Yin Li
Weizhen Liu
Xingtan Zhang
Shouchuang Wang
Ramin Yadegari5
Jianping Wang- 1The Genetic Engineering International Cooperation Base of Chinese Ministry of Science and Technology, The Key Laboratory of Molecular Biophysics of Chinese Ministry of Education, College of Life Science and Technology, Huazhong University of Science & Technology, Wuhan, China
- 2School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, China
- 3Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- 4Hainan Yazhou Bay Seed Laboratory, Sanya Nanfan Research Institute of Hainan University, Sanya, China
- 5School of Plant Sciences, University of Arizona, Tucson, AZ, United States
- 6Agronomy Department, University of Florida, Gainesville, FL, United States
Editorial on the Research Topic
Advances in crop biomass production based on multi-omics approach
Introduction
While as the dominant source of energy during the past century, the detrimental impacts of fossil fuels have become apparent in environmental pollution, unsustainability, and global warming (Sharif et al., 2021). With increasing efforts and capitalization on renewable energy technologies, bioenergy has become one important type of renewable energy. Biomass of plants is an important feedstock of bioenergy production. Plants suitable for biomass production share common characteristics: high yield (of dry matter or a type of biomass, i.e., starch or sugar), low agronomic inputs, and low nutrition requirements. Based on these features, woody species (e.g., willow and poplar), grasses (e.g., sugarcane, switchgrass, and Miscanthus), aquatic plants (e.g., algae and duckweed), and oil plants have been considered biomass plants. Additionally, wheat and rice straw are important biomass sources. Biomass has several types according to the source species, the moisture content, and composition of biomass material, such as lignocellulosic biomass from woody plants, biomass from grasses (including cellulosic biomass from grasses or extracted starch/sugar), aquatic plant biomass, and manures (McKendry, 2002). In turn, these biomass types are compatible with different bio-conversion methods, e.g., combustion, fermentation, gasification, pyrolysis, and mechanical extraction of starch or oils. Recently, numerous efforts have been made to convert biomass to high-value chemicals and bio-based materials (Anchan and Dutta, 2021).
Downstream utilizations of biomass (e.g., conversion to biofuels or bio-based chemicals) requires multiple disciplines, such as agricultural science, microbiology, and chemistry. By contrast, upstream knowledge of biomass, such as the genetic determinants of biomass-related traits and molecular mechanisms of biomass accumulation and composition, relies on plant biology, and agricultural science. Notably, many biomass plants with large and complex genomes (such as sugarcane) have been less studied or have bottlenecks in transformation and traditional genetics (Zhang et al., 2018; Wang et al., 2021; An et al., 2021; Chen et al., 2022). Recently, research on biomass and bioenergy plants has been advanced rapidly due to the development of genomics. For example, state-of-the-art genomic technologies facilitated the successful assembly of reference genomes for sugarcane, Miscanthus, and switchgrass (Zhang et al., 2018; Mitros et al., 2020; Lovell et al., 2021). Though huge diversity within and among biomass crops provides invaluable resources for biomass utilization, understanding of biomass production mechanisms is still limited due to shortage of molecular and omic resources and challenges of functional studies. It has become apparent that synergistic integration of multiple omic technologies (e.g., transcriptomics, proteomics, epigenomics, metabolomics, and phenomics) serves as a key approach to circumvent the challenges. This Research Topic includes seven research articles and two reviews, covering several biomass species, including maize, sorghum, sugarcane, rice, and oil plants to reveal the current advances of multi-omics in addressing the mechanisms of biomass production.
