Development and Genetic Characterization of an Advanced Backcross-Nested Association Mapping (AB-NAM) Population of Wild × Cultivated Barley

Joint linkage and association analysis identifies genomic regions and candidate genes for yield-related traits in wheat

KEY MESSAGE

Twenty-six QTLs associated with yield-related traits in wheat were identified through joint linkage and association analysis, with TraesCS5A03G0002500 being selected as a candidate gene for QGl.caas-5A.1. As a major staple crop worldwide, continuously increasing wheat yield is crucial for ensuring food security. Wheat yield is influenced by multiple traits, and elucidating the genetic basis of yield-related traits lays a foundation for future gene cloning and molecular mechanism studies. In this study, a recombinant inbred line (RIL) population derived from 292 lines of Hengguan 35/Zhoumai 18 was genotyped with the Affymetrix wheat 660 K SNP array. Combined with the phenotype of the RIL population in 13 environments, linkage analysis of six yield-related traits including plant height, grain number per spike, thousand-grain weight, grain length, grain width, and grain thickness was conducted. A total of 262 quantitative trait locus (QTLs) (logarithm of odds [LOD] > 3) were identified across 21 chromosomes, in which 50 QTLs were repeatedly detected in more than three environments. Numerous QTLs harbored cloned genes and overlapped with those reported in previous studies. Subsequently, joint analysis of genome-wide association study (GWAS) data from the advanced backcross-nested association mapping plus inter-crossed (AB-NAMIC) population and QTLs identified in the RIL population revealed 26 overlapping genomic regions. Notably, the QGl.caas-5A.1 associated with grain length on chromosome 5A was detected in both the RIL and AB-NAMIC populations, and TraesCS5A03G0002500 was selected as a candidate gene. A kompetitive allele-specific PCR (KASP) marker based on a variant [A/G] in TraesCS5A03G0002500 was developed and validated in a natural population containing 350 accessions. Taken together, these results provide valuable information for fine mapping and cloning of yield-related wheat genes in the future.

Barley2035: A decadal vision for barley research and breeding

Barley (Hordeum vulgare ssp. vulgare) is one of the oldest founder crops in human civilization and has been widely dispersed across the globe to support human society as a livestock feed and a raw material for the brewing industries. Since the early half of the 20th century, it has been used for innovative research on cytogenetics, biochemistry, and genetics, facilitated by its mode of reproduction through self-pollination and its true diploid status, which have contributed to the accumulation of numerous germplasm and mutant resources. In the era of molecular genomics and biology, a multitude of barley genes and their related regulatory mechanisms have been identified and functionally validated, providing a paradigm for equivalent studies in other Triticeae crops. This review highlights important advances on barley research over the past decade, focusing mainly on genomics and genomics-assisted germplasm exploration, genetic dissection of developmental and adaptation-related traits, and the complex dynamics of yield and quality formation. In the coming decade, the prospect of integrating these innovations in barley research and breeding shows great promise. Barley is proposed as a reference Triticeae crop for the discovery and functional validation of new genes and the dissection of their molecular mechanisms. The application of precise genome editing as well as genomic prediction and selection, further enhanced by artificial intelligence-based tools and applications, is expected to promote barley improvement to efficiently meet the evolving global demands for this important crop.

The auxin efflux carrier PIN1a regulates vascular patterning in cereal roots

Barley (Hordeum vulgare) is an important global cereal crop and a model in genetic studies. Despite advances in characterising barley genomic resources, few mutant studies have identified genes controlling root architecture and anatomy, which plays a critical role in capturing soil resources. Our phenotypic screening of a TILLING mutant collection identified line TM5992 exhibiting a short-root phenotype compared with wild-type (WT) Morex background. Outcrossing TM5992 with barley variety Proctor and subsequent SNP array-based bulk segregant analysis, fine mapped the mutation to a cM scale. Exome sequencing pinpointed a mutation in the candidate gene HvPIN1a, further confirming this by analysing independent mutant alleles. Detailed analysis of root growth and anatomy in Hvpin1a mutant alleles exhibited a slower growth rate, shorter apical meristem and striking vascular patterning defects compared to WT. Expression and mutant analyses of PIN1 members in the closely related cereal brachypodium (Brachypodium distachyon) revealed that BdPIN1a and BdPIN1b were redundantly expressed in root vascular tissues but only Bdpin1a mutant allele displayed root vascular defects similar to Hvpin1a. We conclude that barley PIN1 genes have sub-functionalised in cereals, compared to Arabidopsis (Arabidopsis thaliana), where PIN1a sequences control root vascular patterning.

Identification of Quantitative Trait Loci Associated with Plant Adaptation Traits Using Nested Association Mapping Population

This study evaluated 290 recombinant inbred lines (RILs) of the nested association mapping (NAM) population from the UK. The population derived from 24 families, where a common parent was "Paragon," one of the UK's spring wheat cultivar standards. All genotypes were tested in two regions of Kazakhstan at the Kazakh Research Institute of Agriculture and Plant Industry (KRIAPI, Almaty region, Southeast Kazakhstan, 2019-2022 years) and Alexandr Barayev Scientific-Production Center for Grain Farming (SPCGF, Shortandy, Akmola region, Northern Kazakhstan, 2019-2022 years). The studied traits consisted of plant adaptation-related traits, including heading date (HD, days), seed maturation date (SMD, days), plant height (PH, cm), and peduncle length (PL, cm). In addition, the yield per m2 was analyzed in both regions. Based on a field evaluation of the population in northern and southeastern Kazakhstan and using 10,448 polymorphic SNP (single-nucleotide polymorphism) markers, the genome-wide association study (GWAS) allowed for detecting 74 QTLs in four studied agronomic traits (HD, SMD, PH, and PL). The literature survey suggested that 16 of the 74 QTLs identified in our study had also been detected in previous QTL mapping studies and GWASs for all studied traits. The results will be used for further studies related to the adaptation and productivity of wheat in breeding projects for higher grain productivity.

A platform for whole-genome speed introgression from Aegilops tauschii to wheat for breeding future crops

Breeding new and sustainable crop cultivars of high yields and desirable traits has been a major challenge for ensuring food security for the growing global human population. For polyploid crops such as wheat, introducing genetic variation from wild relatives of its subgenomes is a key strategy to improve the quality of their breeding pools. Over the past decades, considerable progress has been made in speed breeding, genome sequencing, high-throughput phenotyping and genomics-assisted breeding, which now allows us to realize whole-genome introgression from wild relatives to modern crops. Here, we present a standardized protocol to rapidly introgress the entire genome of Aegilops tauschii, the progenitor of the D subgenome of bread wheat, into elite wheat backgrounds. This protocol integrates multiple modern high-throughput technologies and includes three major phases: development of synthetic octaploid wheat, generation of hexaploid A. tauschii-wheat introgression lines (A-WIs) and homozygosis of the generated A-WIs. Our approach readily generates stable introgression lines in 2 y, thus greatly accelerating the generation of A-WIs and the introduction of desirable genes from A. tauschii to wheat cultivars. These A-WIs are valuable for wheat-breeding programs and functional gene discovery. The current protocol can be easily modified and used for introgressing the genomes of wild relatives to other polyploid crops.

