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Objectives The present study was undertaken to explore the effects and mechanisms of Wei-Tong-Xin (WTX) in inhibiting lipopolysaccharide (LPS)-induced inflammatory response of macrophages, in turn, to study the influences on GLP-1 secretion of GLUTag cells. Methods We first evaluated the activation of Raw 264.7 cells and measured the intracellular ROS, CD86 and CD206 levels by flow cytometry. The expressions of proteins were detected by western blot and immunofluorescence. GLP-1 levels were detected by ELISA kits. TLR4 siRNA was used to investigate the role of TLR4 in the regulation of macrophage polarization by WTX. Key findings The results showed that WTX inhibited LPS-induced polarization of macrophages toward the M1 phenotype, but promoted the M2 phenotype. Meanwhile, WTX inhibited the TLR4/MyD88 pathway. The polarization of M1 phenotype promoted GLP-1 secretion by GLUTag cells, which was inhibited by WTX. The results of siRNA showed that WTX exhibited anti-inflammatory effects through targeting TLR4. Conclusions Overall, WTX inhibited polarization of macrophages towards M1 phenotype but promoted the amounts of M2 phenotype, further the macrophages regulated by WTX alleviated GLP-1 content secreted by GLUTag cells. The aforementioned results were produced by WTX-mediated TLR4.

Over the past years, genome-wide association studies (GWAS) have generated a wealth of new information. Summary data from many GWAS are now publicly available, promoting the development of many statistical methods for association studies based on GWAS summary statistics, which avoids the increasing challenges associated with individual-level genotype and phenotype data sharing. However, for population-based association studies such as GWAS, it has been long recognized that population stratification can seriously confound association results. For large GWAS, it is very likely that there exist population stratification and cryptic relatedness, which will result in inflated Type I error in association testing. Although many methods have been developed to control for population stratification, only two of these approaches can be used to control population stratification without individual-level data: one is based on genomic control (GC) and the other one is based on linkage disequilibrium score regression (LDSC). However, the performance of these two approaches is currently unknown. In this study, we use extensive simulation studies including populations with subpopulations, spatially structured populations, and populations with cryptic relatedness to compare the performance of these two approaches to control for population stratification using only GWAS summary statistics without individual-level data. Data sets from the genetic analysis workshop 19 and UK Biobank are also used to evaluate these two approaches. We demonstrate that the intercept of LDSC can be used as a more accurate correction factor than GC. The results from this study will provide very useful information for researchers using GWAS summary statistics while trying to control for population stratification.

Pepper (Capsicum) are consumed worldwide as vegetables and food additives due to their pungent taste. Capsaicinoids are the bioactive compounds that confer the desired pungency to pepper fruits. Capsaicinoid biosynthesis was thought to occur exclusively in fruit placenta. Recently, biosynthesis in the pericarp of extremely pungent varieties was discovered, however, the mechanism of capsaicinoid biosynthesis regulation in the pericarp remains largely unknown. Here, the capsaicinoid contents of placenta and pericarp were analyzed. The results indicated that the Capsicum chinense pericarp accumulated a vast amount of capsaicinoids. Expression of the master regulator MYB31 and capsaicinoid biosynthesis genes (CBGs) were significantly upregulated in the pericarp in C. chinense accessions compared to accessions in other tested species. Moreover, in fruit of extremely-pungent 'Trinidad Moruga Scorpion' (C. chinense) and low-pungent '59' inbred line (C. annuum), the capsaicinoid accumulation patterns in the pericarp were consistent with expression levels of CBGs and MYB31. Silencing MYB31 in 'Trinidad Moruga Scorpion' pericarp leads to a significantly decreased CBGs transcription level and capsaicinoids content. Taken together, our results provide insights into the molecular mechanism arising from the expression of MYB31 in the pericarp that results in exceedingly hot peppers.

