The link between social comparison orientation and domain-specific risk-taking: exploring the mediating role of two dimensions of trait competitiveness.

Introduction: Our recent research has demonstrated that social comparison orientation of ability (SCO-ability) is an antecedent of trait competitiveness (TC), and TC mediates the relation between SCO-ability and domain-specific risk-taking. TC is a multi-dimensional trait, therefore we sought to expand on prior research by examining whether SCO-ability predicted two distinct dimensions of TC: hypercompetitive orientation (HCO) and self-development competitive orientation (SDCO). Methods: We investigated how these different dimensions of TC mediated the relation between SCO-ability and both overall and domain-specific risk-taking in two correlational studies of 622 college students (313 males, mean age = 22.10, SD = 2.35) and 717 adult workers (368 males, mean age = 27.92, SD = 5.11). Results: We found that SCO-ability positively predicted HCO. Together, SCO-ability and HCO predicted overall risk-taking and risk-taking in the recreational and ethical domains in both samples. HCO mediated the relation between SCO-ability and both overall risk-taking and risk-taking in the recreational and ethical domains. Additionally, SCO-ability positively predicted SDCO. SCO-ability and SDCO mainly predicted risk-taking in the recreational domain in both studies. SDCO mediated the relation between SCO-ability and risk-taking only in the recreational domain. Discussion: Collectively, the findings above advance our understanding of the relation between competition and risk-taking by using differentiated measures of TC (HCO and SDCO). Our findings suggest that HCO is more strongly related to risk-taking than SDCO, thereby refining the possible role of SCO-ability and TC in predicting overall risk-taking and domain-specific risk-taking.

Infection risk associated with carnivore carcasses may govern trophic interactions between maggots and insectivorous passerine birds.

Infection risk by pathogenic agents motivates hosts to avoid using resources with high risks. This, in turn, results in increased availability of these resources for other species that are more tolerant of infections. For instance, carcasses of mammalian carnivores are frequently avoided by conspecific or closely related carnivores, allowing them to be almost exclusively used by maggots. This may lead to novel interactions with other species. This study investigated the consumption of maggots from carnivore carcasses by non-corvid passerines. We successfully monitored 66 raccoon carcasses in Hokkaido, Japan, from 2016 to 2019. Vertebrates only scavenged 14 carcasses before maggot dispersal; the other 52 carcasses produced abundant maggots that regularly fed at least 12 species of non-corvid passerines. Surprisingly, predation occurred at a distance from the carcasses, mainly after maggot dispersal for pupation, despite the higher efficiency of feeding on maggot masses on the carcasses. Birds are likely to reduce the potential risk of infection from the carcass and/or from maggots on the carcasses. Overall, only 1% of maggots were consumed. Our results suggest that necrophagous flies could benefit from the infection risk associated with carnivore carcasses, which may decrease scavenging by other carnivores and constrain maggot consumption by insectivorous birds.

Variant level heritability estimates of type 2 diabetes in African Americans.

Type 2 diabetes (T2D) is caused by both genetic and environmental factors and is associated with an increased risk of cardiorenal complications and mortality. Though disproportionately affected by the condition, African Americans (AA) are largely underrepresented in genetic studies of T2D, and few estimates of heritability have been calculated in this race group. Using genome-wide association study (GWAS) data paired with phenotypic data from ~ 19,300 AA participants of the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, Genetics of Hypertension Associated Treatments (GenHAT) study, and the Electronic Medical Records and Genomics (eMERGE) network, we estimated narrow-sense heritability using two methods: Linkage-Disequilibrium Adjusted Kinships (LDAK) and Genome-Wide Complex Trait Analysis (GCTA). Study-level heritability estimates adjusting for age, sex, and genetic ancestry ranged from 18% to 34% across both methods. Overall, the current study narrows the expected range for T2D heritability in this race group compared to prior estimates, while providing new insight into the genetic basis of T2D in AAs for ongoing genetic discovery efforts.

Genome-wide association analysis of fleece traits in Northwest Xizang white cashmere goat.

