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Simple Summary: Inner Mongolian cashmere goats (IMCGs) are an excellent local breed that formed due to natural selection and artificial breeding over a long time, and they are a world-class breed used for both cashmere and meat consumption. Growth traits are the key indicators of cashmere goats' growth, development, and health. Therefore, in this study, based on resequencing data (20×), the molecular markers and candidate genes affecting the growth traits of Inner Mongolian cashmere goats (Erlangshan type) were identified through a genome-wide association study combined with haplotype analysis. In this study, genome-wide association analysis was performed on the growth traits (body height, body length, chest circumference, chest depth, chest width, tube circumference, and body weight) of Inner Mongolian cashmere goats (Erlangshan type) based on resequencing data. The population genetic parameters were estimated, haplotypes were constructed for the significant sites, and association analysis was conducted between the haplotypes and phenotypes. A total of two hundred and eighty-four SNPs and eight candidate genes were identified by genome-wide association analysis, gene annotation, and enrichment analysis. The phenotypes of 16 haplotype combinations were significantly different by haplotype analysis. Combined with the above results, the TGFB2, BAG3, ZEB2, KCNJ12, MIF, MAP2K3, HACD3, and MEGF11 functional candidate genes and the haplotype combinations A2A2, C2C2, E2E2, F2F2, I2I2, J2J2, K2K2, N2N2, O2O2, P2P2, R1R1, T1T1, W1W1, X1X1, Y1Y1, and Z1Z1 affected the growth traits of the cashmere goats and could be used as molecular markers to improve the accuracy of early selection and the economic benefits of breeding. [ABSTRACT FROM AUTHOR]

Cultivated soybean is an important legume crop that is generally sensitive to flooding stress, including submergence and waterlogging treatments. Wild soybeans, the ancestor of cultivated soybeans, have been potential genetic resources for resistance to abiotic or biotic stresses. The present study aimed to evaluate 163 wild soybean accessions for foliar damages at the early vegetative stage and 105 accessions for germination rates, normal seedling rates, and electrical conductivity at the germination stage under submergence stress. In addition, a genome-wide association study (GWAS) was conducted to identify genomic regions associated with phenotypic measurements at these two growth stages by using MLM and FarmCPU models with publicly available genotypic data. The phenotypic evaluation revealed six and three accessions were tolerant to submergence at the early vegetative and germination stages, respectively. Notably, only one wild soybean accession showed a tolerance reaction to submergence at two stages. Through GWAS analysis, 16 and 20 SNPs across different chromosomes were determined for the submergence-related traits at the early vegetative and germination stages, respectively. Based on the linkage disequilibrium block on the detected genomic regions, ten and four putative genes were identified at the early vegetative and germination stages, respectively. Of these genes, certain genes may be related to submergence stress in wild soybeans. Further studies should be performed to validate the function of these putative genes in the responses of wild soybeans to submergence stress. [ABSTRACT FROM AUTHOR]

[Objective] Identification of single nucleotide polymorphisms (SNPs) and candidate genes significantly associated with the content of γ-aminobutyric acid (GABA) in rice grains may provide a theoretical basis for further exploring the molecular mechanism of GABA enrichment in rice grains, and lay the foundation for cultivating high-GABA content varieties. [Method] This study performed genome-wide association studies (GWAS) for GABA content with re-sequencing in 139 early japonica rice core germplasm resources in Northwest China. The candidate genes were screened based on haplotype analysis and gene annotation, and expression pattern of candidate genes were analyzed by expression profile database and fluorescence quantitative PCR. [Result] GABA content in grains showed abundant variation with a coefficient of variation of 31.25%. Genome-wide association analysis showed a total of 6 significant and representative SNPs on chromosomes 6, 8, 9, 11 and 12 were detected, and OsBADH2 and OsGABA-T2, which have been cloned in relation to GABA content. In addition, six candidate genes were predicted for GABA content in the rice grains, among which LOC_Os09g10720 was identified as highlight candidate gene, and the feasibility of its involvement in the decomposition of GABA in rice grains was further verified. [Conclusion] A total of 6 SNPs significantly associated with GABA content in rice grain are detected. And 6 candidate genes that might be associated with GABA content are screened out, they are LOC_Os09g09750, LOC_Os09g09760, LOC_Os09g10210, LOC_Os09g09820, LOC_Os09g10280 and LOC_ Os09g10720. Among them, LOC_Os09g10720 was used as a focus candidate gene. [ABSTRACT FROM AUTHOR]

Seed vigor significantly affects peanut breeding and agricultural yield by influencing seed germination and seedling growth and development. Traditional vigor testing methods are inadequate for modern high-throughput assays. Although hyperspectral technology shows potential for monitoring various crop traits, its application in predicting peanut seed vigor is still limited. This study developed and validated a method that combines hyperspectral technology with genome-wide association studies (GWAS) to achieve high-throughput detection of seed vigor and identify related functional genes. Hyperspectral phenotyping data and physiological indices from different peanut seed populations were used as input data to construct models using machine learning regression algorithms to accurately monitor changes in vigor. Model-predicted phenotypic data from 191 peanut varieties were used in GWAS, gene-based association studies, and haplotype analyses to screen for functional genes. Real-time fluorescence quantitative PCR (qPCR) was used to analyze the expression of functional genes in three high-vigor and three low-vigor germplasms. The results indicated that the random forest and support vector machine models provided effective phenotypic data. We identified Arahy.VMLN7L and Arahy.7XWF6F, with Arahy.VMLN7L negatively regulating seed vigor and Arahy.7XWF6F positively regulating it, suggesting distinct regulatory mechanisms. This study confirms that GWAS based on hyperspectral phenotyping reveals genetic relationships in seed vigor levels, offering novel insights and directions for future peanut breeding, accelerating genetic improvements, and boosting agricultural yields. This approach can be extended to monitor and explore germplasms and other key variables in various crops. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) and frailty impose substantial health and economic burdens. MDD is recognized as a significant risk factor for frailty, but the genetic associations between these conditions remain unclear. This study investigates the genetic correlation, shared pleiotropic loci, causal relationships, and comorbid genes between MDD and frailty. The genetic correlation between MDD and frailty was assessed using linkage disequilibrium score regression (LDSC) based on data from genome-wide association studies (GWAS). A detailed analysis was performed to identify shared pleiotropic loci and causal relationships through cross-phenotype association tests and Mendelian randomization. Additionally, tissue enrichment analysis was conducted using stratified LDSC, gene-based associations with both conditions were assessed using Multimarker Analysis of Genomic Annotation (MAGMA), and pathway analysis of comorbid genes was performed using the g: GOSt tool. Our findings revealed a significant positive genetic correlation between MDD and frailty (r g = 0.65, P = 1.49E-219). We identified 57 shared risk SNPs between the two conditions, including 6 novel SNPs. Mendelian randomization analyses indicated robust causal effects of MDD on frailty and vice versa. Furthermore, we observed tissue-specific heritability enrichment in 9 brain tissues. By combining MAGMA and CPASSOC analyses, we identified 10 comorbid genes associated with both MDD and frailty, primarily involved in synapse formation, modulation, plasticity, and desaturase activity. This study provides strong evidence for a shared genetic basis between MDD and frailty. The identification of comorbid genes offers new insights into the mechanisms underlying the relationship between these conditions. • A remarkably positive genetic correlation between major depressive disorder and frailty. • A total of 57 shared risk SNPs were identified between major depressive disorder and frailty, including 6 newly identified shared SNPs. • Multiple mendelian randomization methods suggest robust bidirectional causal relationship between major depressive disorder and frailty. • Both major depressive disorder and frailty were was significantly heritability enrichments in 9 brain tissues, including anterior cingulate cortex, frontal cortex, hippocampus, hypothalamus, amygdala, nucleus accumbens, putamen, caudate, and cerebellum. • Ten comorbid genes were identified. These comorbid genes are mainly enriched in synapse formation, modulation, plasticity, and desaturase activity. [ABSTRACT FROM AUTHOR]

