Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Maize multi-omics reveal roles for autophagic recycling in proteome remodelling and lipid turnover

Nature Plants volume 4, pages 1056–1070 (2018)Cite this article

Subjects

Abstract

The turnover of cytoplasmic material by autophagic encapsulation and delivery to vacuoles is essential for recycling cellular constituents, especially under nutrient-limiting conditions. To determine how cells/tissues rely on autophagy, we applied in-depth multi-omic analyses to study maize (Zea mays) autophagy mutants grown under nitrogen-replete and -starvation conditions. Broad alterations in the leaf metabolome were evident in plants missing the core autophagy component ATG12, even in the absence of stress, particularly affecting products of lipid turnover and secondary metabolites, which were underpinned by substantial changes in the transcriptome and/or proteome. Cross-comparison of messenger RNA and protein abundances allowed for the identification of organelles, protein complexes and individual proteins targeted for selective autophagic clearance, and revealed several processes controlled by this catabolism. Collectively, we describe a facile multi-omic strategy to survey autophagic substrates, and show that autophagy has a remarkable influence in sculpting eukaryotic proteomes and membranes both before and during nutrient stress.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Maize atg12 mutants are hypersensitive to nitrogen stress and have elevated protein content.
Fig. 2: Maize atg12 mutants have substantially altered metabolomes in nitrogen-rich and -starvation conditions, especially with respect to lipids and secondary products.
Fig. 3: A survey of metabolic processes identifies points in maize lipid and secondary metabolism that are severely affected in atg12 plants.
Fig. 4: The maize transcriptome is substantially altered in the atg12 mutants under both nitrogen-rich and -starvation conditions.
Fig. 5: The maize proteome is substantially altered in the atg12 mutants under both nitrogen-rich and -starvation conditions.
Fig. 6: The impact of the atg12 mutations on the abundances of cellular compartments, metabolic processes and protein complexes in maize leaves.
Fig. 7: Comparisons between transcript and protein profiles identify processes impacted by transcription and/or autophagy and describe how various aspects of lipid and secondary metabolism are impacted by mRNA abundance and/or autophagy.

Data availability

The raw values obtained from the metabolomic data sets are available in Supplementary Table 1 (associated figures: Figs. 2, 3 and 7, Supplementary Figs. 1, 2 and 3 and Supplementary Table 2). RNA-seq data sets for the transcriptome analysis are available at the NCBI Sequence Read Archive database under the submission number SRP139303 (associated figures: Figs. 1, 4 and 7, Supplementary Figs. 1, 4 and 8 and Supplementary Tables 3–7 and 15). The raw sequence, msf and xml files for the mass spectrometry data sets are available in the ProteomeXchange database under accession number PXD009627 within the PRIDE repository (http://www.proteomexchange.org/). Protein identifiers and the corresponding gene accession numbers for the catalogue of maize proteins identified here can be found in Supplementary Tables 10–13. If any data sets are unavailable through the links stated above, they can be obtained from the corresponding author on request.

References

  1. Eguchi, M., Kimura, K., Makino, A. & Ishida, H. Autophagy is induced under Zn limitation and contributes to Zn-limited stress tolerance in Arabidopsis (Arabidopsis thaliana). Soil Sci. Plant Nutr. 63, 342–350 (2017).

    Article  CAS  Google Scholar 

  2. Havé, M., Marmagne, A., Chardon, F. & Masclaux-Daubresse, C. Nitrogen re-mobilization during leaf senescence: lessons from Arabidopsis to crops. J. Exp. Bot. 68, 2513–2529 (2017).

    PubMed  Google Scholar 

  3. Avin-Wittenberg, T. et al. Autophagy-related approaches for improving nutrient use efficiency and crop yield protection. J. Exp. Bot. 69, 1335–1353 (2018).

    Article  PubMed  CAS  Google Scholar 

  4. Marshall, R. S. & Vierstra, R. D. Autophagy: the master of bulk and selective recycling. Annu. Rev. Plant Biol. 69, 173–208 (2018).

    Article  CAS  PubMed  Google Scholar 

  5. Wang, P., Mugume, Y. & Bassham, D. C. New advances in autophagy in plants: regulation, selectivity and function. Sem. Cell Dev. Biol. 80, 113–122 (2017).

    Article  CAS  Google Scholar 

  6. Masclaux-Daubresse, C., Chen, Q. & Havé, M. Regulation of nutrient recycling via autophagy. Cur. Opin. Plant Biol. 39, 8–17 (2017).

