Genetic Sequence Analysis Techniques

❓ ONT, Illumina & MGI – What’s the Difference? 🔬 Next-Generation Sequencing (NGS) allows scientists to read genetic code by sequencing millions (or billions) of DNA fragments in parallel. Let’s explore some key platforms: 1️⃣ Illumina 1) Sample & Library Preparation: DNA/RNA is purified, fragmented, and ligated with adapters containing cluster recognition sites (bind to specific spots on the flow cell), index sequences (identify the sample), and primer binding sites. NEBNext UltraExpress® FS DNA Library Prep Kit https://lnkd.in/dMjcZphg is widely used for high-quality library preparation. 2) Cluster Generation: The flow cell has oligonucleotides complementary to the adapters, allowing fragments to bind. A PCR-like process (bridge amplification) forms clusters. Multiple copies of the strand ensure that the fluorescent signal during sequencing will be strong enough. 3) Sequencing: Fluorescently labeled nucleotides (G,C,A,T) with terminators bind one at a time to all single strands in the cluster (at any given moment, only one type of nucleotide binds, emitting a specific color). A camera records fluorescence to identify nucleotides. Terminator groups are cleaved to allow the next cycle. 4) Reverse Strand Sequencing: Index sequences are read, the reverse strand is synthesized and sequencing is repeated. 5) Data Analysis: Low-quality reads are filtered, and sequences are aligned. 2️⃣ MGI 1) Sample & Library Preparation: DNA is fragmented, ligated with adapters, and circularized into ssCirDNA. NEBNext® FS DNA Library Prep Kit for MGI® https://lnkd.in/dQMtgbNd provides a reliable solution for generating high-complexity libraries with optimized workflow. 2) DNB Generation by Rolling Circle Amplification: ssCirDNA acts as a template for continuous amplification, forming dense DNA Nanoballs (DNBs) with multiple copies of the sequence. 3) Loading DNBs: DNBs bind to specific spots on the flow cell. 4) Sequencing: Fluorescently labeled nucleotides with terminators bind one at a time to all sequences in the DNBs simultaneously. A camera records fluorescence to identify each nucleotide. Terminators are cleaved to allow the next cycle. 3️⃣ Oxford Nanopore Technologies 1) Sample & Library Preparation: DNA/RNA is extracted, purified, and ligated with motor protein adapters. 2) Loading the Flow Cell: The library is added to a flow cell containing thousands of nanopores. 3) Sequencing: The motor protein unzips the DNA, guiding it through the nanopore one base at a time. Each nucleotide disrupts the ionic current in a unique way, producing a signal used to determine the sequence. 4) Base Calling & Data Analysis: Signals are converted into nucleotide sequences, followed by read alignment and error correction. #NGS #Sequencing #Genomics #Bioinformatics #Illumina #Nanopore #MGI #Biotech

🧬 K-mer Analysis: The Building Blocks of Genome Assembly 🔹 What is a K-mer? A k-mer is a substring of length 'k' from a DNA sequence. Think of them as puzzle pieces that help us reconstruct the complete genome picture! 🔹 Why K-mers Matter: 📊 Quality Control 📊 Genome Size Estimation 📊 Repeat Detection 📊 Assembly Graph Construction 🔹 Choosing the Right K-mer Size: Smaller K (15-21): ✅ Better handling of errors ✅ Higher coverage ❌ More repeat issues Larger K (31-127): ✅ Better repeat resolution ✅ More specific matches ❌ Requires higher coverage 🔹 K-mer Frequency Distribution: 📈 Single peak: Homozygous genome 📈 Two peaks: Heterozygous genome 📈 Multiple peaks: Potential contamination/repeats 🔹 Essential K-mer Tools: 🛠️ Jellyfish: Fast k-mer counting 🛠️ KMC: Memory-efficient counting 🛠️ GenomeScope: Genome characteristics 🛠️ BBTools: K-mer analysis suite 🔹 Common Applications: 1️⃣ Error Correction: Low-frequency k-mers → likely errors 2️⃣ Coverage Estimation: K-mer depth = read depth × (L-K+1)/L 3️⃣ Genome Size Estimation: Total bases ÷ average k-mer depth 🔹 Best Practices: ✅ Start with k=21 for most applications ✅ Use odd k values to avoid reverse complements ✅ Consider multiple k values for complex genomes ✅ Monitor memory usage for large datasets 🔹 Troubleshooting Tips: ❌ Issue: High memory usage ✅ Solution: Use disk-based tools like KMC ❌ Issue: Strange k-mer distribution ✅ Solution: Check for contamination/quality 🔹 Advanced Applications: 🧪 Metagenome Analysis 🧪 Variant Detection 🧪 Species Identification 🧪 Assembly Quality Assessment #Bioinformatics #GenomeAssembly #SequencingData #DataAnalysis

