Person:

Liu, Jun

Altered activity of the human dopamine transporter gene (hDAT) is asssociated with several common and severe brain disorders including cocaine abuse. However, there is little a priori information on whether such alteration was due to nature (genetic variantion) or nurture (human behaviors such as cocaine abuse). This study investigated the correlation between seven markers throughout hDAT and its mRNA levels in postmortem ventral midbrain tissues from 18 cocaine abusers and 18 strictly matched drug-free controls in the African American population. Here we show that one major haplotype with same frequency in cocaine abusers versus drug-free controls displays a 37.1%-reduction of expression levels in cocaine abusers, compared to matched controls (P = 0.0057). The most studied genetic marker, variable number tandem repeats (VNTR) located in Exon 15 (3′VNTR), is not correlated with hDAT mRNA levels. A 5′ upstream VNTR (rs70957367) has repeat numbers positively correlated with expression levels in controls (r2 0.9536, P = 0.0235) but this positive correlation disappears in cocaine abusers. The findings suggest that varying hDAT activity is attributed to both genetics and cocaine abuse.

Background: We recently showed that enzymes of the TET family convert 5-mC to 5-hydroxymethylcytosine (5-hmC) in DNA. 5-hmC is present at high levels in embryonic stem cells and Purkinje neurons. The methylation status of cytosines is typically assessed by reaction with sodium bisulfite followed by PCR amplification. Reaction with sodium bisulfite promotes cytosine deamination, whereas 5-methylcytosine (5-mC) reacts poorly with bisulfite and is resistant to deamination. Since 5-hmC reacts with bisulfite to yield cytosine 5-methylenesulfonate (CMS), we asked how DNA containing 5-hmC behaves in bisulfite sequencing. Methodology/Principal Findings: We used synthetic oligonucleotides with different distributions of cytosine as templates for generation of DNAs containing C, 5-mC and 5-hmC. The resulting DNAs were subjected in parallel to bisulfite treatment, followed by exposure to conditions promoting cytosine deamination. The extent of conversion of 5-hmC to CMS was estimated to be 99.7%. Sequencing of PCR products showed that neither 5-mC nor 5-hmC undergo C-to-T transitions after bisulfite treatment, confirming that these two modified cytosine species are indistinguishable by the bisulfite technique. DNA in which CMS constituted a large fraction of all bases (28/201) was much less efficiently amplified than DNA in which those bases were 5-mC or uracil (the latter produced by cytosine deamination). Using a series of primer extension experiments, we traced the inefficient amplification of CMS-containing DNA to stalling of Taq polymerase at sites of CMS modification, especially when two CMS bases were either adjacent to one another or separated by 1–2 nucleotides.Conclusions We have confirmed that the widely used bisulfite sequencing technique does not distinguish between 5-mC and 5-hmC. Moreover, we show that CMS, the product of bisulfite conversion of 5-hmC, tends to stall DNA polymerases during PCR, suggesting that densely hydroxymethylated regions of DNA may be underrepresented in quantitative methylation analyses.

Studies of the relationship between DNA variation and gene expression variation, often referred to as “expression quantitative trait loci (eQTL) mapping”, have been conducted in many species and resulted in many significant findings. Because of the large number of genes and genetic markers in such analyses, it is extremely challenging to discover how a small number of eQTLs interact with each other to affect mRNA expression levels for a set of co-regulated genes. We present a Bayesian method to facilitate the task, in which co-expressed genes mapped to a common set of markers are treated as a module characterized by latent indicator variables. A Markov chain Monte Carlo algorithm is designed to search simultaneously for the module genes and their linked markers. We show by simulations that this method is more powerful for detecting true eQTLs and their target genes than traditional QTL mapping methods. We applied the procedure to a data set consisting of gene expression and genotypes for 112 segregants of S. cerevisiae. Our method identified modules containing genes mapped to previously reported eQTL hot spots, and dissected these large eQTL hot spots into several modules corresponding to possibly different biological functions or primary and secondary responses to regulatory perturbations. In addition, we identified nine modules associated with pairs of eQTLs, of which two have been previously reported. We demonstrated that one of the novel modules containing many daughter-cell expressed genes is regulated by AMN1 and BPH1. In conclusion, the Bayesian partition method which simultaneously considers all traits and all markers is more powerful for detecting both pleiotropic and epistatic effects based on both simulated and empirical data.