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Plants
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Crop Genetics and Breeding
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Crop Genetics and Breeding

A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Genetics, Genomics and Biotechnology".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 2215

Special Issue Editors

Prof. Dr. Hai Du

E-Mail Website
Guest Editor
College of Agronomy and Biotechnology, Southwest University, Chongqing 400716, China
Interests: plant; crop genetics and breeding; genomics; next-generation sequencing; plant biology; bioinformatics; genome editing; gene function
Special Issues, Collections and Topics in MDPI journals
Dr. Zhe Liang

E-Mail Website
Guest Editor
Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Interests: plant genome; RNA methylation; multi-omics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The journal Plants will be publishing a Special Issue on crop genetics and breeding. As an enduring and thriving academic discipline worldwide, crop genetics and breeding play crucial roles in agricultural development, contributing to the improvement of crop varieties with desirable traits such as higher yield and/or quality, resistance to biotic and abiotic stresses, tolerance to environmental stress, adaptability to climate change, enhanced nutritional content, etc. Great advances have been made in both theoretical and applied research fields of crop genetics and breeding and its linkages with related disciplines, attributing to advancements in genomics, biotechnology, molecular biology, population genetics, multi-omics, bioinformatics, etc., which have opened new interdisciplinary areas of plant genetics and breeding. We welcome submissions of different types of manuscripts, including original research papers, reviews and methods, encompassing, but not limited to:

  1. Genetic Diversity:
    - Genetic diversity is the foundation of crop improvement. It refers to the variety of genetic material within a species.
    - Maintaining and utilizing genetic diversity is essential for developing crops with resilience to changing environmental conditions.
  1. Gene Discovery:
    - Advances in molecular biology and genomics have facilitated the discovery and understanding of specific genes associated with important traits.
    - Identification of the genes responsible for traits such as drought tolerance, disease resistance and nutritional content allows for targeted breeding efforts.
  1. Marker-Assisted Selection (MAS):
    - MAS involves using molecular markers linked to specific genes or traits to aid in traditional breeding.
    - This technique allows for a more precise selection of desired traits and reduces the time needed for conventional breeding.
  1. Genome Editing:
    - Technologies such as CRISPR-Cas9 have revolutionized genetic engineering by enabling the precise modification of specific genes.
    - Genome editing can be used to enhance traits or introduce new traits into crops more rapidly than traditional breeding methods.
  1. Quantitative Genetics:
    - Quantitative genetics involves the study of traits that are controlled by multiple genes, often with a significant environmental influence.|
    - Understanding the genetic basis of quantitative traits helps breeders make more informed decisions in selecting plants for breeding programs.
  1. Hybridization and Crossbreeding:
    - Crossbreeding involves mating individuals from different populations to combine desirable traits from each parent.
    - Hybrid varieties often exhibit heterosis or hybrid vigor, resulting in superior performance compared to their parents.
  1. Genetic Modification (GM):
    - Genetic modification involves the introduction of genes from different organisms to confer specific traits.
    - GM crops may have improved resistance to pests, diseases or environmental stresses.
  1. Phenotypic Selection:
    - Traditional breeding methods often rely on the observation of physical characteristics (phenotypes) to select plants with desired traits.
    - This method has been used for centuries and remains an important part of many breeding programs.
  1. Data-Driven Breeding:
    - With the advent of big data and bioinformatics, there is an increasing emphasis on data-driven approaches in crop breeding.
    - Analyzing large datasets can help identify patterns, correlations, and markers associated with desirable traits.

Prof. Dr. Hai Du
Dr. Zhe Liang
Guest Editors

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. Plants is an international peer-reviewed open access semimonthly 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 2700 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

  • crops
  • population
  • QTL
  • sequencing
  • genome
  • SNP
  • molecular markers
  • genome editing
  • phenotypes
  • omics
  • polyploidy
  • evolution

Published Papers (3 papers)