Key message: QTL mapping combined with genome-wide association studies, revealed a potential candidate gene for resistance to northern leaf blight in the tropical CATETO-related maize line YML226, providing a basis for marker-assisted selection of maize varieties Northern leaf blight (NLB) is a foliar disease that can cause severe yield losses in maize. Identifying and utilizing NLB-resistant genes is the most effective way to prevent and control this disease. In this study, five important inbred lines of maize were used as parental lines to construct a multi-parent population for the identification of NLB-resistant loci. QTL mapping and GWAS analysis revealed that QTL qtl_YML226_1, which had the largest phenotypic variance explanation (PVE) of 9.28%, and SNP 5-49,193,921 were co-located in the CATETO-related line YML226. This locus was associated with the candidate gene Zm00001d014471, which encodes a pentatricopeptide repeat (PPR) protein. In the coding region of Zm00001d014471, YML226 had more specific SNPs than the other parental lines. qRT-PCR showed that the relative expressions of Zm00001d014471 in inoculated and uninoculated leaves of YML226 were significantly higher, indicating that the expression of the candidate gene was correlated with NLB resistance. The analysis showed that the higher expression level in YML226 might be caused by SNP mutations. This study identified NLB resistance candidate loci and genes in the tropical maize inbred line YML226 derived from the CATETO germplasm, thereby providing a theoretical basis for using modern marker-assisted breeding techniques to select genetic resources resistant to NLB. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Fusarium head blight (FHB) can cause serious yield loss and significant mycotoxin contamination, which seriously threaten global food security and safety. Breeding stable and durable cultivars that are resistant to FHB is one of the most effective approaches to controlling this disease. Fhb1 is a well-known genetic locus for FHB resistance, but its resistance is not always effective across diverse wheat genetic backgrounds. To achieve a high and durable level of resistance, the discovery and use of additional quantitative trait loci (QTL) for FHB resistance are essentially needed in breeding programs. In this study, two independent wheat natural populations of different origins were used for mining resistance QTL with a major and stable effect. Using genome-wide association analysis (GWAS), a total of 58 marker–trait associations (MTAs) on chromosomes 1A, 2B, 3A, 3B, 4A, 4B, 4D, 5A, 5B, 5D, 6A, 6B, 6D, 7A and 7B were found to be significant for type II resistance to FHB. These 58 MTAs represent 24 putative QTL. Among these QTL, Qfhb.yzu.3B.1 and Qfhb.yzu.6B.3 were stably detected in the two natural populations across three consecutive experimental years. The favorable haplotypes at the two QTL could significantly reduce the disease severity, either individually or in combination. These two QTL are also additive to Fhb1 in cultivars with different genetic backgrounds. Breeder-friendly markers were designed to differentiate the contrasting alleles at these two loci, thus proving very useful for improving FHB resistance in wheat by marker-assisted selection. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) significantly enhance our ability to identify trait-associated genomic variants by considering the host genome. Moreover, the hologenome refers to the host organism's collective genetic material and its associated microbiome. In this study, we utilized the hologenome framework, called Hologenome-wide association studies (HWAS), to dissect the architecture of complex traits, including milk yield, methane emissions, rumen physiology in cattle, and gut microbial composition in pigs. We employed four statistical models: (1) GWAS, (2) Microbial GWAS (M-GWAS), (3) HWAS-CG (hologenome interaction estimated using COvariance between Random Effects Genome-based restricted maximum likelihood (CORE-GREML)), and (4) HWAS-H (hologenome interaction estimated using the Hadamard product method). We applied Bonferroni correction to interpret the significant associations in the complex traits. The GWAS and M-GWAS detected one and sixteen significant SNPs for milk yield traits, respectively, whereas the HWAS-CG and HWAS-H each identified eight SNPs. Moreover, HWAS-CG revealed four, and the remaining models identified three SNPs each for methane emissions traits. The GWAS and HWAS-CG detected one and three SNPs for rumen physiology traits, respectively. For the pigs' gut microbial composition traits, the GWAS, M-GWAS, HWAS-CG, and HWAS-H identified 14, 16, 13, and 12 SNPs, respectively. We further explored these associations through SNP annotation and by analyzing biological processes and functional pathways. Additionally, we integrated our GWA results with expression quantitative trait locus (eQTL) data using transcriptome-wide association studies (TWAS) and summary-based Mendelian randomization (SMR) methods for a more comprehensive understanding of SNP-trait associations. Our study revealed hologenomic variability in agriculturally important traits, enhancing our understanding of host-microbiome interactions. [ABSTRACT FROM AUTHOR]

An appropriate flowering period is an important selection criterion in maize breeding. It plays a crucial role in the ecological adaptability of maize varieties. To explore the genetic basis of flowering time, GWAS and GS analyses were conducted using an associating panel consisting of 379 multi-parent DH lines. The DH population was phenotyped for days to tasseling (DTT), days to pollen-shedding (DTP), and days to silking (DTS) in different environments. The heritability was 82.75%, 86.09%, and 85.26% for DTT, DTP, and DTS, respectively. The GWAS analysis with the FarmCPU model identified 10 single-nucleotide polymorphisms (SNPs) distributed on chromosomes 3, 8, 9, and 10 that were significantly associated with flowering time-related traits. The GWAS analysis with the BLINK model identified seven SNPs distributed on chromosomes 1, 3, 8, 9, and 10 that were significantly associated with flowering time-related traits. Three SNPs 3_198946071, 9_146646966, and 9_152140631 showed a pleiotropic effect, indicating a significant genetic correlation between DTT, DTP, and DTS. A total of 24 candidate genes were detected. A relatively high prediction accuracy was achieved with 100 significantly associated SNPs detected from GWAS, and the optimal training population size was 70%. This study provides a better understanding of the genetic architecture of flowering time-related traits and provides an optimal strategy for GS. [ABSTRACT FROM AUTHOR]

Seven grain quality traits were tested in the panel of 188 winter wheat accessions from Xinjiang. Twelve co-associated genetic loci were detected in four different environments via GWAS, explaining 6.021%-31.467% phenotypic variation. Two pleiotropism loci, located on chromosomes 6A and 2B, associated with protein content and settlement value, protein content and bulk density of wheat. Five pleiotropism loci, located on 3A, 1B, 6B, 7B, and 7D, shared by protein content and wet gluten content. One pleiotropism locus, located on 5B chromosome, associated with settlement value, bulk density of wheat and grain hardness. Three pleiotropism loci located on 7A, 3B, and 2D, respectively, which shared by protein content, settlement value, and wet gluten content, while one pleiotropism locus with unknown site was also associated with protein content, settlement value, and wet gluten content. These associated loci or genes might be employed to select favorite wheat genotypes, and cultivate elite wheat genotypes via marker-assisted selection in wheat quality breeding. Candidate genes at stable loci associated with multiple traits were searched, and 11 candidate genes that might be related to wheat grain quality with multiple traits and environments were screened. Among them, TraesCS6B01G347500 encoded a storage and transportation protein, TraesCS1B01G395400 encoded a carbohydrate transport protein/sugar transport protein, and TraesCS2D01G246500 gene encoded a protein ESKIMO1 related to cold tolerance, salt tolerance, and water conservation. These genes can be used as candidate genes for allelic variation analysis and marker development, provide molecular tools for wheat marker assisted selection breeding. [ABSTRACT FROM AUTHOR]

Maize Ustilago maydis is a disease that severely affects maize yield and quality. In this paper, we employed transcriptome sequencing and GWAS analysis to identify candidate genes and reveal disease-resistant germplasm resources, thereby laying the foundation for further analysis of the molecular mechanism of maize Ustilago maydis resistance and genetic improvement. The results of transcriptome sequencing revealed that a considerable number of receptor kinase genes, signal-transduction-related protein genes, redox-response-related genes, WRKYs, and P450s genes were significantly upregulated. There was a wide range of mutations of Ustilago maydis in maize inbred lines. Thirty-two high-resistance maize inbred lines were selected, and 16 SNPs were significantly associated with the disease index. By integrating the results of GWAS and RNA-seq, five genes related to disease resistance were identified, encoding the chitinase 1 protein, fatty acid elongase (FAE), IAA9, GATA TF8, and EREB94, respectively. It provides a certain reference for the cloning of maize anti-tumor smut genes and the breeding of new varieties. [ABSTRACT FROM AUTHOR]