DNA sequencing is the process of determining the exact order of nucleotides (A, T, C, and G) in a DNA molecule. It is a crucial technique in genetics and molecular biology, allowing scientists to study genes, diagnose genetic disorders, and even track diseases like cancer and infectious pathogens. Types of DNA Sequencing: 1. Sanger Sequencing (First-Generation) Developed by Frederick Sanger in the 1970s. Uses chain termination with fluorescent or radioactive labeling. Highly accurate but slow and expensive. 2. Next-Generation Sequencing (NGS) Includes platforms like Illumina and Roche 454. Allows for sequencing millions of DNA fragments in parallel. Faster and cheaper than Sanger sequencing. 3. Third-Generation Sequencing Examples: PacBio and Oxford Nanopore. Can sequence long DNA fragments in real time. Useful for complex genome studies and detecting epigenetic modifications. Applications of DNA Sequencing: Medical Diagnostics: Identifies genetic mutations linked to diseases. Personalized Medicine: Helps tailor treatments based on a person’s genetic makeup. Forensic Science: Used in crime investigations and human identification. Evolutionary Biology: Helps trace ancestry and evolutionary relationships. Agriculture & Biotechnology: Improves crops and livestock breeding. Would you like details on a specific aspect of DNA sequencing?

🟡🟡Multiplex PCR technique:🟡🟡 Multiplex PCR is a powerful molecular biology technique that enables the simultaneous amplification of multiple target DNA sequences in a single reaction. This technique is highly efficient, cost-effective, and saves time and reagents, making it widely used in genetic research, clinical diagnostics, forensic analysis, and pathogen detection. ✴️ Definition: A variant of PCR that amplifies multiple distinct DNA sequences in one reaction by using specific primer pairs for each target. ✴️ Principle: Like conventional PCR, it involves denaturation, annealing, and extension but requires careful primer design, concentration balancing, and optimized thermal cycling to prevent interference between primers. ✴️ Types of Multiplex PCR: 1. Single-Template PCR: Uses one DNA template with multiple primer pairs to amplify different regions within the same genome. Commonly applied in genomic analysis and multi-locus targeting. 2. Multi-Template PCR: Uses multiple DNA templates and primer pairs in a single reaction. Requires careful primer design to prevent cross-hybridization and ensure specific amplification. ✴️ In Multiplex PCR, there are two main approaches for detecting the amplified products (amplicons): 1. Fluorescent Dye Detection: All primers are mixed in a single tube, and amplicons are identified by unique fluorescent dyes emitting at specific wavelengths. Used in qPCR or capillary electrophoresis for differentiation and quantification. 2. Size-Based Detection: Amplicons are separated by agarose gel electrophoresis, appearing as distinct bands. Their sizes are compared to a DNA ladder for target identification. ✅️ for exemple in the workshop below that i did in my higher school, we used a multiplex PCR approach with five different master mixes (A, B, C, D, E) to study deletions in the SRY and AZF regions of the Y chromosome. For each sample, we set up five reaction tubes—one for each master mix—and included essential controls: a positive control with male genomic DNA and a negative control with nuclease-free water instead of DNA. The master mixes, containing primers and Taq DNA polymerase, were carefully prepared and added to the reaction tubes along with the DNA samples or controls. We then used a thermocycler to amplify the DNA, and the results were analyzed using agarose gel electrophoresis. The presence or absence of amplification bands indicated whether deletions were present. If all expected bands appeared, the sample had no deletions, suggesting a normal Y chromosome. If specific bands were missing, this indicated deletions in the corresponding regions, which could be associated with male infertility or disorders of sex development (DSD). #Molecular_Biology_Techniques #PCR #PCR_Multiplex #DNA_amplification

🟥 Common Experimental Methods in Genomics Genomics is the study of the complete DNA sequence of an organism, including all genes. It plays a vital role in understanding genetic variation, disease mechanisms, and the development of personalized medicine. Several key experimental methods are commonly used in genomics to analyze DNA sequence, structure, and function. DNA extraction is one of the most basic techniques in genomics, which can isolate high-quality genomic DNA from various biological samples such as blood, tissues, or cells. This step is essential for downstream applications such as PCR, sequencing, and library preparation. Accurate and contamination-free DNA extraction ensures reliable genomic analysis. Polymerase chain reaction (PCR) and quantitative PCR (qPCR) are widely used to amplify specific DNA regions and quantify gene expression levels. These methods are essential for genotyping, mutation analysis, and sequencing data validation. qPCR is particularly suitable for detecting gene copy number variations and mRNA levels. Next-generation sequencing (NGS) has revolutionized genomics by enabling high-throughput sequencing of the entire genome, exome, or transcriptome. It is widely used in whole genome sequencing, RNA sequencing, epigenetic studies, and microbiome analysis. NGS platforms enable deep insights into gene mutations, alternative splicing events, and gene regulatory networks. Microarray technology still plays an important role in gene expression profiling and single nucleotide polymorphism (SNP) analysis. Although microarrays have been partially replaced by NGS, they are still used for high-throughput screening of large cohorts due to their cost-effectiveness and speed. They are often used in cancer genomics, pharmacogenomics, and biomarker discovery. Another powerful method is CRISPR-Cas9 genome editing, which can precisely modify DNA sequences. In genomics research, it is used for gene function validation, disease model construction, and large-scale genetic screening. These experimental tools, combined with bioinformatics, continue to accelerate genomic discoveries in medicine and biotechnology.