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Marginal likelihood estimate comparisons to obtain optimal species delimitations in Silene sect. Cryptoneurae (Caryophyllaceae).

ABSTRACT: Coalescent-based inference of phylogenetic relationships among species takes into account gene tree incongruence due to incomplete lineage sorting, but for such methods to make sense species have to be correctly delimited. Because alternative assignments of individuals to species result in different parametric models, model selection methods can be applied to optimise model of species classification. In a Bayesian framework, Bayes factors (BF), based on marginal likelihood estimates, can be used to test a range of possible classifications for the group under study. Here, we explore BF and the Akaike Information Criterion (AIC) to discriminate between different species classifications in the flowering plant lineage Silene sect. Cryptoneurae (Caryophyllaceae). We estimated marginal likelihoods for different species classification models via the Path Sampling (PS), Stepping Stone sampling (SS), and Harmonic Mean Estimator (HME) methods implemented in BEAST. To select among alternative species classification models a posterior simulation-based analog of the AIC through Markov chain Monte Carlo analysis (AICM) was also performed. The results are compared to outcomes from the software BP&P. Our results agree with another recent study that marginal likelihood estimates from PS and SS methods are useful for comparing different species classifications, and strongly support the recognition of the newly described species S. ertekinii.

SUBMITTER: Aydin Z

PROVIDER: S-EPMC4162574 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Project description:Flower color polymorphisms are widely used as model traits from genetics to ecology, yet determining the biochemical and molecular basis can be challenging. Anthocyanin-based flower color variations can be caused by at least 12 structural and three regulatory genes in the anthocyanin biosynthetic pathway (ABP). We use mRNA-Seq to simultaneously sequence and estimate expression of these candidate genes in nine samples of Silene littorea representing three color morphs (dark pink, light pink and white) across three developmental stages in hopes of identifying the cause of flower color variation. We identified 29 putative paralogs for the 15 candidate genes in the ABP. We assembled complete coding sequences for 16 structural loci and nine of ten regulatory loci. Among these 29 putative paralogs, we identified 622 SNPs, yet only nine synonymous SNPs in Ans had allele frequencies that differentiated pigmented petals (dark pink and light pink) from white petals. These Ans allele frequency differences were further investigated with an expanded sequencing survey of 38 individuals, yet no SNPs consistently differentiated the color morphs. We also found one locus, F3h1, with strong differential expression between pigmented and white samples (>42x). This may be caused by decreased expression of Myb1a in white petal buds. Myb1a in S. littorea is a regulatory locus closely related to Subgroup 7 Mybs known to regulate F3h and other loci in the first half of the ABP in model species. We then compare the mRNA-Seq results with petal biochemistry which revealed cyanidin as the primary anthocyanin and five flavonoid intermediates. Concentrations of three of the flavonoid intermediates were significantly lower in white petals than in pigmented petals (rutin, quercetin and isovitexin). The biochemistry results for rutin, quercetin, luteolin and apigenin are consistent with the transcriptome results suggesting a blockage at F3h, possibly caused by downregulation of Myb1a.

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Marginal likelihood estimate comparisons to obtain optimal species delimitations in Silene sect. Cryptoneurae (Caryophyllaceae).

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