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Abstract Detail



Pteridology

Rothfels, Carl [1], Sundue, Michael A. [2], Testo, Weston L. [3], Wolf, Paul G. [4].

A sequence-capture approach to multi-locus nuclear phylogenetics of ferns.

The vast majority of molecular phylogenetic studies in ferns have been based on chloroplast genes; only a handful have used data from nuclear genes. These plastid-based analyses have made great contributions to our knowledge of fern phylogeny, however, information is still lost in uniparentally inherited characters compared to those that are biparentally inherited. To facilitate nuclear-phylogenetic studies in ferns, we have developed a targeted sequence capture approach to gather data from 25 nuclear genes across 24 species from across the fern tree of life. We designed 19,863 120-bp baits, excluding chloroplast sequences, simple repeats, and low-complexity DNA. We sequenced the captured targets using paired-end MiSeq 250 bp reads. Across the 24 samples sequenced we generated contigs of an average total length of 134,537 bp per sample. Although the baits were designed entirely from exon (transcript) data, we successfully captured intronic regions that should be useful for shallower phylogenetic studies. We present phylogenetic analyses of the new target sequence capture data and integrate this into previous transcript-based analyses. We also make our bait sequences available to the community as a resource for further studies of fern phylogeny based on nuclear-encoded genes.


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1 - University of California Berkeley, University Herbarium and Dept. of Integrative Biology, Berkeley, CA, 94720-2465, USA
2 - 111 Jeffords Hall, 63 Carrigan Dr., Burlington, VT, 05405, USA
3 - University of Vermont
4 - Utah State University, Department Of Biology, 5305 OLD MAIN HILL, Logan, UT, 84322-5305, USA

Keywords:
fern phylogeny
target capture sequencing
low-copy nuclear genes.

Presentation Type: Oral Paper
Session: 6, Pteridological Section/AFS
Location: Sundance 1/Omni Hotel
Date: Monday, June 26th, 2017
Time: 11:00 AM
Number: 6006
Abstract ID:387
Candidate for Awards:None


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