D-HaploDB: a database of definitive haplotypes determined by genotyping complete hydatidiform mole samples

Inhibition of AHR transcription by NF1C is affected by a single-nucleotide polymorphism, and is involved in suppression of human uterine endometrial cancer

Involvement of the aryl hydrocarbon receptor (AHR) in carcinogenesis has been suggested in many studies. Upregulation of AHR has been reported in some cancer species, and an association between single-nucleotide polymorphisms (SNPs) of AHR and cancer risk or cancer development has also been reported. This evidence suggests the involvement of some specific SNPs in AHR transcriptional regulation in the process of carcinogenesis or cancer development, but there have been no studies to elucidate the mechanism involved. In this study, we identified the transcription factor Nuclear Factor 1-C (NF1C) as a candidate to regulate AHR transcription in a polymorphism-dependent manner. SNP rs10249788 was included in a consensus binding site for NF1C. Our results suggested that NF1C preferred the C allele to the T allele at rs10249788 for binding. Forced expression of NF1C suppressed the activity of the AHR promoter with C at rs10249788 stronger than that with T. Moreover, expression analysis of human uterine endometrial cancer (HEC) specimens showed greater upregulation of AHR and downregulation of NF1C than those of normal endometrium specimens. Sequence analysis showed HEC patients at advanced stages tended to possess T/T alleles more frequently than healthy women. We also demonstrated that NF1C suppressed proliferation, motility and invasion of HEC cells. This function was at least partially mediated by AHR. This study is the first to report that a polymorphism on the AHR regulatory region affected transcriptional regulation of the AHR gene in vitro. Because NF1C is a tumor suppressor, our new insights into AHR deregulation and its polymorphisms could reveal novel mechanisms of genetic susceptibility to cancer.

ParaHaplo: A program package for haplotype-based whole-genome association study using parallel computing

Background

Since more than a million single-nucleotide polymorphisms (SNPs) are analyzed in any given genome-wide association study (GWAS), performing multiple comparisons can be problematic. To cope with multiple-comparison problems in GWAS, haplotype-based algorithms were developed to correct for multiple comparisons at multiple SNP loci in linkage disequilibrium. A permutation test can also control problems inherent in multiple testing; however, both the calculation of exact probability and the execution of permutation tests are time-consuming. Faster methods for calculating exact probabilities and executing permutation tests are required.

Methods

We developed a set of computer programs for the parallel computation of accurate P-values in haplotype-based GWAS. Our program, ParaHaplo, is intended for workstation clusters using the Intel Message Passing Interface (MPI). We compared the performance of our algorithm to that of the regular permutation test on JPT and CHB of HapMap.

Results

ParaHaplo can detect smaller differences between 2 populations than SNP-based GWAS. We also found that parallel-computing techniques made ParaHaplo 100-fold faster than a non-parallel version of the program.

Conclusion

ParaHaplo is a useful tool in conducting haplotype-based GWAS. Since the data sizes of such projects continue to increase, the use of fast computations with parallel computing--such as that used in ParaHaplo--will become increasingly important. The executable binaries and program sources of ParaHaplo are available at the following address:

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.

VarySysDB: a human genetic polymorphism database based on all H-InvDB transcripts

Creation of a vast variety of proteins is accomplished by genetic variation and a variety of alternative splicing transcripts. Currently, however, the abundant available data on genetic variation and the transcriptome are stored independently and in a dispersed fashion. In order to provide a research resource regarding the effects of human genetic polymorphism on various transcripts, we developed VarySysDB, a genetic polymorphism database based on 187,156 extensively annotated matured mRNA transcripts from 36,073 loci provided by H-InvDB. VarySysDB offers information encompassing published human genetic polymorphisms for each of these transcripts separately. This allows comparisons of effects derived from a polymorphism on different transcripts. The published information we analyzed includes single nucleotide polymorphisms and deletion-insertion polymorphisms from dbSNP, copy number variations from Database of Genomic Variants, short tandem repeats and single amino acid repeats from H-InvDB and linkage disequilibrium regions from D-HaploDB. The information can be searched and retrieved by features, functions and effects of polymorphisms, as well as by keywords. VarySysDB combines two kinds of viewers, GBrowse and Sequence View, to facilitate understanding of the positional relationship among polymorphisms, genome, transcripts, loci and functional domains. We expect that VarySysDB will yield useful information on polymorphisms affecting gene expression and phenotypes. VarySysDB is available at http://h-invitational.jp/varygene/.