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PHYSICAL
MAPPING
I N T R O D U C T I O N
• Genome mapping is an important tool for locating a specific gene on a particular region of
a chromosome and to determine relative distances between genes and molecular markers
on the chromosomes.
• There are two types of Genome mapping:
• Genetic Mapping
• Physical Mapping
P H Y S I C A L M A P P I N G
• Physical mapping is a technique used in molecular biology to find the order and physical
distance between DNA base pairs by DNA markers. It is one of the gene mapping techniques
which can determine the sequence of DNA base pairs with high accuracy.
• A physical map, as related to genomics, is a graphical representation of physical locations of
landmarks or markers (such as genes, variants and other DNA sequences of interest) within a
chromosome or genome.
• Physical mapping uses DNA fragments and DNA markers to assemble larger DNA pieces. With
the overlapping regions of the fragments, researchers can deduce the positions of the DNA
bases.
• A physical map provides detail of the actual physical distance between genetic markers, as well
as the number of nucleotides.
• The three basic varieties of physical mapping are restriction mapping, Sequence tagged
site (STS) mapping,Expressed sequence tag(EST)
• The goal of physical mapping, as a common mechanism under genomic analysis, is to
obtain a complete genome sequence in order to deduce any association between the
target DNA sequence and phenotypic traits.
• If the actual positions of genes which control certain phenotypes are known, it is possible
to resolve genetic diseases by providing advice on prevention and developing new
treatments.
R E S T R I C T I O N M A P P I N G
• Restriction mapping is a technique used in molecular biology to identify the locations of
specific restriction enzyme recognition sites within a DNA molecule.
• Restriction endonucleases, are enzymes that cleave DNA at specific sequences,
generating fragments.
M E T H O D S
1. Isolation of DNA:
- Start by extracting DNA from a biological source, such as cells or tissues.
- Purify the DNA to remove contaminants and ensure a high-quality sample for subsequent analysis.
2. Digestion with Restriction Enzymes:
- Choose appropriate restriction enzymes based on the target DNA sequence. These enzymes recognize specific nucleotide
sequences and cut the DNA at or near those sites.
- Incubate the DNA sample with the selected restriction enzymes. The result is a set of DNA fragments with distinct sizes.
3. Electrophoresis
- Load the digested DNA samples onto an agarose gel.
- Apply an electric field to the gel, causing the DNA fragments to migrate through the gel based on their sizes.
- After electrophoresis, visualize the separated DNA fragments using a staining agent or by incorporating a DNA-intercalating
dye.
4. Southern Blotting (optional):
- Transfer the separated DNA fragments from the gel onto a membrane, typically made of nitrocellulose or nylon.
- This step allows for easier manipulation and analysis of the DNA fragments.
5. Hybridization (optional):
- If performing a Southern blot, hybridize the membrane with a labeled DNA probe.
- The probe is a single-stranded DNA or RNA sequence that is complementary to the target sequence. This step helps
identify specific DNA fragments.
6. Fragment Size Analysis:
- Measure the sizes of the DNA fragments using a reference ladder or marker with known fragment sizes.
- Software or imaging systems can assist in accurately determining the migration distances of the fragments.
7. Construction of Restriction Map:
- Based on the fragment sizes obtained from gel electrophoresis, deduce the relative positions of the restriction sites.
- Construct a linear representation of the DNA molecule indicating the distances between restriction sites. This is the
restriction map.
A D VA N TA G E S O F R E S T R I C T I O N M A P P I N G
1. Genome Analysis: Helps in understanding the structure and organization of a genome
by identifying the locations of specific restriction sites.
2. Gene Mapping: Useful for mapping genes within a DNA sequence, aiding in the
identification of gene locations and their arrangement.
3.DNA Sequencing Assists in sequencing DNA fragments by determining the order of
restriction sites, aiding in the overall sequencing process.
4. Comparative Studies: Facilitates the comparison of different DNA samples by revealing
similarities and differences in their restriction fragment patterns.
• 5. Cloning: Essential in molecular cloning by allowing the precise insertion of DNA
fragments into vectors at specific restriction sites.
• 6. Diagnostic Tool:Acts as a diagnostic tool for genetic diseases or variations by analyzing
the presence or absence of specific restriction sites.
• 7. Evolutionary Studies:Helps in studying the evolution of species by comparing restriction
maps across different organisms.
