Genome Technology and Engineering Chapter Notes | Biology for Year 12 PDF Download

Mapping of Genome: Genetic and Physical

• Genome refers to the complete genetic information present in an organism’s cell, encompassing all DNA content.
• In prokaryotes, the genome includes DNA in the nucleoid region and plasmids, which are small, circular DNA molecules found in bacteria.
• In eukaryotes, the genome comprises DNA in the nucleus (chromosomes) and organelles like mitochondria and chloroplasts (in plants).
• Genome mapping is crucial for identifying the position and relative distances of genes or loci, aiding in understanding genetic relationships and phenotypes.
• Two primary approaches to genome mapping are genetic mapping and physical mapping, each utilizing distinct techniques to create genome maps.
• Comparing genomes or DNA from different organisms helps understand conserved genes, sequence relationships, and genetic bases of phenotypes.
• Complete DNA sequencing of samples allows precise comparison to identify similarities, differences, and mutations responsible for specific traits.

Genetic Mapping

• Genetic mapping estimates distances between genetic loci based on recombination frequency observed during crossover events.
• Crossing over, studied in Class XI, involves the exchange of genetic material between homologous chromosomes during meiosis.
• Recombination frequency, measured as the percentage of recombinant offspring, indicates the relative distance between loci.
• One map unit equals 1% recombination frequency and is expressed in centimorgans (cM), a unit of genetic distance.
• Lower recombination frequency suggests closer proximity of loci, while higher frequency indicates greater distance.
• Genetic maps are created by arranging loci based on their genetic distances, derived from crossover analysis.
• A limitation of genetic mapping is the reliance on a limited number of loci with known phenotypes, resulting in sparsely populated maps.
• Sparsely populated genetic maps restrict their utility for fine mapping of new phenotypes or traits.

Physical Mapping

• Physical mapping identifies specific genome locations using DNA-based features like restriction enzyme sites, SSLP, and STS.
• Restriction Fragment Length Polymorphism (RFLP) uses restriction enzymes to cut DNA at specific sequences, producing fragments of varying lengths.
• Fragment patterns are visualized via agarose gel electrophoresis, where fragment size depends on the number and location of restriction sites.
• For circular DNA, a single cut yields one fragment, while dual cuts produce two; for linear DNA, a single cut gives two fragments, and dual cuts give three.
• Enzymes like EcoRI or BamHI are used singly or sequentially to map restriction sites based on fragment sizes.
• RFLP maps help identify genetic variations, such as disease-associated loci, by comparing fragment patterns among individuals.
• Southern hybridization uses specific DNA probes to distinguish fragments in complex genomes, like mammalian DNA with numerous restriction sites.
• Simple Sequence Length Polymorphism (SSLP) maps use microsatellites and minisatellites, repetitive sequences varying in length, for physical mapping.
• Sequence Tagged Sites (STS) are unique 200-500 bp DNA sequences occurring once in the genome, identified via PCR for high-resolution mapping.
• STS combined with restriction maps enhances the resolution and effectiveness of physical mapping.

High-throughput DNA Sequencing

• High-throughput DNA sequencing enables rapid, cost-effective sequencing of entire genomes, overcoming limitations of earlier methods.
• Early sequencing was expensive, focusing on small loci associated with phenotypes to avoid full genome sequencing costs.
• Advances in sequencing technology have reduced costs, making it feasible to sequence complete genomes of various organisms.

First Generation DNA Sequencing Technology

• First-generation sequencing involved multiple steps: chromosome separation via Pulse Field Gel Electrophoresis (PFGE), restriction digestion, and ligation to high-capacity vectors like BAC, YAC, or PAC.
• DNA fragments from these vectors were physically mapped and subcloned into sequencing plasmids for sequencing.
• The chain termination method created a ladder of single-stranded DNA, each terminating at a specific base tagged with fluorescence.
• Fragments were separated by capillary gel electrophoresis, and a fluorescence detector identified bases based on color and position.
• Each capillary sequenced 800-1000 bases per run, with up to 96 capillaries in a single machine, yielding up to 96,000 bases per run.
• Drawbacks included high labor intensity, time consumption, and prohibitive costs for large-scale genome sequencing.

