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Targeted enrichment: maximizing orthologous gene comparisons across deep evolutionary time.

ABSTRACT: Estimated phylogenies of evolutionarily diverse taxa will be well supported and more likely to be historically accurate when the analysis contains large amounts of data-many genes sequenced across many taxa. Inferring such phylogenies for non-model organisms is challenging given limited resources for whole-genome sequencing. We take advantage of genomic data from a single species to test the limits of hybridization-based enrichment of hundreds of exons across frog species that diverged up to 250 million years ago. Enrichment success for a given species depends greatly on the divergence time between it and the reference species, and the resulting alignment contains a significant proportion of missing data. However, our alignment generates a well-supported phylogeny of frogs, suggesting that this technique is a practical solution towards resolving relationships across deep evolutionary time.

SUBMITTER: Hedtke SM

PROVIDER: S-EPMC3699465 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Targeted enrichment: maximizing orthologous gene comparisons across deep evolutionary time.

Hedtke Shannon M SM Morgan Matthew J MJ Cannatella David C DC Hillis David M DM

PloS one 20130702 7

Estimated phylogenies of evolutionarily diverse taxa will be well supported and more likely to be historically accurate when the analysis contains large amounts of data-many genes sequenced across many taxa. Inferring such phylogenies for non-model organisms is challenging given limited resources for whole-genome sequencing. We take advantage of genomic data from a single species to test the limits of hybridization-based enrichment of hundreds of exons across frog species that diverged up to 250 ...[more]

PMID: 23844125

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Project description:The potential of a metabolomics method to detect statistically significant perturbations in the metabolome of an organism is enhanced by excellent analytical precision, unequivocal identification, and broad metabolomic coverage. While the former two metrics are usually associated with targeted metabolomics and the latter with non-targeted metabolomics, a systematic comparison of the performance of both approaches has not yet been carried out. The present work reports on the development and performance evaluation of separate targeted and non-targeted metabolomics methods. The targeted approach facilitated determination of 181 metabolites (quantitative analysis of 18 amino acids, 11 biogenic amines, 5 neurotransmitters, 5 nucleobases and semi-quantitative analysis of 50 carnitines, 83 phosphatidylcholines, and 9 sphingomyelins) using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and flow injection-tandem mass spectrometry (FI-MS/MS). Method accuracy and/or precision were assessed using replicate samples of NIST SRM1950 as well as fish liver and brain tissue from Gilthead Bream (Sparus aurata). The non-target approach involved UPLC-high resolution (Orbitrap) mass spectrometry (UPLC-HRMS). Testing of ionization mode and stationary phase revealed that a combination of positive electrospray ionization and HILIC chromatography produced the largest number of chromatographic features during non-target analysis. Furthermore, an evaluation of 4 different sequence drift correction algorithms, and combinations thereof, revealed that batchCorr produced the best precision in almost every test. However, even following correction of non-target data for signal drift, the precision of targeted data was better, confirming our existing assumptions about the strengths of targeted metabolomics. Finally, the accuracy of the online MS2-library mzCloud was evaluated using reference standards for 38 different metabolites. This is among the few studies that have systematically evaluated the performance of targeted and non-targeted metabolomics and provides new insight into the advantages and disadvantages of each approach.

Dataset Information

Targeted enrichment: maximizing orthologous gene comparisons across deep evolutionary time.

Publications

Targeted enrichment: maximizing orthologous gene comparisons across deep evolutionary time.

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