• 8. Forensic Applications:Used in forensic science to analyze DNA samples and establish
identity or relationships based on restriction fragment patterns.
D I S A D VA N TA G E O F R E S T R I C T I O N
M A P P I N G
• Sample Size Requirements: Restriction mapping typically requires a substantial amount
of DNA for accurate analysis. This can be a limitation when dealing with scarce or precious
samples, as obtaining sufficient quantities of DNA might be challenging.
• Labor-Intensive: The process involves multiple steps, including digestion with restriction
enzymes, gel electrophoresis, and analysis of resulting band patterns. This can be time-
consuming and labor-intensive, especially when compared to more modern and automated
techniques.
• Resolution Limitations: Restriction mapping may have limitations in resolving very small
differences in fragment sizes, particularly when dealing with complex genomes. This can
result in less precise mapping information compared to newer sequencing methods.
• Inability to Identify Sequences: Restriction mapping provides information about the sizes
of DNA fragments but doesn’t reveal the actual DNA sequences. In contrast, DNA
sequencing technologies provide detailed sequence information, allowing for a more
comprehensive understanding of the genetic material.
• Dependency on Restriction Enzymes: The technique relies on the specificity of
restriction enzymes, which recognize and cleave specific DNA sequences. This
dependency can be a limitation when dealing with genomes that have rare or no
recognition sites for certain enzymes.
S E Q U E N C E TA G G E D S I T E M A P P I N G
• It is a relatively short, easily PCR-amplified sequence (200 to 500 bp) which can be
specifically amplified by PCR and detected in the presence of all other genomic sequences
and whose location in the genome is mapped.
• The STS concept was introduced by Olson et al (1989).
• In assessing the likely impact of the Polymerase Chain Reaction (PCR) on human
genome research, they recognized that single-copy DNA sequences of known map
location could serve as markers for genetic and physical mapping of genes along the
chromosome.
M E T H O D S O F S T S M A P P I N G
• Southern Blotting: DNA fragments are separated by gel electrophoresis, transferred to a
membrane, and hybridized with labeled probes to detect specific STS.
• Fluorescence In Situ Hybridization (FISH): Fluorescently labeled probes are hybridized
to chromosomes in situ, allowing visualization of STS locations under a microscope.
• Radiation Hybrid Mapping: Fragments of DNA are irradiated, and the presence or
absence of STS is determined, helping establish their relative order.
• PCR-Based Methods: Techniques like Long-Range PCR or Multiplex PCR are used to
amplify STS, aiding in their detection and mapping.
• Pulsed-Field Gel Electrophoresis (PFGE): Large DNA fragments are separated by
applying alternating electric fields, helping in the construction of physical maps.
• Yeast Artificial Chromosome (YAC) Libraries: YACs carrying genomic inserts are used
to identify and map STS within the context of yeast chromosomes.
• Bacterial Artificial Chromosome (BAC) Libraries: Similar to YACs, BACs are used for
STS mapping, providing a way to maintain and manipulate large genomic fragments.
A D VA N TA G E S O F S T S M A P P I N G
• Improved Search Accuracy: By mapping and structuring text data, STS allows for more
accurate and targeted search queries. Users can narrow down their search criteria based
on specific attributes, resulting in more relevant and precise search results.
• Efficient Information Retrieval: The structured nature of STS mapping enables efficient
retrieval of information. It provides a systematic way to index and organize data, reducing
the time and resources required to locate specific information within a dataset.
• Contextual Understanding: STS mapping considers the relationships and context
between different elements in the text. This contextual understanding enhances the
relevance of search results by taking into account the relationships and associations
between various pieces of information.
• Adaptability to Complex Datasets: In scenarios where data is complex and varied, STS
mapping can adapt to the intricacies of the dataset. This flexibility is particularly useful
when dealing with diverse and large information repositories.
• Enhanced User Experience: Users benefit from a more user-friendly experience when
searching for information. The structured approach simplifies the navigation and
exploration of data, making it easier for users to find what they are looking for.
• Consistent Organization: STS mapping provides a consistent and organized framework
for data. This uniformity aids in maintaining data integrity and ensures a standardized
approach to information organization, which is crucial for large-scale systems.
D I S A D VA N TA G E O F S T S M A P P I N G
• Complex Implementation: Implementing STS mapping can be complex, especially for
large and intricate datasets. Creating an effective mapping structure may require
significant time and resources.
