Nitrogen uptake, assimilation and remobilization in plants: challenges for sustainable and productive agriculture

BACKGROUND

Productive agriculture needs a large amount of expensive nitrogenous fertilizers. Improving nitrogen use efficiency (NUE) of crop plants is thus of key importance. NUE definitions differ depending on whether plants are cultivated to produce biomass or grain yields. However, for most plant species, NUE mainly depends on how plants extract inorganic nitrogen from the soil, assimilate nitrate and ammonium, and recycle organic nitrogen. Efforts have been made to study the genetic basis as well as the biochemical and enzymatic mechanisms involved in nitrogen uptake, assimilation, and remobilization in crops and model plants. The detection of the limiting factors that could be manipulated to increase NUE is the major goal of such research.

SCOPE

An overall examination of the physiological, metabolic, and genetic aspects of nitrogen uptake, assimilation and remobilization is presented in this review. The enzymes and regulatory processes manipulated to improve NUE components are presented. Results obtained from natural variation and quantitative trait loci studies are also discussed.

CONCLUSIONS

This review presents the complexity of NUE and supports the idea that the integration of the numerous data coming from transcriptome studies, functional genomics, quantitative genetics, ecophysiology and soil science into explanatory models of whole-plant behaviour will be promising.

Plasma proteomic associations with genetics and health in the UK Biobank

The Pharma Proteomics Project is a precompetitive biopharmaceutical consortium characterizing the plasma proteomic profiles of 54,219 UK Biobank participants. Here we provide a detailed summary of this initiative, including technical and biological validations, insights into proteomic disease signatures, and prediction modelling for various demographic and health indicators. We present comprehensive protein quantitative trait locus (pQTL) mapping of 2,923 proteins that identifies 14,287 primary genetic associations, of which 81% are previously undescribed, alongside ancestry-specific pQTL mapping in non-European individuals. The study provides an updated characterization of the genetic architecture of the plasma proteome, contextualized with projected pQTL discovery rates as sample sizes and proteomic assay coverages increase over time. We offer extensive insights into trans pQTLs across multiple biological domains, highlight genetic influences on ligand-receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks, and illustrate long-range epistatic effects of ABO blood group and FUT2 secretor status on proteins with gastrointestinal tissue-enriched expression. We demonstrate the utility of these data for drug discovery by extending the genetic proxied effects of protein targets, such as PCSK9, on additional endpoints, and disentangle specific genes and proteins perturbed at loci associated with COVID-19 susceptibility. This public-private partnership provides the scientific community with an open-access proteomics resource of considerable breadth and depth to help to elucidate the biological mechanisms underlying proteo-genomic discoveries and accelerate the development of biomarkers, predictive models and therapeutics1.

Importance of epistasis as the genetic basis of heterosis in an elite rice hybrid

The genetic basis of heterosis was investigated in an elite rice hybrid by using a molecular linkage map with 150 segregating loci covering the entire rice genome. Data for yield and three traits that were components of yield were collected over 2 years from replicated field trials of 250 F(2:3) families. Genotypic variations explained from about 50% to more than 80% of the total variation. Interactions between genotypes and years were small compared with the main effects. A total of 32 quantitative trait loci (QTLs) were detected for the four traits; 12 were observed in both years and the remaining 20 were detected in only one year. Overdominance was observed for most of the QTLs for yield and also for a few QTLs for the component traits. Correlations between marker heterozygosity and trait expression were low, indicating that the overall heterozygosity made little contribution to heterosis. Digenic interactions, including additive by additive, additive by dominance, and dominance by dominance, were frequent and widespread in this population. The interactions involved large numbers of marker loci, most of which individually were not detectable on single-locus basis; many interactions among loci were detected in both years. The results provide strong evidence that epistasis plays a major role as the genetic basis of heterosis.

