A dose-dependent requirement for the proline motif of CD28 in cellular and humoral immunity revealed by a targeted knockin mutant

Activation of naive T cells requires the integration of signals through the antigen receptor and CD28. Although there is agreement on the importance of CD28, there remains controversy on the mechanism by which CD28 regulates T cell function. We have generated a gene-targeted knockin mouse expressing a mutation in the C-terminal proline-rich region of the cytoplasmic tail of CD28. Our analysis conclusively showed that this motif is essential for CD28-dependent regulation of interleukin 2 secretion and proliferation. In vivo analysis revealed that mutation of this motif-dissociated CD28-dependent regulation of cellular and humoral responses in an allergic airway inflammation model. Furthermore, we find an important gene dosage effect on the phenotype of the mutation and provide a mechanistic explanation for the conflicting data on the significance of this motif in CD28 function

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology

BACKGROUND: The arrival of RNA-seq as a high-throughput method competitive to the established microarray technologies has necessarily driven a need for comparative evaluation. To date, cross-platform comparisons of these technologies have been relatively few in number of platforms analyzed and were typically gene name annotation oriented. Here, we present a more extensive and yet precise assessment to elucidate differences and similarities in performance of numerous aspects including dynamic range, fidelity of raw signal and fold-change with sample titration, and concordance with qRT-PCR (TaqMan). To ensure that these results were not confounded by incompatible comparisons, we introduce the concept of probe mapping directed “transcript pattern”. A transcript pattern identifies probe(set)s across platforms that target a common set of transcripts for a specific gene. Thus, three levels of data were examined: entire data sets, data derived from a subset of 15,442 RefSeq genes common across platforms, and data derived from the transcript pattern defined subset of 7,034 RefSeq genes. RESULTS: In general, there were substantial core similarities between all 6 platforms evaluated; but, to varying degrees, the two RNA-seq protocols outperformed three of the four microarray platforms in most categories. Notably, a fourth microarray platform, Agilent with a modified protocol, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments, especially in regards to fold-change evaluation. Furthermore, these 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80 % fold-change concordance with the gold standard qRT-PCR (TaqMan). CONCLUSIONS: This study suggests that microarrays can perform on nearly equal footing with RNA-seq, in certain key features, specifically when the dynamic range is comparable. Furthermore, the concept of a transcript pattern has been introduced that may minimize potential confounding factors of multi-platform comparison and may be useful for similar evaluations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1913-6) contains supplementary material, which is available to authorized users