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While numerous Fabaceae seeds are a good nutritional source of high-quality protein, the use of some species is hampered by toxic effects caused by exposure to metabolites that accumulate in the seeds. One such species is the faba or broad bean (Vicia faba L.), which accumulates vicine and convicine. These two glycoalkaloids cause favism, the breakdown of red blood cells in persons with a glucose-6-phosphate dehydrogenase deficiency. Because this is the most common enzyme deficiency worldwide, faba bean breeding efforts have focused on developing cultivars with low levels of these alkaloids. Consequently, quantification methods have been developed; however, they quantify vicine and convicine only and not the derivatives of these compounds that potentially generate the same bio-active molecules. Based on the recognition of previously unknown (con)vicine-containing compounds, we screened the fragmentation spectra of LC-MS/MS data from five faba bean cultivars using the characteristic fragments generated by (con)vicine. This resulted in the recognition of more than a hundred derivatives, of which 89 were tentatively identified. (Con)vicine was mainly derivatized through the addition of sugars, hydroxycinnamic acids, and dicarboxylic acids, with a group of compounds composed of two (con)vicine residues linked by dicarboxyl fatty acids. In general, the abundance profiles of the different derivatives in the five cultivars mimicked that of vicine and convicine, but some showed a derivative-specific profile. The description of the (con)vicine diversity will impact the interpretation of future studies on the biosynthesis of (con)vicine, and the content in potentially bio-active alkaloids in faba beans may be higher than that represented by the quantification of vicine and convicine alone. [ABSTRACT FROM AUTHOR]

The aim of this study was to integrate multi omics data to characterize underlying functional pathways and candidate genes for drip loss in pigs. The consideration of different omics levels allows elucidating the black box of phenotype expression. Metabolite and protein profiling was applied in Musculus longissimus dorsi samples of 97 Duroc × Pietrain pigs. In total, 126 and 35 annotated metabolites and proteins were quantified, respectively. In addition, all animals were genotyped with the porcine 60 k Illumina beadchip. An enrichment analysis resulted in 10 pathways, amongst others, sphingolipid metabolism and glycolysis/gluconeogenesis, with significant influence on drip loss. Drip loss and 22 metabolic components were analyzed as intermediate phenotypes within a genome-wide association study (GWAS). We detected significantly associated genetic markers and candidate genes for drip loss and for most of the metabolic components. On chromosome 18, a region with promising candidate genes was identified based on SNPs associated with drip loss, the protein "phosphoglycerate mutase 2" and the metabolite glycine. We hypothesize that association studies based on intermediate phenotypes are able to provide comprehensive insights in the genetic variation of genes directly involved in the metabolism of performance traits. In this way, the analyses contribute to identify reliable candidate genes. [ABSTRACT FROM AUTHOR]

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The aim of the study was to investigate single nucleotide polymorphisms (SNPs) and expression of SOX-6 to support its candidacy for growth, carcass, and meat quality traits in pigs. The first SNP, rs81358375, was associated with pH 45 min post mortem in loin (pH1 L ), the thickness of backfat and side fat, and carcass length in Pietrain (Pi) population, and related with backfat thickness and daily gain in Duroc × Pietrain F 2 (DuPi) population. The other SNP, rs321666676, was associated with meat colour in Pi population. In DuPi population, the protein, not mRNA, level of SOX-6 in high pH1 L pigs was significantly less abundant compared with low pH1 L pigs, where microRNAs targeting SOX-6 were also differently regulated. This paper shows that SOX-6 could be a potential candidate gene for porcine growth, carcass, and meat quality traits based on genetic association and gene expression. [ABSTRACT FROM AUTHOR]