Fast and accurate bootstrap confidence limits on genome-scale phylogenies using little bootstraps

Research Articles ◽

Bootstrap Resampling ◽

Confidence Limits ◽

Sequence Alignments ◽

Computational Burden ◽

Phylogenomic Analyses ◽

Felsenstein's bootstrap resampling approach, applied in thousands of research articles, imposes a high computational burden for very long sequence alignments. We show that the bootstrapping of a collection of little subsamples, coupled with median bagging of subsample confidence limits, produces accurate bootstrap confidence for phylogenetic relationships in a fraction of time and memory. The little bootstraps approach will enhance rigor, efficiency, and parallelization of big data phylogenomic analyses.

Total Ortholog Median Matrix as an alternative unsupervised approach for phylogenomics based on evolutionary distance between protein coding genes

Scientific Reports ◽

10.1038/s41598-021-81926-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Sandra Regina Maruyama ◽

Luana Aparecida Rogerio ◽

Patricia Domingues Freitas ◽

Marta Maria Geraldes Teixeira ◽

José Marcos Chaves Ribeiro

Keyword(s):

Amino Acid ◽

Single Gene ◽

Gene Families ◽

Distance Measures ◽

Sequence Alignments ◽

Multiple Sequence ◽

Protein Coding ◽

Phylogenomic Analyses ◽

Amino Acid Distance

AbstractThe increasing number of available genomic data allowed the development of phylogenomic analytical tools. Current methods compile information from single gene phylogenies, whether based on topologies or multiple sequence alignments. Generally, phylogenomic analyses elect gene families or genomic regions to construct phylogenomic trees. Here, we presented an alternative approach for Phylogenomics, named TOMM (Total Ortholog Median Matrix), to construct a representative phylogram composed by amino acid distance measures of all pairwise ortholog protein sequence pairs from desired species inside a group of organisms. The procedure is divided two main steps, (1) ortholog detection and (2) creation of a matrix with the median amino acid distance measures of all pairwise orthologous sequences. We tested this approach within three different group of organisms: Kinetoplastida protozoa, hematophagous Diptera vectors and Primates. Our approach was robust and efficacious to reconstruct the phylogenetic relationships for the three groups. Moreover, novel branch topologies could be achieved, providing insights about some phylogenetic relationships between some taxa.

Plastid phylogenomics resolves ambiguous relationships within the orchid family and provides a solid timeframe for biogeography and macroevolution

Scientific Reports ◽

10.1038/s41598-021-83664-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Maria Alejandra Serna-Sánchez ◽

Oscar A. Pérez-Escobar ◽

Diego Bogarín ◽

María Fernanda Torres-Jimenez ◽

Astrid Catalina Alvarez-Yela ◽

...

Keyword(s):

Divergence Times ◽

Molecular Clocks ◽

Phylogenetic Placement ◽

Plastid Genomes ◽

Phylogenetic Reconstructions ◽

A Genome ◽

Tree Models ◽

Phylogenomic Analyses ◽

First Time

AbstractRecent phylogenomic analyses based on the maternally inherited plastid organelle have enlightened evolutionary relationships between the subfamilies of Orchidaceae and most of the tribes. However, uncertainty remains within several subtribes and genera for which phylogenetic relationships have not ever been tested in a phylogenomic context. To address these knowledge-gaps, we here provide the most extensively sampled analysis of the orchid family to date, based on 78 plastid coding genes representing 264 species, 117 genera, 18 tribes and 28 subtribes. Divergence times are also provided as inferred from strict and relaxed molecular clocks and birth–death tree models. Our taxon sampling includes 51 newly sequenced plastid genomes produced by a genome skimming approach. We focus our sampling efforts on previously unplaced clades within tribes Cymbidieae and Epidendreae. Our results confirmed phylogenetic relationships in Orchidaceae as recovered in previous studies, most of which were recovered with maximum support (209 of the 262 tree branches). We provide for the first time a clear phylogenetic placement for Codonorchideae within subfamily Orchidoideae, and Podochilieae and Collabieae within subfamily Epidendroideae. We also identify relationships that have been persistently problematic across multiple studies, regardless of the different details of sampling and genomic datasets used for phylogenetic reconstructions. Our study provides an expanded, robust temporal phylogenomic framework of the Orchidaceae that paves the way for biogeographical and macroevolutionary studies.