Advances in multi-omic technologies and resources facilitate studies on biomass-related traits
This section showcases how omic technologies and resources can facilitate biomass studies. Voelker et al. reported the genome assemblies of 10 sorghum accessions including sweet and non-sweet sorghum genotypes (Boatwright et al.; Kumar et al., 2022). A large number of structural variations (SVs) were identified, which highlighted the SV-related functional difference between sweet and non-sweet sorghum genotypes. Wang et al. developed an image-based phenotypic acquisition method to characterize leaf-sheath traits in detail and applied the method to genome-wide association studies (GWAS), providing a detailed genetic architecture of leaf-sheath morphology. Guo et al. presented an integrative genomic database for oil plants, the Genomic Information Repository for Oil Plants (GROP, www.grop.site), which hosts 22 reference genomes of 18 species with 46 transcriptome datasets (Bayer et al., 2017; Unver et al., 2017; Wang et al., 2018; Song et al., 2020; Sturtevant et al., 2020; Chen et al., 2021). The construction of such an omics repository addresses the need to integrate, share, and analyze the omics data across oil plants for the research community. In addition, Tu et al. reviewed the major applications of regular short-read RNA-seq in plant biology, described a cohort of representative RNA-seq-analysis tools in model plants and major crops, and emphasized that the full utilization of fruitful RNA-seq resources will promote the omic research on under studied species (including biomass crops) to a high level.
Applications of omic approaches provide insights into biomass-related biology
This section collects representative papers using omic technologies to gain insights into biomass-related biological questions. Sugarcane is one of the key biomass and bioenergy crops, providing about 80% of global sugar production and 40% of ethanol production (Zhang et al., 2018). Efforts have been made to investigate the molecular mechanisms of sugar accumulation in sugarcane and in the comparable species sweet sorghum (Li et al., 2018; Li et al., 2019a; Li et al., 2019b), from sugar transportation and physiology to transcriptome and quantitative trait loci mapping (Babu et al., 2009; Liu et al.; Moore, 2005; Aitken et al., 2006; Casu et al., 2007; Zhang et al., 2021). Yuan et al. performed transcriptomic and metabolomic studies on two sugarcane varieties and revealed candidate genes for sucrose metabolism, stem texture, and rind color. While the genes associated with stem sugar accumulation have been identified in sugarcane (Casu et al., 2007; Zhang et al., 2021), epigenetic regulation remains elusive. Xue et al. profiled the DNA methylation in sugarcane (Saccharum officinarum) leaves, roots, rinds, and piths, and observed DNA methylation valleys (DMVs) overlapped with transcription factors and sucrose-related genes, indicating the involvement of epigenetic regulation in sucrose metabolism. Liu et al. revealed the link of OsPRR37, a key component of the rice circadian clock, with biomass production through DNA methylation analysis. Overexpression of OsPRR37 in rice led to suppressed growth and lowered biomass likely through the diurnal changes of DNA methylation regulators (such as ROS1A/DNG702) to hypo-methylate a key signal component controlling metabolism, OsHXK1 (Zheng et al., 2021; Zhou et al., 2021). Ain et al. presented a comprehensive review on recent progress in the identification of molecular and genetic factors regulating growth, biomass accumulation, and assimilate partitioning in bioenergy crops. The review highlights a plethora of genes related to cell cycle, cell wall, hormones, and related transcription factors as the targets to improve photosynthesis, carbohydrate allocation, and biomass production in the bioenergy crops. Additionally, this topic also hosts an example of omics-enabled trait association study. Specifically, Wang et al. used comparative RNA-seq to profile seed-specific long-lived mRNA and identify a number of the long-lived mRNA associated with rice seed longevity.
Concluding remarks
This Research Topic exemplifies that multi-omics represent an important route to strengthen the studies of biomass crops, particularly with complex genomes. Importantly, trends emerged from these articles that a combination of multiple omic resources and tools is a powerful approach to gaining new insights into biomass production and related traits. The discoveries will pave the road toward molecular design and breeding biomass crops with tailored bioenergy purposes.
Author contributions
YL, WL, XZ, SW, RY, and JW drafted and revised this editorial based on this Research Topic’s contributions. All authors approved the submitted version.
Funding
YL was funded by the National Natural Science Foundation of China (32272126), the Fundamental Research Funds for Central Universities, HUST (2021XXJS070, 3004170157), and Wuhan Knowledge Innovation Project (2022020801010073). WL was funded by the National Natural Science Foundation of China (32200331) and the Major Science and Technology Research Project of Hubei Province (2021AFB002). The project was supported by USDA Research Capacity Fund (Hatch), FLA-AGR-006269 to JW.
