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37 results for “AFLP data”
Data from: Influence of parameter settings in automated scoring of AFLPs on population genetic analysis
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Data from: Comparative analyses of plastid and AFLP data suggest different colonization history and asymmetric hybridisation between Betula pubescens and B. nana
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Data from: A novel method to infer the origin of polyploids from AFLP data reveals that the Alpine polyploid complex of Senecio carniolicus (Asteraceae) evolved mainly via autopolyploidy
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Data from: Dealing with AFLP genotyping errors to reveal genetic structure in Plukenetia volubilis (Euphorbiaceae) in the Peruvian Amazon
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Data from: Can AFLP genome scans detect small islands of differentiation? The case of shell sculpture variation in the periwinkle Echinolittorina hawaiiensis
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Data from: One, two or three? Integrative species delimitation of short-range endemic Hemicycla species (Gastropoda: Helicidae) from the Canary Islands based on morphology, barcoding, AFLP and ddRADseq data
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Data from: Identifying and reducing AFLP genotyping error: an example of tradeoffs when comparing population structure in broadcast spawning versus brooding oysters
Phylogeographic inferences about gene flow are strengthened through comparison of co-distributed taxa, but also depend on adequate genomic sampling. Amplified Fragment Length Polymorphisms (AFLP) provide a rapid and inexpensive source of multilocus allele frequency data for making genomically robust inferences. Every AFLP study initially generates markers with a range of locus-specific genotyping error rates and applies criteria to select a subset for analysis. However, there has been very little empirical evaluation of the best tradeoff between culling all but the lowest-error loci to minimize overall genotyping error versus the potential for increasing population genetic signal by retaining more loci. Here, we used AFLPs to compare population structure in co-distributed broadcast spawning (Crassostrea virginica) and brooding (Ostrea equestris) oyster species. Using existing methods for almost entirely automated marker selection and scoring, genotyping error tradeoffs were evaluated by comparing results across a nested series of datasets with mean mismatch errors of 0, 1, 2, 3, 4 and >4%. Artifactual population structure was diagnosed in high-error datasets and we assessed the low-error point at which expected population substructure signal was lost. In both species we identified substructure patterns deemed to be inaccurate at error rates {less than or equal to}2% and >4%. In the species comparison, the optimum datasets showed higher gene flow for the brooding oyster with more oceanic salinity tolerances. AFLP tradeoffs may differ among studies, but our results suggest that important signal may be lost in the pursuit of 'acceptable' error levels and our procedures provide a general method for empirically exploring these tradeoffs.
Data from: Galega orientalis is more diverse than Galega officinalis in Caucasus – whole-genome AFLP analysis and phylogenetics of symbiosis-related genes
Legume plants can obtain combined nitrogen for their growth in an efficient way through symbiosis with specific bacteria. The symbiosis between Rhizobium galegae and its host plant Galega is an interesting case where the plant species G. orientalis and G. officinalis form effective, nitrogen fixing, symbioses only with the appropriate rhizobial counterpart, R. galegae bv. orientalis and R. galegae bv. officinalis respectively. There is plenty of information available on the symbiotic properties of nitrogen fixing rhizobia, while more information is needed on the properties of the host plants. The Caucasus region in Eurasia has been identified as the gene centre (centre of origin) of G. orientalis, although both G. orientalis and G. officinalis can be found in this region. In this study, the diversity of these two Galega species in Caucasus was investigated to test the hypothesis that in this region G. orientalis is more diverse than G. officinalis. The amplified fragment length polymorphism (AFLP) fingerprinting performed here showed that the populations of G. orientalis and R. galegae bv. orientalis are more diverse than those of G. officinalis and R. galegae bv. officinalis respectively. These results are consistent with the centre of origin status of Caucasus for G. orientalis. Phylogenies of the symbiosis-related plant genes NORK and Nfr5 were congruent with the AFLP result from a diversity point of view. Finally, the results of this work indicate that the NORK and Nfr5 genes of Galega follow the same evolutionary pattern as conserved plant genes.
Data from: A call for more transparent reporting of error rates: the quality of AFLP data in ecological and evolutionary research
Despite much discussion of the importance of quantifying and reporting genotyping error in molecular studies, it is still not standard practice in the literature. This is particularly a concern for amplified fragment length polymorphism (AFLP) studies, where differences in laboratory, peak-calling and locus-selection protocols can generate data sets varying widely in genotyping error rate, the number of loci used and potentially estimates of genetic diversity or differentiation. In our experience, papers rarely provide adequate information on AFLP reproducibility, making meaningful comparisons among studies difficult. To quantify the extent of this problem, we reviewed the current molecular ecology literature (470 recent AFLP articles) to determine the proportion of studies that report an error rate and follow established guidelines for assessing error. Fifty-four per cent of recent articles do not report any assessment of data set reproducibility. Of those studies that do claim to have assessed reproducibility, the majority (~90%) either do not report a specific error rate or do not provide sufficient details to allow the reader to judge whether error was assessed correctly. Even of the papers that do report an error rate and provide details, many (≥23%) do not follow recommended standards for quantifying error. These issues also exist for other marker types such as microsatellites, and next-generation sequencing techniques, particularly those which use restriction enzymes for fragment generation. Therefore, we urge all researchers conducting genotyping studies to estimate and more transparently report genotyping error using existing guidelines and encourage journals to enforce stricter standards for the publication of genotyping studies.
Data from: Nonspecific PCR amplification by high-fidelity polymerases: implications for next-generation sequencing of AFLP markers.
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Data from: Identifying insecticide resistance genes in mosquito by combining AFLP genome scan and 454 pyrosequencing
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Data from: A call for more transparent reporting of error rates: the quality of AFLP data in ecological and evolutionary research
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Data from: Identifying and reducing AFLP genotyping error: an example of tradeoffs when comparing population structure in broadcast spawning versus brooding oysters
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Data from: Optimisation of AFLP for extremely large genomes over 70 Gb.
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Data from: Galega orientalis is more diverse than Galega officinalis in Caucasus – whole-genome AFLP analysis and phylogenetics of symbiosis-related genes
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Data from: Distribution and genetic diversity of the rare plant Veratrum woodii (Liliales: Melanthiaceae) in Georgia: a preliminary study with AFLP fingerprint data
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Fig. 1 in Floral scent and its correlation with AFLP data in Sorbus
Fig. 1 Cluster analysis (UPGMA) of the scent data based on the Jaccard index of S. latifolia taxa S. adeana (plus sign), S. franconica (asterisk), and S. cordigastensis (multiplication sign) as well as their parental species
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OpenNeuro
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