This is not the exhaustive list of NGS technology that can be applied, but the examples listed here are the most common. Those are:
Whole Genome Sequencing (WGS). Whole Genome Sequencing (WGS) is a process that reads and analyzes your entire DNA. It provides detailed information about genetic changes, such as chromosomal alterations, small insertions and deletions (indels), and mutations. The primary result of WGS is identifying genetic differences in the DNA being studied.
Whole-exome sequencing (WES). The exome, a little over 1% of our entire genome, focuses on the parts of our DNA that provide instructions for making proteins. It's commonly used in identifying mutations linked to diseases. Like Whole Genome Sequencing (WGS), Whole Exome Sequencing (WES) also results in identifying genetic variants, but these are found explicitly in the exome (the sum of all exons in the genome).
Targeted sequencing. Targeted sequencing is a method that zeroes in on specific genes or areas in the DNA, allowing for a more detailed study of these selected regions. This approach can achieve higher coverage, meaning more detailed and accurate readings of the chosen areas. There are pre-made panels for targeted sequencing, but custom ones can be created, too. It's often used in medical testing, particularly with tumor panels designed for specific types of cancer. The main result of this process is identifying genetic variations in the specific areas of the genome that were targeted for sequencing.
De novo sequencing. De novo sequencing is sequencing a new genome without a pre-existing reference genome for comparison. Essentially, it's a type of whole genome sequencing, but more complex because it involves assembling the genome from scratch without any reference template.
Expression analysis / RNA Sequencing (RNA-Seq). RNA-Seq allows you to study the differences in RNA expression between different tissues. It can also be used to investigate things like exon usage, gene fusions, and genetic variations such as SNPs, indels, and mutations. Unlike other methods mentioned above, RNA-Seq primarily provides data on the expression levels/rates of specific genes in a given tissue, so the final output is quantitative data that reflects gene expression levels.
DNA–protein interactions / ChIP Sequencing (ChIP-Seq). ChIP-Seq (Chromatin Immunoprecipitation Sequencing) is used to study DNA regulatory elements like transcription factor binding sites or histone modifications. These elements are often found in areas such as promoters, silencers, or enhancers and influence gene transcription. Unlike other sequencing techniques which output genetic variants, or expression techniques which measure expression levels, ChIP-Seq results include the genomic locations of DNA regions that bind to certain proteins and their statistical significance. Additionally, it provides feature count data, giving a numerical representation of features within specific genomic regions, which is useful for further statistical analysis.
DNA Methylation (Methyl-Seq). Like ChIP-Seq, Next-Generation Sequencing (NGS) has also advanced the study of DNA methylation, particularly in CpG islands. DNA methylation is an epigenetic modification crucial for regulating gene expression and allelic use, impacting various biological processes and diseases. The main result of this sequencing technique comes after the methylation calling step, which identifies regions of the genome that are methylated and determines their methylation status. This status, whether methylated or unmethylated status, is assessed at specific genomic locations and can be done in contexts like CpG, CHG, and CHH. The data obtained from the methylation calling step are then used for detailed analyses, such as examining methylation patterns across various genomic regions (like promoters and genes), studying regions with low methylation, and analyzing differences in methylation.