B7‐H3 belongs to the B7 superfamily, a group of molecules that costimulate or down‐modulate T‐cell responses. Although it was shown that B7‐H3 could inhibit T‐cell responses, several studies – most of them performed in murine systems – found B7‐H3 to act in a costimulatory manner. In this study, we have specifically addressed a potential functional dualism of human B7‐H3 by assessing the effect of this molecule under varying experimental conditions as well as on different T‐cell subsets. We show that B7‐H3 does not costimulate human T cells. In the presence of strong activating signals, B7‐H3 potently and consistently down‐modulated human T‐cell responses. This inhibitory effect was evident when analysing proliferation and cytokine production and affected naïve as well as pre‐activated T cells. Furthermore, we demonstrate that B7‐H3–T‐cell interaction is characterised by an early suppression of IL‐2 and that T‐cell inhibition can be reverted by exogenous IL‐2. Since the triggering receptor expressed on myeloid cells like transcript 2 (TREML2/TLT‐2) has been recently described as costimulatory receptor of murine B7‐H3 we have extensively analysed interaction of human B7‐H3 with TREML2/TLT‐2. In these experiments we found no evidence for such an interaction. Furthermore, our data do not point to a role for murine TREML2 as a receptor for murine B7‐H3.

Summary: Arabidopsis thaliana is a host for the sugar beet cyst nematode Heterodera schachtii. Juvenile nematodes invade the roots and induce the development of a syncytium, which functions as a feeding site for the nematode. Here, we report on the transcriptome of syncytia induced in the roots of Arabidopsis. Microaspiration was employed to harvest pure syncytium material, which was then used to prepare RNA for hybridization to Affymetrix GeneChips. Initial data analysis showed that the gene expression in syncytia at 5 and 15 days post‐infection did not differ greatly, and so both time points were compared together with control roots. Out of a total of 21 138 genes, 18.4% (3893) had a higher expression level and 15.8% (3338) had a lower expression level in syncytia, as compared with control roots, using a multiple‐testing corrected false discovery rate of below 5%. A gene ontology (GO) analysis of up‐ and downregulated genes showed that categories related to high metabolic activity were preferentially upregulated. A principal component analysis was applied to compare the transcriptome of syncytia with the transcriptome of different Arabidopsis organs (obtained by the AtGenExpress project), and with specific root tissues. This analysis revealed that syncytia are transcriptionally clearly different from roots (and all other organs), as well as from other root tissues.

Li et al. identify the top-performing methods to improve cross-site differential gene expression analysis with RNA-seq. High-throughput RNA sequencing (RNA-seq) enables comprehensive scans of entire transcriptomes, but best practices for analyzing RNA-seq data have not been fully defined, particularly for data collected with multiple sequencing platforms or at multiple sites. Here we used standardized RNA samples with built-in controls to examine sources of error in large-scale RNA-seq studies and their impact on the detection of differentially expressed genes (DEGs). Analysis of variations in guanine-cytosine content, gene coverage, sequencing error rate and insert size allowed identification of decreased reproducibility across sites. Moreover, commonly used methods for normalization (cqn, EDASeq, RUV2, sva, PEER) varied in their ability to remove these systematic biases, depending on sample complexity and initial data quality. Normalization methods that combine data from genes across sites are strongly recommended to identify and remove site-specific effects and can substantially improve RNA-seq studies.