Northwest Xizang White Cashmere Goat (NXWCG) is the first new breed of cashmere goat in the Xizang Autonomous Region. It has significant characteristics of extremely high fineness, gloss, and softness. Genome-wide association analysis is an effective biological method used to measure the consistency and correlation of genotype changes between two molecular markers in the genome. In addition, it can screen out the key genes affecting the complex traits of biological individuals. The aim of this study was to analyze the genetic mechanism of cashmere trait variation in NXWCG and to discover SNP locus and key genes closely related to traits such as superfine cashmere. Additionally, the key genes near the obtained significant SNPs were analyzed by gene function annotation and biological function mining. In this study, the phenotype data of the four traits (cashmere length, fiber length, cashmere diameter, and cashmere production) were collected. GGP_Goat_70K SNP chip was used for genotyping the ear tissue DNA of the experimental group. Subsequently, the association of phenotype data and genotype data was performed using Gemma-0.98.1 software. A linear mixed model was used for the association study. The results showed that four fleece traits were associated with 18 significant SNPs at the genome level and 232 SNPs at the chromosome level, through gene annotated from Capra hircus genome using assembly ARS1. A total of 107 candidate genes related to fleece traits were obtained. Combined with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, we can find that CLNS1A, CCSER1, RPS6KC1, PRLR, KCNRG, KCNK9, and CLYBL can be used as important candidate genes for fleece traits of NXWCG. We used Sanger sequencing and suitability chi-square test to further verify the significant loci and candidate genes screened by GWAS, and the results show that the base mutations loci on the five candidate genes, CCSER1 (snp12579, 34,449,796, A → G), RPS6KC1 (snp41503, 69,173,527, A → G), KCNRG (snp41082, 67,134,820, G → A), KCNK9 (14:78472665, 78,472,665, G → A), and CLYBL (12: 9705753, 9,705,753, C → T), significantly affect the fleece traits of NXWCG. The results provide a valuable basis for future research and contribute to a better understanding of the genetic structure variation of the goat.

Enhancing the potential of phenomic and genomic prediction in winter wheat breeding using high-throughput phenotyping and deep learning.

Integrating high-throughput phenotyping (HTP) based traits into phenomic and genomic selection (GS) can accelerate the breeding of high-yielding and climate-resilient wheat cultivars. In this study, we explored the applicability of Unmanned Aerial Vehicles (UAV)-assisted HTP combined with deep learning (DL) for the phenomic or multi-trait (MT) genomic prediction of grain yield (GY), test weight (TW), and grain protein content (GPC) in winter wheat. Significant correlations were observed between agronomic traits and HTP-based traits across different growth stages of winter wheat. Using a deep neural network (DNN) model, HTP-based phenomic predictions showed robust prediction accuracies for GY, TW, and GPC for a single location with R2 of 0.71, 0.62, and 0.49, respectively. Further prediction accuracies increased (R2 of 0.76, 0.64, and 0.75) for GY, TW, and GPC, respectively when advanced breeding lines from multi-locations were used in the DNN model. Prediction accuracies for GY varied across growth stages, with the highest accuracy at the Feekes 11 (Milky ripe) stage. Furthermore, forward prediction of GY in preliminary breeding lines using DNN trained on multi-location data from advanced breeding lines improved the prediction accuracy by 32% compared to single-location data. Next, we evaluated the potential of incorporating HTP-based traits in multi-trait genomic selection (MT-GS) models in the prediction of GY, TW, and GPC. MT-GS, models including UAV data-based anthocyanin reflectance index (ARI), green chlorophyll index (GCI), and ratio vegetation index 2 (RVI_2) as covariates demonstrated higher predictive ability (0.40, 0.40, and 0.37, respectively) as compared to single-trait model (0.23) for GY. Overall, this study demonstrates the potential of integrating HTP traits into DL-based phenomic or MT-GS models for enhancing breeding efficiency.

Shared genetic effect of kidney function on bipolar and major depressive disorders: a large-scale genome-wide cross-trait analysis.

BACKGROUND: Epidemiological studies have revealed a significant association between impaired kidney function and certain mental disorders, particularly bipolar disorder (BIP) and major depressive disorder (MDD). However, the evidence regarding shared genetics and causality is limited due to residual confounding and reverse causation. METHODS: In this study, we conducted a large-scale genome-wide cross-trait association study to investigate the genetic overlap between 5 kidney function biomarkers (eGFRcrea, eGFRcys, blood urea nitrogen (BUN), serum urate, and UACR) and 2 mental disorders (MDD, BIP). Summary-level data of European ancestry were extracted from UK Biobank, Chronic Kidney Disease Genetics Consortium, and Psychiatric Genomics Consortium. RESULTS: Using LD score regression, we found moderate but significant genetic correlations between kidney function biomarker traits on BIP and MDD. Cross-trait meta-analysis identified 1 to 19 independent significant loci that were found shared among 10 pairs of 5 kidney function biomarkers traits and 2 mental disorders. Among them, 3 novel genes: SUFU, IBSP, and PTPRJ, were also identified in transcriptome-wide association study analysis (TWAS), most of which were observed in the nervous and digestive systems (FDR < 0.05). Pathway analysis showed the immune system could play a role between kidney function biomarkers and mental disorders. Bidirectional mendelian randomization analysis suggested a potential causal relationship of kidney function biomarkers on BIP and MDD. CONCLUSIONS: In conclusion, the study demonstrated that both BIP and MDD shared genetic architecture with kidney function biomarkers, providing new insights into their genetic architectures and suggesting that larger GWASs are warranted.