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Teat number (TNUM) is an important reproductive trait of sows, which affects the weaning survival rate of piglets. In this study, 1166 Dutch Large White pigs with TNUM phenotype were used as the research object. These pigs were genotyped by 50K SNP chip and the chip data were further imputed to the resequencing level. The estimated heritabilities of left teat number (LTN), right teat number (RTN) and total teat number (TTN) were 0.21, 0.19 and 0.3, respectively. Based on chip data, significant SNPs for RTN on SSC2, SSC5, SSC9 and SSC13 were identified using genome‐wide association analysis (GWAS). Significant SNPs for TTN were identified on SSC2, SSC5 and SSC7. Based on imputed data, the GWAS identified a significant SNP (rs329158522) for LTN on SSC17, two significant SNPs (rs342855242 and rs80813115) for RTN on SSC2 and SSC9, and two significant SNPs (rs327003548 and rs326943811) for TTN on SSC5 and SSC6. Among them, four novel QTL were discovered. The Bayesian fine‐mapping method was used to fine map the QTL identified in the GWAS of the imputed data, and the confidence intervals of QTL affecting LTN (SSC17: 45.22–46.20 Mb), RTN (SSC9: 122.18–122.80 Mb) and TTN (SSC5: 14.01–15.91 Mb, SSC6: 120.06–121.25 Mb) were detected. A total of 52 candidate genes were obtained. Furthermore, we identified five candidate genes, WNT10B, AQP5, FMNL3, NUAK1 and CKAP4, for the first time, which involved in breast development and other related functions by gene annotation. Overall, this study provides new molecular markers for the breeding of teat number in pigs. [ABSTRACT FROM AUTHOR]

Salt stress poses a significant challenge to crop productivity, and understanding the genetic basis of salt tolerance is paramount for breeding resilient soybean varieties. In this study, a soybean natural population was evaluated for salt tolerance during the germination stage, focusing on key germination traits, including germination rate (GR), germination energy (GE), and germination index (GI). It was seen that under salt stress, obvious inhibitions were found on these traits, with GR, GE, andGI diminishing by 32% to 54% when compared to normal conditions. These traits displayed a coefficient of variation (31.81% to 50.6%) and a substantial generalized heritability (63.87% to 86.48%). Through GWAS, a total of 1841 significant singlenucleotide polymorphisms (SNPs)were identified to be associated with these traits, distributed across chromosome 2, 5, 6, and 20. Leveraging these significant association loci, 12 candidate genes were identified to be associated with essential functions in coordinating cellular responses, regulating osmotic stress, mitigating oxidative stress, clearing reactive oxygen species (ROS), and facilitating heavymetal ion transport - all of which are pivotal for plant development and stress tolerance. To validate the candidate genes, quantitative real-time polymerase chain reaction (qRT-PCR) analysis was conducted, revealing three highly expressed genes (Glyma.02G067700, Glyma.02G068900, and Glyma.02G070000) that play pivotal roles in plant growth, development, and osmoregulation. In addition, based on these SNPs related with salt tolerance, KASP (Kompetitive Allele-Specific PCR)markers were successfully designed to genotype soybean accessions. These findings provide insight into the genetic base of soybean salt tolerance and candidate genes for enhancing soybean breeding programs in this study. [ABSTRACT FROM AUTHOR]

To understand the genetic basis of soybean sulfur utilization, a genome-wide association study (GWAS) and transcriptome analysis were used to discover new sulfur utilization genes in 121 wild soybeans. The shoot sulfur accumulation (SA) and shoot sulfur concentration (SC) of 121 wild soybean seedlings growing in a Hoagland nutrient solution for 14 days were evaluated in a greenhouse. The maximum coefficients of variation of SA and SC were 66.79% and 49.74%, respectively. An analysis of variance revealed that SA and SC had significant differences among materials. Compared with SC, SA had higher heritability (68%) and was significantly positively correlated with multiple agronomic traits. According to the GWAS, 33 and 18 single nucleotide polymorphisms (SNPs) were significantly associated with SA and SC, respectively. Six quantitative trait loci containing ten SNPs associated with SA were mapped in two or three environments on chromosome 9, 12, 13, 14, 15, and 19. Twenty-seven candidate genes were identified in the six stable loci by searching the low-sulfur-induction soybean transcriptome. A genetic diversity analysis of the ribosomal gene GsRPL35, a candidate gene on chromosome 15, revealed 10 haplotypes (Hap1-10) based on 7 SNPs in 99 wild soybeans. Wild soybeans carrying Hap2 had a higher SA than those carrying Hap6. In general, the results provide novel sulfur accumulation loci and candidate genes for sulfur utilization improvements in soybean in the future. [ABSTRACT FROM AUTHOR]

Mercury (Hg) pollution not only poses a threat to the environment but also adversely affects the growth and development of plants, with potential repercussions for animals and humans through bioaccumulation in the food chain. Maize, a crucial source of food, industrial materials, and livestock feed, requires special attention in understanding the genetic factors influencing mercury accumulation. Developing maize varieties with low mercury accumulation is vital for both maize production and human health. In this study, a comprehensive genome-wide association study (GWAS) was conducted using an enlarged SNP panel comprising 1.25 million single nucleotide polymorphisms (SNPs) in 230 maize inbred lines across three environments. The analysis identified 111 significant SNPs within 78 quantitative trait loci (QTL), involving 169 candidate genes under the Q model. Compared to the previous study, the increased marker density and optimized statistical model led to the discovery of 74 additional QTL, demonstrating improved statistical power. Gene ontology (GO) enrichment analysis revealed that most genes participate in arsenate reduction and stress responses. Notably, GRMZM2G440968, which has been reported in previous studies, is associated with the significant SNP chr6.S_155668107 in axis tissue. It encodes a cysteine proteinase inhibitor, implying its potential role in mitigating mercury toxicity by inhibiting cysteine. Haplotype analyses provided further insights, indicating that lines carrying hap3 exhibited the lowest mercury content compared to other haplotypes. In summary, our study significantly enhances the statistical power of GWAS, identifying additional genes related to mercury accumulation and metabolism. These findings offer valuable insights into unraveling the genetic basis of mercury content in maize and contribute to the development of maize varieties with low mercury accumulation. [ABSTRACT FROM AUTHOR]

Background: Previous studies have demonstrated the coexistence of erythema nodosum (EN) and inflammatory bowel disease (IBD), while the exact etiology of the co‐occurrence of the two disorders remains uncertain. Methods: A bidirectional two‐sample Mendelian randomization (MR) design was employed to determine the causal link between EN and IBD. Genetic variations associated with Crohn's disease (CD) and ulcerative colitis (UC) were derived from accessible genome‐wide association studies pertaining to European ancestry. The FinnGen database was used to find the genetic variations containing EN. In the forward model, IBD was identified as the exposure, whereas in the reverse model, EN was identified as the exposure. The causal link between IBD and EN was examined using a range of different analysis techniques, the primary one being the inverse variance weighted (IVW) method, including inverse variance weighted‐fixed effects (IVW‐FE) and inverse‐variance weighted‐multiplicative random effects (IVW‐MRE). To strengthen the results, assessments of sensitivity, heterogeneity, and pleiotropy were also conducted. Results: MR results showed that IBD increased the risk of EN (IVW‐MRE: OR = 1.242, 95% CI = 1.068–1.443, p = 0.005). Furthermore, there was a strong correlation found between CD and a higher risk of EN (IVW‐FE: OR = 1.250, 95% CI = 1.119–1.396, p = 8.036 × 10−5). However, UC did not appear to be linked to EN (IVW‐FE: OR = 1.104, 95% CI = 0.868–1.405, p = 0.421). The reverse MR analysis findings did not imply that EN was linked to IBD. Horizontal pleiotropy did not appear to exist, and the robustness of these findings was confirmed. Conclusion: The current investigation found that in European populations, IBD and its subtype CD could raise the incidence of EN. [ABSTRACT FROM AUTHOR]

BackgroundThe causal associations between dietary intake and the risk and severity of Inflammatory Arthritis (IA) are currently unknown.ObjectiveIn this study, we aimed to investigate the causal relationship between nine dietary categories (30 types of diet) and IA using Mendelian randomization (MR).MethodsWe analyzed data from 30 diets and IA in a genome-wide association study (GWAS). Single nucleotide polymorphisms (SNPs) that could influence the results of MR analyses were screened out through the Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test. SNPs were analyzed through two-sample bidirectional MR using inverse variance weighting, MR-Egger regression, and weighted median method. The multiplicity and heterogeneity of SNPs were assessed using MR-Egger intercept term tests and Cochran’s Q tests. FDR correction was used to correct the p-values.ResultsIVW results showed that Beef intake [Odds ratio (OR) = 2.862; 95% confidence interval (CI), 1.360–6.021, p = 0.006, p_fdr 0.05) was positively associated with psoriatic arthritis (PsA); Cheese intake (OR = 0.579; 95% CI, 0.367–0.914, p = 0.019, p_fdr > 0.05) was negatively associated with PsA; both were suggestive evidence. Processed meat intake (OR = 0.238; 95% CI, 0.100–0.565, p = 0.001, p_fdr 0.05) and no directional pleiotropy was detected. Leave-one-out analyses demonstrated the robustness of the causal relationship in the positive results.ConclusionOur study presents genetic evidence supporting a causal relationship between diet and an increased risk of IA. It also identifies a causal relationship between various dietary modalities and different types of IA. These findings have significant implications for the prevention and management of IA through dietary modifications.

