Gene Identification via Phenotype Sequencing: A Tool That Guides Sequencing Based Forward Genetics Studies

The cost-efficiency of next generation sequencing (NGS) has been increasing exponentially at a rate that beats the Moore's Law of computing hardware. Today, whole-genome sequencing has become a viable approach for the identification of Mendelian genes from phenotype-exhibiting individuals. In such forward genetics studies, the choice of experimental parameters and analysis protocols has significant impacts on the likelihood of successful gene identification. We present the Gene Identification via Phenotype Sequencing (GIPS) software, which analyzes the impacts of important experimental designs and analysis decisions on the likelihood of successful gene identification, which include the number of phenotype-exhibiting individuals being sequenced, sequencing depth, sequence alignment and variance calling protocols, and variance selection strategies. For a specific experiment and analysis design, GIPS calculates three expected likelihoods: the chance of discovering the true phenotype-controlling gene, the chance of discovering unrelated genes, and the chance that the phenotype under scrutiny is controlled by more than one gene. GIPS calculates these likelihoods using both empirical data (e.g. genomic distribution of known Mendelian genes), and case-specific experimental data when they are available (e.g. the sequencing results of some phenotype-exhibiting individuals). GIPS was developed to provide a theoretic guidance for effective planning and execution of large scale forward genetics studies that are to be performed in the Center of Molecular Breeding at Zhejiang University. The Center of Molecular Breeding at Zhejiang University is actively looking for perspective young scientists to work on both traditional and molecular breeding, with marker-assisted elite gene pyramiding.