Celebrity influence on body image and eating disorders: A review

Journal of Health Psychology ◽

10.1177/1359105320988312 ◽

2021 ◽

pp. 135910532098831

Author(s):

Zoe Brown ◽

Marika Tiggemann

Keyword(s):

Eating Disorders ◽

Body Image ◽

Big Data ◽

Body Dissatisfaction ◽

Disordered Eating ◽

Research Articles ◽

Inclusion Criteria ◽

Media Attention ◽

Research Findings ◽

Appearance Comparison

Celebrities are well-known individuals who receive extensive public and media attention. There is an increasing body of research on the effect of celebrities on body dissatisfaction and disordered eating. Yet, there has been no synthesis of the research findings. A systematic search for research articles on celebrities and body image or eating disorders resulted in 36 studies meeting inclusion criteria. Overall, the qualitative, correlational, big data, and experimental methodologies used in these studies demonstrated that exposure to celebrity images, appearance comparison, and celebrity worship are associated with maladaptive consequences for individuals’ body image.

The First Glimpse of Streptocarpus ionanthus (Gesneriaceae) Phylogenomics: Analysis of Five Subspecies’ Chloroplast Genomes

Plants ◽

10.3390/plants9040456 ◽

2020 ◽

Vol 9 (4) ◽

pp. 456 ◽

Cited By ~ 1

Author(s):

Cornelius M. Kyalo ◽

Zhi-Zhong Li ◽

Elijah M. Mkala ◽

Itambo Malombe ◽

Guang-Wan Hu ◽

...

Keyword(s):

Sequence Data ◽

Structural Features ◽

Base Pairs ◽

Protein Coding ◽

Variable Regions ◽

Morphological Heterogeneity ◽

Chloroplast Genomes ◽

Chloroplast Genome Sequence ◽

Phylogenomic Analyses

Streptocarpus ionanthus (Gesneriaceae) comprise nine herbaceous subspecies, endemic to Kenya and Tanzania. The evolution of Str. ionanthus is perceived as complex due to morphological heterogeneity and unresolved phylogenetic relationships. Our study seeks to understand the molecular variation within Str. ionanthus using a phylogenomic approach. We sequence the chloroplast genomes of five subspecies of Str. ionanthus, compare their structural features and identify divergent regions. The five genomes are identical, with a conserved structure, a narrow size range (170 base pairs (bp)) and 115 unique genes (80 protein-coding, 31 tRNAs and 4 rRNAs). Genome alignment exhibits high synteny while the number of Simple Sequence Repeats (SSRs) are observed to be low (varying from 37 to 41), indicating high similarity. We identify ten divergent regions, including five variable regions (psbM, rps3, atpF-atpH, psbC-psbZ and psaA-ycf3) and five genes with a high number of polymorphic sites (rps16, rpoC2, rpoB, ycf1 and ndhA) which could be investigated further for phylogenetic utility in Str. ionanthus. Phylogenomic analyses here exhibit low polymorphism within Str. ionanthus and poor phylogenetic separation, which might be attributed to recent divergence. The complete chloroplast genome sequence data concerning the five subspecies provides genomic resources which can be expanded for future elucidation of Str. ionanthus phylogenetic relationships.

The era of big data: Genome-scale modelling meets machine learning

Computational and Structural Biotechnology Journal ◽

10.1016/j.csbj.2020.10.011 ◽

2020 ◽

Vol 18 ◽

pp. 3287-3300 ◽

Cited By ~ 1

Author(s):

Athanasios Antonakoudis ◽

Rodrigo Barbosa ◽

Pavlos Kotidis ◽

Cleo Kontoravdi

Keyword(s):

Machine Learning ◽

Big Data ◽

Scale Modelling ◽

The phylogenetic relationships of the anaerobic chytridiomycetous gut fungi (Neocallimasticaceae) and the Chytridiomycota. I. Cladistic analysis of rRNA sequences

Canadian Journal of Botany ◽

10.1139/b92-215 ◽

1992 ◽

Vol 70 (9) ◽

pp. 1738-1746 ◽

Cited By ~ 41

Author(s):

Jinliang Li ◽

I. Brent Heath

Keyword(s):

