In human cancers, the methylation of long interspersed nuclear element -1 (LINE-1 or L1) retrotransposons is reduced. This occurs within the context of genome wide hypomethylation, and although it is common, its role is poorly understood. L1s are widely distributed both inside and outside of genes, intragenic and intergenic, respectively. Interestingly, the insertion of active full-length L1 sequences into host gene introns disrupts gene expression. Here, we evaluated if intragenic L1 hypomethylation influences their host gene expression in cancer. First, we extracted data from L1base (http://l1base.molgen.mpg.de), a database containing putatively active L1 insertions, and compared intragenic and intergenic L1 characters. We found that intragenic L1 sequences have been conserved across evolutionary time with respect to transcriptional activity and CpG dinucleotide sites for mammalian DNA methylation. Then, we compared regulated mRNA levels of cells from two different experiments available from Gene Expression Omnibus (GEO), a database repository of high throughput gene expression data, (http://www.ncbi.nlm.nih.gov/geo) by chi-square. The odds ratio of down-regulated genes between demethylated normal bronchial epithelium and lung cancer was high (p<1E−27; OR = 3.14; 95% CI = 2.54–3.88), suggesting cancer genome wide hypomethylation down-regulating gene expression. Comprehensive analysis between L1 locations and gene expression showed that expression of genes containing L1s had a significantly higher likelihood to be repressed in cancer and hypomethylated normal cells. In contrast, many mRNAs derived from genes containing L1s are elevated in Argonaute 2 (AGO2 or EIF2C2)-depleted cells. Hypomethylated L1s increase L1 mRNA levels. Finally, we found that AGO2 targets intronic L1 pre-mRNA complexes and represses cancer genes. These findings represent one of the mechanisms of cancer genome wide hypomethylation altering gene expression. Hypomethylated intragenic L1s are a nuclear siRNA mediated cis-regulatory element that can repress genes. This epigenetic regulation of retrotransposons likely influences many aspects of genomic biology.

This study evaluated methylation patterns of long interspersed nuclear element-1 (LINE-1) sequences from 17 loci in several cell types, including squamous cell cancer cell lines, normal oral epithelium (NOE), white blood cells and head and neck squamous cell cancers (HNSCC). Although sequences of each LINE-1 are homologous, LINE-1 methylation levels at each locus are different. Moreover, some loci demonstrate the different methylation levels between normal tissue types. Interestingly, in some chromosomal regions, wider ranges of LINE-1 methylation levels were observed. In cancerous cells, the methylation levels of most LINE-1 loci demonstrated a positive correlation with each other and with the genome-wide levels. Therefore, the loss of genome-wide methylation in cancerous cells occurs as a generalized process. However, different LINE-1 loci showed different incidences of HNSCC hypomethylation, which is a lower methylation level than NOE. Additionally, we report a closer direct association between two LINE-1s in different EPHA3 introns. Finally, hypermethylation of some LINE-1s can be found sporadically in cancer. In conclusion, even though the global hypomethylation process that occurs in cancerous cells can generally deplete LINE-1 methylation levels, LINE-1 methylation can be influenced differentially depending on where the particular sequences are located in the genome.

Data availabilitySummary statistics generated by COVID-19 Host Genetics Initiative are available online (https://www.covid19hg.org/results/r6/). The analyses described here use the freeze 6 data. The COVID-19 Host Genetics Initiative continues to regularly release new data freezes. Summary statistics for samples from individuals of non-European ancestry are not currently available owing to the small individual sample sizes of these groups, but the results for 23 loci lead variants are reported in Supplementary Table 3. Individual-level data can be requested directly from the authors of the contributing studies, listed in Supplementary Table 1.

Background: The aim of this study was to evaluate epigenetic status of cyclin A1 in human papillomavirusassociated cervical cancer. Y. Tokumaru et al., Cancer Res 64, 5982-7 (Sep 1, 2004)demonstrated in head and neck squamous-cell cancer an inverse correlation between cyclin A1 promoter hypermethylation and TP53 mutation. Human papillomavirus-associated cervical cancer, however, is deprived of TP53 function by a different mechanism. Therefore, it was of interest to investigate the epigenetic alterations during multistep cervical cancer development.

To maximize the potential of genomics in medicine, it is essential to establish databases of genomic variants for ethno‐geographic groups that can be used for filtering and prioritizing candidate pathogenic variants. Populations with non‐European ancestry are poorly represented among current genomic variant databases. Here, we report the first high‐density survey of genomic variants for the Thai population, the Thai Reference Exome (T‐REx) variant database. T‐REx comprises exome sequencing data of 1092 unrelated Thai individuals. The targeted exome regions common among four capture platforms cover 30.04 Mbp on autosomes and chromosome X. 345 681 short variants (18.27% of which are novel) and 34 907 copy number variations were found. Principal component analysis on 38 469 single nucleotide variants present worldwide showed that the Thai population is most genetically similar to East and Southeast Asian populations. Moreover, unsupervised clustering revealed six Thai subpopulations consistent with the evidence of gene flow from neighboring populations. The prevalence of common pathogenic variants in T‐REx was investigated in detail, which revealed subpopulation‐specific patterns, in particular variants associated with erythrocyte disorders such as the HbE variant in HBB and the Viangchan variant in G6PD. T‐REx serves as a pivotal addition to the current databases for genomic medicine.