• Resource Intensive: The process of mapping and structuring text data can be resource-
intensive, especially when dealing with extensive datasets. This may lead to increased
storage and processing requirements.
• Maintenance Challenges: Keeping the structured mapping updated and aligned with
evolving data can be challenging. Changes in data formats or additions to the dataset may
necessitate frequent updates to the mapping structure.
• Limited Flexibility: In some cases, the structured approach of STS mapping might lack
the flexibility needed to accommodate dynamic or unstructured data. Adapting the mapping
to diverse information types can be a constraint.
• Learning Curve: Users may experience a learning curve when transitioning to a system
utilizing STS mapping. Familiarizing oneself with the structured search approach may take
time, potentially impacting user adoption.
• Loss of Information Granularity: In an attempt to structure data for efficient search, there
is a risk of losing granularity or fine details present in unstructured data. This loss may
impact the ability to capture subtle nuances or specific details in the information.
• Dependency on Quality of Mapping: The effectiveness of STS mapping heavily relies on
the quality of the mapping structure created. Poorly designed mappings may lead to
inaccurate search results and reduced user satisfaction.
E X P R E S S E D S E Q U E N C E TA G
• Expressed sequence tags (ESTs) are randomly selected clones sequenced from cDNA libraries.
• Each cDNA library is constructed from total RNA or poly (A) RNA derived from a specific tissue
or cell, and thus the library represents genes expressed in the original cellular population.
• A typical EST consists of 300–1000 base pairs (bp) of DNA and is often deposited in a database
as a “single pass read” that is sufficiently long to establish the identity of the expressed gene.
• EST analysis has proved to be a rapid and efficient means of characterizing the massive sets of
gene sequences that are expressed in a life-stage-specific manner in a wide variety of tissues
and organisms; the approach was first applied to the screening of a human brain cDNA library
M E T H O D S O F E S T
• 1. cDNA Library Construction:
• mRNA Extraction: Isolate mRNA from the target tissue or cell type.
• cDNA Synthesis: Convert the mRNA into cDNA using reverse transcriptase.
• Normalization: Reduce abundant transcripts to increase the representation of rare
transcripts.
• 2. cDNA Cloning:
• Vector Insertion: Ligating cDNA into a cloning vector (commonly plasmids).
• Transformation: Introducing the vector into a host organism (usually bacteria) to replicate
the cDNA.
• 3. Sequencing:
• Single-Pass Sequencing: Typically using Sanger sequencing, where only one read is obtained from each
cDNA clone.
• Automated Sequencing: High-throughput methods for sequencing multiple clones simultaneously.
• 4. Sequence Analysis:
• Assembly: Combining overlapping sequences to create longer contiguous sequences (contigs).
• Quality Filtering: Removing low-quality or ambiguous sequences.
• 5. Annotation:
• Comparison with Genomic Databases: Aligning EST sequences with genomic databases to identify
potential gene locations.
• Functional Annotation: Assigning putative functions to the identified genes based on sequence homology.
• 6. EST Clustering and Unigene Construction:
• Clustering: Grouping similar ESTs to represent a single gene, reducing redundancy.
• Unigene Formation: Creating a set of unique gene sequences (unigenes) from the clustered ESTs.
• 7.Database Submission:
• Deposition in Public Databases: Submitting the annotated EST sequences to public
databases for broader access and analysis.
• 8.Gene Expression Studies:
• Quantitative PCR (qPCR): Validating gene expression levels for specific ESTs.
• Microarray Analysis: Studying global gene expression patterns using arrays containing EST
probes.
• 9.Next-Generation Sequencing (NGS):
• RNA-Seq: Using NGS technologies to obtain a comprehensive view of the transcriptome,
surpassing the limitations of traditional EST methods.
A D VA N TA G E S O F E S T
• Rapid Gene Discovery: ESTs provide a rapid and cost-effective method for discovering new
genes. They represent fragments of actively transcribed genes, allowing researchers to identify
and catalog expressed sequences in a particular tissue or under specific conditions.
• Gene Expression Profiling: ESTs enable the study of gene expression patterns across
different tissues, developmental stages, or environmental conditions. This information is crucial
for understanding the regulation and function of genes in various biological processes.
• Identification of Alternative Splicing: ESTs can reveal alternative splicing variants of genes,
providing insights into the diversity of gene products and their potential roles in cellular
processes.
