Genome optimization via virtual simulation to accelerate maize hybrid breeding.

The employment of doubled-haploid (DH) technology in maize has vastly accelerated the efficiency of developing inbred lines. The selection of superior lines has to rely on genotypes with genomic selection (GS) model, rather than phenotypes due to the high expense of field phenotyping. In this work, we implemented 'genome optimization via virtual simulation (GOVS)' using the genotype and phenotype data of 1404 maize lines and their F1 progeny. GOVS simulates a virtual genome encompassing the most abundant 'optimal genotypes' or 'advantageous alleles' in a genetic pool. Such a virtually optimized genome, although can never be developed in reality, may help plot the optimal route to direct breeding decisions. GOVS assists in the selection of superior lines based on the genomic fragments that a line contributes to the simulated genome. The assumption is that the more fragments of optimal genotypes a line contributes to the assembly, the higher the likelihood of the line favored in the F1 phenotype, e.g. grain yield. Compared to traditional GS method, GOVS-assisted selection may avoid using an arbitrary threshold for the predicted F1 yield to assist selection. Additionally, the selected lines contributed complementary sets of advantageous alleles to the virtual genome. This feature facilitates plotting the optimal route for DH production, whereby the fewest lines and F1 combinations are needed to pyramid a maximum number of advantageous alleles in the new DH lines. In summary, incorporation of DH production, GS and genome optimization will ultimately improve genomically designed breeding in maize. Short abstract: Doubled-haploid (DH) technology has been widely applied in maize breeding industry, as it greatly shortens the period of developing homozygous inbred lines via bypassing several rounds of self-crossing. The current challenge is how to efficiently screen the large volume of inbred lines based on genotypes. We present the toolbox of genome optimization via virtual simulation (GOVS), which complements the traditional genomic selection model. GOVS simulates a virtual genome encompassing the most abundant 'optimal genotypes' in a breeding population, and then assists in selection of superior lines based on the genomic fragments that a line contributes to the simulated genome. Availability of GOVS (https://govs-pack.github.io/) to the public may ultimately facilitate genomically designed breeding in maize.

BHAFT: Bayesian heredity-constrained accelerated failure time models for detecting gene-environment interactions in survival analysis.

In addition to considering the main effects, understanding gene-environment (G × E) interactions is imperative for determining the etiology of diseases and the factors that affect their prognosis. In the existing statistical framework for censored survival outcomes, there are several challenges in detecting G × E interactions, such as handling high-dimensional omics data, diverse environmental factors, and algorithmic complications in survival analysis. The effect heredity principle has widely been used in studies involving interaction identification because it incorporates the dependence of the main and interaction effects. However, Bayesian survival models that incorporate the assumption of this principle have not been developed. Therefore, we propose Bayesian heredity-constrained accelerated failure time (BHAFT) models for identifying main and interaction (M-I) effects with novel spike-and-slab or regularized horseshoe priors to incorporate the assumption of effect heredity principle. The R package rstan was used to fit the proposed models. Extensive simulations demonstrated that BHAFT models had outperformed other existing models in terms of signal identification, coefficient estimation, and prognosis prediction. Biologically plausible G × E interactions associated with the prognosis of lung adenocarcinoma were identified using our proposed model. Notably, BHAFT models incorporating the effect heredity principle could identify both main and interaction effects, which are highly useful in exploring G × E interactions in high-dimensional survival analysis. The code and data used in our paper are available at https://github.com/SunNa-bayesian/BHAFT.

Elevated remnant cholesterol is a risk factor for acute ischemic stroke.

