The role of DNA methylation modifiers in shaping the hematopoietic differentiation topology

造血分化是一个随机的过程，它确定性地提供多种不同的细胞类型。 固定频率。这些对立面通过一种分化的拓扑表示来协调：EVEN 如果每个干细胞的命运决定是随机的，那么地形的形状将决定 分化种群的频率。但是，差异拓扑是如何编码的？ DNA甲基化(DNAME)可能是形成分化拓扑结构的关键因素。DNAME是 最稳定遗传的表观遗传标记，因此是编码拓扑信息的有力候选者。 此外，人类的克隆性造血，一种构成重大拓扑破坏的状态，通常 涉及DNAME修饰物的体细胞突变，包括DNMT3A、TET2和IDH2。 为了研究DNA甲基化如何重塑分化拓扑结构，我们进行了单细胞RNAseq &gt；来自TET2、IDH2、DNMT3A突变和野生型小鼠的50,000个骨髓祖细胞。TET2淘汰赛结果显示 红系祖细胞数量减少，单核细胞祖细胞数量增加。值得注意的是，这 红系与单核细胞命运的决定偏差是由于早期未确定的造血干细胞启动中断所致。 此外，DNMT3A缺失会对甲基化(低甲基化)产生相反的影响，也会导致 相反的拓扑偏斜。这就提出了这样一个问题：随机和随机之间的机械联系是什么？ 全基因组的DNAME变化和确定性的拓扑偏斜(例如单核细胞与红系)。 我们假设全基因组DNAME的获得或丢失可能通过在基因组中的固有偏见来影响命运决定 Tf基序CpG富集区。事实上，我们对谱系定义转录因子(TF)结合基序的分析 研究发现，与单核细胞相比，红系细胞的CpG含量显著增加。 为了进一步探索这一假设，我们将检查Tf基序的DNAME对HSC启动的影响，使用 两种新的互补方法。首先，ATAC-SEQ与亚硫酸氢盐测序将同时进行 研究开放染色质对启动至关重要的位置及其甲基化状态。第二，要直接对接 DNAME和HSCs的转录状态，我们将应用联合单细胞亚硫酸氢盐测序和RNAseq， 在单细胞水平上，评估Tf结合基序DNAME和启动之间的相互作用。 为了进一步确定基序DNAME对转铁蛋白结合的影响，我们将评估红系和单核细胞转铁蛋白 使用芯片-亚硫酸氢盐-顺序与DNAME相关的绑定。从功能上检查漫反射绑定的影响 如果基序DNAME发生变化，我们将使用针对结合基序本身的引导RNA进行表观遗传编辑。 最后，为了研究人类HSC分化中的这一现象，我们将应用我们的新的单细胞多细胞。 联合捕获单细胞甲基组、转录本和基因的组学平台。因此，我们将比较 在同一个克隆造血的个体中，突变型和野生型HSCs的分化拓扑结构， 并确定DNAME在重塑人类HSC分化中的作用。

Hematopoietic differentiation is a stochastic process that delivers multiple distinct cell types at deterministically fixed frequencies. These opposites are reconciled through a topological representation of differentiation: even if the fate decision of each individual stem cell is stochastic, the shape of the landscape will determine the frequencies of the differentiated populations. However, how is the differentiation topology encoded? DNA methylation (DNAme) may be a key contributor to shaping the differentiation topology. DNAme is the most stably inherited epigenetic mark and therefore a strong candidate for encoding topological information. Moreover, clonal hematopoiesis in humans, a state that constitutes a significant topological disruption, often involves somatic mutations in modifiers of DNAme, including Dnmt3a, Tet2 and Idh2. To study how DNA methylation reshapes the differentiation topology we preformed single-cell RNAseq of >50,000 bone marrow progenitors from Tet2, Idh2, Dnmt3a mutated and wildtype mice. Tet2 knockout showed a decrease in erythroid-committed progenitors, and increase in monocyte-committed progenitors. Notably, this erythroid vs. monocyte fate-decision skew is caused by disruption in priming of early, uncommitted HSCs. Moreover, Dnmt3a deletion, which causes the opposite effect on methylation (hypomethylation), also results in opposite topological skews. This raises the question of what is the mechanistic link between stochastic genome-wide DNAme changes and deterministic topology skews (e.g. monocyte vs. erythroid). We hypothesize that genome-wide DNAme gain or loss may affect fate-decision through inherent biases in the TF motif CpG enrichment. Indeed, our analysis across lineage-defining transcription factor (TF) binding motifs uncovered that erythroid motifs show a marked enrichment in CpG content, compared with monocytic motifs. To further explore this hypothesis, we will examine the impact of DNAme of TF motifs on HSC priming, using two novel complementary approaches. First, ATAC-seq coupled with bisulfite sequencing will simultaneously study the sites of open chromatin critical to priming together with their methylation state. Second, to directly link DNAme and the transcriptional state of HSCs, we will apply joint single-cell bisulfite sequencing and RNAseq, to evaluate, at the single cell level, the interplay between TF binding motif DNAme and priming. To further define the impact of motif DNAme on TF binding, we will evaluate erythroid and monocytic TF binding in relation to DNAme using ChIP-bisulfite-seq. To functionally examine the impact of diffuse binding motif DNAme changes, we will apply epigenetic editing with guide RNAs targeting the binding motif itself. Finally, to examine this phenomenon in human HSC differentiation, we will apply our novel single-cell muti- omics platforms to jointly capture single-cell methylome, transcriptone and genotype. Thus, we will compare within the same individual with clonal hematopoiesis, the differentiation topology of mutant vs. wildtype HSCs, and define the role of DNAme in reshaping HSC differentiation in humans.