Plant Bioinformatics

A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Molecular Biology".

Deadline for manuscript submissions: closed (31 December 2019) | Viewed by 47455

Special Issue Editors


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Guest Editor
Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth SY23 3EB, UK
Interests: transcriptomics; structural modeling and design; interactomics; SNPs; machine learning; web servers and databases

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Guest Editor
NIAB, Cambridge CB23EA, UK
Interests: disease modelling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

The advances in high-throughput experimental techniques have permeated Life Sciences. Among these, different aspects of plant biology are most prominent, turning Life Sciences into data-intensive disciplines. This is particularly evident in genomics linked to the development of so-called next generation sequencing (NGS), which have resulted in a dramatic increase on the number of plant genomes being sequenced but also in the development of genome-wide protein networks, transcriptome profiling, and other related -omic technologies. Closely related to that has been the growth of Bioinformatics, resulting in the development of novel tools, databases, and other resources required to analyze the ever-increasing volume of available data.

In this Special Issue, we aim at presenting recent advances in the field of Plant Bioinformatics. From studies on the sequencing and annotation of genomic data to the study of molecular processes using transcriptome-wide profiling studies and to the linking of genetic variants to plant traits, as well as plant phenotyping and new high-throughput approaches to analyze and integrate data, we aim at presenting novel computational tools and resources to manage, analyze and visualize -omic data. Finally, robust data analytics pipelines for descriptive and predictive modeling are also a focus for this Special Issue.

Dr. Narcis Fernandez-Fuentes
Dr. Anyela Valentina Camargo Rodríguez
Guest Editors

Manuscript Submission Information

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Keywords

  • transcriptomics
  • genomics
  • genotypic by sequencing (GBS)
  • GWAS
  • intelligent breeding
  • biological databases
  • bioinformatics resources
  • phenomics
  • statistical genomics
  • machine learning

Published Papers (10 papers)

