Article Online

Articles Online (Volume 23, Issue 6)

Original Research

A Co-essentiality Network of Cancer Driver Genes Better Prioritizes Anticancer Drugs

Kwanghwan Lee, Donghyo Kim, Inhae Kim, Juhee Lee, Doyeon Ha, Seongsu Lim, Eunjee Kim, Sin-Hyeog Im, Kunyoo Shin, Sanguk Kim

Diverse molecular networks have been extensively studied to discover therapeutic targets and repurpose approved drugs. However, it is necessary to select a suitable network since the performance of network medicine relies heavily on the completeness and characteristics of the selected network. Although a network using gene essentiality in cancer cells could be an effective platform for identifying anticancer targets, efforts to apply these networks to therapeutic applications have been limited. We constructed a phenotype-level network using co-essentiality relationships among genes from CRISPR screens across 769 cancer cell lines to discover therapeutic targets for diverse cancer types. By leveraging cancer driver genes and network propagation, we found that the co-essentiality network better prioritized anticancer targets and biomarkers and predicted more precise drug responses in cancer cells than other molecular networks. The co-essentiality network outperformed conventional molecular networks in drug repurposing and was validated in silico by clinical trial records. Notably, the co-essentiality network identified 30 repurposed drugs that the other networks have not yet covered, and we showcased three approved drugs repurposed for lung adenocarcinoma (atovaquone, eflornithine, and teriflunomide). Our study provides a novel network for precision oncology to improve the identification of therapeutic targets in specific cancers.
人们已广泛研究多种分子网络，以发现治疗靶点和进行已批准药物的再利用。然而，由于网络医学的性能在很大程度上依赖于所选网络的完整性和特性，因此选择一个合适的网络至关重要。尽管利用癌细胞基因必需性构建的网络可能是一个识别抗癌靶点的有效平台，但将这类网络应用于治疗的尝试仍然有限。 我们利用来自769种癌细胞系的CRISPR筛选数据，通过基因间的“共必需性”关系，构建了一个表型层面的网络，旨在为多种癌症类型发现治疗靶点。通过在该网络上利用癌症驱动基因和网络传播算法，我们发现，与其它分子网络相比，共必需性网络能够更好地优先筛选出抗癌靶点和生物标志物，并更精确地预测癌细胞的药物反应。 在药物再利用方面，共必需性网络也优于传统的分子网络，这一点通过临床试验记录进行了计算机模拟验证。值得注意的是，共必需性网络找到了30种其他网络未能覆盖的可再利用药物，我们重点展示了其中三种被重新用于治疗肺腺癌的已批准药物：阿托伐醌（atovaquone）、依氟鸟氨酸（eflornithine）和特立氟胺（teriflunomide）。 我们的研究为精准肿瘤学提供了一种新颖的网络工具，以改进特定癌症中治疗靶点的识别。

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Method

HGCPep: Hypergraph Deep Learning Identifies Cancer-associated Non-coding Peptides

Wentao Long, Zhongshen Li, Junru Jin, Jianbo Qiao, Yu Wang, Leyi Wei

A small peptide encoded by a non-coding RNA (ncRNA), known as a non-coding peptide (ncPEP), is emerging as a critical regulator and biomarker in cancer, holding immense promise for immunotherapy. However, the systematic identification of ncPEPs remains a challenge because existing computational methods typically analyze peptides based on sequence alone. Sequence-only analysis overlooks the fundamental biological principle that multiple distinct peptides can be translated from a single non-coding RNA transcript, thus sharing a common transcriptional origin. Here, we address this limitation by developing HGCPep, a deep learning framework that leverages hypergraphs to model these intrinsic relationships. In our model, each ncRNA is represented as a hyperedge connecting the set of peptides it encodes, thereby enriching peptide feature representations with transcriptional context. We demonstrate that HGCPep, which integrates a hypergraph neural network with a convolutional neural network, outperforms state-of-the-art methods in identifying cancer-associated ncPEPs. Furthermore, dimensionality reduction of the learned embeddings reveals distinct clustering of ncPEPs by cancer type, illustrating how the model effectively deciphers complex biological associations. Our work introduces a new method for ncPEP analysis and provides a powerful tool for discovering novel therapeutic targets in oncology. The dataset and source code of our proposed method can be found via https://github.com/Longwt123/HGCPep_Github.

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Method

iRUNNER: A Baseline Mutation Burden Regression for Identifying Gene Interaction Between Rare Variants for Diseases

Hui Jiang, Bin Tang, Kun Li, Liubin Zhang, Junhao Liang, Clara Sze-Man Tang , Paul Kwong-Hang Tam, Binbin Wang, Youqiang Song, Qiang Wang, Mulin Jun Li, Hailiang Huang, Miaoxin Li

Genetic interactions play a crucial role in elucidating the susceptibility and etiology of complex multifactorial diseases. Despite significant efforts to identify disease-associated nonlinear effects in genome-wide association studies, efficient methods for detecting the epistatic impact of rare variants remain lacking. In this study, we propose iRUNNER, a novel and powerful mutation burden test focused on analyzing the interaction effects of rare variants on a binary trait. In contrast to conventional association tests that compare cases with controls, iRUNNER evaluates the relative enrichment of rare variant interaction burden of pairwise genes in patients against its baseline, estimated by a recursive truncated negative-binomial regression model that leverages multiple genomic features from public databases. Extensive simulations demonstrate that iRUNNER outperforms existing epistasis tests in statistical power and maintains reasonable type I error rates even when population stratification exists in control samples. When applied to real datasets from five complex diseases, iRUNNER yielded substantial gains in gene–gene interaction detection. Notably, the majority of these signals were missed by alternative methods, especially in small- to medium-sized samples. Furthermore, we found that these identified gene pairs of each trait can form interconnected networks, which may provide valuable insights into the underlying molecular mechanisms. We have implemented iRUNNER as a module in our integrative platform KGGSeq (http://pmglab.top/kggseq/) that enables rapid testing of pairwise interactions among all possible non-synonymous rare coding variants within hours.
研究问题： 遗传交互作用（又称上位性或基因-基因交互作用）是人类复杂疾病遗传结构的重要组成部分。尽管已有大量研究致力于在全基因组遗传关联中识别疾病相关的非线性效应，但高效检测罕见变异遗传交互作用的方法仍然匮乏。现有方法在统计功效、计算效率方面存在明显不足。因此，开发一种能够高效、稳健地检测罕见变异基因-基因交互作用的新方法，是复杂疾病遗传学研究的迫切需求。 研究方法： 研究团队开发了一种新的统计检验方法iRUNNER，用于系统识别与复杂疾病风险相关的罕见变异基因-基因交互作用。该方法利用来自基因组聚集数据库（Genome aggregation database, gnomAD）的六种影响基因罕见突变数量的基因组特征（包括编码区长度、次要等位基因频率、GC含量等）作为预测变量，构建迭代截断负二项回归模型，以估计一般人群中（即非疾病风险关联下）成对基因间罕见变异交互负荷的“基线”水平。在此基础上，iRUNNER通过评估病例人群中所观察到的罕见变异交互负荷相对于该基线的富集程度，判断基因-基因对是否与疾病风险显著相关，实现对疾病相关基因-基因交互作用的统计检验。为全面评估该方法的性能，研究团队开展了广泛的模拟实验，并将其应用于五种真实复杂疾病数据集中进行实例验证。 主要结果： 1. 在不同样本量、次要等位基因频率阈值，甚至对照组存在群体分层的情况下，iRUNNER均能控制合理的I型错误率，具有良好的稳健性。 2. 在三种上位性疾病模型的多种模拟场景下，iRUNNER展现出优于现有7种交互作用检测方法的统计功效。 3. 应用于五种复杂疾病真实数据集中，iRUNNER发现了17对疾病风险相关的显著罕见变异基因交互作用，其中大多数信号被其他方法遗漏。 4. 每种疾病中，iRUNNER识别出的显著（或接近显著）基因对可以形成相互连接的基因网络，为揭示疾病分子机制提供线索。 5. iRUNNER已作为功能模块实现于KGGSeq/KGGSNV高通量测序数据下游综合分析平台中，可在数小时内完成外显子组范围内成对编码基因罕见变异交互作用的快速检测。 工具和代码链接： KGGSeq分析平台： http://pmglab.top/kggseq/ KGGSNV分析平台： http://pmglab.top/kggsnv/ 代码： https://github.com/pmglab/KGGSeq/ 或https://ngdc.cncb.ac.cn/biocode/tools/BT007786

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Method

CanID: A Robust and Accurate RNA-seq Expression-based Diagnostic Classification Scheme for Pediatric Malignancies

