A design of multi-source samples as a shared control for association studies in genetically stratified populations

Dear Editors,More and more genetic variants which contribute to human complex traits were identified recently in genome-wide association studies （GWAS）, an approach that shows more efficiency than any other genetic approaches ever before [1]. It holds the promise to disclose genetic mechanism underlying the mystery of human diseases, since the most, if not all, of the genetic variants in the human genome could be investigated for their possible association with diseases by comparing the frequencies of alleles in the cases （patients） and controls （healthy subjects）.

Evaluation of Protocols for Measuring Leaf Photosynthetic Properties of Field-Grown Rice

Largely due to the heterogeneity of environmental parameters and the logistical difficulty of moving photosynthetic equipment in the paddy fields, effective measurement of lowland rice photosynthesis is still a challenge. In this study, we showed that measuring detached rice leaves in the laboratory can not effectively represent the parameters measured in situ. We further described a new indoor facility, high-efficiency all-weather photosynthetic measurement system（HAPS）, and the associated measurement protocol to enable whole-weather measurement of photosynthetic parameters of rice grown in the paddy fields. Using HAPS, we can conduct photosynthetic measurements with a time span much longer than that appropriate for the outdoor measurements. Comparative study shows that photosynthetic parameters obtained with the new protocol can effectively represent the parameters in the fields. There was much less standard deviation for measurements using HAPS compared to the outdoor measurements, no matter for technical replications of each recording or for biological replications of each leaf position. This new facility and protocol enables rice photosynthetic physiology studies to be less tough but more efficient, and provides a potential option for large scale studies of rice leaf photosynthesis.

Gastric precancerous lesions are associated with gene variants in Helicobacter pylori -susceptible ethnic Malays

AIM: To identify genes associated with gastric pre-cancerous lesions in Helicobacter pylori (H. pylori )susceptible ethnic Malays. METHODS: Twenty-three Malay subjects with H. pylori infection and gastric precancerous lesions identified during endoscopy were included as "cases". Thirtyseven Malay subjects who were H. pylori negative and had no precancerous lesions were included as "controls". Venous blood was collected for genotyping with Affymetrix 50K Xba1 kit. Genotypes with call rates < 90% for autosomal single nucleotide polymorphisms (SNPs) were excluded. For each precancerous lesion, associated SNPs were identified from Manhattan plots, and only SNPs with a χ2 P value < 0.05 and Hardy Weinberg Equilibrium P value > 0.5 was considered as significant markers. RESULTS: Of the 23 H. pylori -positive subjects recruited, one sample was excluded from further analysis due to a low genotyping call rate. Of the 22 H. pylori positive samples, atrophic gastritis only was present in 50.0%, complete intestinal metaplasia was present in 18.25%, both incomplete intestinal metaplasia and dysplasia was present in 22.7%, and dysplasia only was present in 9.1%. SNPs rs9315542 (UFM1 gene), rs6878265 (THBS4 gene), rs1042194 (CYP2C19 gene) and rs10505799 (MGST1 gene) were significantly associated with atrophic gastritis, complete intestinal metaplasia, incomplete metaplasia with foci of dysplasia and dysplasia, respectively. Allele frequencies in "cases" vs "controls" for rs9315542, rs6878265, rs1042194 and rs10505799 were 0.4 vs 0.06, 0.6 vs 0.01, 0.6 vs 0.01 and 0.5 vs 0.02, respectively. CONCLUSION: Genetic variants possibly related to gastric precancerous lesions in ethnic Malays susceptible to H. pylori infection were identified for testing in subsequent trials.

Smad2 mediates Activin/Nodal signaling in mesendoderm differentiation of mouse embryonic stem cells

Although Activin/Nodal signaling regulates pluripotency of human embryonic stem （ES） cells, how this signaling acts in mouse ES cells remains largely unclear. To investigate this, we confirmed that mouse ES cells possess active Smad2-mediated Activin/Nodal signaling and found that Smad2-mediated Activin/Nodal signaling is dispensable for self-renewal maintenance but is required for proper differentiation toward the mesendoderm lineage. To gain insights into the underlying mechanisms, Smad2-associated genes were identified by genome-wide chromatin immu- noprecipitation-chip analysis. The results showed that there is a transcriptional correlation between Smad2 binding and Activin/Nodal signaling modulation, and that the development-related genes were enriched among the Smad2- bound targets. We further identified Tapbp as a key player in mesendoderm differentiation of mouse ES cells acting downstream of the Activin/Nodal-Smad2 pathway. Taken together, our findings suggest that Smad2-mediated Activin/Nodal signaling orchestrates mesendoderm lineage commitment of mouse ES cells through direct modulation of corresponding developmental regulator expression.

