Molecular Plant Breeding 2024, Vol.15 http://genbreedpublisher.com/index.php/mpb © 2024 GenBreed Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved. Publisher
Molecular Plant Breeding 2024, Vol.15 http://genbreedpublisher.com/index.php/mpb © 2024 GenBreed Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved. GenBreed Publisher is an international Open Access publisher specializing in molecular genetics, plant genes or traits, and plant breeding registered at the publishing platform that is operated by Sophia Publishing Group (SPG), founded in British Columbia of Canada. Publisher GenBreed Publisher Editedby Editorial Team of Molecular Plant Breeding Email: edit@mpb.genbreedpublisher.com Website: http://genbreedpublisher.com/index.php/mpb Address: 11388 Stevenston Hwy, PO Box 96016, Richmond, V7A 5J5, British Columbia Canada Molecular Plant Breeding (ISSN 1923-8266) is an international, open access, peer reviewed journal published online by BioPublisher. The journal publishes all the latest and outstanding research articles, letters and reviews in all areas of transgene, molecular genetics, crop QTL analysis, germplasm genetic diversity, and advanced breeding technologies. Molecular Plant Breeding is archived in LAC (Library and Archives Canada) and deposited in CrossRef. The Journal has been indexed by ProQuest as well. The Journal is expected to be indexed by PubMed and other databases in near future. All the articles published in Molecular Plant Breeding are Open Access, and are distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. GenBreed Publisher uses CrossCheck service to identify academic plagiarism through the world’s leading plagiarism prevention tool, iParadigms, and to protect the original authors’ copyrights.
Molecular Plant Breeding (online), 2024, Vol. 15 ISSN 1923-8266 http://genbreedpublisher.com/index.php/mpb © 2024 GenBreed Publisher, an online publishing platform of Sophia Publishing Group. All Rights Reserved. Sophia Publishing Group (SPG), founded in British Columbia of Canada, is a multilingual publisher Latest Content Revealing the Genetic Differentiation of Different Geographical Populations of Juniperus spp. Based on Chloroplast Genome Weichang Wu Molecular Plant Breeding, 2024, Vol. 15, No. 1, pp.1-7 Breeding 3.0: The Precise Revolution of Genotype Selection JimX. Fang Molecular Plant Breeding, 2024, Vol. 15, No. 1, pp.8-14 Breeding 4.0: The Breeding Revolution of Genetic Information Integration and Editing JimFang Molecular Plant Breeding, 2024, Vol. 15, No. 1, pp.15-26 Breeding 5.0: AI-Driven Revolution in Designed Plant Breeding JimFang Molecular Plant Breeding, 2024, Vol. 15, No. 1, pp.27-33 Effects of Biodegradable Mulch on Soil Microorganisms Ruye Cui, Xia An, Xiahong Luo, Changli Chen, Tingting Liu, Lina Zou Molecular Plant Breeding, 2024, Vol. 15, No. 1, pp.34-41
Molecular Plant Breeding 2024, Vol.15, No.1, 1-7 http://genbreedpublisher.com/index.php/mpb 1 Review and Progress Open Access Revealing the Genetic Differentiation of Different Geographical Populations of Juniperus spp. Based on Chloroplast Genome Weichang Wu Jiugu MolBreed SciTech Ltd., Zhuji, 311800, Zhejiang, China Corresponding email: 3397575099@qq.com Molecular Plant Breeding, 2024, Vol.15, No.1 doi: 10.5376/mpb.2024.15.0001 Received: 05 Dec., 2023 Accepted: 09 Jan., 2024 Published: 21 Jan., 2024 Copyright © 2024 Wu, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Wu W.C., 2024, Revealing the genetic differentiation of different geographical populations of Juniperus spp. based on chloroplast genome, Molecular Plant Breeding, 15(1): 1-7 (doi: 10.5376/mpb.2024.15.0001) Abstract Juniperus spp. are a diverse group of coniferous trees with wide distribution. This review focuses on the genetic differentiation of juniper populations across different geographic regions based on chloroplast genome analysis. By examining chloroplast genome sequences of junipers, significant genetic variations were identified among different geographic populations. These variations include single nucleotide polymorphisms, insertions/deletions, and structural differences in the genomes, reflecting the genetic adaptation and evolutionary history within distinct geographical environments. We also summarize the major driving factors behind juniper genetic differentiation, such as topography, climate, and human activities, all of which are closely associated with juniper genetic diversity and adaptability, and we emphasize the importance of studying juniper population genetic differentiation through chloroplast genome analysis and the potential applications of such research in the conservation and management of juniper resources. Keywords Juniperus spp.; Chloroplast genome; Genetic differentiation; Geographic populations; Genetic diversity 1 Introduction Cypress, as an ancient and important tree species, not only plays a key role in forestry, but also has significant value in environmental protection, soil fixation and ecological balance (Figure 1) (Charpin et al., 2019). Its wide distribution spans different geographical settings and covers a wide range of environmental types and climatic conditions, from cold alpine regions to warm subtropical zones, reflecting its ability to adapt to diverse habitats. This tree is known for its drought tolerance, cold tolerance and adaptability, and is widely used in forestry, horticulture and ecological restoration. Its natural resistance and growth characteristics make cypress occupy an important position in different geographical locations and ecosystems (Fu et al., 2018). However, behind this geographical distribution lies rich genetic diversity and adaptability, which is one of the important reasons for this study to further study the genetic differentiation of geographic populations of cypress. Figure 1Juniperus spp.