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Research

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15 pages, 865 KiB  
Article
Genomic Predictions Using Low-Density SNP Markers, Pedigree and GWAS Information: A Case Study with the Non-Model Species Eucalyptus cladocalyx
by Paulina Ballesta, David Bush, Fabyano Fonseca Silva and Freddy Mora
Plants 2020, 9(1), 99; https://doi.org/10.3390/plants9010099 - 13 Jan 2020
Cited by 23 | Viewed by 3643
Abstract
High-throughput genotyping techniques have enabled large-scale genomic analysis to precisely predict complex traits in many plant species. However, not all species can be well represented in commercial SNP (single nucleotide polymorphism) arrays. In this study, a high-density SNP array (60 K) developed for [...] Read more.
High-throughput genotyping techniques have enabled large-scale genomic analysis to precisely predict complex traits in many plant species. However, not all species can be well represented in commercial SNP (single nucleotide polymorphism) arrays. In this study, a high-density SNP array (60 K) developed for commercial Eucalyptus was used to genotype a breeding population of Eucalyptus cladocalyx, yielding only ~3.9 K informative SNPs. Traditional Bayesian genomic models were investigated to predict flowering, stem quality and growth traits by considering the following effects: (i) polygenic background and all informative markers (GS model) and (ii) polygenic background, QTL-genotype effects (determined by GWAS) and SNP markers that were not associated with any trait (GSq model). The estimates of pedigree-based heritability and genomic heritability varied from 0.08 to 0.34 and 0.002 to 0.5, respectively, whereas the predictive ability varied from 0.19 (GS) and 0.45 (GSq). The GSq approach outperformed GS models in terms of predictive ability when the proportion of the variance explained by the significant marker-trait associations was higher than those explained by the polygenic background and non-significant markers. This approach can be particularly useful for plant/tree species poorly represented in the high-density SNP arrays, developed for economically important species, or when high-density marker panels are not available. Full article
(This article belongs to the Special Issue Plant Bioinformatics)
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9 pages, 1082 KiB  
Article
PAST: The Pathway Association Studies Tool to Infer Biological Meaning from GWAS Datasets
by Adam Thrash, Juliet D. Tang, Mason DeOrnellis, Daniel G. Peterson and Marilyn L. Warburton
Plants 2020, 9(1), 58; https://doi.org/10.3390/plants9010058 - 02 Jan 2020
Cited by 17 | Viewed by 6269
Abstract
In recent years, a bioinformatics method for interpreting genome-wide association study (GWAS) data using metabolic pathway analysis has been developed and successfully used to find significant pathways and mechanisms explaining phenotypic traits of interest in plants. However, the many scripts implementing this method [...] Read more.
In recent years, a bioinformatics method for interpreting genome-wide association study (GWAS) data using metabolic pathway analysis has been developed and successfully used to find significant pathways and mechanisms explaining phenotypic traits of interest in plants. However, the many scripts implementing this method were not straightforward to use, had to be customized for each project, required user supervision, and took more than 24 h to process data. PAST (Pathway Association Study Tool), a new implementation of this method, has been developed to address these concerns. PAST has been implemented as a package for the R language. Two user-interfaces are provided; PAST can be run by loading the package in R and calling its methods, or by using an R Shiny guided user interface. In testing, PAST completed analyses in approximately half an hour to one hour by processing data in parallel and produced the same results as the previously developed method. PAST has many user-specified options for maximum customization. Thus, to promote a powerful new pathway analysis methodology that interprets GWAS data to find biological mechanisms associated with traits of interest, we developed a more accessible, efficient, and user-friendly tool. These attributes make PAST accessible to researchers interested in associating metabolic pathways with GWAS datasets to better understand the genetic architecture and mechanisms affecting phenotypes. Full article
(This article belongs to the Special Issue Plant Bioinformatics)
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15 pages, 4722 KiB  
Article
The Complete Chloroplast Genomes of Two Lespedeza Species: Insights into Codon Usage Bias, RNA Editing Sites, and Phylogenetic Relationships in Desmodieae (Fabaceae: Papilionoideae)
by Yamuna Somaratne, De-Long Guan, Wen-Qiang Wang, Liang Zhao and Sheng-Quan Xu
Plants 2020, 9(1), 51; https://doi.org/10.3390/plants9010051 - 31 Dec 2019
Cited by 34 | Viewed by 3049
Abstract
The genus Lespedeza (tribe: Desmodieae) consists of about 40 species that have high medicinal and economic value. However, in this genus, using morphological characters, the species identification is quite complicated, which can be solved by the analysis of the complete chloroplast genomes. As [...] Read more.
The genus Lespedeza (tribe: Desmodieae) consists of about 40 species that have high medicinal and economic value. However, in this genus, using morphological characters, the species identification is quite complicated, which can be solved by the analysis of the complete chloroplast genomes. As primary organelle genomes, the complete genome sequences of chloroplasts (cp) provide unique molecular information to study the divergence of species, RNA editing, and phylogeny. Therefore, to the best of our knowledge, for the first time, we sequenced the complete cp genomes of two representative Lespedeza species: Lespedeza davurica and Lespedeza cuneata. The cp genomes of both the species were found to be 149,010 bp in length, exhibiting the typical angiosperm chloroplast structure containing four regions. The Lespedeza cp genomes showed similar conserved gene contents, order, and orientations with a total GC content of 35.0%. A total of 128 genes, including 83 protein-coding genes, 37 tRNAs, and eight rRNAs, were identified from each genome. Unique molecular features of the two Lespedeza cp genome sequences were obtained by performing the analysis of repeats, sequence divergence, codon usage, and predicting the RNA editing sites in addition to phylogenetic analysis with other key genera in tribe Desmodieae. Using the two datasets, the phylogenetic relationship of Lespedeza species among Deasmodieae was discovered, suggesting that whole cp genomes provided useful information for phylogenetic studies of these species. Full article
