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The Principles and Workflow of SNP Microarray

Single nucleotide polymorphism

Single nucleotide polymorphism (SNP) refers to the difference of single nucleotide at the same position in the genomic DNA sequence. In general, a single nucleotide variation with a frequency greater than 1% is called a SNP. The SNPs involve only a single base variation, which can be caused by a single base transition or transversion. There is approximately one SNP per 1000 bases in the human genome, and the total number of SNPs in the human genome is around 3 x 106.

SNP has become the third generation of genetic markers. The characteristics of SNPs make them more suitable for studies on genetic pleiotropy in complex traits and diseases, and population-based gene recognition than other polymorphic markers. SNPs have significant importance in biomedical research. SNPs have been used in genome-wide association studies as high-resolution markers in gene mapping related to diseases or normal traits. SNPs without an observable impact on the phenotype (called silent mutations) may also be useful due to their quantity and stable inheritance over generations.

The Principles and Workflow of SNP MicroarrayFigure 1. The upper DNA molecule differs from the lower DNA molecule at a single base-pair location (a C/A polymorphism).


The DNA microarray refers to a gene chip with a large number of probe DNA sequences in a specific arrangement immobilized on a solid substrate. The principle is the nucleic acid hybridization theory, and the detected sample DNA is hybridized with the DNA microarray and extended. Subsequently, the fragments of the non-complementary binding reaction on the chip are washed away, and the gene chip is subjected to laser confocal scanning. Fluorescence signal intensities are then measured and interpreted as the abundance of different genes through certain data processing.

The Principles and Workflow of SNP MicroarrayFigure 2. The principle of microarray.

SNP microarray

SNP microarray uses known nucleotide sequences as probes to hybridize with the tested DNA sequences, allowing qualitative and quantitative SNP analysis through signal detection. Compared with the traditional single cell diagnostic method, SNP microarray is a high throughput method, which is capable of performing thousands of reactions on the surface of the oligonucleotide chip at one time.

The workflow of SNP microarray

The general workflow of SNP microarray is shown in figure 3. Briefly speaking, there are several processes: SNP chip fabrication, sample genomic DNA preparation, hybridization, and fluorescence scanning.

The Principles and Workflow of SNP MicroarrayFigure 3. The workflow of SNP microarray.

  • SNP chip fabrication
    The predesigned oligonucleotide or cDNA chips are arranged orderly and in high density on the glass carrier to make microarrays or core chips. The fabrication methods of the chip include light-guided in-situ synthesis, chemical spray method, contact dot coating method, in-situ DNA controlled synthesis, non-contact micromechanical printing method TOPSPOT® and soft lithography reproduction, etc. A total of 4×105 different DNA molecules can now be placed on a 1 cm2 chip. Affymetrix GeneChip® technology allows high-density, in situ oligonucleotide synthesis, and has been a pioneer in this field.
  • Sample genomic DNA preparation
    Firstly, preparing the sample material. Then the genomic DNA is extracted and is amplified by PCR. Finally, different fluorescent dyes are used to label it.
  • Hybridization and scan
    The genomic DNA labeled with fluorescence is hybridized with SNP microarray under suitable reaction conditions. After being washed, a specific fluorescence scanner is used to scan the fluorescence. Then the computer image analysis is made to process the data before the target gene bioinformatics analysis is carried out.

At CD Genomics, we are dedicated to providing reliable SNP genotyping services, including genotyping by sequencing, SNP microarray, MassARRAY SNP genotyping, Hi-SNPseq, SNaPshot Multiplex System for SNP genotyping, and TaqMan SNP genotyping.


  1. Iwamoto K, Bundo M, Ueda J, et al. Detection of chromosomal structural alterations in single cells by SNP arrays: a systematic survey of amplification bias and optimized workflow. Plos One, 2007, 2(12): e1306.
  2. Ho C C, Mun K S, Naidu R. SNP array technology: an array of hope in breast cancer research. Malaysian Journal of Pathology, 2013, 35(1):33-43.
  3. Ahmad A, Iqbal M A. Significance of genome-wide analysis of copy number alterations and UPD in myelodysplastic syndromes using combined CGH-SNP arrays. Current Medicinal Chemistry, 2012, 19(22).
  4. Sund K L, Zimmerman S L, Thomas C, et al. Regions of homozygosity identified by SNP microarray analysis aid in the diagnosis of autosomal recessive disease and incidentally detect parental blood relationships. Genetics in Medicine Official Journal of the American College of Medical Genetics, 2013, 15(1):70-78.
  5. Liu S, Zhou Z, Lu J, et al. Generation of genome-scale gene-associated SNPs in catfish for the construction of a high-density SNP array. Bmc Genomics, 2011, 12(1):53.

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