Next Generation Sequencing (Genomics)

Brief history: DNA sequencing has evolved from the early manual methods to automated technologies.

Key milestone: The Human Genome Project (1990–2003) used traditional Sanger sequencing to map the human genome.

Impact: It revolutionized genetics research, but was costly, taking billions of dollars to complete.

Timeline: 1990–2003

Size of the Genome: 3 billion base pairs

Sequencing Method: Traditional Sanger Sequencing

Significance: The project unravelled the first human genome sequence, serving as a foundation for genetics research, with a high cost of billions of dollars.

Time Efficiency: What used to take years is now achievable in just a day.

Cost Reduction: The sequencing process is now more affordable compared to the initial billion-dollar investment.

NGS: A collection of modern sequencing technologies that allow for massively parallel sequencing.

Advantage: NGS is faster, cheaper, and more scalable than traditional methods like Sanger sequencing.

Application: Used in various fields including genomics, cancer research, and personalized medicine.

Principle: PCR is used to amplify specific regions of DNA by copying the target sequence.

Process: Primers flank the target region, and each cycle of PCR doubles the DNA amount.

Role in Sequencing: Amplifies sufficient DNA for sequencing or other molecular applications.

Significance: It is a fundamental technique for enabling DNA sequencing.

Inventor: Fred Sanger

Year: 1977

Cycle Sequencing: Sanger sequencing is based on cycle sequencing.

PCR-Based: It relies on a PCR product as input.

Primers: Specific primers are required to initiate the sequencing reaction.

Modified Nucleotides: Uses chain terminators and nucleotide-specific colour tags.

Purpose of Modification: A small proportion of nucleotides are modified to allow the sequence to be read base by base.

Throughput: Low-throughput—one reaction equals one sequence.

Length: It can sequence up to 800 base pairs per reaction.

Speed: It is slow, taking more time compared to modern sequencing methods.

Cost: High cost, especially when compared to newer technologies.

Accuracy: Sanger sequencing is highly accurate, with an error rate of 99.99%.

Reliability: It has been the gold standard in DNA sequencing until the late 2000s.

SNPs and Mutations: Used to identify single nucleotide polymorphisms (SNPs) and mutations.

Monogenic Diseases: Commonly used for identifying mutations causing monogenic diseases.

Single Gene Testing: Frequently used for single-gene tests, such as CFTR in cystic fibrosis.

Cost Reduction: The cost of DNA sequencing has dramatically decreased.

Rate of Decrease: Since 2007, the cost reduction has surpassed the rate of Moore's law (which predicts the doubling of computing power every two years).

Technological Advancements: Significant improvements have been made in sequencing technologies, increasing throughput and accuracy.

Introduction: 454 pyrosequencing marked the beginning of new NGS methods around 13 years ago.

Throughput: DNA sequencing throughput increased by 10 orders of magnitude compared to earlier methods.

Impact: This advancement set the stage for further improvements in sequencing technology, making high-throughput sequencing more accessible.

Development: Solexa SBS was developed at the end of 2005.

Method: It is a sequencing-by-synthesis (SBS) method, which involves synthesizing complementary strands of DNA and detecting the bases in real-time.

Contribution: Solexa's technology formed the foundation for Illumina's SBS sequencing, a dominant method in the sequencing market today.

Illumina SBS: Illumina's sequencing-by-synthesis (SBS) technology is the leading method in the sequencing market.

Reason for Dominance: Illumina's SBS provides high-throughput, cost-effective, and accurate sequencing, making it the preferred choice in research and clinical settings.

Replacement: NGS has largely replaced Sanger sequencing for almost all sequencing tests in the lab.

Advantage: NGS is faster, more cost-effective, and offers higher throughput compared to Sanger sequencing.

Definition: Whole genome sequencing (WGS) involves sequencing the entire DNA of an organism, including all its genes and non-coding regions.

Application: Used to comprehensively analyze genetic variations across the entire genome, including mutations and structural changes.

Significance: WGS provides complete genetic information, making it useful for diverse research, including personalized medicine and disease studies.

Definition: Whole exome sequencing (WES) focuses on sequencing the exons, which are the protein-coding regions of the genome.

Difference from WGS: Unlike WGS, which sequences the entire genome, WES targets only the exonic regions, which make up about 1-2% of the entire genome.

Efficiency: WES is more cost-effective than WGS while still providing important insights into genetic variations that may lead to diseases.

Application: Commonly used to study genetic disorders, as most disease-related mutations are found in the exons.

DNA Library Construction: DNA is prepared by chopping it into small fragments.

