Validate a

bioinformatic prediction through experimentation to find a specific mRNA or

protein that matches to a predicted open reading frame

Running an RNA sequencing experiment to determine the

genes that are expressed by the organism of interest

Using bioinformatic tools to detect features common to

genes, such as predicted open reading frames

Using bioinformatic tools to detect features common to

genes, such as protein coding open reading frames

4

3

2

6

Conserved sequences within introns

Exon-intron junctions within the coding sequence

Polyadenylation signals in the 3’ UTR

Trans-regulatory regions

Use de novo

assembly of DNA reads by identifying overlaps

Compare the reads to known protein-coding genes

Align reads to a reference genome from a model

organism

Use transcriptomic data to infer the genome sequence

It affects the promoter region

50% of the native amino acids will be lost

75% of the native amino acids will be lost

It alters the entire

downstream amino acid sequence

Measuring the levels of the gene x transcript in the

affected tissues

Comparing the

mutation to known variants in ClinVar

Sequencing gene X and identifying the locations of

mutations

Identifying the mutation’s location within the coding

region of the gene

Biological network analysis to map gene regulatory

pathways

Genomic sequencing to locate mutations in non-coding

regions

Structural

bioinformatics to model 3D protein conformations

Transcriptomic profiling of mRNA expression levels

One or more mutations

are present in the gene that codes for the protein

The gene that is producing the protein is over-expressed

The gene that is producing the protein is under-expressed

Multiple mutations are present in the gene that codes

for the protein