Joint analysis of multiple correlated phenotypes for genome-wide association studies (GWAS) can identify and interpret pleiotropic loci which are essential to understand pleiotropy in diseases and complex traits. Meanwhile, constructing a network based on associations between phenotypes and genotypes provides a new insight to analyze multiple phenotypes, which can explore whether phenotypes and genotypes might be related to each other at a higher level of cellular and organismal organization. In this paper, we first develop a bipartite signed network by linking phenotypes and genotypes into a Genotype and Phenotype Network (GPN). The GPN can be constructed by a mixture of quantitative and qualitative phenotypes and is applicable to binary phenotypes with extremely unbalanced case-control ratios in large-scale biobank datasets. We then apply a powerful community detection method to partition phenotypes into disjoint network modules based on GPN. Finally, we jointly test the association between multiple phenotypes in a network module and a single nucleotide polymorphism (SNP). Simulations and analyses of 72 complex traits in the UK Biobank show that multiple phenotype association tests based on network modules detected by GPN are much more powerful than those without considering network modules. The newly proposed GPN provides a new insight to investigate the genetic architecture among different types of phenotypes. Multiple phenotypes association studies based on GPN are improved by incorporating the genetic information into the phenotype clustering. Notably, it might broaden the understanding of genetic architecture that exists between diagnoses, genes, and pleiotropy.

There is strong evidence showing that joint analysis of multiple phenotypes in genome-wide association studies (GWAS) can increase statistical power when detecting the association between genetic variants and human complex diseases. We previously developed the Clustering Linear Combination (CLC) method and a computationally efficient CLC (ceCLC) method to test the association between multiple phenotypes and a genetic variant, which perform very well. However, both of these methods require individual-level genotypes and phenotypes that are often not easily accessible. In this research, we develop a novel method called sCLC for association studies of multiple phenotypes and genetic variants based on GWAS summary statistics. We use the LD score regression to estimate the correlation matrix among phenotypes. The test statistic of sCLC is constructed by GWAS summary statistics and has an approximate Cauchy distribution. We perform a variety of simulation studies and compare sCLC with other commonly used methods for multiple phenotype association studies using GWAS summary statistics. Simulation results show that sCLC can control Type I error rates well and has the highest power in most scenarios. Moreover, we apply the newly developed method to the UK Biobank GWAS summary statistics from the XIII category with 70 related musculoskeletal system and connective tissue phenotypes. The results demonstrate that sCLC detects the most number of significant SNPs, and most of these identified SNPs can be matched to genes that have been reported in the GWAS catalog to be associated with those phenotypes. Furthermore, sCLC also identifies some novel signals that were missed by standard GWAS, which provide new insight into the potential genetic factors of the musculoskeletal system and connective tissue phenotypes.

SummaryCarotenoids act as phytohormones and volatile compound precursors that influence plant development and confer characteristic colours, affecting both the aesthetic and nutritional value of fruits. Carotenoid pigmentation in ripening fruits is highly dependent on developmental trajectories. Transcription factors incorporate developmental and phytohormone signalling to regulate the biosynthesis process. In contrast to the well-established pathways regulating ripening-related carotenoid biosynthesis in climacteric fruit, carotenoid regulation in nonclimacteric fruit is poorly understood. Capsanthin is the primary carotenoid of nonclimacteric pepper (Capsicum) fruit; its biosynthesis is tightly associated with fruit ripening, and it confers red pigment to the ripening fruit. In this study, using a weighted gene coexpression network and expression analysis, we identified an R-R-type MYB transcription factor, DIVARICATA1, and demonstrated that it is tightly associated with the levels of carotenoid biosynthetic genes (CBGs) and capsanthin accumulation. DIVARICATA1 encodes a nucleus-localized protein that functions primarily as a transcriptional activator. Functional analyses demonstrated that DIVARICATA1 positively regulates CBG transcript levels and capsanthin contents by directly binding to and activating the CBG promoter transcription. Furthermore, the association analysis revealed a significant positive association between DIVARICATA1 transcription level and capsanthin content. Abscisic acid (ABA) promotes capsanthin biosynthesis in a DIVARICATA1-dependent manner. Comparative transcriptomic analysis of DIVARICATA1 in pepper and its orthologue in a climacteric fruit, tomato, suggests that its function might be subject to divergent evolution among the two species. This study illustrates the transcriptional regulation of capsanthin biosynthesis and offers a novel target for breeding peppers with high red colour intensity.

