Heme, an organometallic tetrapyrrole, is widely engaged in oxygen transport, electron delivery, enzymatic reactions, and signal transduction. In plants, it is also involved in photomorphogenesis and photosynthesis. HEME OXYGENASE 1 (HO1) initiates the first committed step in heme catabolism, and it has generally been thought that this reaction takes place in chloroplasts. Here, we show that HO1 in both Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) has 2 transcription start sites (TSSs), producing long (HO1L) and short (HO1S) transcripts. Their products localize to the chloroplast and the cytosol, respectively. During early development or de-etiolation, the HO1L/HO1S ratio gradually increases. Light perception via phytochromes (Phys) and cryptochromes elevates the HO1L/HO1S ratio in the whole seedling through the functions of ELONGATED HYPOCOTYL 5 (HY5) and HY5 HOMOLOG and through the suppression of DE-ETIOLATED 1, CONSTITUTIVE PHOTOMORPHOGENESIS 1, and PHYTOCHROME INTERACTING FACTORs. HO1L introduction complements the HO1-deficient mutant; surprisingly, HO1S expression also restores the short hypocotyl phenotype and high pigment content and helps the mutant recover from the genomes uncoupled (gun) phenotype. This indicates the assembly of functional Phys within these lines. Furthermore, our findings support the hypothesis that a mobile heme signal is involved in retrograde signaling from the chloroplast. Altogether, our work clarifies the molecular mechanism of HO1 TSS regulation and highlights the presence of a cytosolic bypass for heme catabolism in plant cells.

The sperm epigenome is thought to affect the developmental programming of the resulting embryo, influencing health and disease in later life. Age-related methylation changes in the sperm of old fathers may mediate the increased risks for reproductive and offspring medical problems. The impact of paternal age on sperm methylation has been extensively studied in humans and, to a lesser extent, in rodents and cattle. Here, we performed a comparative analysis of paternal age effects on protein-coding genes in the human and marmoset sperm methylomes. The marmoset has gained growing importance as a non-human primate model of aging and age-related diseases. Using reduced representation bisulfite sequencing, we identified age-related differentially methylated transcription start site (ageTSS) regions in 204 marmoset and 27 human genes. The direction of methylation changes was the opposite, increasing with age in marmosets and decreasing in humans. None of the identified ageTSS was differentially methylated in both species. Although the average methylation levels of all TSS regions were highly correlated between marmosets and humans, with the majority of TSS being hypomethylated in sperm, more than 300 protein-coding genes were endowed with species-specifically (hypo)methylated TSS. Several genes of the glycosphingolipid (GSL) biosynthesis pathway, which plays a role in embryonic stem cell differentiation and regulation of development, were hypomethylated (<5%) in human and fully methylated (>95%) in marmoset sperm. The expression levels and patterns of defined sets of GSL genes differed considerably between human and marmoset pre-implantation embryo stages and blastocyst tissues, respectively.

BACKGROUND: We recently developed two high-resolution methods for genome-wide mapping of two prominent types of DNA damage, single-strand DNA breaks (SSBs) and abasic (AP) sites and found highly complex and non-random patterns of these lesions in mammalian genomes. One salient feature of SSB and AP sites was the existence of single-nucleotide hotspots for both lesions.
RESULTS: In this work, we show that SSB hotspots are enriched in the immediate vicinity of transcriptional start sites (TSSs) in multiple normal mammalian tissues, however the magnitude of enrichment varies significantly with tissue type and appears to be limited to a subset of genes. SSB hotspots around TSSs are enriched on the template strand and associate with higher expression of the corresponding genes. Interestingly, SSB hotspots appear to be at least in part generated by the base-excision repair (BER) pathway from the AP sites.
CONCLUSIONS: Our results highlight complex relationship between DNA damage and regulation of gene expression and suggest an exciting possibility that SSBs at TSSs might function as sensors of DNA damage to activate genes important for DNA damage response.

The budding yeast Saccharomyces cerevisiae is an excellent model organism for studying chromatin regulation with high-resolution genome-wide analyses. Since newly generated genome-wide data are often compared with publicly available datasets, expanding our dataset repertoire will be beneficial for the field. Information on transcription start sites (TSSs) determined at base pair resolution is essential for elucidating mechanisms of transcription and related chromatin regulation, yet no datasets that cover two different cell types are available. Here, we present a CAGE (cap analysis of gene expression) dataset for a-cells and α-cells grown in defined and rich media. Cell type-specific genes were differentially expressed as expected, ensuring the reliability of the data. Some of the differentially expressed TSSs were medium-specific or detected due to unrecognized chromosome rearrangement. By comparing the CAGE data with a high-resolution nucleosome map, major TSSs were primarily found in +1 nucleosomes, with a peak approximately 30 bp from the promoter-proximal end of the nucleosome. The dataset is available at DDBJ/GEA.