Eggshell color is an important visual characteristic that affects consumer preferences for eggs. Eggshell color, which has moderate to high heritability, can be effectively enhanced through molecular marker selection. Various studies have been conducted on eggshell color at specific time points. However, few longitudinal data are available on eggshell color. Therefore, the objective of this study was to investigate eggshell color using the Commission International de L'Eclairage L*a*b* system with multiple measurements at different ages (age at the first egg and at 32, 36, 40, 44, 48, 52, 56, 60, 66, and 72 weeks) within the same individuals from an F2 resource population produced by crossing White Leghorn and Dongxiang Blue chicken. Using an Affymetrix 600 single nucleotide polymorphism (SNP) array, we estimated the genetic parameters of the eggshell color trait, performed genome-wide association studies (GWASs), and screened for the potential candidate genes. The results showed that pink-shelled eggs displayed a significant negative correlation between L* values and both a* and b* values. Genetic heritability based on SNPs showed that the heritability of L*, a*, and b* values ranged from 0.32 to 0.82 for pink-shelled eggs, indicating a moderate to high level of genetic control. The genetic correlations at each time point were mostly above 0.5. The major-effect regions affecting the pink eggshell color were identified in the 10.3–13.0 Mb interval on Gallus gallus chromosome 20, and candidate genes were selected, including SLC35C2, PCIF1, and SLC12A5. Minor effect polygenic regions were identified on chromosomes 1, 6, 9, 12, and 15, revealing 11 candidate genes, including MTMR3 and SLC35E4. Members of the solute carrier family play an important role in influencing eggshell color. Overall, our findings provide valuable insights into the phenotypic and genetic aspects underlying the variation in eggshell color. Using GWAS analysis, we identified multiple quantitative trait loci (QTLs) for pink eggshell color, including a major QTL on chromosome 20. Genetic variants associated with eggshell color may be used in genomic breeding programs.

ABSTRACT: Plumage color is a characteristic trait of ducks that originates as a result of natural and artificial selection. As a conspicuous phenotypic feature, it is a breed characteristic. Previous studies have identified some genes associated with the formation of black and white plumage in ducks. However, studies on the genetic basis underlying the red plumage phenotype in ducks are limited. Here, genome-wide association analysis (GWAS) and selection signal detection (Fst, θπ ratio, and cross-population composite likelihood ratio [XP-CLR]) were conducted to identify candidate regions and genes underlying duck plumage color phenotype. Selection signal detection revealed 29 overlapping genes (including ENPP1 and ULK1) significantly associated with red plumage color in Ji'an Red ducks. ENSAPLG00000012679, ESRRG, and SPATA5 were identified as candidate genes associated with red plumage using GWAS. Selection signal detection revealed that 19 overlapping genes (including GMDS, PDIA6, and ODC1) significantly correlated with light brown plumage in Brown Tsaiya ducks. GWAS to narrow down the significant regions further revealed nine candidate genes (AKT1, ATP6V1C2, GMDS, LRP4, MAML3, PDIA6, PLD5, TMEM63B, and TSPAN8). Notably, in Brown Tsaiya ducks, GMDS, ODC1, and PDIA6 exhibit significantly differentiated allele frequencies among other feather-colored ducks, while in Ji'an Red ducks, ENSAPLG00000012679 has different allele frequency distributions compared with that in other feather-colored ducks. This study offers new insights into the variation and selection of the red plumage phenotype using GWAS and selective signals.

ABSTRACT: Egg weight (EW) and age at first egg (AFE) are economically important traits in breeder chicken production. The genetic basis of these traits, however, is far from understood, especially for broiler breeders. In this study, genetic parameter estimation, genome-wide association analysis, meta-analysis, and selective sweep analysis were carried out to identify genetic loci associated with EW and AFE in 6,842 broiler breeders. The study found that the heritability of EW ranged from 0.42 to 0.44, while the heritability of AFE was estimated at 0.33 in the maternal line. Meta-analysis and selective sweep analysis identified two colocalized regions on GGA4 that significantly influenced EW at 32 wk (EW32W) and at 43 wk (EW43W) with both paternal and maternal lines. The genes AR, YIPF6, and STARD8 were located within the significant region (GGA4: 366.86-575.50 kb), potentially affecting EW through the regulation of follicle development, cell proliferation, and lipid transfer etc. The promising genes LCORL and NCAPG were positioned within the significant region (GGA4:75.35-75.42 Mb), potentially influencing EW through pleiotropic effects on growth and development. Additionally, 3 significant regions were associated with AFE on chromosomes GGA7, GGA19, and GGA27. All of these factors affected the AFE by influencing ovarian development. In our study, the genomic information from both paternal and maternal lines was used to identify genetic regions associated with EW and AFE. Two genomic regions and eight genes were identified as the most likely candidates affecting EW and AFE. These findings contribute to a better understanding of the genetic basis of egg production traits in broiler breeders and provide new insights into future technology development.

Abstract Background As an important vegetable crop, cultivated lettuce is grown worldwide and a great variety of agronomic traits have been preserved within germplasm collections. The mechanisms underlying these phenotypic variations remain to be elucidated in association with sequence variations. Compared with single nucleotide polymorphisms, structural variations (SVs) that have more impacts on gene functions remain largely uncharacterized in the lettuce genome. Results Here, we produced a comprehensive SV set for 333 wild and cultivated lettuce accessions. Comparison of SV frequencies showed that the SVs prevalent in L. sativa affected the genes enriched in carbohydrate derivative catabolic and secondary metabolic processes. Genome-wide association analysis of seven agronomic traits uncovered potentially causal SVs associated with seed coat color and leaf anthocyanin content. Conclusion Our work characterized a great abundance of SVs in the lettuce genome, and provides a valuable genomic resource for future lettuce breeding.

Abstract Accelerating biomass improvement is a major goal of Miscanthus breeding. The development and implementation of genomic‐enabled breeding tools, like marker‐assisted selection (MAS) and genomic selection, has the potential to improve the efficiency of Miscanthus breeding. The present study conducted genome‐wide association (GWA) and genomic prediction of biomass yield and 14 yield‐components traits in Miscanthus sacchariflorus. We evaluated a diversity panel with 590 accessions of M. sacchariflorus grown across 4 years in one subtropical and three temperate locations and genotyped with 268,109 single‐nucleotide polymorphisms (SNPs). The GWA study identified a total of 835 significant SNPs and 674 candidate genes across all traits and locations. Of the significant SNPs identified, 280 were localized in mapped quantitative trait loci intervals and proximal to SNPs identified for similar traits in previously reported Miscanthus studies, providing additional support for the importance of these genomic regions for biomass yield. Our study gave insights into the genetic basis for yield‐component traits in M. sacchariflorus that may facilitate marker‐assisted breeding for biomass yield. Genomic prediction accuracy for the yield‐related traits ranged from 0.15 to 0.52 across all locations and genetic groups. Prediction accuracies within the six genetic groupings of M. sacchariflorus were limited due to low sample sizes. Nevertheless, the Korea/NE China/Russia (N = 237) genetic group had the highest prediction accuracy of all genetic groups (ranging 0.26–0.71), suggesting that with adequate sample sizes, there is strong potential for genomic selection within the genetic groupings of M. sacchariflorus. This study indicated that MAS and genomic prediction will likely be beneficial for conducting population‐improvement of M. sacchariflorus.

In this study, genome-wide association analysis was performed on the growth traits (body height, body length, chest circumference, chest depth, chest width, tube circumference, and body weight) of Inner Mongolian cashmere goats (Erlangshan type) based on resequencing data. The population genetic parameters were estimated, haplotypes were constructed for the significant sites, and association analysis was conducted between the haplotypes and phenotypes. A total of two hundred and eighty-four SNPs and eight candidate genes were identified by genome-wide association analysis, gene annotation, and enrichment analysis. The phenotypes of 16 haplotype combinations were significantly different by haplotype analysis. Combined with the above results, the TGFB2, BAG3, ZEB2, KCNJ12, MIF, MAP2K3, HACD3, and MEGF11 functional candidate genes and the haplotype combinations A2A2, C2C2, E2E2, F2F2, I2I2, J2J2, K2K2, N2N2, O2O2, P2P2, R1R1, T1T1, W1W1, X1X1, Y1Y1, and Z1Z1 affected the growth traits of the cashmere goats and could be used as molecular markers to improve the accuracy of early selection and the economic benefits of breeding.

