Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies

Inheritance of resilience: genetic Mapping of transgenerational and intergenerational drought stress memory in wheat

Drought stress is a critical challenge for global wheat production, threatening food security by reducing crop yields and quality. The ability of wheat to adapt to and survive under drought conditions is largely dependent on its genetic makeup. Therefore, understanding the genetic associations controlling the effects of intergenerational and transgenerational stress memory underlying drought exposure histories in a diverse collection of 111 wheat accessions using a genome-wide association study (GWAS) plays a significant role in sustaining yields. In this study, we conducted a comprehensive comparison between seeds from the second-generation group that were not subjected to drought stress (C1C2) and seeds from groups that experienced drought stress in one generation, either two generations prior (D1C2; transgenerational drought memory) or in the preceding generation (C1D2; intergenerational drought memory). Additionally, we analyzed seeds from the group exposed to drought stress in both generations (D1D2; combined drought memory). Our findings reveal that historical exposure to drought stress, irrespective of the specific generational context, led to significant alterations in several key plant characteristics, including spike length, the number of spikelets per spike, grain number per spike, grain weight per spike, thousand kernel weight, and levels of both enzymatic and non-enzymatic antioxidants. These results suggest that previous encounters with drought stress impart a lasting impact on the plant, potentially priming it for altered responses under future stress conditions. Using GWAS analysis, we identified highly significant associations and candidate genes associated with most of the traits evaluated, highlighting the genetic underpinnings that may drive these stress memory effects. Interestingly, the candidate gene TraesCS2A02G432800 on chromosome 2 A mapped as Leucine-rich repeat protein 1 (LRR) that harbors the variation of all the agronomical traits for the wheat genotypes that experienced drought stress over three generations. LRR proteins are involved in various physiological processes, including stress response, making them key players in the adaptation of wheat to drought stress. This research underscores the importance of understanding environmental stressors' transgenerational and intergenerational impact on crop performance, with potential implications for breeding and agricultural resilience.

Genomic prediction in Persian walnut: Optimization levers according to genetic architecture of complex traits

Persian walnut (Juglans regia L.) is a widespread cultivated nut tree species in temperate regions. Advances in genomic tools, such as the high-density Axiom J. regia 700K single nucleotide polymorphism (SNP) genotyping array, enable the exploration of genomic prediction (GP) for this crop. This study is the first to evaluate GP accuracy and several influencing factors in walnut for traits related to phenology and nut quality. A core-collection of 170 accessions was phenotyped for 25 traits over 1 or 2 years. Highly heritable traits, such as budbreak date and female flowering date, were predicted with high accuracy (∼0.75) using ridge regression best linear unbiased prediction (rrBLUP). Three key factors influencing GP performance were examined: marker density, prediction model, and training set size. Selecting the top 1% of 364,275 SNPs based on their variance (∼3600 SNPs) was sufficient to achieve accurate predictions. Bayesian models slightly improved prediction accuracy for some traits when using this reduced SNP set, but rrBLUP provided robust results, balancing accuracy, simplicity, and computational efficiency. Training population size also influenced accuracy, with a subset comprising 50% of the population still yielding reliable predictions. Optimization of training set was assessed using coefficient of determination mean, prediction error variance mean, and mean relatedness (MeanRel) parameters, with MeanRel performing best for shell traits. However, incorporating SNPs identified in genome-wide association study into the prediction models did not enhance accuracy. In summary, this study demonstrates the feasibility and potential of GPs for walnut breeding programs using a core-collection, offering valuable insights for optimizing GP approaches in this crop.

Metabolome guided treasure hunt - learning from metabolic diversity

Metabolomics is a rapidly evolving field focused on the comprehensive identification and quantification of small molecules in biological systems. As the final layer of the biological hierarchy following of the genome, transcriptome and proteome, it presents a dynamic snapshot of phenotype, influenced by genetic, environmental and physiological factors. Whilst the metabolome sits downstream of genes and proteins, there are multiple higher levels-tissues, organs, the entire organism, and interactions with other organisms, which need to be considered in order to fully comprehend organismal biology. Advances in metabolomics continue to expand its applications in plant biology, biotechnology, and natural product discovery unlocking many of nature's most beneficial colors, tastes, nutrients and medicines. Flavonoids and other specialized metabolites are essential for plant defense against oxidative stress and function as key phytonutrients for human health. Recent advancements in gene-editing and metabolic engineering have significantly improved the nutritional value and flavor of crop plants. Here we highlight how advanced metabolic analysis is driving improvements in crops uncovering genes that influence nutrient and flavor profile and plant derived compounds with medicinal potential.

Dissection of the Genetic Basis for Total γ-Oryzanol and Its Components in Whole Grain Brown Rice through Genome-Wide Association Study

Antioxidants detain the onset and progression of several noncommunicable diseases. γ-oryzanol (GOZ), a major antioxidant in rice grain, is a mixture of steryl esters of ferulic acid and caffeic acid. The present study was conducted with the objective of assessing the natural genetic variation for GOZ and its components in Indian rice cultivars and further identify the genomic regions associated with it. A panel of 174 Indian rice accessions depicted significant genetic variation for GOZ concentration, which ranged from 78.96 to 765.43 mg kg-1 of brown rice. 24-Methylenecycloartanyl ferulate was the major constituent (23.99-317.82 mg kg-1), followed by campesteryl ferulate (13.86-117.56 mg kg-1) and cycloartenyl ferulate (7.18-207.50 mg kg-1). Further, a genome-wide association study (GWAS) conducted using 32,712 single nucleotide polymorphism (SNP) markers with BLINK and FarmCPU models identified 19 significant marker-trait associations (MTAs) for GOZ and its components. These significant MTAs could explain the phenotypic variation ranging from 0.001 to 48.875% and have enormous potential in marker-assisted breeding programs aiming at the development of nutrient-dense rice varieties.

Beyond the Standard GWAS-A Guide for Plant Biologists

Classic genome-wide association studies (GWAS) look for associations between individual single-nucleotide polymorphisms (SNPs) and phenotypes of interest. With the rapid progress of high-throughput genotyping and phenotyping technologies, GWAS have become increasingly powerful for detecting genetic determinants and their molecular mechanisms underpinning natural phenotypic variation. However, GWAS frequently yield results with neither expected nor promising loci, nor any significant associations. This is often because associations between SNPs and a single phenotype are confounded, for example with the environment, other traits or complex genetic structures. Such confounding can mask true genotype-phenotype associations, or inflate spurious associations. To address these problems, numerous methods have been developed that go beyond the standard model. Such advanced GWAS models are flexible and can offer improved statistical power for understanding the genetics underlying complex traits. Despite this advantage, these models have not been widely adopted and implemented compared to the standard GWAS approach, partly because this literature is diverse and often technical. In this review, our aim is to provide an overview of the application and the benefits of various advanced GWAS models for handling complex traits and genetic structures, targeting plant biologists who wish to carry out GWAS more effectively.

Genome-wide analysis of genetic loci and candidate genes related to teat number traits in Dongliao black pigs

This study investigated the genetic basis of teat number variation in Dongliao black pigs. A total of 765 pigs were genotyped using the Porcine 50K SNP chip, and their teat numbers were recorded. Heritability estimates for total teat number (TTN) and teat pair number (TPN) were 0.091 and 0.097, respectively. Genome-wide association studies identified 74 significant SNPs for TTN and 105 for TPN. Nine candidate genes related to the teat number were identified: CSNK1G1, PLEKHM2, CABLES1, SLC25A21, RYR3, PIGH, GUCY1A1, RAPGEF2, and TRPC4AP. These findings provide insights into the genetic architecture of teat number variation in Dongliao black pigs.

Identification and validation of a major quantitative trait locus for precise control of heading date in wheat (Triticum aestivum L.)

BACKGROUND

Heading date (HD) is a crucial agronomic trait in wheat, significantly influencing both adaptation and yield. Despite having identical genotypes for the major heading genes Vrn-1 and Ppd-1, two Korean wheat cultivars, Jokyoung and Joongmo2008, exhibit substantial differences in heading date. However, the underlying genetic factors responsible for this variation remain unclear. To address this, we aimed to identify major quantitative trait loci (QTLs) associated with narrow-sense earliness under field conditions and develop a practical molecular marker for wheat breeding programs.

RESULTS

A recombinant inbred line (RIL) population was developed from a cross between the late-heading Jokyoung and the early-heading Joongmo2008 using speed breeding systems. The RILs were genotyped using a 35 K SNP chip, and a genetic map was constructed. A stable QTL for HD (qDH-3A) was identified on chromosome 3A, with an average logarithm of the odds (LOD) score of 59.4, explaining 72.6% of the phenotypic variance in HD across three years of field phenotyping. This indicates the robustness of qDH-3 A across multiple environments. Additionally, a kompetitive allele-specific PCR (KASP) marker linked to qDH-3A was developed and validated. The marker showed significant genotypic differences and effectiveness across diverse genetic backgrounds, including 616 worldwide wheat accessions.

CONCLUSIONS

The successful application of the KASP marker in both the RIL population and broader genetic resources highlights its potential use for marker-assisted selection (MAS) in wheat breeding programs. This study provides valuable insights into the genetic basis of HD in wheat and offers practical tools for developing cultivars better adapted to specific environmental conditions.

