device loads a few nanoliters of sample product to the prefabricated matrix loaded chip array (384‐pad spectroCHIP) (Oath et al. 2009). The SpectroCHIP is then loaded to the MALDI‐TOF MS analyzer for the analysis.
2.2.3 Custom Assay Technologies
Once any significant SNP with a vital role in gene regulation, phenotype change, disease response, and so on is discovered, the next step is to validate it in a larger population. Arrays designed with few vital SNPs, mainly for validation purposes are called custom‐designed SNP assays. These assays must meet at least majority of the following criteria:
1 should be able to analyze large amounts of samples quickly,
2 should have a high design to assay conversion rate for custom SNPs, and
3 should be reliable and cost‐effective.
To achieve these requirements, these technologies have incorporated a variety of sophisticated molecular biology techniques. The advantage of customized array is that SNPs from genomic regions of interest can be specifically added to the array and the number of interested SNPs to be fabricated on the array can be adjusted to the customer's needs. Customized SNP array cost per sample is low to moderate approximately $28–$90 (USD) while the NGS method have approximately $35 per sample price for GBS (Peng et al. 2017) which will increase drastically from diploid to polyploid as much higher coverage is required for accurate SNP calling. The major disadvantage of customized SNP array is that it requires prior genomic information and location (Vos et al. 2015). Furthermore, its design and further optimization can take a long time. Another issue is that SNP discovery requires fewer samples, which will primarily remove rare alleles while capturing common alleles (Gravel et al. 2011).
2.2.4 Summary
SNPs constitute one of the most popular and significant genetic markers in studying disease development and progression, breeding crops for improved traits etc. Two major strategies are involved in SNP genotyping viz. allele discrimination and allele detection. The high‐throughput platforms used for SNP genotyping have generated huge amount of data in many crops. Further utilization of this information in plant breeding is important for crop improvement.
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