Genome-wide enhancer RNA profiling adds molecular links between genetic variation and human cancers.

BACKGROUND: Dysregulation of enhancer transcription occurs in multiple cancers. Enhancer RNAs (eRNAs) are transcribed products from enhancers that play critical roles in transcriptional control. Characterizing the genetic basis of eRNA expression may elucidate the molecular mechanisms underlying cancers. METHODS: Initially, a comprehensive analysis of eRNA quantitative trait loci (eRNAQTLs) was performed in The Cancer Genome Atlas (TCGA), and functional features were characterized using multi-omics data. To establish the first eRNAQTL profiles for colorectal cancer (CRC) in China, epigenomic data were used to define active enhancers, which were subsequently integrated with transcription and genotyping data from 154 paired CRC samples. Finally, large-scale case-control studies (34,585 cases and 69,544 controls) were conducted along with multipronged experiments to investigate the potential mechanisms by which candidate eRNAQTLs affect CRC risk. RESULTS: A total of 300,112 eRNAQTLs were identified across 30 different cancer types, which exert their influence on eRNA transcription by modulating chromatin status, binding affinity to transcription factors and RNA-binding proteins. These eRNAQTLs were found to be significantly enriched in cancer risk loci, explaining a substantial proportion of cancer heritability. Additionally, tumor-specific eRNAQTLs exhibited high responsiveness to the development of cancer. Moreover, the target genes of these eRNAs were associated with dysregulated signaling pathways and immune cell infiltration in cancer, highlighting their potential as therapeutic targets. Furthermore, multiple ethnic population studies have confirmed that an eRNAQTL rs3094296-T variant decreases the risk of CRC in populations from China (OR = 0.91, 95%CI 0.88-0.95, P = 2.92 × 10-7) and Europe (OR = 0.92, 95%CI 0.88-0.95, P = 4.61 × 10-6). Mechanistically, rs3094296 had an allele-specific effect on the transcription of the eRNA ENSR00000155786, which functioned as a transcriptional activator promoting the expression of its target gene SENP7. These two genes synergistically suppressed tumor cell proliferation. Our curated list of variants, genes, and drugs has been made available in CancereRNAQTL ( http://canernaqtl.whu.edu.cn/#/ ) to serve as an informative resource for advancing this field. CONCLUSION: Our findings underscore the significance of eRNAQTLs in transcriptional regulation and disease heritability, pinpointing the potential of eRNA-based therapeutic strategies in cancers.

Exploring the Shared Genetic Architecture Between Obstructive Sleep Apnea and Body Mass Index.

Purpose: The reciprocal comorbidity of obstructive sleep apnea (OSA) and body mass index (BMI) has been observed, yet the shared genetic architecture between them remains unclear. This study aimed to explore the genetic overlaps between them. Methods: Summary statistics were acquired from the genome-wide association studies (GWASs) on OSA (Ncase = 41,704; Ncontrol = 335,573) and BMI (Noverall = 461,460). A comprehensive genome-wide cross-trait analysis was performed to quantify global and local genetic correlation, infer the bidirectional causal relationships, detect independent pleiotropic loci, and investigate potential comorbid genes. Results: A positive significant global genetic correlation between OSA and BMI was observed (r g = 0.52, P = 2.85e-122), which was supported by three local signal. The Mendelian randomization analysis confirmed bidirectional causal associations. In the meta-analysis of cross-traits GWAS, a total of 151 single-nucleotide polymorphisms were found to be pleiotropic between OSA and BMI. Additionally, we discovered that the genetic association between OSA and BMI is concentrated in 12 brain regions. Finally, a total 134 expression-tissue pairs were observed to have a significant impact on both OSA and BMI within the specified brain regions. Conclusion: Our comprehensive genome-wide cross-trait analysis indicates a shared genetic architecture between OSA and BMI, offering new perspectives on the possible mechanisms involved.