Internal Transcribed Spacer ◽

Phylogenetic Trees ◽

18S Rrna ◽

Cladistic Analysis ◽

Anaerobic Fungi ◽

Confidence Limits ◽

Maximum Likelihood Algorithm ◽

Rrna Sequences ◽

Partial 18S

To clarify the phylogenetic relationships of the Chytridiomycota and the anaerobic fungi from the rumen and caecum of herbivorous animals, we analyzed the partial 18S rRNA sequences from 28 species ranging from protists to mammals and internal transcribed spacer 1 (ITS1) and its adjacent sequences from four gut fungi and one chytrid by using three algorithms from the Phylogeny Inference Package (PHYLIP). To get the confidence limits for each branch, we applied bootstrapping for each algorithm. Our analysis on partial 18S rRNA sequences shows that the Chytridiomycota are clustered with other fungi with 98, 76, and 30% confidences in the Fitch–Margoliash, neighbour-joining, and maximum parsimony algorithms. None of these three algorithms place any of 17 protists from 12 phyla with the fungi, including the chytrids. The same analysis also shows that the Spizellomycetales and Chytridiales cluster with the gut fungi but does not identify which order is closest to them. These results suggest that the Chytridiomycota, including the gut fungi, are indeed fungi but the gut fungi might not belong to the Spizellomycetales. The phylogenetic trees generated by the above three algorithms, plus the maximum likelihood algorithm, based on ITS1 and its adjacent regions show that Anaeromyces is more distant from Orpinomyces, Neocallimastix, and Piromyces. However, they failed to determine the relationships among the last three genera. Key words: Chytridiomycota, gut fungi, rumen fungi, phylogeny, rRNA sequences.

Did viruses evolve as a distinct supergroup from common ancestors of cells?

10.1101/049171 ◽

2016 ◽

Cited By ~ 1

Author(s):

Ajith Harish ◽

Aare Abroi ◽

Julian Gough ◽

Charles Kurland

Keyword(s):

Common Ancestor ◽

Phylogenetic Analyses ◽

Marker Gene ◽

Host Cells ◽

Data Driven ◽

Evolutionary Origins ◽

Phylogenetic Methods ◽

Universal Common Ancestor ◽

Phylogenomic Analyses ◽

AbstractThe evolutionary origins of viruses according to marker gene phylogenies, as well as their relationships to the ancestors of host cells remains unclear. In a recent article Nasir and Caetano-Anollés reported that their genome-scale phylogenetic analyses identify an ancient origin of the “viral supergroup” (Nasir et al (2015) A phylogenomic data-driven exploration of viral origins and evolution. Science Advances, 1(8):e1500527). It suggests that viruses and host cells evolved independently from a universal common ancestor. Examination of their data and phylogenetic methods indicates that systematic errors likely affected the results. Reanalysis of the data with additional tests shows that small-genome attraction artifacts distort their phylogenomic analyses. These new results indicate that their suggestion of a distinct ancestry of the viral supergroup is not well supported by the evidence.

Transcriptome Ortholog Alignment Sequence Tools (TOAST) for Phylogenomic Dataset Assembly

10.21203/rs.2.16269/v4 ◽

2020 ◽

Author(s):

Dustin J. Wcisel ◽

J. Thomas Howard ◽

Jeffrey A. Yoder ◽

Alex Dornburg

Keyword(s):

Missing Data ◽

Open Source ◽

Research Question ◽

Single Copy ◽

Sequence Alignments ◽

Multiple Sequence ◽

Multiple Sequence Alignments ◽

Sequencing Technologies ◽

Phylogenomic Analyses ◽

The Impact

Abstract Background Advances in next-generation sequencing technologies have reduced the cost of whole transcriptome analyses, allowing characterization of non-model species at unprecedented levels. The rapid pace of transcriptomic sequencing has driven the public accumulation of a wealth of data for phylogenomic analyses, however lack of tools aimed towards phylogeneticists to efficiently identify orthologous sequences currently hinders effective harnessing of this resource. Results We introduce TOAST, an open source R software package that can utilize the ortholog searches based on the software Benchmarking Universal Single-Copy Orthologs (BUSCO) to assemble multiple sequence alignments of orthologous loci from transcriptomes for any group of organisms. By streamlining search, query, and alignment, TOAST automates the generation of locus and concatenated alignments, and also presents a series of outputs from which users can not only explore missing data patterns across their alignments, but also reassemble alignments based on user-defined acceptable missing data levels for a given research question. Conclusions TOAST provides a comprehensive set of tools for assembly of sequence alignments of orthologs for comparative transcriptomic and phylogenomic studies. This software empowers easy assembly of public and novel sequences for any target database of candidate orthologs, and fills a critically needed niche for tools that enable quantification and testing of the impact of missing data. As open-source software, TOAST is fully customizable for integration into existing or novel custom informatic pipelines for phylogenomic inference.

