Genome-wide DNA methylation analyses in the brain reveal four differentially methylated regions between humans and non-human primates

P14.5 functions to inhibit cell migration and can be used as a prognostic marker in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy with a high mortality rate. P14.5 is a member of the highly conserved YER057c/YIL051c/YjgF subfamily and is highly expressed in the liver. However, its low expression is associated with carcinogenesis in HCC.

OBJECTIVE

This study aimed to investigate the role and prognostic significance of P14.5 in HCC.

METHODS

The clinical significance of P14.5 in HCC was examined using ONCOMINE, UALCAN, Human Protein Atlas, and Kaplan-Meier plotter. The DNA methylation profile of the P14.5 promoter was examined in 103 HCC and paired precancerous tissues; the HCC cell lines HepG2, MHCC-97L, SMMC-7721, SK-Hep-1, and Huh7; and the normal hepatic cell line HL-7702 via MALDI-TOF mass spectrometry. In addition, in vitro experiments were performed to examine the effects of P14.5 overexpression on the proliferation and migration of SMMC-7721 cells.

RESULTS

Low expression of P14.5 was correlated with shorter overall survival (OS) and disease-free survival (DFS) in HCC. Based on the results of MALDI-TOF mass spectrometry, no difference was observed in the methylation level between HCC cells and normal human hepatic cells and between HCC and paired precancerous tissues. Additionally, P14.5 overexpression promoted the proliferation and inhibited the migration of SMMC7721 cells in vitro.

CONCLUSIONS

P14.5 may serve as a prognostic biomarker in HCC and plays a role in the migration and proliferation of HCC cells. Low expression of P14.5 during hepatocarcinogenesis is not attributed to DNA methylation.

Prospects for incorporation of epigenetic biomarkers in human health and environmental risk assessment of chemicals

Epigenetic mechanisms have gained relevance in human health and environmental studies, due to their pivotal role in disease, gene × environment interactions and adaptation to environmental change and/or contamination. Epigenetic mechanisms are highly responsive to external stimuli and a wide range of chemicals has been shown to determine specific epigenetic patterns in several organisms. Furthermore, the mitotic/meiotic inheritance of such epigenetic marks as well as the resulting changes in gene expression and cell/organismal phenotypes has now been demonstrated. Therefore, epigenetic signatures are interesting candidates for linking environmental exposures to disease as well as informing on past exposures to stressors. Accordingly, epigenetic biomarkers could be useful tools in both prospective and retrospective risk assessment but epigenetic endpoints are currently not yet incorporated into risk assessments. Achieving a better understanding on this apparent impasse, as well as identifying routes to promote the application of epigenetic biomarkers within environmental risk assessment frameworks are the objectives of this review. We first compile evidence from human health studies supporting the use of epigenetic exposure-associated changes as reliable biomarkers of exposure. Then, specifically focusing on environmental science, we examine the potential and challenges of developing epigenetic biomarkers for environmental fields, and discuss useful organisms and appropriate sequencing techniques to foster their development in this context. Finally, we discuss the practical incorporation of epigenetic biomarkers in the environmental risk assessment of chemicals, highlighting critical data gaps and making key recommendations for future research within a regulatory context.

Cell Type and Species-specific Patterns in Neuronal and Non-neuronal Methylomes of Human and Chimpanzee Cortices

Epigenetic changes have likely contributed to the large size and enhanced cognitive abilities of the human brain which evolved within the last 2 million years after the human–chimpanzee split. Using reduced representation bisulfite sequencing, we have compared the methylomes of neuronal and non-neuronal cells from 3 human and 3 chimpanzee cortices. Differentially methylated regions (DMRs) with genome-wide significance were enriched in specific genomic regions. Intraspecific methylation differences between neuronal and non-neuronal cells were approximately 3 times more abundant than interspecific methylation differences between human and chimpanzee cell types. The vast majority (>90%) of human intraspecific DMRs (including DMRs in retrotransposons) were hypomethylated in neurons, compared with glia. Intraspecific DMRs were enriched in genes associated with different neuropsychiatric disorders. Interspecific DMRs were enriched in genes showing human-specific brain histone modifications. Human–chimpanzee methylation differences were much more frequent in non-neuronal cells (n. DMRs = 666) than in neurons (n. DMRs = 96). More than 95% of interspecific DMRs in glia were hypermethylated in humans. Although without an outgroup we cannot assign whether a change in methylation occurred in the human or chimpanzee lineage, our results are consistent with a wave of methylation affecting several hundred non-neuronal genes during human brain evolution.