OBJECTIVES: Remnant cholesterol (RC) is thought to be an important pathogenic risk factor for atherosclerosis, however, the relationship between RC and acute ischemic stroke (AIS) is still unclear. This study aimed to determine whether fasting blood RC level is an independent risk factor for AIS. MATERIALS AND METHODS: A retrospective analysis was performed on 650 patients with AIS and 598 healthy controls during the same time period. The association between RC and AIS was investigated using binary logistic regression, and the relationship between RC and AIS risk was demonstrated using Restricted Cubic Splines (RCS). RESULTS: RC was significantly higher in the AIS group compared with control group, and was an independent risk factor for AIS when the covariates were not adjusted;After adjusting some covariates, RC was still an independent risk factor for AIS. The RCS analysis found the risk was non-linear: when RC concentration was less than 0.69 mol/L, the risk of AIS increased with the elevation of RC, and when RC concentration was more than or equal to 0.69 mol/L, the risk of AIS was insignificant with the elevation of RC. Correlation analysis revealed that RC was associated with diabetes and fasting glucose. Further analysis revealed that the incidence of AIS in diabetic patients increased significantly with the increase of RC, and RCS analysis revealed that the risk of AIS in diabetic patients increased with the increase of RC when RC was more than 1.15 mol/L. CONCLUSIONS: This study confirms RC as an independent risk factor for AIS, which highlights a distinct non-linear association between RC levels and AIS risk. These findings suggest the need for targeted AIS risk assessment strategies, especially in diabetic patients, and underscore the relevance of RC as a biomarker in AIS risk stratification.

WNT9A Affects Late-Onset Acute Respiratory Distress Syndrome and 28-Day Survival: Evidence from a Three-Step Multiomics Study.

Late-onset (more than 48 h after ICU admission) acute respiratory distress syndrome (ARDS) is associated with shorter survival time and higher mortality; however, the underlying molecular targets remain unclear. As the WNT gene family is known to drive inflammation, immunity, and tissue fibrosis, all of which are closely related to the pathogenesis and prognosis of ARDS, we aim to investigate the associations of the WNT family with late-onset ARDS and 28-day survival. Genetic (n = 380), epigenetic (n = 185), transcriptional (n = 160), and protein (n = 300) data of patients with ARDS were extracted from the MEARDS (Molecular Epidemiology of ARDS) cohort. We used sure independence screening to identify late onset-related genetic biomarkers and constructed a genetic score on the basis of eight SNPs, which was associated with risk for late-onset ARDS (odds ratio [OR], 2.72; P = 3.81 × 10-14) and survival (hazard ratio [HR], 1.28; P = 0.008). The associations were further externally validated in the iSPAAR (Identification of SNPs Predisposing to Altered Acute Lung Injury Risk) (ORlate onset, 2.49 [P = 0.006]; HRsurvival, 1.87 [P = 0.045]) and MESSI (Molecular Epidemiology of Severe Sepsis in the ICU) (ORlate onset, 4.12 [P = 0.026]; HRsurvival, 1.45 [P = 0.036]) cohorts. Furthermore, we functionally interrogated the six mapped genes of eight SNPs in the multiomics data and noted associations of WNT9A (WNT family member 9A) in epigenetic (ORlate onset, 2.95 [P = 9.91 × 10-4]; HRsurvival, 1.53 [P = 0.011]) and protein (ORlate onset, 1.42 [P = 0.035]; HRsurvival, 1.38 [P = 0.011]) data. The mediation analysis indicated that the effects of WNT9A on ARDS survival were mediated by late onset (HRindirect, 1.12 [P = 0.014] for genetic data; HRindirect, 1.05 [P = 0.030] for protein data). The essential roles of WNT9A in immunity and fibrosis may explain the different trajectories of recovery and dysfunction between early- and late-onset ARDS, providing clues for ARDS treatment.

A predictive paradigm for COVID-19 prognosis based on the longitudinal measure of biomarkers.

Novel coronavirus disease 2019 (COVID-19) is an emerging, rapidly evolving crisis, and the ability to predict prognosis for individual COVID-19 patient is important for guiding treatment. Laboratory examinations were repeatedly measured during hospitalization for COVID-19 patients, which provide the possibility for the individualized early prediction of prognosis. However, previous studies mainly focused on risk prediction based on laboratory measurements at one time point, ignoring disease progression and changes of biomarkers over time. By using historical regression trees (HTREEs), a novel machine learning method, and joint modeling technique, we modeled the longitudinal trajectories of laboratory biomarkers and made dynamically predictions on individual prognosis for 1997 COVID-19 patients. In the discovery phase, based on 358 COVID-19 patients admitted between 10 January and 18 February 2020 from Tongji Hospital, HTREE model identified a set of important variables including 14 prognostic biomarkers. With the trajectories of those biomarkers through 5-day, 10-day and 15-day, the joint model had a good performance in discriminating the survived and deceased COVID-19 patients (mean AUCs of 88.81, 84.81 and 85.62% for the discovery set). The predictive model was successfully validated in two independent datasets (mean AUCs of 87.61, 87.55 and 87.03% for validation the first dataset including 112 patients, 94.97, 95.78 and 94.63% for the second validation dataset including 1527 patients, respectively). In conclusion, our study identified important biomarkers associated with the prognosis of COVID-19 patients, characterized the time-to-event process and obtained dynamic predictions at the individual level.

