An investigation of the molecular characterization of the tripartite motif (TRIM) family and primary validation of TRIM31 in gastric cancer.

Most TRIM family members characterized by the E3-ubiquitin ligases, participate in ubiquitination and tumorigenesis. While there is a dearth of a comprehensive investigation for the entire family in gastric cancer (GC). By combining the TCGA and GEO databases, common TRIM family members (TRIMs) were obtained to investigate gene expression, gene mutations, and clinical prognosis. On the basis of TRIMs, a consensus clustering analysis was conducted, and a risk assessment system and prognostic model were developed. Particularly, TRIM31 with clinical prognostic and diagnostic value was chosen for single-gene bioinformatics analysis, in vitro experimental validation, and immunohistochemical analysis of clinical tissue microarrays. The combined dataset consisted of 66 TRIMs, of which 52 were differentially expressed and 43 were differentially prognostic. Significant survival differences existed between the gene clusters obtained by consensus clustering analysis. Using 4 differentially expressed genes identified by multivariate Cox regression and LASSO regression, a risk scoring system was developed. Higher risk scores were associated with a poorer prognosis, suppressive immune cell infiltration, and drug resistance. Transcriptomic data and clinical sample tissue microarrays confirmed that TRIM31 was highly expressed in GC and associated with a poor prognosis. Pathway enrichment analysis, cell migration and colony formation assay, EdU assay, reactive oxygen species (ROS) assay, and mitochondrial membrane potential assay revealed that TRIM31 may be implicated in cell cycle regulation and oxidative stress-related pathways, contribute to gastric carcinogenesis. This study investigated the whole functional and expression profile and a risk score system based on the TRIM family in GC. Further investigation centered around TRIM31 offers insight into the underlying mechanisms of action exhibited by other members of its family in the context of GC.

Trehalose 6-phosphate synthase gene rdtps1 contributes to thermal acclimation in Rhyzopertha dominica.

BACKGROUND: The lesser grain borer (Rhyzopertha dominica), a worldwide primary pest of stored grain, causes serious economic losses and threatens stored food safety. R. dominica can respond to changes in temperature, especially the adaptability to heat. In this study, transcriptome analysis of R. dominica exposed to different temperatures was performed to elucidate differences in gene expression and the underling molecular mechanism. RESULTS: Isoform-sequencing generated 17,721,200 raw reads and yielded 20,416 full-length transcripts. A total of 18,880 (92.48%) transcripts were annotated. We extracted RNA from R. dominica reared at 5 °C (cold stress), 15 °C (cold stress), 27 °C (ambient temperature) and 40 °C (heat stress) for RNA-seq. Compared to those of control insects reared at 27 °C, 119, 342, and 875 differentially expressed genes (DEGs) were identified at 5 °C, 15 °C, and 40 °C, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that pathways associated with "fatty acid metabolism", "fatty acid biosynthesis", "AMPK signaling pathway", "neuroactive ligand receptor interaction", and "longevity regulating pathway-multiple species" were significantly enriched. The functional annotation revealed that the genes encoding heat shock proteins (HSPs), fatty acid synthase (FAS), phospholipases (PLA), trehalose transporter (TPST), trehalose 6-phosphate synthase (TPS), and vitellogenin (Vg) were most likely involved in temperature regulation, which was also validated by RT-qPCR. Seven candidate genes (rdhsp1, rdfas1, rdpla1, rdtpst1, rdtps1, rdvg1, and rdP450) were silenced in the RNA interference (RNAi) assay. RNAi of each candidate gene suggested that inhibiting rdtps1 expression significantly decreased the trehalose level and survival rate of R. dominica at 40 °C. CONCLUSIONS: These results indicated that trehalose contributes to the high temperature resistance of R. dominica. Our study elucidates the molecular mechanisms underlying heat tolerance and provides a potential target for the pest management in R. dominica.

Adhesion between EVs and tumor cells facilitated EV-encapsulated doxorubicin delivery via ICAM1.