Review. The strength and genetic basis of reproductive isolating barriers in flowering plants

Speciation is characterized by the evolution of reproductive isolation between two groups of organisms. Understanding the process of speciation requires the quantification of barriers to reproductive isolation, dissection of the genetic mechanisms that contribute to those barriers and determination of the forces driving the evolution of those barriers. Through a comprehensive analysis involving 19 pairs of plant taxa, we assessed the strength and patterns of asymmetry of multiple prezygotic and postzygotic reproductive isolating barriers. We then reviewed contemporary knowledge of the genetic architecture of reproductive isolation and the relative role of chromosomal and genic factors in intrinsic postzygotic isolation. On average, we found that prezygotic isolation is approximately twice as strong as postzygotic isolation, and that postmating barriers are approximately three times more asymmetrical in their action than premating barriers. Barriers involve a variable number of loci, and chromosomal rearrangements may have a limited direct role in reproductive isolation in plants. Future research should aim to understand the relationship between particular genetic loci and the magnitude of their effect on reproductive isolation in nature, the geographical scale at which plant speciation occurs, and the role of different evolutionary forces in the speciation process.

Molecular genetic dissection of quantitative trait loci regulating rice grain size

Grain size is one of the most important factors determining rice yield. As a quantitative trait, grain size is predominantly and tightly controlled by genetic factors. Several quantitative trait loci (QTLs) for grain size have been molecularly identified and characterized. These QTLs may act in independent genetic pathways and, along with other identified genes for grain size, are mainly involved in the signaling pathways mediated by proteasomal degradation, phytohormones, and G proteins to regulate cell proliferation and cell elongation. Many of these QTLs and genes have been strongly selected for enhanced rice productivity during domestication and breeding. These findings have paved new ways for understanding the molecular basis of grain size and have substantial implications for genetic improvement of crops.

Progress in research and development on hybrid rice: a super-domesticate in China

BACKGROUND

China has been successful in breeding hybrid rice strains, but is now facing challenges to develop new hybrids with high-yielding potential, better grain quality, and tolerance to biotic and abiotic stresses. This paper reviews the most significant advances in hybrid rice breeding in China, and presents a recent study on fine-mapping quantitative trait loci (QTLs) for yield traits.

SCOPE

By exploiting new types of male sterility, hybrid rice production in China has become more diversified. The use of inter-subspecies crosses has made an additional contribution to broadening the genetic diversity of hybrid rice and played an important role in the breeding of super rice hybrids in China. With the development and application of indica-inclined and japonica-inclined parental lines, new rice hybrids with super high-yielding potential have been developed and are being grown on a large scale. DNA markers for subspecies differentiation have been identified and applied, and marker-assisted selection performed for the development of restorer lines carrying disease resistance genes. The genetic basis of heterosis in highly heterotic hybrids has been studied, but data from these studies are insufficient to draw sound conclusions. In a QTL study using stepwise residual heterozygous lines, two linked intervals harbouring QTLs for yield traits were resolved, one of which was delimited to a 125-kb region.

CONCLUSIONS

Advances in rice genomic research have shed new light on the genetic study and germplasm utilization in rice. Molecular marker-assisted selection is a powerful tool to increase breeding efficiency, but much work remains to be done before this technique can be extended from major genes to QTLs.

The selfing syndrome: a model for studying the genetic and evolutionary basis of morphological adaptation in plants

BACKGROUND

In angiosperm evolution, autogamously selfing lineages have been derived from outbreeding ancestors multiple times, and this transition is regarded as one of the most common evolutionary tendencies in flowering plants. In most cases, it is accompanied by a characteristic set of morphological and functional changes to the flowers, together termed the selfing syndrome. Two major areas that have changed during evolution of the selfing syndrome are sex allocation to male vs. female function and flower morphology, in particular flower (mainly petal) size and the distance between anthers and stigma.

SCOPE

A rich body of theoretical, taxonomic, ecological and genetic studies have addressed the evolutionary modification of these two trait complexes during or after the transition to selfing. Here, we review our current knowledge about the genetics and evolution of the selfing syndrome.

CONCLUSIONS

We argue that because of its frequent parallel evolution, the selfing syndrome represents an ideal model for addressing basic questions about morphological evolution and adaptation in flowering plants, but that realizing this potential will require the molecular identification of more of the causal genes underlying relevant trait variation.

