SNP Genotyping Service

Overview

SNP (Single Nucleotide Polymorphism) genotyping, as a high-throughput molecular technology, its core function lies in precisely identifying and deeply analyzing single-base variations in the DNA sequences of individuals or populations. These genetic markers are widely distributed throughout the entire genome. With this characteristic, they have become powerful tools for studying areas such as genetic diversity, trait associations, population structure, and evolutionary relationships. In many fields such as precision medicine, agricultural breeding, forensic science and population genetics, SNP genotyping has become indispensable. Compared with traditional methods, it has an incomparable resolution advantage and excellent scalability. By detecting subtle genetic differences, this approach enables researchers to uncover links between genotypes and phenotypes, track ancestry, or identify disease-related variants with high precision.

Our SNP Genotyping Service Enhances Your Research with:

High-density SNP panel: We will meticulously design and deploy customized or pre-verified SNP arrays based on the species, research goals, or disease priorities you are concerned about. This move aims to ensure the optimal coverage of the target area while guaranteeing good compatibility with different types of samples, such as humans, plants, animals, etc.

Cutting-Edge Genotyping Platforms: Utilizing advanced technologies such as Illumina's Infinium or Axiom systems, we deliver high-accuracy, high-throughput SNP detection with minimal error rates, even for complex genomes or low-quality DNA samples.

Comprehensive Bioinformatics Analysis: Our pipelines integrate quality control, genotype calling, and statistical analysis (e.g., PCA, admixture, GWAS) to identify significant genetic associations, population stratification, or selective sweeps, with options for custom scripting to meet project-specific needs.

Flexible Sample Processing: We have flexible and diverse sample processing capabilities, capable of handling both individual samples and large cohort samples with ease. We support processing samples in various input formats, including blood, tissues, saliva, and FFPE, among others. For projects of any scale, we can provide scalable solutions to maximize cost-effectiveness while ensuring that data quality is not compromised.

What Is SNP Genotyping

SNP (Single Nucleotide Polymorphism) genotyping is an advanced molecular biology technique used to identify and characterize single-base changes in DNA among individuals or populations. These minute genetic variations—which arise when one nucleotide (A, T, C, or G) is substituted—act as valuable biomarkers for investigating genetic diversity, disease predisposition, evolutionary history, and trait linkages. In contrast to whole-genome sequencing, SNP genotyping targets specific genomic loci, allowing cost-efficient, large-scale profiling of thousands to millions of variants in parallel. This methodology has revolutionized areas including personalized medicine, agricultural genomics, forensics, and public health by delivering accurate genetic information that elucidates the role of variations in biological processes and disease mechanisms.
The general procedure for SNP genotyping involves isolating DNA from biological specimens (such as blood, saliva, or tissues), enriching targeted SNP-containing regions via PCR or other capture techniques, and determining alleles using platforms such as microarrays, next-generation sequencing (NGS), or allele-specific probes. Then, based on the reference genome or the genotype data obtained through statistical framework analysis, specific variations are linked to traits, diseases or ancestral information. For instance, in the healthcare context, SNP genotyping can help identify mutations related to diseases such as diabetes and cancer, promoting the early detection of these diseases. In crop science, it enhances crop productivity and resilience by screening for favorable genetic variations and supports marker-assisted breeding. Due to its high efficiency, high throughput and reliability, SNP genotyping is a cornerstone technology for deciphering the genetic structure of complex traits and promoting the progress of precision disciplines.

How to Measure

1. Sample Collection and Experimental Design

In terms of sample collection and experimental design, we have formulated comprehensive and detailed plans for different research subjects. The sample types are rich and diverse. Human samples include blood, saliva, oral swabs and FFPE tissues. Animal samples include blood, tissue biopsy, hair follicles, and also support non-invasive sampling through fecal DNA. Plant samples can be selected from the leaves, seeds, roots of individual plants, or a large number of samples from a population. Microbial samples are analyzed by using culture isolates or environmental DNA from soil, water, etc., for metagenomic SNP analysis. In terms of sampling strategy, we adopt spatial replication to collect samples across geographical regions or habitats, thereby capturing genetic variations at the population level. By using time replication, the population is resampled over time to track genetic changes caused by selection, drift or environmental stress. At the same time, emphasis is placed on the depth of replication, with the goal of collecting 30 to 100 + individuals from each population (the specific number depends on the research objective), to ensure the statistical ability to detect rare variations or weak associations.