In the Lixiahe region of China, co-culture has been rapidly promoted in flooded paddy fields owing to its ecological and economic benefits. Rice-prawn co-culture can reduce the damage of crab and shrimp to rice growth and paddy field and substantially change the soil microbial community and soil fertility. In this study, we compared changes in the soil microbial community and soil fertility in waterlogged paddies under conventional rice culture (CR), rice-prawn (Macrobrachium nipponense) co-culture (RP), and pond culture (PC). The microbial abundance in RP was significantly higher than that in CR. RP soil microbial diversity was significantly higher than PC soil microbial diversity. The dominant bacteria in RP soil were Proteobacteria, Chloroflexi, and Bacteroidetes. Compared with those in CR, total organic matter (TOM) and total nitrogen in RP were relatively stable, available potassium and available phosphorus (AP) decreased, and other indicators increased significantly. Soil fertility significantly benefited from co-culture, with total organic carbon (TOC) increasing. Interactive relationship analysis showed that TOM, TOC, AP, and NH

Although genome-wide association studies (GWAS) have been successfully applied to a variety of complex diseases and identified many genetic variants underlying complex diseases, there is still a considerable heritability of complex diseases that could not be explained by GWAS. One alternative approach to overcome the missing heritability caused by the genetic heterogeneity is gene-based analysis, which considers the aggregate effects of multiple genetic variants in a single test. Another alternative approach is transcriptome-wide association study (TWAS). TWAS aggregates genomic information into functionally relevant units that map to genes and their expression. TWAS is not only powerful, but can also increase the interpretability in biological mechanisms of identified trait associated genes. In this study, we propose two powerful and computationally efficient gene-based association tests, Overall and Copula. These two tests aggregate information from three traditional types of gene-based association tests and also incorporate expression quantitative trait locus (eQTL) data into GWAS using GWAS summary statistics. Overall utilizes the extended Simes procedure and Copula utilizes the Gaussian copula approximation-based method. We show that after a small number of replications to estimate the correlation among the integrated gene-based tests, the P values of these two methods can be calculated analytically. Simulation studies show that these two tests can control type I error rate very well and have higher power than the tests that we compared. We also apply these two methods to two schizophrenia GWAS summary datasets and two lipids GWAS summary datasets. The results show that these two newly developed methods can identify more significant genes than other methods we compared with.

Wei-Tong-Xin (WTX) is a traditional Chinese medicine (TCM) that has been screened and improved in accordance with the famous ancient Chinese formula "Wan Ying Yuan". It has been shown to be clinically effective in treating gastric dysmotility, but its underlying molecular mechanism remains unclear.This study primarily dealt with the effects and mechanisms of WTX on functional dyspepsia (FD) induced by chemotherapeutic drug cisplatin (CIS).Firstly, the UPLC fingerprint and multi-component determination of WTX were established. In vivo, gastrointestinal motility of mice was detected by charcoal propulsion test. Besides, HE, western blot and qRT-PCR were performed to evaluate the occurrence of gastric antral inflammation. ROS-DHE staining was used to detect ROS levels. Further, the gut microbiota were subjected to sequencing by 16S rRNA, and the levels of bacterial metabolites short-chain fatty acids (SCFAs) and lipopolysaccharide (LPS) were detected by GC-MS and Limulus kits, respectively. The levels of GLP-1 in gastric antrum were assessed by ELISA kits. Finally, siRNA-FFAR2 experiment was performed in Raw 264.7 cells.23 common peaks were obtained from the UPLC fingerprint, and the content of 10 target components was determined. WTX increased the relative abundance of Firmicutes and decreased the number of Verrucomicrobia, accompanied by changes in the levels of SCFAs and LPS. By mediating the expression changes of free fatty acid receptor 2 (FFAR2) and toll-like receptor 4 (TLR4), WTX inhibited the phosphorylation of nuclear factor-κB (NF-κB), JNK and P38, decreased the levels of IL-1β, inducible nitric oxide synthase (iNOS) and ROS, increased the expressions of nuclear factor erythroid 2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), IL-4 and arginase-1 (Arg-1). Decreased expressions of glucagon-like peptide 1 (GLP-1) induced by WTX promoted gastric motility in FD mice. In vitro, siRNA-FFAR2 of Raw 264.7 cells eliminated the effects of WTX on TLR4 signaling pathway.In this study, the chemical profile of WTX was first reported. Based on remodeling the gut microbiota structure and adjusting the levels of metabolites (SCFAs and LPS), WTX inactivated the TLR4/MyD88 signaling pathway to inhibit the occurrence of gastric antral inflammation, which reversed the inhibitory effect of GLP-1 on gastric motility, and improved CIS-induced FD symptoms.