(This article belongs to the Special Issue Plant Bioinformatics)
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16 pages, 1351 KiB  
Article
Characterization and Expression Analysis of the Ca2+/Cation Antiporter Gene Family in Tomatoes
by Kayoko Amagaya, Tomoki Shibuya, Manabu Nishiyama, Kazuhisa Kato and Yoshinori Kanayama
Plants 2020, 9(1), 25; https://doi.org/10.3390/plants9010025 - 23 Dec 2019
Cited by 18 | Viewed by 3257
Abstract
The Ca2+/cation antiporter (CaCA) superfamily plays an important role in the regulation of the essential element Ca2+ and cation concentrations. Characterization and expression analyses of CaCA superfamily genes were performed in the tomato (Solanum lycopersicum) as a representative [...] Read more.
The Ca2+/cation antiporter (CaCA) superfamily plays an important role in the regulation of the essential element Ca2+ and cation concentrations. Characterization and expression analyses of CaCA superfamily genes were performed in the tomato (Solanum lycopersicum) as a representative of dicotyledonous plants and fruit crops. Sixteen CaCA candidate genes were found and identified as tomato CaCA, SlCaCA, by a domain search. In a phylogenetic analysis of the SlCaCA superfamily, the 16 genes were classified into SlCAX, SlNCL, SlCCX, and SlMHX families. Among them, Solyc12g011070, belonging to the SlCAX family, had four splice variants, three of which were predicted to be nonfunctional because of a lack of important motifs. EF-hand domains were only found in SlNCL, in addition to consensus Na_Ca_ex domains, and the region containing EF-hand domains was characteristically long in some members of SlNCL. Furthermore, four genes of the SlCCX family were found to be intronless. As for intracellular localization, one SlCCX member was predicted to be localized to the plasma membrane, while other SlCCXs, SlCAXs, and SlMHXs were predicted to be localized to the vacuolar membrane. The expression patterns of SlCaCAs in various organs, including during several developmental stages of fruit, were classified into four groups. Genes involved in each of the SlCAX, SlNCL, and SlCCX gene families were categorized into three or four groups according to expression patterns, suggesting role sharing within each family. The main member in each subfamily and the members with characteristic fruit expression patterns included genes whose expression was regulated by sugar or auxin and that were highly expressed in a line having metabolite-rich fruit. Full article
(This article belongs to the Special Issue Plant Bioinformatics)
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14 pages, 4165 KiB  
Article
Comparison of the Complete Eragrostis pilosa Chloroplast Genome with Its Relatives in Eragrostideae (Chloridoideae; Poaceae)
by Yamuna Somaratne, De-Long Guan, Nibras Najm Abbood, Liang Zhao, Wen-Qiang Wang and Sheng-Quan Xu
Plants 2019, 8(11), 485; https://doi.org/10.3390/plants8110485 - 09 Nov 2019
Cited by 12 | Viewed by 2956
Abstract
Eragrostis of the tribe Eragrostideae is a taxonomically complex genus, because of its polyploid nature and the presence of similar morphological characters among its species. However, the relationship between these morphologically indistinguishable species at the genomic level has not yet been investigated. Here, [...] Read more.
Eragrostis of the tribe Eragrostideae is a taxonomically complex genus, because of its polyploid nature and the presence of similar morphological characters among its species. However, the relationship between these morphologically indistinguishable species at the genomic level has not yet been investigated. Here, we report the complete chloroplast genome of E. pilosa and compare its genome structures, gene contents, simple sequence repeats (SSRs), sequence divergence, codon usage bias, and Kimura 2-parameter (K2P) interspecific genetic distances with those of other Eragrostideae species. The E. pilosa chloroplast genome was 134,815 bp in length and contained 132 genes and four regions, including a large single-copy region (80,100 bp), a small single-copy region (12,661 bp), and a pair of inverted repeats (21,027 bp). The average nucleotide diversity between E. pilosa and E. tef was estimated to be 0.011, and 0.01689 among all species. The minimum and maximum K2P interspecific genetic distance values were identified in psaA (0.007) and matK (0.029), respectively. Of 45 SSRs, eight were shared with E. tef, all of which were in the LSC region. Phylogenetic analysis resolved the monophyly of the sampled Eragrostis species and confirmed the close relationship between E. pilosa and E. tef. This study provides useful chlorophyll genomic information for further species identification and phylogenetic reconstruction of Eragrostis species. Full article
(This article belongs to the Special Issue Plant Bioinformatics)
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15 pages, 3049 KiB  
Article
Complete Chloroplast Genomes of Ampelopsis humulifolia and Ampelopsis japonica: Molecular Structure, Comparative Analysis, and Phylogenetic Analysis
by Xiaolei Yu, Wei Tan, Huanyu Zhang, Han Gao, Wenxiu Wang and Xiaoxuan Tian
Plants 2019, 8(10), 410; https://doi.org/10.3390/plants8100410 - 14 Oct 2019
Cited by 25 | Viewed by 4093
Abstract
Ampelopsis humulifolia (A. humulifolia) and Ampelopsis japonica (A. japonica), which belong to the family Vitaceae, are valuably used as medicinal plants. The chloroplast (cp) genomes have been recognized as a convincing data for marker selection and phylogenetic studies. Therefore, [...] Read more.
Ampelopsis humulifolia (A. humulifolia) and Ampelopsis japonica (A. japonica), which belong to the family Vitaceae, are valuably used as medicinal plants. The chloroplast (cp) genomes have been recognized as a convincing data for marker selection and phylogenetic studies. Therefore, in this study we reported the complete cp genome sequences of two Ampelopsis species. Results showed that the cp genomes of A. humulifolia and A. japonica were 161,724 and 161,430 bp in length, respectively, with 37.3% guanine-cytosine (GC) content. A total of 114 unique genes were identified in each cp genome, comprising 80 protein-coding genes, 30 tRNA genes, and 4 rRNA genes. We determined 95 and 99 small sequence repeats (SSRs) in A. humulifolia and A. japonica, respectively. The location and distribution of long repeats in the two cp genomes were identified. A highly divergent region of psbZ (Photosystem II reaction center protein Z) -trnG (tRNA-Glycine) was found and could be treated as a potential marker for Vitaceae, and then the corresponding primers were designed. Additionally, phylogenetic analysis showed that Vitis was closer to Tetrastigma than Ampelopsis. In general, this study provides valuable genetic resources for DNA barcoding marker identification and phylogenetic analyses of Ampelopsis. Full article