Molecular dissection of the genetic architecture of phenology underlying Lupinus hispanicus early flowering and adaptation to winter- or spring sowing

Spanish lupin, Lupinus hispanicus Boiss. et Reut. is an untapped grain legume species characterized by moderate frost resistance, tolerance to poor soil and waterlogging, high yield stability, and remarkable seed protein content. It has been recognized as a good candidate for domestication to broaden the palette of crop diversity. One of the key characteristics that need to be precisely addressed during domestication is the vernalization responsiveness of flowering, which is advantageous in autumn sowing due to improved frost tolerance, whilst undesired in spring sowing as it delays flowering. Ahead of L. hispanicus breeding, in the present work, we aimed to recognize existing phenotypic variability of flowering time and vernalization response and to evaluate the genetic architecture of early and late phenology by DArT-seq genotyping and genome-wide association study (GWAS) in world germplasm collection of the species. Controlled environment phenotyping revealed high variability of flowering time and vernalization responsiveness and significant correlations with population structure. DArT-seq genotyping yielded 23 728 highly polymorphic markers distributed extensively across all 26 chromosomes. GWAS identified a number of markers significantly associated with flowering time with or without pre-sowing vernalization, including those overlapping with the two major quantitative trait loci reported previously for white lupin species. Microsynteny-based analysis of the genetic content of L. hispanicus genome regions carrying significantly associated markers highlighted several candidate genes from photoperiodic and vernalization pathways. To summarize, the present study identified germplasm resources for autumn- and spring-sown cultivation of L. hispanicus and provided tools for marker-assisted selection towards required flowering phenology.

Plant genotype-specific modulation of Clonostachys rosea-mediated biocontrol of septoria tritici blotch disease in wheat

BACKGROUND

Beneficial microorganisms can act as biological control agents (BCAs) directly by targeting pathogens or indirectly by enhancing the plant's defense mechanisms against pathogens. However, efficiencies with which plants benefit from BCAs vary, potentially because of genetic variation in plants for plant-BCA compatibility. The aim of this study was to explore the genetic variation in winter wheat for modulation of Clonostachys rosea-mediated biocontrol of septoria tritici blotch disease caused by the fungal pathogen Zymoseptoria tritici.

RESULTS

In total, 202 winter wheat genotypes, including landraces and old cultivars grown from 1900 onwards in the Scandinavian countries, were tested under greenhouse-controlled conditions. Foliar spray applications of the pathogen and the fungal BCA in two treatments, i.e., Z. tritici (Zt) alone and Z. tritici along with C. rosea (ZtCr) were used to assess the disease progress over time. The absence and presence of C. rosea in Zt and ZtCr, respectively, allowed the dissection of variation for plant disease resistance and biocontrol efficacy. The study showed significant (P < 0.05) phenotypic variation among plant genotypes for disease progression in both Zt and ZtCr treatments. Moreover, the application of C. rosea resulted in a significant (P < 0.05) reduction in disease progression for seven genotypes and increased disease progression for eleven genotypes, indicating a plant genotype-dependent effect on the interaction between wheat, C. rosea and Z. tritici. For the phenotypic variation in disease progress and biocontrol efficacy, a genome-wide association study using a 20K single-nucleotide polymorphism (SNP) marker array was also performed. In total, five distinct SNP markers associated with disease resistance and four SNP markers associated with C. rosea biocontrol efficacy were identified.

CONCLUSIONS

This work serves as a foundation to further characterize the genetic basis of plant-BCA interactions when inoculated with Z. tritici, facilitating opportunities for simultaneous breeding for disease resistance and biocontrol efficacy.

Multi-Experiment and Multi-Locus Genome-Wide Association Mapping for Grain Arsenic in Rice Population

Rice is a globally important crop and is particularly efficient at assimilating arsenic (As). Identifying QTLs and genes associated with grain As is essential for breeding low-As rice cultivars. In this study, data on As accumulation in grains of Rice Diversity Panel 1 in five field environments at four diverse geographic sites were reanalyzed to compare genome-wide association (GWA) methods. Two single-locus (EMMAX for single trait and GEMMA for multi-experiments) and six multi-locus (FASTmrEMMA, ISIS EM-BLASSO, mrMLM, pKWmEB, pLARmEB, and FASTmrMLM) GWA methods were used. A total of 90 and 111 QTLs were detected using EMMAX and GEMMA, respectively. A total of 2, 11, 12, 19, 23, and 25 QTNs were identified by FASTmrEMMA, ISIS EM-BLASSO, mrMLM, pKWmEB, pLARmEB, and FASTmrMLM, respectively. Among these, 22 QTLs/QTNs were co-detected by single-locus and multi-locus GWAS methods. From these QTLs/QTNs, a total of 10 candidate genes were identified. Analysis of the haplotype variants of one candidate genes, OsABCC1, and one cluster of the plasma membrane intrinsic proteins genes revealed that a greater than 10% reduction in grain As could be achieved. The QTLs/QTNs and candidate genes identified give insight into the molecular mechanisms regulating As accumulation in rice and serve as breeding targets for developing low grain As rice cultivars.

SPDC-HG: An accelerator of genomic hybrid breeding in maize

Integrating multiple modern breeding techniques in maize has always been challenging. This study aimed to address this issue by applying a flexible sparse partial diallel cross design composed of 945 maize hybrids derived from 266 inbred lines across different heterotic groups. The research integrated genome-wide association studies, genomic selection and genomic evaluation of parental inbred lines to accelerate the breeding process for developing single-cross hybrids. Significant associations were identified for 7-25 stable single nucleotide polymorphisms (SNPs) associated with the general combining abilities (GCAs) of nine yield-related traits. Using the maizeGDB and NCBI databases, 264 candidate genes were screened and functionally annotated based on significant SNPs detected by at least three statistical methods. The marker set developed from these GCA SNPs significantly improved the prediction accuracy of hybrids across all traits. The GCA estimates of the inbred lines involved in the top 100 and bottom 100 hybrids consistently ranked at the top and bottom, thereby confirming the accuracy of the predictions. Furthermore, the top 100 crosses selected using BayesB, GBLUP and LASSO showed a 105.4-108.6% increase in average ear weight compared to the bottom 100 crosses in field validation, demonstrating strong selection gains. Notably, amongst the top 100 hybrids, A017/A037 and A037/A169, each containing six superior genotypes were registered as Suyu 161 and Tongyu 1701, respectively, by the National Crop Variety Approval Committee in China. These results highlight the effectiveness of genomic selection and provide valuable insights for advancing genomic hybrid breeding in maize.

Whole plant transpiration responses of common bean (Phaseolus vulgaris L.) to drying soil: Water channels and transcription factors

Common bean (Phaseolus vulgaris L.) is the main legume crop for direct human consumption worldwide. Among abiotic factors affecting common bean, drought is the most limiting. This study aimed at characterizing genetic variability and architecture of transpiration, stomatal regulation and whole plant water use within the Mesoamerican germplasm. A critical fraction of transpirable soil water (FTSWc) was estimated as the inflection point at which NTR starts decreasing linearly. Genome-wide association (GWA) analyses for mean NTR and FTSWc were performed. High variation on mean NTR and FTSWc was found among genotypes. Unreported genomic signals controlling the variation of these traits were identified on Pv01 and Pv07 some located in intergenic, intronic and exonic regions. A set of novel candidate genes and putative regulatory elements located in these QTL were identified. Some of the genes have been previously reported to be involved in abiotic tolerance in model species, including some of the five transcription factors (TF) identified. Four candidate genes, one with potential water transportation activity and three TFs were validated. The gene Phvul.001G108800, an aquaporin SIP2-1 related gene, showed water channel activity through oocyte water assays. Mutant Arabidopsis thaliana (Ath) lines for the homologous genes of common bean were evaluated in transpiration experiments. Two of the three evaluated TFs, UPBEAT1 and C2H2-type ZN finger protein, were involved in the control of transpiration responses to drying soil. Our results provide evidence of novel genes to accelerate the drought tolerance improvement in the crop and study the physiological basis of drought response in plants.

Transcripts and genomic intervals associated with variation in metabolite abundance in maize leaves under field conditions

Plants exhibit extensive environment-dependent intraspecific metabolic variation, which likely plays a role in determining variation in whole plant phenotypes. However, much of the work seeking to use natural variation to link genes and transcript's impacts on plant metabolism has employed data from controlled environments. Here, we generated and analyzed data on the variation in the abundance of 26 metabolites across 660 maize inbred lines under field conditions. We employ these data and previously published transcript and whole plant phenotype data reported for the same field experiment to identify both genomic intervals (through genome-wide association studies (GWAS)) and transcripts (using both transcriptome-wide association studies (TWAS) and an explainable artificial intelligence (AI) approach based on random forest (RF)) associated with variation in metabolite abundance. Both genome-wide association and random forest-based methods identified substantial numbers of significant associations including genes with plausible links to the metabolites they are associated with. In contrast, the transcriptome-wide association identified only six significant associations. In three cases, genetic markers associated with metabolic variation in our study colocalized with markers linked to variation in non-metabolic traits scored in the same experiment. We speculate that the poor performance of transcriptome-wide association studies in identifying transcript-metabolite associations may reflect a high prevalence of non-linear interactions between transcripts and metabolites and/or a bias towards rare transcripts playing a large role in determining intraspecific metabolic variation.

