From phenotypes to causal sequences: using genome wide association studies to dissect the sequence basis for variation of plant development

Fast and Efficient Root Phenotyping via Pose Estimation

Image segmentation is commonly used to estimate the location and shape of plants and their external structures. Segmentation masks are then used to localize landmarks of interest and compute other geometric features that correspond to the plant's phenotype. Despite its prevalence, segmentation-based approaches are laborious (requiring extensive annotation to train) and error-prone (derived geometric features are sensitive to instance mask integrity). Here, we present a segmentation-free approach that leverages deep learning-based landmark detection and grouping, also known as pose estimation. We use a tool originally developed for animal motion capture called SLEAP (Social LEAP Estimates Animal Poses) to automate the detection of distinct morphological landmarks on plant roots. Using a gel cylinder imaging system across multiple species, we show that our approach can reliably and efficiently recover root system topology at high accuracy, few annotated samples, and faster speed than segmentation-based approaches. In order to make use of this landmark-based representation for root phenotyping, we developed a Python library (sleap-roots) for trait extraction directly comparable to existing segmentation-based analysis software. We show that pose-derived root traits are highly accurate and can be used for common downstream tasks including genotype classification and unsupervised trait mapping. Altogether, this work establishes the validity and advantages of pose estimation-based plant phenotyping. To facilitate adoption of this easy-to-use tool and to encourage further development, we make sleap-roots, all training data, models, and trait extraction code available at: https://github.com/talmolab/sleap-roots and https://osf.io/k7j9g/.

Genome-wide association analysis reveals genes controlling an antagonistic effect of biotic and osmotic stress on Arabidopsis thaliana growth

While the response of Arabidopsis thaliana to drought, herbivory or fungal infection has been well-examined, the consequences of exposure to a series of such (a)biotic stresses are not well studied. This work reports on the genetic mechanisms underlying the Arabidopsis response to single osmotic stress, and to combinatorial stress, either fungal infection using Botrytis cinerea or herbivory using Pieris rapae caterpillars followed by an osmotic stress treatment. Several small-effect genetic loci associated with rosette dry weight (DW), rosette water content (WC), and the projected rosette leaf area in response to combinatorial stress were mapped using univariate and multi-environment genome-wide association approaches. A single-nucleotide polymorphism (SNP) associated with DROUGHT-INDUCED 19 (DI19) was identified by both approaches, supporting its potential involvement in the response to combinatorial stress. Several SNPs were found to be in linkage disequilibrium with known stress-responsive genes such as PEROXIDASE 34 (PRX34), BASIC LEUCINE ZIPPER 25 (bZIP25), RESISTANCE METHYLATED GENE 1 (RMG1) and WHITE RUST RESISTANCE 4 (WRR4). An antagonistic effect between biotic and osmotic stress was found for prx34 and arf4 mutants, which suggests PRX34 and ARF4 play an important role in the response to the combinatorial stress.

Genetic analysis for detection of genes associated to drought tolerance in rice accessions belonging to north east India

INTRODUCTION

The North East (NE) India is rich in biodiversity and also considered as the secondary centre for origin of rice. The NE rice accessions was characterized previously using genetic markers and morphological traits. Simultaneously, genome-wide association studies (GWAS) reveal significant marker-trait associations for the drought tolerance traits.

METHODS AND RESULTS

The genetic diversity and population structure of 296 NE rice accessions were studied using 96,712 single nucleotide polymorphism (SNP) markers distributed across 12 chromosomes. The accessions were clustered into two major sub-groups (SG). A total of 91 accessions were assembled as SG1 and 114 accessions as SG2, while the remaining 91 were admixture genotypes. A total of 200 genotypes belonging to different groups were phenotyped for yield component traits under drought and control conditions. The GWAS was performed to identify significant marker-trait associations (MTAs). Consequently, 47 MTAs were detected under drought, exhibiting 0.02-9.95% of phenotypic variance (P.V.). Whereas 58 MTAs were discovered under control conditions, showing a 0.01-9.74% contribution to the phenotype. Through in-silico mining of QTLs, 2999 genes were identified. Among these; only 22 genes were directly associated with stress response.

CONCLUSION

These QTLs/genes may be deployed for marker-assisted pyramiding to improve drought tolerance in popular drought susceptible rice varieties.

Unlocking the potentials of nitrate transporters at improving plant nitrogen use efficiency

Nitrate ( NO 3 - ) transporters have been identified as the primary targets involved in plant nitrogen (N) uptake, transport, assimilation, and remobilization, all of which are key determinants of nitrogen use efficiency (NUE). However, less attention has been directed toward the influence of plant nutrients and environmental cues on the expression and activities of NO 3 - transporters. To better understand how these transporters function in improving plant NUE, this review critically examined the roles of NO 3 - transporters in N uptake, transport, and distribution processes. It also described their influence on crop productivity and NUE, especially when co-expressed with other transcription factors, and discussed these transporters' functional roles in helping plants cope with adverse environmental conditions. We equally established the possible impacts of NO 3 - transporters on the uptake and utilization efficiency of other plant nutrients while suggesting possible strategic approaches to improving NUE in plants. Understanding the specificity of these determinants is crucial to achieving better N utilization efficiency in crops within a given environment.

Genome-wide association study of 23 flowering phenology traits and 4 floral agronomic traits in tree peony (Paeonia section Moutan DC.) reveals five genes known to regulate flowering time

Tree peony is a unique traditional flower in China, with large, fragrant, and colorful flowers. However, a relatively short and concentrated flowering period limits the applications and production of tree peony. A genome-wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of flowering phenology traits and ornamental phenotypes in tree peony. A diverse panel of 451 tree peony accessions was phenotyped for 23 flowering phenology traits and 4 floral agronomic traits over 3 years. Genotyping by sequencing (GBS) was used to obtain a large number of genome-wide single-nucleotide polymorphisms (SNPs) (107 050) for the panel genotypes, and 1047 candidate genes were identified by association mapping. Eighty-two related genes were observed during at least 2 years for flowering, and seven SNPs repeatedly identified for multiple flowering phenology traits over multiple years were highly significantly associated with five genes known to regulate flowering time. We validated the temporal expression profiles of these candidate genes and highlighted their possible roles in the regulation of flower bud differentiation and flowering time in tree peony. This study shows that GWAS based on GBS can be used to identify the genetic determinants of complex traits in tree peony. The results expand our understanding of flowering time control in perennial woody plants. Identification of markers closely related to these flowering phenology traits can be used in tree peony breeding programs for important agronomic traits.

A genome-wide association study identifies novel players in Na and Fe homeostasis in Arabidopsis thaliana under alkaline-salinity stress

In nature, multiple stress factors occur simultaneously. The screening of natural diversity panels and subsequent Genome-Wide Association Studies (GWAS) is a powerful approach to identify genetic components of various stress responses. Here, the nutritional status variation of a set of 270 natural accessions of Arabidopsis thaliana grown on a natural saline-carbonated soil is evaluated. We report significant natural variation on leaf Na (LNa) and Fe (LFe) concentrations in the studied accessions. Allelic variation in the NINJA and YUC8 genes is associated with LNa diversity, and variation in the ALA3 is associated with LFe diversity. The allelic variation detected in these three genes leads to changes in their mRNA expression and correlates with plant differential growth performance when plants are exposed to alkaline salinity treatment under hydroponic conditions. We propose that YUC8 and NINJA expression patters regulate auxin and jasmonic signaling pathways affecting plant tolerance to alkaline salinity. Finally, we describe an impairment in growth and leaf Fe acquisition associated with differences in root expression of ALA3, encoding a phospholipid translocase active in plasma membrane and the trans Golgi network which directly interacts with proteins essential for the trafficking of PIN auxin transporters, reinforcing the role of phytohormonal processes in regulating ion homeostasis under alkaline salinity.

