NORMAL GENOMIC

• Wu H, Wu X, Shen L, Zhang Y
• Single-base resolution analysis of active DNA demethylation using methylase-assisted bisulfite sequencing.
• Nat Biotechnol. 2014; 32: 1231-40
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• Active DNA demethylation in mammals involves TET-mediated iterative oxidation of 5-methylcytosine (5mC)/5-hydroxymethylcytosine (5hmC) and subsequent excision repair of highly oxidized cytosine bases 5-formylcytosine (5fC)/5-carboxylcytosine (5caC) by thymine DNA glycosylase (TDG). However, quantitative and high-resolution analysis of active DNA demethylation activity remains challenging. Here, we describe M.SssI methylase-assisted bisulfite sequencing (MAB-seq), a method that directly maps 5fC/5caC at single-base resolution. Genome-wide MAB-seq allows systematic identification of 5fC/5caC in Tdg-depleted embryonic stem cells, thereby generating a base-resolution map of active DNA demethylome. A comparison of 5fC/5caC and 5hmC distribution maps indicates that catalytic processivity of TET enzymes correlates with local chromatin accessibility. MAB-seq also reveals strong strand asymmetry of active demethylation within palindromic CpGs. Integrating MAB-seq with other base-resolution mapping methods enables quantitative measurement of cytosine modification states at key transitioning steps of the active DNA demethylation cascade and reveals a regulatory role of 5fC/5caC excision repair in this step-wise process.

• Moen EL et al.
• Genome-wide variation of cytosine modifications between European and African populations and the implications for complex traits.
• Genetics. 2013; 194: 987-96
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• Elucidating cytosine modification differences between human populations can enhance our understanding of ethnic specificity in complex traits. In this study, cytosine modification levels in 133 HapMap lymphoblastoid cell lines derived from individuals of European or African ancestry were profiled using the Illumina HumanMethylation450 BeadChip. Approximately 13% of the analyzed CpG sites showed differential modification between the two populations at a false discovery rate of 1%. The CpG sites with greater modification levels in European descent were enriched in the proximal regulatory regions, while those greater in African descent were biased toward gene bodies. More than half of the detected population-specific cytosine modifications could be explained primarily by local genetic variation. In addition, a substantial proportion of local modification quantitative trait loci exhibited population-specific effects, suggesting that genetic epistasis and/or genotype x environment interactions could be common. Distinct correlations were observed between gene expression levels and cytosine modifications in proximal regions and gene bodies, suggesting epigenetic regulation of interindividual expression variation. Furthermore, quantitative trait loci associated with population-specific modifications can be colocalized with expression quantitative trait loci and single nucleotide polymorphisms previously identified for complex traits with known racial disparities. Our findings revealed abundant population-specific cytosine modifications and the underlying genetic basis, as well as the relatively independent contribution of genetic and epigenetic variations to population differences in gene expression.

• Kono H, Sarai A
• Structure-based prediction of DNA target sites by regulatory proteins.
• Proteins. 1999; 35: 114-31
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• Regulatory proteins play a critical role in controlling complex spatial and temporal patterns of gene expression in higher organism, by recognizing multiple DNA sequences and regulating multiple target genes. Increasing amounts of structural data on the protein-DNA complex provides clues for the mechanism of target recognition by regulatory proteins. The analyses of the propensities of base-amino acid interactions observed in those structural data show that there is no one-to-one correspondence in the interaction, but clear preferences exist. On the other hand, the analysis of spatial distribution of amino acids around bases shows that even those amino acids with strong base preference such as Arg with G are distributed in a wide space around bases. Thus, amino acids with many different geometries can form a similar type of interaction with bases. The redundancy and structural flexibility in the interaction suggest that there are no simple rules in the sequence recognition, and its prediction is not straightforward. However, the spatial distributions of amino acids around bases indicate a possibility that the structural data can be used to derive empirical interaction potentials between amino acids and bases. Such information extracted from structural databases has been successfully used to predict amino acid sequences that fold into particular protein structures. We surmised that the structures of protein-DNA complexes could be used to predict DNA target sites for regulatory proteins, because determining DNA sequences that bind to a particular protein structure should be similar to finding amino acid sequences that fold into a particular structure. Here we demonstrate that the structural data can be used to predict DNA target sequences for regulatory proteins. Pairwise potentials that determine the interaction between bases and amino acids were empirically derived from the structural data. These potentials were then used to examine the compatibility between DNA sequences and the protein-DNA complex structure in a combinatorial "threading" procedure. We applied this strategy to the structures of protein-DNA complexes to predict DNA binding sites recognized by regulatory proteins. To test the applicability of this method in target-site prediction, we examined the effects of cognate and noncognate binding, cooperative binding, and DNA deformation on the binding specificity, and predicted binding sites in real promoters and compared with experimental data. These results show that target binding sites for several regulatory proteins are successfully predicted, and our data suggest that this method can serve as a powerful tool for predicting multiple target sites and target genes for regulatory proteins.