Arong Luo

Performance of criteria for selecting evolutionary models in phylogenetics: a comprehensive study based on simulated datasets.

BackgroundExplicit evolutionary models are required in maximum-likelihood and Bayesian inference, the two methods that are overwhelmingly used in phylogenetic studies of DNA sequence data. Appropriate selection of nucleotide substitution models is important because the use of incorrect models can mislead phylogenetic inference. To better understand the performance of different model-selection criteria, we used 33,600 simulated data sets to analyse the accuracy, precision, dissimilarity, and biases of the hierarchical likelihood-ratio test, Akaike information criterion, Bayesian information criterion, and decision theory.ResultsWe demonstrate that the Bayesian information criterion and decision theory are the most appropriate model-selection criteria because of their high accuracy and precision. Our results also indicate that in some situations different models are selected by different criteria for the same dataset. Such dissimilarity was the highest between the hierarchical likelihood-ratio test and Akaike information criterion, and lowest between the Bayesian information criterion and decision theory. The hierarchical likelihood-ratio test performed poorly when the true model included a proportion of invariable sites, while the Bayesian information criterion and decision theory generally exhibited similar performance to each other.ConclusionsOur results indicate that the Bayesian information criterion and decision theory should be preferred for model selection. Together with model-adequacy tests, accurate model selection will serve to improve the reliability of phylogenetic inference and related analyses.

Characterization of the complete mitochondrion genome of diurnal Moth Amata emma (Butler) (Lepidoptera: Erebidae) and its phylogenetic implications.

Mitogenomes can provide information for phylogenetic analyses and evolutionary biology. The complete mitochondrial genome of Amata emma (Lepidoptera: Erebidae) was sequenced and analyzed in the study. The circular genome is 15,463 bp in size, with the gene content, orientation and order identical to other ditrysian insects. The genome composition of the major strand shows highly A+T biased and exhibits negative AT-skew and GC-skew. The initial codons are the canonical putative start codons ATN with the exception of cox1 gene which uses CGA instead. Ten genes share complete termination codons TAA, and three genes use incomplete stop codons TA or T. Additionally, the codon distribution and Relative Synonymous Codon Usage of the 13 PCGs in the A. emma mitogenome are consistent with those in other Noctuid mitogenomes. All tRNA genes have typical cloverleaf secondary structures, except for the trnS1 (AGN) gene, in which the dihydrouridine (DHU) arm is simplified down to a loop. The secondary structures of two rRNA genes broadly conform with the models proposed for these genes of other Lepidopteran insects. Except for the A+T-rich region, there are three major intergenic spacers, spanning at least 10 bp and five overlapping regions. There are obvious differences in the A+T-rich region between A. emma and other Lepidopteran insects reported previously except that the A+T-rich region contains an ‘ATAGA’ -like motif followed by a 19 bp poly-T stretch and a (AT)9 element preceded by the ‘ATTTA’ motif. It neither has a poly-A (in the α strand) upstream trnM nor potential stem-loop structures and just has some simple structures like (AT)nGTAT. The phylogenetic relationships based on nucleotide sequences of 13 PCGs using Bayesian inference and maximum likelihood methods provided a well-supported a broader outline of Lepidoptera and which agree with the traditional morphological classification and recently working, but with a much higher support.

Positive selection on hemagglutinin and neuraminidase genes of H1N1 influenza viruses