UDP-glucosyltransferase HvUGT13248 confers type II resistance to Fusarium graminearum in barley

Fusarium head blight (FHB) of barley (Hordeum vulgare) causes yield losses and accumulation of trichothecene mycotoxins (e.g. deoxynivalenol [DON]) in grains. Glucosylation of DON to the nontoxic DON-3-O-glucoside (D3G) is catalyzed by UDP-glucosyltransferases (UGTs), such as barley UGT13248. We explored the natural diversity of UGT13248 in 496 barley accessions and showed that all carried potential functional alleles of UGT13248, as no genotypes showed strongly increased seedling sensitivity to DON. From a TILLING population, we identified 2 mutant alleles (T368I and H369Y) that, based on protein modeling, likely affect the UDP-glucose binding of UGT13248. In DON feeding experiments, DON-to-D3G conversion was strongly reduced in spikes of these mutants compared to controls, and plants overexpressing UGT13248 showed increased resistance to DON and increased DON-to-D3G conversion. Moreover, field-grown plants carrying the T368I or H369Y mutations inoculated with Fusarium graminearum showed increased FHB disease severity and reduced D3G production. Barley is generally considered to have type II resistance that limits the spread of F. graminearum from the infected spikelet to adjacent spikelets. Point inoculation experiments with F. graminearum showed increased infection spread in T368I and H369Y across the spike compared to wild type, while overexpression plants showed decreased spread of FHB symptoms. Confocal microscopy revealed that F. graminearum spread to distant rachis nodes in T368I and H369Y mutants but was arrested at the rachis node of the inoculated spikelet in wild-type plants. Taken together, our data reveal that UGT13248 confers type II resistance to FHB in barley via conjugation of DON to D3G.

Genome-wide association study as a powerful tool for dissecting competitive traits in legumes

Legumes are extremely valuable because of their high protein content and several other nutritional components. The major challenge lies in maintaining the quantity and quality of protein and other nutritional compounds in view of climate change conditions. The global need for plant-based proteins has increased the demand for seeds with a high protein content that includes essential amino acids. Genome-wide association studies (GWAS) have evolved as a standard approach in agricultural genetics for examining such intricate characters. Recent development in machine learning methods shows promising applications for dimensionality reduction, which is a major challenge in GWAS. With the advancement in biotechnology, sequencing, and bioinformatics tools, estimation of linkage disequilibrium (LD) based associations between a genome-wide collection of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits has become accessible. The markers from GWAS could be utilized for genomic selection (GS) to predict superior lines by calculating genomic estimated breeding values (GEBVs). For prediction accuracy, an assortment of statistical models could be utilized, such as ridge regression best linear unbiased prediction (rrBLUP), genomic best linear unbiased predictor (gBLUP), Bayesian, and random forest (RF). Both naturally diverse germplasm panels and family-based breeding populations can be used for association mapping based on the nature of the breeding system (inbred or outbred) in the plant species. MAGIC, MCILs, RIAILs, NAM, and ROAM are being used for association mapping in several crops. Several modifications of NAM, such as doubled haploid NAM (DH-NAM), backcross NAM (BC-NAM), and advanced backcross NAM (AB-NAM), have also been used in crops like rice, wheat, maize, barley mustard, etc. for reliable marker-trait associations (MTAs), phenotyping accuracy is equally important as genotyping. Highthroughput genotyping, phenomics, and computational techniques have advanced during the past few years, making it possible to explore such enormous datasets. Each population has unique virtues and flaws at the genomics and phenomics levels, which will be covered in more detail in this review study. The current investigation includes utilizing elite breeding lines as association mapping population, optimizing the choice of GWAS selection, population size, and hurdles in phenotyping, and statistical methods which will analyze competitive traits in legume breeding.

Fast integration and accumulation of beneficial breeding alleles through an AB-NAMIC strategy in wheat

Wheat (Triticum aestivum) is among the most important staple crops for safeguarding the food security of the growing world population. To bridge the gap between genebank diversity and breeding programs, we developed an advanced backcross-nested association mapping plus inter-crossed population (AB-NAMIC) by crossing three popular wheat cultivars as recurrent founders to 20 germplasm lines from a mini core collection. Selective backcrossing combined with selection against undesirable traits and extensive crossing within and between sub-populations created new opportunities to detect unknown genes and increase the frequency of beneficial alleles in the AB-NAMIC population. We performed phenotyping of 590 AB-NAMIC lines and a natural panel of 476 cultivars for six consecutive growing seasons and genotyped these 1066 lines with a 660K SNP array. Genome-wide association studies of both panels for plant development and yield traits demonstrated improved power to detect rare alleles and loci with medium genetic effects in AB-NAMIC. Notably, genome-wide association studies in AB-NAMIC detected the candidate gene TaSWEET6-7B (TraesCS7B03G1216700), which has high homology to the rice SWEET6b gene and exerts strong effects on adaptation and yield traits. The commercial release of two derived AB-NAMIC lines attests to its direct applicability in wheat improvement. Valuable information on genome-wide association study mapping, candidate genes, and their haplotypes for breeding traits are available through WheatGAB. Our research provides an excellent framework for fast-tracking exploration and accumulation of beneficial alleles stored in genebanks.

Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers' traditional knowledge

In the smallholder, low-input farming systems widespread in sub-Saharan Africa, farmers select and propagate crop varieties based on their traditional knowledge and experience. A data-driven integration of their knowledge into breeding pipelines may support the sustainable intensification of local farming. Here, we combine genomics with participatory research to tap into traditional knowledge in smallholder farming systems, using durum wheat (Triticum durum Desf.) in Ethiopia as a case study. We developed and genotyped a large multiparental population, called the Ethiopian NAM (EtNAM), that recombines an elite international breeding line with Ethiopian traditional varieties maintained by local farmers. A total of 1,200 EtNAM lines were evaluated for agronomic performance and farmers' appreciation in three locations in Ethiopia, finding that women and men farmers could skillfully identify the worth of wheat genotypes and their potential for local adaptation. We then trained a genomic selection (GS) model using farmer appreciation scores and found that its prediction accuracy over grain yield (GY) was higher than that of a benchmark GS model trained on GY. Finally, we used forward genetics approaches to identify marker-trait associations for agronomic traits and farmer appreciation scores. We produced genetic maps for individual EtNAM families and used them to support the characterization of genomic loci of breeding relevance with pleiotropic effects on phenology, yield, and farmer preference. Our data show that farmers' traditional knowledge can be integrated in genomics-driven breeding to support the selection of best allelic combinations for local adaptation.

Sources of Bacterial Leaf Streak Resistance Identified in a Diverse Collection of Barley Germplasm

Bacterial leaf streak (BLS) is a sporadic yet damaging disease of cereals that is growing in importance across the Upper Midwest production region. In barley (Hordeum vulgare ssp. vulgare), this disease is caused primarily by the bacterium Xanthomonas translucens pv. translucens. Accessions resistant to BLS have been reported in past studies, but few have been rigorously validated in the field. To identify accessions carrying diverse resistance alleles to BLS, a largescale germplasm screening study was undertaken against strain CIX95 of X. translucens pv. translucens in St. Paul and Crookston, Minnesota, in 2020 and 2021. The germplasm screened was diverse and included adapted breeding lines from two improvement programs, two landrace panels (one global and one from Ethiopia/Eritrea), introgression lines from wild barley (H. vulgare ssp. spontaneum) in the genetic background of barley cultivar 'Rasmusson', and an assemblage of accessions previously reported to carry BLS resistance. Of the 2,094 accessions evaluated in this study, 32 (1.5%) exhibited a consistently high level of resistance across locations and years and had heading dates similar to standard cultivars grown in the region. Accessions resistant to BLS were identified from all germplasm panels tested, providing genetically diverse sources for barley improvement programs focused on breeding for resistance to this important bacterial disease.

