Genome-scale metabolic modelling identifies reactions mediated by SNP-SNP interactions associated with yeast sporulation
Abstract Genome-scale metabolic models (GEMs) are powerful tools used to understand the functional effects of genetic variants. However, the impact of single nucleotide polymorphisms (SNPs) in transcription factors and their interactions on metabolic fluxes remains largely unexplored. Using gene exp...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | npj Systems Biology and Applications |
| Online Access: | https://doi.org/10.1038/s41540-025-00503-3 |
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| author | Srijith Sasikumar S Pavan Kumar Nirav Pravinbhai Bhatt Himanshu Sinha |
| author_facet | Srijith Sasikumar S Pavan Kumar Nirav Pravinbhai Bhatt Himanshu Sinha |
| author_sort | Srijith Sasikumar |
| collection | DOAJ |
| description | Abstract Genome-scale metabolic models (GEMs) are powerful tools used to understand the functional effects of genetic variants. However, the impact of single nucleotide polymorphisms (SNPs) in transcription factors and their interactions on metabolic fluxes remains largely unexplored. Using gene expression data from a yeast allele replacement panel grown during sporulation, we constructed co-expression networks and SNP-specific GEMs. Analysis of co-expression networks revealed that during sporulation, SNP-SNP interactions impact the connectivity of metabolic regulators involved in glycolysis, steroid and histidine biosynthesis, and amino acid metabolism. Further, genome-scale differential flux analysis identified reactions within six major metabolic pathways associated with sporulation efficiency variation. Notably, autophagy was predicted to act as a pentose pathway-dependent compensatory mechanism supplying critical precursors like nucleotides and amino acids, enhancing sporulation. Our study highlights how transcription factor polymorphisms interact to shape metabolic pathways in yeast, offering insights into genetic variants associated with metabolic traits in genome-wide association studies. |
| format | Article |
| id | doaj-art-7f4031ecf20047a2bdf3eaac09b38adc |
| institution | OA Journals |
| issn | 2056-7189 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Systems Biology and Applications |
| spelling | doaj-art-7f4031ecf20047a2bdf3eaac09b38adc2025-08-20T02:34:14ZengNature Portfolionpj Systems Biology and Applications2056-71892025-05-0111111510.1038/s41540-025-00503-3Genome-scale metabolic modelling identifies reactions mediated by SNP-SNP interactions associated with yeast sporulationSrijith Sasikumar0S Pavan Kumar1Nirav Pravinbhai Bhatt2Himanshu Sinha3Systems Genetics Lab, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology MadrasCentre for Integrative Biology and Systems Medicine (IBSE), Indian Institute of Technology MadrasCentre for Integrative Biology and Systems Medicine (IBSE), Indian Institute of Technology MadrasSystems Genetics Lab, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology MadrasAbstract Genome-scale metabolic models (GEMs) are powerful tools used to understand the functional effects of genetic variants. However, the impact of single nucleotide polymorphisms (SNPs) in transcription factors and their interactions on metabolic fluxes remains largely unexplored. Using gene expression data from a yeast allele replacement panel grown during sporulation, we constructed co-expression networks and SNP-specific GEMs. Analysis of co-expression networks revealed that during sporulation, SNP-SNP interactions impact the connectivity of metabolic regulators involved in glycolysis, steroid and histidine biosynthesis, and amino acid metabolism. Further, genome-scale differential flux analysis identified reactions within six major metabolic pathways associated with sporulation efficiency variation. Notably, autophagy was predicted to act as a pentose pathway-dependent compensatory mechanism supplying critical precursors like nucleotides and amino acids, enhancing sporulation. Our study highlights how transcription factor polymorphisms interact to shape metabolic pathways in yeast, offering insights into genetic variants associated with metabolic traits in genome-wide association studies.https://doi.org/10.1038/s41540-025-00503-3 |
| spellingShingle | Srijith Sasikumar S Pavan Kumar Nirav Pravinbhai Bhatt Himanshu Sinha Genome-scale metabolic modelling identifies reactions mediated by SNP-SNP interactions associated with yeast sporulation npj Systems Biology and Applications |
| title | Genome-scale metabolic modelling identifies reactions mediated by SNP-SNP interactions associated with yeast sporulation |
| title_full | Genome-scale metabolic modelling identifies reactions mediated by SNP-SNP interactions associated with yeast sporulation |
| title_fullStr | Genome-scale metabolic modelling identifies reactions mediated by SNP-SNP interactions associated with yeast sporulation |
| title_full_unstemmed | Genome-scale metabolic modelling identifies reactions mediated by SNP-SNP interactions associated with yeast sporulation |
| title_short | Genome-scale metabolic modelling identifies reactions mediated by SNP-SNP interactions associated with yeast sporulation |
| title_sort | genome scale metabolic modelling identifies reactions mediated by snp snp interactions associated with yeast sporulation |
| url | https://doi.org/10.1038/s41540-025-00503-3 |
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