Medicago truncatula quantitative resistance to a new strain of Verticillium alfalfae from Iran revealed by a genome-wide association study

Verticillium wilt is a major threat to many crops, among them alfalfa (Medicago sativa). The model plant Medicago truncatula, a close relative of alfalfa was used to study the genetic control of resistance towards a new Verticillium alfalfae isolate. The accidental introduction of pathogen strains through global trade is a threat to crop production and such new strains might also be better adapted to global warming. Isolates of V. alfalfae were obtained from alfalfa fields in Iran and characterized. The Iranian isolate AF1 was used in a genome-wide association study (GWAS) involving 242 accessions from the Mediterranean region. Root inoculations were performed with conidia at 25°C and symptoms were scored regularly. Maximum Symptom Score and Area under Disease Progess Curve were computed as phenotypic traits to be used in GWAS and for comparison to a previous study with French isolate V31.2 at 20°C. This comparison showed high correlation with a shift to higher susceptibility, and similar geographical distribution of resistant and susceptible accessions to AF1 at 25°C, with resistant accessions mainly in the western part. GWAS revealed 30 significant SNPs linked to resistance towards isolate AF1. None of them were common to the previous study with isolate V31.2 at 20°C. To confirm these loci, the expression of nine underlying genes was studied. All genes were induced in roots following inoculation, in susceptible and resistant plants. However, in resistant plants induction was higher and lasted longer. Taken together, the use of a new pathogen strain and a shift in temperature revealed a completely different genetic control compared to a previous study that demonstrated the existence of two major QTLs. These results can be useful for Medicago breeding programs to obtain varieties better adapted to future conditions.

In-depth analysis of genomes and functional genomics of orchid using cutting-edge high-throughput sequencing

High-throughput sequencing technology has been facilitated the development of new methodologies and approaches for studying the origin and evolution of plant genomes and subgenomes, population domestication, and functional genomics. Orchids have tens of thousands of members in nature. Many of them have promising application potential in the extension and conservation of the ecological chain, the horticultural use of ornamental blossoms, and the utilization of botanical medicines. However, a large-scale gene knockout mutant library and a sophisticated genetic transformation system are still lacking in the improvement of orchid germplasm resources. New gene editing tools, such as the favored CRISPR-Cas9 or some base editors, have not yet been widely applied in orchids. In addition to a large variety of orchid cultivars, the high-precision, high-throughput genome sequencing technology is also required for the mining of trait-related functional genes. Nowadays, the focus of orchid genomics research has been directed to the origin and classification of species, genome evolution and deletion, gene duplication and chromosomal polyploidy, and flower morphogenesis-related regulation. Here, the progressing achieved in orchid molecular biology and genomics over the past few decades have been discussed, including the evolution of genome size and polyploidization. The frequent incorporation of LTR retrotransposons play important role in the expansion and structural variation of the orchid genome. The large-scale gene duplication event of the nuclear genome generated plenty of recently tandem duplicated genes, which drove the evolution and functional divergency of new genes. The evolution and loss of the plastid genome, which mostly affected genes related to photosynthesis and autotrophy, demonstrated that orchids have experienced more separate transitions to heterotrophy than any other terrestrial plant. Moreover, large-scale resequencing provide useful SNP markers for constructing genetic maps, which will facilitate the breeding of novel orchid varieties. The significance of high-throughput sequencing and gene editing technologies in the identification and molecular breeding of the trait-related genes in orchids provides us with a representative trait-improving gene as well as some mechanisms worthy of further investigation. In addition, gene editing has promise for the improvement of orchid genetic transformation and the investigation of gene function. This knowledge may provide a scientific reference and theoretical basis for orchid genome studies.

Genome-Wide Association Study Reveals Candidate Genes for Root-Related Traits in Rice

Root architecture is a determinant factor of drought resistance in rice and plays essential roles in the absorption of water and nutrients for the survival of rice plants. Dissection of the genetic basis for root structure can help to improve stress-resistance and grain yield in rice breeding. In this study, a total of 391 rice (Oryz asativa L.) accessions were used to perform a genome-wide association study (GWAS) on three root-related traits in rice, including main root length (MRL), average root length (ARL), and total root number (TRN). As a result, 13 quantitative trait loci (QTLs) (qMRL1.1, qMRL1.2, qMRL3.1, qMRL3.2, qMRL3.3, qMRL4.1, qMRL7.1, qMRL8.1, qARL1.1, qARL9.1, qTRN9.1, qTRN9.2, and qTRN11.1) significantly associated with the three traits were identified, among which three (qMRL3.2, qMRL4.1 and qMRL8.1) were overlapped with OsGNOM1, OsARF12 and qRL8.1, respectively, and ten were novel QTLs. Moreover, we also detected epistatic interactions affecting root-related traits and identified 19 related genetic interactions. These results lay a foundation for cloning the corresponding genes for rice root structure, as well as provide important genomic resources for breeding high yield rice varieties.

Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform

The plant kingdom contains a stunning array of complex morphologies easily observed above-ground, but more challenging to visualize below-ground. Understanding the magnitude of diversity in root distribution within the soil, termed root system architecture (RSA), is fundamental in determining how this trait contributes to species adaptation in local environments. Roots are the interface between the soil environment and the shoot system and therefore play a key role in anchorage, resource uptake, and stress resilience. Previously, we presented the GLO-Roots (Growth and Luminescence Observatory for Roots) system to study the RSA of soil-grown Arabidopsis thaliana plants from germination to maturity (Rellán-Álvarez et al., 2015). In this study, we present the automation of GLO-Roots using robotics and the development of image analysis pipelines in order to examine the temporal dynamic regulation of RSA and the broader natural variation of RSA in Arabidopsis, over time. These datasets describe the developmental dynamics of two independent panels of accessions and reveal highly complex and polygenic RSA traits that show significant correlation with climate variables of the accessions’ respective origins.

Genetic basis underlying tiller angle in rice (Oryza sativa L.) by genome-wide association study

Novel alleles of two reported tiller angle genes and eleven candidate genes for rice tiller angle were identified by combining GWAS with transcriptomic, qRT-PCR and haplotype analysis. Rice tiller angle is a key agronomic trait determining rice grain yield. Several quantitative trait loci (QTLs) affecting rice tiller angle have been mapped in the past decades. Little is known about the genetic base of tiller angle in rice, because rice tiller angle is a complex polygenic trait. In this study, we performed genome-wide association study (GWAS) on tiller angle in rice using a population of 164 japonica varieties derived from the 3 K Rice Genomes Project (3 K RGP). We detected a total of 18 QTLs using 1135519 single-nucleotide polymorphisms (SNP) based on three GWAS models (GLM, FastLMM and FarmCPU). Among them, two identified QTLs, qTA8.3 and qTA8.4, overlapped with PAY1 and TIG1, respectively, and additional 16 QTLs were identified for the first time. Combined with haplotype and expression analyses, we further revealed that PAY1 harbors one non-synonymous variation at its coding region, likely leading to variable tiller angle in the population, and that nature variations in the promoter of TIG1 significantly affect its expression, closely correlating with tiller angle phenotypes observed. Similarly, using qRT-PCR and haplotype analysis, we identified 1 and 7 candidate genes in qTA6.1 and qTA8.1 that were commonly detected by two GWAS models, respectively. In addition, we identified 3 more candidate genes in the remaining 14 novel QTLs after filtering by transcriptome analysis and qRT-PCR. In summary, this study provides new insights into the genetic architecture of rice tiller angle and candidate genes for rice breeding.