There has been an increasing interest in joint analysis of multiple phenotypes in genome-wide association studies (GWAS) because jointly analyzing multiple phenotypes may increase statistical power to detect genetic variants associated with complex diseases or traits. Recently, many statistical methods have been developed for joint analysis of multiple phenotypes in genetic association studies, including the Clustering Linear Combination (CLC) method. The CLC method works particularly well with phenotypes that have natural groupings, but due to the unknown number of clusters for a given data, the final test statistic of CLC method is the minimum p-value among all p-values of the CLC test statistics obtained from each possible number of clusters. Therefore, a simulation procedure must be used to evaluate the p-value of the final test statistic. This makes the CLC method computationally demanding. We develop a new method called computationally efficient CLC (ceCLC) to test the association between multiple phenotypes and a genetic variant. Instead of using the minimum p-value as the test statistic in the CLC method, ceCLC uses the Cauchy combination test to combine all p-values of the CLC test statistics obtained from each possible number of clusters. The test statistic of ceCLC approximately follows a standard Cauchy distribution, so the p-value can be obtained from the cumulative density function without the need for the simulation procedure. Through extensive simulation studies and application on the COPDGene data, the results demonstrate that the type I error rates of ceCLC are effectively controlled in different simulation settings and ceCLC either outperforms all other methods or has statistical power that is very close to the most powerful method with which it has been compared.

Background The basic helix–loop–helix (bHLH) transcription factors (TFs) serve crucial roles in regulating plant growth and development and typically participate in biological processes by interacting with other TFs. Capsorubin and capsaicinoids are found only in Capsicum, which has high nutritional and economic value. However, whether bHLH family genes regulate capsorubin and capsaicinoid biosynthesis and participate in these processes by interacting with other TFs remains unknown. Results In this study, a total of 107 CabHLHs were identified from the Capsicum annuum genome. Phylogenetic tree analysis revealed that these CabHLH proteins were classified into 15 groups by comparing the CabHLH proteins with Arabidopsis thaliana bHLH proteins. The analysis showed that the expression profiles of CabHLH009, CabHLH032, CabHLH048, CabHLH095 and CabHLH100 found in clusters C1, C2, and C3 were similar to the profile of carotenoid biosynthesis in pericarp, including zeaxanthin, lutein and capsorubin, whereas the expression profiles of CabHLH007, CabHLH009, CabHLH026, CabHLH063 and CabHLH086 found in clusters L5, L6 and L9 were consistent with the profile of capsaicinoid accumulation in the placenta. Moreover, CabHLH007, CabHLH009, CabHLH026 and CabHLH086 also might be involved in temperature-mediated capsaicinoid biosynthesis. Yeast two-hybrid (Y2H) assays demonstrated that CabHLH007, CabHLH009, CabHLH026, CabHLH063 and CabHLH086 could interact with MYB31, a master regulator of capsaicinoid biosynthesis. Conclusions The comprehensive and systematic analysis of CabHLH TFs provides useful information that contributes to further investigation of CabHLHs in carotenoid and capsaicinoid biosynthesis.