BackgroundSince its emergence in March 2009, the pandemic 2009 H1N1 influenza A virus has posed a serious threat to public health. To trace the evolutionary path of these new pathogens, we performed a selection-pressure analysis of a large number of hemagglutinin (HA) and neuraminidase (NA) gene sequences of H1N1 influenza viruses from different hosts.ResultsPhylogenetic analysis revealed that both HA and NA genes have evolved into five distinct clusters, with further analyses indicating that the pandemic 2009 strains have experienced the strongest positive selection. We also found evidence of strong selection acting on the seasonal human H1N1 isolates. However, swine viruses from North America and Eurasia were under weak positive selection, while there was no significant evidence of positive selection acting on the avian isolates. A site-by-site analysis revealed that the positively selected sites were located in both of the cleaved products of HA (HA1 and HA2), as well as NA. In addition, the pandemic 2009 strains were subject to differential selection pressures compared to seasonal human, North American swine and Eurasian swine H1N1 viruses.ConclusionsMost of these positively and/or differentially selected sites were situated in the B-cell and/or T-cell antigenic regions, suggesting that selection at these sites might be responsible for the antigenic variation of the viruses. Moreover, some sites were also associated with glycosylation and receptor-binding ability. Thus, selection at these positions might have helped the pandemic 2009 H1N1 viruses to adapt to the new hosts after they were introduced from pigs to humans. Positive selection on position 274 of NA protein, associated with drug resistance, might account for the prevalence of drug-resistant variants of seasonal human H1N1 influenza viruses, but there was no evidence that positive selection was responsible for the spread of the drug resistance of the pandemic H1N1 strains.

The complete mitochondrial genome of the rice moth, Corcyra cephalonica

Abstract The complete mitochondrial genome (mitogenome) of the rice moth, Corcyra cephalonica Stainton (Lepidoptera: Pyralidae) was determined as a circular molecular of 15,273 bp in size. The mitogenome composition (37 genes) and gene order are the same as the other lepidopterans. Nucleotide composition of the C. cephalonica mitogenome is highly A+T biased (80.43%) like other insects. Twelve protein-coding genes start with a typical ATN codon, with the exception of coxl gene, which uses CGA as the initial codon. Nine protein-coding genes have the common stop codon TAA, and the nad2, cox1, cox2, and nad4 have single T as the incomplete stop codon. 22 tRNA genes demonstrated cloverleaf secondary structure. The mitogenome has several large intergenic spacer regions, the spacer1 between trnQ gene and nad2 gene, which is common in Lepidoptera. The spacer 3 between trnE and trnF includes microsatellite-like repeat regions (AT)18 and (TTAT)3. The spacer 4 (16 bp) between trnS2 gene and nad1 gene has a motif ATACTAT; another species, Sesamia inferens encodes ATCATAT at the same position, while other lepidopteran insects encode a similar ATACTAA motif. The spacer 6 is A+T rich region, include motif ATAGA and a 20-bp poly(T) stretch and two microsatellite (AT)9, (AT)8 elements.

A simulation study of sample size for DNA barcoding

Abstract For some groups of organisms, DNA barcoding can provide a useful tool in taxonomy, evolutionary biology, and biodiversity assessment. However, the efficacy of DNA barcoding depends on the degree of sampling per species, because a large enough sample size is needed to provide a reliable estimate of genetic polymorphism and for delimiting species. We used a simulation approach to examine the effects of sample size on four estimators of genetic polymorphism related to DNA barcoding: mismatch distribution, nucleotide diversity, the number of haplotypes, and maximum pairwise distance. Our results showed that mismatch distributions derived from subsamples of ≥20 individuals usually bore a close resemblance to that of the full dataset. Estimates of nucleotide diversity from subsamples of ≥20 individuals tended to be bell‐shaped around that of the full dataset, whereas estimates from smaller subsamples were not. As expected, greater sampling generally led to an increase in the number of haplotypes. We also found that subsamples of ≥20 individuals allowed a good estimate of the maximum pairwise distance of the full dataset, while smaller ones were associated with a high probability of underestimation. Overall, our study confirms the expectation that larger samples are beneficial for the efficacy of DNA barcoding and suggests that a minimum sample size of 20 individuals is needed in practice for each population.