The distribution of the effects of genes affecting quantitative traits in livestock

Meta-analysis of information from quantitative trait loci (QTL) mapping experiments was used to derive distributions of the effects of genes affecting quantitative traits. The two limitations of such information, that QTL effects as reported include experimental error, and that mapping experiments can only detect QTL above a certain size, were accounted for. Data from pig and dairy mapping experiments were used. Gamma distributions of QTL effects were fitted with maximum likelihood. The derived distributions were moderately leptokurtic, consistent with many genes of small effect and few of large effect. Seventeen percent and 35% of the leading QTL explained 90% of the genetic variance for the dairy and pig distributions respectively. The number of segregating genes affecting a quantitative trait in dairy populations was predicted assuming genes affecting a quantitative trait were neutral with respect to fitness. Between 50 and 100 genes were predicted, depending on the effective population size assumed. As data for the analysis included no QTL of small effect, the ability to estimate the number of QTL of small effect must inevitably be weak. It may be that there are more QTL of small effect than predicted by our gamma distributions. Nevertheless, the distributions have important implications for QTL mapping experiments and Marker Assisted Selection (MAS). Powerful mapping experiments, able to detect QTL of 0.1sigma(p), will be required to detect enough QTL to explain 90% the genetic variance for a quantitative trait.

CRISPR for Crop Improvement: An Update Review

The availability of genome sequences for several crops and advances in genome editing approaches has opened up possibilities to breed for almost any given desirable trait. Advancements in genome editing technologies such as zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) has made it possible for molecular biologists to more precisely target any gene of interest. However, these methodologies are expensive and time-consuming as they involve complicated steps that require protein engineering. Unlike first-generation genome editing tools, CRISPR/Cas9 genome editing involves simple designing and cloning methods, with the same Cas9 being potentially available for use with different guide RNAs targeting multiple sites in the genome. After proof-of-concept demonstrations in crop plants involving the primary CRISPR-Cas9 module, several modified Cas9 cassettes have been utilized in crop plants for improving target specificity and reducing off-target cleavage (e.g., Nmcas9, Sacas9, and Stcas9). Further, the availability of Cas9 enzymes from additional bacterial species has made available options to enhance specificity and efficiency of gene editing methodologies. This review summarizes the options available to plant biotechnologists to bring about crop improvement using CRISPR/Cas9 based genome editing tools and also presents studies where CRISPR/Cas9 has been used for enhancing biotic and abiotic stress tolerance. Application of these techniques will result in the development of non-genetically modified (Non-GMO) crops with the desired trait that can contribute to increased yield potential under biotic and abiotic stress conditions.

Genome-environment associations in sorghum landraces predict adaptive traits

Improving environmental adaptation in crops is essential for food security under global change, but phenotyping adaptive traits remains a major bottleneck. If associations between single-nucleotide polymorphism (SNP) alleles and environment of origin in crop landraces reflect adaptation, then these could be used to predict phenotypic variation for adaptive traits. We tested this proposition in the global food crop Sorghum bicolor, characterizing 1943 georeferenced landraces at 404,627 SNPs and quantifying allelic associations with bioclimatic and soil gradients. Environment explained a substantial portion of SNP variation, independent of geographical distance, and genic SNPs were enriched for environmental associations. Further, environment-associated SNPs predicted genotype-by-environment interactions under experimental drought stress and aluminum toxicity. Our results suggest that genomic signatures of environmental adaptation may be useful for crop improvement, enhancing germplasm identification and marker-assisted selection. Together, genome-environment associations and phenotypic analyses may reveal the basis of environmental adaptation.