Evaluating Introgression Sorghum Germplasm Selected at the Population Level While Exploring Genomic Resources as a Screening Method

To exploit the novel genetic diversity residing in tropical sorghum germplasm, an expansive backcross nested-association mapping (BC-NAM) resource was developed in which novel genetic diversity was introgressed into elite inbreds. A major limitation of exploiting this type of genetic resource in hybrid improvement programs is the required evaluation in hybrid combination of the vast number of BC-NAM populations and lines. To address this, the utility of genomic information was evaluated to predict the hybrid performance of BC-NAM populations. Two agronomically elite BC-NAM populations were chosen for evaluation in which elite inbred RTx436 was the recurrent parent. Each BC₁F₃ line was evaluated in hybrid combination with an elite tester in two locations with phenotypes of grain yield, plant height, and days to anthesis collected on all test cross hybrids. Lines from both populations were found to outperform their recurrent parent. Efforts to utilize genetic distance based on genotyping-by-sequence (GBS) as a predictive tool for hybrid performance was ineffective. However, utilizing genomic prediction models using additive and dominance GBLUP kernels to screen germplasm appeared to be an effective method to eliminate inferior-performing lines that will not be useful in a hybrid breeding program.

Identification of two new QTLs of maize (Zea mays L.) underlying kernel row number using the HNAU-NAM1 population

BACKGROUND

Maize kernel row number (KRN) is one of the most important yield traits and has changed greatly during maize domestication and selection. Elucidating the genetic basis of KRN will be helpful to improve grain yield in maize.

RESULTS

Here, we measured KRN in four environments using a nested association mapping (NAM) population named HNAU-NAM1 with 1,617 recombinant inbred lines (RILs) that were derived from 12 maize inbred lines with a common parent, GEMS41. Then, five consensus quantitative trait loci (QTLs) distributing on four chromosomes were identified in at least three environments along with the best linear unbiased prediction (BLUP) values by the joint linkage mapping (JLM) method. These QTLs were further validated by the separate linkage mapping (SLM) and genome-wide association study (GWAS) methods. Three KRN genes cloned through the QTL assay were found in three of the five consensus QTLs, including qKRN1.1, qKRN2.1 and qKRN4.1. Two new QTLs of KRN, qKRN4.2 and qKRN9.1, were also identified. On the basis of public RNA-seq and genome annotation data, five genes highly expressed in ear tissue were considered candidate genes contributing to KRN.

CONCLUSIONS

This study carried out a comprehensive analysis of the genetic architecture of KRN by using a new NAM population under multiple environments. The present results provide solid information for understanding the genetic components underlying KRN and candidate genes in qKRN4.2 and qKRN9.1. Single-nucleotide polymorphisms (SNPs) closely linked to qKRN4.2 and qKRN9.1 could be used to improve inbred yield during molecular breeding in maize.

High-throughput characterization, correlation, and mapping of leaf photosynthetic and functional traits in the soybean (Glycine max) nested association mapping population

Photosynthesis is a key target to improve crop production in many species including soybean [Glycine max (L.) Merr.]. A challenge is that phenotyping photosynthetic traits by traditional approaches is slow and destructive. There is proof-of-concept for leaf hyperspectral reflectance as a rapid method to model photosynthetic traits. However, the crucial step of demonstrating that hyperspectral approaches can be used to advance understanding of the genetic architecture of photosynthetic traits is untested. To address this challenge, we used full-range (500-2,400 nm) leaf reflectance spectroscopy to build partial least squares regression models to estimate leaf traits, including the rate-limiting processes of photosynthesis, maximum Rubisco carboxylation rate, and maximum electron transport. In total, 11 models were produced from a diverse population of soybean sampled over multiple field seasons to estimate photosynthetic parameters, chlorophyll content, leaf carbon and leaf nitrogen percentage, and specific leaf area (with R2 from 0.56 to 0.96 and root mean square error approximately <10% of the range of calibration data). We explore the utility of these models by applying them to the soybean nested association mapping population, which showed variability in photosynthetic and leaf traits. Genetic mapping provided insights into the underlying genetic architecture of photosynthetic traits and potential improvement in soybean. Notably, the maximum Rubisco carboxylation rate mapped to a region of chromosome 19 containing genes encoding multiple small subunits of Rubisco. We also mapped the maximum electron transport rate to a region of chromosome 10 containing a fructose 1,6-bisphosphatase gene, encoding an important enzyme in the regeneration of ribulose 1,5-bisphosphate and the sucrose biosynthetic pathway. The estimated rate-limiting steps of photosynthesis were low or negatively correlated with yield suggesting that these traits are not influenced by the same genetic mechanisms and are not limiting yield in the soybean NAM population. Leaf carbon percentage, leaf nitrogen percentage, and specific leaf area showed strong correlations with yield and may be of interest in breeding programs as a proxy for yield. This work is among the first to use hyperspectral reflectance to model and map the genetic architecture of the rate-limiting steps of photosynthesis.

Genetic dissection of maize plant architecture using a novel nested association mapping population

The leaf angle (LA), plant height (PH), and ear height (EH) are key plant architectural traits influencing maize (Zea mays L.) yield. However, their genetic determinants have not yet been well-characterized. Here, we developed a maize advanced backcross-nested association mapping population in Henan Agricultural University (HNAU-NAM1) comprised of 1,625 BC₁ F₄ /BC₂ F₄ lines. These were obtained by crossing a diverse set of 12 representative inbred lines with the common GEMS41 line, which were then genotyped using the MaizeSNP9.4K array. Genetic diversity and phenotypic distribution analyses showed considerable levels of genetic variation. We obtained 18-88 quantitative trait loci (QTLs) associated with LA, PH, and EH by using three complementary mapping methods, named as separate linkage mapping, joint linkage mapping, and genome-wide association studies. Our analyses enabled the identification of ten QTL hot-spot regions associated with the three traits, which were distributed on nine different chromosomes. We further selected 13 major QTLs that were simultaneously detected by three methods and deduced the candidate genes, of which eight were not reported before. The newly constructed HNAU-NAM1 population in this study will further broaden our insights into understanding of genetic regulation of plant architecture, thus will help to improve maize yield and provide an invaluable resource for maize functional genomics and breeding research.

