Bioinformatics Basics: Whole-Genome Sequencing vs. Resequencing

Bioinformatics Basics: Whole-Genome Sequencing vs. Resequencing

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Whole-Genome Sequencing

Whole-genome sequencing defines the order of nucleotides (A, C, G, and T) throughout an organism's genome. Whole-genome sequencing is usually used to search for genetic abnormalities (eg, single nucleotide variants, deletions, insertions, and copy number variants). Alterations in the noncoding segments of DNA within genes, known as introns, can also be defined because the whole genome is being sequenced. Introns are deleted by RNA splicing during a post-transcriptional process in normal circumstances, and changes in these areas can affect whether DNA is transcribed into RNA or results in a truncated, non-functional protein.

Advantages of Whole-Genome Sequencing

    - Enables analysis of SV and CNVs in the genome's coding and non-coding regions. Detects structural variations as well as complex rearrangements like deletions, inversions, and translocations.

    - WGS provides more consistent sequence coverage. Even for complex or polyploid genomes, it produces reliable reference sequences .

    - No PCR amplification is needed during library preparation, lowering the possibility of GC bias.

    - WGS does not have problems regarding reference bias.

    - WGS is more global.

    - Offers efficient details for mapping genomes of novel microbes or finishing genomes of known organisms.

    - Analyzes highly similar or repetitive areas for accurate de novo assessment.


When an individual's genome is sequenced and assembled using the reference genome as a framework, this is referred to as a resequencing project. The primary goal of resequencing is to make distinctions between genomes from various organisms.

The Illumina platforms are well appropriate for most resequencing technologies. Illumina sequencing generates a large amount of high-quality short reads (300 bp), enabling robust variant identification. Illumina databases are widely used in genomic researches of viruses, bacteria, mammals, and plants, and can be used with a variety of input components, such as low-input DNA, FFPE specimens, and circulating cell-free DNA.

Targeted Re-sequencing

One of the most common software of next-generation sequencing is targeted sequencing. Targeted sequencing can be divided into three categories:

    - Exome sequencing

    - Gene targeting based on amplicons

    - Hybridization and gene targeting based on probes

Difference Between Whole Genome Sequencing and Re-sequencing

When a reference genome sequence is accessible, resequencing is usually done. The alignment of sequencing reads to the reference determines where in the genome a particular read best matches. Variant identification (single nucleotide polymorphisms, small insertions/deletions, structural variations, copy number variation) and derivatives thereof (tumor vs normal comparison, population genetic assessment, Mendelian disease assessment, and trio sequencing) are all common techniques for resequencing.

De novo sequencing and assembly is commonly used in microbes where there is no obtainable reference genome or the accessible reference is of bad quality. Following sequencing, genomes that have never been sequenced must be constructed from scratch. This configuration can then be used for further analysis as well as the foundation for future resequencing projects.

While whole-genome sequencing and re-sequencing account for roughly 90% of all DNA-based sequencing applications, it's essential not to overlook the plethora of new epi-genomic attribute counting and detection protocols now accessible. Genotyping, DNA-protein interactions, and epigenetic markers are among them.

About CD Genomics Bioinformatics Analysis

The bioinformatics analysis department of CD Genomics provides novel solutions for data-driven innovation aimed at discovering the hidden potential in biological data, tapping new insights related to life science research, and predicting new prospects.


  1. Hou Y, Wu K, Shi X, et al. Comparison of variations detection between whole-genome amplification methods used in single-cell resequencing. Gigascience. 2015, 4(1).
  2. Lam HY, Clark MJ, Chen R, et al. Performance comparison of whole-genome sequencing platforms. Nature biotechnology. 2012, 30(1).
  3. Lutz KA, Wang W, Zdepski A, Michael TP. Isolation and analysis of high quality nuclear DNA with reduced organellar DNA for plant genome sequencing and resequencing. BMC biotechnology. 2011, 11(1).
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