Motivation: The risk of many complex diseases is determined by an interplay of genetic and environmental factors. The examination of gene-environment interactions (G×Es) for multiple traits can yield valuable insights about the etiology of the disease and increase power in detecting disease-associated genes. However, the methods for testing G×Es for multiple traits are very limited. Method: We developed novel approaches to test G×Es for multiple traits in sequencing association studies. We first perform a transformation of multiple traits by using either principal component analysis or standardization analysis. Then, we detect the effects of G×Es using novel proposed tests: testing the effect of an optimally weighted combination of G×Es (TOW-GE) and/or variable weight TOW-GE (VW-TOW-GE). Finally, we employ Fisher’s combination test to combine the p values. Results: Extensive simulation studies show that the type I error rates of the proposed methods are well controlled. Compared to the interaction sequence kernel association test (ISKAT), TOW-GE is more powerful when there are only rare risk and protective variants; VW-TOW-GE is more powerful when there are both rare and common variants. Both TOW-GE and VW-TOW-GE are robust to directions of effects of causal G×Es. Application to the COPDGene Study demonstrates that our proposed methods are very effective. Conclusions: Our proposed methods are useful tools in the identification of G×Es for multiple traits. The proposed methods can be used not only to identify G×Es for common variants, but also for rare variants. Therefore, they can be employed in identifying G×Es in both genome-wide association studies and next-generation sequencing data analyses.

Recently, gene-based association studies have shown that integrating genome-wide association studies (GWAS) with expression quantitative trait locus (eQTL) data can boost statistical power and that the genetic liability of traits can be captured by polygenic risk scores (PRSs). In this paper, we propose a new gene-based statistical method that leverages gene-expression measurements and new PRSs to identify genes that are associated with phenotypes of interest. We used a generalized linear model to associate phenotypes with gene expression and PRSs and used a score-test statistic to test the association between phenotypes and genes. Our simulation studies show that the newly developed method has correct type I error rates and can boost statistical power compared with other methods that use either gene expression or PRS in association tests. A real data analysis figure based on UK Biobank data for asthma shows that the proposed method is applicable to GWAS.

The human nervous system senses the physical world in an analogue but efficient way. As a crucial ability of the human brain, sound localization is a representative analogue computing task and often employed in virtual auditory systems. Different from well-demonstrated classification applications, all output neurons in localization tasks contribute to the predicted direction, introducing much higher challenges for hardware demonstration with memristor arrays. In this work, with the proposed multi-threshold-update scheme, we experimentally demonstrate the in-situ learning ability of the sound localization function in a 1K analogue memristor array. The experimental and evaluation results reveal that the scheme improves the training accuracy by ∼45.7% compared to the existing method and reduces the energy consumption by ∼184× relative to the previous work. This work represents a significant advance towards memristor-based auditory localization system with low energy consumption and high performance.

