Oct 22, 2023
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Природная генетика, том 55,
Nature Genetics, том 55, страницы 268–279 (2023 г.) Процитировать эту статью
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Профилирование экспрессии генов выявило многочисленные процессы, изменяемые с возрастом, но как возникают эти изменения, в значительной степени неизвестно. Здесь мы объединили секвенирование зарождающейся РНК и иммунопреципитацию хроматина РНК-полимеразы II с последующим секвенированием, чтобы выяснить основные механизмы, вызывающие изменения экспрессии генов у старых мышей дикого типа. Мы обнаружили, что в печени 2-летнего возраста 40% элонгирующих РНК-полимераз останавливаются, что снижает продуктивную транскрипцию и искажает результаты транскрипции в зависимости от длины гена. Мы демонстрируем, что этот транскрипционный стресс вызван эндогенным повреждением ДНК и объясняет большинство изменений экспрессии генов при старении в большинстве постмитотических органов, в частности влияя на характерные пути старения, такие как восприятие питательных веществ, аутофагия, протеостаз, энергетический метаболизм, иммунная функция и клеточный стресс. устойчивость. Возрастной транскрипционный стресс эволюционно консервативен от нематод до человека. Таким образом, накопление стохастических эндогенных повреждений ДНК во время старения ухудшает базальную транскрипцию, что устанавливает возрастной транскриптом и вызывает дисфункцию ключевых путей, характерных для старения, раскрывая, как повреждение ДНК функционально лежит в основе основных аспектов нормального старения.
Старение характеризуется прогрессирующим молекулярным, клеточным и физиологическим упадком, что приводит к снижению жизнеспособности, возрастным заболеваниям и увеличению смертности. Поскольку многие процессы ухудшаются или изменяются с возрастом1, на удивление мало известно о функциональном статусе процесса базальной транскрипции при старении. Мозг пожилых крыс и плодовых мух производит меньше информационных РНК2,3, а межклеточные вариации транскрипции увеличиваются в некоторых тканях4,5,6, в то время как координация транскрипции между генами снижается с возрастом7. Однако транскрипция при старении в основном изучается в связи с изменениями экспрессии генов. Транскриптомика внесла значительный вклад в идентификацию многочисленных клеточных путей и процессов, влияющих на старение8,9,10. Хотя часть возрастных органоспецифичных изменений экспрессии генов можно объяснить транскрипционными факторами, микроРНК11,12, измененным составом типов клеток8,13 и эпигенетическими изменениями14,15, недавний метаанализ транскриптомики показал, что большинство сходств экспрессии генов у пожилых людей органы мыши не могут быть отнесены к этим известным регуляторным механизмам8.
Накопление повреждений ДНК было постулировано как основная причина нормального старения16,17 и вышеупомянутых транскрипционных фенотипов6,7,18,19, в основном основанных на сходстве с клетками, подвергшимися воздействию агентов, повреждающих ДНК, или преждевременном старении нарушений репарации ДНК, таких как синдром Коккейна и трихотиодистрофия. Эти состояния имеют дефекты в репарации, связанной с транскрипцией (TCR), что приводит к остановке активности РНК-полимеразы на повреждениях ДНК20, что позволяет предположить, что повреждение ДНК, блокирующее транскрипцию, также может быть вовлечено в нормальное старение. Хотя эндогенные повреждения ДНК, блокирующие транскрипцию, накапливаются при нормальном старении21,22,23,24,25, в настоящее время неясно, вызывают ли они значимые транскрипционные ответы. В этом исследовании мы проанализировали базальную транскрипцию, лежащую в основе изменений экспрессии генов у нормальных мышей дикого типа (WT), используя метод секвенирования зарождающейся РНК in vivo в сочетании с иммунопреципитацией хроматина РНК-полимеразой II (RNAPII) с последующим секвенированием (ChIP-seq) и конфокальная визуализация. Мы выявили сильное возрастное снижение транскрипции и искажение результатов транскрипции за счет накопления повреждений ДНК как общего фенотипа старения, вызывающего возрастные изменения транскрипции в целом, особенно влияющие на основные пути старения, определяющие продолжительность жизни.
