Table_1_A Genome-Wide Study of Allele-Specific Expression in Colorectal Cancer.XLSX

Accumulating evidence from small-scale studies has suggested that allele-specific expression (ASE) plays an important role in tumor initiation and progression. However, little is known about genome-wide ASE in tumors. In this study, we conducted a comprehensive analysis of ASE in individuals with colorectal cancer (CRC) on a genome-wide scale. We identified 5.4 thousand genome-wide ASEs of single nucleotide variations (SNVs) from tumor and normal tissues of 59 individuals with CRC. We observed an increased ASE level in tumor samples and the ASEs enriched as hotspots on the genome. Around 63% of the genes located there were previously reported to contain complex regulatory elements, e.g., human leukocyte antigen (HLA), or were implicated in tumor progression. Focussing on the allelic expression of somatic mutations, we found that 37.5% of them exhibited ASE, and genes harboring such somatic mutations, were enriched in important pathways implicated in cancers. In addition, by comparing the expected and observed ASE events in tumor samples, we identified 50 tumor specific ASEs which possibly contributed to the somatic events in the regulatory regions of the genes and significantly enriched known cancer driver genes. By analyzing CRC ASEs from several perspectives, we provided a systematic understanding of how ASE is implicated in both tumor and normal tissues and will be of critical value in guiding ASE studies in cancer.</p

Data_Sheet_1_A Genome-Wide Study of Allele-Specific Expression in Colorectal Cancer.PDF

Accumulating evidence from small-scale studies has suggested that allele-specific expression (ASE) plays an important role in tumor initiation and progression. However, little is known about genome-wide ASE in tumors. In this study, we conducted a comprehensive analysis of ASE in individuals with colorectal cancer (CRC) on a genome-wide scale. We identified 5.4 thousand genome-wide ASEs of single nucleotide variations (SNVs) from tumor and normal tissues of 59 individuals with CRC. We observed an increased ASE level in tumor samples and the ASEs enriched as hotspots on the genome. Around 63% of the genes located there were previously reported to contain complex regulatory elements, e.g., human leukocyte antigen (HLA), or were implicated in tumor progression. Focussing on the allelic expression of somatic mutations, we found that 37.5% of them exhibited ASE, and genes harboring such somatic mutations, were enriched in important pathways implicated in cancers. In addition, by comparing the expected and observed ASE events in tumor samples, we identified 50 tumor specific ASEs which possibly contributed to the somatic events in the regulatory regions of the genes and significantly enriched known cancer driver genes. By analyzing CRC ASEs from several perspectives, we provided a systematic understanding of how ASE is implicated in both tumor and normal tissues and will be of critical value in guiding ASE studies in cancer.</p

Data_Sheet_2_A Genome-Wide Study of Allele-Specific Expression in Colorectal Cancer.PDF

Accumulating evidence from small-scale studies has suggested that allele-specific expression (ASE) plays an important role in tumor initiation and progression. However, little is known about genome-wide ASE in tumors. In this study, we conducted a comprehensive analysis of ASE in individuals with colorectal cancer (CRC) on a genome-wide scale. We identified 5.4 thousand genome-wide ASEs of single nucleotide variations (SNVs) from tumor and normal tissues of 59 individuals with CRC. We observed an increased ASE level in tumor samples and the ASEs enriched as hotspots on the genome. Around 63% of the genes located there were previously reported to contain complex regulatory elements, e.g., human leukocyte antigen (HLA), or were implicated in tumor progression. Focussing on the allelic expression of somatic mutations, we found that 37.5% of them exhibited ASE, and genes harboring such somatic mutations, were enriched in important pathways implicated in cancers. In addition, by comparing the expected and observed ASE events in tumor samples, we identified 50 tumor specific ASEs which possibly contributed to the somatic events in the regulatory regions of the genes and significantly enriched known cancer driver genes. By analyzing CRC ASEs from several perspectives, we provided a systematic understanding of how ASE is implicated in both tumor and normal tissues and will be of critical value in guiding ASE studies in cancer.</p

Data_Sheet_3_A Genome-Wide Study of Allele-Specific Expression in Colorectal Cancer.PDF