Doxorubicin (Dox) is an anti-tumor drug with a broad spectrum, whereas the cardiotoxicity limits its further application. In clinical settings, liposome delivery vehicles are used to reduce Dox cardiotoxicity. Here, we substitute extracellular vesicles (EVs) for liposomes and deeply investigate the mechanism for EV-encapsulated Dox delivery. The results demonstrate that EVs dramatically increase import efficiency and anti-tumor effects of Dox in vitro and in vivo, and the efficiency increase benefits from its unique entry pattern. Dox-loading EVs repeat a "kiss-and-run" motion before EVs internalization. Once EVs touch the cell membrane, Dox disassociates from EVs and directly enters the cytoplasm, leading to higher and faster Dox import than single Dox. This unique entry pattern makes the adhesion between EVs and cell membrane rather than the total amount of EV internalization the key factor for regulating the Dox import. Furthermore, we recognize ICAM1 as the molecule mediating the adhesion between EVs and cell membranes. Interestingly, EV-encapsulated Dox can induce ICAM1 expression by irritating IFN-γ and TNF-α secretion in TME, thereby increasing tumor targeting of Dox-loading EVs. Altogether, EVs and EV-encapsulated Dox synergize via ICAM1, which collectively enhances the curative effects for tumor treatment.

CancerMIRNome: an interactive analysis and visualization database for miRNome profiles of human cancer.

MicroRNAs (miRNAs), which play critical roles in gene regulatory networks, have emerged as promising diagnostic and prognostic biomarkers for human cancer. In particular, circulating miRNAs that are secreted into circulation exist in remarkably stable forms, and have enormous potential to be leveraged as non-invasive biomarkers for early cancer detection. Novel and user-friendly tools are desperately needed to facilitate data mining of the vast amount of miRNA expression data from The Cancer Genome Atlas (TCGA) and large-scale circulating miRNA profiling studies. To fill this void, we developed CancerMIRNome, a comprehensive database for the interactive analysis and visualization of miRNA expression profiles based on 10 554 samples from 33 TCGA projects and 28 633 samples from 40 public circulating miRNome datasets. A series of cutting-edge bioinformatics tools and machine learning algorithms have been packaged in CancerMIRNome, allowing for the pan-cancer analysis of a miRNA of interest across multiple cancer types and the comprehensive analysis of miRNome profiles to identify dysregulated miRNAs and develop diagnostic or prognostic signatures. The data analysis and visualization modules will greatly facilitate the exploit of the valuable resources and promote translational application of miRNA biomarkers in cancer. The CancerMIRNome database is publicly available at http://bioinfo.jialab-ucr.org/CancerMIRNome.

Synergistic Ionic Liquid in Hole Transport Layers for Highly Stable and Efficient Perovskite Solar Cells.

Perovskite solar cells (PSCs) with n-i-p structures often utilize an organic 2,2',7,7'-tetrakis (N, N-di-p-methoxyphenyl-amine) 9,9'-spirobifluorene (spiro-OMeTAD) along with additives of lithium bis(trifluoromethanesulfonyl)imide salt (LiTFSI) and tert-butylpyridine as the hole transporting layer (HTL). However, the HTL lacks stability in ambient air, and numerous defects are often present on the perovskite surface, which is not conducive to a stable and efficient PSC. Therefore, constructive strategies that simultaneously stabilize spiro-OMeTAD and passivate the perovskite surface are required. In this work, it is demonstrated that a novel ionic liquid of dimethylammonium bis(trifluoromethanesulfonyl)imide (DMATFSI) could act as a bifunctional HTL modulator in n-i-p PSCs. The addition of DMATFSI into spiro-OMeTAD can effectively stabilize the oxidized spiro-OMeTAD+ cation radicals through the formation of spiro-OMeTAD+ TFSI- because of the excellent charge delocalization of the conjugated CF3 SO2 - moiety within TFSI- . In addition, DMA+ cations could move toward the perovskite from the HTL, resulting in the passivation of defects at the perovskite surface. Accordingly, a power conversion efficiency of 23.22% is achieved for PSCs with DMATFSI and LiTFSI co-doped spiro-OMeTAD. Moreover, benefiting from the improved ion migration barrier and hydrophobicity of the HTL, still retained nearly 80% of their initial power conversion efficiency after 36 days of exposure to ambient air.

Precise Control of Crystallization and Phase-Transition with Green Anti-Solvent in Wide-Bandgap Perovskite Solar Cells with Open-Circuit Voltage Exceeding 1.25 V.

