The evolution of fast-growing coral reef fishes

Siqueira, Alexandre C.; Yan, Helen F.; Morais, Renato A.; Bellwood, David R.

doi:10.1038/s41586-023-06070-z

Cited by 6 publications

(2 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Phylogenetic analyses elucidate relationships and evolutionary histories across various species (Misof, et al 2014; Zeng, et al 2014; Prum, et al 2015), strains (Lemieux, et al 2021), individuals (Prüfer, et al 2014; Sun, et al 2023), cells (Coorens, et al 2021) and genes (Li, et al 2022). Furthermore, phylogenetic trees play a pivotal role in downstream applications, including ancestral state reconstruction, testing evolutionary hypotheses, conducting phylogenetic comparative and diversity analyses, and consequently, they are widely used in research of evolutionary biology, conservation biology, earth history, and ecology (Mitchell, et al 2015; Lu, et al 2018; Liang, et al 2023; Siqueira, et al 2023). The advent of high-throughput sequencing technology has facilitated the generation of extensive omic datasets, encompassing genomes, transcriptomes, amplicons, and plastomes.…”

Section: Introductionmentioning

confidence: 99%

PhyloAln: a convenient reference-based tool to align sequences and high-throughput reads for phylogeny and evolution in the omic era

Huang,

Sun,

et al. 2024

Preprint

View full text Add to dashboard Cite

The current trend in phylogenetic and evolutionary analyses predominantly relies on omic data. However, traditional methods typically involve intricate and time-consuming procedures prior to core analyses. These procedures encompass assembly from high-throughput reads, decontamination, gene prediction, homology search, orthology assignment, multiple alignment, and matrix trimming. Such processes significantly impede the efficiency of research when dealing with extensive datasets. In this study, we present PhyloAln, a convenient reference-based tool capable of directly aligning high-throughput reads or complete sequences with existing alignments as reference for phylogenetic and evolutionary analyses. Through testing with both simulated and authentic datasets, PhyloAln demonstrates consistently robust performance in terms of alignment completeness and identity when compared to other reference-based tools. Additionally, we validate the tool's adeptness in managing foreign and cross-contamination issues prevalent in sequencing data, which are often overlooked by other tools. Moreover, we showcase the broad applicability of PhyloAln by generating alignments and reconstructing phylogenies from transcriptomes of ladybird beetles, plastid genes of peppers, and ultraconserved elements of turtles. These results underscore the versatility of our tool. Leveraging these advantages, PhyloAln stands poised to expedite phylogenetic and evolutionary analyses in the omic era. The tool is accessible at https://github.com/huangyh45/PhyloAln.

show abstract

Section: Introductionmentioning

confidence: 99%

PhyloAln: a convenient reference-based tool to align sequences and high-throughput reads for phylogeny and evolution in the omic era

Huang,

Sun,

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Phylogenetic analyses clarify relationships and evolutionary histories across various species ( Misof et al 2014 ; Zeng et al 2014 ; Prum et al 2015 ), strains ( Lemieux et al 2021 ), individuals ( Prüfer et al 2014 ; Sun et al 2023 ), cells ( Coorens et al 2021 ), and genes ( Li et al 2022 ). Furthermore, phylogenetic trees play a vital role in downstream applications, including ancestral state reconstruction, testing evolutionary hypotheses, and conducting phylogenetic comparative and diversity analyses, and consequently, they are widely used in research of evolutionary biology, conservation biology, earth history, and ecology ( Mitchell et al 2015 ; Lu et al 2018 ; Liang et al 2023 ; Siqueira et al 2023 ). With the development of high-throughput sequencing technology, extensive omic data sets have been generated, including genomes, transcriptomes, amplicons, and plastomes.…”

Section: Introductionmentioning

confidence: 99%

PhyloAln: A Convenient Reference-Based Tool to Align Sequences and High-Throughput Reads for Phylogeny and Evolution in the Omic Era

Huang,

Sun,

et al. 2024

Molecular Biology and Evolution

View full text Add to dashboard Cite

The current trend in phylogenetic and evolutionary analyses predominantly relies on omic data. However, prior to core analyses, traditional methods typically involve intricate and time-consuming procedures, including assembly from high-throughput reads, decontamination, gene prediction, homology search, orthology assignment, multiple sequence alignment, and matrix trimming. Such processes significantly impede the efficiency of research when dealing with extensive datasets. In this study, we develop PhyloAln, a convenient reference-based tool capable of directly aligning high-throughput reads or complete sequences with existing alignments as a reference for phylogenetic and evolutionary analyses. Through testing with simulated datasets of species spanning the tree of life, PhyloAln demonstrates consistently robust performance compared with other reference-based tools across different data types, sequencing technologies, coverages, and species, with percent completeness and identity at least 50 percentage points higher in the alignments. Additionally, we validate the efficacy of PhyloAln in removing a minimum of 90% foreign and 70% cross-contamination issues, which are prevalent in sequencing data but often overlooked by other tools. Moreover, we showcase the broad applicability of PhyloAln by generating alignments (completeness mostly larger than 80%, identity larger than 90%) and reconstructing robust phylogenies using real datasets of transcriptomes of ladybird beetles, plastid genes of peppers, or ultraconserved elements of turtles. With these advantages, PhyloAln is expected to facilitate phylogenetic and evolutionary analyses in the omic era. The tool is accessible at https://github.com/huangyh45/PhyloAln.

show abstract