Dataset Information

RAD-ADAPT: Software for modelling clonogenic assay data in radiation biology.

ABSTRACT: We present a comprehensive software program, RAD-ADAPT, for the quantitative analysis of clonogenic assays in radiation biology. Two commonly used models for clonogenic assay analysis, the linear-quadratic model and single-hit multi-target model, are included in the software. RAD-ADAPT uses maximum likelihood estimation method to obtain parameter estimates with the assumption that cell colony count data follow a Poisson distribution. The program has an intuitive interface, generates model prediction plots, tabulates model parameter estimates, and allows automatic statistical comparison of parameters between different groups. The RAD-ADAPT interface is written using the statistical software R and the underlying computations are accomplished by the ADAPT software system for pharmacokinetic/pharmacodynamic systems analysis. The use of RAD-ADAPT is demonstrated using an example that examines the impact of pharmacologic ATM and ATR kinase inhibition on human lung cancer cell line A549 after ionizing radiation.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC5396547 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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RAD-ADAPT: Software for modelling clonogenic assay data in radiation biology.

Zhang Yaping Y Hu Kaiqiang K Beumer Jan H JH Bakkenist Christopher J CJ D'Argenio David Z DZ

DNA repair 20170220

We present a comprehensive software program, RAD-ADAPT, for the quantitative analysis of clonogenic assays in radiation biology. Two commonly used models for clonogenic assay analysis, the linear-quadratic model and single-hit multi-target model, are included in the software. RAD-ADAPT uses maximum likelihood estimation method to obtain parameter estimates with the assumption that cell colony count data follow a Poisson distribution. The program has an intuitive interface, generates model predic ...[more]

PMID: 28254357

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Project description:Reduced-representation genome sequencing represents a new source of data for systematics, and its potential utility in interspecific phylogeny reconstruction has not yet been explored. One approach that seems especially promising is the use of inexpensive short-read technologies (e.g., Illumina, SOLiD) to sequence restriction-site associated DNA (RAD)--the regions of the genome that flank the recognition sites of restriction enzymes. In this study, we simulated the collection of RAD sequences from sequenced genomes of different taxa (Drosophila, mammals, and yeasts) and developed a proof-of-concept workflow to test whether informative data could be extracted and used to accurately reconstruct "known" phylogenies of species within each group. The workflow consists of three basic steps: first, sequences are clustered by similarity to estimate orthology; second, clusters are filtered by taxonomic coverage; and third, they are aligned and concatenated for "total evidence" phylogenetic analysis. We evaluated the performance of clustering and filtering parameters by comparing the resulting topologies with well-supported reference trees and we were able to identify conditions under which the reference tree was inferred with high support. For Drosophila, whole genome alignments allowed us to directly evaluate which parameters most consistently recovered orthologous sequences. For the parameter ranges explored, we recovered the best results at the low ends of sequence similarity and taxonomic representation of loci; these generated the largest supermatrices with the highest proportion of missing data. Applications of the method to mammals and yeasts were less successful, which we suggest may be due partly to their much deeper evolutionary divergence times compared to Drosophila (crown ages of approximately 100 and 300 versus 60 Mya, respectively). RAD sequences thus appear to hold promise for reconstructing phylogenetic relationships in younger clades in which sufficient numbers of orthologous restriction sites are retained across species.

Project description:Background and aimsThe genus Asarum sect. Heterotropa (Aristolochiaceae) probably experienced rapid diversification into 62 species centred on the Japanese Archipelago and Taiwan, providing an ideal model for studying island adaptive radiation. However, resolving the phylogeny of this plant group using Sanger sequencing-based approaches has been challenging. To uncover the radiation history of Heterotropa, we employed a phylogenomic approach using double-digested RAD-seq (ddRAD-seq) to yield a sufficient number of phylogenetic signals and compared its utility with that of the Sanger sequencing-based approach.MethodsWe first compared the performance of phylogenetic analysis based on the plastid matK and trnL-F regions and nuclear ribosomal internal transcribed spacer (nrITS), and phylogenomic analysis based on ddRAD-seq using a reduced set of the plant materials (83 plant accessions consisting of 50 species, one subspecies and six varieties). We also conducted more thorough phylogenomic analyses including the reconstruction of biogeographic history using comprehensive samples of 135 plant accessions consisting of 54 species, one subspecies, nine varieties of Heterotropa and six outgroup species.Key resultsPhylogenomic analyses of Heterotropa based on ddRAD-seq were superior to Sanger sequencing-based approaches and resulted in a fully resolved phylogenetic tree with strong support for 72.0-84.8 % (depending on the tree reconstruction methods) of the branches. We clarified the history of Heterotropa radiation and found that A. forbesii, the only deciduous Heterotropa species native to mainland China, is sister to the evergreen species (core Heterotropa) mostly distributed across the Japanese Archipelago and Taiwan.ConclusionsThe core Heterotropa group was divided into nine subclades, each of which had a narrow geographic distribution. Moreover, most estimated dispersal events (22 out of 24) were between adjacent areas, indicating that the range expansion has been geographically restricted throughout the radiation history. The findings enhance our understanding of the remarkable diversification of plant lineages in the Japanese Archipelago and Taiwan.

Dataset Information

RAD-ADAPT: Software for modelling clonogenic assay data in radiation biology.

Publications

RAD-ADAPT: Software for modelling clonogenic assay data in radiation biology.

Similar Datasets

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