Nutritional improvement of cereal crops to combat hidden hunger during COVID-19 pandemic: Progress and prospects

COVID-19 has posed a severe challenge on food security by limiting access to food for the marginally placed population. While access to food is a challenge, access to nutritional food is a greater challenge to the population. The present-day foods are not sufficient to meet the nutritional requirements of the human body. In a pandemic condition, providing nutritious food to the population is imperative to ensure the health and well-being of humankind. Exploiting the existing biodiversity of crop species and deploying classical and modern tools to improve the nutritional potential of these species holds the key to addressing the above challenge. Breeding has been a classical tool of crop improvement that relied predominantly on genetic diversity. Collecting and conserving diverse germplasms and characterizing their diversity using molecular markers is essential to preserve diversity and use them in genetic improvement programs. These markers are also valuable for association mapping analyses to identify the genetic determinants of traits-of-interest in crop species. Association mapping identifies the quantitative trait loci (QTL) underlying the trait-of-interest by exploring marker-trait associations, and these QTLs can further be exploited for the genetic improvement of cultivated species through genomics-assisted breeding. Conventional breeding and genomics approaches are also being applied to develop biofortified cereal crops to reduce nutritional deficiencies in consumers. In this context, chapter explains the prerequisites for association mapping, population structure, genetic diversity, different approaches of performing association mapping to dissect nutritional traits, use the information for genomics-assisted breeding for nutrient-rich cereal crops, and application of genomics strategies in crop biofortification. These approaches will ensure food and nutrition security for all amidst the current COVID-19 crisis.

Reap the crop wild relatives for breeding future crops

Crop wild relatives (CWRs) have provided breeders with several 'game-changing' traits or genes that have boosted crop resilience and global agricultural production. Advances in breeding and genomics have accelerated the identification of valuable CWRs for use in crop improvement. The enhanced genetic diversity of breeding pools carrying optimum combinations of favorable alleles for targeted crop-growing regions is crucial to sustain genetic gain. In parallel, growing sequence information on wild genomes in combination with precise gene-editing tools provide a fast-track route to transform CWRs into ideal future crops. Data-informed germplasm collection and management strategies together with adequate policy support will be equally important to improve access to CWRs and their sustainable use to meet food and nutrition security targets.

Designing Future Crops: Genomics-Assisted Breeding Comes of Age

Over the past decade, genomics-assisted breeding (GAB) has been instrumental in harnessing the potential of modern genome resources and characterizing and exploiting allelic variation for germplasm enhancement and cultivar development. Sustaining GAB in the future (GAB 2.0) will rely upon a suite of new approaches that fast-track targeted manipulation of allelic variation for creating novel diversity and facilitate their rapid and efficient incorporation in crop improvement programs. Genomic breeding strategies that optimize crop genomes with accumulation of beneficial alleles and purging of deleterious alleles will be indispensable for designing future crops. In coming decades, GAB 2.0 is expected to play a crucial role in breeding more climate-smart crop cultivars with higher nutritional value in a cost-effective and timely manner.

Multiparental Population in Crops: Methods of Development and Dissection of Genetic Traits

Multiparental populations are located midway between association mapping that relies on germplasm collections and classic linkage analysis, based upon biparental populations. They provide several key advantages such as the possibility to include a higher number of alleles and increased level of recombination with respect to biparental populations, and more equilibrated allelic frequencies than association mapping panels. Moreover, in these populations new allele's combinations arise from recombination that may reveal transgressive phenotypes and make them a useful pre-breeding material. Here we describe the strategies for working with multiparental populations, focusing on nested association mapping populations (NAM) and multiparent advanced generation intercross populations (MAGIC). We provide details from the selection of founders, population development, and characterization to the statistical methods for genetic mapping and quantitative trait detection.

Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding

Crop populations derived from experimental crosses enable the genetic dissection of complex traits and support modern plant breeding. Among these, multi-parent populations now play a central role. By mixing and recombining the genomes of multiple founders, multi-parent populations combine many commonly sought beneficial properties of genetic mapping populations. For example, they have high power and resolution for mapping quantitative trait loci, high genetic diversity and minimal population structure. Many multi-parent populations have been constructed in crop species, and their inbred germplasm and associated phenotypic and genotypic data serve as enduring resources. Their utility has grown from being a tool for mapping quantitative trait loci to a means of providing germplasm for breeding programmes. Genomics approaches, including de novo genome assemblies and gene annotations for the population founders, have allowed the imputation of rich sequence information into the descendent population, expanding the breadth of research and breeding applications of multi-parent populations. Here, we report recent successes from crop multi-parent populations in crops. We also propose an ideal genotypic, phenotypic and germplasm 'package' that multi-parent populations should feature to optimise their use as powerful community resources for crop research, development and breeding.

Genomic interventions for sustainable agriculture

Agricultural production faces a Herculean challenge to feed the increasing global population. Food production systems need to deliver more with finite land and water resources while exerting the least negative influence on the ecosystem. The unpredictability of climate change and consequent changes in pests/pathogens dynamics aggravate the enormity of the challenge. Crop improvement has made significant contributions towards food security, and breeding climate-smart cultivars are considered the most sustainable way to accelerate food production. However, a fundamental change is needed in the conventional breeding framework in order to respond adequately to the growing food demands. Progress in genomics has provided new concepts and tools that hold promise to make plant breeding procedures more precise and efficient. For instance, reference genome assemblies in combination with germplasm sequencing delineate breeding targets that could contribute to securing future food supply. In this review, we highlight key breakthroughs in plant genome sequencing and explain how the presence of these genome resources in combination with gene editing techniques has revolutionized the procedures of trait discovery and manipulation. Adoption of new approaches such as speed breeding, genomic selection and haplotype-based breeding could overcome several limitations of conventional breeding. We advocate that strengthening varietal release and seed distribution systems will play a more determining role in delivering genetic gains at farmer's field. A holistic approach outlined here would be crucial to deliver steady stream of climate-smart crop cultivars for sustainable agriculture.

Genetic architecture of agronomic and quality traits in a nested association mapping population of spring wheat

Germplasm collections are rich sources of genetic variation to improve crops for many valuable traits. Nested association mapping (NAM) populations can overcome the limitations of genome-wide association studies (GWAS) in germplasm collections by reducing the effect of population structure. We exploited the genetic diversity of the USDA-ARS wheat (Triticum aestivum L.) core collection by developing the Spring Wheat Multiparent Introgression Population (SWMIP). To develop this population, twenty-five core parents were crossed and backcrossed to the Minnesota spring wheat cultivar RB07. The NAM population and 26 founder parents were genotyped using genotyping-by-sequencing and phenotyped for heading date, height, test weight, and grain protein content. After quality control, 20,312 markers with physical map positions were generated for 2,038 recombinant inbred lines (RILs). The number of RILs in each family varied between 58 and 96. Three GWAS models were utilized for quantitative trait loci (QTL) detection and accounted for known family stratification, genetic kinship, and both covariates. GWAS was performed on the whole population and also by bootstrap sampling of an equal number of RILs from each family. Greater power of QTL detection was achieved by treating families equally through bootstrapping. In total 16, 15, 12, and 13 marker-trait associations (MTAs) were identified for heading date, height, test weight, and grain protein content, respectively. Some of these MTAs were coincident with major genes known to control the traits, but others were novel and contributed by the wheat core parents. The SWMIP will be a valuable source of genetic variation for spring wheat breeding.

