METHODS: DNA methylation profiles (Illumina Infinium® HumanMethylation450 BeadChip) from 1941 individuals from four population-based European cohorts were analysed in relation to body mass index, waist circumference, waist-hip and waist-height ratio within a meta-analytical framework. In a subset of these individuals, data on genome-wide gene expression level, biomarkers of glucose and lipid metabolism were also available. Validation of methylation markers associated with all adiposity measures was performed in 358 individuals. Finally, we investigated the association of obesity-related methylation marks with breast, colorectal cancer and myocardial infarction within relevant subsets of the discovery population.
RESULTS: We identified 40 CpG loci with methylation levels associated with at least one adiposity measure. Of these, one CpG locus (cg06500161) in ABCG1 was associated with all four adiposity measures (P = 9.07×10-8 to 3.27×10-18) and lower transcriptional activity of the full-length isoform of ABCG1 (P = 6.00×10-7), higher triglyceride levels (P = 5.37×10-9) and higher triglycerides-to-HDL cholesterol ratio (P = 1.03×10-10). Of the 40 informative and obesity-related CpG loci, two (in IL2RB and FGF18) were significantly associated with colorectal cancer (inversely, P
RESULTS: The genome size of LM115 and LM41 was 2,959,041 and 2,963,111 bp, respectively. These two strains shared approximately 90% homologous genes. Comparative genomics and phylogenomic analyses revealed that LM115 and LM41 were more closely related to the reference strains F2365 and EGD-e, respectively. Our virulence profiling indicated a total of 31 virulence genes shared by both analysed strains. These shared genes included those that encode for internalins and L. monocytogenes pathogenicity island 1 (LIPI-1). Both the Malaysian L. monocytogenes strains also harboured several genes associated with stress tolerance to counter the adverse conditions. Seven antibiotic and efflux pump related genes which may confer resistance against lincomycin, erythromycin, fosfomycin, quinolone, tetracycline, and penicillin, and macrolides were identified in the genomes of both strains.
CONCLUSIONS: Whole genome sequencing and comparative genomics analyses revealed two virulent L. monocytogenes strains isolated from ready-to-eat foods in Malaysia. The identification of strains with pathogenic, persistent, and antibiotic resistant potentials from minimally processed food warrant close attention from both healthcare and food industry.
Result: This study describes for the first time, a 33.90 Mbp de novo assembled genome of a putative C. theobromae isolate from cacao. Ab initio gene prediction identified 9264 protein-coding genes, of which 800 are unique to C. theobromae when compared to Rhizoctonia spp., a closely related group. Transcriptome analysis using RNA isolated from 4 independent VSD symptomatic cacao stems identified 3550 transcriptionally active genes when compared to the assembled C. theobromae genome while transcripts for only 4 C. theobromae genes were detected in 2 asymptomatic stems. De novo assembly of the non-cacao associated reads from the VSD symptomatic stems uniformly produced genes with high identity to predicted genes in the C. theobromae genome as compared to Rhizoctonia spp. or genes found in Genbank. Further analysis of the predicted C. theobromae transcriptome was carried out identifying CAZy gene classes, KEGG-pathway associated genes, and 138 putative effector proteins.
Conclusion: These findings put forth, for the first time, a predicted genome for the fastidious basidiomycete C. theobromae causing VSD on cacao providing a model for testing and comparison in the future. The C. theobromae genome predicts a pathogenesis model involving secreted effector proteins to suppress plant defense mechanisms and plant cell wall degrading enzymes.
METHODS: To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74-421 samples).
RESULTS: We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction.
CONCLUSIONS: By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.
METHODS: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data.
RESULTS: Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10-5). We found seven loci associated with risk for both cancers (P Bonferroni < 2.4 × 10-9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10-7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation.
CONCLUSIONS: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis.
IMPACT: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.