Peter Adorjan

Differences in DNA methylation patterns between humans and chimpanzees

Methylation at CpG dinucleotides is important for gene regulation in mammals [1]. However, it is unknown how methylation patterns change during evolution. Here, we compare methylation patterns between humans and chimpanzees at 36 genes in the brain, the liver and in lymphocytes. We find that the extent of the change in methylation pattern is much more extensive in the brain than in the other tissues. Furthermore, of the 15 CpGs that have significantly changed methylation in the brain, 14 are more methylated in humans than in chimpanzees. This indicates that CpGs might generally be more methylated in human brains than in chimpanzee brains. Despite considerable phenotypic differences, humans and their closest living relatives, the chimpanzees, are on average 98.8% identical in their alignable genomic DNA sequences [2,3]. It is currently unknown which genotypic differences are responsible for the phenotypic differences. One possibility to tackle this question is to compare gene expression patterns between humans and chimpanzees using functional genomic approaches [4–6]. In this respect, it may also be useful to compare methylation patterns in regulatory DNA sequences, as the methylation status can be viewed as a “footprint” of the chromatin structures that are crucial for gene regulation [7,8]. In order to take a first step toward understanding the evolution of methylation patterns, we compared the methylation status of 145 CpGs in the presumed regulatory regions of 36 different genes between humans and chimpanzees in brain, liver and lymphocytes using a recently developed array technique [9–11]. Thereby, genomic DNA is treated with sodium bisulphite such that unmethylated CpGs are amplified as TpGs in the following PCR. For each CpG examined, the arrays contain two oligonucleotides: one complementary to a TpG, resembling a formerly unmethylated CpG and one complementary to a CpG, resembling a formerly methylated CpG. We identified 22 CpGs in which the ratio of the intensities of these two oligonucleotides differed significantly between human and chimpanzee in at least one tissue. By contrast, zero to three differences would be expected due to random experimental and biological variation, as is shown by permutating the species labels for each tissue (see supplemental data for all methodological details). Therefore, the differences between the two species are highly significant, whereas the differences between the individuals of the same species are within the range of the experimental error (data not shown). We also do not observe a strong correlation of methylation levels with age or time post mortem (see supplemental data), Thus, we conclude that most of the observed methylation differences between humans and chimpanzees are neither due to random measurement errors nor due to random or systematic differences in their environment. To exclude trivial genetic causes, we sequenced the region of the 22 CpG sites in the chimpanzee and excluded 4 CpGs that carried a sequence difference between the chimpanzee sequence and the human-based oligonucleotide sequence. The remaining 18 CpGs from 12 genes are shown in Figure 1. Three observations from these experiments are especially noteworthy: First, despite the limited number of CpGs studied, several significant differences in their methylation status can be found between humans and chimpanzees. Second, out of 18 differences, 15 are found between chimpanzee and human brain, whereas only six are found between the other two tissues. Third, 14 of the 15 sites differing in methylation in the brain show a higher degree of methylation in humans. The first observation indicates that — at least in humans and chimpanzees — the methylation status of many CpG sites changes during the course of evolution. The second observation indicates that more CpG sites have changed their methylation status in the brain than in liver or lymphocytes. Notably, DNA methylation seems to be especially important for the brain, as defects in methylation lead to mental retardation in humans [8] and a mouse model for one of these diseases — Rett syndrome — indicates that the symptoms can be caused solely by a defect in postmitotic neurons [12,13]. Our third observation, namely that 14 of 15 CpG sites differently methylated in the brain show a higher degree of methylation in humans, might reflect a general up-methylation of genes in the human brain, rather than several independent, gene-specific methylation changes. Although it is unclear at this point whether this up-methylation directly translates into observable changes in gene expression (supplemental data), it is tempting to speculate that such an upmethylation was important for the evolution of the human brain. However, we cannot exclude that a general tendency towards a lower degree of methylation occurred on the chimpanzee lineage. It is furthermore unclear if the change in methylation patterns is especially pronounced in the human brain or if a rapid change in methylation patterns is typical of brain evolution in many mammals. Further work has to clarify these issues.

Identification and Validation of Colorectal Neoplasia–Specific Methylation Markers for Accurate Classification of Disease

Aberrant DNA methylation occurs early in oncogenesis, is stable, and can be assayed in tissues and body fluids. Therefore, genes with aberrant methylation can provide clues for understanding tumor pathways and are attractive candidates for detection of early neoplastic events. Identification of sequences that optimally discriminate cancer from other diseased and healthy tissues is needed to advance both approaches. Using well-characterized specimens, genome-wide methylation techniques were used to identify candidate markers specific for colorectal neoplasia. To further validate 30 of these candidates from genome-wide analysis and 13 literature-derived genes, including genes involved in cancer and others with unknown functions, a high-throughput methylation-specific oligonucleotide microarray was used. The arrays were probed with bisulfite-converted DNA from 89 colorectal adenocarcinomas, 55 colorectal polyps, 31 inflammatory bowel disease, 115 extracolonic cancers, and 67 healthy tissues. The 20 most discriminating markers were highly methylated in colorectal neoplasia (area under the receiver operating characteristic curve > 0.8; P < 0.0001). Normal epithelium and extracolonic cancers revealed significantly lower methylation. Real-time PCR assays developed for 11 markers were tested on an independent set of 149 samples from colorectal adenocarcinomas, other diseases, and healthy tissues. Microarray results could be reproduced for 10 of 11 marker assays, including eight of the most discriminating markers (area under the receiver operating characteristic curve > 0.72; P < 0.009). The markers with high specificity for colorectal cancer have potential as blood-based screening markers whereas markers that are specific for multiple cancers could potentially be used as prognostic indicators, as biomarkers for therapeutic response monitoring or other diagnostic applications, compelling further investigation into their use in clinical testing and overall roles in tumorigenesis. (Mol Cancer Res 2007;5(2):153–63)

Rapid adaptation to internal states as a coding strategy in visual cortex

Adaptation is a prominent feature of biological neuronal systems. A common interpretation of adaptation in terms of function is that it provides flexibility for a neuronal system to perform well under varying external conditions, for example by adjusting the input/output relation of a sensory system with reference to the ensemble of stimuli the organism currently perceives. This interpretation, however, only applies if the time-scale of adaptation is slower than the time-scale at which the environment changes. Experimentally it is observed, however, that adaptation can be very rapid. Spike-frequency adaptation of cortical neurons, for example, occurs on a time-scale of ∼100u2009ms. Here we show that those rapid adaptation processes can also be understood within the framework of information theory. We start with the hypothesis that neuronal codes are designed to optimize the information a neuronal representation conveys about an input stimulus for any increasing time window beginning with stimulus onset, and we show that this implies a rapid adaptation of the neuronal code on the time-scale of stimulus presentation. Adaptation, however, does not occur because the state of the environment changes. Rather it is a reaction to changes of the organisms own internal state, e.g. the level of noise in the neuronal representation. We apply this approach to a model of an orientation hypercolumn in the primary visual cortex, and predict that inter-columnar interactions should adapt on the time-scale of a typical fixation period (∼300u2009ms).