RESUMO
Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI. We analyzed genotype and blood gene expression data in up to 5,619 samples from the Framingham Heart Study (FHS). Using 3,992 single nucleotide polymorphisms (SNPs) at 97 BMI loci and 20,692 transcripts within 1 Mb, we performed separate association analyses of transcript with BMI and SNP with transcript (PBMI and PSNP, respectively) and then a correlated meta-analysis between the full summary data sets (PMETA). We identified transcripts that met Bonferroni-corrected significance for each omic, were more significant in the correlated meta-analysis than each omic, and were at least nominally associated with BMI in FHS data. Among 308 significant SNP-transcript-BMI associations, we identified seven genes (NT5C2, GSTM3, SNAPC3, SPNS1, TMEM245, YPEL3, and ZNF646) in five association regions. Using an independent sample of blood gene expression data, we validated results for SNAPC3 and YPEL3. We tested for generalization of these associations in hypothalamus, nucleus accumbens, and liver and observed significant (PMETA<0.05 & PMETA
RESUMO
As the fossil fuel reserves are depleting rapidly, there is a need for alternate fuels to meet the day to day mounting energy demands. As fossil fuel started depleting, a quest for alternate forms of fuel was initiated and biofuel is one of its promising outcomes. First-generation biofuels are made from edible sources like vegetable oils, starch, and sugars. Second-generation biofuels (SGB) are derived from lignocellulosic crops and the third-generation involves algae for biofuel production. Technical challenges in the production of SGB are hampering its commercialization. Advanced molecular technologies like metagenomics can help in the discovery of novel lignocellulosic biomass-degrading enzymes for commercialization and industrial production of SGB. This review discusses the metagenomic outcomes to enlighten the importance of unexplored habitats for novel cellulolytic gene mining. It also emphasizes the potential of different metagenomic approaches to explore the uncultivable cellulose-degrading microbiome as well as cellulolytic enzymes associated with them. This review also includes effective pre-treatment technology and consolidated bioprocessing for efficient biofuel production.