Sheathing the blade: Significant contribution of sheaths to daytime and nighttime gas exchange in a grass crop

Despite representing a sizeable fraction of the canopy, very little is known about leaf sheath gas exchange in grasses. Specifically, estimates of sheath stomatal conductance, transpiration and photosynthesis along with their responses to light, CO₂ and vapour pressure deficit (VPD) are unknown. Furthermore, the anatomical basis of these responses is poorly documented. Here, using barley as a model system, and combining leaf-level gas exchange, whole-plant gravimetric measurements, transpiration inhibitors, anatomical observations, and biophysical modelling, we found that sheath and blade stomatal conductance and transpiration were similar, especially at low light, in addition to being genotypically variable. Thanks to high abaxial stomata densities and surface areas nearly half those of the blades, sheaths accounted for up to 17% of the daily whole-plant water use, which -surprisingly- increased to 45% during the nighttime. Sheath photosynthesis was on average 17-25% that of the blade and was associated with lower water use efficiency. Finally, sheaths responded differently to the environment, exhibiting a lack of response to CO₂ but a strong sensitivity to VPD. Overall, these results suggest a key involvement of sheaths in feedback loops between canopy architecture and gas exchange with potentially significant implications on adaptation to current and future climates in grasses.

Exploration of the Yield Potential of Mesoamerican Wild Common Beans From Contrasting Eco-Geographic Regions by Nested Recombinant Inbred Populations

Genetic analyses and utilization of wild genetic variation for crop improvement in common bean (Phaseolus vulgaris L.) have been hampered by yield evaluation difficulties, identification of advantageous variation, and linkage drag. The lack of adaptation to cultivation conditions and the existence of highly structured populations make association mapping of diversity panels not optimal. Joint linkage mapping of nested populations avoids the later constraint, while populations crossed with a common domesticated parent allow the evaluation of wild variation within a more adapted background. Three domesticated by wild backcrossed-inbred-line populations (BC₁S₄) were developed using three wild accessions representing the full range of rainfall of the Mesoamerican wild bean distribution crossed to the elite drought tolerant domesticated parent SEA 5. These populations were evaluated under field conditions in three environments, two fully irrigated trials in two seasons and a simulated terminal drought in the second season. The goal was to test if these populations responded differently to drought stress and contained progenies with higher yield than SEA 5, not only under drought but also under water-watered conditions. Results revealed that the two populations derived from wild parents of the lower rainfall regions produced lines with higher yield compared to the domesticated parent in the three environments, i.e., both in the drought-stressed environment and in the well-watered treatments. Several progeny lines produced yields, which on average over the three environments were 20% higher than the SEA 5 yield. Twenty QTLs for yield were identified in 13 unique regions on eight of the 11 chromosomes of common bean. Five of these regions showed at least one wild allele that increased yield over the domesticated parent. The variation explained by these QTLs ranged from 0.6 to 5.4% of the total variation and the additive effects ranged from -164 to 277 kg ha^-1, with evidence suggesting allelic series for some QTLs. Our results underscore the potential of wild variation, especially from drought-stressed regions, for bean crop improvement as well the identification of regions for efficient marker-assisted introgression.

Genetic Architecture of Chilling Tolerance in Sorghum Dissected with a Nested Association Mapping Population

Dissecting the genetic architecture of stress tolerance in crops is critical to understand and improve adaptation. In temperate climates, early planting of chilling-tolerant varieties could provide longer growing seasons and drought escape, but chilling tolerance (<15°) is generally lacking in tropical-origin crops. Here we developed a nested association mapping (NAM) population to dissect the genetic architecture of early-season chilling tolerance in the tropical-origin cereal sorghum (Sorghum bicolor [L.] Moench). The NAM resource, developed from reference line BTx623 and three chilling-tolerant Chinese lines, is comprised of 771 recombinant inbred lines genotyped by sequencing at 43,320 single nucleotide polymorphisms. We phenotyped the NAM population for emergence, seedling vigor, and agronomic traits (>75,000 data points from ∼16,000 plots) in multi-environment field trials in Kansas under natural chilling stress (sown 30-45 days early) and normal growing conditions. Joint linkage mapping with early-planted field phenotypes revealed an oligogenic architecture, with 5-10 chilling tolerance loci explaining 20-41% of variation. Surprisingly, several of the major chilling tolerance loci co-localize precisely with the classical grain tannin (Tan1 and Tan2) and dwarfing genes (Dw1 and Dw3) that were under strong directional selection in the US during the 20^th century. These findings suggest that chilling sensitivity was inadvertently selected due to coinheritance with desired nontannin and dwarfing alleles. The characterization of genetic architecture with NAM reveals why past chilling tolerance breeding was stymied and provides a path for genomics-enabled breeding of chilling tolerance.

TeoNAM: A Nested Association Mapping Population for Domestication and Agronomic Trait Analysis in Maize

Recombinant inbred lines (RILs) are an important resource for mapping genes controlling complex traits in many species. While RIL populations have been developed for maize, a maize RIL population with multiple teosinte inbred lines as parents has been lacking. Here, we report a teosinte nested association mapping (TeoNAM) population, derived from crossing five teosinte inbreds to the maize inbred line W22. The resulting 1257 BC1S4 RILs were genotyped with 51,544 SNPs, providing a high-density genetic map with a length of 1540 cM. On average, each RIL is 15% homozygous teosinte and 8% heterozygous. We performed joint linkage mapping (JLM) and a genome-wide association study (GWAS) for 22 domestication and agronomic traits. A total of 255 QTL from JLM were identified, with many of these mapping near known genes or novel candidate genes. TeoNAM is a useful resource for QTL mapping for the discovery of novel allelic variation from teosinte. TeoNAM provides the first report that PROSTRATE GROWTH1, a rice domestication gene, is also a QTL associated with tillering in teosinte and maize. We detected multiple QTL for flowering time and other traits for which the teosinte allele contributes to a more maize-like phenotype. Such QTL could be valuable in maize improvement.

Development of a Multiparent Population for Genetic Mapping and Allele Discovery in Six-Row Barley

Germplasm collections hold valuable allelic diversity for crop improvement and genetic mapping of complex traits. To gain access to the genetic diversity within the USDA National Small Grain Collection (NSGC), we developed the Barley Recombinant Inbred Diverse Germplasm Population (BRIDG6), a six-row spring barley multiparent population (MPP) with 88 cultivated accessions crossed to a common parent (Rasmusson). The parents were randomly selected from a core subset of the NSGC that represents the genetic diversity of landrace and breeding accessions. In total, we generated 6160 F5 recombinant inbred lines (RILs), with an average of 69 and a range of 37-168 RILs per family, that were genotyped with 7773 SNPs, with an average of 3889 SNPs segregating per family. We detected 23 quantitative trait loci (QTL) associated with flowering time with five QTL found coincident with previously described flowering time genes. A major QTL was detected near the flowering time gene, HvPpd-H1 which affects photoperiod. Haplotype-based analysis of HvPpd-H1 identified private alleles to families of Asian origin conferring both positive and negative effects, providing the first observation of flowering time-related alleles private to Asian accessions. We evaluated several subsampling strategies to determine the effect of sample size on the power of QTL detection, and found that, for flowering time in barley, a sample size >50 families or 3000 individuals results in the highest power for QTL detection. This MPP will be useful for uncovering large and small effect QTL for traits of interest, and identifying and utilizing valuable alleles from the NSGC for barley improvement.

