Based on a statistical model, we show that even in technical replicate tests using identical samples, it is highly likely that the selected DEG lists will be very inconsistent in the presence of small measurement variations. Therefore, the apparently low reproducibility of DEG detection from current technical replicate tests does not indicate low quality of microarray technology. We also demonstrate that heterogeneous biological variations existing in real cancer data will further reduce the overall reproducibility of DEG detection. Nevertheless, in small subsamples from both simulated and real data, the actual false discovery rate (FDR) for each DEG list tends to be low, suggesting that each separately determined list may comprise mostly true DEGs. Rather than simply counting the overlaps of the discovery lists from different studies for a complex disease, novel metrics are needed for evaluating the reproducibility of discoveries characterized with correlated molecular changes. Supplementaty information: Supplementary data are available at Bioinformatics online.

p73, a p53 family protein, shares significant sequence homolog and functional similarity with p53. However, unlike p53, p73 has at least seven alternatively spliced isoforms with different carboxyl termini (p73␣-). Moreover, the p73 gene can be transcribed from a cryptic promoter located in intron 3, producing seven more proteins (⌬Np73␣-). ⌬Np73, which does not contain the N-terminal activation domain in p73, has been thought to be transcriptionally inactive and dominant negative over p53 or p73. To systemically analyze the activity of the ⌬N variant, we generated stable cell lines, which inducibly express ⌬Np73␣, ⌬Np73␤, and various ⌬Np73␤ mutants by using the tetracycline-inducible expression system. Surprisingly, we found that ⌬Np73␤ is indeed active in inducing cell cycle arrest and apoptosis. Importantly, we found that, when ⌬Np73␤ is expressed at a physiologically relevant level, it is capable of suppressing cell growth. We then demonstrated that these ⌬Np73␤ activities are not cell type specific. We showed that the 13 unique residues at the N terminus are required for ⌬Np73␤ to suppress cell growth. We also found that, among the 13 residues, residues 6 to 10 are critical to ⌬Np73␤ function. Furthermore, we found that ⌬Np73␤ is capable of inducing some p53 target genes, albeit to a lesser extent than does p73␤. Finally, we found that the 13 unique residues, together with the N-terminal PXXP motifs, constitute a novel activation domain. Like ⌬Np73␤, ⌬Np73␥ is active in transactivation. However, unlike ⌬Np73␤, ⌬Np73␣ is inactive in suppressing cell growth. Our data, together with others' previous findings, suggest that ⌬Np73␤ may have distinct functions under certain cellular circumstances.p73, along with p53 and p63, constitutes the p53 family. p73 shares 63% identity in amino acids with p53 in the DNAbinding domain, including all the DNA contact residues, 38% identity in the tetramerization domain, and 29% identity in the transactivation domain (31,37,55). In contrast to the human p53 gene, which is found to only encode one protein, human TP73 produces at least seven alternatively spliced isoforms with different carboxyl termini (p73␣-), termed the TA variant (10,28,38,53). For example, p73␣ is the longest form of the p73 protein, which contains a sterile ␣ motif (SAM domain) and an extreme C-terminal region, whereas p73␤ is a smaller polypeptide, missing the extreme C-terminal region and most of the SAM domain in p73␣ (8,29,31,50). In addition to the alternative splicing in the C terminus, TP73 is also transcribed from a cryptic promoter located in intron 3, which gives rise to at least another seven isoforms (⌬Np73␣-), termed the ⌬N variant (28,55,56,58). The ⌬N variant does not contain the activation domain in p73 due to lack of sequences encoded by exon 2 (45, 56). However, the ⌬N variant acquires 13 unique residues at the N terminus compared with the TA variant (45, 56). Similar to TP73, TP63 encodes both .In addition to the significant sequence homology, p53 and p73 share a lot of functional similar...

Motivation: According to current consistency metrics such as percentage of overlapping genes (POG), lists of differentially expressed genes (DEGs) detected from different microarray studies for a complex disease are often highly inconsistent. This irreproducibility problem also exists in other high-throughput post-genomic areas such as proteomics and metabolism. A complex disease is often characterized with many coordinated molecular changes, which should be considered when evaluating the reproducibility of discovery lists from different studies.Results: We proposed metrics percentage of overlapping genes-related (POGR) and normalized POGR (nPOGR) to evaluate the consistency between two DEG lists for a complex disease, considering correlated molecular changes rather than only counting gene overlaps between the lists. Based on microarray datasets of three diseases, we showed that though the POG scores for DEG lists from different studies for each disease are extremely low, the POGR and nPOGR scores can be rather high, suggesting that the apparently inconsistent DEG lists may be highly reproducible in the sense that they are actually significantly correlated. Observing different discovery results for a disease by the POGR and nPOGR scores will obviously reduce the uncertainty of the microarray studies. The proposed metrics could also be applicable in many other high-throughput post-genomic areas.Contact: guoz@ems.hrbmu.edu.cnSupplementary information: Supplementary data are available at Bioinformatics online.