Nucleotide diversity (π) of previous reported balancing selection genes and the <i>LMBR1</i> intron 5 studied here.

<p>It shows that <i>LMBR1</i> intron 5 had low π among these genes with documented evidence of balancing selection. The data are from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002948#pone.0002948-Fagundes1" target="_blank">[29]</a> (<i>LDLR</i>), <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002948#pone.0002948-Nakajima1" target="_blank">[30]</a> (<i>HAVCR1</i>), <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002948#pone.0002948-Wooding2" target="_blank">[18]</a> (<i>ABO</i>, <i>IL10R</i>B, <i>IL1A</i>, and <i>ACE2</i>), <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002948#pone.0002948-Hudson1" target="_blank">[19]</a> (5′ <i>CCR5</i>), <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002948#pone.0002948-Bernig1" target="_blank">[31]</a> (<i>MBL2</i>), <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002948#pone.0002948-Barreiro1" target="_blank">[32]</a> (<i>CD209L</i>), <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002948#pone.0002948-Soejima1" target="_blank">[33]</a> (<i>C6</i>), <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002948#pone.0002948-Stephens3" target="_blank">[13]</a> (<i>PTC</i>), <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002948#pone.0002948-Grigorova1" target="_blank">[34]</a> (<i>FSHB</i>), <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002948#pone.0002948-Allerston1" target="_blank">[35]</a> (<i>FMO3</i>), <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002948#pone.0002948-Verrelli1" target="_blank">[36]</a> (<i>G6PD</i>), <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002948#pone.0002948-Koda1" target="_blank">[37]</a> (<i>FUT2</i>).</p

Linkage disequilibrium pattern of chr7: 155920–156290 kbp (NCBI35) region in the East Asian, European and African populations based on the HapMap Data.

<p><i>LMBR1</i> gene and the intron 5 are showed.</p

Genetic variation analyses in the <i>LMBR1</i> intron 5 among 41 East Asian individuals.

<p>A: The 13 haplotypes constructed by PHASE program, and the right-most column shows the number of each haplotypes among 41 subjects. B: Median joining network of haplotypes. Each circle represents a haplotype indicated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002948#pone-0002948-g001" target="_blank">Figure 1A</a>, and the size of the circle is the relative frequency. Beside the branches are labels of the SNPs in the haplotypes counted from left to right. C: Graph of pairwise differences between the haplotypes. The dash line represent the observed sequence pairwise difference, and the real line represent the expected distribution of pairwise difference simulated by DnaSP under population growth with initial theta as 3.442, final theta as 1000, and final tau as 2.267. The “twin-peak” of observed mismatch distribution is suggestive of balancing selection. D: LD extent analyzed by R² of all pairwise comparisons between the 20 SNPs. The shadows indicate significant pairwise comparison identified with χ² tests by using a Bonferroni correction for multiple testing.</p

mtDNA content in Chinese populations.

<p>The mtDNA content of the northern populations is significant higher than that of the southern populations (<i>P</i>_<i>N/S</i>=0.1×10^-2), with the highest mean content observed in the northeastern populations (NE) and the lowest in the southern populations (<i>P</i>_<i>NE/S</i>=6.7×10^-8, <i>P</i>_<i>NW/S</i>=0.23). Darker colors represents higher levels of mtDNA content.</p

Principal components analysis of mtDNA haplotypes in the 26 populations.

<p>The analysis was performed using the basal haplogroup frequency matrix for the 26 Chinese populations retrieved from the literature (Table S2).</p

Correlation of mtDNA content with temperature factors in Chinese populations.

<p>(A) The results of regression analysis between temperature and mtDNA content in each subpopulation (R²=0.292, <i>P</i>=0.4×10^-2); (B) the regression between temperature and mtDNA content considering 3 geographical clusters (R²=0.866). (NE, the northeastern China; NW, the northwestern China; S, the southern China; QT, Qinghai-Tibet plateau). .</p

MOESM5 of Insights into long noncoding RNAs of naked mole rat (Heterocephalus glaber) and their potential association with cancer resistance

Additional file 5: Table S4. List of homologous lncRNA groups between human, mouse and naked mole rat

A Genome-Wide Scan Reveals Important Roles of DNA Methylation in Human Longevity by Regulating Age-Related Disease Genes

<div><p>It is recognized that genetic factors contribute to human longevity. Besides the hypothesis of existence of longevity genes, another suggests that a lower frequency of risk alleles decreases the incidence of age-related diseases in the long-lived people. However, the latter finds no support from recent genetic studies. Considering the crucial role of epigenetic modification in gene regulation, we then hypothesize that suppressing disease-related genes in longevity individuals is likely achieved by epigenetic modification, e.g. DNA methylation. To test this hypothesis, we investigated the genome-wide methylation profile in 4 Chinese female centenarians and 4 middle-aged controls using methyl-DNA immunoprecipitation sequencing. 626 differentially methylated regions (DMRs) were observed between both groups. Interestingly, genes with these DMRs were enriched in age-related diseases, including type-2 diabetes, cardiovascular disease, stroke and Alzheimer’s disease. This pattern remains rather stable after including methylomes of two white individuals. Further analyses suggest that the observed DMRs likely have functional roles in regulating disease-associated gene expressions, with some genes [e.g. caspase 3 (<i>CASP3</i>)] being down-regulated whereas the others [i.e. interleukin 1 receptor, type 2 (<i>IL1R2</i>)] up-regulated. Therefore, our study suggests that suppressing the disease-related genes via epigenetic modification is an important contributor to human longevity.</p></div

Pathway enrichment analysis for the genes with DMRs in Chinese samples.

<p>Pathway enrichment analysis for the genes with DMRs in Chinese samples.</p

The identified differentially methylated regions (DMRs).

<p>(A) Vision of the distribution of DMRs on each chromosome. (B) Heatmap of all DMRs (The methylation value of each DMR was log2 transformed).</p