Molecular Plant Breeding 2024, Vol.15, No.1, 1-7 http://genbreedpublisher.com/index.php/mpb 2 The objective of this study is to explore the genetic differentiation of different geographic populations of cypress, in order to reveal the genetic basis of its adaptation to the environment, so as to provide scientific basis for the protection and restoration of the ecosystem. Such research is of great significance for understanding the genetic structure, genetic flow and population adaptability among cypress populations, and it also helps to guide the rational use of cypress resources and promote its sustainable development in different ecosystems. In the past, cypress genetic research has mainly focused on the analysis of specific regions or specific genetic markers. Although previous work has provided us with some insight into the genetic diversity of cypress trees, it is still lacking in comprehensiveness and depth, especially at the chloroplast genome level, and a comprehensive understanding of the genetic differentiation and adaptation of different geographic populations of cypress trees has not been fully developed. The aim of this study was to review the current situation of cypress genetic research, with special focus on the contribution of chloroplast genome to genetic differentiation of different geographic populations of Cypress. Through the comprehensive analysis of the previous research results, we hope to provide a more systematic and comprehensive understanding of genetic differentiation of cypress trees, and provide theoretical support and scientific guidance for the protection and sustainable use of cypress resources in the future. 2 Introduction of Chloroplast Genome 2.1 Role and importance of chloroplast genome As one of the important organelles in plant cells, the chloroplast genome carries abundant genetic information and plays a key role in plant growth and development, adaptation to the environment and genetic transmission. In the study of plant genetics, the role and importance of the chloroplast genome has attracted increasing attention (Cheng et al., 2018). Chloroplast genome has relatively simple structure and stable transmission mode. Its DNA sequence is relatively small, but contains key genes that encode photosynthesis and energy metabolism, such as genes related to the photosynthetic complex and electron transport chain. Because the chloroplast genome is mainly passed through the maternal pathway, it has little genetic variation, making it an ideal tool for studying plant relatability, population genetic structure, and evolutionary history. The chloroplast genome plays an important role in the physiological processes of plants. Chloroplasts are the main site of photosynthesis and contain genes involved in the energy capture and conversion process in photosynthesis. In addition, chloroplasts are also involved in regulating plant metabolic activities, synthesizing secondary metabolites such as amino acids, lipids and flavonoids, which affect plant growth and development and the ability to adapt to the environment. The genetic diversity and mutation frequency of chloroplast genome are also the focus of research. The haploid and highly conserved chloroplast genome is of great value in the study of geographical distribution, population genetic structure and adaptive evolution of species. The analysis of chloroplast DNA sequence can reveal the genetic diversity of different species, populations and even individuals, and provide important clues for biodiversity conservation, germplasm resource utilization and plant evolution mechanism. 2.2 Structure and characteristics of cypress chloroplast genome As one of the common conifers, cypress chloroplast genome has certain research value in plant genomics. The structure and characteristics of cypress chloroplast genome show its importance in plant evolution and genetic diversity. Cypress chloroplast genome presents a typical circular double-stranded DNA structure and usually contains a conserved set of genes, including genes encoding photosynthesis and respiratory chain, such as photosynthetic complex, ATP synthase and nucleic acid metabolism enzyme (Duan et al., 2020). These genes play a key role in ensuring plant growth, development and energy metabolism.
Molecular Plant Breeding 2024, Vol.15, No.1, 1-7 http://genbreedpublisher.com/index.php/mpb 3 Although the chloroplast genome of cypress may have a certain degree of diversity within the species, it is relatively conserved on the whole, which makes the chloroplast DNA sequence have a wide application prospect in phylogenetic and phylogenetic studies. Chloroplast genome sequence can be used to study the genetic differentiation, inter-population relationship and potential species evolution history of cypress geographic populations, which is helpful to understand the genetic diversity, adaptability and ecological characteristics of cypress, and provide scientific basis for its conservation and utilization. 2.3 Application of chloroplast genome in genetic differentiation research Chloroplast genomes play an important role in the study of plant genetic differentiation, especially for revealing genetic differences and kinship relationships among different geographic populations (Liu et al., 2018). As an important conifer species, the chloroplast genome of cypress has shown a wide application prospect in the study of genetic differentiation of geographic populations of cypress. Chloroplast genomes have been used by a team of researchers to conduct an in-depth analysis of the genetic diversity of European cypress populations. This study involved samples of European cypress trees from different geographical locations, sequencing and analyzing their chloroplast genomes to explore the genetic differentiation between different geographic populations. The research team first collected samples of European cypress trees from multiple geographic locations, including the Mediterranean coast, the Balkans and the Italian peninsula, and extracted DNA from the chloroplast genome for sequencing. After comparing and analyzing chloroplast genome sequences, the research team found that there were significant differences in chloroplast genome sequences among different geographic populations. These differences reflect the genetic evolution events experienced by cypress populations in different geographical locations during their evolution, including migration, dispersal and isolation among populations. The study identified some specific patterns of chloroplast genome sequence variation, which are related to the distribution of cypress populations in different geographic regions. For example, cypress populations along the Mediterranean coast and in the Balkans show high similarity at the chloroplast genome level, while cypress populations on the Italian peninsula show different chloroplast genome sequence characteristics, and the results of this study reveal genetic differences and evolutionary relationships between different geographic populations of European cypress trees. It provides important clues for understanding the population evolution of cypress. 3 Genetic Diversity of Different Geographic Populations of Cypress 3.1 Genetic diversity of different geographic populations As a common conifer, cypress is widely distributed throughout the world, showing significant genetic diversity among its different geographic populations. This diversity usually exists based on growth conditions and genetic evolution in different geographical environments, and using the genetic markers of the chloroplast genome, researchers can delve into the genetic diversity among different geographic populations of cypress trees (Yang et al., 2016). Along the Mediterranean coast, in North America, Asia, and elsewhere, cypress populations exhibit varying degrees of genetic diversity, which can be caused by a variety of factors, including geographic isolation, climatic differences, habitat characteristics, and natural selection. Cypress populations along the Mediterranean coast may have higher genetic diversity because they have long existed in growing environments with diverse climates, compared to other regions where cypress populations may have undergone more geographic separation and genetic evolution, resulting in some degree of genetic variation. Studying the genetic diversity of different geographic populations of cypress contributes to a deeper understanding of the genetic structure and geographic differentiation of these populations, which is of great significance for the conservation of cypress resources, optimization of its genetic gene pool, improvement of its resilience, and formulation of better conservation strategies. We can make better use of these resources to promote adaptive and sustainable use of cypress trees.