Two decades of association mapping: Insights on disease resistance in major crops

Climate change across the globe has an impact on the occurrence, prevalence, and severity of plant diseases. About 30% of yield losses in major crops are due to plant diseases; emerging diseases are likely to worsen the sustainable production in the coming years. Plant diseases have led to increased hunger and mass migration of human populations in the past, thus a serious threat to global food security. Equipping the modern varieties/hybrids with enhanced genetic resistance is the most economic, sustainable and environmentally friendly solution. Plant geneticists have done tremendous work in identifying stable resistance in primary genepools and many times other than primary genepools to breed resistant varieties in different major crops. Over the last two decades, the availability of crop and pathogen genomes due to advances in next generation sequencing technologies improved our understanding of trait genetics using different approaches. Genome-wide association studies have been effectively used to identify candidate genes and map loci associated with different diseases in crop plants. In this review, we highlight successful examples for the discovery of resistance genes to many important diseases. In addition, major developments in association studies, statistical models and bioinformatic tools that improve the power, resolution and the efficiency of identifying marker-trait associations. Overall this review provides comprehensive insights into the two decades of advances in GWAS studies and discusses the challenges and opportunities this research area provides for breeding resistant varieties.

The INCREASE project: Intelligent Collections of food-legume genetic resources for European agrofood systems

Food legumes are crucial for all agriculture-related societal challenges, including climate change mitigation, agrobiodiversity conservation, sustainable agriculture, food security and human health. The transition to plant-based diets, largely based on food legumes, could present major opportunities for adaptation and mitigation, generating significant co-benefits for human health. The characterization, maintenance and exploitation of food-legume genetic resources, to date largely unexploited, form the core development of both sustainable agriculture and a healthy food system. INCREASE will implement, on chickpea (Cicer arietinum), common bean (Phaseolus vulgaris), lentil (Lens culinaris) and lupin (Lupinus albus and L. mutabilis), a new approach to conserve, manage and characterize genetic resources. Intelligent Collections, consisting of nested core collections composed of single-seed descent-purified accessions (i.e., inbred lines), will be developed, exploiting germplasm available both from genebanks and on-farm and subjected to different levels of genotypic and phenotypic characterization. Phenotyping and gene discovery activities will meet, via a participatory approach, the needs of various actors, including breeders, scientists, farmers and agri-food and non-food industries, exploiting also the power of massive metabolomics and transcriptomics and of artificial intelligence and smart tools. Moreover, INCREASE will test, with a citizen science experiment, an innovative system of conservation and use of genetic resources based on a decentralized approach for data management and dynamic conservation. By promoting the use of food legumes, improving their quality, adaptation and yield and boosting the competitiveness of the agriculture and food sector, the INCREASE strategy will have a major impact on economy and society and represents a case study of integrative and participatory approaches towards conservation and exploitation of crop genetic resources.

Exploring the gene pool of Brassica napus by genomics-based approaches

De novo allopolyploidization in Brassica provides a very successful model for reconstructing polyploid genomes using progenitor species and relatives to broaden crop gene pools and understand genome evolution after polyploidy, interspecific hybridization and exotic introgression. B. napus (AACC), the major cultivated rapeseed species and the third largest oilseed crop in the world, is a young Brassica species with a limited genetic base resulting from its short history of domestication, cultivation, and intensive selection during breeding for target economic traits. However, the gene pool of B. napus has been significantly enriched in recent decades that has been benefit from worldwide effects by the successful introduction of abundant subgenomic variation and novel genomic variation via intraspecific, interspecific and intergeneric crosses. An important question in this respect is how to utilize such variation to breed crops adapted to the changing global climate. Here, we review the genetic diversity, genome structure, and population-level differentiation of the B. napus gene pool in relation to known exotic introgressions from various species of the Brassicaceae, especially those elucidated by recent genome-sequencing projects. We also summarize progress in gene cloning, trait-marker associations, gene editing, molecular marker-assisted selection and genome-wide prediction, and describe the challenges and opportunities of these techniques as molecular platforms to exploit novel genomic variation and their value in the rapeseed gene pool. Future progress will accelerate the creation and manipulation of genetic diversity with genomic-based improvement, as well as provide novel insights into the neo-domestication of polyploid crops with novel genetic diversity from reconstructed genomes.

Development of an Aus-Derived Nested Association Mapping (Aus-NAM) Population in Rice

A genetic resource for studying genetic architecture of agronomic traits and environmental adaptation is essential for crop improvements. Here, we report the development of a rice nested association mapping population (aus-NAM) using 7 aus varieties as diversity donors and T65 as the common parent. Aus-NAM showed broad phenotypic variations. To test whether aus-NAM was useful for quantitative trait loci (QTL) mapping, known flowering genes (Ehd1, Hd1, and Ghd7) in rice were characterized using single-family QTL mapping, joint QTL mapping, and the methods based on genome-wide association study (GWAS). Ehd1 was detected in all the seven families and all the methods. On the other hand, Hd1 and Ghd7 were detected in some families, and joint QTL mapping and GWAS-based methods resulted in weaker and uncertain peaks. Overall, the high allelic variations in aus-NAM provide a valuable genetic resource for the rice community.

ABA Metabolism and Homeostasis in Seed Dormancy and Germination

Abscisic acid (ABA) is a key hormone that promotes dormancy during seed development on the mother plant and after seed dispersal participates in the control of dormancy release and germination in response to environmental signals. The modulation of ABA endogenous levels is largely achieved by fine-tuning, in the different seed tissues, hormone synthesis by cleavage of carotenoid precursors and inactivation by 8'-hydroxylation. In this review, we provide an overview of the current knowledge on ABA metabolism in developing and germinating seeds; notably, how environmental signals such as light, temperature and nitrate control seed dormancy through the adjustment of hormone levels. A number of regulatory factors have been recently identified which functional relationships with major transcription factors, such as ABA INSENSITIVE3 (ABI3), ABI4 and ABI5, have an essential role in the control of seed ABA levels. The increasing importance of epigenetic mechanisms in the regulation of ABA metabolism gene expression is also described. In the last section, we give an overview of natural variations of ABA metabolism genes and their effects on seed germination, which could be useful both in future studies to better understand the regulation of ABA metabolism and to identify candidates as breeding materials for improving germination properties.

Cadmium Immobilization in the Rhizosphere and Plant Cellular Detoxification: Role of Plant-Growth-Promoting Rhizobacteria as a Sustainable Solution

Food is the major cadmium (Cd)-exposure pathway from agricultural soils to humans and other living entities and must be reduced in an effective way. A plant can select beneficial microbes, like plant-growth-promoting rhizobacteria (PGPR), depending upon the nature of root exudates in the rhizosphere, for its own benefits, such as plant growth promotion as well as protection from metal toxicity. This review intends to seek out information on the rhizo-immobilization of Cd in polluted soils using the PGPR along with plant nutrient fertilizers. This review suggests that the rhizo-immobilization of Cd by a combination of PGPR and nanohybrid-based plant nutrient fertilizers would be a potential and sustainable technology for phytoavailable Cd immobilization in the rhizosphere and plant cellular detoxification, by keeping the plant nutrition flow and green dynamics of plant nutrition and boosting the plant growth and development under Cd stress.

Genome wide association studies for japonica rice resistance to blast in field and controlled conditions

BACKGROUND

Rice blast, caused by the fungus Pyricularia oryzae, represents the most damaging fungal disease of rice worldwide. Utilization of rice resistant cultivars represents a practical way to control the disease. Most of the rice varieties cultivated in Europe and several other temperate regions are severely depleted of blast resistance genes, making the identification of resistant sources in genetic background adapted to temperate environments a priority. Given these assumptions, a Genome Wide Association Study (GWAS) for rice blast resistance was undertaken using a panel of 311 temperate/tropical japonica and indica accessions adapted to temperate conditions and genotyped with 37,423 SNP markers. The panel was evaluated for blast resistance in field, under the pressure of the natural blast population, and in growth chamber, using a mixture of three different fungal strains.