Food security: the challenge of increasing wheat yield and the importance of not compromising food safety

Current wheat yield and consumption is considered in the context of the historical development of wheat, from early domestication through to modern plant breeding, the Green Revolution and wheat's place as one of the world's most productive and important crops in the 21st Century. The need for further improvement in the yield potential of wheat in order to meet current and impending challenges is discussed, including rising consumption and the demand for grain for fuel as well as food. Research on the complex genetics underlying wheat yield is described, including the identification of quantitative trait loci and individual genes, and the prospects of biotechnology playing a role in wheat improvement in the future are discussed. The challenge of preparing wheat to meet the problems of drought, high temperature and increasing carbon dioxide concentration that are anticipated to come about as a result of climate change is also reviewed. Wheat yield must be increased while not compromising food safety, and the emerging problem of processing contaminants is reviewed, focussing in particular on acrylamide, a contaminant that forms from free asparagine and reducing sugars during high temperature cooking and processing. Wheat breeders are strongly encouraged to consider the contaminant issue when breeding for yield.

Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression

Recent developments in stem cell biology have enabled the study of cell fate decisions in early human development that are impossible to study in vivo. However, understanding how development varies across individuals and, in particular, the influence of common genetic variants during this process has not been characterised. Here, we exploit human iPS cell lines from 125 donors, a pooled experimental design, and single-cell RNA-sequencing to study population variation of endoderm differentiation. We identify molecular markers that are predictive of differentiation efficiency of individual lines, and utilise heterogeneity in the genetic background across individuals to map hundreds of expression quantitative trait loci that influence expression dynamically during differentiation and across cellular contexts.

Database of cattle candidate genes and genetic markers for milk production and mastitis

A cattle database of candidate genes and genetic markers for milk production and mastitis has been developed to provide an integrated research tool incorporating different types of information supporting a genomic approach to study lactation, udder development and health. The database contains 943 genes and genetic markers involved in mammary gland development and function, representing candidates for further functional studies. The candidate loci were drawn on a genetic map to reveal positional overlaps. For identification of candidate loci, data from seven different research approaches were exploited: (i) gene knockouts or transgenes in mice that result in specific phenotypes associated with mammary gland (143 loci); (ii) cattle QTL for milk production (344) and mastitis related traits (71); (iii) loci with sequence variations that show specific allele-phenotype interactions associated with milk production (24) or mastitis (10) in cattle; (iv) genes with expression profiles associated with milk production (207) or mastitis (107) in cattle or mouse; (v) cattle milk protein genes that exist in different genetic variants (9); (vi) miRNAs expressed in bovine mammary gland (32) and (vii) epigenetically regulated cattle genes associated with mammary gland function (1). Fourty-four genes found by multiple independent analyses were suggested as the most promising candidates and were further in silico analysed for expression levels in lactating mammary gland, genetic variability and top biological functions in functional networks. A miRNA target search for mammary gland expressed miRNAs identified 359 putative binding sites in 3'UTRs of candidate genes.

Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease

Identifying methylation quantitative trait loci (meQTLs) and integrating them with disease-associated variants from genome-wide association studies (GWAS) may illuminate functional mechanisms underlying genetic variant-disease associations. Here, we perform GWAS of >415 thousand CpG methylation sites in whole blood from 4170 individuals and map 4.7 million cis- and 630 thousand trans-meQTL variants targeting >120 thousand CpGs. Independent replication is performed in 1347 participants from two studies. By linking cis-meQTL variants with GWAS results for cardiovascular disease (CVD) traits, we identify 92 putatively causal CpGs for CVD traits by Mendelian randomization analysis. Further integrating gene expression data reveals evidence of cis CpG-transcript pairs causally linked to CVD. In addition, we identify 22 trans-meQTL hotspots each targeting more than 30 CpGs and find that trans-meQTL hotspots appear to act in cis on expression of nearby transcriptional regulatory genes. Our findings provide a powerful meQTL resource and shed light on DNA methylation involvement in human diseases.

Landrace Germplasm for Improving Yield and Abiotic Stress Adaptation

Plant landraces represent heterogeneous, local adaptations of domesticated species, and thereby provide genetic resources that meet current and new challenges for farming in stressful environments. These local ecotypes can show variable phenology and low-to-moderate edible yield, but are often highly nutritious. The main contributions of landraces to plant breeding have been traits for more efficient nutrient uptake and utilization, as well as useful genes for adaptation to stressful environments such as water stress, salinity, and high temperatures. We propose that a systematic landrace evaluation may define patterns of diversity, which will facilitate identifying alleles for enhancing yield and abiotic stress adaptation, thus raising the productivity and stability of staple crops in vulnerable environments.