Cultivated soybean is an important legume crop that is generally sensitive to flooding stress, including submergence and waterlogging treatments. Wild soybeans, the ancestor of cultivated soybeans, have been potential genetic resources for resistance to abiotic or biotic stresses. The present study aimed to evaluate 163 wild soybean accessions for foliar damages at the early vegetative stage and 105 accessions for germination rates, normal seedling rates, and electrical conductivity at the germination stage under submergence stress. In addition, a genome-wide association study (GWAS) was conducted to identify genomic regions associated with phenotypic measurements at these two growth stages by using MLM and FarmCPU models with publicly available genotypic data. The phenotypic evaluation revealed six and three accessions were tolerant to submergence at the early vegetative and germination stages, respectively. Notably, only one wild soybean accession showed a tolerance reaction to submergence at two stages. Through GWAS analysis, 16 and 20 SNPs across different chromosomes were determined for the submergence-related traits at the early vegetative and germination stages, respectively. Based on the linkage disequilibrium block on the detected genomic regions, ten and four putative genes were identified at the early vegetative and germination stages, respectively. Of these genes, certain genes may be related to submergence stress in wild soybeans. Further studies should be performed to validate the function of these putative genes in the responses of wild soybeans to submergence stress.

Seed vigor significantly affects peanut breeding and agricultural yield by influencing seed germination and seedling growth and development. Traditional vigor testing methods are inadequate for modern high-throughput assays. Although hyperspectral technology shows potential for monitoring various crop traits, its application in predicting peanut seed vigor is still limited. This study developed and validated a method that combines hyperspectral technology with genome-wide association studies (GWAS) to achieve high-throughput detection of seed vigor and identify related functional genes. Hyperspectral phenotyping data and physiological indices from different peanut seed populations were used as input data to construct models using machine learning regression algorithms to accurately monitor changes in vigor. Model-predicted phenotypic data from 191 peanut varieties were used in GWAS, gene-based association studies, and haplotype analyses to screen for functional genes. Real-time fluorescence quantitative PCR (qPCR) was used to analyze the expression of functional genes in three high-vigor and three low-vigor germplasms. The results indicated that the random forest and support vector machine models provided effective phenotypic data. We identified Arahy.VMLN7L and Arahy.7XWF6F, with Arahy.VMLN7L negatively regulating seed vigor and Arahy.7XWF6F positively regulating it, suggesting distinct regulatory mechanisms. This study confirms that GWAS based on hyperspectral phenotyping reveals genetic relationships in seed vigor levels, offering novel insights and directions for future peanut breeding, accelerating genetic improvements, and boosting agricultural yields. This approach can be extended to monitor and explore germplasms and other key variables in various crops.

STUDY QUESTION Which genetic factors regulate female propensity for giving birth to spontaneous dizygotic (DZ) twins? SUMMARY ANSWER We identified four new loci, GNRH1 , FSHR , ZFPM1 , and IPO8 , in addition to previously identified loci, FSHB and SMAD3. WHAT IS KNOWN ALREADY The propensity to give birth to DZ twins runs in families. Earlier, we reported that FSHB and SMAD3 as associated with DZ twinning and female fertility measures. STUDY DESIGN, SIZE, DURATION We conducted a genome-wide association meta-analysis (GWAMA) of mothers of spontaneous dizygotic (DZ) twins (8265 cases, 264 567 controls) and of independent DZ twin offspring (26 252 cases, 417 433 controls). PARTICIPANTS/MATERIALS, SETTING, METHODS Over 700 000 mothers of DZ twins, twin individuals and singletons from large cohorts in Australia/New Zealand, Europe, and the USA were carefully screened to exclude twins born after use of ARTs. Genetic association analyses by cohort were followed by meta-analysis, phenome wide association studies (PheWAS), in silico and in vivo annotations, and Zebrafish functional validation. MAIN RESULTS AND THE ROLE OF CHANCE This study enlarges the sample size considerably from previous efforts, finding four genome-wide significant loci, including two novel signals and a further two novel genes that are implicated by gene level enrichment analyses. The novel loci, GNRH1 and FSHR , have well-established roles in female reproduction whereas ZFPM1 and IPO8 have not previously been implicated in female fertility. We found significant genetic correlations with multiple aspects of female reproduction and body size as well as evidence for significant selection against DZ twinning during human evolution. The 26 top single nucleotide polymorphisms (SNPs) from our GWAMA in European-origin participants weakly predicted the crude twinning rates in 47 non-European populations (r  = 0.23 between risk score and population prevalence, s.e. 0.11, 1-tail P = 0.058) indicating that genome-wide association studies (GWAS) are needed in African and Asian populations to explore the causes of their respectively high and low DZ twinning rates. In vivo functional tests in zebrafish for IPO8 validated its essential role in female, but not male, fertility. In most regions, risk SNPs linked to known expression quantitative trait loci (eQTLs). Top SNPs were associated with in vivo reproductive hormone levels with the top pathways including hormone ligand binding receptors and the ovulation cycle. LARGE SCALE DATA The full DZT GWAS summary statistics will made available after publication through the GWAS catalog (https://www.ebi.ac.uk/gwas/). LIMITATIONS, REASONS FOR CAUTION Our study only included European ancestry cohorts. Inclusion of data from Africa (with the highest twining rate) and Asia (with the lowest rate) would illuminate further the biology of twinning and female fertility. WIDER IMPLICATIONS OF THE FINDINGS About one in 40 babies born in the world is a twin and there is much speculation on why twinning runs in families. We hope our results will inform investigations of ovarian response in new and existing ARTs and the causes of female infertility. STUDY FUNDING/COMPETING INTEREST(S) Support for the Netherlands Twin Register came from the Netherlands Organization for Scientific Research (NWO) and The Netherlands Organization for Health Research and Development (ZonMW) grants, 904-61-193, 480-04-004, 400-05-717, Addiction-31160008, 911-09-032, Biobanking and Biomolecular Resources Research Infrastructure (BBMRI.NL, 184.021.007), Royal Netherlands Academy of Science Professor Award (PAH/6635) to DIB, European Research Council (ERC-230374), Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the Avera Institute, Sioux Falls, South Dakota (USA) and the National Institutes of Health (NIH R01 HD042157-01A1) and the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health and Grand Opportunity grants 1RC2 MH089951. The QIMR Berghofer Medical Research Institute (QIMR) study was supported by grants from the National Health and Medical Research Council (NHMRC) of Australia (241944, 339462, 389927, 389875, 389891, 389892, 389938, 443036, 442915, 442981, 496610, 496739, 552485, 552498, 1050208, 1075175). L.Y. is funded by Australian Research Council (Grant number DE200100425). The Minnesota Center for Twin and Family Research (MCTFR) was supported in part by USPHS Grants from the National Institute on Alcohol Abuse and Alcoholism (AA09367 and AA11886) and the National Institute on Drug Abuse (DA05147, DA13240, and DA024417). The Women's Genome Health Study (WGHS) was funded by the National Heart, Lung, and Blood Institute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913), with support for genotyping provided by Amgen. Data collection in the Finnish Twin Registry has been supported by the Wellcome Trust Sanger Institute, the Broad Institute, ENGAGE—European Network for Genetic and Genomic Epidemiology, FP7-HEALTH-F4-2007, grant agreement number 201413, National Institute of Alcohol Abuse and Alcoholism (grants AA-12502, AA-00145, AA-09203, AA15416, and K02AA018755) and the Academy of Finland (grants 100499, 205585, 118555, 141054, 264146, 308248, 312073 and 336823 to J. Kaprio). TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Zoe Ltd and the National Institute for Health Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London. For NESDA, funding was obtained from the Netherlands Organization for Scientific Research (Geestkracht program grant 10000-1002), the Center for Medical Systems Biology (CSMB, NVVO Genomics), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL), VU University's Institutes for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam, University Medical Center Groningen, Leiden University Medical Center, National Institutes of Health (NIH, ROI D0042157-01A, MH081802, Grand Opportunity grants 1 RC2 Ml-1089951 and IRC2 MH089995). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. Computing was supported by BiG Grid, the Dutch e-Science Grid, which is financially supported by NWO. Work in the Del Bene lab was supported by the Programme Investissements d'Avenir IHU FOReSIGHT (ANR-18-IAHU-01). C.R. was supported by an EU Horizon 2020 Marie Skłodowska-Curie Action fellowship (H2020-MSCA-IF-2014 #661527). H.S. and K.S. are employees of deCODE Genetics/Amgen. The other authors declare no competing financial interests. TRIAL REGISTRATION NUMBER N/A. [ABSTRACT FROM AUTHOR]