Acknowledgments
We thank all authors who submitted their work for this Research Topic, the support of professional editorial staff at Frontiers, and the invaluable time and efforts of reviewers in manuscript evaluation.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
Aitken, K., Jackson, P., Mcintyre, C. (2006). Quantitative trait loci identified for sugar related traits in a sugarcane (Saccharum spp.) cultivar Saccharum officinarum population. Theor. Appl. Genet. 112, 1306–1317. doi: 10.1007/s00122-006-0233-2
An, Y., Liu, Y., Liu, Y., Lu, M., Kang, X., Mansfield, S. D., et al. (2021). Opportunities and barriers for biofuel and bioenergy production from poplar. GCB Bioenergy. 13, 905–913. doi: 10.1111/gcbb.12829
Anchan, H. N., Dutta, S. (2021). Recent advances in the production and value addition of selected hydrophobic analogs of biomass-derived 5-(hydroxymethyl)furfural. Biomass Conv. Bioref. 13, 2571–2593. doi: 10.1007/s13399-021-01315-1
Babu, C., Koodalingam, K., Natarajan, U., Shanthi, R., Govindaraj, P. (2009). Assessment of rind hardness in sugarcane (Sachharum spp. hybrids) genotypes for development of non lodging erect canes. Adv. Biol. Res. 3, 48–52. Available at: http://www.idosi.org/abr/3(1-2)/10.pdf.
Bayer, P. E., Hurgobin, B., Golicz, A. A., Chan, C. K. K., Yuan, Y., Lee, H. T., et al. (2017). Assembly and comparison of two closely related Brassica napus genomes. Plant Biotechnol. J. 15, 1602–1610. doi: 10.1111/pbi.12742
Casu, R. E., Jarmey, J. M., Bonnett, G. D., Manners, J. M. (2007). Identification of transcripts associated with cell wall metabolism and development in the stem of sugarcane by affymetrix GeneChip sugarcane genome array expression profiling. Funct. Integr. Genomics 7, 153–167. doi: 10.1007/s10142-006-0038-z
Chen, Z., Debernardi, J. M., Dubcovsky, J., Gallavotti, A. (2022). Recent advances in crop transformation technologies. Nat. Plants 8, 1343–1351. doi: 10.1038/s41477-022-01295-8
Chen, X., Tong, C., Zhang, X., Song, A., Hu, M., Dong, W., et al. (2021). A high-quality Brassica napus genome reveals expansion of transposable elements, subgenome evolution and disease resistance. Plant Biotechnol. J. 19, 615–630. doi: 10.1111/pbi.13493
Kumar, N., Brenton, Z., Myers, M. T., Boyles, R. E., Sapkota, S., Boatwright, J. L., et al. (2022). Registration of the sorghum carbon-partitioning nested association mapping (CP-NAM) population. J. Plant Regist. 16, 656–663. doi: 10.1002/plr2.20229
Li, Y., Mehta, R., Messing, J. (2018). A new high-throughput assay for determining soluble sugar in sorghum internode-extracted juice. Planta 248, 785–793. doi: 10.1007/s00425-018-2932-8
Li, Y., Tu, M., Feng, Y., Wang, W., Messing, J. (2019b). Common metabolic networks contribute to carbon sink strength of sorghum internodes: Implications for bioenergy improvement. Biotechnol. Biofuels. 12, 274. doi: 10.1186/s13068-019-1612-7
Li, Y., Wang, W., Feng, Y., Tu, M., Wittich, P. E., Bate, N. J., et al. (2019a). Transcriptome and metabolome reveal distinct carbon allocation patterns during internode sugar accumulation in different sorghum genotypes. Plant Biotechnol. J. 17, 472–487. doi: 10.1111/pbi.12991
Lovell, J. T., MacQueen, A. H., Mamidi, S., Bonnette, J., Jenkins, J., Napier, J. D., et al. (2021). Genomic mechanisms of climate adaptation in polyploid bioenergy switchgrass. Nature 590, 438–444. doi: 10.1038/s41586-020-03127-1
