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Open Access Highly Accessed Research article

Discovery of the photosynthetic relatives of the "Maltese mushroom" Cynomorium

Daniel L Nickrent1*, Joshua P Der1 and Frank E Anderson2

Author Affiliations

1 Department of Plant Biology, Southern Illinois University, Carbondale, IL 62901-6509, USA

2 Department of Zoology, Southern Illinois University, Carbondale, IL 62901-6501, USA

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BMC Evolutionary Biology 2005, 5:38  doi:10.1186/1471-2148-5-38

Published: 21 June 2005

Additional files

Additional File 1:

Taxon sampling – global data set. MS Excel file giving taxon sampling by gene and GenBank accession numbers for the global data set.

Format: XLS Size: 30KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional File 2:

Taxon sampling – Saxifragales data set. MS Excel file giving taxon sampling by gene and GenBank accession numbers for the Saxifragales data set.

Format: XLS Size: 31KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional File 3:

BI tree from global data set. Bayesian inference majority rule consensus tree of 50,000 trees derived from the global data set composed of nuclear SSU rDNA, chloroplast rbcL, atpB, and mitochondrial matR. Trees were generated in two separate BI analyses, each run for 15 million generations with trees from the first 2.5 million generations removed as burn-in.

Format: PDF Size: 864KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

Additional File 4:

BI tree from the nuclear SSU rDNA partition. Bayesian inference majority rule consensus tree of 50,000 trees derived from the nuclear SSU rDNA partition. Trees were generated in two separate BI analyses, each run for 15 million generations with trees from the first 2.5 million generations removed as burn-in.

Format: PDF Size: 756KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

Additional File 5:

ML tree from the nuclear SSU rDNA partition. Phylogram from maximum likelihood (ML) analysis of the nuclear SSU rDNA partition (GTR+I+Γ model. The tree was generated using a successive approximations approach in which a MP tree was generated and used as a starting tree for additional branch swapping under ML.

Format: PDF Size: 544KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

Additional File 6:

BI tree from the mitochondrial matR partition. Bayesian inference majority rule consensus tree of 50,000 trees derived from the mitochondrial matR partition. Trees were generated in two separate BI analyses, each run for 15 million generations with trees from the first 2.5 million generations removed as burn-in.

Format: PDF Size: 741KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

Additional File 7:

BI tree from the Saxifragales data set. Bayesian inference majority rule consensus tree of 50,000 trees derived from the Saxifragales data set. Trees were generated in two separate BI analyses, each run for 15 million generations with trees from the first 2.5 million generations removed as burn-in.

Format: PDF Size: 748KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

Additional File 8:

MP phylogram from the global data set. Data set of combined nuclear SSU rDNA, chloroplast rbcL and atpB and mitochondrial matR. Tree one of four is shown, with branch lengths drawn proportional to the number of changes.

Format: PDF Size: 524KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

Additional File 9:

BI majority rule phylogram from the global data set. Bayesian inference majority rule consensus phylogram from the global data set (nuclear SSU rDNA, chloroplast rbcL and atpB and mitochondrial matR). Branch lengths are means of the branch length posterior probability distribution across all post burn-in trees from one of the two MrBayes runs (branch lengths resulting from the other run are nearly identical).

Format: PDF Size: 529KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data