    Article  CAS  Google Scholar 

  7. Li, F. et al. Autophagic recycling plays a central role in maize nitrogen re-mobilization. Plant Cell 27, 1389–1408 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Reggiori, F. & Klionsky, D. J. Autophagic processes in yeast: mechanism, machinery and regulation. Genetics 194, 341–361 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Farré, J. C. & Subramani, S. Mechanistic insights into selective autophagy pathways: lessons from yeast. Nat. Rev. Mol. Cell Biol. 17, 537–552 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Khaminets, A., Behl, C. & Dikic, I. Ubiquitin-dependent and -independent signals in selective autophagy. Trends Cell Biol. 26, 6–16 (2016).

    Article  CAS  PubMed  Google Scholar 

  11. Masclaux-Daubresse, C. et al. Stitching together the multiple dimensions of autophagy using metabolomics and transcriptomics reveals impacts on metabolism, development, and plant responses to the environment in Arabidopsis. Plant Cell 26, 1857–1877 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Avin-Wittenberg, T. et al. Global analysis of the role of autophagy in cellular metabolism and energy homeostasis in Arabidopsis seedlings under carbon starvation. Plant Cell 27, 306–322 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Rabinowitz, J. D. & White, E. Autophagy and metabolism. Science 330, 1344–1348 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Galluzzi, L., Pietrocola, F., Levine, B. & Kroemer, G. Metabolic control of autophagy. Cell 159, 1263–1276 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Wada, S. et al. Autophagy supports biomass production and nitrogen use efficiency at the vegetative stage in rice. Plant Physiol. 168, 60–73 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Robertson, G. P. & Vitousek, P. M. Nitrogen in agriculture: balancing the cost of an essential resource. Annu. Rev. Environ. Resour. 34, 97–125 (2009).

    Article  Google Scholar 

  17. Yang, X. S. et al. Gene expression biomarkers provide sensitive indicators of in planta nitrogen status in maize. Plant Physiol. 157, 1841–1852 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Curci, P. L. et al. Transcriptomic response of durum wheat to nitrogen starvation. Sci. Rep. 7, 1176 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Chung, T., Phillips, A. R. & Vierstra, R. D. ATG8 lipidation and ATG8-mediated autophagy in Arabidopsis require ATG12 expressed from the differentially controlled ATG12a and ATG12b loci. Plant J. 62, 483–493 (2010).

    Article  CAS  PubMed  Google Scholar 

  20. Thompson, A. R., Doelling, J. H., Suttangkakul, A. & Vierstra, R. D. Autophagic nutrient recycling in Arabidopsis directed by the ATG8 and ATG12 conjugation pathways. Plant Physiol. 138, 2097–2110 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Li, F., Chung, T. & Vierstra, R. D. AUTOPHAGY-RELATED11 plays a critical role in general autophagy and senescence-induced mitophagy in Arabidopsis. Plant Cell 26, 788–807 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Suttangkakul, A., Li, F., Chung, T. & Vierstra, R. D. The ATG1/ATG13 protein kinase complex is both a regulator and a target of autophagic recycling in Arabidopsis. Plant Cell 23, 3761–3779 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Evans, A. M., DeHaven, C. D., Barrett, T., Mitchell, M. & Milgram, E. Integrated, non-targeted, ultra-high performance liquid chromatography/electrospray ionization tandem mass spectrometry platform for the identification and relative quantification of the small-molecule complement of biological systems. Anal. Chem. 81, 6656–6667 (2009).

    Article  CAS  PubMed  Google Scholar 

  24. Ohta, T. et al. Untargeted metabolomic profiling as an evaluative tool of fenofibrate-induced toxicology in Fischer 344 male rats. Toxicol. Pathol. 37, 521–535 (2009).

    Article  CAS  PubMed  Google Scholar 

  25. Gerhardt, B. Fatty acid degradation in plants. Prog. Lipid Res. 31, 417–446 (1992).

    Article  CAS  PubMed  Google Scholar 

  26. Corbin, C. et al. Functional characterization of the pinoresinol-lariciresinol reductase-2 gene reveals its roles in yatein biosynthesis and flax defense response. Planta 246, 405–420 (2017).

    Article  CAS  PubMed  Google Scholar 

  27. Vogt, T. Phenylpropanoid biosynthesis. Mol. Plant 3, 2–20 (2010).

    Article  CAS  PubMed  Google Scholar 

  28. Dixon, D. P., Lapthorn, A. & Edwards, R. Plant glutathione transferases. Genome Biol. 3, reviews3004 (2002).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Zilic, S., Serpen, A., Akillioglu, G., Gokmen, V. & Vancetovic, J. Phenolic compounds, carotenoids, anthocyanins, and antioxidant capacity of colored maize (Zea mays L.) kernels. J. Agric. Food Chem. 60, 1224–1231 (2012).

