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The Basics and Applications of Genome Sequencing

The Basics and Applications of Genome Sequencing

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    Overview of Genome Sequencing


    Genome sequencing refers to the use of high-throughput sequencing platforms to sequence the genomes of different individuals or groups and perform bioinformatics analysis at the individual or group level. Genome sequencing can comprehensively mine genetic variations at the DNA level, including larger structural variations, providing crucial information for screening pathogenic and susceptibility genes for diseases, researching pathogenesis and genetic mechanisms, and inferring population migration and evolution.


    Categories of Genome Sequencing


    De novo Sequencing


    De novo sequencing can sequence the genome of a species without any reference genome information. Through bioinformatics analysis methods for splicing and assembling, the complete genome sequence map of the species can be obtained, thereby advancing in-depth research on the species. Only through de novo sequencing can detailed genetic analysis be conducted for any organism. This method is often used for genetic analysis of species that frequently mutate, such as highly variable viruses.


    Resequencing


    Resequencing involves genome sequencing of different individuals of a species with an existing reference genome, followed by differential analysis at the individual or group level. After a genome has been published, resequencing does not require reassembly and can directly align the sequenced reads against the short sequences. In short, resequencing is genome sequencing of individuals of a species with a known genome sequence, primarily aimed at identifying types of variations such as single nucleotide polymorphisms (SNPs), copy number variations (CNVs), insertions/deletions (InDels), etc.


    Genome Sequencing Experimental Workflow


    Library Construction Process


    1.Sample sources can include fresh tissues and blood, from which DNA is extracted after processing;


    2. Then, genomic fragmentation is performed using enzymatic or physical methods to recover the target DNA fragments;


    3. Next, end repair and A-tailing of the target DNA fragments are performed, followed by adding sequencing adapters to the adenylated DNA fragments from the previous step. Fragment selection is then done to effectively recover DNA fragments with sequencing adapters added at both ends. This is followed by PCR amplification enrichment of the captured library and then quality control of the library;


    4. Finally, the library is diluted, mixed, and loaded onto the sequencing machine.


    Bioinformatics Analysis Workflow


    1. Data Generation


    Statistics are generated for total base count, number of reads mapped to the whole genome, and number of uniquely mapped reads, followed by sequencing depth analysis.


    2. Consensus Sequence Assembly


    Sequencing data are aligned to the reference genome sequence using Bayesian statistical model is applied to call the most likely genotype at each base position, generating the consensus sequence of the individual's genome.


    3. SNP Detection and Distribution


    All polymorphic sites across the entire genome are extracted, then filtered based on quality score, sequencing depth, and reproducibility to obtain a high-confidence SNP dataset. Detected variants are annotated using the reference genome sequence.


    4. InDel Detection and Distribution


    Gap alignments to detect credible short InDels (insertions/deletions) are allowed during mapping, with gap lengths ranging from 1 to 5 bases.


    5. Structural Variation (SV) Detection and Distribution


    Structural variation types are detected and annotated at the whole-genome level, including insertions- deletions, duplications, inversions, and translocations. These structural variations are identified and annotated based on the alignment results of the sequenced individual’s genome to the reference genome.


    Applications of Genome Sequencing


    In biomedical research, genome sequencing is widely used in genome-wide association studies (GWAS) to identify single nucleotide polymorphism (SNP) sites associated with specific diseases.


    Genome sequencing also has significant value in clinical medicine. In 2009, Illumina launched a genome analysis suite for clinical medicine, aiding physicians in diagnosing cases where the cause of disease is unknown or traditional therapies have been proven ineffective. With the significant reduction in genome sequencing costs in recent years, its clinical application potential has increased substantially. In 2011, Brigham and Women's Hospital and Harvard Medical School jointly established the Genomes2People (G2P) program, which aims to integrate genome sequencing into clinical medicine.




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