2. DNA Extraction and SNP Target Preparation

In the DNA extraction stage, we adopt scientific and efficient methods to ensure the acquisition of high-quality DNA samples. In terms of extraction methods, commercial reagent kits can be selected, such as mature products like Qiagen DNeasy, which are simple to operate and have strong stability. We will also apply an optimized plan to separate DNA for different sample types to ensure the extraction effect to the greatest extent.

SNP Target Enrichment/Amplification

Primer/Probe Design:

• For genotyping arrays: Use pre-designed SNP panels (e.g., Illumina Global Screening Array) or custom-design probes targeting specific genomic regions.
• For PCR-based methods: Design primers flanking target SNPs (e.g., KASP assays for low-throughput projects).
  Amplification/Enrichment:
• Perform PCR or hybrid capture (e.g., SureSelect) to enrich target regions prior to sequencing.
• Include controls (e.g., no-template, positive controls) to validate amplification success.

3. Genotyping and Data Generation

In the field of genotyping and data generation, genotyping technology plays a crucial role. Among them, array-based genotyping technology has unique advantages. With fixed SNP panels, it has become an ideal choice for large-scale projects. Fields such as human genome-wide association studies (GWAS) and agricultural breeding widely apply this technology to achieve efficient and accurate genotyping. Next-generation sequencing (NGS) technology has further expanded the boundaries of genotyping. It includes two methods: targeted sequencing and whole-genome sequencing (WGS). Targeted sequencing can conduct in-depth sequencing on specific genomic regions, such as exome and candidate genes, thereby obtaining detailed genetic information of these key regions. Whole genome sequencing (WGS) can achieve comprehensive SNP discovery and provide researchers with a complete genomic variation map. However, its cost is relatively high and it is more suitable for the study of model organisms or small populations.

4. SNP Analysis and Interpretation

Population Genetics Analysis

• Genetic Diversity Metrics: Calculate observed/expected heterozygosity, nucleotide diversity (π), or inbreeding coefficients (FIS).
• Population Structure:
  • Use PCA (e.g., PLINK, EIGENSOFT) or admixture analysis (e.g., STRUCTURE, ADMIXTURE) to infer ancestry or subpopulations.
  • Detect genetic bottlenecks or founder effects with tools like BOTTLENECK or NeEstimator.

Association Studies

• Case-Control GWAS: Identify SNPs significantly associated with traits/diseases using logistic regression (e.g., PLINK, PLINK2).
• Quantitative Trait Loci (QTL) Mapping: Link SNPs to phenotypic traits (e.g., crop yield, animal growth rate) via linear mixed models (e.g., GEMMA, TASSEL).

Functional Annotation

• Predict Effect of Variants: Use tools like SnpEff or ANNOVAR to classify SNPs as synonymous, missense, or nonsense mutations.
• Pathway Enrichment: Identify biological pathways enriched for disease-associated SNPs (e.g., DAVID, g:Profiler).

5. Phylogenetic and Evolutionary Analysis (Optional)

Phylogenetic and evolutionary analysis, as an optional and highly valuable research subject, plays a crucial role in exploring the course of biological evolution. In the construction of phylogenetic trees, we leverage SNP data and employ professional tools such as RAxML and BEAST to precisely infer the evolutionary relationships between species or populations, clearly presenting the evolutionary trajectory of organisms over a long period of time. Meanwhile, we also carry out the detection work of selective features. Through methods such as XP-CLR and FST outlier tests, we identify gene regions under positive selection, and deeply explore how organisms respond to environmental changes through adaptive evolution, thereby deepening our understanding of the mechanism of life evolution.