Molecular Plant Breeding 2024, Vol.15, No.1, 1-7 http://genbreedpublisher.com/index.php/mpb 4 3.2 The main factors to reveal genetic differentiation Many complex factors are involved in genetic differentiation of cypress populations. Chloroplast genome plays a key role in this process, and its sequence variation can provide important clues about genetic differentiation among cypress populations. One of the main factors of genetic differentiation is geographical isolation. Due to geographical isolation, cypress populations live in different habitats and are affected by environmental conditions, land forms and climate for a long time (Li et al., 2022). This isolation leads to a reduction in genetic communication between different geographic populations, which encourages populations to differentiate at the genetic level, and the greater the degree and duration of geographical isolation, the more pronounced the genetic differentiation between populations is likely to be. Another important factor is ecological adaptation. The adaptability of cypress populations to different habitats may lead to genetic differentiation. Due to different environments, cypress populations may gradually develop adaptive characteristics to different habitats, such as adaptability to temperature, humidity and soil conditions. The formation of these ecological adaptive characteristics may be accompanied by the selection of specific genotypes, thus leading to genetic differentiation among cypress populations. In addition, factors such as population size, migration pattern, natural selection and genetic drift may also affect the genetic differentiation of cypress populations. These factors interweave with each other, affect the genetic structure and diversity of cypress population, and promote the genetic differentiation among different geographic populations. 3.3 The influence of geographical environment on genetic diversity Geographic environment has a profound impact on the genetic diversity of cypress, which involves many aspects, from geomorphic features to climatic diversity, shaping the genetic structure of geographic population of Cypress (Xu et al., 2010). The complexity of geographical environment directly affects the genetic differentiation among different populations of cypress. The variation of terrain and geographical isolation resulted in the uneven distribution of cypress population in space. The presence of mountains, rivers, and different land forms can limit gene flow between cypress populations and contribute to genetic differences between populations. This geographical isolation of spatial distribution can lead to reduced gene exchange within geographic populations, thus promoting the occurrence of genetic differentiation. The change of climate conditions also affected the genetic diversity of cypress populations. The climate differences in different geographical environments will trigger the adaptability of cypress populations to different environments, and this adaptability may be reflected at the genetic level. For example, differences in climate factors such as temperature and precipitation may lead to gradual variation in the physiological and morphological characteristics of different populations, thus shaping the genetic characteristics of populations. The stability and change of geographical environment also have significant influence on genetic diversity. The relatively stable geographical environment may maintain the stability of some genetic characteristics, while the changing environmental conditions may promote the gradual variation and selection of some genotypes or phenotypes, thus affecting the genetic diversity of cypress populations. 4 Mechanisms of Genetic Differentiation Revealed by Chloroplast Genome 4.1 The role of chloroplast genome in genetic evolution Chloroplast genome plays a key role in plant genetic evolution, which goes far beyond the mere transmission of genetic information. As an important genetic element in plant cells, chloroplast genome is not only responsible for carrying and transmitting genetic information, but also plays an important functional and adaptive role in the evolution of populations (Jia et al., 2019, Bulletin of Biology, 44(11): 7-9).