• Functional Annotation: ESTs contribute to the functional annotation of genomes by
associating expressed sequences with potential gene functions. This aids in understanding the
molecular basis of biological functions and pathways.
• Marker Development for Genetic Mapping: ESTs can be used to develop molecular
markers, such as SSRs (simple sequence repeats) or SNPs (single nucleotide
polymorphisms), for genetic mapping and marker-assisted breeding studies.
• Comparative Genomics: ESTs facilitate comparative genomics by allowing the
comparison of gene expression profiles across different species. This helps identify
conserved genes and understand evolutionary relationships.
• Drug Discovery and Disease Research: ESTs play a role in drug discovery by identifying
genes associated with diseases. Understanding the expression patterns of these genes
can aid in the development of targeted therapies.
• Resource for Genome Annotation: EST data contribute to the annotation of genomic
sequences by providing experimental evidence for the presence of genes. This enhances
the accuracy of gene prediction algorithms and improves the overall annotation quality.
• Seed for Full-Length cDNA Sequencing: ESTs can serve as starting points for obtaining
full-length cDNA sequences. This is particularly valuable for acquiring complete coding
sequences and understanding the structure and function of genes.
• Population Studies and Evolutionary Biology: ESTs can be utilized in population
genetic studies to assess genetic diversity and evolutionary processes within a species.
D I S A D VA N TA G E O F E S T
• Fragmented Sequences: ESTs are typically short sequences, representing only a portion
of a gene. This fragmentation can make it challenging to assemble complete gene
sequences and accurately predict gene structures.
• Redundancy: Cloning and sequencing cDNA libraries may result in the identification of the
same gene multiple times, leading to redundant information. This redundancy can
complicate data analysis and interpretation.
• Incompleteness: ESTs may not capture the entire transcriptome, and certain low-
abundance transcripts may be missed. This limitation can result in an incomplete
representation of the expressed genes in a given tissue or condition.
• Bias Toward Highly Expressed Genes: The process of cDNA library construction and
sequencing may favor highly expressed genes, potentially overlooking genes with lower
expression levels. This bias can impact the comprehensiveness of gene discovery.
• No Information on Non-Coding RNAs: ESTs primarily focus on protein-coding genes,
providing limited information about non-coding RNAs, which play important roles in gene
regulation and cellular processes.
• Tissue-Specificity: ESTs obtained from specific tissues may not accurately represent the
entire transcriptome of an organism. The gene expression profile can vary across tissues,
developmental stages, or environmental conditions.
• Lack of Information on Gene Function: While ESTs provide information on the presence
of transcripts, they may not directly reveal the function of the encoded proteins. Additional
experimental work is often needed for functional characterization.
• Technological Advances: With the advent of next-generation sequencing (NGS)
technologies, the limitations associated with traditional Sanger sequencing used for ESTs,
such as lower throughput and higher cost per base, have become more pronounced.
• Limited Information for Evolutionary Studies: While ESTs contribute to comparative
genomics, they may not capture the full complexity of gene evolution. Full-genome
sequencing and transcriptome studies using newer technologies provide more
comprehensive datasets for evolutionary analyses.
• Resource-Intensive: Generating and analyzing EST data can be resource-intensive,
requiring significant time and laboratory resources. This can be a limitation, especially
when more cost-effective and high-throughput sequencing methods are available.
R E F E R E N C E S
• Blackstock, W. P., & Weir, M. P. (1999). Proteomics: quantitative and physical mapping of cellular proteins.
Trends in biotechnology, 17(3), 121-127.
• Deonier, R. C., Waterman, M. S., & Tavaré, S. (2005). Physical Mapping of DNA (pp. 99-119). Springer New
York.
• Golumbic, M. C., Kaplan, H., & Shamir, R. (1994). On the complexity of DNA physical mapping. Advances in
Applied Mathematics, 15(3), 251-261.
• Olson, M., Hood, L., Cantor, C., & Botstein, D. (1989). A common language for physical mapping of the
human genome. Science, 245(4925), 1434-1435.
• Sourdille, P., Cadalen, T., Gay, G., Gill, B., & Bernard, M. (2002). Molecular and physical mapping of genes
affecting awning in wheat. Plant Breeding, 121(4), 320-324.
• Umehara, Y., Inagaki, A., Tanoue, H., Yasukochi, Y., Nagamura, Y., Saji, S., & Minobe, Y. (1995).