A large nested association mapping population for breeding and quantitative trait locus mapping in Ethiopian durum wheat

The Ethiopian plateau hosts thousands of durum wheat (Triticum turgidum subsp. durum) farmer varieties (FV) with high adaptability and breeding potential. To harness their unique allelic diversity, we produced a large nested association mapping (NAM) population intercrossing fifty Ethiopian FVs with an international elite durum wheat variety (Asassa). The Ethiopian NAM population (EtNAM) is composed of fifty interconnected bi-parental families, totalling 6280 recombinant inbred lines (RILs) that represent both a powerful quantitative trait loci (QTL) mapping tool, and a large pre-breeding panel. Here, we discuss the molecular and phenotypic diversity of the EtNAM founder lines, then we use an array featuring 13 000 single nucleotide polymorphisms (SNPs) to characterize a subset of 1200 EtNAM RILs from 12 families. Finally, we test the usefulness of the population by mapping phenology traits and plant height using a genome wide association (GWA) approach. EtNAM RILs showed high allelic variation and a genetic makeup combining genetic diversity from Ethiopian FVs with the international durum wheat allele pool. EtNAM SNP data were projected on the fully sequenced AB genome of wild emmer wheat, and were used to estimate pairwise linkage disequilibrium (LD) measures that reported an LD decay distance of 7.4 Mb on average, and balanced founder contributions across EtNAM families. GWA analyses identified 11 genomic loci individually affecting up to 3 days in flowering time and more than 1.6 cm in height. We argue that the EtNAM is a powerful tool to support the production of new durum wheat varieties targeting local and global agriculture.

Convergent Evolution of Effector Protease Recognition by Arabidopsis and Barley

The Pseudomonas syringae cysteine protease AvrPphB activates the Arabidopsis resistance protein RPS5 by cleaving a second host protein, PBS1. AvrPphB induces defense responses in other plant species, but the genes and mechanisms mediating AvrPphB recognition in those species have not been defined. Here, we show that AvrPphB induces defense responses in diverse barley cultivars. We also show that barley contains two PBS1 orthologs, that their products are cleaved by AvrPphB, and that the barley AvrPphB response maps to a single locus containing a nucleotide-binding leucine-rich repeat (NLR) gene, which we termed AvrPphB Response 1 (Pbr1). Transient coexpression of PBR1 with wild-type AvrPphB but not with a protease inactive mutant triggered defense responses, indicating that PBR1 detects AvrPphB protease activity. Additionally, PBR1 coimmunoprecipitated with barley and Nicotiana benthamiana PBS1 proteins, suggesting mechanistic similarity to detection by RPS5. Lastly, we determined that wheat cultivars also recognize AvrPphB protease activity and contain two putative Pbr1 orthologs. Phylogenetic analyses showed, however, that Pbr1 is not orthologous to RPS5. Our results indicate that the ability to recognize AvrPphB evolved convergently and imply that selection to guard PBS1-like proteins occurs across species. Also, these results suggest that PBS1-based decoys may be used to engineer protease effector recognition-based resistance in barley and wheat.

Barley yield formation under abiotic stress depends on the interplay between flowering time genes and environmental cues

Since the dawn of agriculture, crop yield has always been impaired through abiotic stresses. In a field trial across five locations worldwide, we tested three abiotic stresses, nitrogen deficiency, drought and salinity, using HEB-YIELD, a selected subset of the wild barley nested association mapping population HEB-25. We show that barley flowering time genes Ppd-H1, Sdw1, Vrn-H1 and Vrn-H3 exert pleiotropic effects on plant development and grain yield. Under field conditions, these effects are strongly influenced by environmental cues like day length and temperature. For example, in Al-Karak, Jordan, the day length-sensitive wild barley allele of Ppd-H1 was associated with an increase of grain yield by up to 30% compared to the insensitive elite barley allele. The observed yield increase is accompanied by pleiotropic effects of Ppd-H1 resulting in shorter life cycle, extended grain filling period and increased grain size. Our study indicates that the adequate timing of plant development is crucial to maximize yield formation under harsh environmental conditions. We provide evidence that wild barley alleles, introgressed into elite barley cultivars, can be utilized to support grain yield formation. The presented knowledge may be transferred to related crop species like wheat and rice securing the rising global food demand for cereals.

The complex genetic architecture of shoot growth natural variation in Arabidopsis thaliana

One of the main outcomes of quantitative genetics approaches to natural variation is to reveal the genetic architecture underlying the phenotypic space. Complex genetic architectures are described as including numerous loci (or alleles) with small-effect and/or low-frequency in the populations, interactions with the genetic background, environment or age. Linkage or association mapping strategies will be more or less sensitive to this complexity, so that we still have an unclear picture of its extent. By combining high-throughput phenotyping under two environmental conditions with classical QTL mapping approaches in multiple Arabidopsis thaliana segregating populations as well as advanced near isogenic lines construction and survey, we have attempted to improve our understanding of quantitative phenotypic variation. Integrative traits such as those related to vegetative growth used in this work (highlighting either cumulative growth, growth rate or morphology) all showed complex and dynamic genetic architecture with respect to the segregating population and condition. The more resolutive our mapping approach, the more complexity we uncover, with several instances of QTLs visible in near isogenic lines but not detected with the initial QTL mapping, indicating that our phenotyping accuracy was less limiting than the mapping resolution with respect to the underlying genetic architecture. In an ultimate approach to resolve this complexity, we intensified our phenotyping effort to target specifically a 3Mb-region known to segregate for a major quantitative trait gene, using a series of selected lines recombined every 100kb. We discovered that at least 3 other independent QTLs had remained hidden in this region, some with trait- or condition-specific effects, or opposite allelic effects. If we were to extrapolate the figures obtained on this specific region in this particular cross to the genome- and species-scale, we would predict hundreds of causative loci of detectable phenotypic effect controlling these growth-related phenotypes.

Domestication and crop evolution of wheat and barley: Genes, genomics, and future directions

Wheat and barley are two of the founder crops of the agricultural revolution that took place 10,000 years ago in the Fertile Crescent and both crops remain among the world's most important crops. Domestication of these crops from their wild ancestors required the evolution of traits useful to humans, rather than survival in their natural environment. Of these traits, grain retention and threshability, yield improvement, changes to photoperiod sensitivity and nutritional value are most pronounced between wild and domesticated forms. Knowledge about the geographical origins of these crops and the genes responsible for domestication traits largely pre-dates the era of next-generation sequencing, although sequencing will lead to new insights. Molecular markers were initially used to calculate distance (relatedness), genetic diversity and to generate genetic maps which were useful in cloning major domestication genes. Both crops are characterized by large, complex genomes which were long thought to be beyond the scope of whole-genome sequencing. However, advances in sequencing technologies have improved the state of genomic resources for both wheat and barley. The availability of reference genomes for wheat and some of its progenitors, as well as for barley, sets the stage for answering unresolved questions in domestication genomics of wheat and barley.

Exome Capture for Variant Discovery and Analysis in Barley

Exome capture is a reduced representation approach that selectively captures sequence from only the gene-bearing regions of a genome. It is based on probes targeted at these regions and, compared with whole genome shotgun sequencing, leads to a significant reduction in cost and data processing effort while still providing insights into the most relevant part of a genome. An exome capture array for barley was released in 2013 and this has opened the door to numerous studies that have put this technology to good use. In this chapter we detail the laboratory protocols required for enrichment and sequencing, and provide detailed step-by-step instructions for the bioinformatics analysis of the resulting data.