Identification of single nucleotide polymorphisms and candidate genes associated with fiber content in sweetpotato (Ipomoea batatas (L.) Lam.) through a genome-wide association study

BACKGROUND

Sweetpotato (Ipomoea batatas (L.) Lam.) is an essential root crop with several nutritional benefits, including high dietary fiber content. While fiber contributes positively to human health by reducing the risk of metabolic and gastrointestinal diseases, excessive fiber accumulation can negatively impact texture and consumer preference. Despite its importance, the genetic mechanisms underlying fiber content in sweetpotato remain largely unexplored. Therefore, this study aimed to identify the genomic regions and candidate genes associated with fiber content through a genome-wide association study (GWAS).

RESULTS

Significant phenotypic variation in fiber content were observed among 140 sweetpotato genotypes. The GWAS analysis identified seven significant single nucleotide polymorphisms (SNPs), with Iba_chr07a_20294133 and Iba_chr12a_38616338 consistently detected across the FarmCPU and BLINK models. Notably, three SNPs (Iba_chr01a_17621178, Iba_chr10a_773882, and Iba_chr12a_38616338) showed significant phenotypic differentiation between homozygous alleles, making them promising candidates for marker development. Candidate gene analysis identified four genes with significantly upregulated expression in high-fiber genotypes: IbANT1 (adenine nucleotide transporter BT1), IbCYP86B1 (cytochrome P450 86B1), IbSCR3 (scarecrow-like protein 3), and IbFER (FERONIA receptor-like kinase). These genes are involved in suberin biosynthesis, cell wall remodeling, and metabolic regulation, suggesting their crucial roles in fiber accumulation.

CONCLUSION

This study provides novel insights into the genetic regulation of fiber content in sweetpotato. The identification of significant SNPs and candidate genes offers valuable resources for breeding programs targeting fiber optimization. Further validation is essential for the effective application of these SNPs and genes into marker-assisted selection strategies.

Recombination and transposition drive genomic structural variation potentially impacting life history traits in a host-generalist fungal plant pathogen

BACKGROUND

An understanding of plant pathogen evolution is important for sustainable management of crop diseases. Plant pathogen populations must maintain adequate heritable phenotypic variability to survive. Polymorphisms ≥ 50 bp, known as structural variants (SVs), could contribute strongly to this variability by disrupting gene activities. SV acquisition is largely driven by mobile genetic elements called transposons, though a less appreciated source of SVs is erroneous meiotic double-strand break repair. The relative impacts of transposons and recombination on SV diversity and the overall contribution of SVs to phenotypic variability is elusive, especially in host generalists.

RESULTS

We use 25 high-quality genomes to create a graphical pan-genome of the globally distributed host-generalist crop pathogen Sclerotinia sclerotiorum. Outcrossing and recombination rates in this self-fertile species have been debated. Using bisulfite sequencing and short-read data from 190 strains, we show that S. sclerotiorum has many hallmarks of eukaryotic meiosis, including recombination hot and cold spots, centromeric and genic recombination suppression, and rapid linkage disequilibrium decay. Using a new statistic that captures average pairwise structural variation, we show that recombination and transposons make distinct contributions to SV diversity. Furthermore, despite only 5% of genes being dispensable, SVs often had a stronger impact than other variants across 14 life history traits measured in 103 distinct strains.

CONCLUSIONS

Transposons and recombination make distinct contributions to SV diversity in S. sclerotiorum. Despite limited gene content diversity, SVs may strongly impact phenotypic variability. This sheds light on the genomic forces shaping adaptive flexibility in host generalists.

GWAS Procedures for Gene Mapping in Diverse Populations With Complex Structures

With reduced genotyping costs, genome-wide association studies (GWAS) face more challenges in diverse populations with complex structures to map genes of interest. The complex structure demands sophisticated statistical models, and increased marker density and population size require efficient computing tools. Many statistical models and computing tools have been developed with varied properties in statistical power, computing efficiency, and user-friendly accessibility. Some statistical models were developed with dedicated computing tools, such as efficient mixed model analysis (EMMA), multiple loci mixed model (MLMM), fixed and random model circulating probability unification (FarmCPU), and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK). However, there are computing tools (e.g., GAPIT) that implement multiple statistical models, retain a constant user interface, and maintain enhancement on input data and result interpretation. In this study, we developed a protocol utilizing a minimal set of software tools (BEAGLE, BLINK, and GAPIT) to perform a variety of analyses including file format conversion, missing genotype imputation, GWAS, and interpretation of input data and outcome results. We demonstrated the protocol by reanalyzing data from the Rice 3000 Genomes Project and highlighting advancements in GWAS model development.

Genetic dissection of total protein content, phenolic content and seed quality traits in pigeonpea (Cajanus cajan) using 62K pigeonpea genic SNP chip

Pigeonpea (Cajanus cajan L. Millsp.), South Asia's second most significant pulse crop and source of dietary protein, is facing production issues due to a lack of improved varieties with high nutritional and seed quality compositions, as well as environmental stress. Identification of genes/alleles governing the nutritional and seed quality traits is key for marker-assisted breeding for quality traits in pigeonpea. Hence, the present study was undertaken to unravel the complex genetic architecture of nutritional and seed quality traits in pigeonpea. We conducted a genome-wide association study (GWAS) to identify SNP markers associated with nutritional traits, namely total protein content (TPC), phenolics content, and seed quality traits, such as seed coat colour, length, width, size, shape, and weight using a 62K SNP genotyping chip array. We estimated TPC of a panel of 287 diverse pigeonpea genotypes using Kjeldahl method to identify 5 significant SNPs associated with TPC on chromosomes 6 and 11 (AX-165344137), encoding a putative disease resistance protein, and Chromosome 11 (AX-165358192), encoding a CBL-interacting serine/threonine-protein kinase. We identified five markers associated with the seed coat colour on Chromosomes 5 (AX-165369586), 2 (AX-165370277), and 8 (AX-165400346). Additionally, we identified 4, 6, 2, 3, 6, and 5 SNPs associated with phenolics content, seed length, seed shape, seed width, seed size, and seed weight, respectively. The study's findings are projected to bring considerable benefits to pigeonpea producers in marker-assisted breeding for the production of varieties with improved protein content and seed quality traits corresponded to consumer preferences, as well as promote improved health and nutrition. Therefore, GWAS provides strong support for exploring the genetic mechanisms underlying important pigeonpea qualities and improving breeding strategies.

Genome-wide association studies dissect the genetic architecture of seed and yield component traits in cowpea (Vigna unguiculata L. Walp)

The identification of loci related to seed and yield component traits in cowpea constitutes a key step for improvement through marker-assisted selection (MAS). Furthermore, seed morphology has an impact on industrial processing and influences consumer and farmer preferences. In this study, we performed genome-wide association studies (GWAS) on a mini-core collection of cowpea to dissect the genetic architecture and detect genomic regions associated with seed morphological traits and yield components. Phenotypic data were measured both manually and by high-throughput image-based approaches to test associations with 41,533 single nucleotide polymorphism markers using the FarmCPU model. From genome-associated regions, we also investigated putative candidate genes involved in the variation of the phenotypic traits. We detected 42 marker-trait associations for pod length and 100-seed weight, length, width, perimeter, and area of the seed. Candidate genes encoding leucine-rich repeat-containing (LRR) and F-box proteins, known to be associated with seed size, were identified; in addition, we identified candidate genes encoding PPR (pentatricopeptide repeat) proteins, recognized to have an important role in seed development in several crops. Our findings provide insights into natural variation in cowpea for yield-related traits and valuable information for MAS breeding strategies in this and other closely related crops.

Soybean genome‑wide association study of seed weight, protein, and oil content in the southeastern USA

Soybean is a globally significant legume crop, providing essential protein and oil for human and livestock nutrition. Improving oil and protein content simultaneously without compromising yield has been challenging due to the quantitative nature of these traits and their interrelationships. This study aims to deepen our understanding of the molecular basis soybean of seed weight, protein, and oil content to facilitate marker-assisted breeding to enhance these traits. In this research, a Genome-Wide Association Study (GWAS) was conducted utilizing 285 diverse soybean accessions from maturity group V, employing genotyping through the SoySNP50K platform. These accessions were tested in three environmental conditions of the southeast US for three traits: 100-seed weight, protein, and oil content. The study identified 18, 23, and 26 SNPs significantly associated with 100-seed weight, seed oil, and protein content. Colocalized protein and oil content regions were discovered on chromosomes 15, 16, and 20. Chromosomes 15 and 20 are well documented to have pleiotropic but opposite effects on oil and protein content, but both regions contain genes that affect individual traits, such as FAD2-1 and nodulin MtN21. A 1.92 Mb region on chromosome 11 exhibits a target region to improve oil and seed weight without affecting protein content. This study highlights key genomic regions and candidate genes influencing seed weight, protein, and oil content, with some regions affecting multiple traits. Hence, these findings provide a valuable foundation for marker-assisted selection to optimize seed weight and simultaneously enhance oil and protein content in soybean breeding programs.