Background: The basic helix–loop–helix (bHLH) transcription factors (TFs) serve crucial roles in the regulation of plant growth and development and usually participate in biological processes by interacting with other TFs. Capsorubin and capsaicinoids are found only in Capsicum, which has high nutritional and economic value. However, whether bHLH family genes regulate capsorubin and capsaicinoid biosynthesis and participate in these processes by interacting with other TFs remains to be determined.Results: In this study, a total of 107 CabHLHs were identified from the Capsicum annuum genome. Phylogenetic tree analysis revealed that these CabHLH proteins were classified into 15 groups by comparing the CabHLH proteins with Arabidopsis bHLH proteins. A transcriptome analysis showed that some CabHLHs might be associated with the regulation of capsorubin and capsaicinoid biosynthesis, and the CabHLHs were focused mainly in cluster C1, cluster C2, cluster C3, cluster C4, cluster L5, cluster L6, cluster L8 and cluster L9. In cluster C1, cluster C2, and cluster C3, the expression profiles of CabHLH009, CabHLH032, CabHLH048, CabHLH095 and CabHLH100 were similar to the pattern of carotenoid biosynthesis in pericarp, including β-carotene, zeaxanthin, lutein and capsorubin, while the expression profiles of CabHLH007, CabHLH009, CabHLH026, CabHLH063 and CabHLH086 found in cluster L5, cluster L6 and cluster L9 were consistent with the pattern of capsaicin accumulation in the placenta. CabHLH007, CabHLH009, CabHLH026 and CabHLH086 also might be involved in temperature-mediated capsaicinoid biosynthesis. Additionally, yeast two-hybrid (Y2H) assays demonstrated that CabHLH007, CabHLH009, CabHLH026, CabHLH063 and CabHLH086 could interact with MYB31, a master regulator for capsaicinoid biosynthesis.Conclusions: The comprehensive and systematic analysis of CabHLH TFs provides significantly useful information that contributes to further investigation of CabHLHs in carotenoid and capsaicinoid biosynthesis.

Capsaicinoids confer pungency in Capsicum fruits, and the capsaicinoid content varies greatly among the five domesticated Capsicum species. Although it is generally recognized that capsaicinoid biosynthesis occurs exclusively in the placenta, few studies have focused on capsaicinoid biosynthesis gene (CBG) expression in the pericarp. Therefore, the transcriptional regulation mechanisms of capsaicinoid biosynthesis in the pericarp remain elusive. Here, the capsaicinoid contents of 32 accessions from five domesticated Capsicum species were analyzed. The results showed that the capsaicinoid contents of C. chinense accessions are significantly higher than those of the other four Capsicum species due to the increased accumulation of capsaicinoids, especially in the pericarp. Compared to that in accessions with low pericarp capsaicinoid content, the expression of the master regulator MYB31 is significantly upregulated in the pericarp in C. chinense accessions, which leads to high levels of CBG expression. Moreover, in fruits of the extremely pungent ‘Trinidad Moruga Scorpion’ (C. chinense) and low-pungency ‘59’ inbred line (C. annuum) at different developmental stages, the capsaicinoid accumulation patterns were consistent with the MYB31 and CBG expression levels in the pericarp. Taken together, our results provide novel insights into the molecular mechanism arising from the expression of a master regulator in the pericarp that results in exceedingly hot peppers. The genetic resources identified in this study could be used as genetic resources for the genetic improvement of pepper pungency.

Background ERF transcription factors (TFs) belong to the Apetala2/Ethylene responsive Factor (AP2/ERF) TF family and play a vital role in plant growth and development processes. Capsorubin and capsaicinoids have relatively high economic and nutritional value, and they are specifically found in Capsicum. However, there is little understanding of how ERFs participate in the regulatory networks of capsorubin and capsaicinoids biosynthesis. Results In this study, a total of 142 ERFs were identified in the Capsicum annuum genome. Subsequent phylogenetic analysis allowed us to divide ERFs into DREB (dehydration responsive element binding proteins) and ERF subfamilies, and further classify them into 11 groups with several subgroups. Expression analysis of biosynthetic pathway genes and CaERFs facilitated the identification of candidate genes related to the regulation of capsorubin and capsaicinoids biosynthesis; the candidates were focused in cluster C9 and cluster C10, as well as cluster L3 and cluster L4, respectively. The expression patterns of CaERF82, CaERF97, CaERF66, CaERF107 and CaERF101, which were found in cluster C9 and cluster C10, were consistent with those of accumulating of carotenoids (β-carotene, zeaxanthin and capsorubin) in the pericarp. In cluster L3 and cluster L4, the expression patterns of CaERF102, CaERF53, CaERF111 and CaERF92 were similar to those of the accumulating capsaicinoids. Furthermore, CaERF92, CaERF102 and CaERF111 were found to be potentially involved in temperature-mediated capsaicinoids biosynthesis. Conclusion This study will provide an extremely useful foundation for the study of candidate ERFs in the regulation of carotenoids and capsaicinoids biosynthesis in peppers.