Wide-bandgap perovskite solar cells (PSCs) have attracted a lot of attention due to their application in tandem solar cells. However, the open-circuit voltage (VOC ) of wide-bandgap PSCs is dramatically limited by high defect density existing at the interface and bulk of the perovskite film. Here, an anti-solvent optimized adduct to control perovskite crystallization strategy that reduces nonradiative recombination and minimizes VOC deficit is proposed. Specifically, an organic solvent with similar dipole moment, isopropanol (IPA) is added into ethyl acetate (EA) anti-solvent, which is beneficial to form PbI2 adducts with better crystalline orientation and direct formation of α-phase perovskite. As a result, EA-IPA (7-1) based 1.67 eV PSCs deliver a power conversion efficiency of 20.06% and a VOC of 1.255 V, which is one of the remarkable values for wide-bandgap around 1.67 eV. The findings provide an effective strategy for controlling crystallization to reduce defect density in PSCs.

Boosting predictabilities of agronomic traits in rice using bivariate genomic selection.

The multivariate genomic selection (GS) models have not been adequately studied and their potential remains unclear. In this study, we developed a highly efficient bivariate (2D) GS method and demonstrated its significant advantages over the univariate (1D) rival methods using a rice dataset, where four traditional traits (i.e. yield, 1000-grain weight, grain number and tiller number) as well as 1000 metabolomic traits were analyzed. The novelty of the method is the incorporation of the HAT methodology in the 2D BLUP GS model such that the computational efficiency has been dramatically increased by avoiding the conventional cross-validation. The results indicated that (1) the 2D BLUP-HAT GS analysis generally produces higher predictabilities for two traits than those achieved by the analysis of individual traits using 1D GS model, and (2) selected metabolites may be utilized as ancillary traits in the new 2D BLUP-HAT GS method to further boost the predictability of traditional traits, especially for agronomically important traits with low 1D predictabilities.

Extended application of genomic selection to screen multiomics data for prognostic signatures of prostate cancer.

Prognostic tests using expression profiles of several dozen genes help provide treatment choices for prostate cancer (PCa). However, these tests require improvement to meet the clinical need for resolving overtreatment, which continues to be a pervasive problem in PCa management. Genomic selection (GS) methodology, which utilizes whole-genome markers to predict agronomic traits, was adopted in this study for PCa prognosis. We leveraged The Cancer Genome Atlas (TCGA) database to evaluate the prediction performance of six GS methods and seven omics data combinations, which showed that the Best Linear Unbiased Prediction (BLUP) model outperformed the other methods regarding predictability and computational efficiency. Leveraging the BLUP-HAT method, an accelerated version of BLUP, we demonstrated that using expression data of a large number of disease-relevant genes and with an integration of other omics data (i.e. miRNAs) significantly increased outcome predictability when compared with panels consisting of a small number of genes. Finally, we developed a novel stepwise forward selection BLUP-HAT method to facilitate searching multiomics data for predictor variables with prognostic potential. The new method was applied to the TCGA data to derive mRNA and miRNA expression signatures for predicting relapse-free survival of PCa, which were validated in six independent cohorts. This is a transdisciplinary adoption of the highly efficient BLUP-HAT method and its derived algorithms to analyze multiomics data for PCa prognosis. The results demonstrated the efficacy and robustness of the new methodology in developing prognostic models in PCa, suggesting a potential utility in managing other types of cancer.

Multifunctional Flame-Retardant, Thermal Insulation, and Antimicrobial Wood-Based Composites.

Wood has been used in a variety of applications in our daily lives and military industry. Nevertheless, its flammability causes potential fire risks and hazards. Improving the flame retardancy of wood is a challenging task. Herein, a phytic acid-based flame retardant (referred to as AMPA) was synthesized based on supramolecular reactions between melamine and p-amino-benzene sulfonic acid followed by a reaction with phytic acid using deionized water as the solvent. A composite wood was prepared by removing lignin to tailor the unique mesoporous structure of the material, followed by coating AMPA on the surfaces of wood microchannels. The limiting oxygen index of wood has been improved to 52.5% with the addition of 5.6 wt % AMPA. The peak heat release rate for the prepared composite wood was reduced by 81% compared to that for delignified wood, which demonstrates the excellent flame-retardant performance of the prepared composite wood. Furthermore, AMPA and mesoporous structures endow antimicrobial and thermal insulation functions. Hence, this work provides a feasible method for preparing flame-retardant wood-based materials for diversified applications.