Unveiling shared genetic regulators of plant architectural and biomass yield traits in the Sorghum Association Panel

Sorghum is emerging as an ideal genetic model for designing high-biomass bioenergy crops. Biomass yield, a complex trait influenced by various plant architectural characteristics, is typically regulated by numerous genes. This study aimed to dissect the genetic regulators underlying 14 plant architectural traits and 10 biomass yield traits in the Sorghum Association Panel across two growing seasons. We identified 321 associated loci through genome-wide association studies (GWAS), involving 234 264 single nucleotide polymorphisms (SNPs). These loci include genes with known associations to biomass traits, such as maturity, dwarfing (Dw), and leafbladeless1, as well as several uncharacterized loci not previously linked to these traits. We also identified 22 pleiotropic loci associated with variation in multiple phenotypes. Three of these loci, located on chromosomes 3 (S03_15463061), 6 (S06_42790178; Dw2), and 9 (S09_57005346; Dw1), exerted significant and consistent effects on multiple traits across both growing seasons. Additionally, we identified three genomic hotspots on chromosomes 6, 7, and 9, each containing multiple SNPs associated with variation in plant architecture and biomass yield traits. Chromosome-wise correlation analyses revealed multiple blocks of positively associated SNPs located near or within the same genomic regions. Finally, genome-wide correlation-based network analysis showed that loci associated with flowering, plant height, leaf traits, plant density, and tiller number per plant were highly interconnected with other genetic loci influencing plant architectural and biomass yield traits. The pyramiding of favorable alleles related to these traits holds promise for enhancing the future development of bioenergy sorghum crops.

A major QTL region associated with powdery mildew resistance in leaves and fruits of the reconstructed garden strawberry

KEY MESSAGE

Multiple QTLs for powdery mildew resistance were identified in a pre-breeding population derived from the octoploid progenitor species of garden strawberry, including a stable major novel factor on chromosome 3B. Powdery mildew (PM), caused by the biotrophic fungal pathogen Podosphaera aphanis, poses an increasing threat to garden strawberry (Fragaria × ananassa) production worldwide. While a few commercial cultivars exhibit partial resistance, fungicide application remains essential for managing PM outbreaks. However, breeding offers a more sustainable approach for controlling PM. A better understanding of the genetics of resistance is required for informed breeding strategies, e.g. through identifying novel resistance factors derived from the progenitor species of garden strawberry, F. chiloensis and F. virginiana. We conducted genome-wide association (GWA) and multivariate analyses in a reconstructed (ReC) strawberry population to investigate PM resistance under natural infection. Leveraging multi-year field trial data and 20,779 single-nucleotide polymorphism markers, we identified a novel major quantitative trait locus (QTL) on chromosome 3B, designated as q.LPM.Rec-3B.2, that was consistently associated with high PM resistance in both leaves and fruits. Greenhouse validation with a subset of the ReC population confirmed that this QTL region was stable across field and greenhouse environments. Promising candidate genes for resistance, including two for MLO and one for EXO70, were identified within this major QTL. In addition, multi-locus GWA models and non-additive GWA revealed additional resistance QTLs on multiple chromosomes. Despite previous challenges in breeding for robust PM resistance due to its quantitative nature and complex genetic control, our results provide valuable insights into resistance-contributing QTL regions already existing in strawberry, novel wild-derived resistance QTLs not previously known, candidate genes, and pre-breeding germplasm carrying resistance traits as resources for future genome-informed breeding efforts.

Genomic Regions and Molecular Markers Associated with Deeper Rooting to Improve Grain Yield in Aerobic Rice (Oryza sativa L.) Production Systems

A greater proportion of deep roots could ensure water uptake at depth and is considered a key trait for aerobic adaptation. However, the study of genomic regions and molecular markers related to deep rooting is limited especially for aerobic rice production. This study utilised 705 genotypes composed of recombinant inbred lines and predominantly diverse japonica sets to identify and validate genomic regions associated with the proportion of deep roots below 20 cm (DR20). Six quantitative trait loci (QTL) for DR20 were identified under well-watered aerobic conditions, explaining 5.3-23.7% of the phenotypic variance and introgression of the favourable alleles resulted in 10-21.6% deeper roots. Simultaneous development of high throughput molecular markers and QTL validation demonstrated the effect of four (qADR1, qADR9, qADR10, and qADR11) out of six QTL increasing DR20 up to 29.4% across genetic backgrounds. The four QTL also conferred a mean grain yield advantage of 1.46 t/ha. This study reports for the first time validated genomic regions and high throughput molecular markers associated with deeper rooting and improved grain yield in rice under aerobic conditions. These tools may accelerate the development of rice adapted to aerobic production systems and ultimately enhance sustainable rice production in areas with limited water availability.

Evaluation of Durum and Hard Red Spring Wheat Panels for Sensitivity to Necrotrophic Effectors Produced by Parastagonospora nodorum

Septoria nodorum blotch (SNB) is an important disease of both durum and hard red spring wheat (HRSW) worldwide. The disease is caused by the necrotrophic fungal pathogen Parastagonospora nodorum when compatible gene-for-gene interactions occur between pathogen-produced necrotrophic effectors (NEs) and corresponding host sensitivity genes. To date, nine sensitivity gene-NE interactions have been identified, but there is little information available regarding their overall frequency in durum and HRSW. Here, we infiltrated a global HRSW panel (HRSWP) and the Global Durum Panel (GDP) with P. nodorum NEs SnToxA, SnTox1, SnTox267, SnTox3, and SnTox5. Frequencies of sensitivity to SnTox1 and SnTox5 were higher in durum compared with HRSW and vice versa for SnTox267 and SnTox3. Strong associations for the known sensitivity loci Tsn1, Snn1, Snn2, Snn3, Snn5, and Snn7 along with potentially novel sensitivity loci on chromosome arms 7DS and 3BL, associated with SnToxA and SnTox267, respectively, were identified in the HRSWP. In the GDP, Snn1, Snn3, and Snn5 were identified along with novel loci associated with sensitivity to SnTox267 on chromosome arms 2AS, 2AL, and 6AS and with SnTox5 sensitivity on 2BS and 7BL. These results reveal additional NE sensitivity loci beyond those previously described, demonstrating a higher level of genetic complexity of the wheat-P. nodorum system than was previously thought. Knowledge regarding the prevalence and genomic locations of SNB susceptibility genes in HRSW and durum will prove useful for developing efficient breeding strategies and improving varieties for SNB resistance.

A Next-Generation Combinatorial Genomic Strategy Scans Genomic Loci Governing Heat Stress Tolerance in Chickpea

In the wake of rising earth temperature, chickpea crop production is haunted by the productivity crisis. Chickpea, a cool season legume manifests tolerance in several agro-physiological level, which is complex quantitative in nature, and regulated by multiple genes and genetic networks. Understanding the molecular genetic basis of this tolerance and identifying key regulators can leverage chickpea breeding against heat stress. This study employed a genomics-assisted breeding strategy utilizing multi-locus GWAS to identify 10 key genomic regions linked to traits contributing to heat stress tolerance in chickpea. These loci subsequently delineated few key candidates and hub regulatory genes, such as RAD23b, CIPK25, AAE19, CK1 and WRKY40, through integrated genomics, transcriptomics and interactive analyses. The differential transcript accumulation of these identified candidates in contrasting chickpea accessions suggests their potential role in heat stress tolerance. Differential ROS accumulation along with their scavengers' transcript abundance aligning with the expression of identified candidates in the contrasting chickpea accessions persuade their regulatory significance. Additionally, their functional significance is ascertained by heterologous expression and subsequent heat stress screening. The high confidence genomic loci and the superior genes and natural alleles delineated here has great potential for swift genomic interventions to enhance heat resilience and yield stability in chickpea.

Transcriptional Reprogramming and Allelic Variation in Pleiotropic QTL Regulates Days to Flowering and Growth Habit in Pigeonpea

The present study investigated the linkage between days to flowering (DTF) and growth habit (GH) in pigeonpea using QTL mapping, QTL-seq, and GWAS approaches. The linkage map developed here is the largest to date, spanning 1825.56 cM with 7987 SNP markers. In total, eight and four QTLs were mapped for DTF and GH, respectively, harbouring 78 pigeonpea orthologs of Arabidopsis flowering time genes. Corroboratively, QTL-seq analysis identified a single linked QTL for both traits on chromosome 3, possessing 15 genes bearing genic variants. Together, these 91 genes were clustered primarily into autonomous, photoperiod, and epigenetic pathways. Further, we identified 39 associations for DTF and 111 associations for GH through GWAS in the QTL regions. Of these, nine associations were consistent and constituted nine haplotypes (five late, two early, one each for super-early and medium duration). The involvement of multiple genes explained the range of allelic effects and the presence of multiple LD blocks. Further, the linked QTL on chromosome 3 was fine-mapped to the 0.24-Mb region with an LOD score of 8.56, explaining 36.47% of the phenotypic variance. We identified a 10-bp deletion in the first exon of TFL1 gene of the ICPL 20338 variety, which may affect its interaction with the Apetala1 and Leafy genes, resulting in determinate GH and early flowering. Further, the genic marker developed for the deletion in the TFL1 gene could be utilized as a foreground marker in marker-assisted breeding programmes to develop early-flowering pigeonpea varieties.