GCH1 plays a role in the high-altitude adaptation of Tibetans

Tibetans are welt adapted to high-altitude hypoxia. Previous genome-wide scans have reported many candidate genes for this adaptation, but only a few have been studied. Here we report on a hypoxia gene （GCH1, GTP-cyclohydrolase I）, involved in maintaining nitric oxide synthetase （NOS） function and normal blood pressure, that harbors many potentially adaptive variants in Tibetans. We resequenced an 80.8 kb fragment covering the entire gene region of GCH1 in 50 unrelated Tibetans Combined with previously published data, we demonstrated many GCHI variants showing deep divergence between highlander Tibetans and lowlander Han Chinese. Neutrality tests confirmed a signal of positive Darwinian selection on GCH1 in Tibetans. Moreover, association analysis indicated that the Tibetan version of GCH1 was significantly associated with multiple physiological traits in Tibetans, including blood nitric oxide concentration, blood oxygen saturation and hemoglobin concentration. Taken together, we propose that GCH1 plays a role in the genetic adaptation of Tibetans to high altitude hypoxia.

EP300 contributes to high-altitude adaptation in Tibetans by regulating nitric oxide production

The genetic adaptation of Tibetans to high altitude hypoxia likely involves a group of genes in the hypoxic pathway, as suggested by earlier studies. To test the adaptive role of the previously reported candidate gene EP300 （histone acetyltransferase p300）, we conducted resequencing of a 108.9 kb gene region of EP300 in 80 unrelated Tibetans. The allele-frequency and haplotype-based neutrality tests detected signals of positive Darwinian selection on EP300 in Tibetans, with a group of variants showing allelic divergence between Tibetans and lowland reference populations, including Han Chinese, Europeans, and Africans. Functional prediction suggested the involvement of multiple EP300 variants in gene expression regulation. More importantly, genetic association tests in 226 Tibetans indicated significant correlation of the adaptive EP300 variants with blood nitric oxide （NO） concentration. Collectively, we propose that EP300 harbors adaptive variants in Tibetans, which might contribute to high-altitude adaptation through regulating NO production.

An introduction to computational tools for differential binding analysis with ChlP-seq data

Background： Gene transcription in eukaryotie cells is collectively controlled by a large panel of ehromatin associated proteins and ChIP-seq is now widely used to locate their binding sites along the whole genome. Inferring the differential binding sites of these proteins between biological conditions by comparing the corresponding ChIP-seq samples is of general interest, yet it is still a computationally challenging task. Results： Here, we briefly review the computationhl tools developed in recent years for differential binding analysis with ChIP-seq data. The methods are extensively classified by their strategy of statistical modeling and s＇cope of application. Finally, a decision tree is presented for choosing proper tools based on the specific dataset. Conclusions： Computational tools for differential binding analysis with ChIP-seq data vary significantly with respect to their applicability and performance. This review can serve as a practical guide for readers to select appropriate tools for their own datasets.

Computational tools for Hi-C data analysis

Background： In eukaryotic genome, chromatin is not randomly distributed in cell nuclei, but instead is organized into higher-order structures. Emerging evidence indicates that these higher-order chromatin structures play important roles in regulating genome functions such as transcription and DNA replication. With the advancement in 3C （chromosome conformation capture） based technologies, Hi-C has been widely used to investigate genome-wide long- range chromatin interactions during cellular differentiation and oncogenesis. Since the first publication of Hi-C assay in 2009, lots of bioinformatic tools have been implemented for processing Hi-C data from mapping raw reads to normalizing contact matrix and high interpretation, either providing a whole workflow pipeline or focusing on a particular process. Results： This article reviews the general Hi-C data processing workflow and the currently popular Hi-C data processing tools. We highlight on how these tools are used for a full interpretation of Hi-C results. Conclusions： Hi-C assay is a powerful tool to investigate the higher-order chromatin structure. Continued development of novel methods for Hi-C data analysis will be necessary for better understanding the regulatory function of genome organization.

