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Special Issue "Generation of Genome-Wide Genetic Data and Evolutionary Analyses"

A special issue of Diversity (ISSN 1424-2818). This special issue belongs to the section "Phylogeny and Evolution".

Deadline for manuscript submissions: 20 March 2023 | Viewed by 3380

Special Issue Editors

Prof. Dr. Naoko Takezaki
E-Mail Website
Guest Editor
Life Science Research Center, Kagawa University, Kagawa 761-0793, Japan
Interests: molecular evolution; phylogeny construction; phylogenomics; divergence time estimation; vertebrate evolution
Dr. Ben-Yang Liao
E-Mail Website
Co-Guest Editor
Institute of Population Health Sciences, National Health Research Institutes, Miaoli County 350, Taiwan
Interests: evolutionary Genomics; bioinformatics

Special Issue Information

Dear Colleagues,

We are pleased to announce a forthcoming Special Issue of Diversity (IF = 2.465, a full open access journal, ISSN 1424-2818) that focuses on generation of genome-wide genetic data and evolutionary analyses.

With advancement of sequencing technology, we can generate different types of large-scale genetic data in any organism of interest. Large-scale data in genomic and taxonomic coverage can be used for evolutionary analyses for investigating characteristics of evolutionary patterns of genomes and resolving phylogenetic relationships of species, populations, and genes. Use of unprecedented amounts of data was expected to provide fine-scale resolution. However, it also created challenges in compiling and analysing large-scale data. This Special Issue provides an exciting opportunity to showcase the studies that generate genome-wide data, elucidate evolutionary patterns using genome-wide data, and highlight the problems that arise from the use of large amounts of genetic data. In particular studies focusing the following topics are welcome.

  1. Generation of genomic and transcriptomic data as well as DNA methylome data of non-model organisms
  2. Generation of various -omics data such as epigenome data (DNA methylome, CHIP-seq based histone modification data), translatome, and interactome of model organisms
  3. Methodologies or tools for integrating, analysing and interpreting these -omics data
  4. Evolutionary analyses elucidating patterns of genome structures, e.g., large indels, transposable elements, and GC content and natural selection
  5. Methodologies or tools for analysing genome sequences and mining databases and interpreting them for the evolutionary analyses
  6. Phylogenetic analyses of species, populations, and genes/gene families
  7. Methodologies or tools for preparing the data and choosing samples and loci for phylogenetic analyses

Prof. Dr. Naoko Takezaki
Guest Editor

Dr. Ben-Yang Liao
Co-guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diversity is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • genome evolution
  • phylogenomics
  • genome-scale data
  • species evolution
  • bioinformatics

Published Papers (2 papers)

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Research

Article
Comprehensive Genomic Analysis of G2-like Transcription Factor Genes and Their Role in Development and Abiotic Stresses in Arabidopsis
Diversity 2022, 14(3), 228; https://doi.org/10.3390/d14030228 - 20 Mar 2022
Cited by 5 | Viewed by 1557
Abstract
GOLDEN2-LIKE (GLK) transcription factors are a subfamily of GARP family transcription factors, which play an essential function in plant growth and development as well as stress response during abiotic and biotic stress conditions. This study reports GLK genes in the Arabidopsis thaliana genome [...] Read more.
GOLDEN2-LIKE (GLK) transcription factors are a subfamily of GARP family transcription factors, which play an essential function in plant growth and development as well as stress response during abiotic and biotic stress conditions. This study reports GLK genes in the Arabidopsis thaliana genome in-depth and identified 55 AtGLK genes in the Arabidopsis genome. Phylogenetic analyses resolved these GLK gene clusters into seven groups. A Ka/Ks ratios analysis indicated that they had experienced purifying selection. Many essential cis elements are present in the promoter regions of AtGLK genes associated with plant hormones, light, and stress. The expression profile from RNA-Seq data revealed that 29.1% of them had relatively high expression in all tested tissues or organs, indicating their crucial housekeeping function in plant growth and development. However, many other GLK members were selectively expressed in particular tissues or organs. In silico study of the transcriptional regulation of AtGLKs indicated that it is strongly regulated by cold, drought, osmotic, salt, and metal ion stressors. Our research provides essential information for the functional studies of each GLK gene in different species in the future. Full article
(This article belongs to the Special Issue Generation of Genome-Wide Genetic Data and Evolutionary Analyses)
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Article
Protein Structure, Models of Sequence Evolution, and Data Type Effects in Phylogenetic Analyses of Mitochondrial Data: A Case Study in Birds
Diversity 2021, 13(11), 555; https://doi.org/10.3390/d13110555 - 01 Nov 2021
Cited by 2 | Viewed by 1324
Abstract
Phylogenomic analyses have revolutionized the study of biodiversity, but they have revealed that estimated tree topologies can depend, at least in part, on the subset of the genome that is analyzed. For example, estimates of trees for avian orders differ if protein-coding or [...] Read more.
Phylogenomic analyses have revolutionized the study of biodiversity, but they have revealed that estimated tree topologies can depend, at least in part, on the subset of the genome that is analyzed. For example, estimates of trees for avian orders differ if protein-coding or non-coding data are analyzed. The bird tree is a good study system because the historical signal for relationships among orders is very weak, which should permit subtle non-historical signals to be identified, while monophyly of orders is strongly corroborated, allowing identification of strong non-historical signals. Hydrophobic amino acids in mitochondrially-encoded proteins, which are expected to be found in transmembrane helices, have been hypothesized to be associated with non-historical signals. We tested this hypothesis by comparing the evolution of transmembrane helices and extramembrane segments of mitochondrial proteins from 420 bird species, sampled from most avian orders. We estimated amino acid exchangeabilities for both structural environments and assessed the performance of phylogenetic analysis using each data type. We compared those relative exchangeabilities with values calculated using a substitution matrix for transmembrane helices estimated using a variety of nuclear- and mitochondrially-encoded proteins, allowing us to compare the bird-specific mitochondrial models with a general model of transmembrane protein evolution. To complement our amino acid analyses, we examined the impact of protein structure on patterns of nucleotide evolution. Models of transmembrane and extramembrane sequence evolution for amino acids and nucleotides exhibited striking differences, but there was no evidence for strong topological data type effects. However, incorporating protein structure into analyses of mitochondrially-encoded proteins improved model fit. Thus, we believe that considering protein structure will improve analyses of mitogenomic data, both in birds and in other taxa. Full article
(This article belongs to the Special Issue Generation of Genome-Wide Genetic Data and Evolutionary Analyses)
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