With rapid advancements of sequencing technologies and accumulations of electronic health records, a large number of genetic variants and multiple correlated human complex traits have become available in many genetic association studies. Thus, it becomes necessary and important to develop new methods that can jointly analyze the association between multiple genetic variants and multiple traits. Compared with methods that only use a single marker or trait, the joint analysis of multiple genetic variants and multiple traits is more powerful since such an analysis can fully incorporate the correlation structure of genetic variants and/or traits and their mutual dependence patterns. However, most of existing methods that simultaneously analyze multiple genetic variants and multiple traits are only applicable to unrelated samples. We develop a new method called MF-TOWmuT to detect association of multiple phenotypes and multiple genetic variants in a genomic region with family samples. MF-TOWmuT is based on an optimally weighted combination of variants. Our method can be applied to both rare and common variants and both qualitative and quantitative traits. Our simulation results show that (1) the type I error of MF-TOWmuT is preserved; (2) MF-TOWmuT outperforms two existing methods such as Multiple Family-based Quasi-Likelihood Score Test and Multivariate Family-based Rare Variant Association Test in terms of power. We also illustrate the usefulness of MF-TOWmuT by analyzing genotypic and phenotipic data from the Genetics of Kidneys in Diabetes study. R program is available at https://github.com/gaochengPRC/MF-TOWmuT.

Background: ERF transcription factors (TFs) belong to the Apetala2/Ethylene responsive Factor (AP2/ERF) TF family and play a vital role in plant growth and development processes. Capsorubin and capsaicinoids have relatively high economic and nutritional value, and they are specifically found in Capsicum. However, there is little understanding of how ERFs participate in the regulatory networks of capsorubin and capsaicinoids biosynthesis. Results: In this study, a total of 142 ERFs were identified in the Capsicum annuum genome. Subsequent phylogenetic analysis allowed us to divide ERFs into DREB (dehydration responsive element binding proteins) and ERF subfamilies, and further classify them into 11 groups with several subgroups. Expression analysis of biosynthetic pathway genes and CaERFs facilitated the identification of candidate genes related to the regulation of capsorubin and capsaicinoids biosynthesis; the candidates were focused in cluster C9 and cluster C10, as well as cluster L3 and cluster L4, respectively. The expression patterns of CaERF82, CaERF97, CaERF66, CaERF107 and CaERF101, which were found in cluster C9 and cluster C10, were consistent with those of accumulating of carotenoids (β-carotene, zeaxanthin and capsorubin) in the pericarp. In cluster L3 and cluster L4, the expression patterns of CaERF102, CaERF53, CaERF111 and CaERF92 were similar to those of the accumulating capsaicinoids. Furthermore, CaERF92, CaERF102 and CaERF111 were found to be potentially involved in temperature-mediated capsaicinoids biosynthesis. Conclusion: This study will provide an extremely useful foundation for the study of candidate ERFs in the regulation of carotenoids and capsaicinoids biosynthesis in peppers.

Additional file 2: Table S1. ERF family genes in Arabidopsis, tomato and rice. Table S2. List of primers used in real-time quantitative PCR (qPCR). Table S3. CaERF genes identified and characterized in the pepper. Table S4. Biological functions of characterized ERF proteins that potentially exist in Arabidopsis and tomato. Table S5. Putative CaERF homologs (version 2.0) of pepper ERF proteins with known biological functions. Table S6. Multilevel consensus sequence identified in 144 CaERF genes.

Additional file 1: Fig. S1. Carotenoids (A) and capsaicinoids (B) biosynthetic pathways. Fig. S2. Physical distribution of all candidate CaERFs among chromosomes. Fig. S3. Multiple sequence alignment of the DREB and ERF protein subfamilies. Fig. S4. Phylogenetic tree of the pepper ERF family in relation to Arabidopsis. Fig. S5. Phylogenetic tree of the pepper ERF family in relation to tomato (137), rice (138) and Arabidopsis (122). Fig. S6. The expression patterns of CaERF genes in different tissues.