C4 Rice-an Ideal Arena for Systems Biology Research

Engineering the C4 photosynthetic pathway into C3 crops has the potential to dramatically increase the yields of major C3 crops. The genetic control of features involved in C4 photosynthesis are still far from being understood; which partially explains why we have gained little success in C4 engineering thus far. Next generation sequencing techniques and other high throughput technologies are offering an unprecedented opportunity to elucidate the developmental and evolutionary processes of C4 photosynthesis. Two contrasting hypotheses about the evolution of C4 photosynthesis exist, i.e. the master switch hypothesis and the incremental gain hypothesis. These two hypotheses demand two different research strategies to proceed in parallel to maximize the success of C4 engineering. In either case, systems biology research will play pivotal roles in identifying key regulatory elements controlling development of C4 features, identifying essential biochemical and anatomical features required to achieve high photosynthetic efficiency, elucidating genetic mechanisms underlining C4 differentiation and ultimately identifying viable routes to engineer C4 rice. As a highly interdisciplinary project, the C4 rice project will have far-reaching impacts on both basic and applied research related to agriculture in the 21st century.

Identifying cooperative transcription factors by combining ChiP-chip data and knockout data

Dear Editor, Eukaryotic transcriptional regulation networks are extremely complex. Usually, multiple transcription factors (TFs) bind to the promoter region of a gene and cooperate to control gene expression precisely. Identifying cooperative TFs remains a major challenge in modem biological research. Various types of data, including genomic sequences, expression profiles, ChiP-chip data and protein-protein interactions, have been used to identify mechanisms of cooperative transcriptional regulation.

Application of Computational Biology to Decode Brain Transcriptomes

The rapid development of high-throughput sequencing technologies has generated massive valuable brain transcriptome atlases,providing great opportunities for systematically investigating gene expression characteristics across various brain regions throughout a series of developmental stages.Recent studies have revealed that the transcriptional architecture is the key to interpreting the molecular mechanisms of brain complexity.However,our knowledge of brain transcriptional characteristics remains very limited.With the immense efforts to generate high-quality brain transcriptome atlases,new computational approaches to analyze these highdimensional multivariate data are greatly needed.In this review,we summarize some public resources for brain transcriptome atlases and discuss the general computational pipelines that are commonly used in this field,which would aid in making new discoveries in brain development and disorders.

New Research into Potential Epigenetic Origins of Type-1Diabetes

Research led by scientists from University College London(UCL),Queen Mary University of London(QMUL)and Dr.Andrew E.Teschendorff from the CAS-MPG Partner Institute for Computational Biology(PICB),Shanghai Institutes for Biological Sciences(SIBS),Chinese Academy of Sciences(CAS)has identified epigenetic changes in three types of immune cells that

Scientists Reveal Impact of Dietary Interventions on Noncoding RNAs and Transposons

Lifestyle interventions,such as modulating dietary macronutrients,caloric intake,and energy expenditure,can considerably affect the susceptibility to aging-related diseases and,in some cases,an organism’s lifespan.Calorie restriction(CR)without malnutrition and other interventions(e.g.。

Back to Science in Searching for SARS-CoV-2 Origins

In recent decades,emerging and re-emerging human-infecting pathogens have been represented as huge threats to public health and have become a global concern(1).After outbreaks of two coronaviruses(CoVs),severe acute respiratory syndrome coronavirus(SARS-CoV)and Middle East respiratory syndrome coronavirus(MERS-CoV),severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)became the first-known pandemic hastening CoV with tremendous wrecking to the world(2).The origin tracing of these emerging pathogens is of great significance in infectious disease prevention and control(3–4).The origin of SARS-CoV-2 remains elusive after the more than 3-year pandemic,though scientists around the world are making great efforts.From the experience of studying many other infectious pathogens,origin tracing is systematic and time-consuming work.The supposed origins of many infectious pathogens are still in debate,including SARS-CoV and human immunodeficiency virus,etc(5).

CIRCpedia v2: An Updated Database for Comprehensive Circular RNA Annotation and Expression Comparison

Circular RNAs （circRNAs） from back-splicing of exon（s） have been recently identified to be broadly expressed in eukaryotes, in tissue-and species-specific manners. Although functions of most circRNAs remain elusive, some circRNAs are shown to be functional in gene expression regulation and potentially relate to diseases. Due to their stability, circRNAs can also be used as biomarkers for diagnosis. Profiling circRNAs by integrating their expression among different samples thus provides molecular basis for further functional study of circRNAs and their potential application in clinic. Here, we report CIRCpedia v2, an updated database for comprehensive circRNA annotation from over 180 RNA-seq datasets across six different species. This atlas allows users to search, browse, and download circRNAs with expression features in various cell types/tissues, including disease samples. In addition, the updated database incorporates conservation analysis of circRNAs between humans and mice. Finally, the web interface also contains computational tools to compare circRNA expression among samples. CIRCpedia v2 is accessible at http：//www.picb.ac.cn/rnomics/circpedia.