Novel trace elements detected in multiple stages of pregnancy impact neonatal birth weight by affecting gestational age.

Prenatal exposure to elements may be associated with birth weight via shortening of gestation. This study aimed to determine if prenatal exposure is associated with birth weight, and to explore the potential mediating role of gestational age in the association. Within an established Bangladesh prospective birth cohort (2008-2011), we analyzed the concentrations of 15 elements in maternal serum samples collected during the first (n = 780) and second (n = 610) trimesters using inductively coupled plasma mass spectrometry. Mediation analyses explored the relationships between these elements, gestational age, and birth weight. Serum concentrations of cobalt (Co) (first trimester: b = 56.5; 95% confidence interval [CI]: 13.5-99.0; false discovery rate [FDR]-q = 0.035; second trimester: b = 73.3; 95% CI: 20.4-130.2; FDR-q = 0.037) and antimony (Sb) in both trimesters (first trimester:b = 92.1; 95% CI: 66.0-118.9; FDR-q < 0.001; second trimester: b = 93.3; 95% CI: 67.3-118.4; FDR-q < 0.001), and strontium (Sr) in the first trimester (b = 142.4; 95% CI: 41.6-247.9; FDR-q = 0.035) were positively associated with birth weight, while negative associations were observed for barium (Ba) (first trimester: b = -154.8; 95% CI: -217.9 to 91.8; FDR-q <0.001; second trimester: b = -26.7; 95% CI: -44.9 to 10.2; FDR-q < 0.001). These elements act partially by affecting gestation age and appear to have heightened impact among smaller infants. Further research is needed to determine the biological underpinnings of these effects, which may inform strategies to avert low birth weight.

ORF355 confers enhanced salinity stress adaptability to S-type cytoplasmic male sterility maize by modulating the mitochondrial metabolic homeostasis.

Moderate stimuli in mitochondria improve wide-ranging stress adaptability in animals, but whether mitochondria play similar roles in plants is largely unknown. Here, we report the enhanced stress adaptability of S-type cytoplasmic male sterility (CMS-S) maize and its association with mild expression of sterilizing gene ORF355. A CMS-S maize line exhibited superior growth potential and higher yield than those of the near-isogenic N-type line in saline fields. Moderate expression of ORF355 induced the accumulation of reactive oxygen species and activated the cellular antioxidative defense system. This adaptive response was mediated by elevation of the nicotinamide adenine dinucleotide concentration and associated metabolic homeostasis. Metabolome analysis revealed broad metabolic changes in CMS-S lines, even in the absence of salinity stress. Metabolic products associated with amino acid metabolism and galactose metabolism were substantially changed, which underpinned the alteration of the antioxidative defense system in CMS-S plants. The results reveal the ORF355-mediated superior stress adaptability in CMS-S maize and might provide an important route to developing salt-tolerant maize varieties.

Comparative analysis of mitochondrial genomes of maize CMS-S subtypes provides new insights into male sterility stability.