Daniel K Putnam, Alexander M Gout, Delaram Rahbarinia, Meiling Jin, David Finkelstein, Xiaotu Ma, Jinghui Zhang, David A Wheeler, Larissa V Furtado, Xiang Chen

Cancer subtype classification is critical for precision therapy, and there is a growing trend to augment histopathology testing with omics-based machine learning classifiers. However, analytical challenges remain in pediatric cancer regarding the scope and precision of current classifiers, as well as the evolving subtype standardization. To address these challenges, we constructed Cancer Identification (CanID), a stacked ensemble machine learning classification scheme, using transcriptomic features derived from gene-level RNA sequencing count data as the sole input. CanID was developed primarily from 3203 pediatric cancer samples across 13 solid tumor subtypes and 38 hematologic malignancy subtypes, with subtype labels curated without the use of RNA-seq data. The accuracies of independent testing in three independent or external datasets for solid tumors and hematologic malignancies were 99% and 92%–93%, respectively. Notably, CanID was able to classify subtypes challenging for clinical histology evaluation and was robust to both biological and technical challenges, including differences in data collection protocols, class imbalance, potential mislabeled training samples, and classes unobserved during training. The high accuracy, robustness, and biological interpretability of this transcriptome-based classification scheme represent a valuable approach to advance tumor diagnosis and clinically meaningful stratification of tumor types. CanID can be accessed on GitHub at https://github.com/chenlab-sj/CanID.
研究问题: 小儿肿瘤亚型分类是精准治疗与风险分层的关键,组学机器学习分类器正逐步补充传统组织病理学诊断。但现有方法存在分类范围窄、精度受限、亚型标准不断演变等问题:已有的 RNA-seq 分类器要么局限于 B-ALL 等单一谱系,要么仅适用于 poly(A) mRNA-seq 一种文库方案,难以应对真实场景中的批次效应、文库差异、标签噪声、类别不平衡,以及训练时未见过的稀有亚型。 研究方法: 研究团队构建了堆叠集成(stacked ensemble)分类框架 CanID,仅以蛋白编码基因的 RNA-seq 计数矩阵作为输入。流程包括:对 poly(A) 与 total RNA 协议敏感基因进行过滤、分位数归一化、冻结代理变量分析(fSVA)批次校正,以及 PCA 特征降维(实体瘤选 PCA80、血液肿瘤选 PCA85),再由 LDA、SVM、MLP、逻辑回归与随机森林五个基学习器组成集成,并以逻辑回归作为元学习器输出最终预测及置信度评分。模型主要基于 3203 例小儿肿瘤样本(13 种实体瘤亚型 + 38 种血液系统恶性肿瘤亚型)训练,亚型标签依据 WHO 标准与病理专家复核获得,完全不使用 RNA-seq 数据,从而避免循环论证。 主要结果: 1. 性能与精度: 在三个独立或外部数据集上,实体瘤分类准确率达 99%,血液系统恶性肿瘤达 92%–93%。与近期发表的同类方法 OTTER 相比,CanID 在敏感性与选择性上均更优(临床 pilot 队列中正确预测 19 例 vs OTTER 7 例,错误 0 例 vs 8 例)。 2. 跨平台与批次稳健性: 通过聚焦全局转录组模式的特征提取,CanID 在 poly(A) mRNA-seq 与 total RNA-seq 两种文库方案间均保持稳定;在不同基因组版本(hg19/hg38)、注释版本与比对工具组合下准确率达 1.0,展现出强可移植性。 3. 抗标签噪声与类别不平衡: 实体瘤模型可耐受约 30%、血液肿瘤模型约 20% 的训练标签噪声而精度基本不变。CanID 还识别出 TARGET 队列中被错误标注的样本 PAKLYZ——标签为横纹肌样瘤(RT),但拷贝数变异(17q 增益、1p 缺失、MYCN 扩增)、表达谱与既往表观遗传证据均支持其实为神经母细胞瘤(NBL),CanID 以 0.969 高置信度做出正确判断。 4. 疑难样本与开放集识别: 对"未特指"(NOS)样本,CanID 成功分类 36/52 例实体瘤与 555/779 例血液肿瘤;在横纹肌肉瘤 NOS 的 ARMS/ERMS 亚型判定上与病理专家完全一致,并经 PAX3/7–FOXO1 融合检测交叉验证。对训练集未包含的稀有亚型(开放集场景),CanID 能将约半数正确判为"不可分类",避免过度自信的错误归类。 5. 生物学可解释性: PCA 特征对应明确的生物学过程(GSEA 揭示免疫应答、肌源性分化、神经递质转运等通路),分类依据可追溯至肿瘤起源相关的生物学信号,而非黑箱判别。

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Brief Communication

On the Completeness of Existing RNA Fragment Structures

Xu Hong, Jian Zhan, Yaoqi Zhou

The success of protein structure prediction by the deep learning method AlphaFold 2 naturally raises the question of whether similar success can be achieved for RNA structure prediction. One reason for the success in protein structure prediction is that the structural space of proteins, from the fragment level to the domain level, has been nearly complete for many years. Here, we examined the completeness of RNA fragment structural space at the di-, tri-, tetra-, and penta-nucleotide levels. We show that the number of non-redundant structural fragments at the tetra- and penta-nucleotide levels is in the midst of exponential increase, suggesting that the structural space currently observed in RNA is far from complete. Thus, more concerted efforts are clearly needed to improve the speed and methods of experimental determination of RNA structures to go beyond the limited structural space observed in RNAs. Moreover, the reference frame composed of three sugar-ring atoms near the base side (O4′, C1′, and C2′) exhibits the least structural diversity among existing RNA structures, suggesting it as the most stable platform for building other parts of RNA structures.
研究问题： AlphaFold 2在蛋白质结构预测上的成功很大程度上归功于蛋白质片段结构空间的完备性。然而，对于RNA而言，其结构测定难度大，PDB库中RNA结构数量稀少（仅占3%）。本研究旨在回答一个关键问题：目前已知的RNA片段结构库是否足以支持像AlphaFold 2那样的高精度AI预测？即RNA的结构空间在二核苷酸至五核苷酸水平上是否已经达到了完备？ 研究方法： 研究团队从PDB数据库中提取了截至2024年初的高分辨率（<3.0 Å）RNA结构，去除了修饰残基和缺失残基，构建了二、三、四、五核苷酸的连续片段库。团队采用了六种不同的原子参考坐标系（包括纯骨架、纯碱基、纯糖环及混合表示）来定义结构相似性，并基于均方根偏差（RMSD）对片段进行聚类分析，统计随时间推移非冗余结构片段数量的增长趋势，从而评估结构空间的完备性。 主要结果： 1. 现有伪扭转角（pseudo-torsion angles）无法完全表征RNA结构多样性：即使伪扭转角几乎相同的片段，其全原子结构也可能存在显著差异（RMSD > 1Å）。 2. 最佳结构表征方式：包含两个骨架原子（C4’, P）和一个碱基原子（N1或N9）的混合参考系（M2S0B1）最能代表RNA的整体结构变化；而靠近碱基侧的糖环部分结构最为稳定。 3. 结构空间远未完备： 四核苷酸和五核苷酸水平的非冗余结构片段数量仍处于指数增长阶段，表明目前观测到的RNA结构空间距离完备还很遥远，这对AI预测提出了挑战。

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Brief Communication

A Human-specific Protein Regulated by Alternative Polyadenylation Shapes Uniqueness of Human Brain Development

Ting Li, Fan Mo, Jianhuan Qi, Chunqiong Li, Xiangshang Li, Jie Zhang, Yingfei Lu, Chao Yao, Li Zhang, Baoyang Hu, Chuan-Yun Li, Ni A An