The lysine 4 of histone H3 (H3K4) can be methylated or acetylated into four states: H3K4me1, H3K4me2, H3K4me3, or H3K4ac. Unlike H3K4 methylation, the genome-wide distribution and functional roles of H3K4ac remain unclear. To understand the relationship of acetylation with methylation at H3K4 and to explore the roles of H3K4ac in the context of chromatin, we analyzed H3K4ac across the human genome and compared it with H3K4 methylation in K562 cells. H3K4ac was positively correlated with H3K4me1/2/3 in reciprocal analysis. A decrease in H3K4ac through the mutation of the histone acetyltransferase p300 reduced H3K4me1 and H3K4me3 at the H3K4ac peaks. H3K4ac was also impaired by H3K4me depletion in the histone methyltransferase MLL3/4-mutated cells. H3K4ac peaks were enriched at enhancers in addition to the transcription start sites (TSSs) of genes. H3K4ac of TSSs and enhancers was positively correlated with mRNA and eRNA transcription. A decrease in H3K4ac reduced H3K4me3 and H3K4me1 in TSSs and enhancers, respectively, and inhibited the eviction of histone H3 from them. The mRNA transcription of highly transcribed genes was affected by the reduced H3K4ac. Interestingly, H3K4ac played a redundant role with regard to H3K27ac in eRNA transcription. These results indicate that H3K4ac serves as a marker of both active TSSs and enhancers and plays a role in histone eviction and RNA transcription by leading to H3K4me1/3.

A member of the Retroviridae, human immunodeficiency virus type 1 (HIV-1), uses the RNA genome packaged into nascent virions to transfer genetic information to its progeny. The genome packaging step is a highly regulated and extremely efficient process as a vast majority of virus particles contain two copies of full-length unspliced HIV-1 RNA that form a dimer. Thus, during virus assembly HIV-1 can identify and selectively encapsidate HIV-1 unspliced RNA from an abundant pool of cellular RNAs and various spliced HIV-1 RNAs. Several \"G\" features facilitate the packaging of a dimeric RNA genome. The viral polyprotein Gag orchestrates virus assembly and mediates RNA genome packaging. During this process, Gag preferentially binds unpaired guanosines within the highly structured 5\' untranslated region (UTR) of HIV-1 RNA. In addition, the HIV-1 unspliced RNA provides a scaffold that promotes Gag:Gag interactions and virus assembly, thereby ensuring its packaging. Intriguingly, recent studies have shown that the use of different guanosines at the junction of U3 and R as transcription start sites results in HIV-1 unspliced RNA species with 99.9% identical sequences but dramatically distinct 5\' UTR conformations. Consequently, one species of unspliced RNA is preferentially packaged over other nearly identical RNAs. These studies reveal how conformations affect the functions of HIV-1 RNA elements and the complex regulation of HIV-1 replication. In this review, we summarize cis- and trans-acting elements critical for HIV-1 RNA packaging, locations of Gag:RNA interactions that mediate genome encapsidation, and the effects of transcription start sites on the structure and packaging of HIV-1 RNA.

Mutations and gene expression are the two most studied genomic features in cancer research. In the last decade, the combined advances in genomic technology and computational algorithms have broadened mutation research with the concept of mutation density and expanded the traditional scope of protein-coding RNA to noncoding RNAs. However, mutation density analysis had yet to be integrated with non-coding RNAs. In this study, we examined long non-coding RNA (lncRNA) mutation density patterns of 57 unique cancer types using 80 cancer cohorts. Our analysis revealed that lncRNAs exhibit mutation density patterns reminiscent to those of protein-coding mRNAs. These patterns include mutation peak and dip around transcription start sites of lncRNA. In many cohorts, these patterns justified statistically significant transcription strand bias, and the transcription strand bias was shared between lncRNAs and mRNAs. We further quantified transcription strand biases with a Log Odds Ratio metric and showed that some of these biases are associated with patient prognosis. The prognostic effect may be exerted due to strong Transcription-coupled repair mechanisms associated with the individual patient. For the first time, our study combined mutational density patterns with lncRNA mutations, and the results demonstrated remarkably comparable patterns between protein-coding mRNA and lncRNA, further illustrating lncRNA\'s potential roles in cancer research.