Molecular Plant Breeding 2024, Vol.15, No.1, 1-7 http://genbreedpublisher.com/index.php/mpb 5 Chloroplast genome, as the genetic gene bank of plant cells, has accumulated a lot of genetic information during the long evolution process. Its relatively stable genetic characteristics make chloroplast gene composition an important index to study the relationship between species and the evolutionary history of populations. By comparing and analyzing chloroplast genome sequences, we can reveal the genetic relationships among different populations and species, infer their evolutionary history and origin, and provide an important basis for exploring speciation and differentiation. The evolution of chloroplast genome has certain conservation and variability. During the evolution of plant species, certain regions or genes in the chloroplast genome may vary or mutate, and this variation can sometimes be retained and passed between populations. This variation may be manifested by the presence of haplotype diversity, i.e. the simultaneous presence of many different chloroplast genotypes in a population, which reflects the genetic diversity and complex genetic structure between populations. Chloroplast genomes also play a role in species adaptation and survival strategies. Some specific variations in the chloroplast genome may be related to environmental adaptations, for example, a particular chloroplast genotype may make a plant more competitive or adaptable in a particular environment, thus affecting the survival and reproduction of the population. The chloroplast genome variation of alpine plants such as Ammopiptanthus nanus may make them more competitive in alpine and high-altitude habitats. 4.2 Reveal the genetic differentiation mechanism of different geographic populations of cypress As an important tree species, cypress exhibits complex and striking features in the genetic differentiation mechanism of its different geographic populations. Genetic differentiation is driven by a series of mechanisms involving biological processes at multiple levels, and these mechanisms are also well represented in the geographic populations of cypress trees (Papageorgiou et al., 2005). Natural selection and environmental adaptation play a key role in the genetic differentiation of cypress geographic populations. The growth conditions and ecological factors in different geographical environments have important effects on the adaptability of cypress populations, resulting in genetic differences among populations. For example, cypress populations in some geographic environments may show greater resilience under certain adverse conditions, and cypress populations in the Himalayas show distinct geographic differences in adaptation to changes in altitude and climate conditions, which may facilitate the widespread spread of certain genotypes or genomic features in that environment. Population size and genetic drift are also important factors affecting genetic differentiation of cypress geographic populations. Small populations can result in random changes in gene frequency due to genetic drift and random events, which increase genetic differences between geographic populations. Studies based on molecular genetics methods provide insight into the genetic differentiation of different geographic populations of cypress. The methods of DNA sequence alignment, genotype identification and population genetic structure analysis provide powerful tools for revealing the genetic differentiation mechanism of cypress geographic populations. 4.3 Effects of genetic differentiation on ecological adaptability of cypress Genetic differentiation plays an important role in the ecological adaptability of cypress. The genetic differentiation of geographical populations not only forms the diversity of genetic characteristics among different populations, but also has a significant impact on their ecological adaptability. Genetic differentiation brought about ecological adaptation differences among cypress populations. Under different geographical environments, the geographical populations of cypress have gradually formed specific genotypes adapted to the local environment through long-term natural selection and adaptation (Pastorino et al., 2010). These adaptive genotypes may have the characteristics of stress resistance, drought tolerance, cold tolerance, etc., so as to improve the survival ability of cypress trees in their respective growing environments.
Molecular Plant Breeding 2024, Vol.15, No.1, 1-7 http://genbreedpublisher.com/index.php/mpb 6 Genetic differentiation affects genetic variation and gene flow in cypress geographic populations. Genetic differentiation between geographic populations reduces the degree of gene flow and the exchange of genes between different geographic populations. This results in increased aggregation of genotypes within populations, while reducing the introduction of genes from other populations, resulting in a more pronounced representation of genetic traits within populations. Genetic differentiation also affects the response of cypress trees to environmental changes. Genetic differentiation of different geographic populations resulted in genotype differences, which made cypress display different ecological responses to environmental stress and climate change. This genetic difference may affect the sensitivity of cypress to environmental stress and its adaptability to different ecological environments. 5 Results and Discussion Geographic populations of cypress show significant differences in genetic differentiation, which provides important clues for us to understand the evolution, adaptation and ecological distribution of this species. By studying the genetic differentiation results of geographic populations of cypress, we can gain insight into the genetic structure and differences of cypress populations in different regions. Genetic differentiation among geographic populations is manifested by significant differences in genotype and allele frequencies of cypress trees. This genetic differentiation reflects the degree of genetic diversity among different regions and the distribution of genotypes within cypress populations, which helps to reveal the evolutionary process and species adaptability. Genetic differentiation may reflect the process by which cypress trees adapt to their respective ecological environments under long-term natural selection and environmental pressures (Bower and Hipkins, 2017). Genetic structure of cypress is influenced by gene exchange among geographic populations. The results of this study will help us understand the influence of gene flow on genetic structure of cypress geographic populations and the effect of geographic isolation on genetic differentiation, which has far-reaching significance in the field of ecology and evolution. From an ecological point of view, it can help us understand the response and adaptability of cypress populations to environmental changes, and in terms of evolution, it provides an opportunity to gain insight into the evolution of cypress species. The results of genetic differentiation of cypress geographic populations also provide implications and potential applications for future research and application, and have guiding significance for biodiversity conservation, ecosystem restoration, and genetic resource management and utilization. Understanding the genetic diversity of cypress geographic populations can also help reduce the risk of species extinction and provide a basis for ecosystem protection. In addition, the study of genetic differentiation of cypress geographic population can guide ecological restoration and adaptive breeding, and promote the reconstruction and restoration of ecosystem. The understanding of genetic diversity of different geographic populations can also be applied to environmental monitoring and ecosystem management, providing a basis for the management and protection of ecosystems, providing an important basis for the utilization and genetic improvement of cypress resources, promoting the development and progress of cypress related fields, and having far-reaching influence and guiding significance for future research in the fields of biology, ecology and resource management. Conflict of Interest Disclosure The author affirms that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.