Accumulating evidence from small-scale studies has suggested that allele-specific expression (ASE) plays an important role in tumor initiation and progression. However, little is known about genome-wide ASE in tumors. In this study, we conducted a comprehensive analysis of ASE in individuals with colorectal cancer (CRC) on a genome-wide scale. We identified 5.4 thousand genome-wide ASEs of single nucleotide variations (SNVs) from tumor and normal tissues of 59 individuals with CRC. We observed an increased ASE level in tumor samples and the ASEs enriched as hotspots on the genome. Around 63% of the genes located there were previously reported to contain complex regulatory elements, e.g., human leukocyte antigen (HLA), or were implicated in tumor progression. Focussing on the allelic expression of somatic mutations, we found that 37.5% of them exhibited ASE, and genes harboring such somatic mutations, were enriched in important pathways implicated in cancers. In addition, by comparing the expected and observed ASE events in tumor samples, we identified 50 tumor specific ASEs which possibly contributed to the somatic events in the regulatory regions of the genes and significantly enriched known cancer driver genes. By analyzing CRC ASEs from several perspectives, we provided a systematic understanding of how ASE is implicated in both tumor and normal tissues and will be of critical value in guiding ASE studies in cancer.</p

Additional file 2 of The self-organization model reveals systematic characteristics of aging

Additional file 2 : Table S1 modules based on order-parameters of the aging self-organization system using methylation profiles. (XLS 2406 kb

Additional file 1 of The self-organization model reveals systematic characteristics of aging

Additional file 1 : Figure S1 Hierarchies of the the aging self-organization system. (a, b) cross-talks between the 492th module and other modules in the model of 0–20 vs. 20–50, the methylation profile; (c, d) cross-talks between the 1799th module and other modules in the model of 20–50 vs. 50–70, the expression profile; (a, c) enriched BP terms; (b, d) enriched KEGG pathways; Figure S2 Age acceleration versus number of somatic mutations in the TCGA data based on methylation profiles. Figure S3 Age acceleration versus number of somatic mutations in the TCGA data based on expression profiles. Figure S4 aging acceleration characteristics across cancers using the top differential expression module. (a) connection of BP terms based on order-parameter modules; (b) connection of KEGG pathways based on order-parameter modules

Expression pattern of APOB and APOA4 in rabbit, mouse and human.

(A) APOA4 fold change in atherosclerotic animal models and human atherosclerotic patients. Blue bars indicate expression increases more than two times in disease groups. (B) APOB fold change in atherosclerotic animal models and human atherosclerotic patients. (C) Expression ratio between APOB and APOA4 in all available samples.</p

Additional file 5 of The self-organization model reveals systematic characteristics of aging

Additional file 5 : Table S7 data partition of gene expression profiles as well as the age (XLS 130 kb

Prediction of Tyrosine Sulfation with mRMR Feature Selection and Analysis

Protein tyrosine sulfation is a ubiquitous post-translational modification (PTM) of secreted and transmembrane proteins that pass through the Golgi apparatus. In this study, we developed a new method for protein tyrosine sulfation prediction based on a nearest neighbor algorithm with the maximum relevance minimum redundancy (mRMR) method followed by incremental feature selection (IFS). We incorporated features of sequence conservation, residual disorder, and amino acid factor, 229 features in total, to predict tyrosine sulfation sites. From these 229 features, 145 features were selected and deemed as the optimized features for the prediction. The prediction model achieved a prediction accuracy of 90.01% using the optimal 145-feature set. Feature analysis showed that conservation, disorder, and physicochemical/biochemical properties of amino acids all contributed to the sulfation process. Site-specific feature analysis showed that the features derived from its surrounding sites contributed profoundly to sulfation site determination in addition to features derived from the sulfation site itself. The detailed feature analysis in this paper might help understand more of the sulfation mechanism and guide the related experimental validation

Additional file 6 of The self-organization model reveals systematic characteristics of aging

Additional file 6 : Table S8 data partition of DNA methylation profiles as well as the age. Note: 0 indicates genes are not selected as order-parameters, otherwise are selected within modules (Table S1-S2). 0 stands for training data, and 1 stands for test data in the third column (Table S7-S8). (XLS 242 kb