BACKGROUND: Cytoplasmic male sterility (CMS) is a trait of economic importance in the production of hybrid seeds. In CMS-S maize, exerted anthers appear frequently in florets of field-grown female populations where only complete male-sterile plants were expected. It has been reported that these reversions are associated with the loss of sterility-conferring regions or other rearrangements in the mitochondrial genome. However, the relationship between mitochondrial function and sterility stability is largely unknown. RESULTS: In this study, we determined the ratio of plants carrying exerted anthers in the population of two CMS-S subtypes. The subtype with a high ratio of exerted anthers was designated as CMS-Sa, and the other with low ratio was designated as CMS-Sb. Through next-generation sequencing, we assembled and compared mitochondrial genomes of two CMS-S subtypes. Phylogenetic analyses revealed strong similarities between the two mitochondrial genomes. The sterility-associated regions, S plasmids, and terminal inverted repeats (TIRs) were intact in both genomes. The two subtypes maintained high transcript levels of the sterility gene orf355 in anther tissue. Most of the functional genes/proteins were identical at the nucleotide sequence and amino acid sequence levels in the two subtypes, except for NADH dehydrogenase subunit 1 (nad1). In the mitochondrial genome of CMS-Sb, a 3.3-kilobase sequence containing nad1-exon1 was absent from the second copy of the 17-kb repeat region. Consequently, we detected two copies of nad1-exon1 in CMS-Sa, but only one copy in CMS-Sb. During pollen development, nad1 transcription and mitochondrial biogenesis were induced in anthers of CMS-Sa, but not in those of CMS-Sb. We suggest that the impaired mitochondrial function in the anthers of CMS-Sb is associated with its more stable sterility. CONCLUSIONS: Comprehensive analyses revealed diversity in terms of the copy number of the mitochondrial gene nad1-exon1 between two subtypes of CMS-S maize. This difference in copy number affected the transcript levels of nad1 and mitochondrial biogenesis in anther tissue, and affected the reversion rate of CMS-S maize. The results of this study suggest the involvement of mitochondrial robustness in modulation of sterility stability in CMS-S maize.

A two-phase comprehensive NSCLC prognostic study identifies lncRNAs with significant main effect and interaction.

Long noncoding RNA (lncRNA) are involved in regulating physiological behaviors for various malignant tumors, including non-small-cell lung cancer (NSCLC). However, few studies comprehensively evaluated both lncRNA-lncRNA interaction effects and main effects of lncRNA on overall survival of NSCLC. Hence, we performed a two-phase designed study of lncRNA expression in tumor tissues using 604 NSCLC patients from The Cancer Genome Atlas as the discovery phase and 839 patients from Gene Expression Omnibus as the validation phase. In the discovery phase, we adopted a two-step strategy, Screening before Testing, for dimension reduction and signal detection. These candidate lncRNAs first screened out by the weighted random forest (Ranger), were then tested through the Cox proportional hazards model adjusted for covariates. Significant lncRNAs with either type of effects aforementioned were carried forward into the validation phase to confirm their significances again. As a result, in the discovery phase, 19 lncRNAs were identified by Ranger, among which five lncRNAs and one pair of lncRNA-lncRNA interaction exhibited significant effects (FDR-q ≤ 0.05) main and interaction effects on NSCLC survival, respectively, through Cox model. After the independent validation, we finally observed that one lncRNA (ENSG00000227403.1) with main effect was robustly associated with NSCLC prognosis (HRdiscovery = 0.90, P = 1.20 × 10-3; HRvalidation = 0.94, P = 4.11 × 10-3) and one pair of lncRNAs (ENSG00000267121.4 and ENSG00000272369.1) had significant interaction effect on NSCLC survival (HRdiscovery = 1.12, P = 3.07 × 10-4; HRvalidation = 1.11, P = 0.0397). Our comprehensive NSCLC prognostic study of lncRNA provided population-level evidence for further functional study.

Associations of genetic risk, BMI trajectories, and the risk of non-small cell lung cancer: a population-based cohort study.

