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Smart Plant Breeding Revealed by NGS Tools, Omics Approaches, and AI Technology

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A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: 20 July 2024 | Viewed by 5701

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Dr. Manosh Biswas

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Department of Genetics and Genome Biology, College of Life Sciences, University of Leicester, Leicester, UK
Interests: bio-informatics; genetics; genomics; cytogenetics; molecular biology; breeding
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Next-generation sequencing (NGS) technologies have accelerated crop improvement methods by enabling the rapid and cost-effective sequencing of entire genomes, transcriptomes, and epigenomes. The combination of NGS tools with omics approaches such as proteomics and metabolomics generates huge amounts genomic data that is frequently used to speed up the development of new crop varieties with desirable traits. Moreover, artificial intelligence (AI) technologies, such as machine learning and deep learning, are likely to transform the field of plant breeding by facilitating the rapid and accurate prediction of crop performance and yield.

The aim of this Special Issue is to bring to light the recent research progress in plant breeding by applying NGS tools, -omics approaches, and AI tech. Original research articles and concepts for review articles to address major issues are welcome.

This Special Issue will focus include articles related to the following topics:

Whole genome sequencing, assembly, and annotation;
Pan-genome assembly;
Transcriptome sequencing, assembly, differentially expressed gene identification;
Genotyping-by-sequencing, genetic diversity, and population structure;
Gene mapping and functional characterization;
Genomic selection for complex traits;
Map-based cloning of novel gene(s);
Molecular markers;
Comparative genomics;
Transposable elements and epigenomics;
Precision phenotyping;
Crop modelling.

Dr. Manosh Biswas
Guest Editor

Manuscript Submission Information

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Keywords

short read
long read
HI-C
genotyping-by-sequencing (GBS)
genome-wide association studies (GWAS)
population structure
genomic selection (GS)
genetic diversity
molecular markers
in situ hybridizations
functional genomics
gene expression
bio-informatics
molecular breeding

Published Papers (6 papers)

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Research

10 pages, 649 KiB

Open AccessArticle

Dig-up Primers: A Pipeline for Identification of Polymorphic Microsatellites Loci within Assemblies of Related Species

by Ante Turudić, Zlatko Liber, Martina Grdiša, Jernej Jakše, Filip Varga, Igor Poljak and Zlatko Šatović

Int. J. Mol. Sci. 2024, 25(6), 3169; https://doi.org/10.3390/ijms25063169 - 9 Mar 2024

Cited by 1 | Viewed by 901

Abstract

Simple sequence repeats (SSRs) have become one of the most popular molecular markers and are used in numerous fields, including conservation genetics, population genetic studies, and genetic mapping. Advances in next-generation sequencing technology and the growing amount of genomic data are driving the development of bioinformatics tools for SSR marker design. These tools work with different combinations of input data, which can be raw reads or assemblies, and with one or more input datasets. We present here a new strategy and implementation of a simple standalone pipeline that utilizes more than one assembly for the in silico design of PCR primers for microsatellite loci in more than one species. Primers are tested in silico to determine if they are polymorphic, eliminating the need to test time-consuming cross-species amplification in the laboratory. The end result is a set of markers that are in silico polymorphic in all analyzed species and have great potential for the identification of interspecies hybrids. The efficiency of the tool is demonstrated using two examples at different taxonomic levels and with different numbers of input assemblies to generate promising, high-quality SSR markers. Full article

(This article belongs to the Special Issue Smart Plant Breeding Revealed by NGS Tools, Omics Approaches, and AI Technology)

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16 pages, 13651 KiB

Open AccessArticle

Comparative Analysis of Six Complete Plastomes of Tripterospermum spp.

by Xiong-De Tu, Wen-Jun Lin, Hou-Hua Fu, Yi-Zhe Lin, Jun Shen, Shuai Chen, Zhong-Jian Liu, Ming-He Li and Shi-Pin Chen