Life history changes accompany increased numbers of cortical neurons: A new framework for understanding human brain evolution

Narratives of human evolution have focused on cortical expansion and increases in brain size relative to body size, but considered that changes in life history, such as in age at sexual maturity and thus the extent of childhood and maternal dependence, or maximal longevity, are evolved features that appeared as consequences of selection for increased brain size, or increased cognitive abilities that decrease mortality rates, or due to selection for grandmotherly contribution to feeding the young. Here I build on my recent finding that slower life histories universally accompany increased numbers of cortical neurons across warm-blooded species to propose a simpler framework for human evolution: that slower development to sexual maturity and increased post-maturity longevity are features that do not require selection, but rather inevitably and immediately accompany evolutionary increases in numbers of cortical neurons, thus fostering human social interactions and cultural and technological evolution as generational overlap increases.

Multiple Innovations in Genetic and Epigenetic Mechanisms Cooperate to Underpin Human Brain Evolution

Our knowledge of how the human brain differs from those of other species in terms of evolutionary adaptations and functionality is limited. Comparative genomics reveal valuable insight, especially the expansion of human-specific noncoding regulatory and repeat-containing regions. Recent studies add to our knowledge of evolving brain function by investigating cellular mechanisms such as protein emergence, extensive sequence editing, retrotransposon activity, dynamic epigenetic modifications, and multiple noncoding RNA functions. These findings present an opportunity to combine newly discovered genetic and epigenetic mechanisms with more established concepts into a more comprehensive picture to better understand the uniquely evolved human brain.

Epigenetics and evolution

Epigenetic mechanisms traditionally have been studied in the domains of development and disease, but they may also play important roles in ecological and evolutionary processes. In this article, we revisit historical as well as recent studies that indicate significant impacts of epigenetic processes on evolution. Our main focus is DNA methylation, which is a prevalent chemical modification of genomic DNA. First, it has been long known that DNA methylation acts as a major mutational facilitator in animal genomes and influences nucleotide compositions of genomes. More recently, genome-wide analyses have demonstrated that the current levels of DNA methylation can be predicted from the evolutionary signatures of DNA methylation, indicating that these two processes are intimately correlated. Indeed, the recent explosive growth in the knowledge of genomic DNA methylation in wide-ranging taxa has revealed that patterns of DNA methylation are surprisingly conserved across deep phylogenies. Interestingly, comparative analyses of humans and closely related primate species show that genomic regions that do show evolutionary divergence of DNA methylation are enriched for developmental and tissue specializations. A key question is how epigenetic patterns transmit between generations and impact evolutionary dynamics. On the one hand, some studies report direct transmissions of epigenetic features to the next generation. On the other hand, it is becoming clear that genomic sequence variants exist that encode and presumably regulate distinctive epigenetic patterns. For instance, numerous single-nucleotide polymorphisms that affect DNA-methylation patterns have been discovered in human populations. These studies begin to unveil a dynamic interplay between genomic and epigenomic factors across long and short evolutionary timescales.

Widespread differences in cortex DNA methylation of the "language gene" CNTNAP2 between humans and chimpanzees

CNTNAP2, one of the largest genes in the human genome, has been linked to human-specific language abilities and neurodevelopmental disorders. Our hypothesis is that epigenetic rather than genetic changes have accelerated the evolution of the human brain. To compare the cortex DNA methylation patterns of human and chimpanzee CNTNAP2 at ultra-high resolution, we combined methylated DNA immunoprecipitation (MeDIP) with NimbleGen tiling arrays for the orthologous gene and flanking sequences. Approximately 1.59 Mb of the 2.51 Mb target region could be aligned and analyzed with a customized algorithm in both species. More than one fifth (0.34 Mb) of the analyzed sequence throughout the entire gene displayed significant methylation differences between six human and five chimpanzee cortices. One of the most striking interspecies differences with 28% methylation in human and 59% in chimpanzee cortex (by bisulfite pyrosequencing) lies in a region 300 bp upstream of human SNP rs7794745 which has been associated with autism and parent-of-origin effects. Quantitative real-time RT PCR revealed that the protein-coding splice variant CNTNAP2-201 is 1.6-fold upregulated in human cortex, compared with the chimpanzee. Transcripts CNTNAP2-001, -002, and -003 did not show skewed allelic expression, which argues against CNTNAP2 imprinting, at least in adult human brain. Collectively, our results suggest widespread cortex DNA methylation changes in CNTNAP2 since the human-chimpanzee split, supporting a role for CNTNAP2 fine-regulation in human-specific language and communication traits.

