A novel approach to finding candidate genes by using gene expression data through liquid association is developed and used to identify multiple sclerosis susceptibility candidate genes.

Studies that elucidate why some human tissues age faster than others may shed light on how we age, and ultimately suggest what interventions may be possible. Here we utilize a recent biomarker of aging (referred to as epigenetic clock) to assess the epigenetic ages of up to 30 anatomic sites from supercentenarians (subjects who reached an age of 110 or older) and younger subjects. Using three novel and three published human DNA methylation data sets, we demonstrate that the cerebellum ages more slowly than other parts of the human body. We used both transcriptional data and genetic data to elucidate molecular mechanisms which may explain this finding. The two largest superfamilies of helicases (SF1 and SF2) are significantly over-represented (p=9.2x10-9) among gene transcripts that are over-expressed in the cerebellum compared to other brain regions from the same subject. Furthermore, SNPs that are associated with epigenetic age acceleration in the cerebellum tend to be located near genes from helicase superfamilies SF1 and SF2 (enrichment p=5.8x10-3). Our genetic and transcriptional studies of epigenetic age acceleration support the hypothesis that the slow aging rate of the cerebellum is due to processes that involve RNA helicases.

Age of Huntington's disease (HD) motoric onset is strongly related to the number of CAG trinucleotide repeats in the huntingtin gene, suggesting that biological tissue age plays an important role in disease etiology. Recently, a DNA methylation based biomarker of tissue age has been advanced as an epigenetic aging clock. We sought to inquire if HD is associated with an accelerated epigenetic age. DNA methylation data was generated for 475 brain samples from various brain regions of 26 HD cases and 39 controls. Overall, brain regions from HD cases exhibit a significant epigenetic age acceleration effect (p=0.0012). A multivariate model analysis suggests that HD status increases biological age by 3.2 years. Accelerated epigenetic age can be observed in specific brain regions (frontal lobe, parietal lobe, and cingulate gyrus). After excluding controls, we observe a negative correlation (r=-0.41, p=5.5×10-8) between HD gene CAG repeat length and the epigenetic age of HD brain samples. Using correlation network analysis, we identify 11 co-methylation modules with a significant association with HD status across 3 broad cortical regions. In conclusion, HD is associated with an accelerated epigenetic age of specific brain regions and more broadly with substantial changes in brain methylation levels.

Genome-wide gene expression studies may provide substantial insight into gene activities and biological pathways differing between tissues and individuals. We investigated such gene expression variation by analyzing expression profiles in brain tissues derived from eight different brain regions and from blood in 12 monkeys from a biomedically important non-human primate model, the vervet (Chlorocebus aethiops sabaeus). We characterized brain regional differences in gene expression, focusing on transcripts for which inter-individual variation of expression in brain correlates well with variation in blood from the same individuals. Using stringent criteria, we identified 29 transcripts whose expression is measurable, stable, replicable, variable between individuals, relevant to brain function and heritable. Polymorphisms identified in probe regions could, in a minority of transcripts, confound the interpretation of the observed inter-individual variation. The high heritability of levels of these transcripts in a large vervet pedigree validated our approach of focusing on transcripts that showed higher inter-individual compared with intra-individual variation. These selected transcripts are candidate expression Quantitative Trait Loci, differentially regulating transcript levels in the brain among individuals. Given the high degree of conservation of tissue expression profiles between vervets and humans, our findings may facilitate the understanding of regional and individual transcriptional variation and its genetic mechanisms in humans. The approach employed here-utilizing higher quality tissue and more precise dissection of brain regions than is usually possible in humans-may therefore provide a powerful means to investigate variation in gene expression relevant to complex brain related traits, including human neuropsychiatric diseases.

Background

We report here the first genome-wide high-resolution polymorphism resource for non-human primate (NHP) association and linkage studies, constructed for the Caribbean-origin vervet monkey, or African green monkey (Chlorocebus aethiops sabaeus), one of the most widely used NHPs in biomedical research. We generated this resource by whole genome sequencing (WGS) of monkeys from the Vervet Research Colony (VRC), an NIH-supported research resource for which extensive phenotypic data are available.

Results

We identified genome-wide single nucleotide polymorphisms (SNPs) by WGS of 721 members of an extended pedigree from the VRC. From high-depth WGS data we identified more than 4 million polymorphic unequivocal segregating sites; by pruning these SNPs based on heterozygosity, quality control filters, and the degree of linkage disequilibrium (LD) between SNPs, we constructed genome-wide panels suitable for genetic association (about 500,000 SNPs) and linkage analysis (about 150,000 SNPs). To further enhance the utility of these resources for linkage analysis, we used a further pruned subset of the linkage panel to generate multipoint identity by descent matrices.