Estimating genetic variance contributed by a quantitative trait locus: A random model approach.

Detecting quantitative trait loci (QTL) and estimating QTL variances (represented by the squared QTL effects) are two main goals of QTL mapping and genome-wide association studies (GWAS). However, there are issues associated with estimated QTL variances and such issues have not attracted much attention from the QTL mapping community. Estimated QTL variances are usually biased upwards due to estimation being associated with significance tests. The phenomenon is called the Beavis effect. However, estimated variances of QTL without significance tests can also be biased upwards, which cannot be explained by the Beavis effect; rather, this bias is due to the fact that QTL variances are often estimated as the squares of the estimated QTL effects. The parameters are the QTL effects and the estimated QTL variances are obtained by squaring the estimated QTL effects. This square transformation failed to incorporate the errors of estimated QTL effects into the transformation. The consequence is biases in estimated QTL variances. To correct the biases, we can either reformulate the QTL model by treating the QTL effect as random and directly estimate the QTL variance (as a variance component) or adjust the bias by taking into account the error of the estimated QTL effect. A moment method of estimation has been proposed to correct the bias. The method has been validated via Monte Carlo simulation studies. The method has been applied to QTL mapping for the 10-week-body-weight trait from an F2 mouse population.

Disulfide Bond Accelerated Transesterification in Poly(ß-hydrazide disulfide esters) toward Fast Network Rearrangements.

The development of catalyst-free ester-based covalent adaptable networks (CANs) provides a new approach to achieve milder reaction conditions to reprocess thermoset resins. Despite recent advances, however, accelerating network rearrangements requires the introduction of hydroxyl groups into the network. In this study, disulfide bonds are introduced into the CANs to add new kinetically facile pathways to accelerate network rearrangement. Kinetic experiments using small molecule models of the CANs show that the presence of the disulfide bonds can accelerate transesterification. These insights are applied to synthesize new kinds of poly(ß-hydrazide disulfide esters) (PSHEs) using thioctic acyl hydrazine (TAH) as a precursor for ring-opening polymerization with the hydroxyl-free multifunctional acrylates. The PSHE CANs have lower relaxation times (505-652 s) than the polymer containing only ß-hydrazide esters (2903 s). The ring-opening polymerization of TAH improves the crosslinking density, heating resistance deformation temperature, and UV shielding performance of the PSHEs. Thus, this work provides a practical strategy to reduce the reprocessing temperatures of CANs.

Improve Quantum Yield of Poly(Maleic Anhydride-Alt-Vinyl Acetate) via Good Solvents.

In this study, the optical properties of poly(maleic anhydride-alt-vinyl acetate) (PMV) synthesized by different polymerization methods are studied systematically. Compared to self-stabilized precipitation polymerization (pPMV), solution polymerization produces PMV solids (sPMV) with an extraordinarily high quantum yield (QY) of 20.65%. Additionally, redissolving pPMV in good solvents (rPMV) will also help to increase QY. The rising QY of sPMV and rPMV supports the idea that good solvents will reduce the rigidity of polymer chains and promote cluster formation, which is confirmed by lower glass transition temperature (Tg ) and small angle X-ray scatterer (SAXS). The study also finds that PMV exhibits application potentials in white light-emitting diodes (WLEDs) and light conversion film.

Research of Ferric Ion Regulation on a Polyimide/C-MXene Microcellular Composite Film.

This paper established a new kind of polyimide/C-MXene composite films with a microcellular structure for electromagnetic interference shielding through solution mixing and liquid phase separation methods. Polyimide was used as the resin material, Ti3C2Tx MXene was used as the electromagnetic wave-shielding medium, l-citrulline was used as the surface modification agent, ferric trichloride (especially the ferric ion) was used as the cross-linking agent between the polyimide and modified C-MXene, and a microcell was used as the shielding structure. By adjusting the content of ferric ions, the foam structure, mechanical properties, thermal conductivity, and electromagnetic interference shielding efficiency of the polyimide/C-MXene microcellular composite film could be controlled. The higher the ferric ion content, the smaller the foam size and the higher the electromagnetic interference shielding efficiency. With increasing ferric ion content, the tensile strength and Young's modulus appeared to first increase and then decrease; when the ferric ion content was 0.8 wt %, the tensile strength and Young's modulus reached their maximum values, which were 10.06 and 325.29 MPa, respectively. In addition, with increasing ferric ion content, the thermal insulation showed first decreasing and then increasing tendency; the lowest thermal conductivity was 0.17 W/(m·K) when the ferric ion content was 0.8 wt %.