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Research

14 pages, 6991 KiB  
Article
Comparative Genomics of Lotus japonicus Reveals Insights into Proanthocyanidin Accumulation and Abiotic Stress Response
by Zhanmin Sun, Ziyang Liu, Manqing Zhi, Qifan Ran, Wenbo Xue, Yixiong Tang and Yanmin Wu
Plants 2024, 13(8), 1151; https://doi.org/10.3390/plants13081151 - 20 Apr 2024
Viewed by 290
Abstract
Lotus japonicus, is an important perennial model legume, has been widely used for studying biological processes such as symbiotic nitrogen fixation, proanthocyanidin (PA) biosynthesis, and abiotic stress response. High-quality L. japonicus genomes have been reported recently; however, the genetic basis of genes [...] Read more.
Lotus japonicus, is an important perennial model legume, has been widely used for studying biological processes such as symbiotic nitrogen fixation, proanthocyanidin (PA) biosynthesis, and abiotic stress response. High-quality L. japonicus genomes have been reported recently; however, the genetic basis of genes associated with specific characters including proanthocyanidin distribution in most tissues and tolerance to stress has not been systematically explored yet. Here, based on our previous high-quality L. japonicus genome assembly and annotation, we compared the L. japonicus MG-20 genome with those of other legume species. We revealed the expansive and specific gene families enriched in secondary metabolite biosynthesis and the detection of external stimuli. We suggested that increased copy numbers and transcription of PA-related genes contribute to PA accumulation in the stem, petiole, flower, pod, and seed coat of L. japonicus. Meanwhile, According to shared and unique transcription factors responding to five abiotic stresses, we revealed that MYB and AP2/ERF play more crucial roles in abiotic stresses. Our study provides new insights into the key agricultural traits of L. japonicus including PA biosynthesis and response to abiotic stress. This may provide valuable gene resources for legume forage abiotic stress resistance and nutrient improvement. Full article
(This article belongs to the Special Issue Crop Genetics and Breeding)
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14 pages, 2774 KiB  
Article
Transcriptomic Analysis of Self-Incompatibility in Alfalfa
by Lulu Li, Sinan Liu, Yulu Wang, Yangzhou Shang, Zhi Qi, Hao Lin and Lifang Niu
Plants 2024, 13(6), 875; https://doi.org/10.3390/plants13060875 - 19 Mar 2024
Viewed by 615
Abstract
Alfalfa (Medicago sativa L.) is an important forage crop worldwide, but molecular genetics and breeding research in this species are hindered by its self-incompatibility (SI). Although the mechanisms underlying SI have been extensively studied in other plant families, SI in legumes, including [...] Read more.
Alfalfa (Medicago sativa L.) is an important forage crop worldwide, but molecular genetics and breeding research in this species are hindered by its self-incompatibility (SI). Although the mechanisms underlying SI have been extensively studied in other plant families, SI in legumes, including alfalfa, remains poorly understood. Here, we determined that self-pollinated pollen tubes could germinate on the stigma of alfalfa, grow through the style, and reach the ovarian cavity, but the ovules collapsed ~48 h after self-pollination. A transcriptomic analysis of dissected pistils 24 h after self-pollination identified 941 differently expressed genes (DEGs), including 784 upregulated and 157 downregulated genes. A gene ontology (GO) analysis showed that the DEGs were highly enriched in functions associated with the regulation of pollen tube growth and pollen germination. A Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated that pentose and glucuronate interconversion, plant hormone signal transduction, the spliceosome, and ribosomes might play important roles in SI. Our co-expression analysis showed that F-box proteins, serine/threonine protein kinases, calcium-dependent protein kinases (CDPKs), bHLHs, bZIPs, and MYB-related family proteins were likely involved in the SI response. Our study provides a catalog of candidate genes for further study to understand SI in alfalfa and related legumes. Full article
(This article belongs to the Special Issue Crop Genetics and Breeding)
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18 pages, 3188 KiB  
Article
Transcriptome Profiling Reveals the Gene Network Responding to Low Nitrogen Stress in Wheat
by Yiwei Wang, Pengfeng Li, Yiwang Zhu, Yuping Shang, Zhiqiang Wu, Yongfu Tao, Hongru Wang, Dongxi Li and Cuijun Zhang
Plants 2024, 13(3), 371; https://doi.org/10.3390/plants13030371 - 26 Jan 2024
Viewed by 903
Abstract
As one of the essential nutrients for plants, nitrogen (N) has a major impact on the yield and quality of wheat worldwide. Due to chemical fertilizer pollution, it has become increasingly important to improve crop yield by increasing N use efficiency (NUE). Therefore, [...] Read more.
As one of the essential nutrients for plants, nitrogen (N) has a major impact on the yield and quality of wheat worldwide. Due to chemical fertilizer pollution, it has become increasingly important to improve crop yield by increasing N use efficiency (NUE). Therefore, understanding the response mechanisms to low N (LN) stress is essential for the regulation of NUE in wheat. In this study, LN stress significantly accelerated wheat root growth, but inhibited shoot growth. Further transcriptome analysis showed that 8468 differentially expressed genes (DEGs) responded to LN stress. The roots and shoots displayed opposite response patterns, of which the majority of DEGs in roots were up-regulated (66.15%; 2955/4467), but the majority of DEGs in shoots were down-regulated (71.62%; 3274/4565). GO and KEGG analyses showed that nitrate reductase activity, nitrate assimilation, and N metabolism were significantly enriched in both the roots and shoots. Transcription factor (TF) and protein kinase analysis showed that genes such as MYB-related (38/38 genes) may function in a tissue-specific manner to respond to LN stress. Moreover, 20 out of 107 N signaling homologous genes were differentially expressed in wheat. A total of 47 transcriptome datasets were used for weighted gene co-expression network analysis (17,840 genes), and five TFs were identified as the potential hub regulatory genes involved in the response to LN stress in wheat. Our findings provide insight into the functional mechanisms in response to LN stress and five candidate regulatory genes in wheat. These results will provide a basis for further research on promoting NUE in wheat. Full article
(This article belongs to the Special Issue Crop Genetics and Breeding)
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