This study integrates whole-genome sequencing and transcriptome data from 1,063 primary colorectal cancers (CRCs) to understand the functional and prognostic impact of somatic mutations. The analysis identified 96 mutated driver genes, including 33 previously unknown ones, and revealed distinct patterns of pathway co-mutations. Timing analyses showed that early events were mostly chromosomal losses, while late events were amplifications. Several prognostic mutations and expression subtypes were identified, such as APC, MT-CYB, and SIN3A mutations, and five prognostic subtypes (CRPS1–CRPS5) were derived from unsupervised classification of transcriptomes. These subtypes were prognostically significant and provided deeper insights into CRC subtypes. The study also found links between tumour hypoxia and specific mutational signatures, and distinct molecular characteristics in microsatellite-instable (MIS) tumours. Overall, this comprehensive analysis provides a detailed understanding of the genomic and transcriptomic landscape of CRC, highlighting potential targets for individualized therapy.This study integrates whole-genome sequencing and transcriptome data from 1,063 primary colorectal cancers (CRCs) to understand the functional and prognostic impact of somatic mutations. The analysis identified 96 mutated driver genes, including 33 previously unknown ones, and revealed distinct patterns of pathway co-mutations. Timing analyses showed that early events were mostly chromosomal losses, while late events were amplifications. Several prognostic mutations and expression subtypes were identified, such as APC, MT-CYB, and SIN3A mutations, and five prognostic subtypes (CRPS1–CRPS5) were derived from unsupervised classification of transcriptomes. These subtypes were prognostically significant and provided deeper insights into CRC subtypes. The study also found links between tumour hypoxia and specific mutational signatures, and distinct molecular characteristics in microsatellite-instable (MIS) tumours. Overall, this comprehensive analysis provides a detailed understanding of the genomic and transcriptomic landscape of CRC, highlighting potential targets for individualized therapy.