Genome-wide association study and genomic selection of flax powdery mildew in Xinjiang Province.

Flax powdery mildew (PM), caused by Oidium lini, is a globally distributed fungal disease of flax, and seriously impairs its yield and quality. To data, only three resistance genes and a few putative quantitative trait loci (QTL) have been reported for flax PM resistance. To dissect the resistance mechanism against PM and identify resistant genetic regions, based on four years of phenotypic datasets (2017, 2019 to 2021), a genome-wide association study (GWAS) was performed on 200 flax core accessions using 674,074 SNPs and 7 models. A total of 434 unique quantitative trait nucleotides (QTNs) associated with 331 QTL were detected. Sixty-four loci shared in at least two datasets were found to be significant in haplotype analyses, and 20 of these sites were shared by multiple models. Simultaneously, a large-effect locus (qDI 11.2) was detected repeatedly, which was present in the mapping study of flax pasmo resistance loci. Oil flax had more QTL with positive-effect or favorable alleles (PQTL) and showed higher PM resistance than fiber flax, indicating that effects of these QTL were mainly additive. Furthermore, an excellent resistant variety C120 was identified and can be used to promote planting. Based on 331 QTLs identified through GWAS and the statistical model GBLUP, a genomic selection (GS) model related to flax PM resistance was constructed, and the prediction accuracy rate was 0.96. Our results provide valuable insights into the genetic basis of resistance and contribute to the advancement of breeding programs.

Genome-wide association studies of root system architecture traits in a broad collection of Brassica genotypes.

The root systems of Brassica species are complex. Eight root system architecture (RSA) traits, including total root length, total root surface area, root average diameter, number of tips, total primary root length, total lateral root length, total tertiary root length, and basal link length, were phenotyped across 379 accessions representing six Brassica species (B. napus, B. juncea, B. carinata, B. oleracea, B. nigra, and B. rapa) using a semi-hydroponic system and image analysis software. The results suggest that, among the assessed species, B. napus and B. oleracea had the most intricate and largest root systems, while B. nigra exhibited the smallest roots. The two species B. juncea and B. carinata shared comparable root system complexity and had root systems with larger root diameters. In addition, 313 of the Brassica accessions were genotyped using a 19K Brassica single nucleotide polymorphism (SNP) array. After filtering by TASSEL 5.0, 6,213 SNP markers, comprising 5,103 markers on the A-genome (covering 302,504 kb) and 1,110 markers on the C-genome (covering 452,764 kb), were selected for genome-wide association studies (GWAS). Two general linear models were tested to identify the genomic regions and SNPs associated with the RSA traits. GWAS identified 79 significant SNP markers associated with the eight RSA traits investigated. These markers were distributed across the 18 chromosomes of B. napus, except for chromosome C06. Sixty-five markers were located on the A-genome, and 14 on the C-genome. Furthermore, the major marker-trait associations (MTAs)/quantitative trait loci (QTLs) associated with root traits were located on chromosomes A02, A03, and A06. Brassica accessions with distinct RSA traits were identified, which could hold functional, adaptive, evolutionary, environmental, pathological, and breeding significance.

Systems genetics of metabolic health in the BXD mouse genetic reference population.

Susceptibility to metabolic syndrome (MetS) is dependent on genetics, environment, and gene-by-environment interactions, rendering the study of underlying mechanisms challenging. The majority of experiments in model organisms do not incorporate genetic variation and lack specific evaluation criteria for MetS. Here, we derived a continuous metric, the metabolic health score (MHS), based on standard clinical parameters and defined its molecular signatures in the liver and circulation. In human UK Biobank, the MHS associated with MetS status and was predictive of future disease incidence, even in individuals without MetS. Using quantitative trait locus analyses in mice, we found two MHS-associated genetic loci and replicated them in unrelated mouse populations. Through a prioritization scheme in mice and human genetic data, we identified TNKS and MCPH1 as candidates mediating differences in the MHS. Our findings provide insights into the molecular mechanisms sustaining metabolic health across species and uncover likely regulators. A record of this paper's transparent peer review process is included in the supplemental information.

Multi-GWAS reveals significant genomic regions for Mungbean yellow mosaic India virus resistance in urdbean (Vigna mungo (L.) across multiple environments.