Construction and characterization of a rice YAC library for physical mapping. Molecular Breeding, 1, 79-89.

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physical mapping- restriction map, STS map, EST map

  • 2. I N T R O D U C T I O N • Genome mapping is an important tool for locating a specific gene on a particular region of a chromosome and to determine relative distances between genes and molecular markers on the chromosomes. • There are two types of Genome mapping: • Genetic Mapping • Physical Mapping
  • 3. P H Y S I C A L M A P P I N G • Physical mapping is a technique used in molecular biology to find the order and physical distance between DNA base pairs by DNA markers. It is one of the gene mapping techniques which can determine the sequence of DNA base pairs with high accuracy. • A physical map, as related to genomics, is a graphical representation of physical locations of landmarks or markers (such as genes, variants and other DNA sequences of interest) within a chromosome or genome. • Physical mapping uses DNA fragments and DNA markers to assemble larger DNA pieces. With the overlapping regions of the fragments, researchers can deduce the positions of the DNA bases. • A physical map provides detail of the actual physical distance between genetic markers, as well as the number of nucleotides.
  • 4. • The three basic varieties of physical mapping are restriction mapping, Sequence tagged site (STS) mapping,Expressed sequence tag(EST) • The goal of physical mapping, as a common mechanism under genomic analysis, is to obtain a complete genome sequence in order to deduce any association between the target DNA sequence and phenotypic traits. • If the actual positions of genes which control certain phenotypes are known, it is possible to resolve genetic diseases by providing advice on prevention and developing new treatments.
  • 5. R E S T R I C T I O N M A P P I N G • Restriction mapping is a technique used in molecular biology to identify the locations of specific restriction enzyme recognition sites within a DNA molecule. • Restriction endonucleases, are enzymes that cleave DNA at specific sequences, generating fragments.
  • 6. M E T H O D S 1. Isolation of DNA: - Start by extracting DNA from a biological source, such as cells or tissues. - Purify the DNA to remove contaminants and ensure a high-quality sample for subsequent analysis. 2. Digestion with Restriction Enzymes: - Choose appropriate restriction enzymes based on the target DNA sequence. These enzymes recognize specific nucleotide sequences and cut the DNA at or near those sites. - Incubate the DNA sample with the selected restriction enzymes. The result is a set of DNA fragments with distinct sizes. 3. Electrophoresis - Load the digested DNA samples onto an agarose gel. - Apply an electric field to the gel, causing the DNA fragments to migrate through the gel based on their sizes. - After electrophoresis, visualize the separated DNA fragments using a staining agent or by incorporating a DNA-intercalating dye.
  • 7. 4. Southern Blotting (optional): - Transfer the separated DNA fragments from the gel onto a membrane, typically made of nitrocellulose or nylon. - This step allows for easier manipulation and analysis of the DNA fragments. 5. Hybridization (optional): - If performing a Southern blot, hybridize the membrane with a labeled DNA probe. - The probe is a single-stranded DNA or RNA sequence that is complementary to the target sequence. This step helps identify specific DNA fragments. 6. Fragment Size Analysis: - Measure the sizes of the DNA fragments using a reference ladder or marker with known fragment sizes. - Software or imaging systems can assist in accurately determining the migration distances of the fragments. 7. Construction of Restriction Map: - Based on the fragment sizes obtained from gel electrophoresis, deduce the relative positions of the restriction sites. - Construct a linear representation of the DNA molecule indicating the distances between restriction sites. This is the restriction map.
  • 8. A D VA N TA G E S O F R E S T R I C T I O N M A P P I N G 1. Genome Analysis: Helps in understanding the structure and organization of a genome by identifying the locations of specific restriction sites. 2. Gene Mapping: Useful for mapping genes within a DNA sequence, aiding in the identification of gene locations and their arrangement. 3.DNA Sequencing Assists in sequencing DNA fragments by determining the order of restriction sites, aiding in the overall sequencing process. 4. Comparative Studies: Facilitates the comparison of different DNA samples by revealing similarities and differences in their restriction fragment patterns.
  • 9. • 5. Cloning: Essential in molecular cloning by allowing the precise insertion of DNA fragments into vectors at specific restriction sites. • 6. Diagnostic Tool:Acts as a diagnostic tool for genetic diseases or variations by analyzing the presence or absence of specific restriction sites. • 7. Evolutionary Studies:Helps in studying the evolution of species by comparing restriction maps across different organisms. • 8. Forensic Applications:Used in forensic science to analyze DNA samples and establish identity or relationships based on restriction fragment patterns.