Comparison of Methods for Molecular Species Delimitation Across a Range of Speciation Scenarios

Abstract.— Species are fundamental units in biological research and can be defined on the basis of various operational criteria. There has been growing use of molecular approaches for species delimitation. Among the most widely used methods, the generalized mixed Yule‐coalescent (GMYC) and Poisson tree processes (PTP) were designed for the analysis of single‐locus data but are often applied to concatenations of multilocus data. In contrast, the Bayesian multispecies coalescent approach in the software Bayesian Phylogenetics and Phylogeography (BPP) explicitly models the evolution of multilocus data. In this study, we compare the performance of GMYC, PTP, and BPP using synthetic data generated by simulation under various speciation scenarios. We show that in the absence of gene flow, the main factor influencing the performance of these methods is the ratio of population size to divergence time, while number of loci and sample size per species have smaller effects. Given appropriate priors and correct guide trees, BPP shows lower rates of species overestimation and underestimation, and is generally robust to various potential confounding factors except high levels of gene flow. The single‐threshold GMYC and the best strategy that we identified in PTP generally perform well for scenarios involving more than a single putative species when gene flow is absent, but PTP outperforms GMYC when fewer species are involved. Both methods are more sensitive than BPP to the effects of gene flow and potential confounding factors. Case studies of bears and bees further validate some of the findings from our simulation study, and reveal the importance of using an informed starting point for molecular species delimitation. Our results highlight the key factors affecting the performance of molecular species delimitation, with potential benefits for using these methods within an integrative taxonomic framework.

A Simulation-Based Evaluation of Total-Evidence Dating Under the Fossilized Birth-Death Process

Bayesian molecular dating is widely used to study evolutionary timescales. This procedure usually involves phylogenetic analysis of nucleotide sequence data, with fossil-based calibrations applied as age constraints on internal nodes of the tree. An alternative approach is Bayesian total-evidence dating, which involves the joint analysis of molecular data from present-day taxa and morphological data from both extant and fossil taxa. Part of its appeal stems from the fossilized birth-death process, which provides a model of lineage diversification for the prior on the tree topology and node times. However, total-evidence dating faces a number of considerable challenges, especially those associated with fossil sampling and evolutionary models for morphological characters. We conducted a simulation study to evaluate the performance of total-evidence dating with the fossilized birth-death model. We simulated fossil occurrences and the evolution of nucleotide sequences and morphological characters under a wide range of conditions. Our analyses show that fossil occurrences have a greater influence than the degree of among-lineage rate variation or the number of morphological characters on estimates of node times and the tree topology. Total-evidence dating generally performs well in recovering the relationships among extant taxa, but has difficulties in correctly placing fossil taxa in the tree and identifying the number of sampled ancestors. The method yields accurate estimates of the origin time of the fossilized birth-death process and the ages of the root and crown group, although the precision of these estimates varies with the probability of fossil occurrence. The exclusion of morphological characters results in a slight overestimation of node times, whereas the exclusion of nucleotide sequences has a negative impact on inference of the tree topology. Overall, our results provide a detailed view of the performance of total-evidence dating, which will inform further development of the method and its application to key questions in evolutionary biology.

Revision of the Anthidiellum Cockerell, 1904 of China (Hymenoptera, Apoidea, Megachilidae, Anthidiini).

The resin bees of the genus Anthidiellum Cockerell, 1904 are revised for China. Seven species are confirmed to occur in China including five new combinations: A. (Pycnanthidium) carinatum (Wu, 1962) comb. nov., A. (P.) coronum (Wu, 2004a) comb. nov., A. (P.) latipes (Bingham, 1897) comb. nov., A. (Clypanthidium) popovii (Wu, 1962) comb. nov., and A. (Anthidiellum) yunnanensis (Wu, 1962) comb. nov.. These five species had previously been classified as Trachusa (Paraanthidium), which is characterized by much larger-bodied bees (only four species of Trachusa (Paraanthidium) are confirmed to occur in China after this study; others reported in the literature were misplaced to genus). Additionally, Anthidiellum ludingensis Wu, 1993, and Anthidiellum (Anthidiellum) xinjiangensis Wu, 2004b, are removed from Anthidiellum forming the new combinations Pseudoanthidium (Pseudoanthidium) ludingense (Wu, 1993) and P. (P.) xinjiangense (Wu, 2004b), thus extending the range of the genus in China to include Sichuan. Illustrations and a key to known Chinese Anthidiellum species are provided.