The differences among the vertebrate β isotypes of tubulin are highly conserved in evolution, suggesting that they have functional significance. To address this, we have used differentiating neuroblastoma cells as a model system. These cells express the βI, βII, and βIII isotypes. Although there is no difference prior to differentiation, a striking difference is seen after differentiation. Both βI and βIII occur in cell bodies and neurites, while βII occurs mostly in neurites. Knocking down βI causes a large decrease in cell viability while silencing βII and βIII does not. Knocking down βII causes a large decrease in neurite outgrowth without affecting viability. Knocking down βIII has little effect on neurite outgrowth and only decreases viability if cells are treated with glutamate and glycine, a combination known to generate free radicals and reactive oxygen species. It appears, therefore, that βI is required for cell viability, βII for neurite outgrowth and βIII for protection against free radicals and reactive oxygen species.

A large proportion of protein-protein interactions is mediated by families of peptide-binding domains. Comprehensive characterization of each of these domains is critical for understanding the mechanisms and networks of protein interaction at the domain level. However, existing methods are all based on large scale screenings for each domain that are inefficient to deal with hundreds of members in major domain families. We developed a systematic strategy for efficient binding property characterization of peptide-binding domains based on high throughput validation screening of a specialized candidate ligand library using yeast two-hybrid mating array. Its outstanding feature is that the overall efficiency is dramatically improved compared with that of traditional screening, and it will be higher as the system cycles. PDZ domain family was first used to test the strategy. Five PDZ domains were rapidly characterized. Broader binding properties were identified compared with other methods, including novel recognition specificities that provided the basis for major revision of conventional PDZ classification. Several novel interactions were discovered, serving as significant clues for further functional investigation. This strategy can be easily extended to a variety of peptide-binding domains as a powerful tool for comprehensive analysis of domain binding property in proteomic scale. Molecular & Cellular Proteomics 5:1368 -1381, 2006.

BackgroundGossypium barbadense (Sea Island, Egyptian or Pima cotton) cotton has high fiber quality, however, few studies have investigated the genetic basis of its traits using molecular markers. Genome complexity reduction approaches such as genotyping-by-sequencing have been utilized to develop abundant markers for the construction of high-density genetic maps to locate quantitative trait loci (QTLs).ResultsThe Chinese G. barbadense cultivar 5917 and American Pima S-7 were used to develop a recombinant inbred line (RIL) population with 143 lines. The 143 RILs together with their parents were tested in three replicated field tests for lint yield traits (boll weight and lint percentage) and fiber quality traits (fiber length, fiber elongation, fiber strength, fiber uniformity and micronaire) and then genotyped using GBS to develop single-nucleotide polymorphism (SNP) markers. A high-density genetic map with 26 linkage groups (LGs) was constructed using 3557 GBS SNPs spanning a total genetic distance of 3076.23 cM at an average density of 1.09 cM between adjacent markers. A total of 42 QTLs were identified, including 24 QTLs on 12 LGs for fiber quality and 18 QTLs on 7 LGs for lint yield traits, with LG1 (9 QTLs), LG10 (7 QTLs) and LG14 (6 QTLs) carrying more QTLs. Common QTLs for the same traits and overlapping QTLs for different traits were detected. Each individual QTLs explained 0.97 to 20.7% of the phenotypic variation.ConclusionsThis study represents one of the first genetic mapping studies on the fiber quality and lint yield traits in a RIL population of G. barbadense using GBS-SNPs. The results provide important information for the subsequent fine mapping of QTLs and the prediction of candidate genes towards map-based cloning and marker-assisted selection in cotton.

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