TreeBASE Search-Analyses for study 12410

@ARTICLE{TreeBASE2Ref20465, author = {Carmelo And?jar and Jos? Serrano and Jes?s G?mez-Zurita}, title = {Winding up the molecular clock in the genus Carabus (Coleoptera: Carabidae): assessment of methodological decisions on rate and node age estimation.}, year = {2012}, keywords = {Molecular clock, rates of molecular evolution, deep node ages, partitioning model, clock model, outgroup selection, Gblocks, mitochondrial genes, nuclear genes, Coleoptera, Carabus.}, doi = {10.1186/1471-2148-12-40}, url = {http://}, pmid = {}, journal = {BMC Evolutionary Biology}, volume = {12}, number = {}, pages = {40}, abstract = {Background: Rates of molecular evolution are known to vary across taxa and among genes, and this requires rate calibration for each specific dataset based on external information. Calibration is sensitive to evolutionary model parameters, partitioning schemes and clock model. However, the way in which these and other analytical aspects affect both the rates and the resulting clade ages from calibrated phylogenies are not yet well understood. To investigate these aspects we have conducted calibration analyses for the genus Carabus (Coleoptera, Carabidae) on five mitochondrial and four nuclear DNA fragments with 7888 nt total length, testing different clock models and partitioning schemes to select the most suitable using Bayes Factors comparisons. Results: Results support an origin of the genus Carabus during the Oligocene in the Eurasian continent followed by a Miocene differentiation that originated all main extant lineages. We used these data to investigate the effect of ambiguous character and outgroup inclusion on both rates of molecular evolution and TMRCA of Carabus. We found a considerable variation in rates of molecular evolution depending on the fragment studied (ranging from 5.02% in cob to 0.26% divergence/My in LSU-A), but also on analytical conditions. Alternative choices of clock model, partitioning scheme, treatment of ambiguous characters, and outgroup inclusion resulted in rate increments ranging from 28% (HUWE1) to 1000% (LSU-b and ITS2) and increments in the TMRCA of Carabus ranging from 8.4% (cox1-a) to 540% (ITS2). Conclusions: The combination of several genes is found the best strategy to minimise both the idiosyncratic behaviors of individual markers and the effect of analytical aspects in rate and age estimations. Our results highlight the importance of estimating rates of molecular evolution for each specific dataset, selecting for optimal clock and partitioning models as well as other methodological issues potentially affecting rate estimation. } }

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Analyses for Study 12410

Citation title: "Winding up the molecular clock in the genus Carabus (Coleoptera: Carabidae): assessment of methodological decisions on rate and node age estimation.".

Study name: "Winding up the molecular clock in the genus Carabus (Coleoptera: Carabidae): assessment of methodological decisions on rate and node age estimation.".

This study is part of submission 12410 (Status: Published).

Analyses

Analysis 1

Analysis details

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Input data

1 Input object(s)

Analysis step

cob, outgroup dataset --

Output data

1 Output object(s)

Analysis 2

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Input data

1 Input object(s)

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nd5 gene outgroup dataset --

Output data

1 Output object(s)

Analysis 3

Analysis details

Name

Input data

1 Input object(s)

Analysis step

cox1-a outgroup dataset --

Output data

1 Output object(s)

Analysis 4

Analysis details

Name

Input data

1 Input object(s)

Analysis step

cox1-b outgroup dataset --

Output data

1 Output object(s)

Analysis 5

Analysis details

Name

Input data

1 Input object(s)

Analysis step

HUWE1 outgroup dataset complete matrix --

Output data

1 Output object(s)

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1 Input object(s)

Analysis step

HUWE1 outgroup dataset only coding matrix --

Output data

1 Output object(s)

Analysis 6

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Name

Input data

1 Input object(s)

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MIT outgroup dataset --

Output data

1 Output object(s)

Analysis 7

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1 Input object(s)

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MITNUC outgroup dataset --

Output data

1 Output object(s)

Analysis 8

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Input data

1 Input object(s)

Analysis step

NUC outgroup dataset --

Output data

1 Output object(s)

Analysis 9

Analysis details

Name
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Input data

1 Input object(s)

Analysis step

rrnL outgroup dataset complete matrix --

Output data

1 Output object(s)

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1 Input object(s)