Чтобы исследовать процесс транскрипции при нормальном старении, взрослым (15 недель) и старым (2 года) мышам-самцам дикого типа (n = 3 на группу) вводили однократную внутрибрюшинную инъекцию этинилуридина (ЕС), аналога уридина, который включен в состав во вновь синтезированную РНК in vivo26. Через пять часов после инъекции флуоресцентное окрашивание ЕС выявило снижение сигнала ЕС в 1,5 раза в старой печени (рис. 1а). Снижение охватывало всю печень, затрагивало почти все гепатоциты и не ограничивалось возрастной полиплоидизацией (рис. 1б). Поскольку снижение сигнала EU было пан-ядерным, за исключением ядрышек (рис. 1a), что указывает на снижение RNAPII-зависимой транскрипции, мы проверили, могут ли более низкие уровни RNAPII объяснить снижение транскрипции. Удивительно, но иммунофлуоресцентное окрашивание RNAPII с использованием тех же образцов печени показало увеличение в 1,4 раза, а не уменьшение в стареющей печени (рис. 1c и расширенные данные, рис. 1a). Инициация RNAPII и проксимальная пауза промотора, отмеченная фосфорилированием остатков серина 5 (ser5p) в C-концевом домене (CTD), существенно не различались (рис. 1d и расширенные данные, рис. 1b), что позволяет предположить, что активность промотора RNAPII в масштабах всего генома практически не изменяется с возрастом. Однако удлинение RNAPII, отмеченное фосфорилированием серина 2 CTD (ser2p), продемонстрировало 1,5-кратное увеличение (рис. 1e и расширенные данные, рис. 1c). Эти данные указывают на то, что базальная транскрипция изменяется в стареющей печени.
90% of RNAPII-dependent nascent RNA production were split into 3 equal bins from its TSS to the transcription termination site (TTS) and corresponding reads from nascent RNA and of RNAPII ChIP–seq mapped in each bin were compared between old and adult liver. Using clustering analysis, we identified genes that were transcriptionally upregulated or downregulated in aging over all bins both in nascent RNA and RNAPII ChIP–seq (Fig. 2f and Extended Data Fig. 3a–c), which reflect promoter regulation. To analyze whether the identified transcriptionally upregulated (n = 778) or downregulated (n = 394) genes are biologically relevant for aging, we used the Enrichr tool for gene set enrichment analysis (GSEA)27,28 to compare these gene signatures with the published aging perturbation database containing 34 mouse liver and 15 rat liver mRNA expression profiles. The transcriptionally upregulated and downregulated gene signatures closely resembled the published rodent liver aging profiles (Fig. 2g,h), indicating that promoter regulatory programs during aging are conserved across transcriptomics studies. In summary, the approximately 1.5-fold lower nascent RNA synthesis in old liver is not due to reduced promoter activity or RNAPII transition to elongation./p>20 kb (x axis) and percentage change between old and adult in EU-seq densities from TSS to 20 kb downstream (y axis) (n = 3,308). i, Percentage stalled RNAPII in gene bodies. The colors indicate the gene-length classes as in Fig. 2e. Data are the mean ± s.d. (10–22 kb: n = 662; 22–30 kb: n = 644; 30–50 kb: n = 788; 50–70 kb: n = 587; 70–110 kb: n = 643; and >110 kb: n = 646)./p>70 kb already comprised approximately 60% of the RNAPII-dependent nascent RNA pool (Extended Data Fig. 3e), long genes disproportionally contributed to reduced nascent RNA levels. The decrease in de novo RNA synthesis and increased RNAPII abundance in gene bodies entail longer residence times and lower transcriptional output of RNAPII. By quantifying the discordance between nascent RNA levels and total RNAPII occupancy (Extended Data Fig. 3f), we estimated an overall approximate 40% nonproductive RNAPII in gene bodies in 2-year-old liver in a gene-length-dependent fashion (Fig. 3i), which implies that they are stalled. Assuming that mouse hepatocytes have a similar number of RNAPII molecules per cell as cultured human fibroblasts33, we believe that the average 2-year-old mouse hepatocyte contains at any time >18,000 stalled RNAPII complexes during elongation (Extended Data Fig. 3g). In summary, liver aging is characterized by a gene-length-dependent, genome-wide loss of transcription elongation and increased RNAPII stalling./p>110 kb from the TSS to 10 kb upstream in Ercc1Δ/− MDFs 