(This article belongs to the Special Issue Plant Bioinformatics)
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12 pages, 2694 KiB  
Article
Comparative and Phylogenetic Analyses of Ginger (Zingiber officinale) in the Family Zingiberaceae Based on the Complete Chloroplast Genome
by Yingxian Cui, Liping Nie, Wei Sun, Zhichao Xu, Yu Wang, Jing Yu, Jingyuan Song and Hui Yao
Plants 2019, 8(8), 283; https://doi.org/10.3390/plants8080283 - 12 Aug 2019
Cited by 50 | Viewed by 6720
Abstract
Zingiber officinale, commonly known as ginger, is an important plant of the family Zingiberaceae and is widely used as an herbal medicine and condiment. The lack of chloroplast genomic information hinders molecular research and phylogenetic analysis on ginger. We introduced the complete [...] Read more.
Zingiber officinale, commonly known as ginger, is an important plant of the family Zingiberaceae and is widely used as an herbal medicine and condiment. The lack of chloroplast genomic information hinders molecular research and phylogenetic analysis on ginger. We introduced the complete chloroplast genome of Z. officinale and identified its phylogenetic position in Zingiberaceae. The chloroplast genome of Z. officinale is 162,621 bp with a four-part circular structure and 36.1% GC content. All 113 unique genes were annotated. A total of 78 simple sequence repeats (SSRs) and 42 long repeat sequences, which are potential areas for species authentication, were found. Comparative analysis revealed some highly variable regions, including rps16-trnQ-UUG, atpH-atpI, trnT-UGU-trnL-UAA, ycf1, and psaC-ndhE. Moreover, the small single-copy (SSC) region was the most variable region in all four shared regions, indicating that it may be undergoing rapid nucleotide substitution in the family Zingiberaceae. Phylogenetic analysis based on all available chloroplasts of Zingiberales in the National Center for Biotechnology Information indicated that Zingiber is a sister branch to Kaempferia species. The availability of the Z. officinale chloroplast genome provided invaluable data for species-level authentication and phylogenetic analysis and can thus benefit further investigations on species in the family Zingiberaceae. Full article
(This article belongs to the Special Issue Plant Bioinformatics)
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13 pages, 1129 KiB  
Article
Constructing a Reference Genome in a Single Lab: The Possibility to Use Oxford Nanopore Technology
by Yun Gyeong Lee, Sang Chul Choi, Yuna Kang, Kyeong Min Kim, Chon-Sik Kang and Changsoo Kim
Plants 2019, 8(8), 270; https://doi.org/10.3390/plants8080270 - 06 Aug 2019
Cited by 10 | Viewed by 5373
Abstract
The whole genome sequencing (WGS) has become a crucial tool in understanding genome structure and genetic variation. The MinION sequencing of Oxford Nanopore Technologies (ONT) is an excellent approach for performing WGS and it has advantages in comparison with other Next-Generation Sequencing (NGS): [...] Read more.
The whole genome sequencing (WGS) has become a crucial tool in understanding genome structure and genetic variation. The MinION sequencing of Oxford Nanopore Technologies (ONT) is an excellent approach for performing WGS and it has advantages in comparison with other Next-Generation Sequencing (NGS): It is relatively inexpensive, portable, has simple library preparation, can be monitored in real-time, and has no theoretical limits on reading length. Sorghum bicolor (L.) Moench is diploid (2n = 2x = 20) with a genome size of about 730 Mb, and its genome sequence information is released in the Phytozome database. Therefore, sorghum can be used as a good reference. However, plant species have complex and large genomes when compared to animals or microorganisms. As a result, complete genome sequencing is difficult for plant species. MinION sequencing that produces long-reads can be an excellent tool for overcoming the weak assembly of short-reads generated from NGS by minimizing the generation of gaps or covering the repetitive sequence that appears on the plant genome. Here, we conducted the genome sequencing for S. bicolor cv. BTx623 while using the MinION platform and obtained 895,678 reads and 17.9 gigabytes (Gb) (ca. 25× coverage of reference) from long-read sequence data. A total of 6124 contigs (covering 45.9%) were generated from Canu, and a total of 2661 contigs (covering 50%) were generated from Minimap and Miniasm with a Racon through a de novo assembly using two different tools and mapped assembled contigs against the sorghum reference genome. Our results provide an optimal series of long-read sequencing analysis for plant species while using the MinION platform and a clue to determine the total sequencing scale for optimal coverage that is based on various genome sizes. Full article
(This article belongs to the Special Issue Plant Bioinformatics)
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15 pages, 3955 KiB  
Article
Sequencing and Structural Analysis of the Complete Chloroplast Genome of the Medicinal Plant Lycium chinense Mill
by Zerui Yang, Yuying Huang, Wenli An, Xiasheng Zheng, Song Huang and Lingling Liang
Plants 2019, 8(4), 87; https://doi.org/10.3390/plants8040087 - 03 Apr 2019
Cited by 27 | Viewed by 4730
Abstract
Lycium chinense Mill, an important Chinese herbal medicine, is widely used as a dietary supplement and food. Here the chloroplast (CP) genome of L. chinense was sequenced and analyzed, revealing a size of 155,756 bp and with a 37.8% GC content. The L. [...] Read more.
Lycium chinense Mill, an important Chinese herbal medicine, is widely used as a dietary supplement and food. Here the chloroplast (CP) genome of L. chinense was sequenced and analyzed, revealing a size of 155,756 bp and with a 37.8% GC content. The L. chinense CP genome comprises a large single copy region (LSC) of 86,595 bp and a small single copy region (SSC) of 18,209 bp, and two inverted repeat regions (IRa and IRb) of 25,476 bp separated by the single copy regions. The genome encodes 114 genes, 16 of which are duplicated. Most of the 85 protein-coding genes (CDS) had standard ATG start codons, while 3 genes including rps12, psbL and ndhD had abnormal start codons (ACT and ACG). In addition, a strong A/T bias was found in the majority of simple sequence repeats (SSRs) detected in the CP genome. Analysis of the phylogenetic relationships among 16 species revealed that L. chinense is a sister taxon to Lycium barbarum. Overall, the complete sequence and annotation of the L. chinense CP genome provides valuable genetic information to facilitate precise understanding of the taxonomy, species and phylogenetic evolution of the Solanaceae family. Full article
(This article belongs to the Special Issue Plant Bioinformatics)
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Review