BACKGROUND: Body mass index (BMI) has been found to be associated with a decreased risk of non-small cell lung cancer (NSCLC); however, the effect of BMI trajectories and potential interactions with genetic variants on NSCLC risk remain unknown. METHODS: Cox proportional hazards regression model was applied to assess the association between BMI trajectory and NSCLC risk in a cohort of 138,110 participants from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. One-sample Mendelian randomization (MR) analysis was further used to access the causality between BMI trajectories and NSCLC risk. Additionally, polygenic risk score (PRS) and genome-wide interaction analysis (GWIA) were used to evaluate the multiplicative interaction between BMI trajectories and genetic variants in NSCLC risk. RESULTS: Compared with individuals maintaining a stable normal BMI (n = 47,982, 34.74%), BMI trajectories from normal to overweight (n = 64,498, 46.70%), from normal to obese (n = 21,259, 15.39%), and from overweight to obese (n = 4,371, 3.16%) were associated with a decreased risk of NSCLC (hazard ratio [HR] for trend = 0.78, P < 2×10-16). An MR study using BMI trajectory associated with genetic variants revealed no significant association between BMI trajectories and NSCLC risk. Further analysis of PRS showed that a higher GWAS-identified PRS (PRSGWAS) was associated with an increased risk of NSCLC, while the interaction between BMI trajectories and PRSGWAS with the NSCLC risk was not significant (PsPRS= 0.863 and PwPRS= 0.704). In GWIA analysis, four independent susceptibility loci (P < 1×10-6) were found to be associated with BMI trajectories on NSCLC risk, including rs79297227 (12q14.1, located in SLC16A7, Pinteraction = 1.01×10-7), rs2336652 (3p22.3, near CLASP2, Pinteraction = 3.92×10-7), rs16018 (19p13.2, in CACNA1A, Pinteraction = 3.92×10-7), and rs4726760 (7q34, near BRAF, Pinteraction = 9.19×10-7). Functional annotation demonstrated that these loci may be involved in the development of NSCLC by regulating cell growth, differentiation, and inflammation. CONCLUSIONS: Our study has shown an association between BMI trajectories, genetic factors, and NSCLC risk. Interestingly, four novel genetic loci were identified to interact with BMI trajectories on NSCLC risk, providing more support for the aetiology research of NSCLC. TRIAL REGISTRATION: http://www. CLINICALTRIALS: gov , NCT01696968 .

Validating ORR and PFS as surrogate endpoints in phase II and III clinical trials for NSCLC patients: difference exists in the strength of surrogacy in various trial settings.

OBJECTIVE: This study aims to systematically validate the performance of surrogate endpoints in phase II and III clinical trials for NSCLC patients under various trial settings. METHODS: A literature search retrieved all registered phase II and III trials of NSCLC patients in which OS, with at least one of ORR and PFS, were reported. Associations between surrogate and true endpoints were assessed on two levels. On the arm level, three pairs of correlations, i.e., ORR vs. median OS, ORR vs. median PFS, and median PFS vs. median OS, were analysed using Spearman's rho. On the trial level, similarly, three pairs of correlations, i.e., ΔORR vs. HR of OS, ΔORR vs. HR of PFS, and HR of PFS vs. HR of OS, were analysed using Spearman's rho and weighted linear regression model respectively. Finally, sensitivity analyses were performed to explore surrogacy under various trial settings. RESULTS: At arm level, three pairs of correlations are all high (Spearman's rho = 0.700, 0.831, 0.755, respectively). At trial level, there is a low correlation between ΔORR and HR of OS, a high correlation between ΔORR and HR of PFS and a moderate correlation between HR of PFS and HR of OS (Spearman's rho = 0.462, 0.764, 0.584, respectively). In the sensitivity analysis, we find correlations between surrogate and true endpoints vary by different trial settings. It is noteworthy that the strength of surrogacy of these intermediate endpoints in targeted therapy is greater than that in immunotherapy. CONCLUSION: According to the arm-level and trial level-analysis, we suggest that in phase II and III trials of targeted therapy and immunotherapy for NSCLC patients: 1) ORR lacks validity for the surrogacy of OS, excluding in first-line therapy, and 2) ORR may be an appropriate surrogate endpoint for PFS, and 3) PFS may be considered a modest surrogacy for OS, with better performance in first-line therapy trials. Moreover, to provide more convincing evidence of surrogacy of the surrogate endpoints, patient-level analyses are in desperate need.

Diversity of endophytic bacteria in hybrid maize seeds and Bacillus mojavensis J2416-7 may be capable of vertical transmission.