24 h after UVC irradiation compared to nonirradiated cells. Black line: >110 kb gene class from normal liver aging data. h, Bias (fraction) of sequencing reads mapping to the coding strand during WT aging from total RNAPII and RNAPII-ser2p ChIP–seq data across all genes (n = 3,809), short (10–22 kb, n = 512) and longest genes (>110 kb, n = 779). P < 0.0001, two-sided unpaired t-test compared to genes with gene length 1–10 kb, 3 mice per group. Data are the mean ± s.e.m. i, Bias (fraction) of sequencing reads mapping to the coding strand during WT aging from total RNAPII and RNAPII-ser2p ChIP–seq data through gene body (3 bins) in all genes and the longest genes (>110 kb, n = 779). Data are the mean ± s.e.m. j, Sequencing read density profiles of the Ghr gene from EU-seq, total RNAPII (all reads aggregated) and total RNAPII split in coding and template strand in WT adult (blue) and aged (red) liver. k, Phosphorylated ATM (red) and γH2A.X (green) in adult and aged mouse liver. Right, Fluorescence intensities shown as box and whisker plots. The center lines show the medians, the box limits mark the IQR, and the whiskers indicate the minimum and maximum values. P = 7.19752 × 10−27 (two-sided unpaired t-test). Counted nuclei: adult n = 313; old n = 315; n = 3 mice per group. Scale bar, 50 μm./p>265-kb long gene frequently downregulated in aged livers across numerous independent studies40, in Xpg−/− and Ercc1Δ/− mutant mice18,34 and in cell cultures exposed to UV light41. Ghr demonstrates a clear GLPT and increased RNAPII abundance across the gene body. We also noticed a 20% shift in reads toward the coding strand in aged livers (Fig. 4j), indicating that Ghr downregulation is the direct result of transcription-blocking lesions. DNA damage-induced RNAPII stalling causes noncanonical DNA damage checkpoint ATM phosphorylation in the absence of double-stranded DNA breaks42, which we also observed in aged livers (Fig. 4k), thereby further demonstrating frequent transcriptional stress in aging. Because the extent of coding strand bias corresponds with the expected level when extrapolated from UV-treated cells38, our data reveal that endogenous transcription-blocking lesions cause RNAPII stalling in a gene-length-dependent manner, which we designated age-related transcriptional stress./p>110 kb, P = 0.000482946). Data are the mean ± s.e.m. P values are from a two-sided unpaired t-test (old versus adult). d, Full transcript abundances (relative to adult) estimated by reads covering 3′UTR from EU-seq of all expressed genes (P = 0.048761825), short (10–22 kb) and long genes (>110 kb, P = 1.78654 × 10−6). Data are the mean ± s.e.m., P values are from a two-sided unpaired t-test. e, Significant overrepresented pathways in TShigh genes by IPA, KEGG, Reactome and GSEA-hallmarks classified by main process category (bold). Aggregated P values were obtained from a Fisher's exact test. See Supplementary Table 2 for detailed pathway information./p>1.5-fold first-to-last exon transcriptional loss in aging (n = 830), representing genes with high transcriptional stress levels (TShigh), for functional examination. Notably, we found a highly significant overlap with the overall profiles of six independent studies representing downregulated mRNAs after UVC-induced DNA damage (Supplementary Table 1), further supporting the link between transcription-blocking DNA lesions and age-related transcriptional stress. Functional examination identified several significantly overrepresented cellular pathways previously classified as hallmarks of aging1 (Fig. 5e and Supplementary Table 2), such as the nutrient sensing pathways IGF1, insulin, growth hormone and mTOR signaling, which are all known to influence life span1,44. Autophagy, the unfolded protein response and the endoplasmic reticulum stress pathway were also identified, linking transcriptional stress to loss of proteostasis. Furthermore, we found key energy metabolic processes such as oxidative phosphorylation and pyruvate metabolism, which were functionally reduced by transcriptional stress in the livers of Ercc1Δ/− mice26. Additional identified processes included immune factors, fatty acid metabolism and the NRF2 antioxidant pathway, which are all causally involved in life span and/or