Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/59873
Título: | Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associations |
Autor(es): | Kang, Kang Bergdahl, Basti Machado, Daniel Dato, Laura Han, Ting-Li Li, Jun Villas-Boas, Silas Herrgård, Markus J. Förster, Jochen Panagiotou, Gianni |
Palavras-chave: | geno-to-phenotype association multi-omic study platform strain Saccharomyces cerevisiae stress resistance |
Data: | 2019 |
Editora: | Oxford University Press |
Revista: | GigaScience |
Citação: | Kang, Kang; Bergdahl, Basti; Machado, Daniel; Dato, Laura; Han, Ting-Li; Li, Jun; Villas-Boas, Silas; Herrgård, Markus J; Förster, Jochen; Panagiotou, Gianni, Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associations. GigaScience, 8(4), giz015, 2019 |
Resumo(s): | The selection of bioengineering platform strains and engineering strategies to improve the stress resistance of Saccharomyces cerevisiae remains a pressing need in bio-based chemical production. Thus, a systematic effort to exploit the genotypic and phenotypic diversity to boost yeast's industrial value is still urgently needed. Here, we analyzed 5400 growth curves obtained from 36 S. cerevisiae strains and comprehensively profiled their resistances against 13 industrially relevant stresses. We observed that bioethanol and brewing strains exhibit higher resistance against acidic conditions, however, plant isolates tend to have wider range of resistance, which may be associated with their metabolome and fluxome signatures in TCA cycle and fatty acid metabolism. By deep genomic sequencing we found that industrial strains have more genomic duplications especially affecting transcription factors, presenting disparate evolutionary paths in comparison to the environmental strains which have more InDels, gene deletions and strain-specific genes. Genome-wide association studies coupled with protein-protein interaction networks uncovered novel genetic determinants of stress resistances. These resistance-related engineering targets and strain rankings provide a valuable source for engineering significantly improved industrial platform strains. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/59873 |
DOI: | 10.1093/gigascience/giz015 |
ISSN: | 2047-217X |
Versão da editora: | https://academic.oup.com/gigascience |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
document_50521_1.pdf | 4,83 MB | Adobe PDF | Ver/Abrir |