Identification of gray leaf spot-resistant donor lines in tropical maize germplasm and their agronomic performance under artificial inoculation

Gray leaf spot (GLS) disease is caused by two fungal pathogens, Cercospora zeae-maydis and Cercospora zeina. The current study evaluated 427 elite tropical/subtropical lines for their responses to GLS under artificial inoculation in Kakamega in western Kenya for 4 years. Furthermore, a subset of 140 lines was used for a high-resolution genome-wide association study (GWAS) for GLS resistance. Among the 427 lines evaluated, 14 were identified as resistant on the basis of a <4 (on a scale of 1-9) GLS disease severity score. Among these 14 lines, three lines, namely CML540, CML559, and CML566, are also known for resistance to MSV, tolerance to drought, and resistance to MLN, respectively. The phenotypic evaluation revealed significant (P < 0.01) genotypic and genotype x environment interaction variances and moderate to high heritability for GLS disease severity, area under disease progress curve (AUDPC), and other agronomic traits. GLS disease severity traits were negatively and significantly correlated (P < 0.01) with anthesis date, silking date, plant height, and ear height. A subset of 140 lines was genotyped with 33,740 DART-GBS SNP markers. Population structure and principal component analysis grouped the lines into two major clusters with moderate structure in the population. GWAS revealed 13 and 11 SNPs significantly associated with GLS disease severity and AUDPC values. Six among the 13 SNPs detected for GLS resistance are overlapped with earlier studies, which can be used for fine mapping and improvement of GLS resistance through marker-assisted selection. However, SNPs on chromosomes 9 and 10 were unique to the present study. Genomic prediction on GLS traits revealed moderate to high prediction correlations, suggesting its usefulness in the selection of desirable candidates with favorable alleles for GLS resistance. Overall, 14 GLS resistance lines identified in this study can be used as donor lines in both genetic studies and resistance breeding programs.

Genome-wide association and selection studies for pod dehiscence resistance in the USDA soybean germplasm collection

As a domestication trait, pod dehiscence has a pleiotropic effect on agronomic traits and significantly contributes to yield loss in soybean. Population studies are still required to comprehend the genetic basis of dehiscence and to develop pod dehiscence-resistant cultivars with the optimal haplotype, thereby improving soybean production. We collected data for one wild (Glycine soja) (G. soja) and four cultivated (Glycine max) (G. max) populations from the USDA database. The G. max populations were evaluated in multi-environment conditions and used for genome-wide association study (GWAS) and selection. GWAS captured 86 quantitative trait loci (QTLs). Seventy-four new QTLs were colocalized in two different G. max populations, and 12 QTLs were closely mapped with previously reported QTLs. Eight out of 86 QTLs were associated with the domestication of pod dehiscence. We implemented marker-assisted selection (MAS) and genomic selection (GS) approaches to select pod dehiscence-resistant accessions with the best haplotype and lowest genomic breeding value (GBV), respectively. While our findings could be utilized for biology, genetics, and plant breeding, selecting pod dehiscence-resistant cultivars with the optimal haplotype will need further studies to confirm additional QTLs and assess advanced GS models.

GWAS identifies novel loci linked to seedling growth traits in highly diverse barley population under drought stress

Climate changes refer to long-term shifts in temperature and weather patterns that may cause drought, one of the major stresses hindering seed germination, plant growth, and crop productivity. Barley (Hordeum vulgare L) is considered one of the most drought-stress-tolerant cereals and may be used for elucidating genes for drought tolerance at seed germination and seedling stages that would pave the way toward improving the performance of all cereals. The current study was performed at IPK-Gatersleben (Germany) in 2023. Our aim was to explore the genetic basis of germination and seedling traits under drought stress (20% PEG6000 treatment) in a 198 global spring barley collection genotyped with 38,632 SNPs via Genotyping by Sequencing (GBS). The drought treatment significantly reduced the seed germination parameters and seedling traits in the genotypes of a global barley collection. Drought tolerance indices (DTI) for the measured germination and seedling traits indicate delayed and lower germination speed under drought stress than the control. The shoot fresh weight was the most affected trait, with a DTI of 37.4, followed by the seedling fresh weight SDLFW (DTI = 46.3) and root fresh weight (DTI = 47). In contrast, the root length DTI was the least affected trait by drought (78.2), followed by RDW DTI (72.8). GWAS was conducted using single-locus (CMLM) and multi-locus models (MLMM, Farm-CPU, BLINK), with significant marker-trait associations determined at -log10 (1.29E-06) ≥ 5.88. In our present study, we identified 79 highly significant SNPs distributed across the seven barley chromosomes related to the germination and seedling growth parameters under both control and drought conditions. Gene annotation of these highly significant SNPs revealed that 35 SNPs were in the exonic regions of genes that play roles in important plant biological and physiological processes. Further analysis exhibited 35 high-confidence candidate genes influencing barley germination and seedling growth under control and drought conditions. These genes represent promising targets for breeding and genetic enhancement efforts to improve drought tolerance in barley, potentially extending these benefits to other cereal crops.

Genome-wide association study reveals genetic loci for seed density per silique in rapeseed (Brassica napus L.)

KEY MESSAGE

Two stable QTLs controlling seed density per silique were detected on chromosomes A09 and C05 in rapeseed via GWAS, and ARF18 was the only causal gene of QTL qSDPS-A09. Seed density per silique (SDPS) is a key agronomic trait that directly or indirectly affects seed yield in rapeseed (Brassica napus L.). Exploring the genetic control of SDPS is beneficial for increasing rapeseed production. In this study, we evaluated the SDPS phenotypes of 413 rapeseed cultivars (lines) across five natural environments and genotyped them by resequencing. A GWAS analysis was performed using 5,277,554 high-quality variants with the MLM_PCA + K and FarmCPU models. A total of 51 loci were identified to be significantly (p < - log10(1.88 × 10-6)) associated with SDPS, of which 5 were detected in all environments (except for SNP-2095656) by both GWAS models. Among the five loci, three were located on chromosome A09, whereas the other two loci were located on chromosome C05. The three loci on chromosome A09 and the two loci on chromosome C05 were physically close to each other. Therefore, only the two common candidate QTLs were integrated and named QTL qSDPS-A09 (320 kb) and qSDPS-C05 (331.48 kb), respectively. Sixty-seven and forty-eight candidate genes were initially identified on A09 and C05 and then narrowed down to 17 and 13 candidate genes, respectively, via LD block analyses. Gene-based association studies, haplotype analyses and expression analyses confirmed that three homologs of Arabidopsis auxin-response factor 18 (BnaA09G0559300ZS) was the most likely candidate genes underlying the QTL qSDPS-A09. ARF18Hap4 was identified as a favorable haplotype for high SDPS. These findings will aid in elucidating the genetic and molecular mechanisms of SDPS and promoting genetic modifications in rapeseed breeding.

Genetic Insights into Breast Cancer in Northeastern Mexico: Unveiling Gene-Environment Interactions and Their Links to Obesity and Metabolic Diseases

Background: Breast cancer (BC), one of the most common cancers, has increased in Mexico during the past decade, along with other chronic and metabolic diseases. Methods: Herein, we analyzed 121 SNPs (85 SNPs related to BC and/or glucose-associated metabolic pathways and 36 SNP classified as ancestry markers) in 92 confirmed BC cases and 126 unaffected BC women from Northeastern Mexico. The relationship of these 121 SNPs with BC, considering BMI, menopause status, and age as cofactors, was explored using a gene-environment (G × E) interaction multi-locus model. Results: Twelve gene variants were significantly associated with BC: three located in exome (rs3856806 PPARG, rs12792229 MMP8, and rs5218 KCNJ11-ABCC8), and nine in non-coding regions, which are involved in accelerated decay of the mRNA transcripts, regulatory regions, and flanking regions (rs3917542 PON1; rs3750804 and rs3750805 TCF7L2; rs1121980 and rs3751812 FTO; rs12946618 RPTOR; rs2833483 SCAF4; rs11652805 AMZ2P1-GNA13; and rs1800955 SCT-DEAF1-DRD4). Conclusions: This study identified an association between BC and menopause, age (above 45), obesity, and overweight status with gene variants implicated in diabetes mellitus, obesity, insulin resistance, inflammation, and remodeling of the extracellular matrix.

Genome-specific association study (GSAS) for exploration of variability in hemp (Cannabis sativa)

Hemp (Cannabis sativa L.) is a versatile crop with substantial potential for creating productive, sustainable, and resilient agricultural systems. However, in contrast to other crops such as cereals, hemp is highly heterozygous, resulting in both challenges and opportunities for agriculture, breeding, and research. Here, we utilise the heterozygosity of hemp to explore the genetic basis of phenotypic variability in a population generated from a single self-pollinated hemp plant. The S1 population shows extensive variability in plant growth, development, and reproductive patterns. Using reduced representation sequencing, selection of alleles heterozygous in the parent plant, and a model originally developed for genome-wide association studies (GWAS), we were able to identify statistically significant single nucleotide variants (SNVs) and haplotypes associated with phenotypic traits of interest, such as flowering time or biomass yield. This new approach, which we term genome-specific association study (GSAS), enables the mapping of traits in a single generation without the need for a large number of diverse cultivars or samples. GSAS might be applicable to other highly heterozygous vegetable and fruit crops, informing the breeding of new cultivars with enhanced uniformity and improved performance in traits relevant to various applications.