Conclusions

The genetic and phenotypic resources now available for the VRC and other Caribbean-origin vervets enable their use for genetic investigation of traits relevant to human diseases.

DNA methylation-based biomarkers of aging have been developed for many mammals but not yet for the vervet monkey (Chlorocebus sabaeus), which is a valuable non-human primate model for biomedical studies. We generated novel DNA methylation data from vervet cerebral cortex, blood, and liver using highly conserved mammalian CpGs represented on a custom array (HorvathMammalMethylChip40). We present six DNA methylation-based estimators of age: vervet multi-tissue epigenetic clock and tissue-specific clocks for brain cortex, blood, and liver. In addition, we developed two dual species clocks (human-vervet clocks) for measuring chronological age and relative age, respectively. Relative age was defined as ratio of chronological age to maximum lifespan to address the species differences in maximum lifespan. The high accuracy of the human-vervet clocks demonstrates that epigenetic aging processes are evolutionary conserved in primates. When applying these vervet clocks to tissue samples from another primate species, rhesus macaque, we observed high age correlations but strong offsets. We characterized CpGs that correlate significantly with age in the vervet. CpG probes that gain methylation with age across tissues were located near the targets of Polycomb proteins SUZ12 and EED and genes possessing the trimethylated H3K27 mark in their promoters. The epigenetic clocks are expected to be useful for anti-aging studies in vervets.

By analyzing multitissue gene expression and genome-wide genetic variation data in samples from a vervet monkey pedigree, we generated a transcriptome resource and produced the first catalog of expression quantitative trait loci (eQTLs) in a nonhuman primate model. This catalog contains more genome-wide significant eQTLs per sample than comparable human resources and identifies sex- and age-related expression patterns. Findings include a master regulatory locus that likely has a role in immune function and a locus regulating hippocampal long noncoding RNAs (lncRNAs), whose expression correlates with hippocampal volume. This resource will facilitate genetic investigation of quantitative traits, including brain and behavioral phenotypes relevant to neuropsychiatric disorders.

We describe a genome reference of the African green monkey or vervet (Chlorocebus aethiops). This member of the Old World monkey (OWM) superfamily is uniquely valuable for genetic investigations of simian immunodeficiency virus (SIV), for which it is the most abundant natural host species, and of a wide range of health-related phenotypes assessed in Caribbean vervets (C. a. sabaeus), whose numbers have expanded dramatically since Europeans introduced small numbers of their ancestors from West Africa during the colonial era. We use the reference to characterize the genomic relationship between vervets and other primates, the intra-generic phylogeny of vervet subspecies, and genome-wide structural variations of a pedigreed C. a. sabaeus population. Through comparative analyses with human and rhesus macaque, we characterize at high resolution the unique chromosomal fission events that differentiate the vervets and their close relatives from most other catarrhine primates, in whom karyotype is highly conserved. We also provide a summary of transposable elements and contrast these with the rhesus macaque and human. Analysis of sequenced genomes representing each of the main vervet subspecies supports previously hypothesized relationships between these populations, which range across most of sub-Saharan Africa, while uncovering high levels of genetic diversity within each. Sequence-based analyses of major histocompatibility complex (MHC) polymorphisms reveal extremely low diversity in Caribbean C. a. sabaeus vervets, compared to vervets from putatively ancestral West African regions. In the C. a. sabaeus research population, we discover the first structural variations that are, in some cases, predicted to have a deleterious effect; future studies will determine the phenotypic impact of these variations.

Using DNA methylation profiles (n = 15,456) from 348 mammalian species, we constructed phyloepigenetic trees that bear marked similarities to traditional phylogenetic ones. Using unsupervised clustering across all samples, we identified 55 distinct cytosine modules, of which 30 are related to traits such as maximum life span, adult weight, age, sex, and human mortality risk. Maximum life span is associated with methylation levels in HOXL subclass homeobox genes and developmental processes and is potentially regulated by pluripotency transcription factors. The methylation state of some modules responds to perturbations such as caloric restriction, ablation of growth hormone receptors, consumption of high-fat diets, and expression of Yamanaka factors. This study reveals an intertwined evolution of the genome and epigenome that mediates the biological characteristics and traits of different mammalian species.