Cluster Generation: DNA fragments are amplified to form clusters.

Sequencing-by-Synthesis: A method used to sequence the DNA fragments.

Data Analysis: Sequencing data is processed and analyzed for genetic information.

DNA Library Construction: DNA is fragmented, adapted, and prepared for sequencing.

Cluster Generation: Fragments are amplified to create clusters for sequencing.

Sequencing-by-Synthesis: DNA sequencing occurs through real-time synthesis and detection.

Data Analysis: The data is processed and analyzed for genetic information.

Fragmentation: DNA is chopped into small fragments, typically 300 base pairs long, through shearing.

Methods of Shearing: Shearing can be done chemically, enzymatically, or physically (e.g., sonication).

Library: A DNA library is created from random fragments, typically from a patient's blood, for further sequencing study.

End Repair: The ends of the sheared DNA fragments are repaired.

Adenine Overhangs: Adenine (A) nucleotides are added to the ends of the fragments.

Adapter Ligation: Adapters with Thymine (T) overhangs are ligated to the DNA fragments, creating a library of stable fragments.

Sequencing Primer Sites: Adapters contain regions where sequencing primers can bind.

Anchors for Attachment: Adapters contain P5 and P7 anchors that attach the DNA fragments to the flow cell.

Role in Sequencing: The adapters enable proper attachment of fragments to the sequencing platform for synthesis.

Amplification: Cluster generation amplifies DNA fragments to a larger size for easier visualization.

Stronger Signal: The amplification ensures that the DNA fragments produce a signal strong enough to be detected during sequencing.

Hybridization: The DNA library fragments are hybridized to the flow cell surface.

Challenge: Individual DNA molecules are too small to be visualized directly, making amplification necessary.

Goal: To amplify the fragments to a size large enough for detection.

Bridge Amplification: A process where DNA fragments are amplified on the flow cell surface to form clusters.

Formation of Clusters: Each cluster originates from a single DNA molecule, leading to the creation of billions of clusters.

Visualization: The resulting clusters are now large enough to be visualized and used in the sequencing process.

Large Clusters: Many billions of amplified DNA clusters are formed from individual DNA library molecules.

Sequencing Readiness: The clusters are now visible and the flow cell is ready to be loaded onto the sequencing platform for sequencing.

Sequencing Machine: The sequencing machine processes a flow cell containing lanes.

Multiple Samples: Each lane of the flow cell can hold multiple DNA samples, which are indexed with DNA barcodes contained in the adapters.

DNA Libraries: DNA libraries are deposited onto the flow cell, where they undergo the next steps of amplification and sequencing.

Bridge Amplification: The DNA libraries are subjected to bridge amplification, where DNA fragments form clusters on the flow cell.

Cluster Formation: Amplification results in the formation of "clusters," each originating from a single DNA fragment.

Sequencing Readiness: Once clusters are formed, the flow cell is ready for sequencing.

Sequencing Process: Sequencing-by-synthesis (SBS) is the method used to sequence the DNA fragments in the clusters on the flow cell.

Synthesis: During SBS, nucleotides are incorporated into the growing DNA strand, and the sequence is read in real-time.

Indexed Samples: DNA samples are indexed with a unique DNA barcode, which is included in the adapters.

Sample Identification: These barcodes allow for multiple samples to be sequenced in the same lane, helping to differentiate and identify each sample during analysis.

Modified Bases: The four bases (A, T, C, G) are modified with chain terminators and different fluorescent dye colors.

Single Nucleotide Incorporation: DNA polymerase incorporates one nucleotide at a time into the growing DNA strand.

Controlled Process: The incorporation is done in a controlled manner, one nucleotide per cycle.

Single Nucleotide Incorporation: DNA polymerase incorporates a single nucleotide into the growing strand.

Flowcell Wash: The flowcell is washed to prepare for the next cycle.

Imaging: The four bases are imaged using digital photography, detecting the fluorescent color of the incorporated base.

Cleavage: The terminator chemical group and fluorescent dye are cleaved by an enzyme.

Repeat: The process is repeated for each cycle to build the full sequence.

Camera Imaging: A camera captures images of the four bases on the surface of the flow cell after each cycle.

Fluorescent Colors: Each base emits a distinct fluorescent signal, allowing identification of the incorporated nucleotide.

Conversion: Each cycle's image is converted into a nucleotide base call (A, C, G, or T).

Cycle Number: Sequencing typically involves between 50 to 600 cycles, depending on the desired sequence length.

Machine DNA Base Calls: The sequencing machine makes DNA base calls, identifying the nucleotide (A, C, G, or T) for each base in the sequence.

