Taking the First Steps towards a Standard for Reporting on Phylogenies: Minimum Information about a Phylogenetic Analysis (MIAPA)

Leebens‐Mack, Jim; Vision, Todd; Brenner, Eric D.; Bowers, John E.; Cannon, Steven B.; Clement, Mark J.; Cunningham, Colleen; dePamphilis, Claude W.; DeSalle, Rob; Doyle, Jeff J.; Eisen, Jonathan A.; Gu, Xun; Harshman, John; Jansen, Robert K.; Kellogg, Elizabeth A.; Koonin, Eugene V.; Mishler, Brent D.; Piégay, Hervé; Pires, J. Chris; Qiu, Yin Long; Rhee, Seung Y.; Sjölander, Kimmen; Soltis, Douglas E.; Soltis, Pamela S.; Stevenson, Dennis Wm.; Wall, Kerr; Warnow, Tandy; Zmasek, Christian M.

doi:10.1089/omi.2006.10.231

Cited by 79 publications

(54 citation statements)

References 51 publications

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“…Additional metadata would allow a comparison of synthesis trees based on, for example, morphological versus molecular data, the inference method, or the number of underlying genes. Manual curation is time-consuming and laborintensive; scalability would improve greatly by having standardized metadata (35) encoded in the files output by inference packages (e.g., in NeXML files) (36).…”

Section: Discussionmentioning

confidence: 99%

Synthesis of phylogeny and taxonomy into a comprehensive tree of life

Hinchliff

Smith

Allman³

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Reconstructing the phylogenetic relationships that unite all lineages (the tree of life) is a grand challenge. The paucity of homologous character data across disparately related lineages currently renders direct phylogenetic inference untenable. To reconstruct a comprehensive tree of life, we therefore synthesized published phylogenies, together with taxonomic classifications for taxa never incorporated into a phylogeny. We present a draft tree containing 2.3 million tipsthe Open Tree of Life. Realization of this tree required the assembly of two additional community resources: (i) a comprehensive global reference taxonomy and (ii) a database of published phylogenetic trees mapped to this taxonomy. Our open source framework facilitates community comment and contribution, enabling the tree to be continuously updated when new phylogenetic and taxonomic data become digitally available. Although data coverage and phylogenetic conflict across the Open Tree of Life illuminate gaps in both the underlying data available for phylogenetic reconstruction and the publication of trees as digital objects, the tree provides a compelling starting point for community contribution. This comprehensive tree will fuel fundamental research on the nature of biological diversity, ultimately providing up-to-date phylogenies for downstream applications in comparative biology, ecology, conservation biology, climate change, agriculture, and genomics.phylogeny | taxonomy | tree of life | biodiversity | synthesis T he realization that all organisms on Earth are related by common descent (1) was one of the most profound insights in scientific history. The goal of reconstructing the tree of life is one of the most daunting challenges in biology. The scope of the problem is immense: there are ∼1.8 million named species, and most species have yet to be described (2-4). Despite decades of effort and thousands of phylogenetic studies on diverse clades, we lack a comprehensive tree of life, or even a summary of our current knowledge. One reason for this shortcoming is lack of data. GenBank contains DNA sequences for ∼411,000 species, only 22% of estimated named species. Although some gene regions (e.g., rbcL, 16S, COI) have been widely sequenced across some lineages, they are insufficient for resolving relationships across the entire tree (5). Most recognized species have never been included in a phylogenetic analysis because no appropriate molecular or morphological data have been collected.There is extensive publication of new phylogenies, data, and inference methods, but little attention to synthesis. We therefore focus on constructing, to our knowledge, the first comprehensive tree of life through the integration of published phylogenies with taxonomic information. Phylogenies by systematists with expertise in particular taxa likely represent the best estimates of relationships for individual clades. By focusing on trees instead of raw data, we avoid issues of dataset assembly (6). However, most published phylogenies are available only as jour...

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Section: Discussionmentioning

confidence: 99%

Synthesis of phylogeny and taxonomy into a comprehensive tree of life

Hinchliff

Smith

Allman³

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

607

585

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“…Instead, only preliminary attempts for reporting data have been made (Leebens-Mack et al 2006). Obviously, manual and semi-automated controls that are in use for single-gene phylogenetics can still be applied, though they are very time-consuming (e.g., several weeks of tedious work in the case of our two previous studies, Philippe et al 2011b andLaurin-Lemay et al 2012) and subjective (i.e., not easily reproducible nor easily assessable by referees).…”

Section: Data Quality Controlmentioning

confidence: 99%

Pitfalls in supermatrix phylogenomics

Piégay

Vienne

Ranwez

et al. 2017

EJT

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122

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Abstract. In the mid-2000s, molecular phylogenetics turned into phylogenomics, a development that improved the resolution of phylogenetic trees through a dramatic reduction in stochastic error. While some then predicted "the end of incongruence", it soon appeared that analysing large amounts of sequence data without an adequate model of sequence evolution amplifies systematic error and leads to phylogenetic artefacts. With the increasing flood of (sometimes low-quality) genomic data resulting from the rise of high-throughput sequencing, a new type of error has emerged. Termed here "data errors", it lumps together several kinds of issues affecting the construction of phylogenomic supermatrices (e.g., sequencing and annotation errors, contaminant sequences). While easy to deal with at a single-gene scale, such errors become very difficult to avoid at the genomic scale, both because hand curating thousands of sequences is prohibitively time-consuming and because the suitable automated bioinformatics tools are still in their infancy. In this paper, we first review the pitfalls affecting the construction of supermatrices European Journal of Taxonomy 283: 1-25 (2017) 2 and the strategies to limit their adverse effects on phylogenomic inference. Then, after discussing the relative non-issue of missing data in supermatrices, we briefly present the approaches commonly used to reduce systematic error.Keywords. Phylogenomics, supermatrix, systematic error, data quality, incongruence. From phylogenetics to phylogenomicsThe last two decades have seen significant changes taking place in the practice of phylogenetic inference from molecular data. These changes have mostly been triggered by the ever-increasing size of the datasets being assembled and analysed in the form of supermatrices of concatenated genes (Driskell et al. 2004). The evolution of the size and shape of these datasets, thanks to new technological advances in DNA amplification and sequencing, has been associated with different phases in the field of phylogenetic inference ( Fig. 1). In the early days of molecular phylogenetics based on PCR amplification and manual Sanger sequencing of a handful of genes for a limited number of taxa, the field laid somewhat in the "uncertainty zone" dominated by stochastic error, even if some naïve over-interpretations did occur. Then, the development of automated Sanger sequencing typically led to a few standard genes (e.g., SSU rRNA, elongation factors, RNA polymerases) being sequenced for a large number of taxa, projecting the field into the "irresolution zone" with only limited information available to resolve a large number of nodes. Yet, at that time the focus was not on resolving large-scale phylogenetic relationships, rather than on identifying species or strains by molecular means, which eventually gave rise to the field of DNA barcoding (Hebert et al. 2003). The first genome sequences from model organisms reverted the situation, with few taxa being sequenced for their entire set of genes causing a sort of "inconsis...

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“…We might also ignore some of the less significant choices made by the experimenters and to use the 'minimum information required by an experiment'. This particular idea has formed the basis of standardized object models for specific experiment types to enable collaboration and data sharing [4][5][6][7]. This natural parallel between the designs of experiments and schemas for bioinformatics systems prompts and enables our work.…”

Section: 'Experimental Type'mentioning

confidence: 99%