The diversity of endophytic bacteria in the progeny is related to the parental lines. In this study, the traditional separation method was used to study the dominant endophytic bacteria of the shared paternal line and its pollen, different maternal lines and their F1 progeny. And the results showed that the dominant endophytic bacteria in maize seeds and the pollen were Bacillus and Pantoea. The Bacillus diversity of the progeny JMC121 and JN728 were the same as both the paternal line and the maternal line, including Bacillus subtilis, Bacillus velezensis, Bacillus mojavensis, and Bacillus licheniformis. The Bacillus subtilis and Bacillus velezensis in JN828 were the same as both the paternal line and the maternal line, while Bacillus licheniformis was only the same as the paternal line. Through the RAPD molecular typing, there was the same strain of Bacillus mojavensis existed in the paternal line J2416, the pollen and the progeny JN728; this meant that the paternal line passed its dominant endophytic bacteria to the progeny through pollen in vertical transmission. This study showed that the dominant endophytic bacteria in maize seeds and the pollen were Bacillus, and the diversity of F1 progeny was related to both the paternal line and the maternal line.

Comprehensive estimation for the length and dispersion of COVID-19 incubation period: a systematic review and meta-analysis.

PURPOSE: To estimate the central tendency and dispersion for incubation period of COVID-19 and, in turn, assess the effect of a certain length of quarantine for close contacts in active monitoring. METHODS: Literature related to SARS-CoV-2 and COVID-19 was searched through April 26, 2020. Quality was assessed according to Agency for Healthcare Research and Quality guidelines. Log-normal distribution for the incubation period was assumed to estimate the parameters for each study. Incubation period median and dispersion were estimated, and distribution was simulated. RESULTS: Fifty-six studies encompassing 4095 cases were included in this meta-analysis. The estimated median incubation period for general transmissions was 5.8 days [95% confidence interval (95% CI): 5.3, 6.2]. Incubation period was significantly longer for asymptomatic transmissions (median: 7.7 days; 95% CI 6.3, 9.4) than for general transmissions (P = 0.0408). Median and dispersion were higher for SARS-CoV-2 incubation compared to other viral respiratory infections. Furthermore, about 12 in 10,000 contacts in active monitoring would develop symptoms after 14 days, or below 1 in 10,000 for asymptomatic transmissions. Meta-regression suggested that each 10-year increase in age resulted in an average 16% increment in length of median incubation (incubation period ratio, 1.16, 95% CI 1.01, 1.32; P = 0.0250). CONCLUSION: This study estimated the median and dispersion of the SARS-CoV-2 incubation period more precisely. A 14-day quarantine period is sufficient to trace and identify symptomatic infections.

Genome-wide identification, characterization, and expression analysis of the monovalent cation-proton antiporter superfamily in maize, and functional analysis of its role in salt tolerance.

Na+, K+ and pH homeostasis are important for plant life and they are controlled by the monovalent cation proton antiporter (CPA) superfamily. The roles of ZmCPAs in salt tolerance are not fully elucidated. In this study, we identified 35 ZmCPAs comprising 13 Na+/H+ exchangers (ZmNHXs), 16 cation/H+ exchanger (ZmCHXs), and 6 K+ efflux antiporters (ZmKEAs). All ZmCPAs have transmembrane domains and most of them were localized to plasma membrane or tonoplast. ZmCHXs were specifically highly expressed in anthers, while ZmNHXs and ZmKEAs showed high expression in various tissues. ZmNHX5 and ZmKEA2 were up-regulated in maize seedlings under both NaCl and KCl stresses. Yeast complementation experiments revealed the roles of ZmNHX5, ZmKEA2 in NaCl tolerance. Analysis of the maize mutants further validated the salt tolerance functions of ZmNHX5 and ZmKEA2. Our study highlights comprehensive information of ZmCPAs and provides new gene targets for salt tolerance maize breeding.

Genome-wide gene-smoking interaction study identified novel susceptibility loci for non-small cell lung cancer in Chinese populations.