Next (Second) Generation DNA Sequencing Technology

• Next-generation sequencing (NGS) employs massively parallel sequencing, performing millions of reactions simultaneously.
• NGS eliminates cloning and subcloning steps, reducing costs and simplifying workflows compared to first-generation methods.
• Advantages include high data accuracy due to deep coverage, a broad range of applications, and streamlined processes.
• Illumina Sequencing Technology, a popular NGS platform, uses a flow cell with attached oligonucleotides for DNA amplification.
• DNA is fragmented (1-2 kb), and adaptors complementary to flow cell oligonucleotides are ligated to facilitate attachment.
• Bridge PCR amplification creates clusters of identical DNA fragments on the flow cell, enhancing sequencing efficiency.
• Sequencing primers bind to adaptors, and fluorescently tagged dNTPs (each base with a unique tag) are added one at a time.
• Incorporated bases are detected via fluorescence, imaged, and the tag is removed before the next base is added.
• Millions of fragments are sequenced in parallel, producing short reads (75-300 bases) compared to first-generation methods.
• Additional strategies address limitations of short read lengths, improving assembly and analysis of sequencing data.

Some Recent Advances in DNA Sequencing Technology

• Third-generation sequencing, such as nanopore sequencing, measures changes in electric current as DNA bases pass through a nanopore.
• Nanopore sequencing uses DNA helicase to unwind double-stranded DNA and a porin-like protein to form a nanopore on a synthetic membrane.
• Single-stranded DNA passes through the nanopore, disrupting ionic current uniquely for each base, allowing base identification.
• Advantages include rapid, simple sample processing, real-time results, and long reads (up to 1 Mb or more) at low cost.
• Nanopore sequencing is ideal for field-based genotyping and high-mobility testing due to its portability and efficiency.

Other Genome-related Technology

Whole Genome Sequencing (WGS)

• WGS determines the complete DNA sequence of an organism’s genome, providing comprehensive genetic information.
• The first WGS was performed on Haemophilus influenzae, followed by the human genome (1990-2003).
• WGS aids in understanding genetic regulation, identifying inherited disorders, and personalizing disease treatment plans.
• It enables analysis of cancer cell variations to select optimal chemotherapy and supports sequencing of microbes, animals, and plants.
• Reference-based WGS uses a related, previously sequenced genome to assemble reads, while de novo WGS assembles without a reference.

Targeted Sequencing

• Targeted sequencing focuses on specific genes or genomic regions to identify variations like mutations, insertions, or deletions.
• It uses a reference genome to assemble sequences and is cost-effective compared to WGS.
• Clinical exome sequencing targets disease-associated genes (e.g., from OMIM, HGMD databases) for cost-effective genetic diagnostics.
• PCR is commonly used to isolate and sequence target regions, enabling focused analysis of genomic variations.

Metagenomics: Sequencing of DNA or cDNA Present in a Microbial Community

• Metagenomics studies the collective genetic material of microbial communities directly from environments like the gut or soil.
• It avoids individual culturing, analyzing DNA or cDNA from all microorganisms in a sample.
• Applications include studying microbial diversity, environmental changes, and identifying novel genes or enzymes for industrial use.
• Examples include analyzing gut or throat microbes, toilet seat microbes, or extreme environment microbes (e.g., high-temperature sulfur springs).
• Metagenomics provides insights into virus-host interactions, epidemiology, and microbial evolution.
• Multiple genomes in samples pose data analysis challenges, requiring specialized computational algorithms.

Genome Engineering

• Genome engineering modifies an organism’s genome to introduce, remove, or alter genes, adding new functionalities or modifying existing ones.
• Techniques include transposon-based knock-out/knock-in and precise genome editing using CRISPR-Cas9.

Knock-out and Knock-in of a Gene by Transposon Insertion

• Transposons, or “jumping genes,” are DNA sequences that move within the genome via a cut-and-paste mechanism.
• Found in both prokaryotes and eukaryotes, transposons can disrupt genes by inserting into them, causing insertional inactivation.
• Engineered transposons target specific gene sequences, knocking out genes by disrupting their coding frame.
• Knock-out inactivates a gene, preventing production of its original transcript and protein product.
• Knock-in uses transposons to insert new DNA sequences, adding functional genes to a specific locus.
• These techniques create animal or plant models to study disease mechanisms and develop new drugs.