RESULTS

The parallel screening identified 11 accessions showing high levels of resistance in the two conditions, representing potential donors of resistance sources harbored in rice genotypes adapted to temperate conditions. A general higher resistance level was observed in tropical japonica and indica with respect to temperate japonica varieties. The GWAS identified 14 Marker-Traits Associations (MTAs), 8 of which discovered under field conditions and 6 under growth chamber screening. Three MTAs were identified in both conditions; five MTAs were specifically detected under field conditions while three for the growth chamber inoculation. Comparative analysis of physical/genetic positions of the MTAs showed that most of them were positionally-related with cloned or mapped blast resistance genes or with candidate genes whose functions were compatible for conferring pathogen resistance. However, for three MTAs, indicated as BRF10, BRF11-2 and BRGC11-3, no obvious candidate genes or positional relationships with blast resistance QTLs were identified, raising the possibility that they represent new sources of blast resistance.

CONCLUSIONS

We identified 14 MTAs for blast resistance using both field and growth chamber screenings. A total of 11 accessions showing high levels of resistance in both conditions were discovered. Combinations of loci conferring blast resistance were identified in rice accessions adapted to temperate conditions, thus allowing the genetic dissection of affordable resistances present in the panel. The obtained information will provide useful bases for both resistance breeding and further characterization of the highlighted resistance loci.

Identification of miRNA-eQTLs in maize mature leaf by GWAS

Background

MiRNAs play essential roles in plant development and response to biotic and abiotic stresses through interaction with their target genes. The expression level of miRNAs shows great variations among different plant accessions, developmental stages, and tissues. Little is known about the content within the plant genome contributing to the variations in plants. This study aims to identify miRNA expression-related quantitative trait loci (miR-QTLs) in the maize genome.

Results

The miRNA expression level from next generation sequencing (NGS) small RNA libraries derived from mature leaf samples of the maize panel (200 maize lines) was estimated as phenotypes, and maize Hapmap v3.2.1 was chosen as the genotype for the genome-wide association study (GWAS). A total of four significant miR-eQTLs were identified contributing to miR156k-5p, miR159a-3p, miR390a-5p and miR396e-5p, and all of them are trans-eQTLs. In addition, a strong positive coexpression of miRNA was found among five miRNA families. Investigation of the effects of these miRNAs on the expression levels and target genes provided evidence that miRNAs control the expression of their targets by suppression and enhancement.

Conclusions

These identified significant miR-eQTLs contribute to the diversity of miRNA expression in the maize penal at the developmental stages of mature leaves in maize, and the positive and negative regulation between miRNA and its target genes has also been uncovered.

Computational solutions for modeling and controlling plant response to abiotic stresses: a review with focus on iron deficiency

Computational solutions enable plant scientists to model protein-mediated stress responses and characterize novel gene functions that coordinate responses to a variety of abiotic stress conditions. Recently, density functional theory was used to study proteins active sites and elucidate enzyme conversion mechanisms involved in iron deficiency responsive signaling pathways. Computational approaches for protein homology modeling and the kinetic modeling of signaling pathways have also resolved the identity and function in proteins involved in iron deficiency signaling pathways. Significant changes in gene relationships under other stress conditions, such as heat or drought stress, have been recently identified using differential network analysis, suggesting that stress tolerance is achieved through asynchronous control. Moreover, the increasing development and use of statistical modeling and systematic modeling of transcriptomic data have provided significant insight into the gene regulatory mechanisms associated with abiotic stress responses. These types of in silico approaches have facilitated the plant science community's future goals of developing multi-scale models of responses to iron deficiency stress and other abiotic stress conditions.

Photosynthesis in a Changing Global Climate: Scaling Up and Scaling Down in Crops

Photosynthesis is the major process leading to primary production in the Biosphere. There is a total of 7000bn tons of CO2 in the atmosphere and photosynthesis fixes more than 100bn tons annually. The CO2 assimilated by the photosynthetic apparatus is the basis of crop production and, therefore, of animal and human food. This has led to a renewed interest in photosynthesis as a target to increase plant production and there is now increasing evidence showing that the strategy of improving photosynthetic traits can increase plant yield. However, photosynthesis and the photosynthetic apparatus are both conditioned by environmental variables such as water availability, temperature, [CO2], salinity, and ozone. The "omics" revolution has allowed a better understanding of the genetic mechanisms regulating stress responses including the identification of genes and proteins involved in the regulation, acclimation, and adaptation of processes that impact photosynthesis. The development of novel non-destructive high-throughput phenotyping techniques has been important to monitor crop photosynthetic responses to changing environmental conditions. This wealth of data is being incorporated into new modeling algorithms to predict plant growth and development under specific environmental constraints. This review gives a multi-perspective description of the impact of changing environmental conditions on photosynthetic performance and consequently plant growth by briefly highlighting how major technological advances including omics, high-throughput photosynthetic measurements, metabolic engineering, and whole plant photosynthetic modeling have helped to improve our understanding of how the photosynthetic machinery can be modified by different abiotic stresses and thus impact crop production.

PANOMICS meets germplasm

Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are emerging providing 1000 and more genotypes and millions of SNPs for one species covering a hitherto inaccessible intraspecific genetic variation. The larger the databases are growing, the better statistical approaches for genomic selection will be available. However, there are clear limitations on the statistical but also on the biological part. Intraspecific genetic variation is able to explain a high proportion of the phenotypes, but a large part of phenotypic plasticity also stems from environmentally driven transcriptional, post-transcriptional, translational, post-translational, epigenetic and metabolic regulation. Moreover, regulation of the same gene can have different phenotypic outputs in different environments. Consequently, to explain and understand environment-dependent phenotypic plasticity based on the available genotype variation we have to integrate the analysis of further molecular levels reflecting the complete information flow from the gene to metabolism to phenotype. Interestingly, metabolomics platforms are already more cost-effective than NGS platforms and are decisive for the prediction of nutritional value or stress resistance. Here, we propose three fundamental pillars for future breeding strategies in the framework of Green Systems Biology: (i) combining genome selection with environment-dependent PANOMICS analysis and deep learning to improve prediction accuracy for marker-dependent trait performance; (ii) PANOMICS resolution at subtissue, cellular and subcellular level provides information about fundamental functions of selected markers; (iii) combining PANOMICS with genome editing and speed breeding tools to accelerate and enhance large-scale functional validation of trait-specific precision breeding.

Exploiting natural variation in root system architecture via genome-wide association studies

Root growth and development has become an important research topic for breeders and researchers based on a growing need to adapt plants to changing and more demanding environmental conditions worldwide. Over the last few years, genome-wide association studies (GWASs) became an important tool to identify the link between traits in the field and their genetic background. Here we give an overview of the current literature concerning GWASs performed on root system architecture (RSA) in plants. We summarize which root traits and approaches have been used for GWAS, mentioning their respective success rate towards a successful gene discovery. Furthermore, we zoom in on the current technical hurdles in root phenotyping and GWAS, and discuss future possibilities in this field of research.

Common alleles of CMT2 and NRPE1 are major determinants of CHH methylation variation in Arabidopsis thaliana

DNA cytosine methylation is an epigenetic mark associated with silencing of transposable elements (TEs) and heterochromatin formation. In plants, it occurs in three sequence contexts: CG, CHG, and CHH (where H is A, T, or C). The latter does not allow direct inheritance of methylation during DNA replication due to lack of symmetry, and methylation must therefore be re-established every cell generation. Genome-wide association studies (GWAS) have previously shown that CMT2 and NRPE1 are major determinants of genome-wide patterns of TE CHH methylation. Here we instead focus on CHH methylation of individual TEs and TE-families, allowing us to identify the pathways involved in CHH methylation simply from natural variation and confirm the associations by comparing them with mutant phenotypes. Methylation at TEs targeted by the RNA-directed DNA methylation (RdDM) pathway is unaffected by CMT2 variation, but is strongly affected by variation at NRPE1, which is largely responsible for the longitudinal cline in this phenotype. In contrast, CMT2-targeted TEs are affected by both loci, which jointly explain 7.3% of the phenotypic variation (13.2% of total genetic effects). There is no longitudinal pattern for this phenotype, however, because the geographic patterns appear to compensate for each other in a pattern suggestive of stabilizing selection.