KEY MESSAGE: Unraveling genetic markers for MYMIV resistance in urdbean, with 8 high-confidence marker-trait associations identified across diverse environments, provides crucial insights for combating MYMIV disease, informing future breeding strategies. Globally, yellow mosaic disease (YMD) causes significant yield losses, reaching up to 100% in favorable environments within major urdbean cultivating regions. The introgression of genomic regions conferring resistance into urdbean cultivars is crucial for combating YMD, including resistance against mungbean yellow mosaic India virus (MYMIV). To uncover the genetic basis of MYMIV resistance, we conducted a genome-wide association study (GWAS) using three multi-locus models in 100 diverse urdbean genotypes cultivated across six individual and two combined environments. Leveraging 4538 high-quality single nucleotide polymorphism (SNP) markers, we identified 28 unique significant marker-trait associations (MTAs) for MYMIV resistance, with 8 MTAs considered of high confidence due to detection across multiple GWAS models and/or environments. Notably, 4 out of 28 MTAs were found in proximity to previously reported genomic regions associated with MYMIV resistance in urdbean and mungbean, strengthening our findings and indicating consistent genomic regions for MYMIV resistance. Among the eight highly significant MTAs, one localized on chromosome 6 adjacent to previously identified quantitative trait loci for MYMIV resistance, while the remaining seven were novel. These MTAs contain several genes implicated in disease resistance, including four common ones consistently found across all eight MTAs: receptor-like serine-threonine kinases, E3 ubiquitin-protein ligase, pentatricopeptide repeat, and ankyrin repeats. Previous studies have linked these genes to defense against viral infections across different crops, suggesting their potential for further basic research involving cloning and utilization in breeding programs. This study represents the first GWAS investigation aimed at identifying resistance against MYMIV in urdbean germplasm.

Integration of QTL and transcriptome approaches for the identification of genes involved in tomato response to nitrogen deficiency.

Optimising plant nitrogen (N) usage and inhibiting N leaching loss in the soil-crop system is crucial to maintaining crop yield and reducing environmental pollution. This study aimed at identifying quantitative trait loci (QTLs) and differentially expressed genes (DEGs) between two N treatments in order to list candidate genes related to nitrogen-related contrasting traits in tomato varieties. We characterised a genetic diversity core-collection (CC) and a multi-parental advanced generation intercross (MAGIC) tomato population grown in greenhouse under two nitrogen levels and assessed several N-related traits and mapped QTLs. Transcriptome response under the two N conditions was also investigated through RNA sequencing of fruit and leaves in four parents of the MAGIC population. Significant differences in response to N input reduction were observed at the phenotypic level for biomass and N-related traits. Twenty-seven (27) QTLs were detected for three target traits (Leaf N content, leaf Nitrogen Balance Index and petiole NO3- content), ten and six at low and high N condition, respectively; while 19 QTLs were identified for plasticity traits. At the transcriptome level, 4,752 and 2,405 DEGs were detected between the two N conditions in leaves and fruits, respectively, among which 3,628 (50.6%) in leaves and 1,717 (71.4%) in fruit were genotype specific. When considering all the genotypes, 1,677 DEGs were shared between organs or tissues. Finally, we integrated DEGs and QTLs analyses to identify the most promising candidate genes. The results highlighted a complex genetic architecture of N homeostasis in tomato and novel putative genes useful for breeding tomato varieties requiring less N input.

Ecological diversification of a cyanobacterium through divergence of its novel chlorophyll d-based light-harvesting system.

The evolution of novel traits can have important consequences for biological diversification. Novelties such as new structures are associated with changes in both genotype and phenotype that often lead to changes in ecological function.1,2 New ecological opportunities provided by a novel trait can trigger subsequent trait modification or niche partitioning3; however, the underlying mechanisms of novel trait diversification are still poorly understood. Here, we report that the innovation of a new chlorophyll (Chl) pigment, Chl d, by the cyanobacterium Acaryochloris marina was followed by the functional divergence of its light-harvesting complex. We identified three major photosynthetic spectral types based on Chl fluorescence properties for a collection of A. marina laboratory strains for which genome sequence data are available,4,5 with shorter- and longer-wavelength types more recently derived from an ancestral intermediate phenotype. Members of the different spectral types exhibited extensive variation in the Chl-binding proteins as well as the Chl energy levels of their photosynthetic complexes. This spectral-type divergence is associated with differences in the wavelength dependence of both growth rate and photosynthetic oxygen evolution. We conclude that the divergence of the light-harvesting apparatus has consequently impacted A. marina ecological diversification through specialization on different far-red photons for photosynthesis.

