Fine mapping of the pond snail left-right asymmetry (chirality) locus using RAD-Seq and fibre-FISH
Liu, Mengning Maureen and Davey, J.W. and Banerjee, Ruby and Han, Jie and Yang, Fengtang and Aboobaker, Aziz and Blaxter, Mark L. and Davison, Angus (2013) Fine mapping of the pond snail left-right asymmetry (chirality) locus using RAD-Seq and fibre-FISH. PLoS ONE, 8 (8). e71067/1-e71067/7. ISSN 1932-6203
The left-right asymmetry of snails, including the direction of shell coiling, is determined by the delayed effect of a maternal gene on the chiral twist that takes place during early embryonic cell divisions. Yet, despite being a well-established classical problem, the identity of the gene and the means by which left-right asymmetry is established in snails remain unknown. We here demonstrate the power of new genomic approaches for identification of the chirality gene, “D”. First, heterozygous (Dd) pond snails Lymnaea stagnalis were self-fertilised or backcrossed, and the genotype of more than six thousand offspring inferred, either dextral (DD/Dd) or sinistral (dd). Then, twenty of the offspring were used for Restriction-site-Associated DNA Sequencing (RAD-Seq) to identify anonymous molecular markers that are linked to the chirality locus. A local genetic map was constructed by genotyping three flanking markers in over three thousand snails. The three markers lie either side of the chirality locus, with one very tightly linked (<0.1 cM). Finally, bacterial artificial chromosomes (BACs) were isolated that contained the three loci. Fluorescent in situ hybridization (FISH) of pachytene cells showed that the three BACs tightly cluster on the same bivalent chromosome. Fibre-FISH identified a region of greater that ~0.4 Mb between two BAC clone markers that must contain D. This work therefore establishes the resources for molecular identification of the chirality gene and the variation that underpins sinistral and dextral coiling. More generally, the results also show that combining genomic technologies, such as RAD-Seq and high resolution FISH, is a robust approach for mapping key loci in non-model systems.
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