Genetic dissection of quantitative and qualitative traits using a minimum set of barley Recombinant Chromosome Substitution Lines

BACKGROUND

Exploring the natural occurring genetic variation of the wild barley genepool has become a major target of barley crop breeding programmes aiming to increase crop productivity and sustainability in global climate change scenarios. However this diversity remains unexploited and effective approaches are required to investigate the benefits that unadapted genomes could bring to crop improved resilience. In the present study, a set of Recombinant Chromosome Substitution Lines (RCSLs) derived from an elite barley cultivar 'Harrington' as the recurrent parent, and a wild barley accession from the Fertile Crescent 'Caesarea 26-24', as the donor parent (Matus et al. Genome 46:1010-23, 2003) have been utilised in field and controlled conditions to examine the contribution of wild barley genome as a source of novel allelic variation for the cultivated barley genepool.

METHODS

Twenty-eight RCSLs which were selected to represent the entire genome of the wild barley accession, were genotyped using the 9 K iSelect SNP markers (Comadran et al. Nat Genet 44:1388-92, 2012) and phenotyped for a range of morphological, developmental and agronomic traits in 2 years using a rain-out shelter with four replicates and three water treatments. Data were analysed for marker traits associations using a mixed model approach.

RESULTS

We identified lines that differ significantly from the elite parent for both qualitative and quantitative traits across growing seasons and water regimes. The detailed genotypic characterisation of the lines for over 1800 polymorphic SNP markers and the design of a mixed model analysis identified chromosomal regions associated with yield related traits where the wild barley allele had a positive response increasing grain weight and size. In addition, variation for qualitative characters, such as the presence of cuticle waxes on the developing spikes, was associated with the wild barley introgressions. Despite the coarse location of the QTLs, interesting candidate genes for the major marker-trait associations were identified using the recently released barley genome assembly.

CONCLUSION

This study has highlighted the role of exotic germplasm to contribute novel allelic variation by using an optimised experimental approach focused on an exotic genetic library. The results obtained constitute a step forward to the development of more tolerant and resilient varieties.

Genome-wide association of yield traits in a nested association mapping population of barley reveals new gene diversity for future breeding

To explore wild barley as a source of useful alleles for yield improvement in breeding, we have carried out a genome-wide association scan using the nested association mapping population HEB-25, which contains 25 diverse exotic barley genomes superimposed on an ~70% genetic background of cultivated barley. A total of 1420 HEB-25 lines were trialled for nine yield-related grain traits for 2 years in Germany and Scotland, with varying N fertilizer application. The phenotypic data were related to genotype scores for 5398 gene-based single nucleotide polymorphism (SNP) markers. A total of 96 quantitative trait locus (QTL) regions were identified across all measured traits, the majority of which co-localize with known major genes controlling flowering time (Ppd-H2, HvCEN, HvGI, VRN-H1, and VRN-H3) and spike morphology (VRS3, VRS1, VRS4, and INT-C) in barley. Fourteen QTL hotspots, with at least three traits coinciding, were also identified, several of which co-localize with barley orthologues of genes controlling grain dimensions in rice. Most of the allele effects are specific to geographical location and/or exotic parental genotype. This study shows the existence of beneficial alleles for yield-related traits in exotic barley germplasm and provides candidate alleles for future improvement of these traits by the breeder.

Contrasting genetic regulation of plant development in wild barley grown in two European environments revealed by nested association mapping

Barley is cultivated more widely than the other major world crops because it adapts well to environmental constraints, such as drought, heat, and day length. To better understand the genetic control of local adaptation in barley, we studied development in the nested association mapping population HEB-25, derived from crossing 25 wild barley accessions with the cultivar 'Barke'. HEB-25 was cultivated in replicated field trials in Dundee (Scotland) and Halle (Germany), differing in regard to day length, precipitation, and temperature. Applying a genome-wide association study, we located 60 and 66 quantitative trait locus (QTL) regions regulating eight plant development traits in Dundee and Halle, respectively. A number of QTLs could be explained by known major genes such as PHOTOPERIOD 1 (Ppd-H1) and FLOWERING LOCUS T (HvFT-1) that regulate plant development. In addition, we observed that developmental traits in HEB-25 were partly controlled via genotype × environment and genotype × donor interactions, defined as location-specific and family-specific QTL effects. Our findings indicate that QTL alleles are available in the wild barley gene pool that show contrasting effects on plant development, which may be deployed to improve adaptation of cultivated barley to future environmental changes.

Identification of QTL conferring resistance to stripe rust (Puccinia striiformis f. sp. hordei) and leaf rust (Puccinia hordei) in barley using nested association mapping (NAM)

The biotrophic rust fungi Puccinia hordei and Puccinia striiformis are important barley pathogens with the potential to cause high yield losses through an epidemic spread. The identification of QTL conferring resistance to these pathogens is the basis for targeted breeding approaches aiming to improve stripe rust and leaf rust resistance of modern cultivars. Exploiting the allelic richness of wild barley accessions proved to be a valuable tool to broaden the genetic base of resistance of barley cultivars. In this study, SNP-based nested association mapping (NAM) was performed to map stripe rust and leaf rust resistance QTL in the barley NAM population HEB-25, comprising 1,420 lines derived from BC₁S₃ generation. By scoring the percentage of infected leaf area, followed by calculation of the area under the disease progress curve and the average ordinate during a two-year field trial, a large variability of resistance across and within HEB-25 families was observed. NAM based on 5,715 informative SNPs resulted in the identification of twelve and eleven robust QTL for resistance against stripe rust and leaf rust, respectively. Out of these, eight QTL for stripe rust and two QTL for leaf rust are considered novel showing no overlap with previously reported resistance QTL. Overall, resistance to both pathogens in HEB-25 is most likely due to the accumulation of numerous small effect loci. In addition, the NAM results indicate that the 25 wild donor QTL alleles present in HEB-25 strongly differ in regard to their individual effect on rust resistance. In future, the NAM concept will allow to select and combine individual wild barley alleles from different HEB parents to increase rust resistance in barley. The HEB-25 results will support to unravel the genetic basis of rust resistance in barley, and to improve resistance against stripe rust and leaf rust of modern barley cultivars.

Genetic Mapping Populations for Conducting High-Resolution Trait Mapping in Plants

Fine mapping of quantitative trait loci (QTL) is the route to more detailed molecular characterization and functional studies of the relationship between polymorphism and trait variation. It is also of direct relevance to breeding since it makes QTL more easily integrated into marker-assisted breeding and into genomic selection. Fine mapping requires that marker-trait associations are tested in populations in which large numbers of recombinations have occurred. This can be achieved by increasing the size of mapping populations or by increasing the number of generations of crossing required to create the population. We review the factors affecting the precision and power of fine mapping experiments and describe some contemporary experimental approaches, focusing on the use of multi-parental or multi-founder populations such as the multi-parent advanced generation intercross (MAGIC) and nested association mapping (NAM). We favor approaches such as MAGIC since these focus explicitly on increasing the amount of recombination that occurs within the population. Whatever approaches are used, we believe the days of mapping QTL in small populations must come to an end. In our own work in MAGIC wheat populations, we started with a target of developing 1,000 lines per population: that number now looks to be on the low side. Graphical Abstract.

