Simplified amino acid alphabets based on deviation of conditional probability from random background

The primitive data for deducing the Miyazawa-Jernigan contact energy or BLOSUM score matrix consists of pair frequency counts. Each amino acid corresponds to a conditional probability distribution. Based on the deviation of such conditional probability from random background, a scheme for reduction of amino acid alphabet is proposed. It is observed that evident discrepancy exists between reduced alphabets obtained from raw data of the Miyazawa-Jernigan's and BLOSUM's residue pair counts. Taking homologous sequence database SCOP40 as a test set, we detect homology with the obtained coarse-grained substitution matrices. It is verified that the reduced alphabets obtained well preserve information contained in the original 20-letter alphabet.Comment: 9 pages,3figure

eQTL Networks Reveal Complex Genetic Architecture in the Immature Soybean Seed

The complex network of regulatory factors and interactions involved in transcriptional regulation within the seed is not well understood. To evaluate gene expression regulation in the immature seed, we utilized a genetical genomics approach on a soybean [Glycine max (L.) Merr.] recombinant inbred line (RIL) population and produced a genome-wide expression quantitative trait loci (eQTL) dataset. The validity of the dataset was confirmed by mapping the eQTL hotspot for flavonoid biosynthesis-related genes to a region containing repeats of chalcone synthase (CHS) genes known to correspond to the soybean inhibitor locus that regulates seed color. We then identified eQTL for genes with seed-specific expression and discovered striking eQTL hotspots at distinct genomic intervals on chromo-somes (Chr) 20, 7, and 13. The main eQTL hotspot for transcriptional regulation of fatty acid biosyn-thesis genes also coincided with regulation of oleosin genes. Transcriptional upregulation of genesets from eQTL with opposite allelic effects were also found. Gene-eQTL networks were constructed and candidate regulatory genes were identified from these three key loci specific to seed expression and enriched in genes involved in seed oil accumulation. Our data provides new insight into the complex nature of gene networks in the immature soybean seed and the genetic architecture that contributes to seed development