DNA methylation is a major component of transposon silencing, and essential for genomic integrity. Recent studies revealed large-scale geographic variation as well as the existence of major trans-acting polymorphisms that partly explained this variation. In this study, we re-analyze previously published data (The 1001 Epigenomes), focusing on CHH methylation patterns of individual TEs and TE families rather than on genome-wide averages (as was done in previous studies). GWAS of the patterns reveals the underlying regulatory networks, and allowed us to comprehensively characterize trans-regulation of CHH methylation and its role in the striking geographic pattern for this phenotype.

Genetic Loci Associated with Early Salt Stress Responses of Roots

Salinity is a devastating abiotic stress accounting for major crop losses yearly. Plant roots can strikingly grow away from high-salt patches. This response is termed halotropism and occurs through auxin redistribution in roots in response to a salt gradient. Here, a natural variation screen for the early and NaCl-specific halotropic response of 333 Arabidopsis accessions revealed quantitative differences in the first 24 h. These data were successfully used to identify genetic components associated with the response through Genome-Wide Association Study (GWAS). Follow-up characterization of knockout mutants in Col-0 background confirmed the role of transcription factor WRKY25, cation-proton exchanger CHX13, and a gene of unknown function DOB1 (Double Bending 1) in halotropism. In chx13 and dob1 mutants, ion accumulation and shoot biomass under salt stress were also affected. Thus, our GWAS has identified genetic components contributing to main root halotropism that provide insight into the genetic architecture underlying plant salt responses.

A Genome-Wide Association Study Revealed Key SNPs/Genes Associated With Salinity Stress Tolerance In Upland Cotton

Millions of hectares of land are too saline to produce economically valuable crop yields. Salt tolerance in cotton is an imperative approach for improvement in response to ever-increasing soil salinization. Little is known about the genetic basis of salt tolerance in cotton at the seedling stage. To address this issue, a genome-wide association study (GWAS) was conducted on a core collection of a genetically diverse population of upland cotton (Gossypium hirsutum L.) comprising of 419 accessions, representing various geographic origins, including China, USA, Pakistan, the former Soviet Union, Chad, Australia, Brazil, Mexico, Sudan, and Uganda. Phenotypic evaluation of 7 traits under control (0 mM) and treatment (150 mM) NaCl conditions depicted the presence of broad natural variation in the studied population. The association study was carried out with the efficient mixed-model association eXpedited software package. A total of 17,264 single-nucleotide polymorphisms (SNPs) associated with different salinity stress tolerance related traits were found. Twenty-three candidate SNPs related to salinity stress-related traits were selected. Final key SNPs were selected based on the r² value with nearby SNPs in a linkage disequilibrium (LD) block. Twenty putative candidate genes surrounding SNPs, A10_95330133 and D10_61258588, associated with leaf relative water content, RWC_150, and leaf fresh weight, FW_150, were identified, respectively. We further validated the expression patterns of twelve candidate genes with qRT-PCR, which revealed different expression levels in salt-tolerant and salt-sensitive genotypes. The results of our GWAS provide useful knowledge about the genetic control of salt tolerance at the seedling stage, which could assist in elucidating the genetic and molecular mechanisms of salinity stress tolerance in cotton plants.

Comparative population genomics identified genomic regions and candidate genes associated with fruit domestication traits in peach

Crop evolution is a long-term process involving selection by natural evolutionary forces and anthropogenic influences; however, the genetic mechanisms underlying the domestication and improvement of fruit crops have not been well studied to date. Here, we performed a population structure analysis in peach (Prunus persica) based on the genome-wide resequencing of 418 accessions and confirmed the presence of an obvious domestication event during evolution. We identified 132 and 106 selective sweeps associated with domestication and improvement, respectively. Analysis of their tissue-specific expression patterns indicated that the up-regulation of selection genes during domestication occurred mostly in fruit and seeds as opposed to other organs. However, during the improvement stage, more up-regulated selection genes were identified in leaves and seeds than in the other organs. Genome-wide association studies (GWAS) using 4.24 million single nucleotide polymorphisms (SNPs) revealed 171 loci associated with 26 fruit domestication traits. Among these loci, three candidate genes were highly associated with fruit weight and the sorbitol and catechin content in fruit. We demonstrated that as the allele frequency of the SNPs associated with high polyphenol composition decreased during peach evolution, alleles associated with high sugar content increased significantly. This indicates that there is genetic potential for the breeding of more nutritious fruit with enhanced bioactive polyphenols without disturbing a harmonious sugar and acid balance by crossing with wild species. This study also describes the development of the genomic resources necessary for evolutionary research in peach and provides the large-scale characterization of key agronomic traits in this crop species.

High-throughput sequencing data and the impact of plant gene annotation quality

The use of draft genomes of different species and re-sequencing of accessions and populations are now common tools for plant biology research. The de novo assembled draft genomes make it possible to identify pivotal divergence points in the plant lineage and provide an opportunity to investigate the genomic basis and timing of biological innovations by inferring orthologs between species. Furthermore, re-sequencing facilitates the mapping and subsequent molecular characterization of causative loci for traits, such as those for plant stress tolerance and development. In both cases high-quality gene annotation-the identification of protein-coding regions, gene promoters, and 5'- and 3'-untranslated regions-is critical for investigation of gene function. Annotations are constantly improving but automated gene annotations still require manual curation and experimental validation. This is particularly important for genes with large introns, genes located in regions rich with transposable elements or repeats, large gene families, and segmentally duplicated genes. In this opinion paper, we highlight the impact of annotation quality on evolutionary analyses, genome-wide association studies, and the identification of orthologous genes in plants. Furthermore, we predict that incorporating accurate information from manual curation into databases will dramatically improve the performance of automated gene predictors.

Genome-wide association multi-locus and multi-variate linear mixed models reveal two linked loci with major effects on partial resistance of apricot to bacterial canker

BACKGROUND

Diseases caused by Pseudomonas syringae (Ps) are recognized as the most damaging factors in fruit trees with a significant economic and sanitary impact on crops. Among them, bacterial canker of apricot is exceedingly difficult to control due to a lack of efficient prophylactic measures. Several sources of partial resistance have been identified among genetic resources but the underlying genetic pattern has not been elucidated thus far. In this study, we phenotyped bacterial canker susceptibility in an apricot core-collection of 73 accessions over 4 years by measuring canker and superficial browning lengths issued from artificial inoculations in the orchard. In order to investigate the genetic architecture of partial resistance, we performed a genome-wide association study using best linear unbiased predictors on genetic (G) and genetic x year (G × Y) interaction effects extracted from linear mixed models. Using a set of 63,236 single-nucleotide polymorphism markers genotyped in the germplasm over the whole genome, multi-locus and multi-variate mixed models aimed at mapping the resistance while controlling for relatedness between individuals.

RESULTS

We detected 11 significant associations over 7 candidate loci linked to disease resistance under the two most severe years. Colocalizations between G and G × Y terms indicated a modulation on allelic effect depending on environmental conditions. Among the candidate loci, two loci on chromosomes 5 and 6 had a high impact on both canker length and superficial browning, explaining 41 and 26% of the total phenotypic variance, respectively. We found unexpected long-range linkage disequilibrium (LD) between these two markers revealing an inter-chromosomal LD block linking the two underlying genes. This result supports the hypothesis of a co-adaptation effect due to selection through population demography. Candidate genes annotations suggest a functional pathway involving abscisic acid, a hormone mainly known for mediating abiotic stress responses but also reported as a potential factor in plant-pathogen interactions.

CONCLUSIONS

Our study contributed to the first detailed characterization of the genetic determinants of partial resistance to bacterial canker in a Rosaceae species. It provided tools for fruit tree breeding by identifying progenitors with favorable haplotypes and by providing major-effect markers for a marker-assisted selection strategy.