  • 10. D I S A D VA N TA G E O F R E S T R I C T I O N M A P P I N G • Sample Size Requirements: Restriction mapping typically requires a substantial amount of DNA for accurate analysis. This can be a limitation when dealing with scarce or precious samples, as obtaining sufficient quantities of DNA might be challenging. • Labor-Intensive: The process involves multiple steps, including digestion with restriction enzymes, gel electrophoresis, and analysis of resulting band patterns. This can be time- consuming and labor-intensive, especially when compared to more modern and automated techniques. • Resolution Limitations: Restriction mapping may have limitations in resolving very small differences in fragment sizes, particularly when dealing with complex genomes. This can result in less precise mapping information compared to newer sequencing methods.
  • 11. • Inability to Identify Sequences: Restriction mapping provides information about the sizes of DNA fragments but doesn’t reveal the actual DNA sequences. In contrast, DNA sequencing technologies provide detailed sequence information, allowing for a more comprehensive understanding of the genetic material. • Dependency on Restriction Enzymes: The technique relies on the specificity of restriction enzymes, which recognize and cleave specific DNA sequences. This dependency can be a limitation when dealing with genomes that have rare or no recognition sites for certain enzymes.
  • 12. S E Q U E N C E TA G G E D S I T E M A P P I N G • It is a relatively short, easily PCR-amplified sequence (200 to 500 bp) which can be specifically amplified by PCR and detected in the presence of all other genomic sequences and whose location in the genome is mapped. • The STS concept was introduced by Olson et al (1989). • In assessing the likely impact of the Polymerase Chain Reaction (PCR) on human genome research, they recognized that single-copy DNA sequences of known map location could serve as markers for genetic and physical mapping of genes along the chromosome.
  • 13. M E T H O D S O F S T S M A P P I N G • Southern Blotting: DNA fragments are separated by gel electrophoresis, transferred to a membrane, and hybridized with labeled probes to detect specific STS. • Fluorescence In Situ Hybridization (FISH): Fluorescently labeled probes are hybridized to chromosomes in situ, allowing visualization of STS locations under a microscope. • Radiation Hybrid Mapping: Fragments of DNA are irradiated, and the presence or absence of STS is determined, helping establish their relative order. • PCR-Based Methods: Techniques like Long-Range PCR or Multiplex PCR are used to amplify STS, aiding in their detection and mapping.
  • 14. • Pulsed-Field Gel Electrophoresis (PFGE): Large DNA fragments are separated by applying alternating electric fields, helping in the construction of physical maps. • Yeast Artificial Chromosome (YAC) Libraries: YACs carrying genomic inserts are used to identify and map STS within the context of yeast chromosomes. • Bacterial Artificial Chromosome (BAC) Libraries: Similar to YACs, BACs are used for STS mapping, providing a way to maintain and manipulate large genomic fragments.
  • 15. A D VA N TA G E S O F S T S M A P P I N G • Improved Search Accuracy: By mapping and structuring text data, STS allows for more accurate and targeted search queries. Users can narrow down their search criteria based on specific attributes, resulting in more relevant and precise search results. • Efficient Information Retrieval: The structured nature of STS mapping enables efficient retrieval of information. It provides a systematic way to index and organize data, reducing the time and resources required to locate specific information within a dataset. • Contextual Understanding: STS mapping considers the relationships and context between different elements in the text. This contextual understanding enhances the relevance of search results by taking into account the relationships and associations between various pieces of information.
  • 16. • Adaptability to Complex Datasets: In scenarios where data is complex and varied, STS mapping can adapt to the intricacies of the dataset. This flexibility is particularly useful when dealing with diverse and large information repositories. • Enhanced User Experience: Users benefit from a more user-friendly experience when searching for information. The structured approach simplifies the navigation and exploration of data, making it easier for users to find what they are looking for. • Consistent Organization: STS mapping provides a consistent and organized framework for data. This uniformity aids in maintaining data integrity and ensures a standardized approach to information organization, which is crucial for large-scale systems.