6. Visualization and Reporting

Key Visualizations

• Manhattan Plots: Highlight significant SNP-trait associations across the genome (e.g., for GWAS results).
• PCA/Admixture Plots: Show population structure or individual ancestry proportions.
• Haplotype Networks: Visualize relationships among SNP haplotypes (e.g., using PopART or TCS).

Figure 1: SNP Genotypin

What Can We do

• Optimize crop and livestock breeding: Select plants and animals with beneficial SNPS, such as making crops more drought-tolerant and cattle more disease-resistant, to accelerate breeding speed and enhance productivity.
• Tracking evolutionary dynamics: Comparing ancient DNA SNPS (from fossils) with SNPS from modern populations to detect changes in allele frequencies caused by natural selection, migration, or environmental stress.
• Studying human migration and ancestors: Analyzing global SNP patterns, tracking ancestral origins, population flows and mixtures, such as the mixture of Native American and European ancestry.
• Ensure the authenticity of food sources: Verify the geographical origin of products such as olive oil and wine with SNPS specific to regional varieties, crack down on counterfeiting, and guarantee quality.

Our Advantages

• Precise identification, eliminating ambiguity

With the help of DNA barcodes, we have achieved extraordinary accuracy in the field of species identification. Determine the unique standardized short DNA sequences of each species and identify different species.

• Efficient and economical, with simplified processes

Compared with the time-consuming and labor-intensive traditional taxonomic research, this method only requires a small tissue sample to complete DNA extraction, amplification and sequencing. Such a simplified process significantly shortens the turnaround time and reduces operating costs, making it an ideal choice for large-scale biodiversity surveys and environmental monitoring projects.

• Widely applicable, facilitating multiple fields

Our DNA barcoding service has an extremely wide coverage and is applicable to plants, animals, fungi and microorganisms. This powerful universality enables us to provide reliable species identification data for multiple research fields such as conservation biology, ecology, agriculture, and forensic science, without being restricted by the biological groups of the research subjects.

Applications

1.Breaking through the limitations of a single point: Deep integration of multi-dimensional SNPS

Traditional SNP genotyping mainly focuses on individual variation detection, while our platform employs a multi-omics integration strategy (such as fusing SNP data with transcriptomics, epigenomics or proteomics data) to analyze the intrinsic connection between genotypes and phenotypes at an unprecedented depth. For instance, by combining eQTL mapping with SNP arrays, we precisely identify regulatory variations that affect gene expression, and thereby conduct in-depth research on the mechanisms of complex traits such as disease susceptibility and crop yield.

2. Beyond Population Averages: High-Resolution Haplotype Reconstruction

Traditional SNP genotyping often treats loci as independent markers, overlooking linkage disequilibrium (LD) patterns. Our service leverages long-range phasing algorithms (e.g., SHAPEIT4 or Eagle2) and imputation pipelines (e.g., Michigan Imputation Server) to reconstruct haplotypes across entire chromosomes. This reveals co-inherited SNP blocks, improving accuracy in GWAS, forensic identification, and ancestry tracing (e.g., resolving fine-scale population structure in admixed human groups or livestock breeds).

3. Beyond Binary Variant Calling: Quantitative Allele Frequency Resolution

Standard SNP assays classify alleles as present/absent or homozygous/heterozygous, but our ultra-deep sequencing approach (e.g., 1000x coverage) quantifies allele frequencies at sub-percent resolution. This is critical for:

• Detecting low-frequency variants in pooled samples (e.g., cancer mutation burden in liquid biopsies).
• Monitoring allele frequency shifts in real-time (e.g., tracking pathogen evolution during an outbreak or pesticide resistance spread in agricultural pests).

Demo

Figure 2: SNP density distribution on each chromosome. The horizontal axis represents the chromosome length, and the vertical axis represents the chromosome number. Different colors represent the number of SNPs in different regions. (Shen, 2025)

Case Study

FAQs