New Insights on the Therapeutic Potential of Runt-Related Transcription Factor 2 for Osteoarthritis: Evidence from Mendelian Randomization.

INTRODUCTION: Research has highlighted the role of runt-related transcription factor 2 (Runx2) in the development of osteoarthritis (OA); however, its causal association remains unclear. This study aimed to explore whether Runx2 expression is causally associated with OA and assess its therapeutic potential for OA. METHODS: Genetic proxy instruments for Runx2 expression were obtained from gene expression quantitative trait locus (eQTLs) study of eQTLGen Consortium (n = 31,684). Aggregated genome-wide association study (GWAS) data for OA (including all OA [177,517 cases and 649,173 controls], knee OA (KOA) [62,497 cases and 333,557 controls], and hip OA (HOA) [36,445 cases and 316,943 controls]) were extracted from the Genetics of Osteoarthritis Consortium. We integrated eQTLs data with OA GWAS data to estimate their causal association and to estimate the potential of Runx2 as a drug target in the treatment of OA using summary data-based Mendelian randomization (SMR) analysis. Furthermore, different OA GWAS data (including all OA [77,052 cases and 378,169 controls], KOA [24,955 cases and 378,169 controls], and HOA [15,704 cases and 378,169 controls]) derived from the GWAS Catalog database were used for replication study. RESULTS: SMR analysis showed that high expression levels of Runx2 were associated with an increased risk of all OA [odds ratio (OR) 1.044, 95% confidence interval (CI) 1.023-1.067; P = 5.03 × 10-5], KOA (OR 1.040, 95% CI 1.006-1.075; P = 0.021), and HOA (OR 1.067, 95% CI 1.022-1.113; P = 0.003). This suggests that Runx2 inhibitors may have promising potential for the treatment of OA. Notably, the causal effects of Runx2 with all OA (OR 1.053, 95% CI 1.027-1.079; P = 3.95 × 10-5) and KOA (OR 1.043, 95% CI 1.001-1.087; P = 0.045) were repeated in the replication study, but limited evidence supported the association of Runx2 expression levels with HOA (OR 1.045, 95% CI 0.993-1.101; P = 0.094). CONCLUSIONS: Our analyses indicate a positive correlation between Runx2 expression and OA risk across all three phenotypes, suggesting the potential of Runx2 inhibitors in the treatment of OA and providing evidence from a genetic perspective.

Root nitrogen reallocation: what makes it matter?

Root nitrogen (N) reallocation involves remobilization of root N-storage pools to support shoot growth. Representing a critical yet underexplored facet of plant function, we developed innovative frameworks to elucidate its connections with key ecosystem components. First, root N reallocation increases with plant species richness and N-acquisition strategies, driven by competitive stimulation of plant N demand and synergies in N uptake. Second, competitive root traits and mycorrhizal symbioses, which enhance N foraging and uptake, exhibit trade-offs with root N reallocation. Furthermore, root N reallocation is attenuated by N-supply attributes such as increasing litter quality, soil fungi-to-bacteria ratios, and microbial recruitment in the hyphosphere/rhizosphere. These frameworks provide new insights and research avenues for understanding the ecological roles of root N reallocation.

Validity and reliability of a questionnaire to investigate people prone to accidents in different industries.

Objectives. In recent years, workplace accidents have imposed a considerable cost on industries. Accident proneness is one of the most influential factors known to cause unsafe behaviors and occupational accidents. Therefore, the present study investigated the validity and reliability of the accident proneness questionnaire in industries. Methods. The questionnaire was developed to measure accident proneness in industries - the developed instrument was distributed in East Azarbaijan industries (1100 questionaries). Content validity, confirmatory factor analysis and exploratory factor analysis were used to examine the construct validity, and Cronbach's α and the test-retest method were used to examine the reliability and reproducibility of the instrument. Results. In the face validity section, the impact score of all items was determined to be >1.5. In the content validity section, the content validity index (CVI) and the content validity ratio (CVR) were higher than the standard value of 0.42. The Cronbach's α coefficient for all dimensions was 0.914. Conclusion. The findings of the study show that the accident proneness questionnaire in industries has acceptable validity and reliability, and can be used as a comprehensive, practical, robust and reliable instrument to investigate the accident proneness of different industries.