age-related diseases47,48,49,50. In conclusion, transcriptional stress appears to be a critical cause of deregulation of aging hallmark pathways and processes in WT aging mice./p>1 dataset of a tissue was present, the mean ± s.d. and aggregated P value (Fisher's exact test) are shown./p>8) was used for further analyses. Total RNA sequencing was performed as described elsewhere62. To selectively isolate EU-labeled nascent RNA, we used the Click-iT nascent RNA Capture Kit (cat. no. c10365, Thermo Fisher Scientific): biotin azide was attached to the ethylene groups of the EU-labeled RNA using Click-iT chemistry. The EU-labeled nascent RNA was purified using MyOne Streptavidin T1 magnetic beads. Captured EU-RNA attached on streptavidin beads was immediately subjected to on-bead sequencing library generation using the TruSeq mRNA Sample Preparation Kit v2 (Illumina) according to the manufacturer's protocols with modifications. The first steps of the protocol were skipped; directly on-bead complementary DNA (cDNA) was synthesized by reverse transcriptase (Super-Script II) using random hexamer primers. The cDNA fragments were then blunt-ended through an end-repair reaction, followed by dA-tailing. Subsequently, specific double-stranded barcoded adapters were ligated and library amplification for 15 cycles was performed. PCR libraries were cleaned up, measured on an Agilent Bioanalyzer using the DNA1000 assay, pooled at equal concentrations and sequenced per three in one lane on a HiSeq 2500./p>90% of all EU-seq reads are mapped to these genes). Ercc1Δ/− mice (k = 20, n = 2,430); Xpg−/− mice (k = 20, n = 3,842); UV-treated Ercc1Δ/− MDFs (k = 10, n = 1974); WT aging kidney (k = 20, n = 2,135); human tendon (k = 5, n = 773); C. elegans (k = 5, n = 2,872). To match WT aging EU-seq data with the corresponding RNAPII ChIP–seq data (generated from the same liver), the corresponding genes from the ‘all expressed genes’ gene set were also selected in the RNAPII ChIP–seq datasets. The intra-sample-specific background was determined by calculating the reads in the intergenic regions and proportionally removed. The overall background signal was subtracted using the DNA input samples. To biologically define the ‘all expressed genes’ (n = 3,970) in WT aging, we performed a k-mean clustering analysis combined with EU-seq and total ChIP–seq reads between adult and old samples. Under the criterion describes in Extended Data Fig. 3a, we defined the four main patterns found in k-mean cluster analysis as four biological groups: promoter-upregulated genes, n = 778 (EU-seq and RNAPII ChIP–seq level increased across three bins); promoter-downregulated genes, n = 394 (EU-seq and RNAPII ChIP–seq level decreased across three bins); GLPThigh genes, n = 914 (steep EU-seq level progressive decrease, steep RNAPII ChIP–seq level increase across three bins); remainder genes, n = 1,884 (mild EU-seq level progressive decrease, mild RNAPII ChIP–seq increase across three bins). To study the relationship between gene length and transcriptional stress phenotype, the expressed genes (n = 3,970) in WT mice were divided into six groups according to their length, each containing a similar number of genes: 10–22 kb (n = 662, average = 16.47 kb, median = 16.75 kb); 22–30 kb (n = 644, average = 26.87 kb, median = 26.94 kb); 30–50 kb (n = 788, average = 40.19 kb, median = 39.68 kb); 50–70 kb (n = 587, average = 59.18 kb, median = 59.02 kb); 70–110 kb (n = 643, average = 87.93 kb, median = 86.75 kb) and >110 kb (n = 646, average = 199.47 kb, median = 160 kb). In figures measuring gene class behavior, we first calculated the per gene the average signal from n = 3 mice followed by averaging the signal for all genes in the gene class./p>8 weeks, old is >14 months and age difference between young/adult and aged organs is >6 months (mouse, rat); human old is >56 years with at least an age difference of >12 years. We adopted a threshold FDR < 0.05. Aggregated P values for the main identified biological processes were calculated by combining the P values of the corresponding detected subpathways using Fisher's exact test./p>400-fold surplus of biotin for every incorporated EU in nascent RNA in the Click-iT reaction, the reaction is saturated or follows the same