Background: Structural variation (SV) acts as an essential mutational force shaping the evolution and function of the human genome. However, few studies have examined the role of SVs in high-altitude adaptation and little is known of adaptive introgressed SVs in Tibetans so far. Results: Here, we generate a comprehensive catalog of SVs in a Chinese Tibetan (n = 15) and Han (n = 10) population using nanopore sequencing technology. Among a total of 38,216 unique SVs in the catalog, 27% are sequence-resolved for the first time. We systematically assess the distribution of these SVs across repeat sequences and functional genomic regions. Through genotyping in additional 276 genomes, we identify 69 Tibetan-Han stratified SVs and 80 candidate adaptive genes. We also discover a few adaptive introgressed SV candidates and provide evidence for a deletion of 335 base pairs at 1p36.32. Conclusions: Overall, our results highlight the important role of SVs in the evolutionary processes of Tibetans’ adaptation to the Qinghai-Tibet Plateau and provide a valuable resource for future high-altitude adaptation studies.

The rapid development of single-molecule long-read sequencing (LRS) and single-cell assay for transposase accessible chromatin sequencing (scATAC-seq) technologies presents both challenges and opportunities for the annotation of noncoding variants. Here, we updated 3DSNP, a comprehensive database for human noncoding variant annotation, to expand its applications to structural variation (SV) and to implement variant annotation down to single-cell resolution. The updates of 3DSNP include (i) annotation of 108 317 SVs from a full spectrum of functions, especially their potential effects on three-dimensional chromatin structures, (ii) evaluation of the accessible chromatin peaks flanking the variants across 126 cell types/subtypes in 15 human fetal tissues and 54 cell types/subtypes in 25 human adult tissues by integrating scATAC-seq data and (iii) expansion of Hi-C data to 49 human cell types. In summary, this version is a significant and comprehensive improvement over the previous version. The 3DSNP v2.0 database is freely available at https://omic.tech/3dsnpv2/.

Lung cancer mortality is exacerbated by late-stage diagnosis. Emerging evidence indicates the potential clinical significance of distinct microbial signatures as diagnostic and prognostic biomarkers across various cancers. However, circulating microbiome DNA (cmDNA) profiles are underexplored in lung cancer (LC). Here, whole-genome sequencing is performed on plasma of LC patients and healthy controls (HCs). Differentially enriched microbial species are identified between LC and HC. A diagnostic model is developed, which has a high sensitivity of 87.7% and achieves an AUC of 93.2% in the independent validation dataset. Crucially, this model demonstrates the capability to detect early-stage LC, achieving a sensitivity of 86.5% for stage I and 87.1% for tumors <1 cm. In addition, we construct a cmDNA model for recurrence, which precisely predicts LC recurrence after surgery. Overall, this study highlights the significant alterations of cmDNA profiles in LC, indicating its potential as biomarkers for early diagnosis and recurrence.

Intestine is a highly radiation-sensitive organ that could be injured during the radiotherapy for pelvic, abdominal, and retroperitoneal tumors. However, the dynamic change of the intestinal microenvironment related to radiation-induced intestine injury (RIII) is still unclear. Using single-cell RNA sequencing, we pictured a dynamic landscape of the intestinal microenvironment during RIII and regeneration. We showed that the various cell types of intestine exhibited heterogeneous radiosensitivities. We revealed the distinct dynamic patterns of three subtypes of intestinal stem cells (ISCs), and the cellular trajectory analysis suggested a complex interconversion pattern among them. For the immune cells, we found that Ly6c⁺ monocytes can give rise to both pro-inflammatory macrophages and resident macrophages after RIII. Through cellular communication analysis, we identified a positive feedback loop between the macrophages and endothelial cells, which could amplify the inflammatory response induced by radiation. Besides, we identified different T cell subtypes and revealed their role in immunomodulation during the early stage of RIII through inflammation and defense response relevant signaling pathways. Overall, our study provides a valuable single-cell map of the multicellular dynamics during RIII and regeneration, which may facilitate the understanding of the mechanism of RIII.

Classification of ovarian cancer by morphologic features has a limited effect on serous ovarian cancer (SOC) treatment and prognosis. Here, we proposed a new system for SOC subtyping based on the molecular categories from the Cancer Genome Atlas project. We analyzed the DNA methylation, protein, microRNA and gene expression of 1203 samples from 599 serous ovarian cancer patients. These samples were divided into nine subtypes based on RNA-seq data and each subtype was found to be associated with the activation and/or suppression of the following four biological processes: immunoactivity, hormone metabolic, mesenchymal development and the MAPK signaling pathway. We also identified four DNA methylation, two protein expression, six microRNA sequencing and four pathway subtypes. By integrating the subtyping results across different omics platforms, we found that most RNA-seq subtypes overlapped with one or two subtypes from other omics data. Our study sheds light on the molecular mechanisms of SOC and provides a new perspective for the more accurate stratification of its subtypes.

As two major types of primary liver cancers, the tumor immune microenvironment (TIME) of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) have been well studied separately. However, a systemic assessment of the similarities and differences between the TIME of HCC and ICC is still lacking. In this study, we pictured a landscape of combined TIME of HCC and ICC by sequencing and integrating 41 single-cell RNA-seq samples from four different tissue types of both malignancies. We found that T cells in HCC tumors generally exhibit higher levels of immunosuppression and exhaustion than those in ICC tumors. Myeloid cells in HCC and ICC tumors also exhibit distinct phenotypes and may serve as a key factor driving the differences between their TIMEs. Besides, we identified a cluster of EGR1⁺ macrophages specifically enriched in HCC tumors. Together, our study provides new insights into cellular composition, states and interactions in the TIMEs of HCC and ICC, which could pave the way for the development of future therapeutic targets for liver cancers.