Anti-MAP3K5 monoclonal antibody, clone FQ664Z Knockout Validated

Background: Feed efficiency is one of the major components determining costs of animal production. Residual feed intake (RFI) is defined as the difference between the observed and the expected feed intake given a certain production. Residual feed intake 1 (RFI1) was calculated based on regression of individual daily feed intake (DFI) on initial test weight and average daily gain. Residual feed intake 2 (RFI2) was as RFI1 except it was also regressed with respect to backfat (BF). It has been shown to be a sensitive and accurate measure for feed efficiency in livestock but knowledge of the genomic regions and mechanisms affecting RFI in pigs is lacking. The study aimed to identify genetic markers and candidate genes for RFI and its component traits as well as pathways associated with RFI in Danish Duroc boars by genome-wide associations and systems genetic analyses. Results: Phenotypic and genotypic records (using the Illumina Porcine SNP60 BeadChip) were available on 1,272 boars. Fifteen and 12 loci were significantly associated (p < 1.52 x 10(-6)) with RFI1 and RFI2, respectively. Among them, 10 SNPs were significantly associated with both RFI1 and RFI2 implying the existence of common mechanisms controlling the two RFI measures. Significant QTL regions for component traits of RFI (DFI and BF) were detected on pig chromosome (SSC) 1 (for DFI) and 2 for (BF). The SNPs within MAP3K5 and PEX7 on SSC 1, ENSSSCG00000022338 on SSC 9, and DSCAM on SSC 13 might be interesting markers for both RFI measures. Functional annotation of genes in 0.5 Mb size flanking significant SNPs indicated regulation of protein and lipid metabolic process, gap junction, inositol phosphate metabolism and insulin signaling pathway are significant biological processes and pathways for RFI, respectively. Conclusions: The study detected novel genetic variants and QTLs on SSC 1, 8, 9, 13 and 18 for RFI and indicated significant biological processes and metabolic pathways involved in RFI. The study also detected novel QTLs for component traits of RFI. These results improve our knowledge of the genetic architecture and potential biological pathways underlying RFI; which would be useful for further investigations of key candidate genes for RFI and for development of biomarkers.

We conducted an epigenome-wide association study on obesity-related traits. We used data from 2 prospective, population-based cohort studies: the Rotterdam Study (RS) (2006-2013) and the Atherosclerosis Risk in Communities (ARIC) Study (1990-1992). We used theRS(n = 1,450) as the discovery panel and the ARIC Study (n = 2,097) as the replication panel. Linear mixed-effect models were used to assess the cross-sectional associations between genome-wide DNA methylation in leukocytes and body mass index (BMI) and waist circumference (WC), adjusting for sex, age, smoking, leukocyte proportions, array number, and position on array. The latter 2 variables were modeled as random effects. Fourteen 5'-C-phosphate-G-3' (CpG) sites were associated with BMI and 26 CpG sites with WC in the RS after Bonferroni correction (P < 1.07 x 10(-7)), of which 12 and 13 CpGs were replicated in the ARIC Study, respectively. The most significant novel CpGs were located on the Musashi RNA binding protein 2 gene (MSI2; cg21139312) and the leucyl-tRNA synthetase 2, mitochondrial gene (LARS2; cg18030453) and were associated with both BMI and WC. CpGs at BRDT, PSMD1, IFI44L, MAP1A, and MAP3K5 were associated with BMI. CpGs at LGALS3BP, MAP2K3, DHCR24, CPSF4L, and TMEM49 were associated with WC. We report novel associations between methylation at MSI2 and LARS2 and obesity-related traits. These results provide further insight into mechanisms underlying obesity-related traits, which can enable identification of new biomarkers in obesity-related chronic diseases.