Although new genes and regulatory events have been linked to the uniqueness of human brain development, it is unknown whether alternative polyadenylation (APA) also contributes to shaping this key feature that differentiates humans from other species. Here, we present an atlas of APAs of the human brain and identified 161 development-related, open-reading-frame-disrupting APAs associated with the dynamic translation of protein products. Among the genes affected by these events, we identified ZNF271P, which encodes a human-specific protein when using the distal polyadenylation site, a site that preferentially occurs during early brain development. The cortical organoids derived from ZNF271P-knockout human embryonic stem cells seemed to exhibit accelerated development and maturation, resulting in a significant decrease in organoid size, implicating that ZNF271P is involved in features unique to human brain development. We thus highlight APAs as new regulators in shaping the unique aspects of human brain development.
研究问题： 尽管已有文献报道新基因参与塑造人类大脑发育的独特性，但目前尚不清楚转录后调控事件，例如可变多聚腺苷酸化（Alternative polyadenylation, APA），尤其是上游APA（Upstream APA, UR-APA），是否也可能参与塑造人类大脑区别于其他物种的关键发育特征。 研究方法： 为了系统鉴定人脑发育过程中的APA事件，研究团队首先基于人脑的全长转录本测序数据，精准定位并构建了全基因组范围的polyadenylation （PA）位点参考图谱。在此基础上，将大量人脑短读长转录组测序数据与已构建的PA参考图谱进行比对分析，在全基因组范围内系统鉴定出与人类大脑发育相关且会破坏开放阅读框（Open reading frames, ORFs）的APA事件及相关基因。从上述关键基因集合中，研究团队聚焦ZNF271P基因，发现其使用远端PA位点时，会产生更长的转录本，并在其上编码一个人类特异的蛋白质产物。最后，研究团队在人胚胎干细胞中建立了ZNF271P敲除与回补细胞系，并将其诱导分化成为大脑皮层类器官，通过研究该过程中的表型变化，初步揭示了该基因在人脑发育中的调控作用。 主要结果： 1. 准确构建人类大脑APA图谱，鉴定出161个与人脑发育动态相关，且影响蛋白翻译的关键APA事件。多数事件表现出显著的物种特异性。 2. 以ZNF271P基因为例，发现其在使用远端PA位点时可编码一个人类特异性蛋白，且该调控事件主要发生在大脑发育早期。 3.人脑类器官研究揭示ZNF271P通过改变细胞命运维持神经祖细胞库，进而影响类器官成熟过程，与部分人脑特异性发育特征一致。

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Original Research

Regulation of Alternative Polyadenylation Events by PABPC1 Affects Erythroid Progenitor Cell Expansion

Yanan Li, Yanbo Yang, Bin Hu, Zi Wang, Wei Wang, Xiaofeng He, Xusheng Wu, Sheng Lin, Narla Mohandas, Hong Liu, Jing Gong, Long Liang, Jing Liu

Erythropoiesis is precisely regulated by multilayered networks. It is crucial for maintaining steady-state hemoglobin levels and ensuring effective oxygen transport. Alternative polyadenylation (APA) is a post-transcriptional regulatory mechanism generating multiple mRNA isoforms from a single gene based on specific 3′ untranslated region sequences. While APA plays a vital role in various cellular processes, the underlying mechanism in erythropoiesis remains largely unexplored. In this study, we employed an integrative approach, combining bioinformatics analyses and experimental validations, to systematically investigate the role of APA in erythropoiesis. We mapped the APA landscape during erythroid differentiation and identified significant APA shifts essential for the differentiation of erythroid cells from burst-forming unit erythroid (BFU–E) to colony-forming unit erythroid (CFU–E). Notably, our findings highlighted polyadenylate-binding protein cytoplasmic 1 (PABPC1) as the primary regulator of APA during these stages. Functional analyses have revealed that knockdown of PABPC1 disrupts erythroid progenitor cell proliferation and differentiation. These results implicate an essential role of PABPC1 in modulating cell fate through APA regulation. Furthermore, we found that decreased PABPC1 levels increased the usage of the proximal polyadenylation sites in the TSC22 domain family member 1 (TSC22D1) gene. This shift led to elevated expression of TSC22D1, uncovering a novel mechanism by which APA influences erythroid progenitor expansion and differentiation. Our findings provide novel insights into APA regulation in early erythropoiesis and suggest potential therapeutic strategies for diseases associated with erythropoietic disorders.
研究问题： 红系发育主要受转录调控、信号传导及各种表观遗传修饰等多种方式的调控，而针对其转录后调控的研究则相对有限。选择性多聚腺苷酸化（APA）是一种关键的转录后调控方式，APA的广泛存在不仅增加了转录本的复杂性，还可通过改变3’UTR长度影响mRNA的稳定性、定位与翻译。然而，目前对于红细胞分化过程中的全局APA动态规律及其在红细胞生成早期阶段的功能与机制尚不明确。 研究方法： 本研究利用计算生物学分析，鉴定了红系分化转录组数据中的APA事件，探究了红细胞生成不同阶段的全局APA模式，绘制了红系分化动态APA图谱。进一步，通过英国牛津纳米孔（Oxford Nanopore Technologies，ONT）三代全长转录组测序分析与实验验证相结合的方法，揭示了PABPC1介导的APA调控影响红系祖细胞扩增与分化的新机制。 主要结果： 1. APA动态在不同的红细胞生成阶段发挥着不同的功能作用，即早期红细胞生成阶段与细胞周期和RNA调控有关。 2. PABPC1是红系分化早期BFU-E到CFU-E阶段APA介导3’UTR 缩短的关键调控因子。 3. 在红系分化早期BFU-E到CFU-E的转变过程中，PABPC1通过调控特异性APA事件，主导红系祖细胞的增殖与分化平衡。 4. PABPC1通过APA机制调控TSC22D1的表达水平，进而影响红系祖细胞的扩增及分化进程。 数据链接或代码连接或其他： https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE61566 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc= GSE53983

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Original Research

Differential Evolution of CDS and UTR Non-canonical RNA G-quadruplex Structures in Eukaryotic Transcriptomes

Eugene Yui-Ching Chow, Jieyu Zhao, Chun Kit Kwok, Ting-Fung Chan

RNA G-quadruplexes (rG4s) are non-classical, four-stranded secondary RNA structures that play regulatory roles in various biological processes. Although canonical rG4s have been studied extensively, recent advancements have underscored the importance of non-canonical rG4s. In this study, we experimentally determined rG4 structures from multiple eukaryotic species. Bioinformatic analysis revealed that across 1 billion years of evolution, rG4s have comprised an integral feature of eukaryotic transcriptomes; additionally, non-canonical rG4s consistently were found to dominate the surveyed rG4omes. Over time, the overall size of the rG4ome has expanded progressively, accompanied by a notable compositional shift such that untranslated region (UTR) rG4s became favored over protein coding sequence (CDS) rG4s. Additionally, we observed distinct evolutionary patterns for CDS and UTR rG4s, which involved differential evolutionary origins and canonicality drift patterns. Our findings suggest that new UTR rG4 sequences emerge rapidly during early mammalian evolution, whereas the more gradual increase in CDS rG4s is linked to changes in selective amino acid residue preferences. This plausible theory accounts for both the prevalence of UTR rG4s and the emergence of canonical motifs in mammalian models. Access to all the rG4 structures identified in this study is available through the rG4-seq Database application at https://rg4s.science/.
RNA G-四链体（rG4）是一类调控基因表达的RNA结构。本研究发现，非经典rG4在多种真核模式生物中占主导，并在早期哺乳动物进化过程中于基因非翻译区快速扩增。结果提示，许多rG4可能在基因诞生后才被引入转录组，且其序列和位置保守性较低，体现动态演化特征。所有发现的rG4已整合至图形化应用 rG4-seq 数据库（https://rg4s.science）。

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Original Research

A Model for the Development of Alzheimer’s Disease

Zhenyu Huang, Xuechen Mu, Qiufen Chen, Lingli Zhong, Jun Xiao, Chunman Zuo, Ye Zhang, Bocheng Shi, Yingwei Qu, Renbo Tan, Long Xu, Renchu Guan, Ying Xu