Schizophrenia, the most common severe mental illness, leads to a serious decrease in higher functions, mainly to a change in cognitive functions and perception of reality. Both genetic and environmental factors are involved in its pathogenesis; however, its genetic component still needs to be studied. The aim of the study was to identify genetic markers of paranoid schizophrenia in Tatars from the Republic of Bashkortostan. Genome-wide genotyping of DNA samples was carried out on the PsychChip biochip, which included 610 000 single nucleotide polymorphic variants (SNPs). The studied sample consisted of 357 patients with paranoid schizophrenia and 383 healthy individuals of Tatar ethnicity. As a result of the study, the association of the SNP rs12376586 of the MAMDC2 gene located in the region 9q21.13 with the development of paranoid schizophrenia in Tatars living in the Republic of Bashkortostan was established for the first time. [ABSTRACT FROM AUTHOR]

Schizophrenia is a highly hereditary disorder. Genetic risk is associated with a large number of alleles, including common alleles with little effect that can be found in genome-wide association studies. The aim of this study was to study genetic risk factors for the development of schizophrenia in a genome-wide association analysis (GWAS) in Russians from the Republic of Bashkortostan. The studied sample consisted of 320 patients with paranoid schizophrenia and 402 healthy individuals. GWAS genotyping of DNA samples was carried out on the PsychChip biochip, which included 610 000 single nucleotide polymorphic variants (SNPs). [ABSTRACT FROM AUTHOR]

Fujian province, an important tea-producing area in China, has abundant tea cultivars. To investigate the genetic relationships of tea plant cultivars in Fujian province and the characteristics of the tea plant varieties, a total of 70 tea cultivars from Fujian and other 12 provinces in China were subjected to restriction site-associated DNA sequencing (RAD-seq). A total of 60,258,975 single nucleotide polymorphism (SNP) sites were obtained. These 70 tea plant cultivars were divided into three groups based on analyzing the phylogenetic tree, principal component, and population structure. Selection pressure analysis indicated that nucleotide diversity was high in Southern China and genetically distinct from cultivars of Fujian tea plant cultivars, according to selection pressure analysis. The selected genes have significant enrichment in pathways associated with metabolism, photosynthesis, and respiration. There were ten characteristic volatiles screened by gas chromatography–mass spectrometry (GC–MS) coupled with multivariate statistical methods, among which the differences in the contents of methyl salicylate, 3-carene, cis-3-hexen-1-ol, (E)-4-hexen-1-ol, and 3-methylbutyraldehyde can be used as reference indicators of the geographical distribution of tea plants. Furthermore, a metabolome genome-wide association study (mGWAS) revealed that 438 candidate genes were related to the aroma metabolic pathway. Further analysis showed that 31 genes of all the selected genes were screened and revealed the reasons for the genetic differences in aroma among tea plant cultivars in Fujian and Southern China. These results reveal the genetic diversity in the Fujian tea plants as well as a theoretical basis for the conservation, development, and utilization of the Fujian highly aromatic tea plant cultivars. [ABSTRACT FROM AUTHOR]

The mining of favorable SNP loci and haplotypes is of great significance for the further cloning and molecular-assisted breeding of alkalinity-tolerance genes in rice. To improve the utilization rate of saline–alkaline lands and the yield of rice, we used the 1,322,884 SNPs obtained from the sequencing 173 of rice accessions in this study. Alkalinity-tolerance-related traits, including the germination energy (GE), germination rate (GR), seedling length (SL), root length (RL), relative alkaline damage rate (RADR) of the GERADR of the GR, RADR of the SL and RADR of the RL, were evaluated in 2019 and 2020 and revealed abundant phenotypes in the studied population. A genome-wide association analysis detected 10 quantitative trait loci (QTLs) related to alkalinity tolerance. In addition, a transcriptome sequencing analysis of the alkalinity-tolerant rice variety 'Yuedao 9' and the alkali-sensitive rice variety 'Tijin' under alkalinity stress and control conditions was performed. Three candidate genes that were predicted to be related to alkalinity tolerance in rice, namely LOC_Os06g06600, LOC_Os011g44680 and LOC_Os011g44600, were screened based on gene annotation, coding sequences and haplotype analysis. The results of this study provide important genetic information for the molecular improvement of rice. [ABSTRACT FROM AUTHOR]

The key to food security is increasing rice yield. Therefore, we performed a genome-wide association study (GWAS) to analyse and identify the effects of plant height (PH), effective tiller number (ETN), heading date (HD) and grain weight per plant (GWPP) on rice yield using 1,220,522 single-nucleotide polymorphisms (SNPs) from 168 rice accessions. The PH, ETN, HD, and GWPP phenotypes of the 168 rice accessions were analysed in 2019, 2020 and 2021, and an abundance of phenotypic variation was found. One QTL for PH was detected on chromosome 4, one QTL for ETN on chromosome 11, two QTLs for GWPP on chromosome 2, and one QTL for HD on chromosome 5, all of which were detected in 3 years of the study period through a general linear model (GLM) and mixed linear model (MLM). We detected two QTLs related to the traits by using multi-trait GWAS. In addition, we identified four novel genes responsible for rice yield. Haplotype analysis indicated that LOC_Os02g07680 was highly associated with GWPP, LOC_Os11g18570 was highly associated with ETN, LOC_Os04g49210 was highly associated with HD, and LOC_Os05g34600 was highly associated with PH. The results provide important genetic information for PH, ETN, HD and GWPP studies, laying the foundation for increasing rice yield. [ABSTRACT FROM AUTHOR]

The stomatal complex on the surface of maize leaves is closely related to photosynthesis and transpiration, and the study of maize stomatal phenotypes and the discovery of their regulatory genes are of great importance for the breeding of high-quality and high-yielding maize. In this study, rapid scanning electron microscopy was used to obtain images of the abaxial stomata of 457 maize inbred lines with extensive genetic variation, and stomata density was obtained by counting. The results of correlation showed that stomata density was significantly correlated with leaf width, and Analysis of variance found that there were significant differences (P value < 0.05) in stomata density among different leaf width and 100-grain weight. The highest stomata density was found in the inbred lines with wide and short leaves and higher 100-grain weight. Furthermore, genome-wide association analysis was performed using a mixed linear model. It showed that eight SNPs significantly associated with stomata density were obtained, which could explain 35.507% of the phenotypic variation. Among these, four SNPs on chromosome 5 were tightly linked, mainly formatting two haplotypes, CTTA (0.636) and TCCG (0.330). Twelve genes with functional annotation were identified within 100 kb upstream and downstream of the eight SNPs. One gene, GRMZM2G068277, which had been shown to be involved in plant mitotic processes and exhibited high expression at the leaf base, was therefore the most likely candidate gene for stomata density. The results presented here could provide references for further cloning of functional genes related to stomata density. [ABSTRACT FROM AUTHOR]

Accelerating biomass improvement is a major goal of Miscanthus breeding. The development and implementation of genomic‐enabled breeding tools, like marker‐assisted selection (MAS) and genomic selection, has the potential to improve the efficiency of Miscanthus breeding. The present study conducted genome‐wide association (GWA) and genomic prediction of biomass yield and 14 yield‐components traits in Miscanthus sacchariflorus. We evaluated a diversity panel with 590 accessions of M. sacchariflorus grown across 4 years in one subtropical and three temperate locations and genotyped with 268,109 single‐nucleotide polymorphisms (SNPs). The GWA study identified a total of 835 significant SNPs and 674 candidate genes across all traits and locations. Of the significant SNPs identified, 280 were localized in mapped quantitative trait loci intervals and proximal to SNPs identified for similar traits in previously reported Miscanthus studies, providing additional support for the importance of these genomic regions for biomass yield. Our study gave insights into the genetic basis for yield‐component traits in M. sacchariflorus that may facilitate marker‐assisted breeding for biomass yield. Genomic prediction accuracy for the yield‐related traits ranged from 0.15 to 0.52 across all locations and genetic groups. Prediction accuracies within the six genetic groupings of M. sacchariflorus were limited due to low sample sizes. Nevertheless, the Korea/NE China/Russia (N = 237) genetic group had the highest prediction accuracy of all genetic groups (ranging 0.26–0.71), suggesting that with adequate sample sizes, there is strong potential for genomic selection within the genetic groupings of M. sacchariflorus. This study indicated that MAS and genomic prediction will likely be beneficial for conducting population‐improvement of M. sacchariflorus. [ABSTRACT FROM AUTHOR]

