Extensive genetic diversity and substructuring among zebrafish strains revealed through copy number variant analysis

Abstract

Copy number variants (CNVs) represent a substantial source of genomic variation in vertebrates and have been associated with numerous human diseases. Despite this, the extent of CNVs in the zebrafish, an important model for human disease, remains unknown. Using 80 zebrafish genomes, representing three commonly used laboratory strains and one native population, we constructed a genome-wide, high-resolution CNV map for the zebrafish comprising 6,080 CNV elements and encompassing 14.6% of the zebrafish reference genome. This amount of copy number variation is four times that previously observed in other vertebrates, including humans. Moreover, 69% of the CNV elements exhibited strain specificity, with the highest number observed for Tubingen. This variation likely arose, in part, from Tubingen's large founding size and composite population origin. Additional population genetic studies also provided important insight into the origins and substructure of these commonly used laboratory strains. This extensive variation among and within zebrafish strains may have functional effects that impact phenotype and, if not properly addressed, such extensive levels of germ-line variation and population substructure in this commonly used model organism can potentially confound studies intended for translation to human diseases.

Inhibition of endogenous MTF-1 signaling in zebrafish embryos identifies novel roles for MTF-1 in development

“…We cannot definitively rule out the possibility of an alternative splice variant because this discrepancy of ~1,480 nucleotides at the beginning of the intron that do not occur in the 3' UTR could result from an alternative splice site within the intron. However, there is still the strong possibility that the truncated zebrafish MTF-1 sequence results from a retained intron and the discrepancy in the intron length could just result from differences in genetic structures between individual zebrafish strains [50, 51]. …”

The MHC class I genes of zebrafish

“…While the zebrafish reference genome has been sequenced, analysis of its polymorphic and structural variation is only beginning. An evaluation of copy number variation (CNV) between the genomes of 80 individual zebrafish revealed 6,080 CNV elements encompassing 14.6% of the zebrafish reference genome (Brown et al 2012). In addition, a comparison of the genomic sequence of a wild caught zebrafish to the reference genome revealed 5.2 million single nucleotide variations and over 1.6 million insertion-deletion variations (Patowary et al 2013).…”

“…This type of variation can significantly influence phenotypic responses so knowledge of this variation and the ability to define the variation between experimental animals is critical for accurately interpreting experimental findings, especially when these findings may be translated to human disease applications. Figure 3 shows that the zebrafish U and Z loci are encoded in genomic regions with increased levels of gene loss, gain, or copy number variation (as identified by Brown et al 2012). As discussed further in Section 6, the high degree of CNV in the MHC class I loci is evidence that some of these genes may be encoded by only a subset of the different haplotypes.…”

“…31,749 CNVs found in 80 individual zebrafish were combined into a non-redundant dataset of 6,080 CNV elements (CNVEs) (Brown et al 2012). Lengths of green (CNV gain) and red (CNV loss) horizontal lines reflect relative CNVE frequencies at respective chromosomal locations.…”

Neuromodulatory Regulation of Behavioral Individuality in Zebrafish

“…Zebrafish display complex behaviors and patterns of neural activity in circuits that receive neuromodulatory input (Brustein et al, 2003; Thirumalai and Cline, 2008; Woods et al, 2014). Zebrafish populations are outbred, highly polymorphic and could therefore have behavioral variation more similar to wild animal populations and humans than do the inbred genetic models that are commonly used in behavioral studies (Brown et al, 2012; Howe et al, 2013). …”