Shanghai Score： A Prognostic and Adjuvant Treatment-evaluating System Constructed for Chinese Patients with Hepatocellular Carcinoma after Curative Resection

Background： For Chinese patients with hepatocellular carcinoma （HCC）, surgical resection is the most important treatment to achieve long-term survival for patients with an early-stage tumor, and yet the prognosis after surgery is diverse. We aimed to construct a scoring system （Shanghai Score） for individualized prognosis estimation and adjuvant treatment evaluation. Methods： A multivariate Cox proportional hazards model was constructed based on 4166 HCC patients undergoing resection during 2001-2008 at Zhongshan Hospital. Age, hepatitis B surface antigen, hepatitis B e antigen, partial thromboplastin time, total bilirubin, alkaline phosphatase, y-glutamyltransferase, a-fetoprotein, tumor size, cirrhosis, vascular invasion, differentiation, encapsulation, and tumor number were finally retained by a backward step-down selection process with the Akaike information criterion. The Harrell＇s concordance index （C-index） was used to measure model performance. Shanghai Score is calculated by summing the products of the 14 variable values times each variable＇s corresponding regression coefficient. Totally 1978 patients from Zhongshan Hospital undergoing resection during 2009-2012, 808 patients from Eastern Hepatobiliary Surgery Hospital during 2008-2010, and 244 patients from Tianjin Medical University Cancer Hospital during 2010-2011 were enrolled as external validation cohorts. Shanghai Score was also implied in evaluating adjuvant treatment choices based on propensity score matching analysis.Results： Shanghai Score showed good calibration and discrimination in postsurgical HCC patients. The bootstrap-corrected C-index （confidence interval [CI]） was 0.74 for overall survival （OS） and 0.68 for recurrence-free survival （RFS） in derivation cohort （4166 patients）, and in the three independent validation cohorts, the CIs for OS ranged 0.70 0.72 and that for RFS ranged 0.63 0.68. Furthermore, Shanghai Score provided evaluation for adjuvant treatment choices （transcatheter arterial chemoembolization or interferon-a）. The identified subset of patients at low risk could be ideal candidates for curative surgery, and subsets of patients at moderate or high risk could be recommended with possible adjuvant therapies after surgery. Finally, a web server with individualized outcome prediction and treatment recommendation was constructed. Conclusions： Based on the largest cohort up to date, we established Shanghai Score - an individualized outcome prediction system specifically designed for Chinese HCC patients after surgery. The Shanghai Score web server provides an easily accessible tool to stratify the prognosis of patients undergoing liver resection for HCC.

Peripheral CD4^(+) T cell signatures in predicting the responses to anti-PD-1/PD-L1 monotherapy for Chinese advanced non-small cell lung cancer

Limited benefit population of immune checkpoint inhibitors makes it urgent to screen predictive biomarkers for stratifying the patients.Herein,we have investigated peripheral CD4^(+) T cell signatures in advanced non-small cell lung cancer(NSCLC)patients receiving anti-PD-1/PD-L1 treatments.It was found that the percentages of IFN-γand IL-17A secreting naïve CD4^(+) T cells(Tn),and memory CD4^(+) T cells(Tm)expressing PD-1,PD-L1 and CTLA-4 were significantly higher in responder(R)than non-responder(NonR)NSCLC patients associated with a longer progression free survival(PFS).Logistic regression analysis revealed that the baseline IFN-γ-producing CD4^(+) Tn cells and PD-1^(+)CD4^(+) Tm cells were the most significant signatures with the area under curve(AUC)value reaching 0.849.This was further validated in another anti-PD-1 monotherapy cohort.Conversely,high percentage of CTLA-4^(+)CD4^(+) Tm cells was associated with a shorter PFS in patients receiving anti-PD-L1 monotherapy.Our study therefore elucidates the significance of functional CD4^(+) Tn and Tm subpopulations before the treatment in predicting the responses to anti-PD-1 treatment in Chinese NSCLC patients.The fact that there display distinct CD4^(+) T cell signatures in the prediction to anti-PD-1 and anti-PD-L1 monotherapy from our study provides preliminary evidence on the feasibility of anti-PD-1 and anti-PD-L1 combination therapy for advanced NSCLC patients.

