. As forGenBank, data in dbEST is directly

submitted by various laboratories worldwide. Scientists of NCBI created dbEST to organize,

retrive,store, and provide access to public EST data that has already accumulated and that continues

to grow daily. Using dbEST, a scientist can access not only data on human ESTs but information on

ESTs from over 300 other organisms as well. Whenever possible, the NCBI scientists make

annotation the EST record with any known information. For example, if an EST matches a DNA

sequence that codes for a known gene with a known function, that gene's name and function are

placed on the EST record. The Annotation produced EST records allows public to utilize dbEST as

for gene discovery. By using a database search tool, such as NCBIs BLAST, any interested person

can conduct sequence similarity searches against dbEST.

EST contigs

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As ,because of the way ESTs are sequenced, many distinct expressed sequence tags are partial

sequences that correspond to the same mRNA of the organism. In the effort to reduce the number of

expressed sequence tags for downstream gene discovery analyses, several groups assembled

expressed sequence tags into EST contigs. Different example of resources that provide EST contigs

include:

TIGR gene indices Unigene

Because an gene can be expressed as mRNA ,many times, ESTs ultimately derived from this mRNA

may be redundant. That is, there may be many identical, or similar, copies of the same EST. Such

an redundancy and overlapping means that when someone searches dbEST for a particular EST, they

may retrieve a list of tags, many of which represent the same gene. Searching through all of these

identical ESTs can be very time consuming. To resolve the redundancy and the overlapping problem

NCBI investigators developed the UniGene database UniGene automatically partitions GenBank

sequences into a non-redundant set of gene-oriented clusters.

Although, it is widely recognized that the production of ESTs constitutes an efficient strategy forthe identification of genes, it is important to acknowledge that despite its advantages, there are

several limitations associated with the EST approach. One is that it is very difficult to isolate mRNA

from different tissues and cell types.

Second, is that important gene regulatory sequences are found within an intron. Because ESTs are

small segments of cDNA, generated from a mRNA in which the introns have been removed, much

valuable information may be lost by focusing only on cDNA sequencing. Despite of the limitations,

ESTs continue to be very valuable in characterizing the human genome, and genomes of other

organisms. They have enabled the mapping of many genes to chromosomal sites and have also

assisted in the discovery of many new genes.

STACK

Constructing EST contigs is not trivial and may yield artifacts i.e (contigs that contain two distinct

gene products). When the complete genome sequence of an organism is available and transcripts are

annotated, it is easy to bypass contig assembly and directly match the founded transcripts with ESTs.

This approach is used in the TissueInfo system and makes it easy to link annotations in the genomic

database to tissue information provided by EST data.

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from MOCCAdb is a curated, open-access, marker data resource for researchers working on Coffea

genus,the Rubiaceaefamily or related species of the Asterid clade (Solanaceae).

It recently has , keepsdata about molecular markers, mainly microsatelite (SSR) markers, developed

on sequences from the two cultivated coffee species, C. canephora (Robusta) or C.arabica.

It gives the easy access to data such as PCR assays conditions, cross amplification within related

species, locus position on different linkage maps and diversity parameters. It also contains the

sequences, both from genomic DNA and ESTs (expressed sequence tags) which were used to design

the markers. All data has been validated by published studies/ongoing research.

Our goal is to facilitate the study of cross-species homology relationships using information derived

from public projects involved in genomic and EST sequencing and to provide a tool for comparative

genomic approaches such as genome mapping and genetic diversity studies.

Tissue information

High-throughput analyses of ESTs may encounter, similar data management challenges. The first

challenge is that 1) tissue provenance of EST libraries is described in plain English in dbEST. This

makes it difficult to write programs thatcan non ambiguously determine that two EST libraries

were sequenced from the a same tissue. Similarly, the disease conditions for the tissue are not

annotated in a computationally and friendly manner.

For example, cancer origin of a library is often mixed with the tissue name (example, the tissue name

"glioblastoma" indicates that the EST library was sequenced from brain tissue and the disease

condition is cancer). With an notable exception of cancer, the disease condition is often not recorded

in dbEST entries. The TissueInfo project was started in 2000 to help with these challenges.

The project provides curated data (updated daily) to disambiguate about the tissue origin and disease

state , offers a tissue ontology that links tissues and organs by "is part of" relationships , it formalizes

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knowledge that hypothalamus is part of brain, and that brain is part of the central nervous system and

distributes the open-source software for linking transcript annotations from sequenced genomes to

various tissue expression profiles calculated with data in dbEST .

Investigators are working hard to sequence and assemble the genomes of various organisms,

including the mouse and human, for a number of important reasons. Although important goals of any

sequencing project isbe to obtain a genomic sequence and identify a complete set of genes, theultimate goal is to gain an understanding of when, where, and how a gene is turned on, a process

commonly referred to as gene expression.

