Evidence for genetic association between chromosome 1q loci and predisposition to colorectal neoplasia.

BACKGROUND: A substantial fraction of familial colorectal cancer (CRC) and polyposis heritability remains unexplained. This study aimed to identify predisposing loci in patients with these disorders. METHODS: Homozygosity mapping was performed using 222 563 SNPs in 302 index patients with various colorectal neoplasms and 3367 controls. Linkage analysis, exome and whole-genome sequencing were performed in a family affected by microsatellite stable CRCs. Candidate variants were genotyped in 10 554 cases and 21 480 controls. Gene expression was assessed at the mRNA and protein level. RESULTS: Homozygosity mapping revealed a disease-associated region at 1q32.3 which was part of the linkage region 1q32.2-42.2 identified in the CRC family. This includes a region previously associated with risk of CRC. Sequencing identified the p.Asp1432Glu variant in the MIA3 gene (known as TANGO1 or TANGO) and 472 additional rare, shared variants within the linkage region. In both cases and controls the population frequency was 0.02% for this MIA3 variant. The MIA3 mutant allele showed predominant mRNA expression in normal, cancer and precancerous tissues. Furthermore, immunohistochemistry revealed increased expression of MIA3 in adenomatous tissues. CONCLUSIONS: Taken together, our two independent strategies associate genetic variations in chromosome 1q loci and predisposition to familial CRC and polyps, which warrants further investigation.

Cost-effective HRMA pre-sequence typing of clone libraries; application to phage display selection.

BACKGROUND: Methodologies like phage display selection, in vitro mutagenesis and the determination of allelic expression differences include steps where large numbers of clones need to be compared and characterised. In the current study we show that high-resolution melt curve analysis (HRMA) is a simple, cost-saving tool to quickly study clonal variation without prior nucleotide sequence knowledge. RESULTS: HRMA results nicely matched those obtained with ELISA and compared favourably to DNA fingerprinting of restriction digested clone insert-PCR. DNA sequence analysis confirmed that HRMA-clustered clones contained identical inserts. CONCLUSION: Using HRMA, analysis of up to 384 samples can be done simultaneously and will take approximately 30 minutes. Clustering of clones can be largely automated using the system's software within 2 hours. Applied to the analysis of clones obtained after phage display antibody selection, HRMA facilitated a quick overview of the overall success as well as the identification of identical clones. Our approach can be used to characterize any clone set prior to sequencing, thereby reducing sequencing costs significantly.

Can subtle changes in gene expression be consistently detected with different microarray platforms?

BACKGROUND: The comparability of gene expression data generated with different microarray platforms is still a matter of concern. Here we address the performance and the overlap in the detection of differentially expressed genes for five different microarray platforms in a challenging biological context where differences in gene expression are few and subtle. RESULTS: Gene expression profiles in the hippocampus of five wild-type and five transgenic deltaC-doublecortin-like kinase mice were evaluated with five microarray platforms: Applied Biosystems, Affymetrix, Agilent, Illumina, LGTC home-spotted arrays. Using a fixed false discovery rate of 10% we detected surprising differences between the number of differentially expressed genes per platform. Four genes were selected by ABI, 130 by Affymetrix, 3,051 by Agilent, 54 by Illumina, and 13 by LGTC. Two genes were found significantly differentially expressed by all platforms and the four genes identified by the ABI platform were found by at least three other platforms. Quantitative RT-PCR analysis confirmed 20 out of 28 of the genes detected by two or more platforms and 8 out of 15 of the genes detected by Agilent only. We observed improved correlations between platforms when ranking the genes based on the significance level than with a fixed statistical cut-off. We demonstrate significant overlap in the affected gene sets identified by the different platforms, although biological processes were represented by only partially overlapping sets of genes. Aberrances in GABA-ergic signalling in the transgenic mice were consistently found by all platforms. CONCLUSION: The different microarray platforms give partially complementary views on biological processes affected. Our data indicate that when analyzing samples with only subtle differences in gene expression the use of two different platforms might be more attractive than increasing the number of replicates. Commercial two-color platforms seem to have higher power for finding differentially expressed genes between groups with small differences in expression.