CIRCexplorer3:A CLEAR Pipeline for Direct Comparison of Circular and Linear RNA Expression

Sequences of circular RNAs(circ RNAs)produced from back-splicing of exon(s)completely overlap with those from cognate linear RNAs transcribed from the same gene loci with the exception of their back-splicing junction(BSJ)sites.Therefore,examination of global circ RNA expression from RNA-seq datasets generally relies on the detection of RNA-seq fragments spanning BSJ sites,which is different from the quantification of linear RNA expression by normalized RNA-seq fragments mapped to whole gene bodies.Thus,direct comparison of circular and linear RNA expression from the same gene loci in a genome-wide manner has remained challenging.Here,we update the previously-reported CIRCexplorer pipeline to version 3 for circular and linear RNA expression analysis from ribosomal-RNA depleted RNA-seq(CIRCexplorer3-CLEAR).A new quantitation parameter,fragments per billion mapped bases(FPB),is applied to evaluate circular and linear RNA expression individually by fragments mapped to circ RNA-specific BSJ sites or to linear RNA-specific splicing junction(SJ)sites.Comparison of circular and linear RNA expression levels is directly achieved by dividing FPBcircby FPBlinearto generate a CIRCscore,which indicates the relative circ RNA expression level using linear RNA expression level as the background.Highlyexpressed circ RNAs with low cognate linear RNA expression background can be readily identified by CIRCexplorer3-CLEAR for further investigation.CIRCexplorer3-CLEAR is publically available at https://github.com/Yang Lab/CLEAR.

Differential stem cell aging kinetics in Hutchinson-Gilford progeria syndrome and Werner syndrome

progeria syndrome （HGPS） and Wemer syndrome （WS） are two of the best characterized human progeroid syndromes. HGPS is caused by a point mutation in lamin A （LMNA） gene, resulting in the production of a truncated protein product-progerin. WS is caused by mutations in 14/RN gem）, encoding a loss-of-function RecQ DNA helicase. Here, by gene editing we created isogenic human embryonic stem cells （ESCs） with heterozygous （G608G/＋） or homozygous （G608G/G608G） LMNA mutation and biallelic WRN knockout, for modeling HGPS and WS pathogenesis, respectively. While ESCs and endothelial cells （ECs） did not present any features of premature senescence, HGPS- and WS-mesenchymal stem cells （MSCs） showed aging-associated phenotypes with different kinetics. WS-MSCs had early-onset mild premature aging phenotypes while HGPS-MSCs exhibited iate-onset acute premature aging characterisitcs. Taken together, our study compares and contrasts the distinct pathologies underpinning the two premature aging disorders, and provides reliable stem-cell based models to identify new therapeutic strategies for pathological and physiological aging.

ePlant for quantitative and predictive plant science research in the big data era --Lay the foundation for the future model guided crop breeding, engineering and agronomy

Background： The increase in global population, climate change and stagnancy in crop yield on unit land area basis in recent decades urgently call for a new approach to support contemporary crop improvements, ePlant is a mathematical model of plant growth and development with a high level of mechanistic details to meet this challenge. Results： ePlant integrates modules developed for processes occurring at drastically different temporal （10-8-106 seconds） and spatial （10-10-10 meters） scales, incorporating diverse physical, biophysical and biochemical processes including gene regulation, metabolic reaction, substrate transport and diffusion, energy absorption, transfer and conversion, organ morphogenesis, plant environment interaction, etc. Individual modules are developed using a divide-and-conquer approach; modules at different temporal and spatial scales are integrated through transfer variables. We further propose a supervised learning procedure based on information geometry to combine model and data for both knowledge discovery and model extension or advances. We finally discuss the recent formation of a global consortium, which includes experts in plant biology, computer science, statistics, agronomy, phenomics, etc. aiming to expedite the development and application of ePlant or its equivalents by promoting a new model development paradigm where models are developed as a community effort instead of driven mainly by individual labs＇ effort. Conclusions： ePlant, as a major research tool to support quantitative and predictive plant science research, will play a crucial role in the future model guided crop engineering, breeding and agronomy.