The diagnosis of rejection in kidney transplant patients is based on histologic classification of a graft biopsy. The current “gold standard” is the Banff 97 criteria; however, there are several limitations in classifying rejection based on biopsy samples. First, a biopsy involves an invasive procedure. Second, there is significant variance among blinded pathologists in the interpretation of a biopsy. And third, there is also variance between the histology and the molecular profiles of a biopsy. To increase the positive predictive value of classifiers of rejection, a Banff committee is developing criteria that integrate histologic and molecular data into a unified classifier that could diagnose and prognose rejection. To develop the most appropriate molecular criteria, there have been studies by multiple groups applying omics technologies in attempts to identify biomarkers of rejection. In this review, we discuss studies using genome-wide data sets of the transcriptome and proteome to investigate acute rejection, chronic allograft dysfunction, and tolerance. We also discuss studies which focus on genetic biomarkers in urine and peripheral blood, which will provide clinicians with minimally invasive methods for monitoring transplant patients. We also discuss emerging technologies, including whole-exome sequencing and RNA-Seq and new bioinformatic and systems biology approaches, which should increase the ability to develop both biomarkers and mechanistic understanding of the rejection process.
Checkpoint gene function prevents meiotic progression when recombination is blocked by mutations in the recA homologue DMC1. Bypass of dmc1 arrest by mutation of the DNA damage checkpoint genes MEC1, RAD17, or RAD24 results in a dramatic loss of spore viability, suggesting that these genes play an important role in monitoring the progression of recombination. We show here that the role of mitotic checkpoint genes in meiosis is not limited to maintaining arrest in abnormal meioses; mec1-1, rad24, and rad17 single mutants have additional meiotic defects. All three mutants display Zip1 polycomplexes in two- to threefold more nuclei than observed in wild-type controls, suggesting that synapsis may be aberrant. Additionally, all three mutants exhibit elevated levels of ectopic recombination in a novel physical assay. rad17 mutants also alter the fraction of recombination events that are accompanied by an exchange of flanking markers. Crossovers are associated with up to 90% of recombination events for one pair of alleles in rad17, as compared with 65% in wild type. Meiotic progression is not required to allow ectopic recombination in rad17 mutants, as it still occurs at elevated levels in ndt80 mutants that arrest in prophase regardless of checkpoint signaling. These observations support the suggestion that MEC1, RAD17, and RAD24, in addition to their proposed monitoring function, act to promote normal meiotic recombination.
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