Int. J. Mol. Sci. 2024, 25(5), 2534; https://doi.org/10.3390/ijms25052534 - 22 Feb 2024

Viewed by 678

Abstract

The Tripterospermum, comprising 34 species, is a genus of Gentianaceae. Members of Tripterospermum are mostly perennial, entwined herbs with high medicinal value and rich in iridoids, xanthones, flavonoids, and triterpenes. However, our inadequate understanding of the differences in the plastid genome sequences of Tripterospermum species has severely hindered the study of their evolution and phylogeny. Therefore, we first analyzed the 86 Gentianae plastid genomes to explore the phylogenetic relationships within the Gentianae subfamily where Tripterospermum is located. Then, we analyzed six plastid genomes of Tripterospermum, including two newly sequenced plastid genomes and four previously published plastid genomes, to explore the plastid genomes’ evolution and phylogenetic relationships in the genus Tripterospermum. The Tripterospermum plastomes have a quadripartite structure and are between 150,929 and 151,350 bp in size. The plastomes of Tripterospermum encoding 134 genes were detected, including 86 protein-coding genes (CDS), 37 transfer RNA (tRNA) genes, eight ribosomal RNA (rRNA) genes, and three pseudogenes (infA, rps19, and ycf1). The result of the comparison shows that the Tripterospermum plastomes are very conserved, with the total plastome GC content ranging from 37.70% to 37.79%. In repeat sequence analysis, the number of single nucleotide repeats (A/T) varies among the six Tripterospermum species, and the identified main long repeat types are forward and palindromic repeats. The degree of conservation is higher at the SC/IR boundary. The regions with the highest divergence in the CDS and the intergenic region (IGS) are psaI and rrn4.5-rrn5, respectively. The average pi of the CDS and the IGS are only 0.071% and 0.232%, respectively, indicating that the Tripterospermum plastomes are highly conserved. Phylogenetic analysis indicated that Gentianinae is divided into two clades, with Tripterospermum as a sister to Sinogeniana. Phylogenetic trees based on CDS and CDS + IGS combined matrices have strong support in Tripterospermum. These findings contribute to the elucidation of the plastid genome evolution of Tripterospermum and provide a foundation for further exploration and resource utilization within this genus. Full article

(This article belongs to the Special Issue Smart Plant Breeding Revealed by NGS Tools, Omics Approaches, and AI Technology)

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18 pages, 14448 KiB

Open AccessArticle

Comparative Analysis of Chloroplast Pan-Genomes and Transcriptomics Reveals Cold Adaptation in Medicago sativa

by Tianxiang Zhang, Xiuhua Chen, Wei Yan, Manman Li, Wangqi Huang, Qian Liu, Yanan Li, Changhong Guo and Yongjun Shu

Int. J. Mol. Sci. 2024, 25(3), 1776; https://doi.org/10.3390/ijms25031776 - 1 Feb 2024

Cited by 1 | Viewed by 931

Abstract

Alfalfa (Medicago sativa) is a perennial forage legume that is widely distributed all over the world; therefore, it has an extremely complex genetic background. Though population structure and phylogenetic studies have been conducted on a large group of alfalfa nuclear genomes, information about the chloroplast genomes is still lacking. Chloroplast genomes are generally considered to be conservative and play an important role in population diversity analysis and species adaptation in plants. Here, 231 complete alfalfa chloroplast genomes were successfully assembled from 359 alfalfa resequencing data, on the basis of which the alfalfa chloroplast pan-genome was constructed. We investigated the genetic variations of the alfalfa chloroplast genome through comparative genomic, genetic diversity, phylogenetic, population genetic structure, and haplotype analysis. Meanwhile, the expression of alfalfa chloroplast genes under cold stress was explored through transcriptome analysis. As a result, chloroplast genomes of 231 alfalfa lack an IR region, and the size of the chloroplast genome ranges from 125,192 bp to 126,105 bp. Using population structure, haplotypes, and construction of a phylogenetic tree, it was found that alfalfa populations could be divided into four groups, and multiple highly variable regions were found in the alfalfa chloroplast genome. Transcriptome analysis showed that tRNA genes were significantly up-regulated in the cold-sensitive varieties, while rps7, rpl32, and ndhB were down-regulated, and the editing efficiency of ycf1, ycf2, and ndhF was decreased in the cold-tolerant varieties, which may be due to the fact that chloroplasts store nutrients through photosynthesis to resist cold. The huge number of genetic variants in this study provide powerful resources for molecular markers. Full article