A Comparative Study of Parameter Identification Methods for Asymmetric Nonlinear Systems with Quadratic and Cubic Stiffness.

Understanding the nonlinear dynamic characteristics of engineering structures is challenging, especially for the systems that exhibit asymmetric nonlinear behavior. This paper compared four parameter identification methods for asymmetric nonlinear systems incorporating quadratic and cubic stiffness nonlinearities. Hilbert transform, zero-crossing, direct quadrature, and wavelet transform were used to obtain the backbone, envelope, and restoring force curves from the free vibration time history. A nonlinear curve-fitting method was then applied to estimate the stiffness parameters of the asymmetric systems, and a linear least square fitting approach was utilized to estimate the damping parameters of the asymmetric systems. We used the Helmholtz-Duffing oscillator as a numerical example and a nonlinear vibration absorber with geometric imperfections to verify the feasibility and accuracy of these methods. The advantages and disadvantages of these methods and the deviations in estimated results are discussed.

Spatial and temporal distribution and influencing factor analysis of the malignant tumor mortality rate around the mining area.

Mining activities can threaten residents' health even lives. Integrating spatial empirical Bayesian smoothing, joinpoint regression and spatiotemporal scanning methods, we analyzed aggregations and possible factors of four tumor mortality rates at township and village scales from 2012 to 2016 in Suxian district of Hunan Province, China. Results indicate: (1) Mortality rates were ranked: lung cancer > liver cancer > gastric cancer > colorectal cancer. (2) Lung cancer had a higher five-year mortality rate in the middle; relative risk (RR) of death from lung cancer from 2012 to 2015 in Xujiadong Village was 7.48. Liver cancer had a higher five-year mortality rate in the Middle West; RR in areas centered on Nanta Street with a radius of 9.87 km from 2015 to 2016, was 1.83. Gastric cancer had a higher five-year mortality rate in the east; RR in Xujiadong Village from 2012 to 2014 was 6.9. Five-year mortality rate of colorectal cancer was higher in the northwest; RR in regions centered on Huangcao Village with a radius of 12.11 km in 2016, was 2.88. (3) Pollution from ore mining and smelting, heavy metal and non-metallic, and mine transportation were the main possible factors. This research provides a method reference for studying spatiotemporal patterns of disease in China even the world.

[A rare case of dicentric ring chromosome and derivative ring chromosome Chimera].

OBJECTIVE: Utilize high-resolution chromosome analysis and microarray detection to determine the genetic etiology of infertility of a 32-year old female patient. METHODS: The peripheral blood of the patient was cultured for high-resolution chromosome G and C banding karyotype analysis, and then 750K SNP-Array chip detection was performed. RESULTS: Karyotype analysis results showed that the patient's karyotype was 45,XX,-13 [7]/46,XX,r(13) (p13q34) [185]/46,XX,dic r(13;13)(p13q34;p13q34) [14]/ 47,XX,+der(13;13;13;13) (p13q34;p13q34;p13q34; p13q34), dic r(13;13) [1]/ 46,XX [3]. The microarray results showed that the patient had a 3.3 Mb deletion in the 13q34 segment of chromosome 13, which may be related to infertility. CONCLUSION: Infertility of the patient reported in this article may be related to the deletion of chromosome segment (13q34-qter).

Inference of Chromosome-Length Haplotypes Using Genomic Data of Three or a Few More Single Gametes.

Compared with genomic data of individual markers, haplotype data provide higher resolution for DNA variants, advancing our knowledge in genetics and evolution. Although many computational and experimental phasing methods have been developed for analyzing diploid genomes, it remains challenging to reconstruct chromosome-scale haplotypes at low cost, which constrains the utility of this valuable genetic resource. Gamete cells, the natural packaging of haploid complements, are ideal materials for phasing entire chromosomes because the majority of the haplotypic allele combinations has been preserved. Therefore, compared with the current diploid-based phasing methods, using haploid genomic data of single gametes may substantially reduce the complexity in inferring the donor's chromosomal haplotypes. In this study, we developed the first easy-to-use R package, Hapi, for inferring chromosome-length haplotypes of individual diploid genomes with only a few gametes. Hapi outperformed other phasing methods when analyzing both simulated and real single gamete cell sequencing data sets. The results also suggested that chromosome-scale haplotypes may be inferred by using as few as three gametes, which has pushed the boundary to its possible limit. The single gamete cell sequencing technology allied with the cost-effective Hapi method will make large-scale haplotype-based genetic studies feasible and affordable, promoting the use of haplotype data in a wide range of research.