asymptote; (2) only one EU incorporation per RNA molecule is sufficient to isolate that specific molecule; (3) EU incorporation is a stochastic process in which the concentration of available EU in the total nucleotide pool linearly correlates with the distance between EU molecules in the nascent RNAs. If there is an EU availability difference between adult and old mice, it is expected that in short RNA species (≤300 nucleotides) the probability of at least one EU incorporation is significantly lower and thus we would empirically observe a lower percentage sequence read mapping to such small RNA species in aged liver. The process of EU incorporation was modeled into nascent RNA species by means of a Poisson process. Specifically, one can think of the number of EU incorporations into nascent RNA as a Poisson process not in time, as it is generally used, but in length as measured in nucleotides. Mathematically, if X(t) is a Poisson process then the probability that there is no event in a time interval (0,t) reads exp(-λt) where λ is the intensity of the Poisson process. Equally, the probability that there is at least one event in the time interval (0,t) is thus 1 − exp(-λt). For each RNA species in our specified RNA length classes identified in the EU-seq datasets, the probability that at least one EU has been incorporated was subsequently computed using the formula above. Clearly, since \(1 - {\mathrm{e}}^{ - {\textstyle{1 \over x}}} > 1 - {\mathrm{e}}^{ - {\textstyle{1 \over y}}}\) for all x < y, Poisson processes with higher intensity will necessarily exhibit a larger probability that at least one EU has been incorporated than Poisson processes of lower intensity. Three groups of RNA species were examined: (1) ≤300 nucleotides (number of RNA species n = 7,932); (2) between 1,000 and 3,000 nucleotides (number of RNA species, n = 1983); and (3) between 2,000 and 4,000 nucleotides (number of species, n = 1,802). The number of RNA species reflect the total number present in the Mus musculus genome database (Ensembl). The latter two classes, although still representing short RNA species, are incorporated as a positive control in which a difference, if there is 1.5-fold less EU available, is not expected. In all cases, the probability vectors were not Gaussian as calculated by Kolmogorov–Smirnov test; thus, for each fixed intensity of the underlying Poisson process, the median and interquartile range (IQR) for the probability that at least one EU is incorporated are calculated. Significance between 1.5-fold-apart intensities was calculated by the Mann–Whitney U-test./p>110 kb (red; n = 646). Data are mean ± SEM. P-value = 7.84163*10−22, two-sided unpaired t-test. e, The contribution (%) of each gene-length class to the total nascent RNA pool in adult samples. f, Calculation of the fraction of unproductive RNAPII complexes in aged liver. g, Estimation of the number of stalling RNAPII complexes in aged liver./p>110 kb). Data are mean ± SEM. Note that the strand bias is only present in MCF7 cells 1 hour after UVB treatment, when RNAPII is still stalled on DNA lesions and DNA repair is ongoing. After 6 hours, most of the stalled RNAPII has been removed from the DNA lesions. This shows that i) the protocol used is able to detect a bias towards the coding strand and therefore can be used to analyze aging samples, ii) the coding strand bias is a transient phenotype after UVB. Based on published amounts of coding strand bias after a known UVC-induced DNA lesion density38, we estimate that livers from wildtype aged mice display a coding strand bias fraction in the range of 0.05–0.10. b–f, Mean local DNA methylation coverage (b) and (c–f) local nucleotide composition status in template strands of 50 genes with that exhibit the highest coding strand bias in general. The intragenic intronic region is chosen with the highest coding strand bias (high strand bias loci). This loci gene set is compared t i) random selected intragenic loci of similar size: 6 times 50 random intronic locations in the template strand, and ii) the complete intronic transcriptome; all introns from transcriptome (including high strand bias locations). Average of n = 50 / group shown. Data are mean ± SD./p>
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