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Bellstedt, Dirk U.
Le Maitre, Nicholas C.
|Title:||Targeted NGS for species level phylogenomics : “made to measure” or “one size fits all”?|
|Online publication date:||13-Oct-2022|
|Year of first publication:||2017|
|Abstract:||Targeted high-throughput sequencing using hybrid-enrichment offers a promising source of data for inferring multiple, meaningfully resolved, independent gene trees suitable to address challenging phylogenetic problems in species complexes and rapid radiations. The targets in question can either be adopted directly from more or less universal tools, or custom made for particular clades at considerably greater effort. We applied custom made scripts to select sets of homologous sequence markers from transcriptome and WGS data for use in the flowering plant genus Erica (Ericaceae). We compared the resulting targets to those that would be selected both using different available tools (Hyb-Seq; MarkerMiner), and when optimising for broader clades of more distantly related taxa (Ericales; eudicots). Approaches comparing more divergent genomes (including MarkerMiner, irrespective of input data) delivered fewer and shorter potential markers than those targeted for Erica. The latter may nevertheless be effective for sequence capture across the wider family Ericaceae. We tested the targets delivered by our scripts by obtaining an empirical dataset. The resulting sequence variation was lower than that of standard nuclear ribosomal markers (that in Erica fail to deliver a well resolved gene tree), confirming the importance of maximising the lengths of individual markers. We conclude that rather than searching for “one size fits all” universal markers, we should improve and make more accessible the tools necessary for developing “made to measure” ones.|
|DDC:||580 Pflanzen (Botanik)|
580 Botanical sciences
|Institution:||Johannes Gutenberg-Universität Mainz|
|Department:||FB 10 Biologie|
|Information on rights of use:||https://creativecommons.org/licenses/by/4.0/|
|Pages or article number:||e3569|
|Appears in collections:||DFG-OA-Publizieren (2012 - 2017)|
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