    Article  CAS  PubMed  Google Scholar 

  30. Loreti, E. et al. Gibberellins, jasmonate and abscisic acid modulate the sucrose-induced expression of anthocyanin biosynthetic genes in Arabidopsis. New Phytol. 179, 1004–1016 (2008).

    Article  CAS  PubMed  Google Scholar 

  31. Doelling, J. H., Walker, J. M., Friedman, E. M., Thompson, A. R. & Vierstra, R. D. The APG8/12-activating enzyme APG7 is required for proper nutrient recycling and senescence in Arabidopsis thaliana. J. Biol. Chem. 277, 33105–33114 (2002).

    Article  CAS  PubMed  Google Scholar 

  32. Hanaoka, H. et al. Leaf senescence and starvation-induced chlorosis are accelerated by the disruption of an Arabidopsis autophagy gene. Plant Physiol. 129, 1181–1193 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Nishizawa, A., Yabuta, Y. & Shigeoka, S. Galactinol and raffinose constitute a novel function to protect plants from oxidative damage. Plant Physiol. 147, 1251–1263 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Yoshimoto, K. et al. Autophagy negatively regulates cell death by controlling NPR1-dependent salicylic acid signaling during senescence and the innate immune response in Arabidopsis. Plant Cell 21, 2914–2927 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Havé, M. et al. Increases in activity of proteasome and papain-like cysteine protease in Arabidopsis autophagy mutants: back-up compensatory effect or cell-death promoting effect? J. Exp. Bot. 69, 1369–1385 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Chen, G., Greer, M. S. & Weselake, R. J. Plant phospholipase A: advances in molecular biology, biochemistry, and cellular function. Biomol. Concepts 4, 527–532 (2013).

    Article  CAS  PubMed  Google Scholar 

  37. Hong, Y. et al. Plant phospholipases D and C and their diverse functions in stress responses. Prog. Lipid Res. 62, 55–74 (2016).

    Article  CAS  PubMed  Google Scholar 

  38. Izumi, M., Ishida, H., Nakamura, S. & Hidema, J. Entire photo-damaged chloroplasts are transported to the central vacuole by autophagy. Plant Cell 29, 377–394 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Sláviková, S. et al. The autophagy-associated Atg8 gene family operates during both favourable growth conditions and starvation stress in Arabidopsis. J. Exp. Bot. 56, 2839–2849 (2005).

    Article  PubMed  Google Scholar 

  40. Chung, T., Suttangkakul, A. & Vierstra, R. D. The ATG autophagic conjugation system in maize: ATG transcripts and abundance of the ATG8–lipid adduct are regulated by development and nutrient availability. Plant Physiol. 149, 220–234 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Shibata, M. et al. Highly oxidized peroxisomes are selectively degraded via autophagy in Arabidopsis. Plant Cell 25, 4967–4983 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Goto-Yamada, S. et al. Chaperone and protease functions of LON protease 2 modulate the peroxisomal transition and degradation with autophagy. Plant Cell Physiol. 55, 482–496 (2014).

    Article  CAS  PubMed  Google Scholar 

  43. Farmer, L. M. et al. Disrupting autophagy restores peroxisome function to an Arabidopsis lon2 mutant and reveals a role for the LON2 protease in peroxisomal matrix protein degradation. Plant Cell 25, 4085–4100 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Marshall, R. S., Li, F., Gemperline, D. C., Book, A. J. & Vierstra, R. D. Autophagic degradation of the 26S proteasome is mediated by the dual ATG8/ubiquitin receptor RPN10 in Arabidopsis. Mol. Cell 58, 1053–1066 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Liu, Y. et al. Degradation of the endoplasmic reticulum by autophagy during endoplasmic reticulum stress in Arabidopsis. Plant Cell 24, 4635–4651 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Guiboileau, A. et al. The autophagy machinery controls nitrogen re-mobilization at the whole plant level under both limiting and ample nitrate conditions in Arabidopsis. New Phytol. 194, 732–740 (2012).

    Article  CAS  PubMed  Google Scholar 

  47. Hu, J. et al. Plant peroxisomes: biogenesis and function. Plant Cell 24, 2279–2303 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Coradetti, S. T. et al. Functional genomics of lipid metabolism in the oleaginous yeast Rhodosporidium toruloides. eLife 7, e32110 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Zhao, L., Dai, J. & Wu, Q. Autophagy-like processes are involved in lipid droplet degradation in Auxenochlorella protothecoides during the heterotrophy-autotrophy transition. Front. Plant Sci. 5, 400 (2014).

