Preparazione della Libreria NGS

NGS Library Preparation

• Illumina next-generation sequencing (NGS) uses a fundamentally different approach than Sanger chain-termination.
• It employs sequencing by synthesis (SBS) technology, tracking the addition of labeled nucleotides as the DNA chain is copied in a massively parallel fashion.
• Next-generation sequencing generates vast amounts of DNA sequence data, richer and more complete than Sanger sequencing.
• Data output ranges from 300 kilobases to multiple terabases in a single run, depending on the instrument and configuration.

Illumina Sequencing Technology

• Sequencing by synthesis (SBS): Detects single bases as they're incorporated into growing DNA strands.
• DNA molecules and primers are first attached to a slide or flow cell, amplified to form clonal DNA colonies (clusters).
• Reversible terminator bases (RT-bases) are added to determine the sequence, and unincorporated nucleotides are washed away.
• Fluorescently labeled nucleotides are imaged.
• The dye and terminal blocker are chemically removed, allowing the next cycle to begin.
• Unlike pyrosequencing, DNA chains are extended one nucleotide at a time, and image acquisition can be performed at a delayed moment—allowing for very large arrays of DNA colonies to be captured by sequential images from a single camera.

Library Preparation

• Samples of longer fragments are sheared into a random library of 100-300 base-pair long fragments.
• After fragmentation, the ends of the DNA fragments are repaired, and an A-overhang is added to the 3' end of each strand.
• Adapters necessary for amplification and sequencing are ligated to both ends of the DNA fragments.
• These fragments are then size-selected and purified.

Basic Steps for Sequencing

• Library Preparation: Libraries are prepared and barcodes are added to individual samples.
• Pooling: Samples are pooled together.
• Sequencing: Sequences are determined in parallel.
• Demultiplexing: Reads are separated based on the added barcodes.
• Alignment: Sequences are aligned to a reference genome.

Sample Multiplexing

• Two representative DNA fragments from two unique samples are attached to specific barcode sequences.
• Libraries for each sample are pooled and sequenced in parallel.
• Each new read contains both the fragment sequence and its sample-identifying barcode.
• Barcode sequences are used to de-multiplex the reads from each sample.
• Each set of reads is aligned to a reference sequence.

Tn5-Transposase Based Library Preparation

• Transposomes attach to genomic DNA, facilitating fragmentation.
• Tagmentation creates fragments (~300 bp).
• Primers (e.g., Read 1 Sequencing Primer, Read 2 Sequencing Primer) and indexes are attached to the fragments.
• PCR amplification generates sequencing-ready fragments.

Multiplex Sequencing Assay

• Sample multiplexing allows processing of many samples on a high-throughput instrument.
• Individual "barcode" sequences are added to each sample to distinguish them in data analysis.
• Pooling samples significantly increases the number of samples processed in a single run without a substantial increase in cost or time.
• Highlights of the strategy include speed, high-throughput capacity, and cost-effectiveness.

Illumina NGS Sequencing

• Sequencing by synthesis: DNA sequence is copied, one nucleotide at a time.
• Massive parallelization: Reaction is performed on many templates simultaneously to increase sequencing capacity.

Cluster Generation

• Single DNA fragments hybridize to oligonucleotides on the flow cell complementary to the ligated adaptors, and are amplified via bridge amplification.
• This forms millions of unique clusters.
• The reverse strands are cleaved during washing.
• Sequencing primers are hybridized to the DNA templates.

Sequencing

• During sequencing, clusters are sequenced simultaneously.
• DNA templates are copied base-by-base, utilizing fluorescently labeled and reversible terminator nucleotides.
• After each synthesis step, clusters are excited by a laser, causing fluorescence of the last incorporated base, to determine the sequence.
• The fluorescence label and blocking group are removed, enabling the next base addition.
• The fluorescence signal is captured by a built-in camera to produce images of the flow cell.

RNA-Seq Data Analysis

• Counts (Text): Matrix containing read counts for all annotated genes in the genome.
• Statistics (Stats): Applying statistical methods to determine if the differential expression is statistically significant.
• Differential Expression (Differential Expression): Representing the results in a proper way.

RNA-Seq in a Nutshell

• Produce sequencing data from the transcriptome (perturbed and control).
• Match sequencing reads to the same genome/transcriptome.
• Count how many reads align to the same region for both conditions.
• Look for differentially expressed genes.

Sequence Alignment Software

• Aligner tools like BWA-mem, Bowtie2, Novoalign, TopHat, STAR, and GSNAP use different approaches for DNA or RNA sequencing applications.

RNA-Seq Data Analysis Output: Volcano Plot

• Volcano plots are scatterplots visualizing the results of differential gene expression analyses.
• They display statistical significance (p-value) versus the magnitude of change (fold change).

RNA-Seq Data Analysis Output: Principal Component Analysis (PCA)

• PCA is used to evaluate overall similarity between samples.
• It identifies samples with similar expression levels and helps analyze experimental designs.

RNA-Seq Data Analysis Output: Identification of Patterns

• Heatmaps visually display gene expression profiles to identify pattern similarities.
• This helps in clustering and classifying samples based on their expression profiles.

RNA-Seq Data Analysis Output: Molecular Functions

• GO enrichment analysis categorizes DEGs according to their molecular functions.

ChIP-Seq Experiments

• Identifying transcription factors (TFs) or histone modifications.
• DNA fragmentation (300bp inserts) and adaptor ligation.
• Sequencing methods (Paired/Single end sequencing).
• Mapping and filtering.
• Peak calling, and motif analysis.

ChIP-Seq Data Analysis Workflows

• Sequencing platform, imaged analysis, quality control, enriched regions, and downstream analyses.

Data Analysis

• Data preprocessing and sequencing reads alignment.
• Read density and visualizations.

Conclusions

• Mediator complexes interact with 2-ketoacid dehydrogenases.
• Dehydrogenases linked with Mediator are enzymatically active, producing acetyl-CoA.
• NO (Nitric Oxide) regulates both Mediator's PDH activity and MED-PDH interaction, influencing acetyl-CoA production.
• Inhibition of NO restoration results in MED-PDH interaction and local Acetyl-CoA production in genomic regions.