Genome-wide association mapping for the identification of stripe rust resistance loci in US hard winter wheat

KEY MESSAGE

The GWAS and testing with Yr gene linked markers identified 109 loci including 40 novel loci for all-stage and adult plant stage resistance to stripe rust in 459 US contemporary hard winter wheat genotypes. Stripe rust is a destructive wheat disease, caused by Puccinia striiformis f. sp. tritici (Pst). To identify sources of stripe rust resistance in US contemporary hard winter wheat, a panel of 459 Great Plains wheat genotypes was evaluated at the seedling stage against five US Pst races and at the adult plant stage in field environments in Oklahoma, Kansas, and Washington. The results showed that 7-14% of the genotypes were resistant to Pst races at the seedling stage, whereas 32-78% of genotypes were resistant at the adult plant stage across field environments, indicating the presence of adult plant resistance. Sixteen genotypes displayed a broad spectrum of resistance to all five Pst races and across all field environments. The panel was further genotyped using 9858 single-nucleotide polymorphisms (SNPs) generated from multiplex restriction amplicon sequencing (MRASeq) and the functional DNA markers linked to the known stripe rust resistance (Yr) genes Yr5, Yr15, Yr17, Yr18, Yr29, Yr36, Yr40, Yr46, and QYr.tamu-2B. A genome-wide association study (GWAS) was performed using genotypic and phenotypic data, which identified 110 SNPs and the functional markers linked to Yr15 and Yr17 to be significantly associated with stripe rust response. In addition, Yr5, Yr15, Yr17, Yr18, Yr29, and QYr.tamu-2B were detected by their functional DNA markers in the panel. This study identified 40 novel loci associated with stripe rust resistance in genomic regions not previously characterized by known Yr genes. These findings offer significant opportunities to diversify and enhance stripe rust resistance in hard winter wheat.

Metabolic marker-assisted genomic prediction improves hybrid breeding

Hybrid breeding is widely acknowledged as the most effective method for increasing crop yield, particularly in maize and rice. However, a major challenge in hybrid breeding is the selection of desirable combinations from the vast pool of potential crosses. Genomic selection (GS) has emerged as a powerful tool to tackle this challenge, but its success in practical breeding depends on prediction accuracy. Several strategies have been explored to enhance prediction accuracy for complex traits, such as the incorporation of functional markers and multi-omics data. Metabolome-wide association studies (MWAS) help to identify metabolites that are closely linked to phenotypes, known as metabolic markers. However, the use of preselected metabolic markers from parental lines to predict hybrid performance has not yet been explored. In this study, we developed a novel approach called metabolic marker-assisted genomic prediction (MM_GP), which incorporates significant metabolites identified from MWAS into GS models to improve the accuracy of genomic hybrid prediction. In maize and rice hybrid populations, MM_GP outperformed genomic prediction (GP) for all traits, regardless of the method used (genomic best linear unbiased prediction or eXtreme gradient boosting). On average, MM_GP demonstrated 4.6% and 13.6% higher predictive abilities than GP for maize and rice, respectively. MM_GP could also match or even surpass the predictive ability of M_GP (integrated genomic-metabolomic prediction) for most traits. In maize, the integration of only six metabolic markers significantly associated with multiple traits resulted in 5.0% and 3.1% higher average predictive ability compared with GP and M_GP, respectively. With advances in high-throughput metabolomics technologies and prediction models, this approach holds great promise for revolutionizing genomic hybrid breeding by enhancing its accuracy and efficiency.

Association study of crude seed protein and fat concentration in a USDA pea diversity panel

Pea (Pisum sativum L.) is a key rotational crop and is increasingly important in the food processing sector for its protein. This study focused on identifying diverse high seed protein concentration (SPC) lines in pea plant genetic resources. Objectives included identifying high-protein pea lines, exploring genetic architecture across environments, pinpointing genes and metabolic pathways associated with high protein, and documenting information for single nucleotide polymorphism (SNP)-based marker-assisted selection. From 2019 to 2021, a 487-accession pea diversity panel, More protein, More pea, More profit, was evaluated in a randomized complete block design. DNA was extracted for genomic analysis via genotype-by-sequencing. Phenotypic analysis included protein and fat measurements in seeds and flower color. Genome-wide association study (GWAS) used multiple models, and the Pathways Association Study Tool was used for metabolic pathway analysis. Significant associations were found between SNPs and pea seed protein and fat concentration. Gene Psat7g216440 on chromosome 7, which targets proteins to cellular destinations, including seed storage proteins, was identified as associated with SPC. Genes Psat4g009200, Psat1g199800, Psat1g199960, and Psat1g033960, all involved in lipid metabolism, were associated with fat concentration. GWAS also identified genes annotated for storage proteins associated with fat concentration, indicating a complex relationship between fat and protein. Metabolic pathway analysis identified 20 pathways related to fat and seven to protein concentration, involving fatty acids, amino acid and protein metabolism, and the tricarboxylic acid cycle. These findings will assist in breeding of high-protein, diverse pea cultivars, and SNPs that can be converted to breeder-friendly molecular marker assays are identified for genes associated with high protein.

Development of a 101.6K liquid-phased probe for GWAS and genomic selection in pine wilt disease-resistance breeding in Masson pine

Masson pine (Pinus massoniana Lamb.), indigenous to southern China, faces serious threats from pine wilt disease (PWD). Several natural genotypes have survived PWD outbreaks. Conducting genetic breeding with these resistant genotypes holds promise for enhancing resistance to PWD in Masson pine at its source. We conducted a genome-wide association study (GWAS) and genomic selection (GS) on 1013 Masson pine seedlings from 72 half-sib families to advance disease-resistance breeding. A set of efficient 101.6K liquid-phased probes was developed for single-nucleotide polymorphisms (SNPs) genotyping through target sequencing. PWD inoculation experiments were then performed to obtain phenotypic data for these populations. Our analysis reveals that the targeted sequencing data successfully divided the experimental population into three subpopulations consistent with the provenance, verifying the reliability of the liquid-phased probe. A total of 548 SNPs were considerably associated with disease-resistance traits using four GWAS algorithms. Among them, 283 were located on or linked to 169 genes, including common plant disease resistance-related protein families such as NBS-LRR and AP2/ERF. The DNNGP (deep neural network-based method for genomic prediction) model demonstrated superior performance in GS, achieving a maximum predictive accuracy of 0.71. The accuracy of disease resistance predictions reached 90% for the top 20% of the testing population ordered by resistance genomic estimated breeding value. This study establishes a foundational framework for advancing research on disease-resistant genes in P. massoniana and offers preliminary evidence supporting the feasibility of utilizing GS for the early identification of disease-resistant individuals.

Variation for QTL alleles associated with total dissolved solids among crop types in a GWAS of a Beta vulgaris diversity panel

Sweetness is a main component of the table beet (Beta vulgaris L.) flavor profile and a key determinant of its market success for fresh consumption. Total dissolved solids (TDS) is a proxy for sugar content in produce and are easily measured through a refractometer, making TDS valuable in breeding programs focused on increasing sweetness. A diversity panel of 238 accessions from the Beta vulgaris crop complex and wild relatives was assembled and genotyped using genotyping-by-sequencing, yielding 10,237 single nucleotide polymorphisms (SNPs) from 226 full panel accessions and 9,847 SNPs from table beet only accessions after filtering. The panel was phenotyped in field trials over 2 years and mean values were adjusted using best linear unbiased estimates. TDS levels varied among crop types and a broad-sense heritability of 0.90 indicated that phenotypic differences can be attributed in large part to genetic variation. A genome-wide association study (GWAS) uncovered four quantitative trait loci (QTLs) identified across multiple models to significantly associate with TDS. A QTL on chromosome 2 was consistently identified among GWAS models, explaining 12.1%-62.6% of the phenotypic variation in the full panel. Bevul.2G176300, a gene directly involved in the sucrose biosynthesis pathway, was located downstream the significant marker. A second QTL identified on chromosome 7 revealed QTL alleles that may differentiate between table beet accessions, explaining nearly half the phenotypic variation, and is the first QTL reported in association with TDS unique to table beet. The QTL described can be used to efficiently breed for higher TDS levels in Beta vulgaris, avoiding intercrop type crosses and linkage drag.

Genome-wide association studies on resistance to powdery mildew in cultivated emmer wheat

Powdery mildew, caused by the fungal pathogen Blumeria graminis (DC.) E. O. Speer f. sp. tritici Em. Marchal (Bgt), is a constant threat to global wheat (Triticum aestivum L.) production. Although ∼100 powdery mildew (Pm) resistance genes and alleles have been identified in wheat and its relatives, more is needed to minimize Bgt's fast evolving virulence. In tetraploid wheat (Triticum turgidum L.), wild emmer wheat [T. turgidum ssp. dicoccoides (Körn. ex Asch. & Graebn.) Thell.] accessions from Israel have contributed many Pm resistance genes. However, the diverse genetic reservoirs of cultivated emmer wheat [T. turgidum ssp. dicoccum (Schrank ex Schübl.) Thell.] have not been fully exploited. In the present study, we evaluated a diverse panel of 174 cultivated emmer accessions for their reaction to Bgt isolate OKS(14)-B-3-1 and found that 66% of accessions, particularly those of Ethiopian (30.5%) and Indian (6.3%) origins, exhibited high resistance. To determine the genetic basis of Bgt resistance in the panel, genome-wide association studies were performed using 46,383 single nucleotide polymorphisms (SNPs) from genotype-by-sequencing and 4331 SNPs from the 9K SNP Infinium array. Twenty-five significant SNP markers were identified to be associated with Bgt resistance, of which 21 SNPs are likely novel loci, whereas four possibly represent emmer derived Pm4a, Pm5a, PmG16, and Pm64. Most novel loci exhibited minor effects, whereas three novel loci on chromosome arms 2AS, 3BS, and 5AL had major effect on the phenotypic variance. This study demonstrates cultivated emmer as a rich source of powdery mildew resistance, and the resistant accessions and novel loci found herein can be utilized in wheat breeding programs to enhance Bgt resistance in wheat.