Molecular Plant Breeding 2024, Vol.15, No.1, 1-7 http://genbreedpublisher.com/index.php/mpb 7 References Bower A.D., and Hipkins V., 2017, Genetic diversity and population structure in the rare, endemic baker cypress (Hesperocyparis bakeri), Madroño, 64(2): 71-82. https://doi.org/10.3120/0024-9637-64.2.71 Charpin D., Pichot C., Belmonte J., Sutra J.P., Zidkova J., Chanez P., Shahali Y., Sénéchal H., and Poncet P., 2019, Cypress pollinosis: from tree to clinic, Clinic Rev. Allerg. Immunol., 56: 174-195. https://doi.org/10.1007/s12016-017-8602-y PMid:28401436 Cheng H., Ge C.F., Zhang H., and Qiao Y.S., 2018, Advances on chloroplast genome sequencing and phylogenetic analysis in fruit trees, Henongxue Bao (Journal of Nuclear Agricultural Sciences), 32(1): 58-69. Duan H., Guo J., Xuan L., Wang Z., Li M., Yin Y., and Yang Y., 2020, Comparative chloroplast genomics of the genus Taxodium, BMC Genomics, 21: 114. https://doi.org/10.1186/s12864-020-6532-1 PMid:32005143 PMCid:PMC6995153 Fu J.F., Tang T.Y., He X.P., Cheng J.W., Li X., Fu J.R., and Yu D.X.,. 2018, A preliminary report on investigation of ancient cypress trees in Jiange County, Journal of Sichuan Forestry Science and Technology, 39(6): 97-101. Li X.Y., Wang M.Q., Yuan M.L., Ueno S., Wu X.T., Cai M.Y., Tsumura Y., and Wen Y.F., Genetic differentiation and demographic history of cryptomeria, a relict plant, in East Asia, Linye Kexue (Scientia Silvae Sinicae), 58(6): 66-78. Liu H.R., Gao Q.B., Zhang F.Q., Xing R., Chi X.F., and Chen S.L., 2018, Gnentic diversity and phylogeographic structure of Triosteum pinnatifidumbased chloroplast DNA sequence rbcL-accD, Zhiwu Yanjiu (Bulletin of Botanical Research), 38(2): 278-283. Papageorgiou A.C., Finkeldey R., Hattemer H.H., and Xenopoulos S., 2005, Genetic differences between autochthonous and breeding populations of common cypress (Cupressus sempervirens L.) in Greece, Eur. J. Forest Res., 124: 119-124. https://doi.org/10.1007/s10342-005-0063-9 Pastorino M.J., Ghirardi S., Grosfeld J., Gallo L.A., and Puntieri J.G., 2010, Genetic variation in architectural seedling traits of Patagonian cypress natural populations from the extremes of a precipitation range, Ann. For. Sci., 67(5): 508. https://doi.org/10.1051/forest/2010010 Xu T., Abbott R.J., Milne R.I., Mao K., Du F.K., Wu G., Ciren Z., Miehe G., and Liu J., 2010, Phylogeography and allopatric divergence of cypress species (Cupressus L.) in the Qinghai-Tibetan Plateau and adjacent regions, BMC Evol. Biol., 10: 194. https://doi.org/10.1186/1471-2148-10-194 PMid:20569425 PMCid:PMC3020627 Yang H., Zhang R., Jin G., Feng Z., and Zhou Z., 2016, Assessing the genetic diversity and genealogical reconstruction of cypress (Cupressus funebris Endl.) breeding parents using SSR markers, Forests, 7(8): 160. https://doi.org/10.3390/f7080160
Molecular Plant Breeding 2024, Vol.15, No.1, 8-14 http://genbreedpublisher.com/index.php/mpb 8 Brief History of Plant Breeding Open Access Breeding 3.0: The Precise Revolution of Genotype Selection JimFang Hainan Institute of Tropical Agricultural Resources, Sanya, 572025, Hainan, China Corresponding email: james.xj.fang@qq.com Molecular Plant Breeding, 2024, Vol.15, No.1 doi: 10.5376/mpb.2024.15.0002 Received: 08 Dec., 2023 Accepted: 14 Jan., 2024 Published: 30 Jan., 2024 Copyright © 2024 Fang, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Fang J., 2024, Breeding 3.0: the precise revolution of genotype selection, Molecular Plant Breeding, 15(1): 8-14 (doi: 10.5376/mpb.2024.15.0002) Abstract Breeding 3.0, the stage of breeding based on precise genotype selection and genetic and genomic data, represents a significant technological shift in the field of plant breeding, transforming traditional phenotypic selection into genotype selection to enhance selection efficiency and accuracy. The beginning of Breeding 3.0 can be traced back to approximately 1995 when molecular markers and genomic data were used to supplement phenotype data. Iconic academic achievements, such as the construction of saturated linkage maps in rice and breakthroughs in rice whole genome sequencing, marked the early stages of Breeding 3.0. The methodological framework of Breeding 3.0 includes marker-assisted backcrossing and pedigree confirmation, the application of linkage maps in unraveling complex traits, and advancements in high-throughput genotyping. The integration of genetic and genomic data confers advantages in precision and efficiency to Breeding 3.0. Genotype-based breeding approaches provide new avenues for improving plant varieties, while genome-wide selection enables the analysis of complex quantitative traits. Keywords Breeding 3.0; Genotype selection; Genetic and genomic data; Marker-assisted breeding 1 Introduction Breeding has always been an important task in the field of agriculture, aimed at improving plant varieties, increasing crop yield, resistance and quality. With the continuous progress of science and technology, breeding methods are also constantly evolving. The Breeding 2.0 stage focuses on conventional breeding, based on Mendel’s Law of Inheritance and Quantitative Genetics Theory, to improve plant varieties by creating mutant populations and applying phenotype selection. However, there are still some limitations in Breeding 2.0, such as limitations in selection efficiency and difficulties in analyzing complex traits (Fang, 2023). About 30 years ago, we entered the Breeding 3.0 stage, which was a significant shift in breeding methods. Breeding 3.0 achieves precise and revolutionary improvements in breeding by integrating genetic and genomic data, based on genotype selection (Wallace et al., 2018). The emergence of this stage marks further optimization and improvement of breeding methods. In Breeding 3.0, the introduction of techniques such as assisted-marker backcrossing and pedigree confirmation has made breeding work more precise and efficient (Fang et al., 2001). Meanwhile, the application of linkage maps has made it more feasible to analyze complex traits, while the development of high-throughput genotyping has expanded the toolkit of quantitative genetics. Through genome-wide association study and genome selection, breeding values can be more accurately estimated and plant variety can be more accurately selected. 