Comprehensive DNA methylation and hydroxymethylation analysis in the human brain and its implication in mental disorders

Covalent modifications of nucleotides, such as methylation or hydroxymethylation of cytosine, regulate gene expression. Early environmental risk factors play a role in mental disorders in adulthood. This may be in part mediated by epigenetic DNA modifications. Methods for comprehensive analysis of DNA methylation and hydroxymethylation include DNA modification methods such as bisulfite sequencing, or collection of methylated, hydroxymethylated, or unmethylated DNA by specific binding proteins, antibodies, or restriction enzymes, followed by sequencing or microarray analysis. Results from these experiments should be interpreted with caution because each method gives different result. Cytosine hydroxymethylation has different effects on gene expression than cytosine methylation; methylation of CpG islands is associated with lower gene expression, whereas hydroxymethylation in intragenic regions is associated with higher gene expression. The role of hydroxymethylcytosine is of particular interest in mental disorders because the modification is enriched in the brain and synapse related genes, and it exhibits dynamic regulation during development. Many DNA methylation patterns are conserved across species, but there are also human specific signatures. Comprehensive analysis of DNA methylation shows characteristic changes associated with tissues, brain regions, cell types, and developmental states. Thus, differences in DNA methylation status between tissues, brain regions, cell types, and developmental stages should be considered when the role of DNA methylation in mental disorders is studied. Several disease-associated changes in methylation have been reported: hypermethylation of SOX10 in schizophrenia, hypomethylation of HCG9 (HLA complex group 9) in bipolar disorder, hypermethylation of PRIMA1, hypermethylation of SLC6A4 (serotonin transporter) in bipolar disorder, and hypomethylation of ST6GALNAC1 in bipolar disorder. These findings need to be replicated in different patient populations to be generalized. Further studies including animal experiments are necessary to understand the roles of DNA methylation in mental disorders.

Identification of optimum sequencing depth especially for de novo genome assembly of small genomes using next generation sequencing data

Next Generation Sequencing (NGS) is a disruptive technology that has found widespread acceptance in the life sciences research community. The high throughput and low cost of sequencing has encouraged researchers to undertake ambitious genomic projects, especially in de novo genome sequencing. Currently, NGS systems generate sequence data as short reads and de novo genome assembly using these short reads is computationally very intensive. Due to lower cost of sequencing and higher throughput, NGS systems now provide the ability to sequence genomes at high depth. However, currently no report is available highlighting the impact of high sequence depth on genome assembly using real data sets and multiple assembly algorithms. Recently, some studies have evaluated the impact of sequence coverage, error rate and average read length on genome assembly using multiple assembly algorithms, however, these evaluations were performed using simulated datasets. One limitation of using simulated datasets is that variables such as error rates, read length and coverage which are known to impact genome assembly are carefully controlled. Hence, this study was undertaken to identify the minimum depth of sequencing required for de novo assembly for different sized genomes using graph based assembly algorithms and real datasets. Illumina reads for E.coli (4.6 MB) S.kudriavzevii (11.18 MB) and C.elegans (100 MB) were assembled using SOAPdenovo, Velvet, ABySS, Meraculous and IDBA-UD. Our analysis shows that 50X is the optimum read depth for assembling these genomes using all assemblers except Meraculous which requires 100X read depth. Moreover, our analysis shows that de novo assembly from 50X read data requires only 6-40 GB RAM depending on the genome size and assembly algorithm used. We believe that this information can be extremely valuable for researchers in designing experiments and multiplexing which will enable optimum utilization of sequencing as well as analysis resources.