Gene-smoking interactions play important roles in the development of non-small cell lung cancer (NSCLC). To identify single-nucleotide polymorphisms (SNPs) that modify the association of smoking behavior with NSCLC risk, we conducted a genome-wide gene-smoking interaction study in Chinese populations. The genome-wide interaction analysis between SNPs and smoking status (ever- versus never-smokers) was carried out using genome-wide association studies of NSCLC, which included 13 327 cases and 13 328 controls. Stratified analysis by histological subtypes was also conducted. We used a genome-wide significance threshold of 5 × 10-8 for identifying significant gene-smoking interactions and 1 × 10-6 for identifying suggestive results. Functional annotation was performed to identify potential functional SNPs and target genes. We identified three novel loci with significant or suggestive gene-smoking interaction. For NSCLC, the interaction between rs2746087 (20q11.23) and smoking status reached genome-wide significance threshold [odds ratio (OR) = 0.63, 95% confidence interval (CI): 0.54-0.74, P = 3.31 × 10-8], and the interaction between rs11912498 (22q12.1) and smoking status reached suggestive significance threshold (OR = 0.72, 95% CI: 0.63-0.82, P = 8.10 × 10-7). Stratified analysis by histological subtypes identified suggestive interactions between rs459724 (5q11.2) and smoking status (OR = 0.61, 95% CI: 0.51-0.73, P = 7.55 × 10-8) in the risk of lung squamous cell carcinoma. Functional annotation indicated that both classic and novel biological processes, including nicotine addiction and airway clearance, may modulate the susceptibility to NSCLC. These novel loci provide new insights into the biological mechanisms underlying NSCLC risk. Independent replication in large-scale studies is needed and experimental studies are warranted to functionally validate these associations.

Comprehensive analyses of m6A regulators and interactive coding and non-coding RNAs across 32 cancer types.

N6-Methyladenosine (m6A) is an RNA modification that interacts with numerous coding and non-coding RNAs and plays important roles in the development of cancers. Nonetheless, the clinical impacts of m6A interactive genes on these cancers largely remain unclear since most studies focus only on a single cancer type. We comprehensively evaluated m6A modification patterns, including 23 m6A regulators and 83 interactive coding and non-coding RNAs among 9,804 pan-cancer samples. We used clustering analysis to identify m6A subtypes and constructed the m6A signature based on an unsupervised approach. We used the signatures to identify potential m6A modification targets across the genome. The prognostic value of one target was further validated in 3,444 samples from six external datasets. We developed three distinct m6A modification subtypes with different tumor microenvironment cell infiltration degrees: immunological, intermediate, and tumor proliferative. They were significantly associated with overall survival in 24 of 27 cancer types. Our constructed individual-level m6A signature was associated with survival, tumor mutation burden, and classical pathways. With the signature, we identified 114 novel genes as potential m6A targets. The gene shared most commonly between cancer types, BCL9L, is an oncogene and interacts with m6A patterns in the Wnt signaling pathway. In conclusion, m6A regulators and their interactive genes impact the outcome of various cancers. Evaluating the m6A subtype and the signature of individual tumors may inform the design of adjuvant treatments.

Natural variations in the P-type ATPase heavy metal transporter gene ZmHMA3 control cadmium accumulation in maize grains.

Cadmium (Cd) accumulation in maize grains is detrimental to human health. Developing maize varieties with low Cd content is important for safe consumption of maize grains. However, the key genes controlling maize grain Cd accumulation have not been cloned. Here, we identified one major locus for maize grain Cd accumulation (qCd1) using a genome-wide association study (GWAS) and bulked segregant RNA-seq analysis with a biparental segregating population of Jing724 (low-Cd line) and Mo17 (high-Cd line). The candidate gene ZmHMA3 was identified by fine mapping and encodes a tonoplast-localized heavy metal P-type ATPase transporter. An ethyl methane sulfonate mutant analysis and an allelism test confirmed that ZmHMA3 influences maize grain Cd accumulation. A transposon in intron 1 of ZmHMA3 is responsible for the abnormal amino acid sequence in Mo17. Based on the natural sequence variations in the ZmHMA3 gene of diverse maize lines, four PCR-based molecular markers were developed, and these were successfully used to distinguish five haplotypes with different grain Cd contents in the GWAS panel and to predict grain Cd contents of widely used maize inbred lines and hybrids. These molecular markers can be used to breed elite maize varieties with low grain Cd contents.

Stalk architecture, cell wall composition, and QTL underlying high stalk flexibility for improved lodging resistance in maize.

