SNP-E: A New Method For Multiple Sequence Alignments Analysis And Accurate Single Nucleotide Polymorphism Evaluation

  • Melody N. Hemmati-Sholeh Genomics Core Facility; Department of Plant Soil and Agricultural Systems, and the Illinois Soybean Center, Southern Illinois University at Carbondale, Carbondale, IL 62901, USA
  • Larry A. Sholeh Department of Electrical and Computer Engineering, Southern Illinois University at Carbondale, Carbondale, IL 62901, USA
  • David A. Lightfoot Genomics Core Facility; Department of Plant Soil and Agricultural Systems, and the Illinois Soybean Center, Southern Illinois University at Carbondale, Carbondale, IL 62901, USA
Keywords: Single Nucleotide Polymorphism (SNP), Sanger, IlluminaTM, Cultivar, Variation

Abstract

Identification of single nucleotide polymorphisms (SNPs) and insertion-deletion mutations are important for discovering the connection between the genetic mutations and complex diseases. The objective of this study was to develop a sensitive and accurate computational method for SNP detection among Multiple Sequence Alignments (MSAs) to be run on Microsoft Office SuiteTM and WindowsTM. The SNP-Evaluator, was designed to simulate the process of human eye visual change-identification. Analysis of three 82-Kbp genomic loci derived from Sanger sequencing and the corresponding SNPs from 31 genomes from IlluminaTM sequencing of soybean (Glycine max L. Merr.) demonstrated that the SNP-E was an effective method for medium-scale genomic research.

Published
2017-05-25
Section
ARTICLES