Genome-Wide Association Studies for Pasmo Resistance in Flax (Linum usitatissimum L.)

Pasmo is one of the most widespread diseases threatening flax production. To identify genetic regions associated with pasmo resistance (PR), a genome-wide association study was performed on 370 accessions from the flax core collection. Evaluation of pasmo severity was performed in the field from 2012 to 2016 in Morden, MB, Canada. Genotyping-by-sequencing has identified 258,873 single nucleotide polymorphisms (SNPs) distributed on all 15 flax chromosomes. Marker-trait associations were identified using ten different statistical models. A total of 692 unique quantitative trait nucleotides (QTNs) associated with 500 putative quantitative trait loci (QTL) were detected from six phenotypic PR datasets (five individual years and average across years). Different QTNs were identified with various statistical models and from individual PR datasets, indicative of the complementation between analytical methods and/or genotype × environment interactions of the QTL effects. The single-locus models tended to identify large-effect QTNs while the multi-loci models were able to detect QTNs with smaller effects. Among the putative QTL, 67 had large effects (3-23%), were stable across all datasets and explained 32-64% of the total variation for PR in the various datasets. Forty-five of these QTL spanned 85 resistance gene analogs including a large toll interleukin receptor, nucleotide-binding site, leucine-rich repeat (TNL) type gene cluster on chromosome 8. The number of QTL with positive-effect or favorite alleles (NPQTL) in accessions was significantly correlated with PR (R 2 = 0.55), suggesting that these QTL effects are mainly additive. NPQTL was also significantly associated with morphotype (R 2 = 0.52) and major QTL with positive effect alleles were present in the fiber type accessions. The 67 large effect QTL are suited for marker-assisted selection and the 500 QTL for effective genomic prediction in PR molecular breeding.

Genome-wide association study of berry-related traits in grape [Vitis vinifera L.] based on genotyping-by-sequencing markers

Deciphering the genetic control of grape berry traits is crucial for optimizing yield, fruit quality, and consumer acceptability. In this study, an association panel of 179 grape genotypes comprising a mixture of ancient cultivars, landraces, and modern varieties collected worldwide were genotyped with genotyping-by-sequencing using a genome-wide association approach based on 32,311 single-nucleotide polymorphism (SNP) markers. Genome-wide efficient mixed-model association was selected as the optimal statistical model based on the results of known control loci of grape berry color traits. Many of the associated SNPs identified in this study were in accordance with the previous QTL analyses using biparental mapping. The grape skin color locus was found to be associated with a mybA transcription factor on chromosome 2. Two strong and distinct association signals associated with berry development periods were found on chromosome 16. Most candidate genes of the interval were highlighted as receptor-like protein kinase. For berry weight, significant association loci were identified on chromosome 18, as previously known, and on chromosome 19 and chromosome 17, as newly mapped. Berry flesh texture was newly located on chromosome 16; candidate genes in the interval were related to calcium. Berry flavor was determined on chromosome 5. Genomic regions were further investigated to reveal candidate genes. In this work, we identified interesting genetic determinants of grape berry-related traits. The identification of the markers closely associated with these berry traits may be useful for grape molecular breeding.

Genome-wide association study of kernel moisture content at harvest stage in maize

Kernel moisture content at harvest stage (KMC) is an important factor affecting maize production, especially for mechanical harvesting. We investigated the genetic basis of KMC using an association panel comprising of 144 maize inbred lines that were phenotypically evaluated at two field trial locations. Significant positive or negative correlations were identified between KMC and a series of other agronomic traits, indicating that KMC is associated with other such traits. Combining phenotypic values and the Maize SNP3K Beadchip to perform a genome-wide association study revealed eight single nucleotide polymorphisms (SNPs) associated with KMC at P ≤ 0.001 using a mixed linear model (PCA+K). These significant SNPs could be converted into five quantitative trait loci (QTLs) distributed on chromosomes 1, 5, 8, and 9. Of these QTLs, three were colocalized with genomic regions previously reported. Based on the phenotypic values of the alleles corresponding to significant SNPs, the favorable alleles were mined. Eight maize inbred lines with low KMC and harboring favorable alleles were identified. These QTLs and elite maize inbred lines with low KMC will be useful in maize breeding.

An assessment of the performance of the logistic mixed model for analyzing binary traits in maize and sorghum diversity panels

The logistic mixed model (LMM) is well-suited for the genome-wide association study (GWAS) of binary agronomic traits because it can include fixed and random effects that account for spurious associations. The recent implementation of a computationally efficient model fitting and testing approach now makes it practical to use the LMM to search for markers associated with such binary traits on a genome-wide scale. Therefore, the purpose of this work was to assess the applicability of the LMM for GWAS in crop diversity panels. We dichotomized three publicly available quantitative traits in a maize diversity panel and two quantitative traits in a sorghum diversity panel, and them performed a GWAS using both the LMM and the unified mixed linear model (MLM) on these dichotomized traits. Our results suggest that the LMM is capable of identifying statistically significant marker-trait associations in the same genomic regions highlighted in previous studies, and this ability is consistent across both diversity panels. We also show how subpopulation structure in the maize diversity panel can underscore the LMM’s superior control for spurious associations compared to the unified MLM. These results suggest that the LMM is a viable model to use for the GWAS of binary traits in crop diversity panels and we therefore encourage its broader implementation in the agronomic research community.

Genome-Wide Association Study for Spot Blotch Resistance in Hard Winter Wheat

Spot blotch (SB) caused by Cochliobolus sativus (anamorph: Bipolaris sorokiniana) is an economically important disease of wheat worldwide. Under a severe epidemic condition, the disease can cause yield losses up to 70%. Previous approaches like bi-parental mapping for identifying SB resistant genes/QTLs exploited only a limited portion of the available genetic diversity with a lower capacity to detect polygenic traits, and had a lower marker density. In this study, we performed genome-wide association study (GWAS) for SB resistance in hard winter wheat association mapping panel (HWWAMP) of 294 genotypes. The HWWAMP was evaluated for response to B. sorokiniana (isolate SD40), and a range of reactions was observed with 10 resistant, 38 moderately resistant, 120 moderately resistant- moderately susceptible, 111 moderately susceptible, and 15 susceptible genotypes. GWAS using 15,590 high-quality SNPs and 294 genotypes we identified six QTLs (p = <0.001) on chromosomes 2D, 3A, 4A, 4B, 5A, and 7B that collectively explained 30% of the total variation for SB resistance. Highly associated SNPs were identified for all six QTLs, QSb.sdsu-2D.1 (SNP: Kukri_c31121_1460, R2 = 4%), QSb.sdsu-3A.1 (SNP: Excalibur_c46082_440, R2 = 4%), QSb.sdsu-4A.1 (SNP: IWA8475, R2 = 5.5%), QSb.sdsu-4B.1 (SNP: Excalibur_rep_c79414_306, R2 = 4%), QSb.sdsu-5A.1 (SNP: Kukri_rep_c104877_2166, R2 = 6%), and QSb.sdsu-7B.1 (SNP: TA005844-0160, R2 = 6%). Our study not only validates three (2D, 5A, and 7B) genomic regions identified in previous studies but also provides highly associated SNP markers for marker assisted selection. In addition, we identified three novel QTLs (QSb.sdsu-3A.1, QSb.sdsu-4A.1, and QSb.sdsu-4B.1) for SB resistance in wheat. Gene annotation analysis of the candidate regions identified nine NBS-LRR and 38 other plant defense-related protein families across multiple QTLs, and these could be used for fine mapping and further characterization of SB resistance in wheat. Comparative analysis with barley indicated the SB resistance locus on wheat chromosomes 2D, 3A, 5A, and 7B identified in our study are syntenic to the previously identified SB resistance locus on chromosomes 2H, 3H, 5H, and 7H in barley. The 10 highly resistant genotypes and SNP markers identified in our study could be very useful resources for breeding of SB resistance in wheat.

