Genes & Genomics

, Volume 40, Issue 4, pp 399–412 | Cite as

Transcriptome analysis of Δmig1Δmig2 mutant reveals their roles in methanol catabolism, peroxisome biogenesis and autophagy in methylotrophic yeast Pichia pastoris

  • Lei Shi
  • Xiaolong Wang
  • Jinjia Wang
  • Ping Zhang
  • Fei Qi
  • Menghao CaiEmail author
  • Yuanxing Zhang
  • Xiangshan ZhouEmail author
Research Article


Two catabolite repressor genes (MIG1 and MIG2) were previously identified in Pichia pastoris, and the derepression of alcohol oxidase (AOX) expression was realized in Δmig1 or Δmig1Δmig2 mutants grown in glycerol, but not in glucose. In this study, genome-wide RNA-seq analysis of Δmig1Δmig2 and the wild-type strain grown in glycerol revealed that the expression of numerous genes was greatly altered. Nearly 7% (357 genes) of approximately 5276 genes annotated in P. pastoris were significantly upregulated, with at least a two-fold differential expression in Δmig1Δmig2; the genes were mainly related to cell metabolism. Approximately 23% (1197 genes) were significantly downregulated; these were mainly correlated with the physiological characteristics of the cell. The methanol catabolism and peroxisome biogenesis pathways were remarkably enhanced, and the genes AOX1 and AOX2 were upregulated higher than 30-fold, which was consistent with the experimental results of AOX expression. The Mig proteins had a slight effect on autophagy when cells were grown in glycerol. The expression analysis of transcription factors showed that deletion of MIG1 and MIG2 significantly upregulated the binding of an essential transcription activator, Mit1p, with the AOX1 promoter, which suggested that Mig proteins might regulate the AOX1 promoter through the regulation of Mit1p. This work provides a reference for the further exploration of the methanol induction and catabolite repression mechanisms of AOX expression in methylotrophic yeasts.


Pichia pastoris RNA-seq Mig Alcohol oxidase Catabolite repression 



This work was supported by Shanghai Science and Technology Innovation Plan (17JC1402400); Fundamental Research Funds for the Central Universities (22A201514040) and Grants of Young and Middle-aged Leading Science and Technology Innovation Talents from Ministry of Science and Technology of China. The authors are grateful to Prof. James M. Cregg, BioGrammatics, Inc. and Keck Graduate Institute of Applied Life Science, for helpful suggestions. The authors also thank Shanghai Huaguan Biochip Co. Ltd. for the help of RNA-seq data analysis.

Compliance with ethical standards

Conflict of interest

Lei Shi declares that she has no conflict of interest. Xiaolong Wang declares that he has no conflict of interest. Jinjia Wang declares that she has no conflict of interest. Ping Zhang declares that she has no conflict of interest. Fei Qi declares that he has no conflict of interest. Menghao Cai declares that he has no conflict of interest. Yuanxing Zhang declares that he has no conflict of interest. Xiangshan Zhou declares that he has no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

13258_2017_641_MOESM1_ESM.pdf (628 kb)
Supplementary material 1 (PDF 627 KB)


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Copyright information

© The Genetics Society of Korea and Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  • Lei Shi
    • 1
  • Xiaolong Wang
    • 1
  • Jinjia Wang
    • 1
  • Ping Zhang
    • 1
  • Fei Qi
    • 1
  • Menghao Cai
    • 1
    Email author
  • Yuanxing Zhang
    • 1
    • 2
  • Xiangshan Zhou
    • 1
    Email author
  1. 1.State Key Laboratory of Bioreactor EngineeringEast China University of Science and TechnologyShanghaiChina
  2. 2.Shanghai Collaborative Innovation Center for BiomanufacturingShanghaiChina

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