Intracellular alkalosis and extracellular acidosis are well-established characteristics of Alzheimer’s disease (AD). We present a computational analysis and modeling of transcriptomic data of AD tissues, aiming to understand their causes and consequences. Our analyses have revealed that (1) persistent mitochondrial alkalization is due to chronic inflammation coupled with elevated iron and copper metabolisms; (2) the affected cells activate multiple acid-producing metabolisms to keep the mitochondrial pH stable for survival; (3) the most significant one is the continuous import and hydrolysis of glutamine to glutamate, N ⁠, and ⁠, resulting in persistent release of glutamate, an excitatory neurotransmitter, into the extracellular space; (4) this leads to persistent hyperexcitability of the nearby neurons, resulting in their continuous firing and release of -rich synaptic vesicles; (5) the is neutralized by bicarbonates released by the neighboring astrocytes in normal tissues, which could not keep up with the increased release of in their discharge rates of bicarbonates in AD tissues, leading to progressively increased extracellular acidosis and ultimately cell death; and (6) multiple extensively studied AD-associated phenotypes, including Aβ aggregates and tau fibers, are induced to help to alleviate the pH imbalances and beneficial to cell survival in the early phase of AD, which gradually become contributors to the AD development. Each step in this model is largely supported by published studies. Overall, we have developed a fundamentally novel and systems-level view of how AD may have evolved.
研究问题： 阿尔茨海默病（AD）的经典病理特征为Aβ沉积与Tau蛋白缠结，然而针对此二者的治疗策略收效甚微，提示其核心驱动因素尚未被完全阐明。本研究旨在超越传统认知，从化学稳态失衡的全新视角，探究驱动AD发生发展的根本机制。研究通过对不同阶段AD组织的转录组数据深度解析，探索细胞内持续性碱中毒与细胞外进行性酸中毒这一核心矛盾，如何引发系统性代谢重编程与病理变化，以构建一个能够统一解释AD复杂病因的创新理论模型。 研究方法： 本研究通过对不同发展阶段AD组织的转录组数据进行深度解析，结合计算生物学、计算化学、统计相关性分析与因果推断方法，构建并验证了一个全新的AD发生发展的演化模型。 主要结果： 1. 研究证实，AD早期神经元线粒体内存在持续性芬顿反应，该反应作为“内在碱源”导致细胞内发生持续性碱性化。 2. 为应对碱性压力，神经元通过激活谷氨酰胺酶水解谷氨酰胺成谷氨酸及H+等方式维持胞内pH稳定；此过程触发的Tau蛋白聚合也伴随H+释放。 3. 持续释放至突触间隙的谷氨酸会驱动邻近神经元进入超兴奋状态，进而形成了两个恶性循环，显著加剧细胞外酸中毒。 4. 研究提出Aβ淀粉样沉积是机体为抵抗细胞外酸中毒而产生的一种代偿性碱性反应，这为其病理角色给出了全新阐释。 5. 统计分析表明，细胞外酸中毒是导致AD晚期大规模神经元死亡的首要驱动因素，其贡献度显著高于Aβ淀粉样沉积本身。 数据链接或代码连接或其他： https://academic.oup.com/gpb/advance-article/doi/10.1093/gpbjnl/qzaf087/8262303

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Original Research

The High Expression of PD-1 Defines A Subpopulation of Tfh Cells Responding to COVID-19 Vaccine in Humans

Jingxin Guo, Zhangfan Fu, Yi Zhang, Mengyuan Xu, Jinhang He, Haocheng Zhang, Qiran Zhang, Jieyu Song, Ke Lin, Mingxiang Fan, Zhangyufan He, Guanmin Yuan, Ning Jiang, Huang Huang, Chao Qiu, Jingwen Ai, Wenhong Zhang

Inactivated coronavirus disease 2019 (COVID-19) vaccines and receptor-binding domain subunit (RBD-subunit) booster vaccination can induce effective humoral immune responses. CD4+ T helper cells are essential for helping B cells and antibody responses. However, the response of CD4+ T cells to booster vaccination, especially the virus-induced T follicular helper (Tfh) cells, needs to be better characterized. In this study, we investigated this response using single-cell sequencing and flow cytometry. Additionally, we employed a customized algorithm to identify virus-induced T cell receptors (VI-TCRs), enabling further exploration of the activation and persistence of virus-induced CD4+ T cell responses. We identified a subset of classic Tfh (cTfh) cells with high expression of PD-1 and IFN-γ. These cells were notably activated following booster vaccination, and their proportion was correlated with antibody titers. Trajectory analysis of activated cTfh cells revealed a subset of virus-induced cTfh cells that might maintain immune responses beyond 90 days post-vaccination. In summary, we identified a group of PD-1high cTfh cells induced by COVID-19 vaccination, which can enhance humoral responses and exhibit the long-term persistence against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We also developed a method for single-cell immune data analysis to understand virus-induced immune responses. Understanding how cTfh cells help antibody production will provide essential insights into the rational design of new vaccine strategies to optimize long-term immunity.

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Original Research

Macrophage Response to Avirulent and Virulent Mycobacterium tuberculosis and Anti-TB Effects of Exosome Treatment

Li Yang, Lingna Lyu, Cuidan Li, Xiuli Zhang, Yingjiao Ju, Ju Zhang, Jie Liu, Liya Yue, Nan Ding, Xiangli Zhang, Dandan Lu, Tingting Yang, Peihan Wang, Jie Wang, Xiaotong Wang, Sihong Xu, Yongjie Sheng, Chunlai Jiang, Jing Wang, Xin Hu, Bahetibieke Tuohetaerbaike, Zongde Zhang, Fei Chen

Tuberculosis (TB) has returned as the leading cause of death caused by a single infectious agent in 2023. Human macrophages and their secreted exosomes play important roles in combating invading Mycobacterium tuberculosis (Mtb). However, a comprehensive understanding of the mechanisms underlying immune regulation in Mtb-infected macrophages, as well as the packaging mechanisms and anti-TB effects of Mtb-treated exosomes, is still lacking. Here, we conducted comprehensive analyses of the macrophages infected with avirulent and virulent Mtb strains (H37Ra and H37Rv) and their exosomes through omics and phenotypic approaches. The results showed that H37Ra stimulated strong immune responses and apoptosis in macrophages to eliminate invading Mtb, while H37Rv induced severe necrosis and immune escape for survival. Interestingly, our results suggest that macrophages kill Mtb in an interferon-gamma (IFN-γ)-independent but compensatory way, highlighting the central role of IFN signaling pathway in anti-TB response. Moreover, we observed selective transport of host and Mtb RNAs from macrophages to exosomes. Notably, H37Ra-treated exosomes displayed a higher anti-TB effect than H37Rv-treated exosomes due to some enriched pro-inflammatory and immune escape-related Mtb proteins in these two exosomes, respectively. In conclusion, our findings shed new light on the immune mechanisms of macrophages in response to Mtb infection, offering a new TB treatment strategy and promising vaccine candidates.
研究问题： 2023年结核病再度成为全球单一传染病“头号杀手”。本研究通过多组学联合湿实验手段力图解答结核病（Tuberculosis，TB）两大核心问题：1. 作为人体 “第一道防线”的巨噬细胞，为何能快速清除结核分枝杆菌（Mycobacterium tuberculosis, Mtb）低毒株H37Ra，却对高毒株H37Rv束手无策？这种“同种不同命”的免疫差异机制何在？2. Mtb感染后，巨噬细胞所外泌体是如何选择性包裹特定RNA与蛋白来传递信号的？这些外泌体是否具备抗Mtb作用，又能否成为疫苗潜在候选抗原？ 研究方法： 采用目前全球实验室通用的结核分枝杆菌高毒株H37Rv和低毒株H37Ra感染人源巨噬细胞（THP-1诱导），24小时同步收集细胞及外泌体，进行RNA-seq 与蛋白组测序绘制差异表达图谱；辅以3-(4,5-二甲基噻唑-2-基)-2,5-二苯基四氮唑溴盐（3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide，MTT）、菌落形成单位（Colony-forming units， CFU）定量细胞活力与细菌负荷及细胞因子释放实验，来评估外泌体单独或联合IFN-γ的抗Mtb效能；最终，通过Ingenuity Pathway Analysis（IPA）通路富集与RBPmap基序分析，构建“感染-免疫-外泌体”多维调控网络图谱。 主要结果： 1．毒株不同，命运不同：低毒株H37Ra引发强烈免疫反应，活化更多凋亡通路、功能，杀灭Mtb；高毒株H37Rv引发强烈免疫逃逸，活化更多的细胞坏死、损伤等非程序性死亡通路和功能，促进Mtb的体内存活和免疫逃逸。 2．IFN-γ不是唯一“开关”：巨噬细胞在无IFN-γ诱导条件下，通过“模拟激活”机制自主启动干扰素通路抗结核。 3．外泌体选择性包裹：宿主与Mtb RNA通过特定RBP基序被选择性包装入外泌体，传递免疫信息。 4．外泌体的抗结核潜力与疫苗抗原候选物：H37Ra感染巨噬细胞产生的外泌体富含 Mmpl8、ESAT-6-like 等促炎/抗原蛋白，抑菌率显著优于H37Rv，为开发TB亚单位疫苗提供了候选抗原。

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Original Research

Unveiling Neonatal Pneumonia Microbiome by High-throughput Sequencing and Droplet Culturomics

Zerui Wang, Xin Cheng, Yibin Xu, Zhiyi Wang, Liyan Ma, Caiming Li, Shize Jiang, Yuchen Li, Shuilong Guo, Wenbin Du