  • 17. D I S A D VA N TA G E O F S T S M A P P I N G • Complex Implementation: Implementing STS mapping can be complex, especially for large and intricate datasets. Creating an effective mapping structure may require significant time and resources. • Resource Intensive: The process of mapping and structuring text data can be resource- intensive, especially when dealing with extensive datasets. This may lead to increased storage and processing requirements. • Maintenance Challenges: Keeping the structured mapping updated and aligned with evolving data can be challenging. Changes in data formats or additions to the dataset may necessitate frequent updates to the mapping structure.
  • 18. • Limited Flexibility: In some cases, the structured approach of STS mapping might lack the flexibility needed to accommodate dynamic or unstructured data. Adapting the mapping to diverse information types can be a constraint. • Learning Curve: Users may experience a learning curve when transitioning to a system utilizing STS mapping. Familiarizing oneself with the structured search approach may take time, potentially impacting user adoption. • Loss of Information Granularity: In an attempt to structure data for efficient search, there is a risk of losing granularity or fine details present in unstructured data. This loss may impact the ability to capture subtle nuances or specific details in the information. • Dependency on Quality of Mapping: The effectiveness of STS mapping heavily relies on the quality of the mapping structure created. Poorly designed mappings may lead to inaccurate search results and reduced user satisfaction.
  • 19. E X P R E S S E D S E Q U E N C E TA G • Expressed sequence tags (ESTs) are randomly selected clones sequenced from cDNA libraries. • Each cDNA library is constructed from total RNA or poly (A) RNA derived from a specific tissue or cell, and thus the library represents genes expressed in the original cellular population. • A typical EST consists of 300–1000 base pairs (bp) of DNA and is often deposited in a database as a “single pass read” that is sufficiently long to establish the identity of the expressed gene. • EST analysis has proved to be a rapid and efficient means of characterizing the massive sets of gene sequences that are expressed in a life-stage-specific manner in a wide variety of tissues and organisms; the approach was first applied to the screening of a human brain cDNA library
  • 20. M E T H O D S O F E S T • 1. cDNA Library Construction: • mRNA Extraction: Isolate mRNA from the target tissue or cell type. • cDNA Synthesis: Convert the mRNA into cDNA using reverse transcriptase. • Normalization: Reduce abundant transcripts to increase the representation of rare transcripts. • 2. cDNA Cloning: • Vector Insertion: Ligating cDNA into a cloning vector (commonly plasmids). • Transformation: Introducing the vector into a host organism (usually bacteria) to replicate the cDNA.
  • 21. • 3. Sequencing: • Single-Pass Sequencing: Typically using Sanger sequencing, where only one read is obtained from each cDNA clone. • Automated Sequencing: High-throughput methods for sequencing multiple clones simultaneously. • 4. Sequence Analysis: • Assembly: Combining overlapping sequences to create longer contiguous sequences (contigs). • Quality Filtering: Removing low-quality or ambiguous sequences. • 5. Annotation: • Comparison with Genomic Databases: Aligning EST sequences with genomic databases to identify potential gene locations. • Functional Annotation: Assigning putative functions to the identified genes based on sequence homology. • 6. EST Clustering and Unigene Construction: • Clustering: Grouping similar ESTs to represent a single gene, reducing redundancy. • Unigene Formation: Creating a set of unique gene sequences (unigenes) from the clustered ESTs.
  • 22. • 7.Database Submission: • Deposition in Public Databases: Submitting the annotated EST sequences to public databases for broader access and analysis. • 8.Gene Expression Studies: • Quantitative PCR (qPCR): Validating gene expression levels for specific ESTs. • Microarray Analysis: Studying global gene expression patterns using arrays containing EST probes. • 9.Next-Generation Sequencing (NGS): • RNA-Seq: Using NGS technologies to obtain a comprehensive view of the transcriptome, surpassing the limitations of traditional EST methods.
  • 23. A D VA N TA G E S O F E S T • Rapid Gene Discovery: ESTs provide a rapid and cost-effective method for discovering new genes. They represent fragments of actively transcribed genes, allowing researchers to identify and catalog expressed sequences in a particular tissue or under specific conditions. • Gene Expression Profiling: ESTs enable the study of gene expression patterns across different tissues, developmental stages, or environmental conditions. This information is crucial for understanding the regulation and function of genes in various biological processes. • Identification of Alternative Splicing: ESTs can reveal alternative splicing variants of genes, providing insights into the diversity of gene products and their potential roles in cellular processes. • Functional Annotation: ESTs contribute to the functional annotation of genomes by associating expressed sequences with potential gene functions. This aids in understanding the molecular basis of biological functions and pathways.