Background: As an important vegetable crop, cultivated lettuce is grown worldwide and a great variety of agronomic traits have been preserved within germplasm collections. The mechanisms underlying these phenotypic variations remain to be elucidated in association with sequence variations. Compared with single nucleotide polymorphisms, structural variations (SVs) that have more impacts on gene functions remain largely uncharacterized in the lettuce genome. Results: Here, we produced a comprehensive SV set for 333 wild and cultivated lettuce accessions. Comparison of SV frequencies showed that the SVs prevalent in L. sativa affected the genes enriched in carbohydrate derivative catabolic and secondary metabolic processes. Genome-wide association analysis of seven agronomic traits uncovered potentially causal SVs associated with seed coat color and leaf anthocyanin content. Conclusion: Our work characterized a great abundance of SVs in the lettuce genome, and provides a valuable genomic resource for future lettuce breeding. [ABSTRACT FROM AUTHOR]

【Objective】This study aims to investigate SNP markers associated with leaf-type related traits in order to provide a reference for molecular marker-assisted breeding of tea plants. 【Method】In this study, simplified genome sequencing (GBS) was conducted on 91 natural tea populations collected in Sichuan. A genome-wide association analysis (GWAS) based on the GLM (Q) model was performed using 863, 468 SNP markers obtained from sequencing. Eight leaf-type related traits, including leaf length (YC), leaf width (YK), leaf length-width ratio (CKB), leaf area (YS), leaf color (YSZ), leaf tip (LD), leaf vein logarithm (YM), and leaf margin (YY), were investigated.【Result】A total of 38 significant SNP markers were detected at a p-value of ＜0.01, and there were 1 SNP marker associated with YC, 24 SNP markers associated with CKB, 6 SNP markers associated with YSZ, 2 SNP markers associated with YD, 1 SNP marker associated with YM and 4 markers associated with YY. The 38 significant SNP markers could explaine the association traits between 31.37% and 60.70%. Further candidate gene mining within the 50 kbp region upstream and downstream of the significant markers yielded. Additionally, 8 candidate genes were further identified, CSA011953 (Sec11a), CSA027293 (CAD3), CSA020561 (GAE2), CSA008530 (AIM1), CSA008531 (MFP), CSA008532 (AIM1), CSA008763 (CYP72A154), and CSA029592 (RABG3F). Through Go and Ko annotation, CSA027293 (CAD3) and CSA008763 (CYP72A154) could be closely associated with leaf length-width ratio (CKB) and leaf color (YSZ). 【Conclusion】The 38 identification of SNP markers and two candidate genes associated with tea leaf shape traits provide valuable genetic resources and a reference basis for the precise localization of genes regulating tea tree leaf shape and for molecular marker-assisted breeding. [ABSTRACT FROM AUTHOR]

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[Objective] SNPs significantly related to numbers of main stems and tubers per plant of potato were screened and candidate genes were mined to provide gene resources for molecular breeding of high-yield potatoes. [Method] The phenotyping of a core collection of 251 potato germplasms for numbers of main stems and tubers per plant was carried out in 8 environments at 4 test sites in main potato production areas during 2018-2019. The genomic DNA was extracted, and high-throughput sequencing was performed on IlluminaHiSeq™ platform for identification of high-quality SNPs markers. On this basis, genome-wide association (GWAS) analysis was carried out in combination with phenotypic data, and the candidate genes in the regions surrounding associated SNP sites were annotated through four databases including NR, Swiss-port, KEGG and GO. [Result] With interactions of environment and genotype, 251 potato germplasms showed extensive phenotypic variations in numbers of main stems and tubers per plant in 2018 and 2019. A total of 1 209 969 high-quality SNP sites were obtained. Seven SNP sites were found to be sig-nificantly associated with the number of main stems, and a total of 1 9 candidate genes were mined. There were 9 candidate genes that overlapped in at least 3 different environments, which may encode galactosyl-transferase, transcription factor MYB, and gibberellin 3-β-dioxygenase and cytochrome P450. There were 13 SNP sites significantly associated with the number of tubers per plant, and a total of 33 candidate genes were mined. Excluding the 4 candidate genes that overlapped in 2 years, 29 candidate genes were associated. Among them, 11 candidate genes overlapped in more than 3 environments, which may encode fructose-1, 6-diphosphate aldolase, auxin response factor 1AA13, transcription factors WRKY, bHLH113 and MADS-box. [Conclusion] A total of 20 SNP loci significantly related to numbers of main stems and tubers per plant were identified, and 48 candidate genes were mined in 8 environments in 2 years. [ABSTRACT FROM AUTHOR]

Sclerotinia stem rot is a broad-spectrum threat to rapeseed production, and Brassica juncea contains abundant genetic resources for resistance against Sclerotinia sclerotiorum. Therefore, it is of great significance to carry out screening, localization, and exploration of resistance loci for sclerotinia stem rot in Brassica juncea germplasm resources for the breeding of Sclerotinia-resistant rapeseed. In this study, the S. sclerotiorum resistance of Brassica juncea germplasm resources collected from various regions in Yunnan Province was evaluated under three different growth environments, and a whole-genome association analysis of S. sclerotiorum resistance loci was conducted based on the resequencing data of 91 Brassica juncea germplasm materials. According to the results of leaf identification under in vitro conditions in the three growth environments, one highly resistant germplasm material J7667 and one relatively resistant germplasm material J047 were selected. The resequencing data of the 91 materials were aligned to the reference genome of Brassica juncea for variation detection analysis, resulting in the detection of 11 337 871 SNPs and 40 170 Indels distributed on the 18 chromosomes of Brassica juncea. After data filtering, 403 211 high-quality SNPs were obtained. The phenotypic data of in vitro leaves, in vitro stems, and stem resistance to S. sclerotiorum of the 91 materials under the three growth environments were subjected to whole-genome association analysis using two analysis software, Emmax and Tassel. In the in vitro leaves, both analysis methods identified a total of 62 significantly associated SNP loci with resistance in the three different growth environments, including 23 and 39 significantly associated SNP loci in the Luoping winter sowing and Xiaoshao winter sowing environments, respectively, while no resistance loci were detected in the Xiaoshao summer sowing environment. In the stem of Luoping winter sowing, both methods detected 3 significantly associated SNP loci with resistance, while no significant SNP was detected in the stem of Xiaoshao summer sowing. In the Tassel method, closely located resistance SNP loci were detected on chromosomes A2, A8, and B2 in Luoping winter sowing and Xiaoshao winter sowing, while in the Emmax method, closely located resistance SNP loci were detected on chromosomes B5 and B8 in Luop-ing winter sowing and Xiaoshao winter sowing. In addition, this study mapped the previously identified S. sclerotio-rum resistance QTL loci and the resistance loci identified in this study to the reference genome of Brassica juncea. It was found that the resistance QTL intervals identified in this study (XLRA2-2, XLRA1-4) overlapped with the reported resistance QTL loci Sll2 and qsr10-1, respectively. [ABSTRACT FROM AUTHOR]

Background: Kidney diseases pose a significant global health burden; there is an urgent need to deepen our understanding of their underlying mechanisms. Summary: This review focuses on new innovative approaches that merge genome-wide association studies (GWAS) and single-cell omics (including transcriptomics) in kidney disease research. We begin by detailing how GWAS has identified numerous genetic risk factors, offering valuable insight into disease susceptibility. Then, we explore the application of scRNA-seq, highlighting its ability to unravel how genetic variants influence cellular phenotypes. Through a synthesis of recent studies, we illuminate the synergy between these two powerful methodologies, demonstrating their potential in elucidating the complex etiology of kidney diseases. Moreover, we discuss how this integrative approach could pave the way for precise diagnostics and personalized treatments. Key Message: This review underscores the transformative potential of combining GWAS and scRNA-seq in the journey toward a deeper understanding of kidney diseases.

