Welcome to the Genomics for Kidney Transplantation Project. The Project was established in 2004 under a National Institute of Allergy and Infectious Diseases Program Project Grant. The aim of the Transplant Genomics Collaborative Group is to apply the developing technologies for gene expression profiling (Project 1), proteomics (Project 2) and complex trait genetics (Project 3) to advance our understanding of kidney transplantation in the context of both its clinical problems and the basic biology of transplantation. Our view is that this "systems biology" approach will be valuable in the advancement of the understanding of problems associated with kidney transplantation. These efforts are supported by a group of collaborators with expertise in all three scientific areas, as well as expertise in clinical kidney transplantation and bioinformatics and statistics.

The data we will generate will be of two types: diagnostic and discovery. The diagnostic component will consist of potentially complex gene and protein expression signatures that will have statistically valid correlations to specific clinical events like acute rejection, chronic allograft nephropathy, and long term well-functioning transplants with no rejection. The discovery component will consist of identifying, within these complex genomic signatures, specific gene candidates that correlate with transplant events and outcomes. Our hypotheses are: 1) that gene and protein expression signatures can be identified in PBL and kidney transplant biopsies that correlate with biopsy-proven acute rejection and chronic allograft nephropathy, 2) that gene and protein expression profiles provide insights into the molecular pathways involved in both the host immune response and the donor organ's response to transplantation, and 3) that the adequacy of immunosuppression, as defined by the absence of rejection-related gene and protein expression, can be determined by the gene and protein expression profiles.

We also propose to examine the possibility that race and sex will influence at least a subset of gene transcripts and proteins expressed post transplant, and correlate with outcomes. The first objective of this application will be to integrate data on gene expression profiling in parallel with data generated by proteomics (Project 2) and complex trait genetics (Project 3) to advance a more comprehensive understanding of the molecular basis of clinical kidney transplantation. The second is to establish the requisite proof of principle to design a prospective clinical trial to test the hypothesis that PBL profiles can be used to monitor the efficacy of immunosuppression in 'real-time'.

If you are interested in learning more about the Transplant Genomics Collaborative Group, please contact us at info-tgcg@genetics.ucla.edu.

• Weighted Gene Co-Expression Network Analysis Software - WGCNA is a user-friendly systems biologic microarray analysis software for finding important genes and pathways. Visit the WGCNA site to download the software and manual, and for more information.
  
  
• Software for differential MicroRNA and mRNA Analysis - MiRMiner is a software package that searches for significant miRNAs (or mRNAs) based on predefined database of base pair matches between miRNAs and mRNAs. It provides hit counts for a input list of miRNAs (or mRNAs) and lists all the detailed hits between each miRNA/mRNA pair as well. Visit the MiRMiner site to download the software and manual, and for more information.