Domestication of plants in the Americas: insights from Mendelian and molecular genetics

BACKGROUND

Plant domestication occurred independently in four different regions of the Americas. In general, different species were domesticated in each area, though a few species were domesticated independently in more than one area. The changes resulting from human selection conform to the familiar domestication syndrome, though different traits making up this syndrome, for example loss of dispersal, are achieved by different routes in crops belonging to different families.

GENETIC AND MOLECULAR ANALYSES OF DOMESTICATION

Understanding of the genetic control of elements of the domestication syndrome is improving as a result of the development of saturated linkage maps for major crops, identification and mapping of quantitative trait loci, cloning and sequencing of genes or parts of genes, and discoveries of widespread orthologies in genes and linkage groups within and between families. As the modes of action of the genes involved in domestication and the metabolic pathways leading to particular phenotypes become better understood, it should be possible to determine whether similar phenotypes have similar underlying genetic controls, or whether human selection in genetically related but independently domesticated taxa has fixed different mutants with similar phenotypic effects.

CONCLUSIONS

Such studies will permit more critical analysis of possible examples of multiple domestications and of the origin(s) and spread of distinctive variants within crops. They also offer the possibility of improving existing crops, not only major food staples but also minor crops that are potential export crops for developing countries or alternative crops for marginal areas.

Quantitative trait loci markers derived from whole genome sequence data increases the reliability of genomic prediction

This study investigated the effect on the reliability of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k single nucleotide polymorphism (SNP) array data. The extra markers were selected with the aim of augmenting the custom low-density Illumina BovineLD SNP chip (San Diego, CA) used in the Nordic countries. The single-marker analysis was done breed-wise on all 16 index traits included in the breeding goals for Nordic Holstein, Danish Jersey, and Nordic Red cattle plus the total merit index itself. Depending on the trait's economic weight, 15, 10, or 5 quantitative trait loci (QTL) were selected per trait per breed and 3 to 5 markers were selected to tag each QTL. After removing duplicate markers (same marker selected for more than one trait or breed) and filtering for high pairwise linkage disequilibrium and assaying performance on the array, a total of 1,623 QTL markers were selected for inclusion on the custom chip. Genomic prediction analyses were performed for Nordic and French Holstein and Nordic Red animals using either a genomic BLUP or a Bayesian variable selection model. When using the genomic BLUP model including the QTL markers in the analysis, reliability was increased by up to 4 percentage points for production traits in Nordic Holstein animals, up to 3 percentage points for Nordic Reds, and up to 5 percentage points for French Holstein. Smaller gains of up to 1 percentage point was observed for mastitis, but only a 0.5 percentage point increase was seen for fertility. When using a Bayesian model accuracies were generally higher with only 54k data compared with the genomic BLUP approach, but increases in reliability were relatively smaller when QTL markers were included. Results from this study indicate that the reliability of genomic prediction can be increased by including markers significant in genome-wide association studies on whole genome sequence data alongside the 54k SNP set.

The Genetics of Nitrogen Use Efficiency in Crop Plants

In the past 50 years, the application of synthetic nitrogen (N) fertilizer to farmland resulted in a dramatic increase in crop yields but with considerable negative impacts on the environment. New solutions are therefore needed to simultaneously increase yields while maintaining, or preferably decreasing, applied N to maximize the nitrogen use efficiency (NUE) of crops. In this review, we outline the definition of NUE, the selection and development of NUE crops, and the factors that interact with NUE. In particular, we emphasize the challenges of developing crop plants with enhanced NUE, using more classical genetic approaches based on utilizing existing allelic variation for NUE traits. The challenges of phenotyping, mapping quantitative trait loci (QTLs), and selecting candidate genes for NUE improvement are described. In addition, we highlight the importance of different factors that lead to changes in the NUE components of nitrogen uptake efficiency (NUpE) and nitrogen utilization efficiency (NUtE).