BACKGROUND: Stalk fracture caused by strong wind can severely reduce yields in maize. Stalks with higher stiffness and flexibility will exhibit stronger lodging resistance. However, stalk flexibility is rarely studied in maize. Stalk fracture of the internode above the ear before tasseling will result in the lack of tassel and pollen, which is devastating for pollination in seed production. In this study, we focused on stalk lodging before tasseling in two maize inbred lines, JING724 and its improved line JING724A1 and their F2:3 population. RESULTS: JING724A1 showed a larger stalk fracture angle than JING724, indicating higher flexibility. In addition, compared to JING724, JING724A1 also had longer and thicker stalks, with a conical, frustum-shaped internode above the ear. Microscopy and X-ray microcomputed tomography of the internal stalk architecture revealed that JING724A1 had more vascular bundles and thicker sclerenchyma tissue. Furthermore, total soluble sugar content of JING724A1, especially the glucose component, was substantially higher than in JING724. Using an F2:3 population derived from a JING724 and JING724A1 cross, we performed bulk segregant analysis for stalk fracture angle and detected one QTL located on Chr3: 14.00-19.28 Mb. Through transcriptome data analysis and ∆ (SNP-index), we identified two candidate genes significantly associated with high stalk fracture angle, which encode a RING/U-box superfamily protein (Zm00001d039769) and a MADS-box transcription factor 54 (Zm00001d039913), respectively. Two KASP markers designed from these two candidate genes also showed significant correlations with stalk fracture angle. CONCLUSIONS: The internode shape and glucose content are possibly correlated with stalk flexibility in maize. Two genes in the detected QTL are potentially associated with stalk fracture angle. These novel phenotypes and associated loci will provide a theoretical foundation for understanding the genetic mechanisms of lodging, and facilitate the selection of maize varieties with improved flexibility and robust lodging resistance.

TOBMI: trans-omics block missing data imputation using a k-nearest neighbor weighted approach.

MOTIVATION: Stitching together trans-omics data is a powerful approach to assess the complex mechanisms of cancer occurrence, progression and treatment. However, the integration process suffers from the 'block missing' phenomena when part of individuals lacks some omics data. RESULTS: We proposed a k-nearest neighbor (kNN) weighted imputation method for trans-omics block missing data (TOBMIkNN) to handle gene-absence individuals in RNA-seq datasets using external information obtained from DNA methylation probe datasets. Referencing to multi-hot deck, mean imputation and missing cases deletion, we assess the relative error, absolute error, inter-omics correlation structure change and variable selection.The proposed method, TOBMIkNN reliably imputed RNA-seq data by borrowing information from DNA methylation data, and showed superiority over the other three methods in imputation error and stability of correlation structure. Our study indicates that TOBMIkNN can be used as an advisable method for trans-omics block missing data imputation. AVAILABILITY AND IMPLEMENTATION: TOBMIkNN is freely available at https://github.com/XuesiDong/TOBMI. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

An endophytic strain of the genus Bacillus isolated from the seeds of maize (Zea mays L.) has antagonistic activity against maize pathogenic strains.

Plant endophytes are microbes that colonize plant internal tissues and are ubiquitously associated with plants. In this study, seven endophytic bacterial strains, 665L2, 725L2, 725R2, 92R2, 728R3, 728R4 and 2416T3, were isolated from seeds of five healthy maize varieties (Zea mays L.) and all identified as Bacillus velezensis by polyphasic taxonomy based on 16S rRNA and gyrA gene phylogenetic analysis. In addition, according to the genotyping results from random amplified polymorphic DNA (RAPD), 665L2, 725L2, 725R2 and 92R2 belonged to the same strain, while 728R3 and 2416T3 belonged to another strain. Pathogenic fungal strains 4, 5 and 6 were isolated from three diseased maize varieties (Zea mays L.), and they were identified as Talaromyces funiculosus, Penicillium oxalicum and Fusarium verticillioides, respectively, by polyphasic taxonomy based on morphological identification, ITS rDNA and bio-control gene phylogenetic analyses. Seven endophytic bacterial Bacillus velezensis strains had favourable antagonistic activity, and antagonistic testing was carried out against the three pathogenic strains, Talaromyces funiculosus 4, Penicillium oxalicum 5 and Fusarium verticillioides 6. Biological control lipopeptide antibiotic genes (bioA, bmyB, ituC, fenD, srfAA, srfAB, yngG and yndJ) were amplified using specific primers, and they were found in the seven endophytic bacterial Bacillus velezensis strains. This study provides a scientific basis for future research on the use of resistant endophytic bacterial resources to enhance crop production.