Abstract Background Due to the influence of extreme weather, the environment in China’s main cotton-producing areas is prone to drought stress conditions, which affect the growth and development of cotton and lead to a decrease in cotton yield. Results In this study, 188 upland cotton germplasm resources were phenotyped for data of 8 traits (including 3 major yield traits) under drought conditions in three environments for two consecutive years. Correlation analysis revealed significant positive correlations between the three yield traits. Genetic analysis showed that the estimated heritability of the seed cotton index (SC) under drought conditions was the highest (80.81%), followed by that of boll weight (BW) (80.64%) and the lint cotton index (LC) (70.49%) With genome-wide association study (GWAS) analysis, a total of 75 quantitative trait loci (QTLs) were identified, including two highly credible new QTL hotspots. Three candidate genes (Gh_D09G064400, Gh_D10G261000 and Gh_D10G254000) located in the two new QTL hotspots, QTL51 and QTL55, were highly expressed in the early stage of fiber development and showed significant correlations with SC, LC and BW. The expression of three candidate genes in two extreme materials after drought stress was analyzed by qRT-PCR, and the expression of these two materials in fibers at 15, 20 and 25 DPA. The expression of these three candidate genes was significantly upregulated after drought stress and was significantly higher in drought-tolerant materials than in drought-sensitive materials. In addition, the expression levels of the three candidate genes were higher in the early stage of fiber development (15 DPA), and the expression levels in drought-tolerant germplasm were higher than those in drought-sensitive germplasm. These three candidate genes may play an important role in determining cotton yield under drought conditions. Conclusions This study is helpful for understanding the regulatory genes affecting cotton yield under drought conditions and provides germplasm and candidate gene resources for breeding high-yield cotton varieties under these conditions.

Maize Ustilago maydis is a disease that severely affects maize yield and quality. In this paper, we employed transcriptome sequencing and GWAS analysis to identify candidate genes and reveal disease-resistant germplasm resources, thereby laying the foundation for further analysis of the molecular mechanism of maize Ustilago maydis resistance and genetic improvement. The results of transcriptome sequencing revealed that a considerable number of receptor kinase genes, signal-transduction-related protein genes, redox-response-related genes, WRKYs, and P450s genes were significantly upregulated. There was a wide range of mutations of Ustilago maydis in maize inbred lines. Thirty-two high-resistance maize inbred lines were selected, and 16 SNPs were significantly associated with the disease index. By integrating the results of GWAS and RNA-seq, five genes related to disease resistance were identified, encoding the chitinase 1 protein, fatty acid elongase (FAE), IAA9, GATA TF8, and EREB94, respectively. It provides a certain reference for the cloning of maize anti-tumor smut genes and the breeding of new varieties.

Fusarium head blight (FHB) can cause serious yield loss and significant mycotoxin contamination, which seriously threaten global food security and safety. Breeding stable and durable cultivars that are resistant to FHB is one of the most effective approaches to controlling this disease. Fhb1 is a well-known genetic locus for FHB resistance, but its resistance is not always effective across diverse wheat genetic backgrounds. To achieve a high and durable level of resistance, the discovery and use of additional quantitative trait loci (QTL) for FHB resistance are essentially needed in breeding programs. In this study, two independent wheat natural populations of different origins were used for mining resistance QTL with a major and stable effect. Using genome-wide association analysis (GWAS), a total of 58 marker–trait associations (MTAs) on chromosomes 1A, 2B, 3A, 3B, 4A, 4B, 4D, 5A, 5B, 5D, 6A, 6B, 6D, 7A and 7B were found to be significant for type II resistance to FHB. These 58 MTAs represent 24 putative QTL. Among these QTL, Qfhb.yzu.3B.1 and Qfhb.yzu.6B.3 were stably detected in the two natural populations across three consecutive experimental years. The favorable haplotypes at the two QTL could significantly reduce the disease severity, either individually or in combination. These two QTL are also additive to Fhb1 in cultivars with different genetic backgrounds. Breeder-friendly markers were designed to differentiate the contrasting alleles at these two loci, thus proving very useful for improving FHB resistance in wheat by marker-assisted selection.

Genome-wide association studies (GWAS) significantly enhance our ability to identify trait-associated genomic variants by considering the host genome. Moreover, the hologenome refers to the host organism’s collective genetic material and its associated microbiome. In this study, we utilized the hologenome framework, called Hologenome-wide association studies (HWAS), to dissect the architecture of complex traits, including milk yield, methane emissions, rumen physiology in cattle, and gut microbial composition in pigs. We employed four statistical models: (1) GWAS, (2) Microbial GWAS (M-GWAS), (3) HWAS-CG (hologenome interaction estimated using COvariance between Random Effects Genome-based restricted maximum likelihood (CORE-GREML)), and (4) HWAS-H (hologenome interaction estimated using the Hadamard product method). We applied Bonferroni correction to interpret the significant associations in the complex traits. The GWAS and M-GWAS detected one and sixteen significant SNPs for milk yield traits, respectively, whereas the HWAS-CG and HWAS-H each identified eight SNPs. Moreover, HWAS-CG revealed four, and the remaining models identified three SNPs each for methane emissions traits. The GWAS and HWAS-CG detected one and three SNPs for rumen physiology traits, respectively. For the pigs’ gut microbial composition traits, the GWAS, M-GWAS, HWAS-CG, and HWAS-H identified 14, 16, 13, and 12 SNPs, respectively. We further explored these associations through SNP annotation and by analyzing biological processes and functional pathways. Additionally, we integrated our GWA results with expression quantitative trait locus (eQTL) data using transcriptome-wide association studies (TWAS) and summary-based Mendelian randomization (SMR) methods for a more comprehensive understanding of SNP-trait associations. Our study revealed hologenomic variability in agriculturally important traits, enhancing our understanding of host-microbiome interactions.

Flowering time and fruit yield are important traits in watermelon crop improvement. There is limited information on the inheritance and genomic loci underlying flowering time and yield performance, especially in citron watermelon. A total of 125 citron watermelon accessions were evaluated in field trials over two growing seasons for days to male and female flowers, fruit count, fruit weight, and fruit yield. The germplasm was genotyped with more than two million single-nucleotide polymorphism (SNP) markers generated via whole-genome resequencing. Trait mapping was conducted using a genomewide association study (GWAS). Broad-sense heritability for all traits ranged from moderate to high, indicating that genetic improvement through breeding and selection is feasible. Significant marker-trait associations were uncovered for days to female flower (chromosomes Ca04, Ca05, Ca08, and Ca09), fruit count (on Ca02, Ca03, and Ca05), fruit weight (on Ca02, Ca06, Ca08, Ca10, and Ca11), and fruit yield on chromosomes Ca05, Ca07, and Ca09. The phenotypic variation explained by the significant SNPs ranged from 1.6 to 25.4, highlighting the complex genetic architecture of the evaluated traits. Candidate genes relevant to flowering time and fruit yield component traits were uncovered on chromosomes Ca02, Ca04, Ca05, Ca06, Ca09, and Ca11. These results lay a foundation for marker-assisted trait introgression of flowering time and fruit yield component traits in watermelons. [ABSTRACT FROM AUTHOR]

[Objective] Conduct genetic analysis of the main nutritional quality traits of maize stems at the molecular level. to provide theoretical basis for genetic improvement of the main nutritional quality traits of maize stems. (Methods] The study used 381 different types of maize inbred lines as associated populations and planted randomly in the experimental field of the Hebi Academy of Agricultural Sciences in Henan Province in 2016 and 2017. The nutritional quality traits acid washing fiber (ADF), neutral washing fiber (NDF), and digestibility (IVDMD) were investigated during the heading, filling, and maturity stages. Using the Maize SNP50 gene chip. 461 053 high-quality SNPs were obtained for genome-wide association analysis. [Results] Using the generalized linear model (GLM) analysis, a total of 392 significantly correlated stem nutritional quality traits SNPs (P<1.08x10-7) were detected on 10 chromosomes of maize during different growth stages of the two years, with phenotypic variation interpretation rates of 9.69% -17.34%. 97 SNPs were found to be independently associated more than twice, resulting in a total of 77 candidate genes associated with stem nutritional quality traits. Using the mixed linear model (MLM) analysis, a total of 257 significantly correlated SNPs were detected over the two years (P<2.17x10-6), with phenotypic variation interpretation rates of 9.82% -20.20% 17 SNPs were found to be independently associated more than twice, resulting in a total of 82 candidate genes. Among them, 10 overlap with GLM model candidate genes. A total of 159 candidate association genes were identified by GLM and MLM, among which 43 candidate genes were detected twice or more. Zm00001/021261 was found to be associated with ADF, NDF, and IVDMD in different years 31 times at multiple loci. This gene encoded ATP binding protein and chloroplast sensor kinase, had the highest expression in leaves at maturity stage. Zm00001/021255 was found to be associated with stem nutritional quality traits 10 times at two loci. This gene encoded cysteine rich receptor like protein kinase 25, which was only expressed in developmental internodes and female panicles, can be further studied and validated. [Conclusion]Using GLM and MLM models could quickly and effectively associate significant loci related to maize stem nutrient quality. HC-SNP could be screened through repetitive significant loci, and then associated gene enrichment regions could be excavated. [ABSTRACT FROM AUTHOR]