2 The Evolution of Breeding 3.0 2.1 The beginning and iconic achievements of Breeding 3.0 About 30 years ago, the beginning of Breeding 3.0 marked the start of the integration of genetic and genomic data with phenotypic data. One of the iconic achievements is the construction of the first saturated molecular genetic map of rice (Causse et al., 1994). Through this map, researchers can accurately locate and associate important agronomic traits on the rice genome (Causse et al., 1994). This study utilized molecular marker techniques such as restriction fragment length polymorphism (RFLP) and simple sequence repeat (SSR) to accurately locate important agronomic traits by analyzing the association between genetic markers and phenotype. Subsequently, with the further development of molecular marker technology, more molecular markers such as single nucleotide polymorphism (SNP) and cleaved amplified polymorphic sequence (CAPS) were applied in Breeding 3.0. These
Molecular Plant Breeding 2024, Vol.15, No.1, 8-14 http://genbreedpublisher.com/index.php/mpb 9 molecular markers have the advantages of high polymorphism and high-throughput typing, enabling researchers to conduct genetic analysis and gene mapping more quickly and accurately. In addition, whole genome sequencing of rice is also one of the important breakthroughs in Breeding 3.0. Through comprehensive sequencing of the rice genome, we have revealed the composition and function of the rice genome, providing a deeper understanding for breeding work (International Rice Genome Sequencing Project, and Sasaki, 2005). 2.2 Technological transformation and Breeding 3.0 The evolution of Breeding 3.0 is driven by technological changes. Initially, assisted-marker backcrossing and pedigree confirmation were widely used in the early stages of Breeding 3.0 (Hospital and Charcosset, 1997). This technology utilizes molecular markers to assist in selecting offspring with target traits, thereby improving selection efficiency (Hospital and Charcosset, 1997). Through the application of molecular markers, researchers are able to accurately track and identify the genetic basis of important agronomic traits. For example, the use of molecular markers in breeding can expedite the selection process and enhance breeding efficiency. By analyzing molecular markers closely associated with target traits, researchers can exclude offspring without the target gene in the early selection stages, thereby reducing breeding cycles and costs (Xu and Crouch, 2008). Subsequently, the application of linkage maps became a key method for analyzing complex traits in Breeding 3.0. By constructing a linkage map, we can reveal the genetic basis of complex traits, providing important clues for breeding work (Ming et al., 2002; Paterson, 2019). In addition, the breakthrough in whole genome sequencing of rice has also driven the development of Breeding 3.0. Whole genome sequencing reveals genes related to important agronomic traits, providing valuable resources for breeding work (Yu et al., 2002). 2.3 High-throughput genotyping and Breeding 3.0 High-throughput genotyping is one of the important tools for Breeding 3.0. Through high-throughput genotyping, researchers can analyze variations in natural populations and identify genes related to agronomic traits (such as genome-wide association study). In addition, breeding values based on genome estimation (such as genome selection) have also become an important method for Breeding 3.0. By utilizing genomic information to predict the breeding value of individuals, genomic selection can accelerate the breeding process and improve selection efficiency (Resinde et al., 2012). In summary, the evolution of Breeding 3.0 is driven by technological advancements, including assisted-marker backcrossing, linkage map construction, and whole genome sequencing. The application of these technologies provides more accurate and efficient methods for breeding work, enabling us to have a deeper understanding of the genetic basis of plant traits. High-throughput genotyping and genome-based breeding value estimation methods play an important role in Breeding 3.0, further improving its efficiency and accuracy, and bringing new opportunities and challenges to breeding work. With the continuous progress and innovation of technology, Breeding 3.0 will continue to promote the development and progress of plant breeding. 3 Methodology of Breeding 3.0 3.1 Optimization of assisted-marker backcrossing and pedigree confirmation In Breeding 3.0, assisted-marker backcrossing and pedigree confirmation technologies have been further optimized and applied. The use of molecular markers to screen offspring with target traits has accelerated the breeding process through the use of assisted markers. In Breeding 3.0, we use more precise molecular markers such as SNP and SSR to improve selection efficiency and accuracy. Meanwhile, pedigree confirmation technology has also been widely applied in Breeding 3.0. Through pedigree confirmation, we can track the genetic background of the target trait and select the highest quality offspring as breeding materials.
