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Phylogenetic Methods in the Genomic Era: Challenges in Multiple Sequence...
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Phylogenetic Methods in the Genomic Era: Challenges in Multiple Sequence Alignment and Phylogenetics for Genome-Scale Data

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Technologies and Resources for Genetics".

Deadline for manuscript submissions: closed (10 January 2022) | Viewed by 9661

Special Issue Editors

Dr. Cedric Notredame

E-Mail Website
Guest Editor
1. Barcelona Institute of Science and Technology (BIST), Bioinformatics and Genomics Programme, 08003 Barcelona, Spain
2. Universitat Pompeu Fabra (UPF), 08005 Barcelona, Spain
Interests: comparative bioinformatics; phylognetics; multiple sequence alignment; biological sequences; algorithms
Dr. Jia-Ming Chang

E-Mail Website
Guest Editor
Department of Computer Science, National Chengchi University, Taipei City 11605, Taiwan
Interests: bioinformatics; sequence alignment; alignment uncertainty; molecular evolution
Dr. Minh Bui

E-Mail Website
Guest Editor
Research School of Computer Science and Research School of Biology, Australian National University, Canberra ACT 2601, Australia
Interests: phylogeny and comparative analysis; molecular evolution; bioinformatics software; distributed computing
Dr. Ding He

E-Mail Website
Guest Editor
Department of Biology, University of Copenhagen, 1165 København, Denmark
Interests: microbiome; molecular evolution; evolutionary biology; phylogenomics; bioinformatics

Special Issue Information

Dear Colleagues,

Genome sequencing projects have become routine due to the drastically lower cost of sequencing. Grand-scale genome sequencing projects dedicating a systematic approach to targeting well-recognized taxonomic groups have started to appear, such as the Bird 10,000 Genomes (B10K) Project (Zhang 2015), the Global Ant Genome Alliance (GAGA) Project (Boomsma et al. 2017), and the Genome 10K (Genome 10K Community of Scientists 2009). These mega sequencing projects are changing the analytical landscape for systematics, posing new challenges to phylogeneticists and algorithmists for developing better ways to accommodate big data. Essentially, the tool development for phylogenetics and multiple sequence alignment (MSA) has been stimulated by the ever-rapidly-growing genomic data. Researchers have begun addressing some aspects of the challenges from a wide variety of angles. Lemoine and colleagues proposed a revised version of Felsenstein’s phylogenetic bootstrap based on gradual “transfer” distance to adjust for lower support due to bigger datasets (Lemoine et al. 2018). Morel and colleagues developed a tool, ParGenes, for massively parallel model selection and phylogenetic tree inference on thousands of genes (Morel et al. 2019). Chatzou and colleagues have shown that large-scale progressive multiple alignment methods are unstable, and could produce significantly different output when changing sequence input order (Chatzou et al. 2018). Sievers and Higgins have developed an improved version of ClustalW, Clustal Omega, to accommodate large-scale MSAs (Sievers and Higgins 2018). To highlight the importance of this exciting moment for phylogenetic method development and evolutionary data inference in facing the big data era, this Special Issue welcomes contributions of methods and metrics addressing challenges from sequence alignment to tree reconstruction in phylogenomics.

Dr. Cedric Notredame
Dr. Jia-Ming Chang
Dr. Minh Bui
Dr. Ding He
Guest Editors

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Keywords

  • Phylogenomics
  • Phylogenetic method development
  • Alignment uncertainty
  • Tree reconstruction
  • Evolutionary data inference
  • Multiple sequence alignment (MSA)
  • Big datasets
  • Bioinformatics
  • Sequencing projects

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Published Papers (2 papers)

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Research

11 pages, 2159 KiB  
Article
Post-Alignment Adjustment and Its Automation
by Xuhua Xia
Genes 2021, 12(11), 1809; https://doi.org/10.3390/genes12111809 - 18 Nov 2021
Cited by 2 | Viewed by 2739
Abstract
Multiple sequence alignment (MSA) is the basis for almost all sequence comparison and molecular phylogenetic inferences. Large-scale genomic analyses are typically associated with automated progressive MSA without subsequent manual adjustment, which itself is often error-prone because of the lack of a consistent and [...] Read more.
Multiple sequence alignment (MSA) is the basis for almost all sequence comparison and molecular phylogenetic inferences. Large-scale genomic analyses are typically associated with automated progressive MSA without subsequent manual adjustment, which itself is often error-prone because of the lack of a consistent and explicit criterion. Here, I outlined several commonly encountered alignment errors that cannot be avoided by progressive MSA for nucleotide, amino acid, and codon sequences. Methods that could be automated to fix such alignment errors were then presented. I emphasized the utility of position weight matrix as a new tool for MSA refinement and illustrated its usage by refining the MSA of nucleotide and amino acid sequences. The main advantages of the position weight matrix approach include (1) its use of information from all sequences, in contrast to other commonly used methods based on pairwise alignment scores and inconsistency measures, and (2) its speedy computation, making it suitable for a large number of long viral genomic sequences. Full article
(This article belongs to the Special Issue Phylogenetic Methods in the Genomic Era: Challenges in Multiple Sequence Alignment and Phylogenetics for Genome-Scale Data)
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16 pages, 743 KiB  
Article
Analysis of the Hosts and Transmission Paths of SARS-CoV-2 in the COVID-19 Outbreak
by Rui Dong, Shaojun Pei, Changchuan Yin, Rong Lucy He and Stephen S.-T. Yau
Genes 2020, 11(6), 637; https://doi.org/10.3390/genes11060637 - 9 Jun 2020
Cited by 17 | Viewed by 5787
Abstract
The severe respiratory disease COVID-19 was initially reported in Wuhan, China, in December 2019, and spread into many provinces from Wuhan. The corresponding pathogen was soon identified as a novel coronavirus named SARS-CoV-2 (formerly, 2019-nCoV). As of 2 May, 2020, over 3 million [...] Read more.
The severe respiratory disease COVID-19 was initially reported in Wuhan, China, in December 2019, and spread into many provinces from Wuhan. The corresponding pathogen was soon identified as a novel coronavirus named SARS-CoV-2 (formerly, 2019-nCoV). As of 2 May, 2020, over 3 million COVID-19 cases had been confirmed, and 235,290 deaths had been reported globally, and the numbers are still increasing. It is important to understand the phylogenetic relationship between SARS-CoV-2 and known coronaviruses, and to identify its hosts for preventing the next round of emergency outbreak. In this study, we employ an effective alignment-free approach, the Natural Vector method, to analyze the phylogeny and classify the coronaviruses based on genomic and protein data. Our results show that SARS-CoV-2 is closely related to, but distinct from the SARS-CoV branch. By analyzing the genetic distances from the SARS-CoV-2 strain to the coronaviruses residing in animal hosts, we establish that the most possible transmission path originates from bats to pangolins to humans. Full article
(This article belongs to the Special Issue Phylogenetic Methods in the Genomic Era: Challenges in Multiple Sequence Alignment and Phylogenetics for Genome-Scale Data)
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