Comparing Different Statistical Models and Multiple Testing Corrections for Association Mapping in Soybean and Maize

Association mapping (AM) is a powerful tool for fine mapping complex trait variation down to nucleotide sequences by exploiting historical recombination events. A major problem in AM is controlling false positives that can arise from population structure and family relatedness. False positives are often controlled by incorporating covariates for structure and kinship in mixed linear models (MLM). These MLM-based methods are single locus models and can introduce false negatives due to over fitting of the model. In this study, eight different statistical models, ranging from single-locus to multilocus, were compared for AM for three traits differing in heritability in two crop species: soybean (Glycine max L.) and maize (Zea mays L.). Soybean and maize were chosen, in part, due to their highly differentiated rate of linkage disequilibrium (LD) decay, which can influence false positive and false negative rates. The fixed and random model circulating probability unification (FarmCPU) performed better than other models based on an analysis of Q-Q plots and on the identification of the known number of quantitative trait loci (QTLs) in a simulated data set. These results indicate that the FarmCPU controls both false positives and false negatives. Six qualitative traits in soybean with known published genomic positions were also used to compare these models, and results indicated that the FarmCPU consistently identified a single highly significant SNP closest to these known published genes. Multiple comparison adjustments (Bonferroni, false discovery rate, and positive false discovery rate) were compared for these models using a simulated trait having 60% heritability and 20 QTLs. Multiple comparison adjustments were overly conservative for MLM, CMLM, ECMLM, and MLMM and did not find any significant markers; in contrast, ANOVA, GLM, and SUPER models found an excessive number of markers, far more than 20 QTLs. The FarmCPU model, using less conservative methods (false discovery rate, and positive false discovery rate) identified 10 QTLs, which was closer to the simulated number of QTLs than the number found by other models.

EPISTASIS AS A SOURCE OF INCREASED ADDITIVE GENETIC VARIANCE AT POPULATION BOTTLENECKS

The role of epistasis in evolution and speciation has remained controversial. We use a new parameterization of physiological epistasis to examine the effects of epistasis on levels of additive genetic variance during a population bottleneck. We found that all forms of epistasis increase average additive genetic variance in finite populations derived from initial populations with intermediate allele frequencies. Average additive variance continues to increase over many generations, especially at larger population sizes (N = 32 to 64). Additive-by-additive epistasis is the most potent source of additive genetic variance in this situation, whereas dominance-by-dominance epistasis contributes smaller amounts of additive genetic variance. With additive-by-dominance epistasis, additive genetic variance decreases at a relatively high rate immediately after a population bottleneck, rebounding to higher levels after several generations. Empirical examples of epistasis for murine adult body weight based on measured genotypes are provided illustrating the varying effects of epistasis on additive genetic variance during population bottlenecks.

Circadian Clock Genes Universally Control Key Agricultural Traits

Circadian clocks are endogenous timers that enable plants to synchronize biological processes with daily and seasonal environmental conditions in order to allocate resources during the most beneficial times of day and year. The circadian clock regulates a number of central plant activities, including growth, development, and reproduction, primarily through controlling a substantial proportion of transcriptional activity and protein function. This review examines the roles that alleles of circadian clock genes have played in domestication and improvement of crop plants. The focus here is on three groups of circadian clock genes essential to clock function in Arabidopsis thaliana: PSEUDO-RESPONSE REGULATORs, GIGANTEA, and the evening complex genes early flowering 3, early flowering 4, and lux arrhythmo. homologous genes from each group underlie quantitative trait loci that have beneficial influences on key agricultural traits, especially flowering time but also yield, biomass, and biennial growth habit. Emerging insights into circadian clock regulation of other fundamental plant processes, including responses to abiotic and biotic stresses, are discussed to highlight promising avenues for further crop improvement.