Molecular Plant Breeding 2024, Vol.15, No.1, 8-14 http://genbreedpublisher.com/index.php/mpb 10 For example, in barley breeding, the paper “Advanced Backcross QTL Analysis in Barley (Hordeum vulgare L.)” demonstrated how to use assisted-marker backcrossing technology to transfer yield-related QTLs from wild barley donors to superior receptors (Pillen et al., 2003). In addition, the study “Population Structure and Breeding Patterns of 145 US Rice Cultivars Based on SSR Marker Analysis” used SSR molecular marker technology to confirm the lineage of 145 US rice germplasm resources, providing accurate genetic background information for breeding work (Lu et al., 2005). 3.2 Application of linkage maps in analyzing complex traits The application of linkage maps in Breeding 3.0 plays a crucial role in analyzing complex traits. By constructing a linkage map, we can reveal the association between traits and loci, and identify key genes that control traits. The analysis of the gene-trait association is crucial for the selection and optimization of breeding objectives. In Breeding 3.0, we use higher resolution linkage mapping technologies such as high-density SNP chips and genome sequencing to more accurately locate and identify genes related to complex traits. The paper “Dissection of Complex Traits in Crop Plants: A Plea for Multiparental Populations” (Plant, Cell&Environment, 2004) proposed the importance of using multi parent populations to construct linkage maps to analyze complex traits in crop plants (Lander and Schork, 2006). In maize breeding, the study “Genome Wide Association Studies Using a New Nonparametric Model Reveal the Genetic Architecture of 17 Agronomic Traits in an Enlarged Maize Association Panel” (Plos Genetics, 2014) conducted a genome-wide association study using high-density SNP markers in maize, showcasing the genetic structure of 17 agronomic traits (Yang et al., 2014). 3.3 Technological progress and application of high-throughput genotyping High throughput genotyping technology has made significant progress and application in breeding 3.0. Through high-throughput genotyping technology, we can quickly and accurately analyze large-scale genetic variations. These technologies include SNP chips, genome-wide association study, and whole genome sequencing. Through these technologies, we can screen candidate genes related to agronomic traits in natural populations and accelerate the breeding process. The technological progress of high-throughput genotyping provides more comprehensive and in-depth genetic information for breeding work, thereby improving the accuracy and efficiency of breeding. For example, the “The 3000 Rice Genomes Project” (GigaScience, 2014) used high-throughput genotyping technology to comprehensively sequence 3 000 rice genomes, revealing the diversity and genetic variation of the rice genome. In wheat breeding, the study “Genome-Wide Association Study Reveals Novel Genes Associated with Culm Cellulose Content in Bread Wheat (Triticum aestivumL.)” (BMC Plant Biology, 2017) analyzed the stem cellulose content of 288 different wheat varieties and conducted genome-wide association studies (GWAS), revealing new genes related to wheat stem cellulose content. Another paper, “Genome-wide Association Mapping of Black Point Reaction in Common Wheat (Triticum aestivum L.)” (BMC Plant Biology, 2017), conducted a genome-wide association study (GWAS) on black point of wheat through high-density 90 K and 660 K single nucleotide polymorphisms (SNP) analysis. The black points of 166 elite wheat varieties was evaluated in five environments, and 25 unique loci were identified, which were distributed on multiple chromosomes and explained 7.9% to 18.0% of phenotypic variations (Liu et al., 2017). Based on the above statements, the methodology of Breeding 3.0 includes optimized assisted-marker backcrossing and pedigree confirmation technologies, the application of linkage maps to analyze complex traits, and the technological progress and application of high-throughput genotyping technology. The development of these methods enables us to select and optimize breeding materials more accurately, providing more genetic information and tools for plant breeding. 4 The Advantages and Applications of Breeding 3.0 4.1 Precision and efficiency in integrating genetic and genomic data A significant advantage of Breeding 3.0 is its ability to integrate genetic and genomic data, thereby improving the accuracy and efficiency of breeding. For example, in tomato breeding, The study “Efficiency of Genomic Selection for Tomato Fruit Quality” (Molecular Breeding, 2016) demonstrated the accuracy of genome selection
Molecular Plant Breeding 2024, Vol.15, No.1, 8-14 http://genbreedpublisher.com/index.php/mpb 11 in evaluating multiple metabolic and quality characteristics through cross validation, and estimated the impact of different factors on its accuracy. The results indicated that the accuracy of predicting phenotype values is closely related to the heritability of traits. The size of the training population increases the accuracy of predictions. The optimal conditions were to use 122 varieties and 5 995 single nucleotide polymorphism (SNP) markers (Duangjit et al., 2016). Obviously, by integrating genetic and genomic data, the accuracy of predicting tomato fruit quality traits can be significantly improved. In citrus breeding, the study “Genome Wide Selection in Citrus Breeding” (Genetics and Molecular Research, 2016) evaluated the efficiency of genome-wide selection (GWS) in citrus populations and compared it with phenotypic selection. Research has shown that GWS can accurately predict phenotypes and shorten selection cycles. This indicated that genome selection is useful in citrus breeding as it can predict phenotypes early and accurately (Gois et al., 2016). Similarly, in maize breeding, the study “Genome Wide Association Study for Drought, Aflatoxin Resistance, and Important Agronomic Traits of Maize Hybrids in the Sub-Tropics” (The Plos One, 2015) used a diversity panel consisting of 346 maize inbred lines from temperate, subtropical, and tropical regions for genome-wide association analysis. The study found 10 quantitative trait variations related to important agronomic traits such as grain yield, plant and spike height, and flowering time. These findings demonstrated the potential of genomic association studies in identifying major variations that affect quantity and complex traits such as yield under drought conditions (Farfan et al., 2015). Similarly, in rice breeding, the study “Genomic Selection and Association Mapping in Rice (Oryza sativa): Effect of Trait Genetic Architecture, Training Population Composition, Marker Number and Statistical Model on Accuracy of Rice Genomic Selection in Elite, Tropical Rice Breeding Lines” (Plos Genetics, 2015) evaluated the effectiveness of genomic selection (GS) in rice breeding. Research has found that genome prediction models outperform predictions based solely on lineage records for all three traits, including grain yield and flowering time. The study also suggested that using a subset of markers every 0.2 cM for genome selection is sufficient in these rice breeding materials (Spindel et al., 2015). 