RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

A novel role of TRIM28 B box domain in L1 retrotransposition and ORF2p-mediated cDNA synthesis

The long interspersed element 1 (LINE-1 or L1) integration is affected by many cellular factors through various mechanisms. Some of these factors are required for L1 amplification, while others either suppress or enhance specific steps during L1 propagation. Previously, TRIM28 has been identified to suppress transposable elements, including L1 expression via its canonical role in chromatin remodeling. Here, we report that TRIM28 through its B box domain increases L1 retrotransposition and facilitates shorter cDNA and L1 insert generation in cultured cells. Consistent with the latter, we observe that tumor specific L1 inserts are shorter in endometrial, ovarian, and prostate tumors with higher TRIM28 mRNA expression than in those with lower TRIM28 expression. We determine that three amino acids in the B box domain that are involved in TRIM28 multimerization are critical for its effect on both L1 retrotransposition and cDNA synthesis. We provide evidence that B boxes from the other two members in the Class VI TRIM proteins, TRIM24 and TRIM33, also increase L1 retrotransposition. Our findings could lead to a better understanding of the host/L1 evolutionary arms race in the germline and their interplay during tumorigenesis.

Quantification of LINE-1 RNA Expression from Bulk RNA-seq Using L1EM

LINE-1 retrotransposons have the potential to cause DNA damage, contribute to genome instability, and induce an interferon response. Thus, accurate measurements of their expression, especially in disease contexts where genome instability and the interferon response are relevant, are of particular importance. Illumina-based bulk RNA sequencing remains the most abundant datatype for measuring gene expression. However, "active" expression from its own internal promoter is only one source of LINE-1 aligning reads in an RNA-seq experiment. With about half a million LINE-1 sequences scattered throughout the genome, many are incorporated into other transcripts that have nothing to do with LINE-1 activity. We call this "passive" co-transcription. Here we will describe how to use L1EM, a computational method that separates active from passive LINE-1 expression at the locus-specific level.

Organ-, sex- and age-dependent patterns of endogenous L1 mRNA expression at a single locus resolution

Expression of L1 mRNA, the first step in the L1 copy-and-paste amplification cycle, is a prerequisite for L1-associated genomic instability. We used a reported stringent bioinformatics method to parse L1 mRNA transcripts and measure the level of L1 mRNA expressed in mouse and rat organs at a locus-specific resolution. This analysis determined that mRNA expression of L1 loci in rodents exhibits striking organ specificity with less than 0.8% of loci shared between organs of the same organism. This organ specificity in L1 mRNA expression is preserved in male and female mice and across age groups. We discovered notable differences in L1 mRNA expression between sexes with only 5% of expressed L1 loci shared between male and female mice. Moreover, we report that the levels of total L1 mRNA expression and the number and spectrum of expressed L1 loci fluctuate with age as independent variables, demonstrating different patterns in different organs and sexes. Overall, our comparisons between organs and sexes and across ages ranging from 2 to 22 months establish previously unforeseen dynamic changes in L1 mRNA expression in vivo. These findings establish the beginning of an atlas of endogenous L1 mRNA expression across a broad range of biological variables that will guide future studies.

Tet1 Deficiency Leads to Premature Ovarian Failure

Tet enzymes participate in DNA demethylation and play critical roles in stem cell pluripotency and differentiation. DNA methylation alters with age. We find that Tet1 deficiency reduces fertility and leads to accelerated reproductive failure with age. Noticeably, Tet1-deficient mice at young age exhibit dramatically reduced follicle reserve and the follicle reserve further decreases with age, phenomenon consistent with premature ovarian failure (POF) syndrome. Consequently, Tet1-deficient mice become infertile by reproductive middle age, while age matched wild-type mice still robustly reproduce. Moreover, by single cell transcriptome analysis of oocytes, Tet1 deficiency elevates organelle fission, associated with defects in ubiquitination and declined autophagy, and also upregulates signaling pathways for Alzheimer's diseases, but down-regulates X-chromosome linked genes, such as Fmr1, which is known to be implicated in POF. Additionally, Line1 is aberrantly upregulated and endogenous retroviruses also are altered in Tet1-deficient oocytes. These molecular changes are consistent with oocyte senescence and follicle atresia and depletion found in premature ovarian failure or insufficiency. Our data suggest that Tet1 enzyme plays roles in maintaining oocyte quality as well as oocyte number and follicle reserve and its deficiency can lead to POF.

Sequencing Analysis of mRNA Profile in Endothelial Cells in Response to ox-LDL

The pathogenesis of atherosclerosis (AS) and abnormal endothelial cells apoptosis is a multifactorial biological process. Oxidized low density lipoprotein (ox-LDL) is a critical factor in the formation of AS. However, the exact mechanism is still not clear. Therefore, the aim of this study was to investigate some genes and biological pathways in endothelial cells apoptosis in response to ox-LDL. First, our results has validated that ox-LDL is an effective inducer of endothelial cells apoptosis, then, transcriptome sequencing was used to detect differential expression genes. In total, 71 differentially expressed genes (DEGs) were identified, including 32 upregulated genes and 39 downregulated genes. GO analysis showed that DEGs were mainly enriched in cytokine-mediated signaling pathway, gene expression, external side of plasma membrane, steroid binding, and signaling receptor binding. After KEGG analysis, the DEGs mainly focused on the following biochemical signaling pathways, including Signaling molecules and interaction (such as ICOSLG, IL6, ITGAM, TNFRSF13C and VTCN1), Signal transduction (such as IL13RA2, IL6, ITGAM, PDE5A, SGK3 and TNFRSF13C), Immune system (such as FCGR2A, ICOSLG, IL6, ITGAM and TNFRSF13C), and so on. These genes may play a dominant role in HAECs apoptosis and AS genesis. The above prediction and analysis provide an important basis for our follow-up study of the mechanism of these genes, which might be used as molecular targets or diagnostic biomarkers for AS.

Comparative analysis on the expression of L1 loci using various RNA-Seq preparations

Background

Retrotransposons are one of the oldest evolutionary forces shaping mammalian genomes, with the ability to mobilize from one genomic location to another. This mobilization is also a significant factor in human disease. The only autonomous human retroelement, L1, has propagated to make up 17% of the human genome, accumulating over 500,000 copies. The majority of these loci are truncated or defective with only a few reported to remain capable of retrotransposition. We have previously published a strand-specific RNA-Seq bioinformatics approach to stringently identify at the locus-specific level the few expressed full-length L1s using cytoplasmic RNA. With growing repositories of RNA-Seq data, there is potential to mine these datasets to identify and study expressed L1s at single-locus resolution, although many datasets are not strand-specific or not generated from cytoplasmic RNA.

Results

We developed whole-cell, cytoplasmic and nuclear RNA-Seq datasets from 22Rv1 prostate cancer cells to test the influence of different preparations on the quality and effort needed to measure L1 expression. We found that there was minimal data loss in the identification of full-length expressed L1 s using whole cell, strand-specific RNA-Seq data compared to cytoplasmic, strand-specific RNA-Seq data. However, this was only possible with an increased amount of manual curation of the bioinformatics output to eliminate increased background. About half of the data was lost when the sequenced datasets were non-strand specific.

Conclusions

The results of these studies demonstrate that with rigorous manual curation the utilization of stranded RNA-Seq datasets allow identification of expressed L1 loci from either cytoplasmic or whole-cell RNA-Seq datasets.