Genetic Basis of Variation in Rice Seed Storage Protein (Albumin, Globulin, Prolamin, and Glutelin) Content Revealed by Genome-Wide Association Analysis

Rice seed storage protein (SSP) is an important source of nutrition and energy. Understanding the genetic basis of SSP content and mining favorable alleles that control it will be helpful for breeding new improved cultivars. An association analysis for SSP content was performed to identify underlying genes using 527 diverse Oryza sativa accessions grown in two environments. We identified more than 107 associations for five different traits, including the contents of albumin (Alb), globulin (Glo), prolamin (Pro), glutelin (Glu), and total SSP (Total). A total of 28 associations were located at previously reported QTLs or intervals. A lead SNP sf0709447538, associated for Glu content in the indica subpopulation in 2015, was further validated in near isogenic lines NIL(Zhenshan97) and NIL(Delong208), and the Glu phenotype had significantly difference between two NILs. The association region could be target for map-based cloning of the candidate genes. There were 13 associations in regions close to grain-quality-related genes; five lead single nucleotide polymorphisms (SNPs) were located less than 20 kb upstream from grain-quality-related genes (PG5a, Wx, AGPS2a, RP6, and, RM1). Several starch-metabolism-related genes (AGPS2a, OsACS6, PUL, GBSSII, and ISA2) were also associated with SSP content. We identified favorable alleles of functional candidate genes, such as RP6, RM1, Wx, and other four candidate genes by haplotype analysis and expression pattern. Genotypes of RP6 and RM1 with higher Pro were not identified in japonica and exhibited much higher expression levels in indica group. The lead SNP sf0601764762, repeatedly detected for Alb content in 2 years in the whole association population, was located in the Wx locus that controls the synthesis of amylose. And Alb content was significantly and negatively correlated with amylose content and the level of 2.3 kb Wx pre-mRNA examined in this study. The associations or candidate genes identified would provide new insights into the genetic basis of SSP content that will help in developing rice cultivars with improved grain nutritional quality through marker-assisted breeding.

A Genome-Wide Association Study of Apple Quality and Scab Resistance

The apple ( × Borkh.) is an economically and culturally important crop grown worldwide. Growers of this long-lived perennial must produce fruit of adequate quality while also combatting abiotic and biotic stress. Traditional apple breeding can take up to 20 yr from initial cross to commercial release, but genomics-assisted breeding can help accelerate this process. To advance genomics-assisted breeding in apple, we performed genome-wide association studies (GWAS) and genomic prediction in a collection of 172 apple accessions by linking over 55,000 single nucleotide polymorphisms (SNPs) with 10 phenotypes collected over 2 yr. Genome-wide association studies revealed several known loci for skin color, harvest date and firmness at harvest. Several significant GWAS associations were detected for resistance to a major fungal pathogen, apple scab ( [Cke.] Wint.), but we demonstrate that these hits likely represent a single ancestral source. Using genomic prediction, we show that most phenotypes are sufficiently predictable using genome-wide SNPs to be candidates for genomic selection. Finally, we detect a signal for firmness retention after storage on chromosome 10 and show that it may not stem from variation in , a gene repeatedly identified in bi-parental mapping studies and widely believed to underlie a major QTL for firmness on chromosome 10. We provide evidence that this major QTL is more likely due to variation in a neighboring ethylene response factor (ERF) gene. The present study showcases the superior mapping resolution of GWAS compared to bi-parental linkage mapping by identifying a novel candidate gene underlying a well-studied, major QTL involved in apple firmness.

Genome-Wide Association Study for Spot Blotch Resistance in Hard Winter Wheat

Spot blotch (SB) caused by Cochliobolus sativus (anamorph: Bipolaris sorokiniana) is an economically important disease of wheat worldwide. Under a severe epidemic condition, the disease can cause yield losses up to 70%. Previous approaches like bi-parental mapping for identifying SB resistant genes/QTLs exploited only a limited portion of the available genetic diversity with a lower capacity to detect polygenic traits, and had a lower marker density. In this study, we performed genome-wide association study (GWAS) for SB resistance in hard winter wheat association mapping panel (HWWAMP) of 294 genotypes. The HWWAMP was evaluated for response to B. sorokiniana (isolate SD40), and a range of reactions was observed with 10 resistant, 38 moderately resistant, 120 moderately resistant- moderately susceptible, 111 moderately susceptible, and 15 susceptible genotypes. GWAS using 15,590 high-quality SNPs and 294 genotypes we identified six QTLs (p = <0.001) on chromosomes 2D, 3A, 4A, 4B, 5A, and 7B that collectively explained 30% of the total variation for SB resistance. Highly associated SNPs were identified for all six QTLs, QSb.sdsu-2D.1 (SNP: Kukri_c31121_1460, R² = 4%), QSb.sdsu-3A.1 (SNP: Excalibur_c46082_440, R² = 4%), QSb.sdsu-4A.1 (SNP: IWA8475, R² = 5.5%), QSb.sdsu-4B.1 (SNP: Excalibur_rep_c79414_306, R² = 4%), QSb.sdsu-5A.1 (SNP: Kukri_rep_c104877_2166, R² = 6%), and QSb.sdsu-7B.1 (SNP: TA005844-0160, R² = 6%). Our study not only validates three (2D, 5A, and 7B) genomic regions identified in previous studies but also provides highly associated SNP markers for marker assisted selection. In addition, we identified three novel QTLs (QSb.sdsu-3A.1, QSb.sdsu-4A.1, and QSb.sdsu-4B.1) for SB resistance in wheat. Gene annotation analysis of the candidate regions identified nine NBS-LRR and 38 other plant defense-related protein families across multiple QTLs, and these could be used for fine mapping and further characterization of SB resistance in wheat. Comparative analysis with barley indicated the SB resistance locus on wheat chromosomes 2D, 3A, 5A, and 7B identified in our study are syntenic to the previously identified SB resistance locus on chromosomes 2H, 3H, 5H, and 7H in barley. The 10 highly resistant genotypes and SNP markers identified in our study could be very useful resources for breeding of SB resistance in wheat.

Post genomics era for orchid research

Among 300,000 species in angiosperms, Orchidaceae containing 30,000 species is one of the largest families. Almost every habitats on earth have orchid plants successfully colonized, and it indicates that orchids are among the plants with significant ecological and evolutionary importance. So far, four orchid genomes have been sequenced, including Phalaenopsis equestris, Dendrobium catenatum, Dendrobium officinale, and Apostaceae shengen. Here, we review the current progress and the direction of orchid research in the post genomics era. These include the orchid genome evolution, genome mapping (genome-wide association analysis, genetic map, physical map), comparative genomics (especially receptor-like kinase and terpene synthase), secondary metabolomics, and genome editing.

Understanding and engineering plant form

A plant's form is an important determinant of its fitness and economic value. Here, we review strategies for producing plants with altered forms. Historically, the process of changing a plant's form has been slow in agriculture, requiring iterative rounds of growth and selection. We discuss modern techniques for identifying genes involved in the development of plant form and tools that will be needed to effectively design and engineer plants with altered forms. Synthetic genetic circuits are highlighted for their potential to generate novel plant forms. We emphasize understanding development as a prerequisite to engineering and discuss the potential role of computer models in translating knowledge about single genes or pathways into a more comprehensive understanding of development.

