Evaluation of Haplotype Inference Using Definitive Haplotype Data Obtained from Complete Hydatidiform Moles, and Its Significance for the Analyses of Positively Selected Regions

The haplotype map constructed by the HapMap Project is a valuable resource in the genetic studies of disease genes, population structure, and evolution. In the Project, Caucasian and African haplotypes are fairly accurately inferred, based mainly on the rules of Mendelian inheritance using the genotypes of trios. However, the Asian haplotypes are inferred from the genotypes of unrelated individuals based on population genetics, and are less accurate. Thus, the effects of this inaccuracy on downstream analyses needs to be assessed. We determined true Japanese haplotypes by genotyping 100 complete hydatidiform moles (CHM), each carrying a genome derived from a single sperm, using Affymetrix 500 K Arrays. We then assessed how inferred haplotypes can differ from true haplotypes, by phasing pseudo-individualized true haplotypes using the programs PHASE, fastPHASE, and Beagle. We found that, at various genomic regions, especially the MHC locus, the expansion of extended haplotype homozygosity (EHH), which is a measure of positive selection, is obscured when inferred Asian haplotype data is used to detect the expansion. We then mapped the genome using a new statistic, XDiHH, which directly detects the difference between the true and inferred haplotypes, in the determination of EHH expansion. We also show that the true haplotype data presented here is useful to assess and improve the accuracy of phasing of Asian genotypes

Conversion of a molecular classifier obtained by gene expression profiling into a classifier based on real-time PCR: a prognosis predictor for gliomas

<p>Abstract</p> <p>Background</p> <p>The advent of gene expression profiling was expected to dramatically improve cancer diagnosis. However, despite intensive efforts and several successful examples, the development of profile-based diagnostic systems remains a difficult task. In the present work, we established a method to convert molecular classifiers based on adaptor-tagged competitive PCR (ATAC-PCR) (with a data format that is similar to that of microarrays) into classifiers based on real-time PCR.</p> <p>Methods</p> <p>Previously, we constructed a prognosis predictor for glioma using gene expression data obtained by ATAC-PCR, a high-throughput reverse-transcription PCR technique. The analysis of gene expression data obtained by ATAC-PCR is similar to the analysis of data from two-colour microarrays. The prognosis predictor was a linear classifier based on the first principal component (PC1) score, a weighted summation of the expression values of 58 genes. In the present study, we employed the delta-delta Ct method for measurement by real-time PCR. The predictor was converted to a Ct value-based predictor using linear regression.</p> <p>Results</p> <p>We selected <it>UBL5 </it>as the reference gene from the group of genes with expression patterns that were most similar to the median expression level from the previous profiling study. The number of diagnostic genes was reduced to 27 without affecting the performance of the prognosis predictor. PC1 scores calculated from the data obtained by real-time PCR showed a high linear correlation (r = 0.94) with those obtained by ATAC-PCR. The correlation for individual gene expression patterns (r = 0.43 to 0.91) was smaller than for PC1 scores, suggesting that errors of measurement were likely cancelled out during the weighted summation of the expression values. The classification of a test set (n = 36) by the new predictor was more accurate than histopathological diagnosis (log rank p-values, 0.023 and 0.137, respectively) for predicting prognosis.</p> <p>Conclusion</p> <p>We successfully converted a molecular classifier obtained by ATAC-PCR into a Ct value-based predictor. Our conversion procedure should also be applicable to linear classifiers obtained from microarray data. Because errors in measurement are likely to be cancelled out during the calculation, the conversion of individual gene expression is not an appropriate procedure. The predictor for gliomas is still in the preliminary stages of development and needs analytical clinical validation and clinical utility studies.</p

Quantitative detection of ALK fusion breakpoints in plasma cell-free DNA from patients with non-small cell lung cancer using PCR-based target sequencing with a tiling primer set and two-step mapping/alignment.

BackgroundTyrosine kinase inhibitors targeted to anaplastic lymphoma kinase (ALK) have been demonstrated to be effective for lung cancer patients with an ALK fusion gene. Application of liquid biopsy, i.e., detection and quantitation of the fusion product in plasma cell-free DNA (cfDNA), could improve clinical practice. To detect ALK fusions, because fusion breakpoints occur somewhere in intron 19 of the ALK gene, sequencing of the entire intron is required to locate breakpoints.ResultsWe constructed a target sequencing system using an adapter and a set of primers that cover the entire ALK intron 19. This system can amplify fragments, including breakpoints, regardless of fusion partners. The data analysis pipeline firstly detected fusions by alignment to selected target sequences, and then quantitated the fusion alleles aligning to the identified breakpoint sequences. Performance was validated using 20 cfDNA samples from ALK-positive non-small cell lung cancer patients and samples from 10 healthy volunteers. Sensitivity and specificity were 50 and 100%, respectively.ConclusionsWe demonstrated that PCR-based target sequencing using a tiling primer set and two-step mapping/alignment quantitatively detected ALK fusions in cfDNA from lung cancer patients. The system offers an alternative to existing approaches based on hybridization capture

Additional file 5: Figure S3. of HLA genotyping by next-generation sequencing of complementary DNA

Primers for measuring single-strand products by Real-time PCR. (PPT 139 kb

Additional file 1: Table S1. of HLA genotyping by next-generation sequencing of complementary DNA

The sequence of the primers for HLA typing system 01. (XLS 30 kb

Additional file 4: Figure S2. of HLA genotyping by next-generation sequencing of complementary DNA

Calculation of the OL (Overlapped Length) between sequences of “Haplotype candidates” and “HLA cDNA database”. (PPT 174 kb

Additional file 3: Table S2. of HLA genotyping by next-generation sequencing of complementary DNA

Comparison of the performance of automatic HLA typing. (XLS 28 kb