(This article belongs to the Special Issue Smart Plant Breeding Revealed by NGS Tools, Omics Approaches, and AI Technology)

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18 pages, 4960 KiB

Open AccessArticle

Integrated Transcriptomic and Metabolomic Analyses Identify Critical Genes and Metabolites Associated with Seed Vigor of Common Wheat

by Zhenrong Yang, Weiguo Chen, Tianxiang Jia, Huawei Shi and Daizhen Sun

Int. J. Mol. Sci. 2024, 25(1), 526; https://doi.org/10.3390/ijms25010526 - 30 Dec 2023

Cited by 3 | Viewed by 960

Abstract

Seed aging is a common physiological phenomenon during storage which has a great impact on seed quality. An in-depth analysis of the physiological and molecular mechanisms of wheat seed aging is of great significance for cultivating high-vigor wheat varieties. This study reveals the physiological mechanisms of wheat seed aging in two cultivars differing in seed vigor, combining metabolome and transcriptome analyses. Differences between cultivars were examined based on metabolomic differential analysis. Artificial aging had a significant impact on the metabolism of wheat seeds. A total of 7470 (3641 upregulated and 3829 downregulated) DEGs were detected between non-aging HT and LT seeds; however, 10,648 (4506 up and 6142 down) were detected between the two cultivars after aging treatment. Eleven, eight, and four key metabolic-related gene families were identified in the glycolysis/gluconeogenesis and TCA cycle pathways, starch and sucrose metabolism pathways, and galactose metabolism pathways, respectively. In addition, 111 up-regulated transcription factor genes and 85 down-regulated transcription factor genes were identified in the LT 48h group. A total of 548 metabolites were detected across all samples. Cultivar comparisons between the non-aged groups and aged groups revealed 46 (30 upregulated and 16 downregulated) and 62 (38 upregulated and 24 downregulated) DIMs, respectively. Network analysis of the metabolites indicated that glucarate O-phosphoric acid, L-methionine sulfoxide, isocitric acid, and Gln-Gly might be the most crucial DIMs between HT and LT. The main related metabolites were enriched in pathways such as glyoxylate and dicarboxylate metabolism, biosynthesis of secondary metabolites, fatty acid degradation, etc. However, metabolites that exhibited differences between cultivars were mainly enriched in carbon metabolism, the TCA cycle, etc. Through combined metabolome and transcriptome analyses, it was found that artificial aging significantly affected glycolysis/gluconeogenesis, pyruvate metabolism, and glyoxylate and dicarboxylate metabolism, which involved key genes such as ACS, F16P2, and PPDK1. We thus speculate that these genes may be crucial in regulating physiological changes in seeds during artificial aging. In addition, an analysis of cultivar differences identified pathways related to amino acid and polypeptide metabolism, such as cysteine and methionine metabolism, glutathione metabolism, and amino sugar and nucleotide sugar metabolism, involving key genes such as BCAT3, CHI1, GAUT1, and GAUT4, which may play pivotal roles in vigor differences between cultivars. Full article

(This article belongs to the Special Issue Smart Plant Breeding Revealed by NGS Tools, Omics Approaches, and AI Technology)

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19 pages, 4494 KiB

Open AccessArticle

Genome-Wide Analysis of Flax (Linum usitatissimum L.) Growth-Regulating Factor (GRF) Transcription Factors

by Jianyu Lu, Zhenhui Wang, Jinxi Li, Qian Zhao, Fan Qi, Fu Wang, Chunxiao Xiaoyang, Guofei Tan, Hanlu Wu, Michael K. Deyholos, Ningning Wang, Yingnan Liu and Jian Zhang