4.2 Improving plant varieties based on genotype selection Another important application of Breeding 3.0 is the improvement of plant varieties based on genotype selection. By utilizing genomic information and genotype selection technologies, Breeding 3.0 can more accurately select plant individuals with target traits, accelerating the breeding process. For example, in wheat breeding, the study “Genomic Selection for Yield and Yyield-related Traits in Durum Wheat” (Molecular Breeding, 2018) evaluated the potential of single trait (ST) and multi trait (MT) genomic prediction models for yield and quality traits in durum wheat. The study used a breeding population (BP) of 170 varieties and advanced breeding lines, as well as 154 double haploid (DH) lines. Both populations underwent Infinium iSelect 90K SNP chip genotyping and multiple trait phenotypes. The study applied six ST-GS models and three MT prediction methods to predict yield, protein content, gluten index, and dough characteristics. The accuracy of ST prediction varies between 0.5 and 0.8 for different traits and models. Except for BayesA and BayesB better predicting gluten index, toughness, and strength in DH populations, the prediction accuracy of most traits in both populations was comparable (Haile et al., 2018). This study indicated that genotype selection can significantly improve the selection efficiency of yield and related traits in durum wheat. In cassava breeding, the study “Genome-wide association and prediction reveals the genetic architecture of cassava mosaic disease resistance and prospects for rapid genetic improvement” (The Plant Geneme, 2015) was the first genome-wide association mapping study conducted on 6128 African cassava breeding lines, aimed at identifying genes related to cassava mosaic disease resistance. Research has found that a region on chromosome 8 is the main resistance region, but 13 small effect regions have also been identified. In addition, the study also evaluated the accuracy of genomic selection for CMD resistance (Wolfe et al., 2015). 4.3 Contribution of genome-wide selection to quantitative trait analysis The genome-wide selection technology in Breeding 3.0 plays an important role in analyzing quantitative traits. Through genome-wide selection, we can accurately analyze the genetic basis of quantitative traits and identify key genes related to these traits. For example, in rice breeding, the study “Genome-wide association mapping for yield and other agronomic traits in an elite breeding population of tropical rice (Oryza sativa)” (PLoS One, 2015) successfully identified 52 QTLs for 11 agronomic traits by using genome-wide association analysis technology, including large effect QTLs for flowering time and grain length/grain width/grain length-width ratio. The study
Molecular Plant Breeding 2024, Vol.15, No.1, 8-14 http://genbreedpublisher.com/index.php/mpb 12 also found haplotypes that can be used to select dwarf, early flowering, and high-yield plants (Begum et al., 2015). Similarly, in apple breeding, the study “Genome-wide Association Mapping of Flowering and Ripening Periods in Apple” (Front. Plant Sci., 2017) conducted a large-scale genome-wide association study (GWAS) on these phenotypic characteristics by using association panels from 1 168 different apple genotypes across Europe. The study identified key SNPs that affect flowering and maturation stages, and explored candidate genes for these genomic regions (Urrestarazu et al., 2017). Breeding 3.0 has improved the accuracy and efficiency of breeding by integrating genetic and genomic data, improving plant varieties based on genotype selection, and making important contributions to quantitative trait analysis through genome-wide selection. These examples of applications fully demonstrate the potential and practical importance of Breeding 3.0 in plant breeding. 5 Challenges and Future Prospects 5.1 Technical and methodological challenges faced by Breeding 3.0 Although Breeding 3.0 has brought many innovations, it still faces some technical and methodological challenges. Firstly, Breeding 3.0 requires large-scale genetic and genomic data, which may be a challenge for resource limited breeding projects. Obtaining and analyzing large-scale genetic and genomic data requires high costs and complex technologies, which may limit the application of Breeding 3.0 in some regions and crops. Breeding 3.0 requires advanced computing and information processing systems to interpret and utilize a large amount of genetic and genomic data. Processing and interpreting such a large amount of data requires highly specialized skills and powerful computing power, which may limit the application of Breeding 3.0 in some breeding projects. Breeding 3.0 also needs to overcome ethical and legal issues related to genetic and genomic data. For example, privacy and intellectual property issues may pose challenges to data sharing and collaboration. In addition, for applications involving emerging technologies such as gene editing, relevant regulations and ethical guidelines need to be established to ensure their safety and sustainability. 5.2 Future directions and prospects of breeding 3.0 development The development prospects of Breeding 3.0 are broad, and there are many future directions to explore. Firstly, with the advancement of technology and the reduction of costs, Breeding 3.0 will be more widely applied to various crops and regions. This will help improve the adaptability, yield and quality of crops, and meet the growing global food demand. Breeding 3.0 will further integrate multiple genetic and genomic data, including phenotype, genome sequence, transcriptome data, etc., to gain a more comprehensive understanding and utilization of the genetic potential of crops. This will help discover more genes related to agronomic traits and improve the accuracy of predicting breeding values. Breeding 3.0 will continue to promote the development of gene editing and genome modification technologies. With the maturity and promotion of gene editing technology, we will be able to more accurately modify crop genomes and create new varieties with greater agronomic value. 5.3 The introduction of the concept of Breeding 4.0 Breeding 4.0 represents a new level in the field of breeding, which involves synthesizing any known allele genome into an ideal combination through the ability of the whole genome. We are currently at the forefront of Breeding 4.0, which can purposefully combine functional genetic variations faster and better than ever before. The development of this breeding level benefits from significant technological advancements in genetics and information systems. For example, the cost of genome resequencing research can now be lower than that of repeated yield trials, and genome editing is expected to enable parallel and precise modifications of hundreds (possibly hundreds) of positions per generation. High throughput phenotyping can measure numerous traits with unprecedented spatiotemporal resolution, and machine learning methods make the processing and interpretation of agronomic data far beyond human capabilities.
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