Lateral monolayer MoS2 homojunction devices prepared by nitrogen plasma doping.

Monolayer MoS2 possesses good electron mobility, structural flexibility and a direct band gap, enabling it to be a promising candidate for flexible and wearable optoelectronic devices. In this article, the lateral monolayer MoS2 homojunctions were prepared by a nitrogen plasma selective doping technique. The monolayer MoS2 thin films were synthesized by chemical vapor deposition and characterized by photoluminescence, atom force microscope and Raman spectroscopy. The electronic and photoelectric properties of the lateral pn and npn homojunctions were discussed. The results showed that the rectifying ratio of the pn homojunction diode is ∼103. As a photodetector of pn homojunction, the optical responsivity is up to 48.5 A W-1, the external quantum efficiency is 11 301%, the detectivity is ∼109 Jones and the response time is 20 ms with the laser of 532 nm and the reverse bias voltage of 10 V. As a bipolar junction transistor of npn homojunction, the amplification coefficient reached ∼102. A controllable plasma doping technique, compatible with traditional CMOS process, is utilized to realize the monolayer MoS2 based pn and npn homojunctions, and it propels the potential applications of 2D materials in the electronic, optoelectronic devices and circuits.

Methodological implementation of mixed linear models in multi-locus genome-wide association studies.

The mixed linear model has been widely used in genome-wide association studies (GWAS), but its application to multi-locus GWAS analysis has not been explored and assessed. Here, we implemented a fast multi-locus random-SNP-effect EMMA (FASTmrEMMA) model for GWAS. The model is built on random single nucleotide polymorphism (SNP) effects and a new algorithm. This algorithm whitens the covariance matrix of the polygenic matrix K and environmental noise, and specifies the number of nonzero eigenvalues as one. The model first chooses all putative quantitative trait nucleotides (QTNs) with ≤ 0.005 P-values and then includes them in a multi-locus model for true QTN detection. Owing to the multi-locus feature, the Bonferroni correction is replaced by a less stringent selection criterion. Results from analyses of both simulated and real data showed that FASTmrEMMA is more powerful in QTN detection and model fit, has less bias in QTN effect estimation and requires a less running time than existing single- and multi-locus methods, such as empirical Bayes, settlement of mixed linear model under progressively exclusive relationship (SUPER), efficient mixed model association (EMMA), compressed MLM (CMLM) and enriched CMLM (ECMLM). FASTmrEMMA provides an alternative for multi-locus GWAS.

Analysis of trait heritability in functionally partitioned rice genomes.

Knowledge of the genetic architecture of importantly agronomical traits can speed up genetic improvement in cultivated rice (Oryza sativa L.). Many recent investigations have leveraged genome-wide association studies (GWAS) to identify single nucleotide polymorphisms (SNPs), associated with agronomic traits in various rice populations. The reported trait-relevant SNPs appear to be arbitrarily distributed along the genome, including genic and nongenic regions. Whether the SNPs in different genomic regions play different roles in trait heritability and which region is more responsible for phenotypic variation remains opaque. We analyzed a natural rice population of 524 accessions with 3,616,597 SNPs to compare the genetic contributions of functionally distinct genomic regions for five agronomic traits, i.e., yield, heading date, plant height, grain length, and grain width. An analysis of heritability in the functionally partitioned rice genome showed that regulatory or intergenic regions account for the most trait heritability. A close look at the trait-associated SNPs (TASs) indicated that the majority of the TASs are located in nongenic regions, and the genetic effects of the TASs in nongenic regions are generally greater than those in genic regions. We further compared the predictabilities using the genetic variants from genic regions with those using nongenic regions. The results revealed that nongenic regions play a more important role than genic regions in trait heritability in rice, which is consistent with findings in humans and maize. This conclusion not only offers clues for basic research to disclose genetics behind these agronomic traits, but also provides a new perspective to facilitate genomic selection in rice.