Identification of leaf rust resistance loci in hard winter wheat using genome-wide association mapping

Leaf rust, caused by Puccinia triticina (Pt), is a serious constraint to wheat production. Developing resistant varieties is the best approach to managing this disease. Wheat leaf rust resistance (Lr) genes have been classified into either all-stage resistance (ASR) or adult-plant resistance (APR). The objectives of this study were to identify sources of leaf rust resistance in contemporary US hard winter wheat (HWW) and to dissect the genetic basis underlying leaf rust resistance in HWW. A panel of 732 elite HWW genotypes was evaluated for response to US Pt races at the seedling stage and at the adult plant stage in leaf rust nurseries in Oklahoma, Texas, and Kansas. Further, the panel was genotyped using multiplex restriction amplicon sequencing (MRA-Seq) and DNA markers linked to the known ASR genes Lr18, Lr19, Lr21, Lr24, Lr37, and Lr42 and APR genes Lr34, Lr46, Lr67, Lr68, Lr77, and Lr78. Single nucleotide polymorphism (SNP) markers derived from MRA-Seq, DNA markers linked to the known Lr genes, and the phenotypic data were used for genome-wide association study (GWAS) to identify markers associated with leaf rust response. Gene postulation based on leaf rust reactions, DNA markers, and GWAS suggested the presence of Lr1, Lr2a, Lr10, Lr14a, Lr16, Lr18, Lr19, Lr21, Lr24, Lr26, Lr34, Lr37, Lr39, Lr42, Lr46, Lr68, Lr77, and Lr78 in the HWW panel. The GWAS identified 59 SNPs significantly associated with leaf rust response, of which 20 were likely associated with novel resistance loci and can be used to enhance wheat leaf rust resistance.

Genomic Markers Associated With Soybean Resistance to the Stem Borer, Dectes texanus (Coleoptera: Cerambycidae)

The Dectes stem borer, Dectes texanus LeConte (Coleoptera: Cerambycidae), can significantly reduce yields by causing significant lodging in soybean. While this stem borer has not been considered a major pest of soybean, damage from it is increasing in the United States Midwest region with no current elite cultivars found resistant. Our objective was to map quantitative trait loci (QTL) that reduce girdled stems caused by Dectes stem borer infection and infestation of Dectes stem borer. A genome-wide association study (GWAS) using 50,000 single nucleotide polymorphisms was used to analyze data from a population of maturity group (MG) V to VII soybean accessions grown in North Carolina, which had been scored for Dectes stem borer larvae infestation and girdled stems caused by Dectes stem borer infestation. The GWAS identified 3 QTL with reduced larvae infestation and 4 QTL for reduced girdled stems. Allele effects ranged from 1% to 9% reduced larvae infestation or girdled stems. The QTL identified and germplasm containing the beneficial alleles can be used for improving resistance to the damage caused by the Dectes stem borer in elite soybean cultivars.

Association mapping and genomic prediction for processing and end-use quality traits in wheat (Triticum aestivum L.)

End-use and processing traits in wheat (Triticum aestivum L.) are crucial for varietal development but are often evaluated only in the advanced stages of the breeding program due to the amount of grain needed and the labor-intensive phenotyping assays. Advances in genomic resources have provided new tools to address the selection for these complex traits earlier in the breeding process. We used association mapping to identify key variants underlying various end-use quality traits and evaluate the usefulness of genomic prediction for these traits in hard red spring wheat from the Northern United States. A panel of 383 advanced breeding lines and cultivars representing the diversity of the University of Minnesota wheat breeding program was genotyped using the Illumina 90K single nucleotide polymorphism array and evaluated in multilocation trials using standard assessments of end-use quality. Sixty-three associations for grain or flour characteristics, mixograph, farinograph, and baking traits were identified. The majority of these associations were mapped in the vicinity of glutenin/gliadin or other known loci. In addition, a putative novel multi-trait association was identified on chromosome 6AL, and candidate gene analysis revealed eight genes of interest. Further, genomic prediction had a high predictive ability (PA) for mixograph and farinograph traits, with PA up to 0.62 and 0.50 in cross-validation and forward prediction, respectively. The deployment of 46 markers from GWAS to predict dough-rheology traits yielded low to moderate PA for various traits. The results of this study suggest that genomic prediction for end-use traits in early generations can be effective for mixograph and farinograph assays but not baking assays.

Genome-wide association study of rice (Oryza sativa L.) inflorescence architecture

Rice yield strongly depends on panicle size and architecture but the genetics underlying these traits and their coordination with environmental cues through various signaling pathways have remained elusive. A genome-wide association study (GWAS) was performed to pinpoint the underlying genetic determinants for rice panicle architecture by analyzing 20 panicle-related traits using a data set consisting of 44,100 SNPs. We defined QTL windows around significant SNPs by the rate of LD decay for each chromosome and used these windows to identify putative candidate genes associated with the trait. Using a publicly available RNA-seq data set we performed analyses to identify the differentially expressed genes between stem and panicle with putative functions in panicle architecture. In total, 52 significant SNPs were identified, corresponding to 41 unique QTLs across the 12 rice chromosomes, with the most signals appearing on chromosome 1 (nine associated SNPs), and seven significant SNPs for each of chromosomes 8 and 12. Some novel genes such as Ankyrin, Duf, Kinesin and Brassinosteroid insensitive were found to be associated with panicle size. A haplotype analysis showed that genetic variation in haplotypes qMIL2 and qNSBBH21 were related to two traits, MIL, the greatest distance between two nodes on the rachis, and NSBBH, the number of primary branches in the bottom half of a panicle, respectively. Analysis of epistatic interactions revealed a marker affecting clustered traits. Several QTLs were identified on different chromosomes for the first time which may explain the phenotypic diversity of rice panicle architecture we observe in our collection of accessions. The identified candidate genes and haplotypes could be used in marker-assisted selection to improve rice yield through gene pyramiding.

Genome-Wide Association Study for Nodule Traits in Guar

Guar [Cyamopsis tetragonoloba (L.) Taub] is a diploid legume crop cultivated for galactomannan (guar gum) extracted from the endosperm of the seed. Previous studies have suggested that nodulation of guar can be poor in field conditions; however, solid proof has yet to be provided. The objectives of this study were to conduct a genome-wide association study (GWAS) and to identify single nucleotide polymorphism (SNP) markers associated with nodules in guar. GWAS was performed on a total of 225 guar genotypes using 19,007 filtered SNPs. Tassel 5 was used to run five models: single marker regression (SMR), generalized mixed linear model with PCA as a covariate (GLM_PCA), generalized mixed linear model with Q matrix as a covariate (GLM_Q), mixed linear model with PCA and Kinship (K) as covariates (GLM_PCA + K), and mixed linear model with Q and K as covariates (MLM_Q + K). Across all statistical models, the results showed a total of 3, 2, 25, 7, 2, and 3 SNPs were associated with plant height, nodule number per plant, fresh nodule weight, dry nodule weight, fresh aboveground plant biomass, and dry aboveground plant biomass. These SNPs could be used as a tool to select for better nodule traits in guar.

Integration of GWAS models and GS reveals the genetic architecture of ear shank in maize

Maize is one of the most important crops for human food, animal feed, and industrial raw materials. Ear shank length (ESL) and ear shank node number (ESNN) are crucial selection criteria in maize breeding, impacting grain yield and dehydration rate during mechanical harvesting. To unravel the genetic basis of ESL and ESNN in maize, an association panel consisting of 379 multi-parent doubled-haploid (DH) lines was developed for genome-wide association studies (GWAS) and genomic selection (GS). The heritabilities of ESL and ESNN were 0.68 and 0.55, respectively, which were controlled by genetic factors and genotype-environment interaction factors. Using five different models for GWAS, 11 significant single nucleotide polymorphisms (SNPs) located on chromosomes 1, 2, and 4 were identified for ESL, with the phenotypic variation explained (PVE) value of each single SNP ranging from 4.91% to 21.35%, and 11 significant SNPs located on chromosomes 1, 2, 4, and 5 were identified for ESNN, with the PVE value of each SNP ranging from 1.22% to 18.42%. Genetic regions in bins 1.06, 2.06, and 2.08 were significantly enriched in SNPs associated with ear shank-related traits. The GS prediction accuracy using all markers by the five-fold cross-validation method for ESL and ESNN was 0.39 and 0.37, respectively, which was significantly improved by using only 500-1000 significant SNPs with the lowest P-values. The optimal training population size (TPS) and marker density (MD) for ear shank-related traits were 50%-60% and 3000, respectively. Our results provide new insights into the GS of ear shank-related traits.

Genome-wide association study dissects the genetic architecture of progesterone content in Persian walnut leaves (Juglans regia L.)

Progesterone (P4) is an endogenous sex steroid hormone involved in the ovulatory cycle and pregnancy of animal species. In sheep and goats, P4 analogues are used to induce synchronized ovulations and oestrus behavior of the females. In humans, P4 from chemical synthesis is used to treat peri-menopausal disorders. However, such molecules are released into aquatic environment and can be a source of pollution, are prohibited in organic farms and go against the trend of "naturality" in animal production as well as in human health. A natural alternative may consist in the extraction and use of P4 in plants. Mammalian hormones were discovered in an increasing number of plant species, including walnut leaves that contain high levels of P4. We compared the content of P4 in leaves of 170 accessions of Juglans regia from the walnut germplasm collection of INRAE Prunus-Juglans Biological Resources Center previously genotyped using the Axiom™ J. regia 700 K SNP array. We conducted a genome-wide association study (GWAS) using multi-locus models. When collected in October, P4 content goes from 34,1 to 287,5 mg/kg dry weight of leaves. The two laciniate accessions have the largest P4 content. We identified seven significant marker-trait associations on chromosomes 1, 2, 3, 6, 7, 15 and 16, and a candidate gene involved in the metabolism of sterols, precursors of plant steroid hormones. Our results raise the huge variability of P4 content within J. regia and propose a candidate gene which may have a role in the control of this variability, opening the way to a potential use of walnut P4 by the pharmaceutical industry towards more natural source of chemical compounds.

