HIGH-THROUGHPUT SEQUENCING-BASED IDENTIFICATION AND FUNCTIONAL ANNOTATION OF GENETIC VARIANTS ASSOCIATED WITH PHENOTYPIC TRAITS

Abstract

High-throughput sequencing has contributed greatly to the discovery of genetic variants and their contribution to phenotypic variation. This paper will seek to identify and annotate genetic variants related to phenotypic traits in Saccharomyces cerevisiae in a systematic and functional way based on an extensive bioinformatics platform. Whole-genome sequencing data of various yeast strains were processed with the help of an integrated pipeline consisting of quality control, sequence alignment, variant calling, and functional annotation. Large amounts of single nucleotide polymorphisms (SNPs) and insertion/deletions (INDELs) were identified in the entire genome with a greater percentage found in non-coding and regulatory regions. The functional classification showed that a considerable number of variants led to non-synonymous mutations that had an impact on the genes related to metabolic pathways and stress response systems. The statistical analysis of association has revealed important variants that were associated with phenotypic phenotypes such as growth rate and stress tolerance to the environment, which suggests a polygenic and complex genetic framework. The results also indicate that the regulatory and rare variants contribute to the variability in phenotypes. On the whole, this paper has shown that high-throughput sequencing together with functional annotation is effective in decoding the genotypephenotype relationships and a scalable model of genomic analysis is possible with model organisms and beyond.