Why do phylogenomic analyses of early animal evolution continue to disagree? Sites in different structural environments yield different answers

10.1101/400465 ◽

2018 ◽

Cited By ~ 2

Author(s):

Akanksha Pandey ◽

Edward L. Braun

Keyword(s):

Solvent Accessibility ◽

Phylogenetic Signal ◽

Tree Of Life ◽

Striking Difference ◽

Relative Solvent Accessibility ◽

Animal Evolution ◽

Phylogenomic Analyses ◽

Cat Model ◽

Protein Datasets ◽

AbstractPhylogenomics has revolutionized the study of evolutionary relationships. However, genome-scale data have not been able to resolve all relationships in the tree of life. This could reflect the poor-fit of the models used to analyze heterogeneous datasets; that heterogeneity is likely to have many explanations. However, it seems reasonable to hypothesize that the different patterns of selection on proteins based on their structures might represent a source of heterogeneity. To test that hypothesis, we developed an efficient pipeline to divide phylogenomic datasets that comprise proteins into subsets based on secondary structure and relative solvent accessibility. We then tested whether amino acids in different structural environments had different signals for the deepest branches in the metazoan tree of life. Sites located in different structural environments did support distinct tree topologies. The most striking difference in phylogenetic signal reflected relative solvent accessibility; analyses of sites on the surface of proteins yielded a tree that placed ctenophores sister to all other animals whereas sites buried inside proteins yielded a tree with a sponge-ctenophore clade. These differences in phylogenetic signal were not ameliorated when we repeated our analyses using the site-heterogeneous CAT model, a mixture model that is often used for analyses of protein datasets. In fact, analyses using the CAT model actually resulted in rearrangements that are unlikely to represent evolutionary history. These results provide striking evidence that it will be necessary to achieve a better understanding the constraints due to protein structure to improve phylogenetic estimation.

Transcriptome Ortholog Alignment Sequence Tools (TOAST) for Phylogenomic Dataset Assembly

10.21203/rs.2.16269/v1 ◽

2019 ◽

Author(s):

Alex Dornburg ◽

Dustin J. Wcisel ◽

J. Thomas Howard ◽

Jeffrey A. Yoder

Keyword(s):

Missing Data ◽

Open Source ◽

Single Copy ◽

Sequence Alignments ◽

Multiple Sequence ◽

Multiple Sequence Alignments ◽

Sequencing Technologies ◽

Phylogenomic Analyses ◽

The Cost ◽

The Impact

Abstract Background Advances in next-generation sequencing technologies have reduced the cost of whole transcriptome analyses, allowing characterization of non-model species at unprecedented levels. The rapid pace of transcriptomic sequencing has driven the public accumulation of a wealth of data for phylogenomic analyses, however lack of tools aimed towards phylogeneticists to efficiently identify orthologous sequences currently hinders effective harnessing of this resource.Results We introduce TOAST, an open source R software package that can utilize the ortholog searches based on the software Benchmarking Universal Single-Copy Orthologs (BUSCO) to assemble multiple sequence alignments of orthologous loci from transcriptomes for any group of organisms. By streamlining search, query, and alignment, TOAST automates the generation of locus and concatenated alignments, and also presents a series of outputs from which users can not only explore missing data patterns across their alignments, but also reassemble alignments based on user-defined acceptable missing data levels for a given research question.Conclusions TOAST provides a comprehensive set of tools for assembly of sequence alignments of orthologs for comparative transcriptomic and phylogenomic studies. This software empowers easy assembly of public and novel sequences for any target database of candidate orthologs, and fills a critically needed niche for tools that enable quantification and testing of the impact of missing data. As open-source software, TOAST is fully customizable for integration into existing or novel custom informatic pipelines for phylogenomic inference.