Integration of multi-omics technologies for crop improvement: Status and prospects
With the rapid development of next-generation sequencing (NGS), multi-omics techniques have been emerging as effective approaches for crop improvement. Here, we focus mainly on addressing the current status and future perspectives toward omics-related technologies and bioinformatic resources with po...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-10-01
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| Series: | Frontiers in Bioinformatics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fbinf.2022.1027457/full |
| _version_ | 1811341302799794176 |
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| author | Ru Zhang Cuiping Zhang Chengyu Yu Jungang Dong Jihong Hu |
| author_facet | Ru Zhang Cuiping Zhang Chengyu Yu Jungang Dong Jihong Hu |
| author_sort | Ru Zhang |
| collection | DOAJ |
| description | With the rapid development of next-generation sequencing (NGS), multi-omics techniques have been emerging as effective approaches for crop improvement. Here, we focus mainly on addressing the current status and future perspectives toward omics-related technologies and bioinformatic resources with potential applications in crop breeding. Using a large amount of omics-level data from the functional genome, transcriptome, proteome, epigenome, metabolome, and microbiome, clarifying the interaction between gene and phenotype formation will become possible. The integration of multi-omics datasets with pan-omics platforms and systems biology could predict the complex traits of crops and elucidate the regulatory networks for genetic improvement. Different scales of trait predictions and decision-making models will facilitate crop breeding more intelligent. Potential challenges that integrate the multi-omics data with studies of gene function and their network to efficiently select desirable agronomic traits are discussed by proposing some cutting-edge breeding strategies for crop improvement. Multi-omics-integrated approaches together with other artificial intelligence techniques will contribute to broadening and deepening our knowledge of crop precision breeding, resulting in speeding up the breeding process. |
| first_indexed | 2024-04-13T18:53:59Z |
| format | Article |
| id | doaj.art-ca30d069b8b7476fa4bd8124cfa4e64b |
| institution | Directory Open Access Journal |
| issn | 2673-7647 |
| language | English |
| last_indexed | 2024-04-13T18:53:59Z |
| publishDate | 2022-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioinformatics |
| spelling | doaj.art-ca30d069b8b7476fa4bd8124cfa4e64b2022-12-22T02:34:19ZengFrontiers Media S.A.Frontiers in Bioinformatics2673-76472022-10-01210.3389/fbinf.2022.10274571027457Integration of multi-omics technologies for crop improvement: Status and prospectsRu ZhangCuiping ZhangChengyu YuJungang DongJihong HuWith the rapid development of next-generation sequencing (NGS), multi-omics techniques have been emerging as effective approaches for crop improvement. Here, we focus mainly on addressing the current status and future perspectives toward omics-related technologies and bioinformatic resources with potential applications in crop breeding. Using a large amount of omics-level data from the functional genome, transcriptome, proteome, epigenome, metabolome, and microbiome, clarifying the interaction between gene and phenotype formation will become possible. The integration of multi-omics datasets with pan-omics platforms and systems biology could predict the complex traits of crops and elucidate the regulatory networks for genetic improvement. Different scales of trait predictions and decision-making models will facilitate crop breeding more intelligent. Potential challenges that integrate the multi-omics data with studies of gene function and their network to efficiently select desirable agronomic traits are discussed by proposing some cutting-edge breeding strategies for crop improvement. Multi-omics-integrated approaches together with other artificial intelligence techniques will contribute to broadening and deepening our knowledge of crop precision breeding, resulting in speeding up the breeding process.https://www.frontiersin.org/articles/10.3389/fbinf.2022.1027457/fullmulti-omicscrop improvementintegrationartificial intelligenceprecision breeding |
| spellingShingle | Ru Zhang Cuiping Zhang Chengyu Yu Jungang Dong Jihong Hu Integration of multi-omics technologies for crop improvement: Status and prospects Frontiers in Bioinformatics multi-omics crop improvement integration artificial intelligence precision breeding |
| title | Integration of multi-omics technologies for crop improvement: Status and prospects |
| title_full | Integration of multi-omics technologies for crop improvement: Status and prospects |
| title_fullStr | Integration of multi-omics technologies for crop improvement: Status and prospects |
| title_full_unstemmed | Integration of multi-omics technologies for crop improvement: Status and prospects |
| title_short | Integration of multi-omics technologies for crop improvement: Status and prospects |
| title_sort | integration of multi omics technologies for crop improvement status and prospects |
| topic | multi-omics crop improvement integration artificial intelligence precision breeding |
| url | https://www.frontiersin.org/articles/10.3389/fbinf.2022.1027457/full |
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