L5_DNA SEQUENCING APPROACH
DNA Sequencing Techniques
Page 1: Basics of DNA Sequencing
DNA Sample: SCAC GOGGGGCCAGCTG
Protein Sequence: PRO CCCTC
Sample Sequences: Various sequences highlighting DNA variability
Page 2: Overview of Sequencing Techniques
Direct Sequencing of PCR Product
Genome Sequencing Approaches:
Hierarchical Shotgun Sequencing
Whole Genome Shotgun Sequencing
Single End and Paired End Sequencing
Page 3: Direct Sequencing of PCR Product
Description: Direct sequencing of amplified DNA focusing on specific target genes.
Data Quality: High-quality sequencing data demand strong, specific PCR product.
Advantages:
Eliminates time-consuming cloning procedures.
Avoids repetitive operations like template extraction.
Applications:
Gene mutation detection
Genetic disease diagnosis
Single nucleotide polymorphism research
Microorganism species identification
Steps:
Extract DNA from samples.
Perform PCR on target genes.
Purify PCR product.
Conduct sequencing.
Page 4: Genome Sequencing Approaches
Hierarchical Shotgun Sequencing:
Creates a physical map of the genome before sequencing.
Involves large pieces of DNA analysis.
Whole Genome Shotgun Sequencing:
Randomly shears entire genome into small fragments.
No need for a physical map; relies on computer assembly.
Factors Determining Sequencing Strategy:
Genome size
Chromosomal structure
Repeat content and characteristics
Page 5: Hierarchical Shotgun Sequencing Details
Also Known As:
BAC-by-BAC or clone-by-clone strategy
Map-based method
Applicability: Useful for higher-order vertebrate genomes with repetitive sequences.
Process:
DNA mapped with genetic markers.
Cut into sub-clones aligned by markers.
Fragments sequenced, matched based on overlaps.
Construct DNA contig from sequenced sub-clones.
Page 6: Generating a Physical Map
Library Creation:
Fragment target genome and insert into BAC vectors.
Transform into E. coli to replicate fragments.
Fingerprinting:
Utilize restriction enzymes for clone fingerprinting.
Identify overlapping clones to define genetic structure.
Sequencing:
Fragment larger clones before individual sequencing.
Assemble shotgun sequences for genome.
Page 7: Hierarchical Shotgun Sequencing Utilization
Constructs genetic and physical maps from diverse sequence data.
Serves as landmarks on developing genomic physical maps.
Page 8: Whole Genome Shotgun Sequencing
Process: Sequence numerous overlapping DNA fragments simultaneously.
Mechanics: Utilizes computer programs to identify overlaps and assemble sequences.
Usage: Common for sequencing microbial genomes due to smaller genome size.
Page 9: Comparison of Sequencing Approaches
Advantages of Hierarchical Shotgun:
Higher accuracy due to known chromosomal locations.
Faster and cost-effective.
Disadvantages of Whole Genome Shotgun:
More error-prone due to random assembly.
Simpler process with fewer assembly steps.
Page 10: Single and Paired End Sequencing
Single-end Read Sequencing: Sequences DNA from one end only.
Paired-end Read Sequencing:
Sequences both ends; better alignment data.
Advantages include higher read quality and ability to detect indels.
Page 11: Benefits of Paired-end Reading
Improves identification of read positions in the genome.
More effective for resolving structural rearrangements and assembling repetitive regions.
Page 12: Genome Assembly Process
Definition: Assembly of DNA fragments to reconstruct complete genome sequence.
Approaches:
De novo Assembly
Reference-guided (resequencing) Assembly
Page 13: De Novo Assembly Explained
Purpose: Used when no reference genome exists.
Process:
Assemble short reads into longer contigs.
Page 14: Sequencing and Reconstruction
Sequencing: Genome fragmentation followed by individual sequencing of short reads.
Error Correction: Correction of errors particularly in long-read technologies.
Overlap Identification:
Three algorithms: OLC, De Bruijn graphs, string graphs.
Merging reads to form contigs, ordered into scaffolds.
Page 15: Applications and Challenges of De Novo Assembly
Applications: Assembling genomes without reference or new reference-quality assemblies.
Challenges: Computational intensity and issues with repetitive genome areas.
Page 16: Conclusion
Acknowledgment: Thank you.