Neonatal pneumonia is a leading cause of infant mortality worldwide; however, a lack of microbial profiling, especially of low-abundance species, makes accurate diagnosis challenging. Traditional methods can fail to capture the complexity of the neonatal respiratory microbiota, thereby obscuring its role in disease progression. Here, we describe a novel approach that combines high-throughput sequencing with droplet-based microfluidic cultivation to investigate microbiome shifts in neonates with pneumonia. Using 16S ribosomal RNA (rRNA) gene sequencing of 71 pneumonia cases and 49 controls, we identified 1009 genera, including 930 low-abundance taxa, which showed significant compositional differences between groups. Linear discriminant analysis effect size identified key pneumonia-associated genera, such as Streptococcus, Rothia, and Corynebacterium. Droplet-based cultivation recovered 299 strains from 94 taxa, including rare species and ESKAPE pathogens, thereby supporting targeted antimicrobial management. Host–pathogen interaction assays showed that Rothia and Corynebacterium induced inflammation in lung epithelial cells, likely via dysregulation of the PI3K-Akt pathway. Integrating these marker taxa with clinical factors, such as gestational age and delivery type, offers the potential for precise diagnosis and treatment. The recovery of diverse species can support the construction of a biobank of neonatal respiratory microbiota to advance mechanistic studies and therapeutic strategies.
研究问题 新生儿肺炎仍是全球婴儿死亡的主因之一。由于临床样本微生物载量低，传统培养方法难以检测低丰度病原菌，导致精准诊断面临巨大挑战。 研究方法 本研究收集71例肺炎患儿及49例对照进行高通量测序分析，并结合临床指标筛选潜在生物标志物。进一步利用液滴微流控技术高通量培养呼吸道细菌，并对分离菌株进行全基因组测序，同时开展宿主–病原互作分析及转录组研究。 主要结果 1. 高通量扩增子测序共鉴定出1009个属，其中低丰度属占比高达92.2%。Streptococcus、Rothia和Corynebacterium与肺炎显著相关，同时这些属与胎龄、分娩方式等临床因素密切相关，有望作为疾病诊断与干预的新靶标。 2. 利用液滴微流控技术成功分离出94种不同的细菌物种，包括ESKAPE多重耐药致病菌和多个罕见菌种。全基因组测序注释到与新生儿感染密切相关的抗生素耐药基因。 3. 宿主-病原互作实验表明，Rothia与Corynebacterium 可诱导肺上皮细胞发生炎症反应，可能与PI3K-Akt信号通路的失调相关。

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News and Views

Why Did Treg and Immune Tolerance Win Nobel Prize This Year?

Song Guo Zheng

no abstract
从1995年Shimon Sakaguchi首次鉴定出CD4⁺CD25⁺调节性T细胞（Treg），到2025年斯德哥尔摩钟声敲响，这群“少数细胞群体”终于登上了免疫耐受研究的中心舞台。本文以第一人称视角回顾Treg研究历程中的关键里程碑。每一个实验都在追问同一个问题：为什么免疫系统不会攻击自身？诺贝尔委员会同时授予天然Treg细胞的发现者（Shimon Sakaguchi）及其调控因子Foxp3基因点突变的发现者（Mary E. Brunkow和Fred Ramsdell）这一殊荣，不仅是在庆祝一段科学传奇，更是在宣告掌握Treg细胞，就等于拥有了治疗自身免疫病、移植排斥反应甚至肿瘤免疫逃逸的“万能遥控器”。

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Original Research

Multi-omics Analysis Reveals How Intratumoral Bacteria Shape the Immune Microenvironment in Gastric Cancer

Yang Mi, Die Dai, Xia Xue, Haiming Qin, Feifei Ren, Barry J Marshall, Alfred Tay, Ihtisham Bukhari, Xiaojie Li, Shaogong Zhu, Yong Yu, Wanqing Wu, Yan Tan, Youcai Tang, Xin Xie, Haiqing Bai, Xiaochen Yin, Pengyuan Zheng

The occurrence and progression of gastric cancer (GC) are closely associated with dysbiosis of the gastric microbiota and alteration in host microenvironments. However, the interaction between intratumoral bacteria and gastric microenvironments remains incompletely understood. In this study, we characterized the biological profiles of intratumoral bacteria, metabolome, and proteome in 20 GC tumors and paired non-tumor tissues, in combination with 6 independent datasets (comprising 477 gastric tissue biopsies and 534 normal tissues), as well as mucosal tissues from 10 individuals without GC. We found that the diversity and richness of gastric microbiota were significantly higher in tumor tissues than in non-tumor tissues. In contrast, the lowest biodiversity, at both the genus and species levels, was found in the microbiota of individuals without GC. Specifically, tumors were enriched with Bacteroides thetaiotaomicron, Lactobacillus parabrevis, Brevundimonas nasdae, and Brevundimonas vesicularis. We also identified 39 human immunity-related proteins, particularly in the tryptophan metabolic pathway, which were differentially expressed across various microenvironments (tumor and non-tumor). Furthermore, we found that several pathways involved in the human immune system and associated with the gastric microbiota, such as thiazole biosynthesis II, pyrimidine deoxyribonucleoside salvage, superpathway of pyrimidine deoxyribonucleoside salvage, and superpathway of heme biosynthesis from uroporphyrinogen-III, hold potential as biomarkers for early detection of GC. Our results provide a comprehensive framework for investigating the complex interactions between the tumor immune microenvironment and intratumoral bacterial community.
研究问题： 当前关于胃癌微生态的研究多聚焦于胃黏膜表面微生物，对肿瘤组织内部细菌的特征及功能探讨较少，且缺乏微生物群与宿主代谢组、蛋白质组的多维度整合分析。 研究方法： 本研究创新性地纳入20例胃癌肿瘤组织及配对非肿瘤组织，结合6个独立数据集（含497例胃组织活检样本及554例正常组织），同时纳入10例非胃癌个体的黏膜组织，构建了多队列、多维度的研究体系。 主要结果： 本研究系统阐明了胃部肿瘤内细菌群落、宿主代谢重编程（特别是色氨酸-犬尿氨酸通路）和免疫抑制微环境三者间的复杂互作，为理解胃癌发生提供了更全面的微生物学视角；差异菌群、关键代谢物（如犬尿氨酸）和免疫相关蛋白的鉴定，为未来开发胃癌的早期诊断生物标志物和新型治疗靶点（如调控菌群、阻断犬尿氨酸通路）奠定了重要基础；研究发现具有潜在关联的特定菌株，未来有可能被开发为新一代的益生菌制剂或基于菌群的创新药物，用于胃癌的预防或辅助治疗。 1. 首次明确肿瘤组织内胃微生物群的多样性和丰富度显著高于非肿瘤组织，且非胃癌个体微生物群在属和种水平上生物多样性均较低 2. 筛选出了拟杆菌属、副干酪乳杆菌、纳斯达短波单胞菌、泡囊短波单胞菌等肿瘤富集菌 3. 犬尿氨酸代谢物在肿瘤组织中显著富集，进而影响宿主免疫系统中的色氨酸代谢，并导致相关代谢物的变化，这可能与肿瘤的发生和发展有关 数据链接或代码链接或其他： 数据链接： https://ngdc.cncb.ac.cn/bioproject/browse/PRJCA042633 代码链接： https://ngdc.cncb.ac.cn/biocode/tools/8049

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Original Research

Deep Transfer Learning Links Benign Glands to Prostate Cancer Progression via Transcriptomics

Justin L Couetil, Ziyu Liu, Chao Chen, Ahmed K Alomari, Kun Huang, Jie Zhang, Travis S Johnson

The field effect describes the phenomena where environmental exposures, infection, and genetic predisposition result in molecular changes in cells that predispose them to developing cancer. Though this is a well-established concept in pathology, it remains underexplored in the context of high-resolution omics. We utilized the Diagnostic Evidence Gauge of Single Cells (DEGAS) deep transfer learning framework to analyze prostate cancer spatial transcriptomics to identify cells and tissues that are highly associated with cancer progression. DEGAS highlighted morphologically benign glands with reduced expression of microseminoprotein-beta (MSMB), a differentiation marker downregulated in aggressive tumors. These glands have upregulated genes associated with antigen presentation and aggressive neoplasms. Integration of single-cell transcriptomics and deep learning image analysis separately revealed altered immune-cell infiltration, suggesting a complex interplay in the tumor environment, facilitating aggressiveness. We used immunohistochemistry to quantify the MSMB protein (PSP-94) expression in morphologically normal and tumor tissues from patients with and without 5-year distant metastasis. Samples from patients who developed metastasis consistently showed lower fractions of positively stained cells, indicating a subtle yet significant “field effect” in seemingly benign regions. These proteomic results validate the transcriptomic findings and further underscore that inflammatory or immune-related changes in ostensibly normal tissue may contribute to aggressive disease progression.

