No evidence for extensive horizontal gene transfer in the genome of the tardigrade Hypsibius dujardini

Abstract

Tardigrades are meiofaunal ecdysozoans that are key to understanding the origins of Arthropoda. Many species of Tardigrada can survive extreme conditions through cryptobiosis. In a recent paper [Boothby TC, et al. (2015) Proc Natl Acad Sci USA 112(52):15976-15981], the authors concluded that the tardigrade Hypsibius dujardini had an unprecedented proportion (17%) of genes originating through functional horizontal gene transfer (fHGT) and speculated that fHGT was likely formative in the evolution of cryptobiosis. We independently sequenced the genome of H. dujardini As expected from whole-organism DNA sampling, our raw data contained reads from nontarget genomes. Filtering using metagenomics approaches generated a draft H. dujardini genome assembly of 135 Mb with superior assembly metrics to the previously published assembly. Additional microbial contamination likely remains. We found no support for extensive fHGT. Among 23,021 gene predictions we identified 0.2% strong candidates for fHGT from bacteria and 0.2% strong candidates for fHGT from nonmetazoan eukaryotes. Cross-comparison of assemblies showed that the overwhelming majority of HGT candidates in the Boothby et al. genome derived from contaminants. We conclude that fHGT into H. dujardini accounts for at most 1-2% of genes and that the proposal that one-sixth of tardigrade genes originate from functional HGT events is an artifact of undetected contamination.

Keywords: blobtools; contamination; horizontal gene transfer; metagenomics; tardigrade.

Fig. 1.

H. dujardini genome assembly. (A) Blobplot of the initial nHd.1.0 assembly, identifying significant contamination with a variety of bacterial genomes. Each scaffold is plotted based on its GC content (x axis) and coverage (y axis), with a diameter proportional to its length and colored by its assignment to phylum. The histograms above and to the right of the main plot sum contig spans for GC proportion bins and coverage bins, respectively. (B) Blobplot of the nHd.2.3 assembly (as in A). (C) Blobplot of the nHd.2.3 assembly, with scaffold points plotted as in B but colored by average base coverage from mapping of RNA-Seq data (42). A high-resolution version of this figure is available in SI Appendix.

Fig. 2.

Contaminants in the UNC assembly. (A) Blobplot of the UNC assembly with coverage derived from pooled UNC raw genomic data. (B) Blobplot showing the UNC assembly with coverage derived from the Edinburgh short insert genomic data. (C) Blobplot (as in A) with the scaffold points colored by average RNA-Seq base coverage. A high-resolution version of this figure is available in SI Appendix.

Fig. 3.

Identifying HGT candidates. (A) Stacked histogram showing scaffolds assigned to different kingdoms (Bacteria, Eukaryota, and “no hits”) in different length classes for UNC and nHd.2.3 assemblies. The nHd.2.3 assembly had no scaffolds >1 Mb, and all of the longest scaffolds (>0.5 Mb) in the UNC assembly were bacterial. (B) Coverage-coverage plot of the UNC assembly using the Edinburgh short insert data (x axis) and in the pooled UNC short insert data (y axis). (C) Coverage-coverage plot of the nHd.2.3 assembly as in B. (D) Expression of soft and hard HGT candidates, and all other genes, in the nHd.2.3 assembly. A high-resolution version of this figure is available in SI Appendix.