Nitrogen use efficiency in crops: lessons from Arabidopsis and rice

Application of chemical fertilizers, especially nitrogen (N), to crops has increased dramatically in the last half century and therefore developing crop varieties with improved N use efficiency (NUE) is urgent for sustainable agriculture. N utilization procedures generally can be divided into uptake, transport, and assimilation. Transporters for nitrate or ammonium acquisition and enzymes for assimilation are among the essential components determining NUE, and many transcription factors also play a pivotal role in regulating N use-associated genes, thereby contributing to NUE. Although some efforts in improving NUE have been made in various plants, the regulatory mechanisms underlying NUE are still elusive, and NUE improvement in crop breeding is very limited. In this review, the crucial components involved in N utilization and the candidates with the potential for NUE improvement in dicot Arabidopsis and monocot rice are summarized. In addition, strategies based on new techniques which can be used for dissecting regulatory mechanisms of NUE and also the possible ways in which NUE can be improved in crops are discussed.

What can genome-wide association studies tell us about the evolutionary forces maintaining genetic variation for quantitative traits?

Contents 21 I. 21 II. 22 III. 24 IV. 25 V. 29 30 References 30 SUMMARY: Understanding the evolutionary forces that shape genetic variation within species has long been a goal of evolutionary biology. Integrating data for the genetic architecture of traits from genome-wide association mapping studies (GWAS) along with the development of new population genetic methods for identifying selection in sequence data may allow us to evaluate the roles of mutation-selection balance and balancing selection in shaping genetic variation at various scales. Here, we review the theoretical predictions for genetic architecture and additional signals of selection on genomic sequence for the loci that affect traits. Next, we review how plant GWAS have tested for the signatures of various selective scenarios. Limited evidence to date suggests that within-population variation is maintained primarily by mutation-selection balance while variation across the landscape is the result of local adaptation. However, there are a number of inherent biases in these interpretations. We highlight these challenges and suggest ways forward to further understanding of the maintenance of variation.

A Guide to Genome-Wide Association Mapping in Plants

Genome-wide association studies (GWAS) have developed into a valuable approach for identifying the genetic basis of phenotypic variation. In this article, we provide an overview of the design, analysis, and interpretation of GWAS. First, we present results from simulations that explore key elements of experimental design as well as considerations for collecting the relevant genomic and phenotypic data. Next, we outline current statistical methods and tools used for GWA analyses and discuss the inclusion of covariates to account for population structure and the interpretation of results. Given that many false positive associations will occur in any GWA analysis, we highlight strategies for prioritizing GWA candidates for further statistical and empirical validation. While focused on plants, the material we cover is also applicable to other systems. © 2017 by John Wiley & Sons, Inc.

Genetic architecture of plant stress resistance: multi-trait genome-wide association mapping

Plants are exposed to combinations of various biotic and abiotic stresses, but stress responses are usually investigated for single stresses only. Here, we investigated the genetic architecture underlying plant responses to 11 single stresses and several of their combinations by phenotyping 350 Arabidopsis thaliana accessions. A set of 214 000 single nucleotide polymorphisms (SNPs) was screened for marker-trait associations in genome-wide association (GWA) analyses using tailored multi-trait mixed models. Stress responses that share phytohormonal signaling pathways also share genetic architecture underlying these responses. After removing the effects of general robustness, for the 30 most significant SNPs, average quantitative trait locus (QTL) effect sizes were larger for dual stresses than for single stresses. Plants appear to deploy broad-spectrum defensive mechanisms influencing multiple traits in response to combined stresses. Association analyses identified QTLs with contrasting and with similar responses to biotic vs abiotic stresses, and below-ground vs above-ground stresses. Our approach allowed for an unprecedented comprehensive genetic analysis of how plants deal with a wide spectrum of stress conditions.

Breeding approaches and genomics technologies to increase crop yield under low-temperature stress

Improved knowledge about plant cold stress tolerance offered by modern omics technologies will greatly inform future crop improvement strategies that aim to breed cultivars yielding substantially high under low-temperature conditions. Alarmingly rising temperature extremities present a substantial impediment to the projected target of 70% more food production by 2050. Low-temperature (LT) stress severely constrains crop production worldwide, thereby demanding an urgent yet sustainable solution. Considerable research progress has been achieved on this front. Here, we review the crucial cellular and metabolic alterations in plants that follow LT stress along with the signal transduction and the regulatory network describing the plant cold tolerance. The significance of plant genetic resources to expand the genetic base of breeding programmes with regard to cold tolerance is highlighted. Also, the genetic architecture of cold tolerance trait as elucidated by conventional QTL mapping and genome-wide association mapping is described. Further, global expression profiling techniques including RNA-Seq along with diverse omics platforms are briefly discussed to better understand the underlying mechanism and prioritize the candidate gene (s) for downstream applications. These latest additions to breeders' toolbox hold immense potential to support plant breeding schemes that seek development of LT-tolerant cultivars. High-yielding cultivars endowed with greater cold tolerance are urgently required to sustain the crop yield under conditions severely challenged by low-temperature.

Medical Subject Heading (MeSH) annotations illuminate maize genetics and evolution

BACKGROUND

High-density marker panels and/or whole-genome sequencing, coupled with advanced phenotyping pipelines and sophisticated statistical methods, have dramatically increased our ability to generate lists of candidate genes or regions that are putatively associated with phenotypes or processes of interest. However, the speed with which we can validate genes, or even make reasonable biological interpretations about the principles underlying them, has not kept pace. A promising approach that runs parallel to explicitly validating individual genes is analyzing a set of genes together and assessing the biological similarities among them. This is often achieved via gene ontology analysis, a powerful tool that involves evaluating publicly available gene annotations. However, additional resources such as Medical Subject Headings (MeSH) can also be used to evaluate sets of genes to make biological interpretations.

RESULTS

In this manuscript, we describe utilizing MeSH terms to make biological interpretations in maize. MeSH terms are assigned to PubMed-indexed manuscripts by the National Library of Medicine, and can be directly mapped to genes to develop gene annotations. Once mapped, these terms can be evaluated for enrichment in sets of genes or similarity between gene sets to provide biological insights. Here, we implement MeSH analyses in five maize datasets to demonstrate how MeSH can be leveraged by the maize and broader crop-genomics community.

CONCLUSIONS

We demonstrate that MeSH terms can be effectively leveraged to generate hypotheses and make biological interpretations in maize, and we provide a pipeline that enables the use of MeSH terms in other plant species.

Genotypes, Networks, Phenotypes: Moving Toward Plant Systems Genetics

One of the central goals in biology is to understand how and how much of the phenotype of an organism is encoded in its genome. Although many genes that are crucial for organismal processes have been identified, much less is known about the genetic bases underlying quantitative phenotypic differences in natural populations. We discuss the fundamental gap between the large body of knowledge generated over the past decades by experimental genetics in the laboratory and what is needed to understand the genotype-to-phenotype problem on a broader scale. We argue that systems genetics, a combination of systems biology and the study of natural variation using quantitative genetics, will help to address this problem. We present major advances in these two mostly disconnected areas that have increased our understanding of the developmental processes of flowering time control and root growth. We conclude by illustrating and discussing the efforts that have been made toward systems genetics specifically in plants.

Genome-Wide Association Study Reveals the Genetic Basis of Stalk Cell Wall Components in Maize

Lignin, cellulose and hemicellulose are the three main components of the plant cell wall and can impact stalk quality by affecting cell wall structure and strength. In this study, we evaluated the lignin (LIG), cellulose (CEL) and hemicellulose (HC) contents in maize using an association mapping panel that included 368 inbred lines in seven environments. A genome-wide association study using approximately 0.56 million SNPs with a minor allele frequency of 0.05 identified 22, 18 and 24 loci significantly associated with LIG, CEL and HC at P < 1.0×10⁻⁴, respectively. The allelic variation of each significant association contributed 4 to 7% of the phenotypic variation. Candidate genes identified by GWAS mainly encode enzymes involved in cell wall metabolism, transcription factors, protein kinase and protein related to other biological processes. Among the association signals, six candidate genes had pleiotropic effects on lignin and cellulose content. These results provide valuable information for better understanding the genetic basis of stalk cell wall components in maize.