Int. J. Mol. Sci. 2023, 24(23), 17107; https://doi.org/10.3390/ijms242317107 - 4 Dec 2023

Cited by 1 | Viewed by 918

Abstract

Flax is an important cash crop globally with a variety of commercial uses. It has been widely used for fiber, oil, nutrition, feed and in composite materials. Growth regulatory factor (GRF) is a transcription factor family unique to plants, and is involved in regulating many processes of growth and development. Bioinformatics analysis of the GRF family in flax predicted 17 LuGRF genes, which all contained the characteristic QLQ and WRC domains. Equally, 15 of 17 LuGRFs (88%) are predicted to be regulated by lus-miR396 miRNA. Phylogenetic analysis of GRFs from flax and several other well-characterized species defined five clades; LuGRF genes were found in four clades. Most LuGRF gene promoters contained cis-regulatory elements known to be responsive to hormones and stress. The chromosomal locations and collinearity of LuGRF genes were also analyzed. The three-dimensional structure of LuGRF proteins was predicted using homology modeling. The transcript expression data indicated that most LuGRF family members were highly expressed in flax fruit and embryos, whereas LuGRF3, LuGRF12 and LuGRF16 were enriched in response to salt stress. Real-time quantitative fluorescent PCR (qRT-PCR) showed that both LuGRF1 and LuGRF11 were up-regulated under ABA and MeJA stimuli, indicating that these genes were involved in defense. LuGRF1 was demonstrated to be localized to the nucleus as expected for a transcription factor. These results provide a basis for further exploration of the molecular mechanism of LuGRF gene function and obtaining improved flax breeding lines. Full article

(This article belongs to the Special Issue Smart Plant Breeding Revealed by NGS Tools, Omics Approaches, and AI Technology)

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23 pages, 7460 KiB

Open AccessArticle

Genome-Wide Analysis of Cation/Proton Antiporter Family in Soybean (Glycine max) and Functional Analysis of GmCHX20a on Salt Response

by Qi Jia, Junliang Song, Chengwen Zheng, Jiahui Fu, Bin Qin, Yongqiang Zhang, Zhongjuan Liu, Kunzhi Jia, Kangjing Liang, Wenxiong Lin and Kai Fan

Int. J. Mol. Sci. 2023, 24(23), 16560; https://doi.org/10.3390/ijms242316560 - 21 Nov 2023

Viewed by 777

Abstract

Monovalent cation proton antiporters (CPAs) play crucial roles in ion and pH homeostasis, which is essential for plant development and environmental adaptation, including salt tolerance. Here, 68 CPA genes were identified in soybean, phylogenetically dividing into 11 Na⁺/H⁺ exchangers (NHXs), 12 K⁺ efflux antiporters (KEAs), and 45 cation/H⁺ exchangers (CHXs). The GmCPA genes are unevenly distributed across the 20 chromosomes and might expand largely due to segmental duplication in soybean. The GmCPA family underwent purifying selection rather than neutral or positive selections. The cis-element analysis and the publicly available transcriptome data indicated that GmCPAs are involved in development and various environmental adaptations, especially for salt tolerance. Based on the RNA-seq data, twelve of the chosen GmCPA genes were confirmed for their differentially expression under salt or osmotic stresses using qRT-PCR. Among them, GmCHX20a was selected due to its high induction under salt stress for the exploration of its biological function on salt responses by ectopic expressing in Arabidopsis. The results suggest that the overexpression of GmCHX20a increases the sensitivity to salt stress by altering the redox system. Overall, this study provides comprehensive insights into the CPA family in soybean and has the potential to supply new candidate genes to develop salt-tolerant soybean varieties. Full article

(This article belongs to the Special Issue Smart Plant Breeding Revealed by NGS Tools, Omics Approaches, and AI Technology)

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