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rrnL outgroup dataset allgaps matrix --

Output data

1 Output object(s)

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1 Input object(s)

Analysis step

rrnL outgroup dataset Nogaps matrix --

Output data

1 Output object(s)

Analysis 10

Analysis details

Name
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Input data

1 Input object(s)

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LSU-a outgroup dataset complete matrix --

Output data

1 Output object(s)

Input data

1 Input object(s)

Analysis step

LSU-a outgroup dataset allgaps matrix --

Output data

1 Output object(s)

Input data

1 Input object(s)

Analysis step

LSU-a outgroup dataset Nogaps matrix --

Output data

1 Output object(s)

Analysis 11

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1 Input object(s)

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LSU-b outgroup dataset complete matrix --

Output data

1 Output object(s)

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1 Input object(s)

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LSU-b outgroup dataset allgaps matrix --

Output data

1 Output object(s)

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1 Input object(s)

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LSU-b outgroup dataset Nogaps matrix --

Output data

1 Output object(s)

Analysis 12

Analysis details

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Input data

1 Input object(s)

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ITS2 outgroup dataset complete matrix --

Output data

1 Output object(s)

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1 Input object(s)

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ITS2 outgroup dataset allgaps matrix --

Output data

1 Output object(s)

Input data

1 Input object(s)

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ITS2 outgroup dataset Nogaps matrix --

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1 Output object(s)

Analysis 13

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1 Input object(s)

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cox1-a ingroup dataset --

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1 Output object(s)

Analysis 14

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1 Input object(s)

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cox1-b ingroup dataset --

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1 Output object(s)

Analysis 15

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1 Input object(s)

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cob_ingroup_dataset --

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1 Output object(s)

Analysis 16

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1 Input object(s)

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nd5 gene ingroup dataset --

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1 Output object(s)

Analysis 17

Analysis details

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Input data

1 Input object(s)

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HUWE1 ingroup dataset complete matrix --

Output data

1 Output object(s)

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1 Input object(s)

Analysis step

HUWE1 ingroup dataset only coding matrix --

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1 Output object(s)

Analysis 18

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1 Input object(s)

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MIT ingroup dataset --

Output data

1 Output object(s)

Analysis 19

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1 Input object(s)

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NUC ingroup dataset --

Output data

1 Output object(s)

Analysis 20

Analysis details

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Input data

1 Input object(s)

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MITNUC ingroup dataset --

Output data

1 Output object(s)

Analysis 21

Analysis details

Name

Input data

1 Input object(s)

Output data

1 Output object(s)

Input data

1 Input object(s)

Analysis step

rrnL ingroup dataset allgaps matrix --

Output data

1 Output object(s)

Input data

1 Input object(s)

Analysis step

rrnL ingroup dataset Nogaps matrix --

Output data

1 Output object(s)

Analysis 22

Analysis details

Name

Input data

1 Input object(s)

Analysis step

LSU-a ingroup dataset complete matrix --

Output data

1 Output object(s)

Input data

1 Input object(s)

Analysis step

LSU-a ingroup dataset allgaps matrix --

Output data

1 Output object(s)

Input data

1 Input object(s)

Analysis step

LSU-a ingroup dataset Nogaps matrix --

Output data

1 Output object(s)

Analysis 23

Analysis details

Name

Input data

1 Input object(s)

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LSU-b ingroup dataset complete matrix --

Output data

1 Output object(s)

Input data

1 Input object(s)

Analysis step

LSU-b ingroup dataset allgaps matrix --

Output data

1 Output object(s)

Input data

1 Input object(s)

Analysis step

LSU-b ingroup dataset Nogaps matrix --

Output data

1 Output object(s)

Analysis 24

Analysis details

Input data

1 Input object(s)

Output data

1 Output object(s)

Input data

1 Input object(s)

Analysis step

ITS2 ingroup dataset allgaps matrix --

Output data

1 Output object(s)

Input data

1 Input object(s)

Analysis step

ITS2 ingroup dataset Nogaps matrix --

Output data