Short-Read Sequences: Millions of short-read sequences are generated, each representing a fragment of the original DNA library.

Short-Read Assembly: Short-read sequences from the sequencing machine need to be pieced together, similar to solving a jigsaw puzzle.

Mapping to Reference Genome: Sequence reads are mapped to the reference genome to locate their positions.

Consensus Sequence: The goal is to generate a consensus sequence that represents the original DNA sample library.

Genetic Variant Detection: The consensus sequence is compared against a reference human genome to identify genetic variants.

Dedicated Software: Specialized software tools are used to map and assemble the sequence reads.

Bioinformatics Tools: Bioinformatics tools are employed to compare the consensus sequence to the reference genome and detect variants.

Readout Type: NGS produces a digital readout, whereas Sanger sequencing produces an analogue readout.

Number of Sequences: Sanger sequencing produces one sequence read, while NGS generates a consensus sequence from multiple reads.

Speed and Throughput: NGS offers high throughput and faster sequencing, whereas Sanger sequencing is slower and more limited in output.

Cost: NGS is generally more cost-effective for large-scale sequencing compared to Sanger sequencing, which is more expensive per read.

Human Genome Overview: The human genome contains approximately 21,000 genes.

Focus on Exons: WES targets the exons of genes, which make up 1-2% of the genome and are responsible for protein coding.

Pathogenic Mutations: Around 80% of pathogenic mutations are found in protein-coding regions (exons).

Cost-Effectiveness: Sequencing the exome is more efficient and cheaper than sequencing the whole genome, with the exome costing £200-£300 compared to £1,000 for a full genome.

Target Enrichment: Specific regions of interest (exons) are captured using probes (baits).

Capture Technique: Baits are designed to bind to the target regions, enriching the sample for the exonic sequences.

Exome Size: The exome typically covers around 50Mb of the genome, which is much smaller than the entire genome (~3 billion base pairs).

Variant Calling: Identifying genetic variants such as single nucleotide polymorphisms (SNPs) or insertions/deletions (indels) in the sequencing data.

Variant Annotation: Providing functional context to variants, such as whether they affect protein coding sequences or regulatory regions.

Sequence Read Alignment: Aligning the short sequence reads from the sequencing machine to the reference genome to identify where the reads map.

Target Coverage: Evaluating how well the target regions (exons) are covered by the sequencing process.

Reporting: Generating reports that summarize the identified variants, their potential impact, and how they relate to known databases.

Protein Coding Mutations: Whole exome sequencing primarily targets mutations within the exons, which are the regions of the genome that code for proteins.

Exons: These are the sequences that will be analyzed because most pathogenic mutations occur within these coding regions.

Exome Sequencing: The patient’s DNA sample is subjected to exome sequencing to capture and analyze the protein-coding regions.

Consensus Sequence: After sequencing, a consensus sequence is generated, representing the most likely sequence of the patient’s exomes.

Mutation Identification: The sequencing results are analyzed to identify any mutations or genetic variations, such as a heterozygous mutation in a gene like CFTR.

Heterozygous Mutation: This means one copy of a gene has a mutation, while the other copy is normal. This can influence the patient’s health depending on the gene and mutation.

Example: In the CFTR gene, a heterozygous mutation could indicate a genetic predisposition to cystic fibrosis.

Disease-Affected Families: Exome sequencing is particularly useful when studying families with individuals affected by a genetic disease.

NGS in Disease Gene Identification: Next-Generation Sequencing (NGS) is used to identify the disease-causing genes in affected individuals.

Variant Profiling: Exome sequencing is performed on affected individuals, and their genetic variants are compared.

Mutation Identification: By comparing the variants, researchers attempt to identify the shared mutation that could be responsible for the disease.

RNA-seq Purpose: RNA-seq is a technique used to study gene expression by analyzing the RNA from cells or tissue samples.

cDNA Conversion: Before sequencing, RNA is converted into complementary DNA (cDNA) to create a library of the sample.

NGS for RNA: NGS is then used to sequence the cDNA, enabling the determination of which genes are actively expressed.

Sequencing Reads: The number of sequencing reads produced from each gene indicates the abundance of that gene’s expression.

Quantification of Expression: This helps quantify the expression levels of thousands of genes in the sample.

Gene Expression Differences: By comparing sequencing results, RNA-seq can identify differences in gene expression across various experimental conditions.

Gene Isoforms: RNA-seq can help discover distinct isoforms of genes, which are variations of a gene that may have different functions.

Differential Regulation: It can also show how different isoforms are differentially regulated and expressed under various conditions.