A nested association mapping population identifies multiple small effect QTL conferring resistance against net blotch (Pyrenophora teres f. teres) in wild barley

The net form of net blotch caused by the necrotrophic fungus Pyrenophora teres f. teres is a major disease of barley, causing high yield losses and reduced malting and feed quality. Exploiting the allelic richness of wild barley proved to be a valuable tool to broaden the genetic base of resistance of modern elite cultivars. In this study, a SNP-based nested association mapping (NAM) study was conducted to map QTL for P. teres resistance in the barley population HEB-25 comprising 1,420 lines derived from BC1S3 generation. By scoring the percentage of infected leaf area followed by calculation of the average ordinate (AO) and scoring of the reaction type (RT) in two-year field trials a large variability of net blotch resistance across and within families of HEB-25 was observed. Genotype response to net blotch infection showed a range of 48.2% for AO (0.9-49.1%) and 6.4 for RT (2.2-8.6). NAM based on 5,715 informative SNPs resulted in the identification of 24 QTL for resistance against net blotch. Out of these, six QTL are considered novel showing no correspondence to previously reported QTL for net blotch resistance. Overall, variation of net blotch resistance in HEB-25 turned out to be controlled by small effect QTL. Results indicate the presence of alleles in HEB-25 differing in their effect on net blotch resistance. Results provide valuable information regarding the genetic architecture of the complex barley-P. teres f. teres interaction as well as for the improvement of net blotch resistance of elite barley cultivars.

QTL controlling grain filling under terminal drought stress in a set of wild barley introgression lines

Drought is a major abiotic stress impeding the yield of cereal crops globally. Particularly in Mediterranean environments, water becomes a limiting factor during the reproductive developmental stage, causing yield losses. The wild progenitor of cultivated barley Hordeum vulgare ssp spontaneum (Hsp) is a potentially useful source of drought tolerance alleles. Wild barley introgression lines like the S42IL library may facilitate the introduction of favorable exotic alleles into breeding material. The complete set of 83 S42ILs was genotyped with the barley 9k iSelect platform in order to complete genetic information obtained in previous studies. The new map comprises 2,487 SNPs, spanning 989.8 cM and covering 94.5% of the Hsp genome. Extent and positions of introgressions were confirmed and new information for ten additional S42ILs was collected. A subset of 49 S42ILs was evaluated for drought response in four greenhouse experiments. Plants were grown under well-watered conditions until ten days post anthesis. Subsequently drought treatment was applied by reducing the available water. Several morphological and harvest parameters were evaluated. Under drought treatment, trait performance was reduced. However, there was no interaction effect between genotype and treatment, indicating that genotypes, which performed best under control treatment, also performed best under drought treatment. In total, 40 QTL for seven traits were detected in this study. For instance, favorable Hsp effects were found for thousand grain weight (TGW) and number of grains per ear under drought stress. In particular, line S42IL-121 is a promising candidate for breeding improved malting cultivars, displaying a TGW, which was increased by 17% under terminal drought stress due to the presence of an unknown wild barley QTL allele on chromosome 4H. The introgression line showed a similar advantage in previous field experiments and in greenhouse experiments under early drought stress. We, thus, recommend using S42IL-121 in barley breeding programs to enhance terminal drought tolerance.

Quantitative trait loci from identification to exploitation for crop improvement

Advancement in the field of genetics and genomics after the discovery of Mendel's laws of inheritance has led to map the genes controlling qualitative and quantitative traits in crop plant species. Mapping of genomic regions controlling the variation of quantitatively inherited traits has become routine after the advent of different types of molecular markers. Recently, the next generation sequencing methods have accelerated the research on QTL analysis. These efforts have led to the identification of more closely linked molecular markers with gene/QTLs and also identified markers even within gene/QTL controlling the trait of interest. Efforts have also been made towards cloning gene/QTLs or identification of potential candidate genes responsible for a trait. Further new concepts like crop QTLome and QTL prioritization have accelerated precise application of QTLs for genetic improvement of complex traits. In the past years, efforts have also been made in exploitation of a number of QTL for improving grain yield or other agronomic traits in various crops through markers assisted selection leading to cultivation of these improved varieties at farmers' field. In present article, we reviewed QTLs from their identification to exploitation in plant breeding programs and also reviewed that how improved cultivars developed through introgression of QTLs have improved the yield productivity in many crops.

New Strategies and Tools in Quantitative Genetics: How to Go from the Phenotype to the Genotype

Quantitative genetics has a long history in plants: It has been used to study specific biological processes, identify the factors important for trait evolution, and breed new crop varieties. These classical approaches to quantitative trait locus mapping have naturally improved with technology. In this review, we show how quantitative genetics has evolved recently in plants and how new developments in phenotyping, population generation, sequencing, gene manipulation, and statistics are rejuvenating both the classical linkage mapping approaches (for example, through nested association mapping) as well as the more recently developed genome-wide association studies. These strategies are complementary in most instances, and indeed, one is often used to confirm the results of the other. Despite significant advances, an emerging trend is that the outcome and efficiency of the different approaches depend greatly on the genetic architecture of the trait in the genetic material under study.

Estimating parent-specific QTL effects through cumulating linked identity-by-state SNP effects in multiparental populations

The emergence of multiparental mapping populations enabled plant geneticists to gain deeper insights into the genetic architecture of major agronomic traits and to map quantitative trait loci (QTLs) controlling the expression of these traits. Although the investigated mapping populations are similar, one open question is whether genotype data should be modelled as identical by state (IBS) or identical by descent (IBD). Whereas IBS simply makes use of raw genotype scores to distinguish alleles, IBD data are derived from parental offspring information. We report on comparing IBS and IBD by applying two multiple regression models on four traits studied in the barley nested association mapping (NAM) population HEB-25. We observed that modelling parent-specific IBD genotypes produced a lower number of significant QTLs with increased prediction abilities compared with modelling IBS genotypes. However, at lower trait heritabilities the IBS model produced higher prediction abilities. We developed a method to estimate multiallelic QTL effects in multiparental populations from simple biallelic IBS data. This method is based on cumulating IBS-derived single-nucleotide polymorphism (SNP) effect estimates in a defined genetic region surrounding a QTL. Comparing the resulting parent-specific QTL effects with those obtained from IBD approaches revealed high accordance that could be confirmed through simulations. The method turned out to be also applicable to a barley multiparent advanced generation inter-cross (MAGIC) population. The 'cumulation method' represents a universal approach to differentiate parent-specific QTL effects in multiparental populations, even if no IBD information is available. In future, the method could further benefit from the availability of much denser SNP maps.

Maximizing the potential of multi-parental crop populations

Most agriculturally significant crop traits are quantitatively inherited which limits the ease and efficiency of trait dissection. Multi-parent populations overcome the limitations of traditional trait mapping and offer new potential to accurately define the genetic basis of complex crop traits. The increasing popularity and use of nested association mapping (NAM) and multi-parent advanced generation intercross (MAGIC) populations raises questions about the optimal design and allocation of resources in their creation. In this paper we review strategies for the creation of multi-parent populations and describe two complementary in silico studies addressing the design and construction of NAM and MAGIC populations. The first simulates the selection of diverse founder parents and the second the influence of multi-parent crossing schemes (and number of founders) on haplotype creation and diversity. We present and apply two open software resources to simulate alternate strategies for the development of multi-parent populations.