Once we begin to understand where and how a gene is expressed under normal circumstances, we

can then study what happens in an altered state, such as in disease. To accomplish the latter goal,

however, researchers must identify and study the protein, or proteins, coded for by a gene.

As one can imagine, finding a gene that codes for a protein, or proteins, is not easy. The scientists

would start their search by defining a biological problem and developing a strategy for researching

the problem. Often, a search of the scientific literature provided various clues about how to proceed.

For example, other laboratories may have published data that established a link between a particularprotein and a disease of interest. Researchers would then work to isolate that protein, determine its

function, and locate the gene that coded for the protein.other scientists could conduct what is referred

to as linkage studies to determine the chromosomal location of a particular gene. Once the

chromosomal location was determined, the scientists would use biochemical methods to isolate the

gene and related protein.The either way,of these methods took a great deal of timeyears in some

casesand yielded the location and description of only a small percentage of the genes found in the

human genome.

Now, however, the time required to locate and fully describe a gene is rapidly decreasing, t a

technology used to generate what are called Expressed Sequence Tags, orESTs. ESTs provide

researchers with the quick and inexpensive way for discovering new genes, for obtaining data on

gene expression and regulation, and for constructing genome maps. Today, researchers using ESTs to

study the human genome find themselves riding the wave of scientific discovery, the likes of which

have never been seen .

What Are ESTs and How Are They Made?

ESTs are small pieces of DNA sequence (usually 200 to 500 nucleotides long) that are made by

sequencing either one or both ends of an expressed gene. The sequence bits of DNA that represent

genes expressed in certain cells, tissues, or organs from different organisms and use the "tags" to

gene out of a portion of chromosomal DNA by matching base pairs. The challenge associated with

identifying genes from genomic sequences varies among organisms and is dependent basically upon

genome size and on thethe presence or absence of introns, the intervening DNA sequences

interrupting the protein coding sequence of a gene.

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Separating the Wheat from the Chaff: Using mRNA to Generate cDNA

The gene identification is very difficult in humans, because most of our genome is composed of

many introns interspersed with a relative few DNA coding sequences, or genes. These genes are

expressed as proteins, a complex process composed of two mainly two steps.

1) Each gene must be convertedor transcribed, into messenger RNA (mRNA), RNA that servesas a template for protein synthesis.

2) The resulting mRNA then guides the synthesis of a protein through a process called

translation.The mRNAs in a cell do not contain sequences from the regions between genes,

nor from the non-coding introns that are present within the genes. Therefore, isolating mRNA

is key to the finding of expressed genes in the vast expanse of the human genome.

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Figure 1. An overview of the process of protein synthesis.

Protein synthesis is the process where the DNA codes for the amino acids and proteins. The process

is divided into two parts: transcription and translation. During transcription, one strand of a

DNA,which is the double helix and is used as a template by mRNA polymerase to synthesize a

mRNA. During the progress of this step, mRNA passes through various phases, including called

splicing, where the non-coding sequences are removed. In the next step, translation, the mRNA

guides the synthesis of the protein by adding amino acids, one by one, as dictated by the DNA and

represented by the mRNA.

The problem, however, is that mRNA is very unstable outside of a cell; as a result of which the ,

scientists use special enzymes to convert it to complementary DNA (cDNA). ThecDNA is a muchmore stable compound and, basically because it was generated from a mRNA, in which the introns

have been removed, cDNA represents only expressed DNA sequence.

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The cDNA is an form of DNA prepared in the laboratory using an enzyme called reverse

transcriptase.The cDNA production is a reverse of the usual process of transcription in cells because

the procedure uses mRNA as a template rather than the DNA. Unlike genomic DNA,/cDNA

contains only expressed DNA sequences/exons.

From cDNAs to ESTs

Once if the cDNA representing an expressed gene has been isolated, scientists can then

sequence a few hundred nucleotides from either end of the molecule to create two different kinds of

ESTs. Sequencing only the beginning portion of the cDNA produces what is called a 5' EST. A 5'

EST is obtained from any portion of a transcript that usually codes for a protein. These regions,

tend to be conserved across the species and do not change much within a gene family.

Sequencing, the ending portion of the cDNA molecule produces what is called a 3' EST. As, these

ESTs are made from the 3' end of a transcript, they fall within non-coding, or untranslated regions

(UTRs), and therefore tend to exhibit less cross-species conservation than do coding sequences.

A "gene family" is a group of closely related genes that produces similar protein products.

A UTR is that part of a gene that is not translated into protein.

Figure 2. An overview of how ESTs are generated.