McKendry, P. (2002). Energy production from biomass (part 1): Overview of biomass. Bioresour. Technol. 83, 37–46. doi: 10.1016/s0960-8524(01)00118-3
Mitros, T., Session, A. M., James, B. T., Wu, G. A., Belaffif, M. B., Clark, L. V., et al. (2020). Genome biology of the paleotetraploid perennial biomass crop Miscanthus. Nat. Commun. 11, 5442. doi: 10.1038/s41467-020-18923-6
Moore, P. H. (2005). Integration of sucrose accumulation processes across hierarchical scales: Towards developing an understanding of the gene-to-crop continuum. Field Crops Res. 92, 119–135. doi: 10.1016/j.fcr.2005.01.031
Sharif, A., Bhattacharya, M., Afshan, S., Shahbaz, M. (2021). Disaggregated renewable energy sources in mitigating CO2 emissions: new evidence from the USA using quantile regressions. Environ. Sci. Pollut. Control Ser. 3, 23–36. doi: 10.1007/s11356-021-13829-2
Song, J. M., Guan, Z., Hu, J., Guo, C., Yang, Z., Wang, S., et al. (2020). Eight high-quality genomes reveal pan-genome architecture and ecotype differentiation of Brassica napus. Nat. Plants 6, 34–45. doi: 10.1038/s41477-019-0577-7
Sturtevant, D., Lu, S., Zhou, Z. W., Shen, Y., Wang, S., Song, J. M., et al. (2020). The genome of jojoba (Simmondsia chinensis): A taxonomically isolated species that directs wax ester accumulation in its seeds. Sci. Adv. 6, 1–14. doi: 10.1126/sciadv.aay3240
Unver, T., Wu, Z., Sterck, L., Turktas, M., Lohaus, R., Li, Z., et al. (2017). Genome of wild olive and the evolution of oil biosynthesis. Proc. Natl. Acad. Sci. 114, E9413–E9422. doi: 10.1073/pnas.1708621114
Wang, C., Kong, Y., Hu, R., Zhou, G. (2021). Miscanthus: A fast-growing crop for environmental remediation and biofuel production. GCB Bioenergy. 13, 58–69. doi: 10.1111/gcbb.12761
Wang, B., Wu, Z., Li, Z., Zhang, Q., Hu, J., Xiao, Y., et al. (2018). Dissection of the genetic architecture of three seed-quality traits and consequences for breeding in Brassica napus. Plant Biotechnol. J. 16, 1336–1348. doi: 10.1111/pbi.12873
Zhang, Q., Hua, X., Liu, H., Yuan, Y., Shi, Y., Wang, Z., et al. (2021). Evolutionary expansion and functional divergence of sugar transporters in saccharum (S. spontaneum and S. officinarum). Plant J. 105, 884–996. doi: 10.1111/tpj.15076
Zhang, J., Zhang, X., Tang, H., Zhang, Q., Hua, X., Ma, X., et al. (2018). Allele-defined genome of the autopolyploid sugarcane Saccharum spontaneum l. Nat. Genet. 50, 1565–1573. doi: 10.1038/s41588-018-0237-2
Zheng, S., Ye, C., Lu, J., Liufu, J., Lin, L., Dong, Z., et al. (2021). Improving the rice photosynthetic efficiency and yield by editing OsHXK1 via CRISPR/Cas9 system. Int. J. Mol. Sci. 22, 9554. doi: 10.3390/ijms22179554
Keywords: genomics, multi-omics, biomass production, biomass related traits, bioinformatics, biomass and bio energy crops
Citation: Li Y, Liu W, Zhang X, Wang S, Yadegari R and Wang J (2023) Editorial: Advances in crop biomass production based on multi-omics approach. Front. Plant Sci. 14:1155442. doi: 10.3389/fpls.2023.1155442
Received: 31 January 2023; Accepted: 11 April 2023;
Published: 19 April 2023.
Edited and Reviewed by:
Jihong Hu, Northwest A&F University, ChinaCopyright © 2023 Li, Liu, Zhang, Wang, Yadegari and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Yin Li, eWlubGkyMDIxQGh1c3QuZWR1LmNu