  • 24. • Marker Development for Genetic Mapping: ESTs can be used to develop molecular markers, such as SSRs (simple sequence repeats) or SNPs (single nucleotide polymorphisms), for genetic mapping and marker-assisted breeding studies. • Comparative Genomics: ESTs facilitate comparative genomics by allowing the comparison of gene expression profiles across different species. This helps identify conserved genes and understand evolutionary relationships. • Drug Discovery and Disease Research: ESTs play a role in drug discovery by identifying genes associated with diseases. Understanding the expression patterns of these genes can aid in the development of targeted therapies. • Resource for Genome Annotation: EST data contribute to the annotation of genomic sequences by providing experimental evidence for the presence of genes. This enhances the accuracy of gene prediction algorithms and improves the overall annotation quality.
  • 25. • Seed for Full-Length cDNA Sequencing: ESTs can serve as starting points for obtaining full-length cDNA sequences. This is particularly valuable for acquiring complete coding sequences and understanding the structure and function of genes. • Population Studies and Evolutionary Biology: ESTs can be utilized in population genetic studies to assess genetic diversity and evolutionary processes within a species.
  • 26. D I S A D VA N TA G E O F E S T • Fragmented Sequences: ESTs are typically short sequences, representing only a portion of a gene. This fragmentation can make it challenging to assemble complete gene sequences and accurately predict gene structures. • Redundancy: Cloning and sequencing cDNA libraries may result in the identification of the same gene multiple times, leading to redundant information. This redundancy can complicate data analysis and interpretation. • Incompleteness: ESTs may not capture the entire transcriptome, and certain low- abundance transcripts may be missed. This limitation can result in an incomplete representation of the expressed genes in a given tissue or condition.
  • 27. • Bias Toward Highly Expressed Genes: The process of cDNA library construction and sequencing may favor highly expressed genes, potentially overlooking genes with lower expression levels. This bias can impact the comprehensiveness of gene discovery. • No Information on Non-Coding RNAs: ESTs primarily focus on protein-coding genes, providing limited information about non-coding RNAs, which play important roles in gene regulation and cellular processes. • Tissue-Specificity: ESTs obtained from specific tissues may not accurately represent the entire transcriptome of an organism. The gene expression profile can vary across tissues, developmental stages, or environmental conditions. • Lack of Information on Gene Function: While ESTs provide information on the presence of transcripts, they may not directly reveal the function of the encoded proteins. Additional experimental work is often needed for functional characterization.
  • 28. • Technological Advances: With the advent of next-generation sequencing (NGS) technologies, the limitations associated with traditional Sanger sequencing used for ESTs, such as lower throughput and higher cost per base, have become more pronounced. • Limited Information for Evolutionary Studies: While ESTs contribute to comparative genomics, they may not capture the full complexity of gene evolution. Full-genome sequencing and transcriptome studies using newer technologies provide more comprehensive datasets for evolutionary analyses. • Resource-Intensive: Generating and analyzing EST data can be resource-intensive, requiring significant time and laboratory resources. This can be a limitation, especially when more cost-effective and high-throughput sequencing methods are available.
  • 29. R E F E R E N C E S • Blackstock, W. P., & Weir, M. P. (1999). Proteomics: quantitative and physical mapping of cellular proteins. Trends in biotechnology, 17(3), 121-127. • Deonier, R. C., Waterman, M. S., & Tavaré, S. (2005). Physical Mapping of DNA (pp. 99-119). Springer New York. • Golumbic, M. C., Kaplan, H., & Shamir, R. (1994). On the complexity of DNA physical mapping. Advances in Applied Mathematics, 15(3), 251-261. • Olson, M., Hood, L., Cantor, C., & Botstein, D. (1989). A common language for physical mapping of the human genome. Science, 245(4925), 1434-1435. • Sourdille, P., Cadalen, T., Gay, G., Gill, B., & Bernard, M. (2002). Molecular and physical mapping of genes affecting awning in wheat. Plant Breeding, 121(4), 320-324. • Umehara, Y., Inagaki, A., Tanoue, H., Yasukochi, Y., Nagamura, Y., Saji, S., & Minobe, Y. (1995). Construction and characterization of a rice YAC library for physical mapping. Molecular Breeding, 1, 79-89.