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A hitchhiker's guide to expressed sequence tag (EST) analysis

Expressed sequence tag (EST) sequencing projects are underway for numerous organisms, generating

millions of short, single-pass nucleotide sequence reads, accumulating in EST databases. Extensive

computational strategies have been developed to organize and analyse both small- and large-scale

EST data for gene discovery, transcript and single nucleotide polymorphism analysis as well as

functional annotation of putative gene products.

They basically ,provide an overview of the significance of ESTs in the genomic era, their properties

and the applications of ESTs. Methods adopted for each step of EST analysis by various research

groups have been compared. Challenges that lie ahead in organizing and analysing the ever

increasing EST data have also been identified.

The most appropriate software tools for EST pre-processing, clustering and assembly, database

matching and functional annotation have been compiled (available online from). We propose a road

map for EST analysis to accelerate the effective analyses of EST data sets. An investigation of EST

analysis platforms reveals that they all terminate prior to downstream functional annotation including

gene ontologies, motif/pattern analysis and pathway mapping.

EST Index ConstructionThe major goal of an EST databases is to organize ,construct and consolidate the largely redundant

EST data to improve maximally the quality of the sequence information so thedata can be used to

extract full-length cDNAs. The process includes a bunch of preprocessingstep that removes vector

contaminants and masks repeats. Vecscreen, introduced in can be used to screen out bacterial vectorsequences. This is followed by a clustering step that associates EST sequences with unique genes.

The next stepis to derive consensus sequences by fusing redundant, overlapping ESTs and to correct

errors, especially frameshift errors. As a result step results in longer EST contigs. Finally, the coding

regions are defined through the use of HMMbasedgene-finding algorithms .it helps to exclude the

potentialintron and 3_-untranslated sequences. Once the coding sequence is identified, it canbe

annotated by translating it into protein sequences for database similarity searching.To go another step

further, compiled ESTs can be used to align with the genomic sequence, if available to identify the

genome locus of the expressed gene as well as intronexon boundaries of the gene. The clustering

process that reduces the EST redundancy and produces a collectionof nonredundant and annotated

EST sequences is known as gene index construction.

DISADVANTAGES OF USING EST

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However, there are number of many drawbacks of using ESTs for te use of expression profile

analysis.ESTsequences are of lowquality because they are automatically generated , without

verification and thus contain high error of rates. the Many bases are ambiguously determined,

represented by Ns. Common errors also include frameshift errors andartifactual stop codons,

resulting in failures of translating the sequences. In addition,there is often contaminationby vector

sequence, introns (from unsplicedRNAs), ribosomalRNA (rRNA), mitochondrialRNA, among

others. ESTs represent only partialsequences of genes. various Gene sequences at the 3_ endtend to be more heavily representedthan those at the 5_ end because reverse transcription is

primed with oligo(dT)primers. Unfortunately, the sequences from the 3_ end are also most error

pronebecause of the low base-call quality at the start of sequence reads. Another problemof ESTs

is the presence of chimeric clones owing to cloning artifacts in libraryconstruction, in which more

than one transcript is ligated in a clone resulting inthe 5_ end of a sequence representing one gene

and the 3_ end another gene. It hasbeen estimated that up to 11% of cDNA clones may be

chimeric. Another fundamental problem with EST profiling is that it predominantly represents

highly expressed,abundant transcripts. Weakly expressed genes are hardly found in a EST

sequencing survey.

Outline of steps to process EST sequences for construction of the UniGene

database

A UniGene is the NCBI EST cluster database.Each cluster is a set of overlapping EST sequences

that are computationally processedto represent a single expressed gene. The database is constructed based on combinedinformationfromdbEST,GenBankmRNAdatabase,andelectronically spliced

genomic DNA. Only ESTs with 3_ poly-A ends are clustered to minimize the the problemof

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chimerism. The resulting 3_ EST sequences provide more unique representation of the transcripts.

The next step is to remove contaminant sequences that includebacterial vectors and linker sequences.

The cleaned ESTs are used to search against adatabase ofknownunique genes(EGADdatabase) with

theBLASTprogram.Thecompilingstep identifies sequence overlaps and derives sequence consensus

using theCAP3program.During this step, errors in individual ESTs are corrected; the sequencesare

then partitioned into clusters and assembled into contigs. The final result is a set of nonredundant,

gene-oriented clusters known as UniGene clusters.