Synergistic insights into human health from aptamer- and antibody-based proteomic profiling

Affinity-based proteomics has enabled scalable quantification of thousands of protein targets in blood enhancing biomarker discovery, understanding of disease mechanisms, and genetic evaluation of drug targets in humans through protein quantitative trait loci (pQTLs). Here, we integrate two partly complementary techniques-the aptamer-based SomaScan^® v4 assay and the antibody-based Olink assays-to systematically assess phenotypic consequences of hundreds of pQTLs discovered for 871 protein targets across both platforms. We create a genetically anchored cross-platform proteome-phenome network comprising 547 protein-phenotype connections, 36.3% of which were only seen with one of the two platforms suggesting that both techniques capture distinct aspects of protein biology. We further highlight discordance of genetically predicted effect directions between assays, such as for PILRA and Alzheimer's disease. Our results showcase the synergistic nature of these technologies to better understand and identify disease mechanisms and provide a benchmark for future cross-platform discoveries.

Quantitative Resistance to Plant Pathogens in Pyramiding Strategies for Durable Crop Protection

Quantitative resistance has gained interest in plant breeding for pathogen control in low-input cropping systems. Although quantitative resistance frequently has only a partial effect and is difficult to select, it is considered more durable than major resistance (R) genes. With the exponential development of molecular markers over the past 20 years, resistance QTL have been more accurately detected and better integrated into breeding strategies for resistant varieties with increased potential for durability. This review summarizes current knowledge on the genetic inheritance, molecular basis, and durability of quantitative resistance. Based on this knowledge, we discuss how strategies that combine major R genes and QTL in crops can maintain the effectiveness of plant resistance to pathogens. Combining resistance QTL with complementary modes of action appears to be an interesting strategy for breeding effective and potentially durable resistance. Combining quantitative resistance with major R genes has proven to be a valuable approach for extending the effectiveness of major genes. In the plant genomics era, improved tools and methods are becoming available to better integrate quantitative resistance into breeding strategies. Nevertheless, optimal combinations of resistance loci will still have to be identified to preserve resistance effectiveness over time for durable crop protection.

Metabolic GWAS-based dissection of genetic bases underlying the diversity of plant metabolism

Plants have served as sources providing humans with metabolites for food and nutrition, biomaterials for living, and treatment for pain and disease. Plants produce a huge array of metabolites, with an immense diversity at both the population and individual levels. Dissection of the genetic bases for metabolic diversity has attracted increasing research attention. The concept of genome-wide association study (GWAS) was extended to studies on the diversity of plant metabolome that benefitted from the development of mass-spectrometry-based analytical systems and genome sequencing technologies. Metabolic genome-wide association study (mGWAS) is one of the most powerful tools for global identification of genetic determinants for diversity of plant metabolism. Recently, mGWAS has been performed for various species with continuous improvements, providing deeper insights into the genetic bases of metabolic diversity. In this review, we discuss fully the achievements to date and remaining challenges that are associated with both mGWAS and mGWAS-based multi-dimensional analysis. We begin with a summary of GWAS and its development based on statistical methods and populations. As variation in targeted traits is essential for GWAS, we review metabolic diversity and its rise at both the population and individual levels. Subsequently, the application of mGWAS for plants and its corresponding achievements are fully discussed. We address the current knowledge on mGWAS-based multi-dimensional analysis and emerging insights into the diversity of metabolism.

Genome-wide association studies of metabolites in Finnish men identify disease-relevant loci

Few studies have explored the impact of rare variants (minor allele frequency < 1%) on highly heritable plasma metabolites identified in metabolomic screens. The Finnish population provides an ideal opportunity for such explorations, given the multiple bottlenecks and expansions that have shaped its history, and the enrichment for many otherwise rare alleles that has resulted. Here, we report genetic associations for 1391 plasma metabolites in 6136 men from the late-settlement region of Finland. We identify 303 novel association signals, more than one third at variants rare or enriched in Finns. Many of these signals identify genes not previously implicated in metabolite genome-wide association studies and suggest mechanisms for diseases and disease-related traits.