Noncoding polymorphism frequently associates with phenotypic variation, but causation and mechanism are rarely established. Noncoding single-nucleotide polymorphisms (SNPs) characterize the major haplotypes of the Arabidopsis thaliana floral repressor gene FLOWERING LOCUS C (FLC). This noncoding polymorphism generates a range of FLC expression levels, determining the requirement for and the response to winter cold. The major adaptive determinant of these FLC haplotypes was shown to be the autumnal levels of FLC expression. Here, we investigate how noncoding SNPs influence FLC transcriptional output. We identify an upstream transcription start site (uTSS) cluster at FLC, whose usage is increased by an A variant at the promoter SNP-230. This variant is present in relatively few Arabidopsis accessions, with the majority containing G at this site. We demonstrate a causal role for the A variant at -230 in reduced FLC transcriptional output. The G variant upregulates FLC expression redundantly with the major transcriptional activator FRIGIDA (FRI). We demonstrate an additive interaction of SNP-230 with an intronic SNP+259, which also differentially influences uTSS usage. Combinatorial interactions between noncoding SNPs and transcriptional activators thus generate quantitative variation in FLC transcription that has facilitated the adaptation of Arabidopsis accessions to distinct climates.

Recognizing transcription start sites is key to gene identification. Several approaches have been employed in related problems such as detecting translation initiation sites or promoters, many of the most recent ones based on machine learning. Deep learning methods have been proven to be exceptionally effective for this task, but their use in transcription start site identification has not yet been explored in depth. Also, the very few existing works do not compare their methods to support vector machines (SVMs), the most established technique in this area of study, nor provide the curated dataset used in the study. The reduced amount of published papers in this specific problem could be explained by this lack of datasets. Given that both support vector machines and deep neural networks have been applied in related problems with remarkable results, we compared their performance in transcription start site predictions, concluding that SVMs are computationally much slower, and deep learning methods, specially long short-term memory neural networks (LSTMs), are best suited to work with sequences than SVMs. For such a purpose, we used the reference human genome GRCh38. Additionally, we studied two different aspects related to data processing: the proper way to generate training examples and the imbalanced nature of the data. Furthermore, the generalization performance of the models studied was also tested using the mouse genome, where the LSTM neural network stood out from the rest of the algorithms. To sum up, this article provides an analysis of the best architecture choices in transcription start site identification, as well as a method to generate transcription start site datasets including negative instances on any species available in Ensembl. We found that deep learning methods are better suited than SVMs to solve this problem, being more efficient and better adapted to long sequences and large amounts of data. We also create a transcription start site (TSS) dataset large enough to be used in deep learning experiments.

HIV-1 relies on host RNA polymeraseII (Pol II) to transcribe its genome and uses multiple transcription start sites (TSS), including three consecutive guanosines located near the U3-R junction, to generate transcripts containing three, two, and one guanosine at the 5\' end, referred to as 3G, 2G, and 1G RNA, respectively. The 1G RNA is preferentially selected for packaging, indicating that these 99.9% identical RNAs exhibit functional differences and highlighting the importance of TSS selection. Here, we demonstrate that TSS selection is regulated by sequences between the CATA/TATA box and the beginning of R. Furthermore, we have generated two HIV-1 mutants with distinct 2-nucleotide modifications that predominantly express 3G RNA or 1G RNA. Both mutants can generate infectious viruses and undergo multiple rounds of replication in T cells. However, both mutants exhibit replication defects compared to the wild-type virus. The 3G-RNA-expressing mutant displays an RNA genome-packaging defect and delayed replication kinetics, whereas the 1G-RNA-expressing mutant exhibits reduced Gag expression and a replication fitness defect. Additionally, reversion of the latter mutant is frequently observed, consistent with sequence correction by plus-strand DNA transfer during reverse transcription. These findings demonstrate that HIV-1 maximizes its replication fitness by usurping the TSS heterogeneity of host RNA Pol II to generate unspliced RNAs with different specialized roles in viral replication. The three consecutive guanosines at the junction of U3 and R may also maintain HIV-1 genome integrity during reverse transcription. These studies reveal the intricate regulation of HIV-1 RNA and complex replication strategy.