ADVANTAGES Various advantages are-: 1) EST technology is still widely used. Thisis because ESTlibraries can be easily generated from various cell lines, tissues, organs, and at

variousdevelopmental stages. ESTs can also facilitate the unique identification of a genefrom

a cDNA library; a short tag can lead to a cDNA clone. 2)Although individual ESTs\are proneto error, an entire collection of ESTs contains valuable information. Often,after consolidation

of multiple EST sequences, a full-length cDNA can be derived.3)By searching a

nonredundant EST collection, one can identify potential genes ofinterest.The rapidaccumulation of EST sequences has prompted the establishment of

public and

APPLICATIONS

Gene Discovery through Expressed Sequence Tag

Sequencing in Trypanosoma cruzi

The analysis of expressed sequence tags basially constitutes a useful approach for gene identificationthat, in that case of human pathogens, may result in the identification of new targets for

chemotherapy and vaccine development. As the part of the Trypanosoma cruzi genome project, we

have partially sequenced the 5 ends of 1,949 clones to generate ESTs. The clones were randomly

selected from the normalized , CL Brener epimastigote cDNA library. the total of which in 14.6% of

the clones were homologous to previously identified T. cruzi genes, while 18.4% of which have had

significant matches to genes from other organisms in the database. The overall total of the 67% of

the ESTs had no matches with the database, and thus, some of them might be T. cruzi-specific genes.

The different Functional groups of those sequences which might match in the database were made

according to their basic biological functions. The two largest categories were protein synthesis

(23.3%) and cell surface molecules (10.8%).

Expressed sequence tags and their application for plantresearch

The Expressed Sequence Tags (ESTs) are short in length, and are usually containing unedited

sequences obtained by single-pass sequencing of cDNA clones from any cDNA library. After

analysis and comparison of ESTs, they can provide information on gene expression, function and

evolution. the Large-scale EST sequencing has become an attractive alternative to plant genome

sequencing.

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Recently, in the plant EST collections have in general as many as 3.8 million sequences from about

200 species. They have proved to be important tool for gene discovery and plant metabolism

analysis. Several plant-specific EST databases have been created which provide access to sequence

data and bioinformatics-based tools for data mining.

Searching EST collections allows pre-selection of genes for the prepration of the cDNA arrays,

targeted to bring about the maximum information on the various specialized processes, like stressresponse, symbiotic nitrogen fixation etc. Also, ESt-based molecular markers such as SNP, SSR, and

indels are fast developing tools for breeders and researchers.

CONCLUSION

The EST is mainly produced by a one-shot sequencing of a cloned mRNA (i.e. sequencing ofseveral hundred base pairs from an end of a cDNA clone taken from a cDNA library). The resulting

sequence is a relatively low quality fragment whose length is limited by current technology to

approximately 500 to 800 nucleotides. Because these clones consist of DNA, that is complementary

to mRNA, the ESTs represent actually the portions of an expressed genes. They may be present in

the database as either cDNA/mRNA sequence or as the reverse complement of the mRNA, the

template strand.

The ESTs can be mapped to various specific chromosome locations usingphysical mapping

techniques, such as radiation hybrid mapping, Happy mapping, orFISH.Or, if the genome of the

organism that originated the EST have been sequenced, one can align the EST sequence to that

genome using an computer. The analysis of expressed sequence tags basially constitutes a useful

approach for gene identification that, in that case of human pathogens, may result in the identification

of new targets for chemotherapy and vaccine development. As the part of the

Trypanosoma cruzi genome project, we have partially sequenced the 5 ends of 1,949 clones to

generate ESTs. The Expressed Sequence Tags (ESTs) are short in length, and are usually containing

unedited sequences obtained by single-pass sequencing of cDNA clones from any cDNA library.

After analysis and comparison of ESTs, they can provide information on gene expression, function

and evolution. the Large-scale EST sequencing has become an attractive alternative to plant genome

sequencing.Expressed sequence tag (EST) sequencing projects are underway for numerous

organisms, generating millions of short, single-pass nucleotide sequence reads, accumulating in ESTdatabases. Extensive computational strategies have been developed to organize and analyse both

small- and large-scale EST data for gene discovery, transcript and single nucleotide polymorphism

analysis as well as functional annotation of putative gene products. The most appropriate software

tools for EST pre-processing, clustering and assembly, database matching and functional annotation

have been compiled (available online from). We propose a road map for EST analysis to accelerate

the effective analyses of EST data sets. An investigation of EST analysis platforms reveals that they

all terminate prior to downstream functional annotation including gene ontologies, motif/pattern

analysis and pathway mapping.

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REFRENCES

http://biolinfo.org/EST

www.ncbi.nlm.nih.gov/UniGene/

www.ncbi.nlm.nih.gov/SAGE\/

WWW.EST.BIOINFO.ORG/HTML/

WWW.BIOWORLD.COM

WWW.BIOMFUNCTION.ORG/

WWW.BIOLINE.INFO.GOV/

WWW.BIOGENOME.COM

WWW.HUMANGENOME.ORG/

WWW.EST%20.COM

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