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14 pages, 1800 KiB  
Review
Emerging Advanced Technologies to Mitigate the Impact of Climate Change in Africa
by Priscilla Francisco Ribeiro and Anyela Valentina Camargo Rodriguez
Plants 2020, 9(3), 381; https://doi.org/10.3390/plants9030381 - 19 Mar 2020
Cited by 10 | Viewed by 5011
Abstract
Agriculture remains critical to Africa’s socioeconomic development, employing 65% of the work force and contributing 32% of GDP (Gross Domestic Product). Low productivity, which characterises food production in many Africa countries, remains a major concern. Compounded by the effects of climate change and [...] Read more.
Agriculture remains critical to Africa’s socioeconomic development, employing 65% of the work force and contributing 32% of GDP (Gross Domestic Product). Low productivity, which characterises food production in many Africa countries, remains a major concern. Compounded by the effects of climate change and lack of technical expertise, recent reports suggest that the impacts of climate change on agriculture and food systems in African countries may have further-reaching consequences than previously anticipated. Thus, it has become imperative that African scientists and farmers adopt new technologies which facilitate their research and provide smart agricultural solutions to mitigating current and future climate change-related challenges. Advanced technologies have been developed across the globe to facilitate adaptation to climate change in the agriculture sector. Clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9), synthetic biology, and genomic selection, among others, constitute examples of some of these technologies. In this work, emerging advanced technologies with the potential to effectively mitigate climate change in Africa are reviewed. The authors show how these technologies can be utilised to enhance knowledge discovery for increased production in a climate change-impacted environment. We conclude that the application of these technologies could empower African scientists to explore agricultural strategies more resilient to the effects of climate change. Additionally, we conclude that support for African scientists from the international community in various forms is necessary to help Africans avoid the full undesirable effects of climate change. Full article
(This article belongs to the Special Issue Plant Bioinformatics)
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