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Original Research

Proteome and Phosphoproteome of Tomato Fruit Identify REDUCED CHLOROPLAST COVERAGE 1a as A Ripening

Jinjuan Tan, Zhongjing Zhou, Hanqian Feng, Jiateng Zhang, Ruikai Zhang, Zhongkai Chen, Yujie Niu, Fangyu Liu, Zhiping Deng

Fruit ripening in tomato (Solanum lycopersicum) has been extensively studied at the transcriptomic level. However, comprehensive profiling of the tomato fruit proteome and phosphoproteome remains limited. In this study, we performed large-scale proteome and phosphoproteome profiling of tomato (Ailsa Craig) fruits across five ripening stages using tandem mass tags (TMT)-based quantitative proteomics. Our analysis quantified over 8800 proteins and 20,000 high-confidence phosphorylation sites. Ripening-associated phosphorylation and dephosphorylation events were identified in diverse ripening regulators, including transcription factors, ethylene biosynthesis and signaling proteins, and epigenetic modifiers. Weighted gene co-expression network analysis (WGCNA) revealed a tetratricopeptide repeat protein, REDUCED CHLOROPLAST COVERAGE 1a (REC1a), as a key regulator of fruit ripening. Parallel reaction monitoring (PRM)-based targeted proteomic analysis validated the expression profiles of REC1a and its three phosphorylation sites. Clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9)-mediated knockout of REC1a resulted in reduced lycopene accumulation and slower chlorophyll degradation, highlighting its role in the chloroplast-to-chromoplast transition, which is critical for fruit pigmentation during ripening. Quantitative proteomic analyses of rec1a mutants demonstrated reduced levels of Clp proteases and chaperones, proteins known to regulate plastid transitions. Additionally, co-immunoprecipitation and split-luciferase complementation assays revealed that REC1a interacts with the eukaryotic translation initiation factor subunits eIF2α and eIF2Bβ, suggesting its role in regulating protein synthesis during ripening. This study provides the most comprehensive quantitative proteome and phosphoproteome atlas of tomato fruits to date and identifies REC1a as a regulator of fruit ripening, offering new insights into the underlying molecular mechanisms.

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Original Research

Crosstalk Between Lysine Lactylation and Acetylation Regulates Lactate Dehydrogenase in Streptococcus mutans

Qizhao Ma, Tao Hu, Yongwang Lin, Jing Li, Jun Huang, Qiong Zhang, Tao Gong, Xuedong Zhou, Lei Lei, Jing Zou, Yuqing Li

Post-translational modifications (PTMs) provide essential fine-tuning of protein functions in response to environmental changes. Among the PTMs, lysine acetylation (Kac) and the recently identified lysine lactylation (Kla) play crucial roles in metabolic regulation, as lactate and acetyl-CoA (Ac-CoA) are generated from pyruvate at the end of glycolysis. However, their crosstalk and regulatory mechanisms remain largely unknown, particularly in prokaryotes. Here, we investigated the intricate interrelation between Kla and Kac in the cariogenic bacterium Streptococcus mutans, a prolific producer of lactate. We conducted a comprehensive profiling of Kla and Kac, revealing their widespread distribution in glycolytic enzymes. Lactate dehydrogenase (LDH), the terminal enzyme of glycolysis, exhibited dynamic Kla and Kac shifts in line with glycolytic intermediates, with the Kla/Kac ratio reflecting the metabolic influx. Furthermore, ActA was pinpointed as a dual-function acyltransferase that catalyzes the Kla and Kac of LDH, both of which negatively regulate its enzymatic activity. Importantly, the study identified lysine 307 (K307) on LDH as a critical site, with its acylation significantly altering LDH activity, thereby affecting lactate production and bacterial growth. Our insights into the metabolic regulation mediated by Kla and Kac contribute to understanding the metabolism-PTM-metabolism feedback loop, allowing bacteria to fine-tune their metabolism in response to the availability of metabolic intermediates.
要点介绍 研究问题： 蛋白质翻译后修饰（PTMs）如何与代谢状态相互作用？新近发现的赖氨酸乳酰化（lysine lactylation, Kla）是否与经典的赖氨酸乙酰化（lysine acetylation, Kac）在细菌中存在功能“串扰”？Kla和Kac是否共同调控核心代谢酶的活性与代谢流向？ 研究方法： 1. 以致龋菌变异链球菌为模型，构建全蛋白Kla/Kac双修饰谱，结合GO/KEGG富集与蛋白互作网络分析，定位潜在的代谢关键节点。 2 模拟糖酵解过程，动态监测胞内/外乳酸、La-CoA与Ac-CoA水平、LDH活性及LDH的Kla/Kac变化。 3 构建体外酰化体系，鉴定ActA作为双功能酰基转移酶，催化LDH的Kla/Kac； 4. 体外构建LDH点突变重组蛋白，筛选鉴定Kla/Kac关键位点。 5. 通过CRISPR-Cas9在菌体内构建ldh K307Q/K307R位点突变菌株，解析关键位点对酶活/产酸/生长的影响。 主要结果： 1. Kla/Kac在变异链球菌内普遍存在且高度重叠，并在糖酵解通路中高度富集；越靠近通路末端的酶，越易出现多位点双修饰。 2. LDH同时受Kla/Kac调控，两种修饰随糖酵解进程与代谢物水平动态变化，均可降低LDH活性并限制乳酸过量生成。 3. ActA是催化LDH发生Kla/Kac的双功能酰基转移酶；其修饰程度受La-CoA/Ac-CoA供体浓度影响。 4. K307为LDH发生Kla/Kac“串扰”的关键位点；K307Q（模拟酰化）显著降低LDH活性与乳酸生成并减缓生长；K307R（模拟去酰化）接近或略优于野生型。 5. 提出“代谢-PTM-代谢”反馈调节模型：中间代谢产物→驱动Kla/Kac→调节代谢酶活性→反过来重塑代谢通量，实现对环境变化的快速响应。

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Original Research

Genomic Insights into Hybridization and Speciation of Mitten Crabs in the Eriocheir Genus

Jun Wang, Xin Hou, Xiaowen Chen, Roland Nathan Mandal, Nusrat Hasan Kanika, Chunhong Yuan, Yongju Luo, Chenghui Wang

Hybridization is a prominent and influential phenomenon with significant implications for adaptive evolution, species distribution, and biodiversity. However, the intricacies of how hybridization influences genomic structure and facilitates adaptive evolution remain poorly understood. By analyzing whole-genome data from seven populations within the Eriocheir genus across diverse geographic regions, we validated a complex hybridization history between Chinese and Japanese mitten crabs. This hybridization gave rise to two distinct ecological species: Hepu and Russian mitten crabs with unique genomic architectures and adaptations. Genes related to reproduction, development, and temperature adaptation exhibited divergent selection signals, potentially contributing to their phenotypic diversity and ecological niches. Meanwhile, genes associated with reproduction, namely Birc6, Bap31, and Poxn, displayed robust evidence of selective sweeps in Hepu mitten crab. Notably, the favored alleles for these genes originated from the parental lineages during the hybridization process. Furthermore, Hepu mitten crab is a homoploid hybrid species that originated from an ancient hybridization event, resolving its longstanding taxonomic controversy. Our study sheds light on the evolutionary history of mitten crabs and highlights the crucial role of hybridization in driving adaptation, range expansion, and diversification within the Eriocheir genus.
研究问题： 杂交是生物学领域中一种具有深远影响的现象，对物种生态分布格局的塑造、适应性进化的推动以及生物多样性的形成均发挥关键作用。然而，杂交如何影响物种基因组结构并促进适应性进化的具体机制仍未被完全揭示。绒螯蟹属（Eriocheir）包含中华绒螯蟹（Eriocheir sinensis）、日本绒螯蟹（Eriocheir japonica）与合浦绒螯蟹（Eriocheir hepuensis）三个主要类群，然而由于三者在形态上相似且分子遗传学证据有限，导致学界难以明确界定它们的分类地位。其中，合浦绒螯蟹的分类争议尤为突出，关于其属于杂交种、独立物种还是日本绒螯蟹的亚种一直存在争论。中华、日本和合浦绒螯蟹自然分布在不同的地理区域，三者具有明显的表型和遗传差异。值得注意的是，分布于俄罗斯符拉迪沃斯托克（海参崴）水域的绒螯蟹，以及中国南方闽江流域等的绒螯蟹，前期研究推测是通过自然杂交形成的种群。同时，中华绒螯蟹是一种具有较高经济价值的水产甲壳动物，在中国广泛养殖，不同水系绒螯蟹具有较明显的生物学特性差异。鉴于绒螯蟹属存在的分类争议、复杂杂交现象及重要经济价值，深入探究其分类地位、杂交历史与适应性演化规律，具有重要的理论意义与应用价值。 研究方法： 本研究以绒螯蟹属7个地理种群的139个个体为对象，首先测定其核心表型与繁殖性状，量化不同水系种群在表型及繁殖特性上的差异；其次基于群体重测序数据，开展系统进化分析、群体遗传结构解析、有效群体大小评估及基因流检测，进而明确该属地理分布格局，揭示其复杂杂交与演化历史；同时完成日本绒螯蟹与合浦绒螯蟹参考基因组拼接，并结合中华绒螯蟹染色体水平参考基因组及其他代表性甲壳动物基因组，通过单拷贝直系同源基因估算三者的物种分化时间；最后通过群体基因组的遗传分化、遗传多样性分析及自然选择信号检测，鉴定出驱动绒螯蟹种群适应性进化的关键功能基因。 主要结果： 1. 绒螯蟹群体基因组分析表明中华绒螯蟹和日本绒螯蟹间存在复杂的杂交历史。 2. 中华绒螯蟹与日本绒螯蟹分别向南北方向扩散，在地理分布上形成两个独立杂交区，进而演化出俄罗斯绒螯蟹与合浦绒螯蟹两个生态杂交种，且这两个杂交种在表型特征与遗传组成上均表现出显著差异。 3. 与繁殖习性、脂类代谢、温度适应及肌肉发育等相关的基因在中华和日本绒螯蟹以及俄罗斯和合浦绒螯蟹之间均检测到强烈的自然选择信号，这些受选择基因可能是推动各类群适应特定生态环境的关键遗传因素。 4. 合浦绒螯蟹中，Birc6、Bap31、Poxn 等繁殖相关基因呈现强烈自然选择信号，且其基因序列特征与中华绒螯蟹、日本绒螯蟹亲本存在显著差异。 5. 合浦绒螯蟹为中华绒螯蟹与日本绒螯蟹杂交起源的同倍体杂交种，该结论不仅为物种杂交成种机制提供新例证，更解决了合浦绒螯蟹分类地位长期存疑的争议。 原始数据链接：https://ngdc.cncb.ac.cn/gsa/browse/CRA013348 原始数据链接：https://ngdc.cncb.ac.cn/gwh/Genome/231936/show