    PubMed  PubMed Central  Google Scholar 

  50. Singh, R. et al. Autophagy regulates lipid metabolism. Nature 458, 1131–1135 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Izumi, M., Hidema, J., Makino, A. & Ishida, H. Autophagy contributes to night-time energy availability for growth in Arabidopsis. Plant Physiol. 161, 1682–1693 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Kurusu, T. et al. OsATG7 is required for autophagy-dependent lipid metabolism in rice postmeiotic anther development. Autophagy 10, 878–888 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Kunz, H. H. et al. The ABC transporter PXA1 and peroxisomal β-oxidation are vital for metabolism in mature leaves of Arabidopsis during extended darkness. Plant Cell 21, 2733–2749 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Ishizaki, K. et al. The critical role of Arabidopsis ELECTRON-TRANSFER FLAVOPROTEIN:UBIQUINONE OXIDOREDUCTASE during dark-induced starvation. Plant Cell 17, 2587–2600 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Okazaki, Y. & Saito, K. Roles of lipids as signaling molecules and mitigators during stress response in plants. Plant J. 79, 584–596 (2014).

    Article  CAS  PubMed  Google Scholar 

  56. Elander, P. H., Minina, E. A. & Bozhkov, P. V. Autophagy in turnover of lipid stores: trans-kingdom comparison. J. Exp. Bot. 69, 1301–1311 (2018).

    Article  PubMed  CAS  Google Scholar 

  57. Pyc, M. et al. Turning over a new leaf in lipid droplet biology. Trends Plant Sci. 22, 596–609 (2017).

    Article  CAS  PubMed  Google Scholar 

  58. Brehelin, C., Kessler, F. & van Wijk, K. J. Plastoglobules: versatile lipoprotein particles in plastids. Trends Plant Sci. 12, 260–266 (2007).

    Article  CAS  PubMed  Google Scholar 

  59. Michaeli, S., Honig, A., Levanony, H., Peled-Zehavi, H. & Galili, G. Arabidopsis ATG8-INTERACTING PROTEIN1 is involved in autophagy-dependent vesicular trafficking of plastid proteins to the vacuole. Plant Cell 26, 4084–4101 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Yoshimoto, K. et al. Processing of the ubiquitin-like ATG8 proteins by ATG4 is essential for plant autophagy. Plant Cell 16, 2967–2983 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Kim, J. et al. Autophagy-related proteins are required for degradation of peroxisomes in Arabidopsis hypocotyls during seedling growth. Plant Cell 25, 4956–4966 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Settles, A. M. et al. Sequence-indexed mutations in maize using the UniformMu transposon-tagging population. BMC Genomics 8, 116 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  63. Arnon, D. I. Copper enzymes in isolated chloroplasts. Polyphenoloxidase in Beta vulgaris. Plant Physiol. 24, 1–15 (1949).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Reyes, F. C. et al. Delivery of prolamins to the protein storage vacuole in maize aleurone cells. Plant Cell 23, 769–784 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Subbaiah, C. C. et al. Mitochondrial localization and putative signaling function of sucrose synthase in maize. J. Biol. Chem. 281, 15625–15635 (2006).

    Article  CAS  PubMed  Google Scholar 

  66. Smalle, J. et al. Cytokinin growth responses in Arabidopsis involve the 26S proteasome subunit RPN12. Plant Cell 14, 17–32 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Dehaven, C. D., Evans, A. M., Dai, H. & Lawton, K. A. Organization of GC/MS and LC/MS metabolomics data into chemical libraries. J. Cheminform. 2, 9 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  68. Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13, 731–740 (2016).

    Article  CAS  PubMed  Google Scholar 

  69. Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Ziegler, G. et al. Ionomic screening of field-grown soybean identifies mutants with altered seed elemental composition. Plant Genome 6, 2 (2013).

    Article  CAS  Google Scholar 

  71. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Trapnell, C. et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protoc. 7, 562–578 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Leng, N. et al. EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq experiments. Bioinformatics 29, 1035–1043 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Pfaffl, M. W. A new mathematical model for relative quantification in real-time RT–PCR. Nucleic Acids Res. 29, e45 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Manoli, A., Sturaro, A., Trevisan, S., Quaggiotti, S. & Nonis, A. Evaluation of candidate reference genes for qPCR in maize. J. Plant Physiol. 169, 807–815 (2012).

