Molecular phylogeny of the aquatic beetle family Noteridae (Coleoptera: Adephaga) with an emphasis on data partitioning strategies

Baca, Stephen M.; Toussaint, Emmanuel F. A.; Miller, Kelly B.; Short, Andrew Edward Z.

doi:10.1016/j.ympev.2016.10.016

Cited by 51 publications

(49 citation statements)

References 62 publications

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“…Sanger sequencing applied to phylogenetic studies started more than two decades ago, and since the early application of this technology in phylogenetics, increasing the amount of data has always been one of the major concerns. On the other hand, molecular studies which include few mitochondrial and nuclear genes continue to provide more resolution in several insect taxa (Baca et al, 2016, Vuataz et al, 2016.…”

Section: The Changing Landscape Of Insect Molecular Systematicsmentioning

confidence: 99%

“…Sometimes wood boring beetles, irrespective of the level of symbiosis, can benefit from a transient association with phyto-pathogenic or other fungi which can weaken the host plant, overcome chemical and mechanical defenses and facilitate beetle colonization as well (Persson et al, 2009, Miller et al, 2016. Bark beetles are mainly phloem feeders that live and develop within the cambium layer of secondary phloem (a relatively richer food source) just under the outer bark of trees.…”

Section: Bark and Ambrosia Beetlesmentioning

confidence: 99%

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Molecular phylogeny of bark and ambrosia beetles (Curculionidae: Scolytinae) based on 18 molecular markers

Pistone

Gohli

Jordal

2017

Systematic Entomology

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Section: The Changing Landscape Of Insect Molecular Systematicsmentioning

confidence: 99%

Section: Bark and Ambrosia Beetlesmentioning

confidence: 99%

Molecular phylogeny of bark and ambrosia beetles (Curculionidae: Scolytinae) based on 18 molecular markers

Pistone

Gohli

Jordal

2017

Systematic Entomology

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“…One of these properties is that with standard DNA sequence data of protein-coding genes, one to two thirds of the data typically consist of invariable characters. These tend to be binned together to the exclusion of other data when using the TIGER binning strategy or the k -means algorithm (Baca et al, 2017). A partition made of only such data can lead to very high likelihood estimates for it although the assumption that all invariant sites observed in the dataset are truly invariant is most likely wrong.…”

Section: Methodsmentioning

confidence: 99%

“…In all test cases, partitioning by both TIGER calculated rates and likelihood calculated rates performed better than traditional methods, with likelihood rates doing much better (Frandsen et al, 2015). However, the k -means algorithm has been found to place all invariable characters into one partition (Baca et al, 2017), which causes a problem because this partition then includes characters that can vary given enough time, but do not in the dataset at hand. A very high likelihood due to lack of variation in the data results in selection of a wrong model.…”

Section: Introductionmentioning

confidence: 99%

A simple method for data partitioning based on relative evolutionary rates

Rota

Malm

Chazot

et al. 2018

PeerJ

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BackgroundMultiple studies have demonstrated that partitioning of molecular datasets is important in model-based phylogenetic analyses. Commonly, partitioning is done a priori based on some known properties of sequence evolution, e.g. differences in rate of evolution among codon positions of a protein-coding gene. Here we propose a new method for data partitioning based on relative evolutionary rates of the sites in the alignment of the dataset being analysed. The rates are inferred using the previously published Tree Independent Generation of Evolutionary Rates (TIGER), and the partitioning is conducted using our novel python script RatePartitions. We conducted simulations to assess the performance of our new method, and we applied it to eight published multi-locus phylogenetic datasets, representing different taxonomic ranks within the insect order Lepidoptera (butterflies and moths) and one phylogenomic dataset, which included ultra-conserved elements as well as introns.MethodsWe used TIGER-rates to generate relative evolutionary rates for all sites in the alignments. Then, using RatePartitions, we partitioned the data into partitions based on their relative evolutionary rate. RatePartitions applies a simple formula that ensures a distribution of sites into partitions following the distribution of rates of the characters from the full dataset. This ensures that the invariable sites are placed in a partition with slowly evolving sites, avoiding the pitfalls of previously used methods, such as k-means. Different partitioning strategies were evaluated using BIC scores as calculated by PartitionFinder.ResultsSimulations did not highlight any misbehaviour of our partitioning approach, even under difficult parameter conditions or missing data. In all eight phylogenetic datasets, partitioning using TIGER-rates and RatePartitions was significantly better as measured by the BIC scores than other partitioning strategies, such as the commonly used partitioning by gene and codon position. We compared the resulting topologies and node support for these eight datasets as well as for the phylogenomic dataset.DiscussionWe developed a new method of partitioning phylogenetic datasets without using any prior knowledge (e.g. DNA sequence evolution). This method is entirely based on the properties of the data being analysed and can be applied to DNA sequences (protein-coding, introns, ultra-conserved elements), protein sequences, as well as morphological characters. A likely explanation for why our method performs better than other tested partitioning strategies is that it accounts for the heterogeneity in the data to a much greater extent than when data are simply subdivided based on prior knowledge.

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“…Various molecular phylogenies ranging from single-gene studies using 18S rDNA to more comprehensive multigene analyses have found support for a monophyletic Hydradephaga (e.g. Shull et al, 2001;Ribera et al, 2002;McKenna et al, 2015, but see Maddison et al, 2009 Baca et al (2017b) provided more detailed reviews on hypotheses of relationships among adephagan families. Most species-rich families of Hydradephaga have been the subject of phylogenetic studies in the last decade.…”

Section: Water Beetle Phylogenymentioning

confidence: 99%

Systematics of aquatic beetles (Coleoptera): current state and future directions

Short

2017

Systematic Entomology

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Molecular phylogeny of the aquatic beetle family Noteridae (Coleoptera: Adephaga) with an emphasis on data partitioning strategies

Cited by 51 publications

References 62 publications

Molecular phylogeny of bark and ambrosia beetles (Curculionidae: Scolytinae) based on 18 molecular markers

Molecular phylogeny of bark and ambrosia beetles (Curculionidae: Scolytinae) based on 18 molecular markers

A simple method for data partitioning based on relative evolutionary rates

Systematics of aquatic beetles (Coleoptera): current state and future directions

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