Page qzaf079

Original Research

A Telomere-to-telomere Diploid Reference Genome and Centromere Structure of the Chinese Quartet

Bo Wang, Peng Jia, Stephen J Bush, Xia Wang, Yi Yang, Yu Zhang, Shijie Wan, Xiaofei Yang, Pengyu Zhang, Yuanting Zheng, Leming Shi, Lianhua Dong, Kai Ye

Recent advances in sequencing technologies have enabled the complete assembly of human genomes from telomere to telomere (T2T), resolving previously inaccessible regions such as centromeres and segmental duplications. Here, we present an updated, higher-quality, haplotype-phased T2T assembly of the Chinese Quartet (T2T-CQ), a family cohort comprising monozygotic twins and their parents, generated using high-coverage Oxford Nanopore Technologies (ONT) ultralong and PacBio high-fidelity (HiFi) sequencing. The T2T-CQ assembly serves as a crucial reference genome for integrating publicly available multi-omics data and advances the utility of the Quartet reference materials. The T2T-CQ assembly scores highly on multiple metrics of continuity and completeness, with Genome Continuity Inspector (GCI) scores of 77.76 (maternal) and 76.41 (paternal), 21-mer quality values (QVs) > 66, and Clipping Reveals Assembly Quality (CRAQ) scores > 99.6 for both haplotypes, enabling complete annotation of centromeric regions. Within these regions, we identified novel 13-mer higher-order repeat patterns on chromosome 17 which exhibited a monophyletic origin and emerged approximately 230 thousand years ago. Overall, this work establishes an essential genomic resource for the Han Chinese population and advances the development of a T2T pan-Chinese reference genome, which will significantly enable future investigations both into population-specific structural variants and the evolutionary dynamics of centromeres.
研究问题： 人类基因组端粒到端粒（T2T）完整组装，是破解复杂重复区域结构和功能的关键，但现有T2T参考基因组仍存在人群代表性不足的问题，中国人群高精度二倍体T2T参考基因组构建、着丝粒结构解析及演化规律仍有待阐明。本研究依托中华家系1号（Chinese Quartet）独特材料，构建高质量T2T二倍体参考基因组，并系统解析着丝粒区域结构特征与演化动态。 研究方法： 本研究整合超高深度Oxford Nanopore Technologies（ONT）超长读长测序（> 100kb）与PacBio HiFi测序数据，采用Verkko、hifiasm工具在trio binning模式下完成初始组装，经基因组补洞、结构变异校正与人工核验获得最终T2T组装版本（T2T-CQ）；通过对着丝粒α-卫星区域精细注释、跨人群基因组比对、系统发育分析与分子钟估算，解析新型高阶重复序列（HOR）的分布特征与起源演化；同时利用家系内同卵双胞胎数据评估不同组装工具在着丝粒区域的稳健性。 主要结果： 1. 获得连续性与完整性优异的二倍体T2T组装，母本单倍型和父本单倍型的GCI分别达到77.76和76.41，21-mer QV均大于66，contig N50均超过155Mb，填补了此前中华家系基因组的剩余缺口。 2. 完成着丝粒区域完整注释，在17号染色体鉴定出欧洲人群T2T-CHM13参考基因组中缺失的新型13-mer HOR模式。 3. 跨人群分析显示该新型HOR模式在全球广泛分布，并非汉族特有；系统发育分析证实其为单系起源，分子钟估算约于23万年前出现。 4. 组装工具评估显示，主流工具在着丝粒区域的组装误差最大不超过300 kb，远小于自然单倍型间的Mb级遗传差异，可支撑高质量遗传变异研究。

Page qzaf118

Original Research

YanHuang Paternal Genomic Resource Suggests A Weakly-differentiated Multi-source Admixture in the Formation of Han Founding Ancestral Lineages

Zhiyong Wang, Kaijun Liu, Haibing Yuan, Shuhan Duan, Yunhui Liu, Lintao Luo, Xiucheng Jiang, Shijia Chen, Lanhai Wei , Renkuan Tang, Liping Hu, Jing Chen, Xiangping Li, Qingxin Yang, Yuntao Sun, Qiuxia Sun, Yuguo Huang, Haoran Su, Jie Zhong, Hongbing Yao, Libing Yun, Jianbo Li, Junbao Yang, Yan Cai, Hong Deng, Jiangwei Yan, Bofeng Zhu, 10K_CPGDP Consortium, Kun Zhou, Shengjie Nie, Chao Liu, Mengge Wang, Guanglin He

