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Background: Pathogenic factors embedded in the germline genome are widely recognized as being crucial to breast cancer development. However, current knowledge is either concentrated on the pathogenic variants of a few individual genes or SNPs distributed sparsely across the genome in non-coding regions. Methods: We developed a multi-layered framework, DAGG, which converts somatic mutations or germline rare coding variants (gRCVs) into a functional spectrum of dozens of cellular functions and signaling pathways to identify potential pathogenic factors.Findings: We analyzed whole-exome sequencing (WES) data of 726 germline DNA samples and 169 breast tumor DNA samples from breast cancer patients with various pathological types and cancer-free female subjects, we found that germline pathogens of breast cancers were (1) mainly distributed in HER2-negative subtypes, and (2) involved Her2 signaling pathway activation and immune suppression. These computational discoveries were experimentally validated and can provide digital features to explain the germline differences between diseased and healthy genome (AUC = 0.76). Furthermore, an individual’s risk for breast cancer can be estimated by calculating the combined effects of these identified germline pathogens. Carriers of BRCA1/2 pathogenic variants were found to have a significantly higher average risk (p = 0.02). Interpretation: The results demonstrated that the identified pathogenic mechanisms by DAGG were compatible with our current understanding of the causes of breast cancer. Moreover, DAGG provides improved performance over currently used polygenic risk score method of measuring complex disease risks. Our framework promises possible future applications for the prevention, diagnosis, and treatment of breast cancer. Citation Format: Mei Yang, Yanhui Fan, Zhi-Yong Wu, Zhendong Feng, Qiangzu Zhang, Shunhua Han, Zhonghai Zhang, Xu Li, Yiqing Xue, Xiaoling Li, Meixia Hu, Jieqing Li, Weiping Li, Hongfei Gao, Ciqiu Yang, Chunming Zhang, Liulu Zhang, Teng Zhu, Minyi Cheng, Fei Ji, Juntao Xu, Hening Cui, Guangming Tan, Michael Q Zhang, Changhong Liang, Zaiyi Liu, You-Qiang Song, Gang Niu, Kun Wang. Rare variants in the germline genome holistically determine receptor-independent Her2 signaling pathway activation and immune suppression, shaping pathological type and risk of HER2-negative breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS8-29.

Faced with the current large-scale public health emergency, collecting, sorting, and analyzing biomedical information related to the “coronavirus” should be done as quickly as possible to gain a global perspective, which is a basic requirement for strengthening epidemic control capacity. However, for human researchers studying the viruses and the hosts, the vast amount of information available cannot be processed effectively and in a timely manner, particularly when the scientific understanding may be limited, which can further lower the information processing efficiency. We present TWIRLS, a method that can automatically acquire, organize, and classify information. Additionally, independent functional data sources can be added to build an inference system using a machine-based approach, which can provide relevant knowledge to help human researchers quickly establish subject cognition and to make more effective decisions. TWIRLS can automatically analyze more than three million words in more than 14,000 literature articles in only 4 hours. Combining with generalized gene interaction databases creates a data interface that can help researchers to further analyze the information. Using the TWIRLS system, we found that an important regulatory factor angiotensin-converting enzyme 2 (ACE2) may be involved in the host pathological changes on binding to the coronavirus after infection. After triggering functional changes in ACE2/AT2R, an imbalance in the steady-state cytokine regulatory axis involving the Renin-Angiotensin System and IP-10 leads to a cytokine storm.

The evolution of bread wheat (Triticum aestivum) is distinctive in that domestication, natural hybridization, and allopolyploid speciation have all had significant effects on the diversification of its genome. Wheat was spread around the world by humans and has been cultivated in China for ~4,600 years. Here, we report a comprehensive assessment of the evolution of wheat based on the genome-wide resequencing of 120 representative landraces and elite wheat accessions from China and other representative regions. We found substantially higher genetic diversity in the A and B subgenomes than in the D subgenome. Notably, the A and B subgenomes of the modern Chinese elite cultivars were mainly derived from European landraces, while Chinese landraces had a greater contribution to their D subgenomes. The duplicated copies of homoeologous genes from the A, B, and D subgenomes were commonly found to be under different levels of selection. Our genome-wide assessment of the genetic changes associated with wheat breeding in China provides new strategies and practical targets for future breeding.