    Article  CAS  PubMed  Google Scholar 

  78. Aguilar-Hernandez, V. et al. Mass spectrometric analyses reveal a central role for ubiquitylation in remodeling the Arabidopsis proteome during photomorphogenesis. Mol. Plant 10, 846–865 (2017).

    Article  CAS  PubMed  Google Scholar 

  79. Eng, J. K., McCormack, A. L. & Yates, J. R. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom. 5, 976–989 (1994).

    Article  CAS  PubMed  Google Scholar 

  80. Silva, J. C., Gorenstein, M. V., Li, G. Z., Vissers, J. P. & Geromanos, S. J. Absolute quantification of proteins by LCMSE: a virtue of parallel MS acquisition. Mol. Cell Proteomics. 5, 144–156 (2006).

    Article  CAS  PubMed  Google Scholar 

  81. Du, Z., Zhou, X., Ling, Y., Zhang, Z. & Su, Z. agriGO: a GO analysis toolkit for the agricultural community. Nucleic Acids Res. 38, W64–W70 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Tian, T. et al. agriGOv2.0: a GO analysis toolkit for the agricultural community, 2017 update. Nucleic Acids Res. 45, W122–W129 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank J. Barrett, G. Ziegler and I. Baxter in the USDA-ARS Plant Genetics Facility at the Donald Danforth Plant Science Center for performing the ionomic analyses; M. Dyer at Washington University in St. Louis for help with the greenhouse studies; D. Alexander and L. Guo at Metabolon for the metabolomic analyses; and A. W. Lomax at the University of Wisconsin-Madison for the NBR1 antibody. This work was supported by a grant from the NSF Plant Genome Research Program (IOS-1329956).

Author information

Author notes

  1. Faqiang Li

    Present address: College of Life Sciences, South China Agricultural University, Guangzhou, China

Authors and Affiliations

  1. Department of Biology, Washington University in St. Louis, St. Louis, MO, USA

    Fionn McLoughlin, Robert C. Augustine, Richard S. Marshall, Liam D. Kirkpatrick & Richard D. Vierstra

  2. Department of Genetics, University of Wisconsin, Madison, WI, USA

    Faqiang Li, Marisa S. Otegui & Richard D. Vierstra

  3. Department of Botany, University of Wisconsin, Madison, WI, USA

    Marisa S. Otegui

  4. Laboratory of Cell and Molecular Biology, University of Wisconsin, Madison, WI, USA

    Marisa S. Otegui

Authors
  1. Fionn McLoughlin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Robert C. Augustine
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Richard S. Marshall
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Faqiang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Liam D. Kirkpatrick
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Marisa S. Otegui
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Richard D. Vierstra
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

F.L. and R.D.V. conceived of and designed the project. F.L. grew the plant material for the omics work. F.M., F.L., R.S.M. and L.D.K. conducted the experiments with help from the staff at Metabolon for the metabolite analyses. F.M., R.C.A., R.S.M., L.D.K., M.S.O. and R.D.V. analysed data. F.M. and R.D.V. wrote the manuscript with input from all of the co-authors.

Corresponding author

Correspondence to Richard D. Vierstra.

Ethics declarations

Competing interests

The authors declare that they have no competing financial interests as defined by Nature Publishing Group, or other interests that might be perceived to influence the results and/or discussion reported in this article.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figures 1–9.

Reporting Summary

Dataset 1

Raw values metabolomics both leaves.

Dataset 2

Metabolomics both leaves.

Dataset 3

Transcriptomics Fragment length and CV values.

Dataset 4

Transcriptomics 2nd leaf raw data.

Dataset 5

Transcriptomics 4th leaf raw data.

Dataset 6

Transcriptomics 2nd leaf.

Dataset 7

Transcriptomics 4th leaf.

Dataset 8

Ionomics Raw data both leaves.

Dataset 9

Values used for protein normalization.

Dataset 10

Proteomics 2nd leaf raw data.

Dataset 11

Proteomics 4th leaf raw data.

Dataset 12

Proteomics 2nd leaf.

Dataset 13

Proteomics 4th leaf.

Dataset 14

Modified gene ontology list.

Dataset 15

Merged mRNA and Protein responses.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

McLoughlin, F., Augustine, R.C., Marshall, R.S. et al. Maize multi-omics reveal roles for autophagic recycling in proteome remodelling and lipid turnover. Nature Plants 4, 1056–1070 (2018). https://doi.org/10.1038/s41477-018-0299-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41477-018-0299-2

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research