The revolution in large-scale human genomics and advancements in statistical methods have profoundly refined our understanding of genetic diversity and structure within human populations. Y-chromosome variations, with their distinct evolutionary characteristics, play crucial roles in reconstructing the origins and interactions of ancient East Asian paternal lineages. We launched the YanHuang cohort employing a high-resolution capture sequencing panel to explore the evolutionary trajectory of Han Chinese, one of the world’s largest ethnic groups. We generated paternal genomic data for 5020 Han Chinese individuals across 29 Chinese administrative regions. We observed that multiple founding paternal lineages originating from ancient western Eurasia, Siberia, and East Asia contributed significantly to the Han Chinese gene pool. We identified fine-scale paternal genetic structures shaped by interactions among ancient populations and geographic barriers like the Qinling-Huaihe line and the Nanling Mountains. These structures reflect both isolation-enhanced and admixture-driven genetic differentiation, underscoring the complexity of Han Chinese genomic diversity. We observed a strong correlation between the frequency of multiple founding lineages and subsistence-related ancestral sources, including western pastoralists, Holocene Mongolian Plateau populations, and ancient East Asians. This relationship highlights the impact of ancient migrations and admixture on Chinese paternal genomic diversity. We introduced the Weakly-Differentiated Multi-Source Admixture model to clarify the intricate interactions among multiple ancestral sources influencing the Han Chinese paternal landscape. This study provides a comprehensive uniparental genomic resource from the YanHuang cohort, proposes a novel admixture model, and delineates the complex genomic landscape shaped by ancient herders, hunter-gatherers, and farmers integral to Han Chinese ancestry.
研究问题： 人类Y染色体具有单倍型遗传与非重组的特性，这些特性使其成为解析人类演化历史、助力法医学父系生物地理溯源和复杂家系排查的独特分子遗传标记。受限于东亚古基因组数据的时空覆盖度不足，人类精细演化历史的重建仍面临挑战，而高质量Y染色体数据可有效弥补这一缺陷。然而，现有的高质量Y染色体基因组资源在全球人群中分布不均，这一现象在东亚人群中尤为突出。汉族作为全球人口数量最多的单一民族，拥有复杂多源融合的演化历史及独特的民族、文化特征，但针对该民族大规模系统性Y染色体研究仍显不足，对其父系精细遗传背景、演化驱动力解析及演化模型构建尤为欠缺。 研究方法： 本研究旨在通过构建汉族高覆盖度Y染色体靶向捕获测序基因组数据库（炎黄基因组资源），完善中国人群父系演化框架。基于自主研发的高分辨率SNP分型体系（YHseqY3000），对来自中国29个省份的5,020例汉族男性个体进行了Y染色体靶向捕获测序。随后，整合主成分分析、系统发育树和群体遗传结构建模等多维度群体遗传学分析方法，系统评估了汉族群体的遗传多样性分布模式、空间遗传结构特征及历史演化动态。同时，精细化解析了古今东亚人群的Y染色体支系频率，并结合遗传多样性和分化指数等量化指标，揭示了汉族人群的父系遗传多样性模式及其形成的演化机制。 主要结果： 本研究基于炎黄基因组资源，构建了包含1,899种单倍型和1,766个末端单倍群的精细化谱系数据库。从基因组角度系统地证实了汉族存在北方、南方与岭南三大父系遗传亚群，其地理分界与秦岭-淮河线、南岭山脉等自然屏障呈现显著的空间对应关系。Fisher精确检验和Mantel相关性检验显示，单倍群O1a、O1b、C2a以及C2b的频率梯度变异是亚群分化的关键遗传基础。通过整合常染色体基因组多样性、东亚人群精细遗传背景与古DNA父系特征，并在常染色体和Y染色体层面联合建模，本研究提出了汉族人群父系遗传结构形成的“弱分化-多祖源混合”模型：新石器时代晚期，多个遗传分化较弱但具有地域特异性的祖先群体在不同地区发生了差异性的混合，进而塑造了各地汉族人群之间不同的遗传多样性模式。该研究阐明了不同地区汉族与周边人群的遗传互动，揭示了汉族群体历史演化动态，为东亚人群遗传多样性研究提供了关键数据和演化模型，也为人类迁徙与混合历史提供新的见解。

Page qzaf049

Review Article

High-quality Population-specific Haplotype-resolved Reference Panel in the Genomic and Pangenomic Eras

Qingxin Yang, Yuntao Sun, Shuhan Duan, Shengjie Nie, Chao Liu, Hong Deng, Mengge Wang, Guanglin He

Large-scale international and regional human genomic and pangenomic resources derived from population-scale biobanks and ancient DNA sequences have provided significant insights into human evolution and the genetic determinants of complex diseases and traits. Despite these advances, challenges persist in optimizing the integration of phasing tools, merging haplotype reference panels (HRPs), developing imputation algorithms, and fully exploiting the diverse applications of post-imputation data. This review comprehensively summarizes the advancements, applications, limitations, and future directions of HRPs in human genomics research. Recent progress in the reconstruction of HRPs, based on over 830,000 human whole-genome sequences, has been synthesized, highlighting the broad spectrum of human genetic diversity captured. Additionally, we recapitulate advancements in 56 HRPs for global and regional populations. The evaluation of imputation accuracy indicated that Beagle and Glimpse are the most effective tools for phasing and imputing data from genotyping arrays and low-coverage sequencing, respectively. A critical strategy for selecting an appropriate HRP involves matching the population background of target groups with HRP reference populations and considering multi-ancestry or homogeneous genetic structures. The necessity of a single, integrative, high-quality HRP that captures haplotype structures and genetic diversity across various genetic variation types from globally representative populations is emphasized to support both modern and ancient genomic research and advance human precision medicine.
在基因组学和泛基因组学迅速发展的背景下，大规模国际性和区域性的人类基因组及泛基因组资源的涌现，为解析人类演化历史及复杂性状和疾病的遗传基础提供了重要见解，并衍生出大量单倍型参考面板（Haplotype Reference Panels, HRP）的构建与应用。尽管近年来HRP相关研究取得了显著进展，但在定相（Phasing）工具的优化、不同HRP的整合、填补（Imputation）方法的开发，以及数据的多维应用与共享方面，仍面临诸多挑战。本综述系统总结了全球及特定群体中已构建的56个HRP，深入探讨了HRP在当代人类基因组学研究中的研究进展、应用局限性和未来发展方向，同时提供定相、填补软件及HRP选择的策略建议。我们强调，高质量HRP的构建对于全面捕获全球代表性人群中的各种遗传变异类型与遗传多样性至关重要，不仅有助于现代和古代基因组学研究，也进一步促进人类精准医学的发展。

Page qzaf022

Review Article

Macrophages in Hematopoiesis and Related Blood Diseases

Hong Huang, Mengya Gao, Francesca Vinchi, Xiuli An, Wei Li, Yaomei Wang

Emerging evidence indicates that macrophages play important roles in hematopoiesis in addition to their immune functions. The well-known immune-unrelated functions of macrophages include their roles in hematopoiesis, especially the quality control of hematopoietic stem cells (HSCs) and hematopoietic stem and progenitor cells (HSPCs), the support of erythropoiesis, and the regulation of megakaryopoiesis. Several studies, most using mouse models, have explored the roles of macrophages in hematopoiesis in different organs such as the yolk sac (YS), fetal liver (FL), bone marrow (BM), and spleen (SP). We have recently documented the potential roles and underlying mechanisms of macrophages in myeloproliferative neoplasm (MPN), aplastic anemia (AA), and idiopathic thrombocytopenic purpura (ITP). In this article, we review the origin of macrophages, introduce their roles in regulating HSCs/HSPCs, erythropoiesis, and megakaryopoiesis within four hematopoietic organs, and summarize the recent advances of macrophages in MPN, AA, and ITP. Finally, we outline the unresolved questions that future studies should address to explore in greater depth the role of macrophages in both normal and disordered hematopoiesis.
要点介绍： 1. 巨噬细胞不仅是免疫细胞，更是造血调控的重要组成部分； 2. 不同来源巨噬细胞具有显著异质性，共同参与造血器官稳态维持； 3. 巨噬细胞是红系造血岛核心细胞，促进红细胞生成和成熟； 4. 巨噬细胞参与巨核细胞发育及血小板稳态调控； 5. 骨髓增殖性肿瘤 (MPN)、再生障碍性贫血 (AA)和特发性血小板减少性紫癜 (ITP)等血液疾病中均存在巨噬细胞异常，具有重要治疗潜力。

Page qzaf112

Review Article

Computational Analyses and Challenges of Single-cell ATAC-seq

Chenfei Wang, Jiaojiao Zhou, Hong Zhang, Zihan Zhuang, Gali Bai, Ming Tang, Song Liu, Tao Liu

Single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) has emerged as a powerful technique to study cell-specific epigenetic landscapes and to provide a multidimensional portrait of gene regulation. However, low genomic coverage per cell results in intrinsic data sparsity and missing-data issues, presenting unique methodological challenges. Consequently, numerous computational methods and techniques have been developed to address these challenges. This review provides a concise overview of published workflows for scATAC-seq analysis, covering preprocessing through downstream analysis including quality control, alignment, peak calling, dimensionality reduction, clustering, gene regulation score calculation, cell type annotation, and multiomics integration. Additionally, we survey key scATAC-seq databases that offer curated, accessible resources; discuss emerging deep-learning methods and Artificial Intelligence (AI) foundation models tailored to scATAC-seq data; and highlight recent advances in spatial ATAC-seq technologies and associated computational approaches. Our objective is to equip readers with a clear understanding of current scATAC-seq methodologies so they can select appropriate tools and construct customized workflows for exploring gene regulation and cellular diversity.
单细胞染色质可及性测序（Single-cell Assay for Transposase-Accessible Chromatin using sequencing, scATAC-seq）是一种革命性技术，能够在表观遗传层面揭示细胞特异性的基因调控景观。这项技术通过分析单个细胞中染色质的开放区域，帮助科学家理解基因表达调控如何决定细胞身份和功能。尽管scATAC-seq技术取得了巨大进展，但由于每个细胞获得的测序片段数量较少，导致数据存在内在的稀疏性和缺失值问题，这为数据分析带来了独特的方法学挑战。因此，亟需通过计算手段来优化分析流程，以实现从原始数据到生物学洞察的完整解析。

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