Genome Editing Using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR-Cas9)

• CRISPR-Cas9 is a precise genome editing tool adapted from a bacterial immune system that targets viral DNA.
• Bacteria use CRISPR-Cas to store viral DNA signatures in CRISPR arrays, enabling recognition and destruction of matching viral DNA.
• In CRISPR-Cas9, guide RNA is designed to be complementary to the target DNA sequence and binds to Cas9 endonuclease.
• The guide RNA-Cas9 complex locates the target DNA, where Cas9 induces a double-strand break.
• The broken DNA undergoes homologous repair using a provided edited DNA template, incorporating desired changes.
• CRISPR-Cas9 allows adding, removing, or altering specific DNA sequences with high precision.
• Applications include correcting disease-causing mutations, as demonstrated in mouse models for premature aging.
• Emmanuelle Charpentier and Jennifer Doudna won the 2020 Nobel Prize in Chemistry for developing CRISPR-Cas9.

Structural, Functional and Comparative Genomics

• Next-generation sequencing generates large datasets requiring computational genomics for analysis using high-performance computing.
• Computational genomics uses statistical and computational tools to decipher biological functions from DNA/RNA sequences and experimental data.
• Tools like BLAST, ClustalW, and Phylip enable homology searches, gene annotation, and evolutionary relationship studies.
• GP-GPU and CUDA programming enhance computational genomics by accelerating data analysis.
• India’s Department of Biotechnology established three National Genomics Core facilities in Hyderabad, Kalyani, and Prayagraj to support genomic research.

Structural Genomics

• Structural genomics has two meanings: studying the 3D structure of proteins encoded by a genome or the physical organization of DNA in chromosomes.
• For proteins, it focuses on solving structures of proteins with unknown folds to expand structural knowledge.
• For chromosomes, it examines DNA organization, nucleosome status, and large structural changes across species.
• An example is comparing gene distribution between mouse and human chromosomes to understand genomic reorganization.

Functional Genomics

• Functional genomics studies how genomic information translates into physiological and pathological functions.
• Tools like RNAseq, ChipSeq, and metagenomics analyze gene expression, transcription regulator binding, and microbial community functions.
• It aims to understand cellular states and their associated functions or dysfunctions.

Comparative Genomics

• Comparative genomics compares genes and genomes across species or within individuals of the same species.
• It annotates new genomes by comparing them to well-known related genomes, identifying common and unique genes.
• Core genomes consist of shared genes, while unique genes may confer species-specific traits or functions.
• It identifies the presence or absence of functional molecules and supports genome-based taxonomy and phylogenetic studies.

Protein Engineering

• Protein engineering uses recombinant DNA technology to create proteins with enhanced or novel properties.
• Engineered proteins may have improved stability under extreme conditions (e.g., high temperature, pH changes, or solvents).
• Applications include developing reagents for research, diagnostics, and therapeutics.

Applications of Protein Engineering

• Critical amino acids responsible for desired traits are identified, and their codons are modified via point mutations to alter protein function.
• Example 1: Subtilisin, a detergent enzyme, is engineered by replacing Met 222 with Ala to prevent oxidation by bleach, enhancing stability.
• Example 2: 6-His-tag, a six-histidine peptide, is fused to recombinant proteins for purification via affinity chromatography.
• 6-His-tagged proteins bind metal ions (e.g., Nickel, Zinc) in agarose gel, allowing selective purification by washing away other proteins.
• Example 3: Green Fluorescent Protein (GFP) tags are added to proteins for visualization and localization in cells using fluorescence microscopy.
• Recombinant immunotoxins combine antibody selectivity with toxin potency to target and kill cancer cells.
• Single-chain variable fragments (scFv) are produced via rDNA technology, linking heavy and light chain variable regions with a peptide linker.
• scFv-toxin fusions bind cancer cell antigens, internalize via endocytosis, and release toxins to kill cells.
• Humanized monoclonal antibodies transfer mouse antigen-binding regions to human antibody frameworks to reduce immunogenicity in humans.
• Mouse monoclonal antibodies, produced via hybridoma technology, are immunogenic in humans, necessitating humanization for therapeutic use.
• Humanized antibodies are created by transferring mouse antigen-binding DNA sequences to human antibody genes, improving immune acceptance.