Tissue-Specific eQTL in Zebrafish

Abstract

Copy number variants (CNVs) refer to the loss or gain of copies of a genomic DNA region. While some CNVs may play a role in species evolution by enriching the diversity of an organism, CNVs may also be linked to certain diseases such as neurological disorders, early onset obesity, and cancer. CNVs may affect gene expression by direct overlap of the genic region or by an indirect effect where the CNV is located outside the gene location. These indirect CNV regions may contain regulatory elements such as transcription enhancers or repressors as well as regulators such as miRNAs which may work at the level of transcription or translation. Danio rerio (zebrafish) is an excellent model organism for CNV studies. Zebrafish genomes contain a large amount of variation with 14.6% of the zebrafish reference genome found to be copy number variable. This level of variation is more than four times the percentage of reference genome sequence covered by similarly common CNVs in humans. It is this high level of variation that makes zebrafish interesting to investigate the effects of CNV on gene expression. Additionally, zebrafish share 70% of genetic similarities with humans, and 84% of genes associated with human disease are also found in zebrafish. Expressive quantitative trait loci (eQTL) analysis may be used in zebrafish to explore how CNVs may affect gene expression in both a direct and indirect manner. eQTL analysis may be performed for cis associations with a 1-Mb (megabase) window upstream and downstream from the transcription probe midpoint to CGH midpoint. Trans associations (variants that are located beyond the 1-Mb window of the gene either on the same chromosome as the gene or on a different chromosome) may be investigated as well through eQTL analysis; however, trans associations require more tests to be performed than cis associations, which limits power to detect associations. Pairwise associations between each pair of copy number variant and gene will be investigated separately from the same individual using Spearman rank correlations with significant associations found being followed with a multi-test correction technique to assess significance of those CNV gene expression associations. An association between a CNV to a gene expression phenotype should be considered significant only if the p value from the analysis of the observed data is lower than the 0.001 tail threshold from a distribution of the minimal p values (which are found from all comparisons for a given gene from 10,000 permutations of the expression phenotypes). Associations between CNVs and genes may be found to be direct or indirect as well as positive (increased copy number—increased expression) or negative (increased copy number—decreased expression, decreased copy number—increased expression). Ongoing analyses with these associations will investigate the impact of CNVs on gene functionality including immune function and potential disease susceptibility.