No abstract

Tetraspanins (TETs) function as key molecular scaffolds for surface signal recognition and transduction via the assembly of tetraspanin-enriched microdomains. TETs’ function in mammalian has been intensively investigated for the organization of multimolecular membrane complexes, regulation of cell migration and cellular adhesion, whereas plant TET studies lag far behind. Animal and plant TETs share similar topologies, despite the hallmark of “CCG” in the large extracellular loop of animal TETs, plant TETs contain a plant specific GCCK/RP motif and more conserved cysteine residues. Here, we showed that the GCCK/RP motif is responsible for TET protein association with the plasma membrane. Moreover, the conserved cysteine residues located within or neighboring the GCCK/RP motif are both crucial for TET anchoring to membrane. During virus infection, the intact TET3 protein enhanced but GCCK/RP motif or cysteine residues-deficient TET3 variants abolished the cell-to-cell movement capability of virus. This study provides cellular evidence that the GCCK/RP motif and the conserved cysteine residues are the primary determinants for the distribution and function of TET proteins in Arabidopsis.

No abstract

Clustering has been widely conducted in the analysis of gene expression data. For complex diseases, it has played an important role in identifying unknown functions of genes, serving as the basis of other analysis, and others. A common limitation of most existing clustering approaches is to assume that genes are separated into disjoint clusters. As genes often have multiple functions and thus can belong to more than one functional cluster, the disjoint clustering results can be unsatisfactory. In addition, due to the small sample sizes of genetic profiling studies and other factors, there may not be sufficient evidence to confirm the specific functions of some genes and cluster them definitively into disjoint clusters. In this study, we develop an effective overlapping clustering approach, which takes account into the multiplicity of gene functions and lack of certainty in practical analysis. A penalized weighted normalized cut (PWNCut) criterion is proposed based on the NCut technique and an L2 norm constraint. It outperforms multiple competitors in simulation. The analysis of TCGA data on breast cancer and cervical cancer leads to biologically sensible findings which differ from those using the alternatives. To facilitate implementation, we develop the function pwncut in the R package NCutYX.