Moisture-responsive root-branching pathways identified in diverse maize breeding germplasm

Plants grow complex root systems to extract unevenly distributed resources from soils. Spatial differences in soil moisture are perceived by root tips, leading to the patterning of new root branches toward available water in a process called hydropatterning. Little is known about hydropatterning behavior and its genetic basis in crop plants. Here, we developed an assay to measure hydropatterning in maize and revealed substantial differences between tropical/subtropical and temperate maize breeding germplasm that likely resulted from divergent selection. Genetic analysis of hydropatterning confirmed the regulatory role of auxin and revealed that the gaseous hormone ethylene locally inhibits root branching from air-exposed tissues. Our results demonstrate how distinct signaling pathways translate spatial patterns of water availability to developmental programs that determine root architecture.

A genome-wide association study identified SNP markers and candidate genes associated with morphometric fruit quality traits in mangoes

BACKGROUND

Mangoes (Mangifera indica L.) are a widely grown fruit tree crop across the world, but breeding new varieties can take 15-20 years due to its long juvenile period and high heterozygosity. Marker-assisted selection can accelerate breeding new mango cultivars with desirable traits for fruit quality, storage, horticulture, pest and disease resistance, and nutrition.

RESULTS

To achieve this, a genome-wide association study (GWAS) was conducted to discover molecular markers for 14 morphometric and economically important fruit traits of 161 mango accessions with diverse genetic backgrounds. These traits included pulp and brix; fruit weight, length, thickness, and width; stone weight, length, thickness, and width; and seed weight, length, thickness, and width. In this report, we employed the fixed and random model circulating probability unification (FarmCPU) model for conducting GWAS using 135,079 high-quality SNP markers. These analyses revealed 103 SNPs that were significantly associated with these traits. Of these markers, 7 were commonly associated with different traits, while 96 markers were uniquely associated with specific traits.

CONCLUSIONS

To choose the most promising mango accessions for future breeding and for closing genetic gaps among the accessions and increasing genetic diversity, a new selection method is suggested based on phenotypic traits such as high-yielding mango fruit cultivars, number of reference alleles, and genetic distance among the selected genotypes. Based on these criteria, 20 accessions were identified as the most promising parents for crossing to produce high mango yield. Gene annotation of the significant markers revealed candidate genes coding for important proteins, enzymes, and transcription factors associated with fruit development traits.

Genome-wide association study reveals major loci for resistance to septoria tritici blotch in a Tunisian durum wheat collection

Septoria tritici blotch (STB) is a devastating fungal disease affecting durum and bread wheat worldwide. Tunisian durum wheat landraces are reported to be valuable genetic resources for resistance to STB and should prominently be deployed in breeding programs to develop new varieties resistant to STB disease. In this study, a collection of 367 old durum and 6 modern wheat genotypes previously assessed using single Tunisian Zymoseptoria tritici isolate TUN06 during 2016 and 2017 and TM220 isolate during 2017 were phenotyped for resistance to a mixture of isolates (BULK) under field conditions. Significant correlations for disease traits using the three different inoculums were observed. Using 7638 SNP markers, fifty-one marker-trait associations (MTAs) for STB resistance were identified by genome-wide association study (GWAS) at Bonferroni correction threshold of -log10(P) > 5.184 with phenotypic variance explained (PVE) reaching up to 58%. A total of eleven QTL were identified using TUN06 isolate mean disease scoring (TUNMeanD and TUNMeanA) including threeQTL controlling resistance to both isolates TUN06 and TM220. A major QTL was identified on each of chromosomes 1B, 4B, 5A, and 7B, respectively. The QTL on 7B chromosome colocalized with Stb8 identified in bread wheat. Four QTL including the major QTL identified on chromosome 1B were considered as novel. SNP linked to the significant QTL have the potential to be used in marker-assisted selection for breeding for resistance to STB.

GRM1 as a Candidate Gene for Buffalo Fertility: Insights from Genome-Wide Association Studies and Its Role in the FOXO Signaling Pathway

BACKGROUND

Water buffaloes represent a crucial genetic resource for the global dairy industry, yet enhancements in their production performance remain relatively constrained. The advent of advanced sequencing technologies, coupled with genome-wide association studies (GWASs), has significantly boosted the potential for breeding superior-quality water buffalo.

METHODS

An integrated genomic analysis was performed on sequencing data from 100 water buffaloes, utilizing the high-quality UOA_WB_1 genome assembly as a reference. This study particularly emphasized reproduction-related traits, with a focus on age at first calving (AFC).

RESULTS

Our analysis revealed two significant single-nucleotide polymorphisms (SNPs). Based on these genetic markers, the GRM1 gene was identified as a candidate gene. This gene shows substantial involvement in various reproduction-associated pathways, including the FOXO signaling pathway, calcium signaling pathway, and estrogen signaling pathway.

CONCLUSIONS

The identification of GRM1 as a candidate gene provides a robust theoretical basis for molecular breeding strategies aimed at enhancing fertility in water buffaloes. These findings offer critical scientific support for optimizing breeding programs, thereby improving overall production efficiency.

Genome-wide association mapping and genomic prediction analyses reveal the genetic architecture of grain yield and agronomic traits under drought and optimum conditions in maize

BACKGROUND

Drought is a major abiotic stress in sub-Saharan Africa, impacting maize growth and development leading to severe yield loss. Drought tolerance is a complex trait regulated by multiple genes, making direct grain yield selection ineffective. To dissect the genetic architecture of grain yield and flowering traits under drought stress, a genome-wide association study (GWAS) was conducted on a panel of 236 maize lines testcrossed and evaluated under managed drought and optimal growing conditions in multiple environments using seven multi-locus GWAS models (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB, ISIS EM-BLASSO, and FARMCPU) from mrMLM and GAPIT R packages. Genomic prediction with RR-BLUP model was applied on BLUEs across locations under optimum and drought conditions.

RESULTS

A total of 172 stable and reliable quantitative trait nucleotides (QTNs) were identified, of which 77 are associated with GY, AD, SD, ASI, PH, EH, EPO and EPP under drought and 95 are linked to GY, AD, SD, ASI, PH, EH, EPO and EPP under optimal conditions. Among these QTNs, 17 QTNs explained over 10% of the phenotypic variation (R2 ≥ 10%). Furthermore, 43 candidate genes were discovered and annotated. Two major candidate genes, Zm00001eb041070 closely associated with grain yield near peak QTN, qGY_DS1.1 (S1_216149215) and Zm00001eb364110 closely related to anthesis-silking interval near peak QTN, qASI_DS8.2 (S8_167256316) were identified, encoding AP2-EREBP transcription factor 60 and TCP-transcription factor 20, respectively under drought stress. Haplo-pheno analysis identified superior haplotypes for qGY_DS1.1 (S1_216149215) associated with the higher grain yield under drought stress. Genomic prediction revealed moderate to high prediction accuracies under optimum and drought conditions.

CONCLUSION

The lines carrying superior haplotypes can be used as potential donors in improving grain yield under drought stress. Integration of genomic selection with GWAS results leads not only to an increase in the prediction accuracy but also to validate the function of the identified candidate genes as well increase in the accumulation of favorable alleles with minor and major effects in elite breeding lines. This study provides valuable insight into the genetic architecture of grain yield and secondary traits under drought stress.

Comparative genome-wide association study of single- and multi-locus models with ontology analysis for enhancing Hanwoo cow reproductive traits

The reproductive characteristics of Hanwoo play a significant role in farm profitability by decreasing the generation interval. This study analyzed 1015 primiparous and 916 multiparous cows using a genome-wide association study with both single-locus (GEMMA, GCTA) and multi-locus models (FarmCPU, BLINK). A significant marker for age at first service was identified across all methods. For age at first conception, GEMMA identified two markers, while FarmCPU and BLINK identified 14 and two markers, respectively. Regarding age at first calving, GEMMA identified two markers, and FarmCPU and BLINK found 15 and two markers, respectively. In multiparous cows, except for days open, one marker for gestation length and two markers for calving interval were identified in the multi-locus models (FarmCPU and BLINK). Additionally, one marker for the number of services per conception was identified using GEMMA. Key candidate genes included PLCB1 (maintaining pregnancy), MUC1 (fetal development), and ADCY5 (associated with fetal birth), while TXNL1 regulates embryo implantation timing. Gene ontology functions associated with embryo implantation and placental regulation were also confirmed (GO:0046875). Although the multi-locus models identified a greater number of markers and candidate genes, there was no overlap with the results from the single-locus models. The multi-locus models showed enhanced detection power, but slight inflation in test statistics (λ values) necessitates cautious interpretation to avoid false positives. Thus, a combination of both models is recommended to improve reproductive efficiency in cows, providing valuable insights into the genetic aspects of reproductive traits.