Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics* ; Humans ; Chromatin/genetics* ; Animals ; Binding Sites ; Mice ; DNA Footprinting/methods*

Infertility is a global health issue,and more and more people are hoping to have babies by means of assisted reproductive technology.However,there are still many challenges in fertilization and pregnancy outcomes.Sperm quality is a key factor affecting the success rate of assisted reproduction.Therefore,sperm quality screening is crucial for achieving breakthroughs in assisted reproduction technology.At present,with its capabilities in the field of image recognition,artificial intelligence(AI)is providing new ideas and methods for sperm screening.Various attempts have been made with AI-based models to evaluate indicators such as sperm morphology,DNA quality,and motility level,and some results have been achieved.Herein,we reviewed the application of AI in sperm quality analysis and selection,providing support for the future development of AI and the improvement in the fertilization rate and outcomes of assisted reproductive technology.

Objective To explore the risk factors of the occurence and 28-day death of acute respiratory distress syndrome (ARDS) in intensive care unit (ICU). Methods A prospective multicentral cohort study was conducted. The patients from five ICUs of grade A tertiary hospitals in Beijing from July 2009 to March 2014, including sepsis,septic shock,trauma,pneumonia,aspiration,massive blood transfusion,bacteremia and pulmonary contusion,were enrolled. Researchers in each center reported the records with uniform tables,which included demographic,systemic conditions,the primary disease,and the severity within 24 hours,past history and so on. According to the admission diagnosis in ICU,these patients were divided into ARDS group and other severe disease control group. The risk factors of occurence and prognosis of ARDS were analyzed by univariate analysis,multivariate logistic regression and multivariate COX regression analysis. Kaplan-Meier method was applied to draw the 28-day survival curves of the two groups. Results There were 343 critical patients included in this prospective multicenter cohort study,of which 163 patients who developed ARDS were considered as ARDS group(2 case lost to follow-up, and 49 died)and 180 patients who did not developed ARDS regarded as severe control group(1 case lost to follow-up, and 34 died). The 28-day mortality of ARDS group was significantly higher than that of severe control group〔30.43%(49/161)vs. 18.99%(34/179),χ2=6.013,P=0.014〕. Multivariate logistic analysis showed that aspiration〔odds ratio(OR)=6.390,95% confidence interval(95%CI)=2.046-19.953,P=0.001〕,history of alcohol (OR=4.854,95%CI=1.730-13.617,P=0.003),sepsis(OR=2.859,95%CI=1.507-5.425,P=0.001), pneumonia(OR=2.822,95%CI=1.640-4.855,P<0.001),acute physiology and chronic health evaluation Ⅱ(APACHEⅡ)score(OR=1.050,95%CI=1.007-1.094,P=0.022)were significantly associated with increased risk of ARDS occurence. When respiratory rate>30 beats/min(OR=3.305,95%CI=1.910-5.721,P<0.001), heart rate>100 beats/min(OR=2.101,95%CI=1.048-4.213,P=0.037)happened in critically ill patients, it highly suggested ARDS would happen. The proportion of the patients whose serum creatinine>176.8 μmol/L in ARDS group was lower than that in control group(OR=0.387,95%CI=0.205-0.733,P=0.004). Multivariate COX regression analysis showed that old age and septic shock were significantly associated with the increased risk of in 28-day death of ARDS〔advanced age:hazard ratio(HR)=1.040,95%CI=1.018-1.064,P<0.001;septic shock:HR=3.209,95%CI=1.676-6.146,P<0.001〕. Kaplan-Meier showed that the survival patients in ARDS group was significantly lower than those in severe control group(χ2=7.032,P=0.008). Conclusions Among critical ill patients,aspiration,history of alcohol,sepsis,pneumonia,increased APACHEⅡ score were the risk factors of ARDS development. Respiratory rate>30 beats/min and heart rate>100 beats/min could predict the occurrence of ARDS in critical patients. Old age and septic shock were the risk factors of 28-day death of ARDS.