Identification and validation of candidate genes associated with domesticated and improved traits in soybean

Soybean, an important source of vegetable oils and proteins for humans, has undergone significant phenotypic changes during domestication and improvement. However, there is limited knowledge about genes related to these domesticated and improved traits, such as flowering time, seed development, alkaline-salt tolerance, and seed oil content (SOC). In this study, more than 106,000 single nucleotide polymorphisms (SNPs) were identified by restriction site associated DNA sequencing of 14 wild, 153 landrace, and 119 bred soybean accessions, and 198 candidate domestication regions (CDRs) were identified via multiple genetic diversity analyses. Of the 1489 candidate domestication genes (CDGs) within these CDRs, a total of 330 CDGs were related to the above four traits in the domestication, gene ontology (GO) enrichment, gene expression, and pathway analyses. Eighteen, 60, 66, and 10 of the 330 CDGs were significantly associated with the above four traits, respectively. Of 134 traitassociated CDGs, 29 overlapped with previous CDGs, 11 were consistent with candidate genes in previous trait association studies, and 66 were covered by the domesticated and improved quantitative trait loci or their adjacent regions, having six common CDGs, such as one functionally characterized gene Glyma15 g17480 (GmZTL3). Of the 68 seed size (SS) and SOC CDGs, 37 were further confirmed by gene expression analysis. In addition, eight genes were found to be related to artificial selection during modern breeding. Therefore, this study provides an integrated method for efficiently identifying CDGs and valuable information for domestication and genetic research

The effect of smear layer removal on marginal contraction gaps.

Journal of Oral Rehabilitation214411-41

Bulletin of the California Polytechnic School 1933-34

Identification of peptides that can bind to major histocompatibility complex (MHC) molecules is important for anticipation of T-cell epitopes and for the design of epitope-based vaccines. Population coverage of epitope vaccines is, however, compromised by the extreme polymorphism of MHC molecules, which is in fact the basis for their differential peptide binding. Therefore, grouping of MHC molecules into supertypes according to peptide-binding specificity is relevant for optimizing the composition of epitope-based vaccines. Despite the fact that the peptide-binding specificity of MHC molecules is linked to their specific amino acid sequences, it is unclear how amino sequence differences correlate with peptide-binding specificities. In this chapter, we detail a method for defining MHC supertypes based on the analysis and subsequent clustering of their peptide-binding repertoires