Summary There is an increasing interest in joint analysis of multiple phenotypes for genome-wide association studies (GWASs) based on the following reasons. First, cohorts usually collect multiple phenotypes and complex diseases are usually measured by multiple correlated intermediate phenotypes. Second, jointly analyzing multiple phenotypes may increase statistical power for detecting genetic variants associated with complex diseases. Third, there is increasing evidence showing that pleiotropy is a widespread phenomenon in complex diseases. In this paper, we develop a clustering linear combination (CLC) method to jointly analyze multiple phenotypes for GWASs. In the CLC method, we first cluster individual statistics into positively correlated clusters and then, combine the individual statistics linearly within each cluster and combine the between-cluster terms in a quadratic form. CLC is not only robust to different signs of the means of individual statistics, but also reduce the degrees of freedom of the test statistic. We also theoretically prove that if we can cluster the individual statistics correctly, CLC is the most powerful test among all tests with certain quadratic forms. Our simulation results show that CLC is either the most powerful test or has similar power to the most powerful test among the tests we compared, and CLC is much more powerful than other tests when effect sizes align with inferred clusters. We also evaluate the performance of CLC through a real case study. Availability and implementation R code for implementing our method is available at http://www.math.mtu.edu/∼shuzhang/software.html. Supplementary information Supplementary data are available at Bioinformatics online.

Despite the extensive discovery of disease-associated common variants, much of the genetic contribution to complex traits remains unexplained. Rare variants may explain additional disease risk or trait variability. Although sequencing technology provides a supreme opportunity to investigate the roles of rare variants in complex diseases, detection of these variants in sequencing-based association studies presents substantial challenges. In this article, we propose novel statistical tests to test the association between rare and common variants in a genomic region and a complex trait of interest based on cross-validation prediction error (PE). We first propose a PE method based on Ridge regression. Based on PE, we also propose another two tests PE-WS and PE-TOW by testing a weighted combination of variants with two different weighting schemes. PE-WS is the PE version of the test based on the weighted sum statistic (WS) and PE-TOW is the PE version of the test based on the optimally weighted combination of variants (TOW). Using extensive simulation studies, we are able to show that (1) PE-TOW and PE-WS are consistently more powerful than TOW and WS, respectively, and (2) PE is the most powerful test when causal variants contain both common and rare variants.

Accumulating evidence suggests that lncRNAs are involved in almost all normal physiological processes and that aberrant expression of lncRNAs may be involved in the development of diseases, including non‑small cell lung cancer (NSCLC). However, the roles of lncRNA‑TPTE pseudogene 1 (TPTEP1) in lung cancer and the underlying molecular mechanisms have remained elusive. In the present study, significant downregulation of TPTEP1 in tumors compared with normal tissues from patients with NSCLC was observed. Overexpression of TPTEP1 inhibited cell proliferation and induced apoptosis in NSCLC cells. A bioinformatics analysis based on miRDB predicted microRNA (miR)‑328‑5p as a potential binding miRNA for TPTEP1. Using a dual‑luciferase reporter assay and western blot analysis, it was further validated that TPTEP1 sponged miR‑328‑5p to upregulate Src kinase signaling inhibitor 1 (SRCIN1) in NSCLC cells. Through regulation of SRCIN1, TPTEP1 was indicated to inactivate the Src and STAT3 pathways in NSCLC cells. Notably, silencing of SRCIN1 reversed the TPTEP1 overexpression‑induced inhibition of cell proliferation and increase of the apoptotic rate in NSCLC cells. Pearson correlation analysis revealed a significant positive correlation between TPTEP1 and SRCIN1 mRNA levels in NSCLC tumors. The present results provided insight into the roles of TPTEP1 in NSCLC and the underlying mechanisms.