Dissecting quantitative trait variation in the resequencing era: complementarity of bi-parental, multi-parental and association panels

Integration of QTL and transcriptome approaches for the identification of genes involved in tomato response to nitrogen deficiency

Optimizing plant nitrogen (N) usage and inhibiting N leaching loss in the soil-crop system is crucial to maintaining crop yield and reducing environmental pollution. This study aimed at identifying quantitative trait loci (QTLs) and differentially expressed genes (DEGs) between two N treatments in order to list candidate genes related to nitrogen-related contrasting traits in tomato varieties. We characterized a genetic diversity core-collection (CC) and a multi-parental advanced generation intercross (MAGIC) tomato population grown in a greenhouse under two nitrogen levels and assessed several N-related traits and mapped QTLs. Transcriptome response under the two N conditions was also investigated through RNA sequencing of fruit and leaves in four parents of the MAGIC population. Significant differences in response to N input reduction were observed at the phenotypic level for biomass and N-related traits. Twenty-seven QTLs were detected for three target traits (leaf N content, leaf nitrogen balance index, and petiole NO3- content), 10 and six in the low and high N condition, respectively, while 19 QTLs were identified for plasticity traits. At the transcriptome level, 4752 and 2405 DEGs were detected between the two N conditions in leaves and fruits, respectively, among which 3628 (50.6%) in leaves and 1717 (71.4%) in fruit were genotype specific. When considering all the genotypes, 1677 DEGs were shared between organs or tissues. Finally, we integrated DEG and QTL analyses to identify the most promising candidate genes. The results highlighted a complex genetic architecture of N homeostasis in tomato and novel putative genes useful for breeding tomato varieties requiring less N input.

Multi-parental fungal mapping population study to detect genomic regions associated with Pyrenophora teres f. teres virulence

In recent years multi-parental mapping populations (MPPs) have been widely adopted in many crops to detect quantitative trait loci (QTLs) as this method can compensate for the limitations of QTL analyses using bi-parental mapping populations. Here we report the first multi-parental nested association mapping (MP-NAM) population study used to detect genomic regions associated with host-pathogenic interactions. MP-NAM QTL analyses were conducted on 399 Pyrenophora teres f. teres individuals using biallelic, cross-specific and parental QTL effect models. A bi-parental QTL mapping study was also conducted to compare the power of QTL detection between bi-parental and MP-NAM populations. Using MP-NAM with 399 individuals detected a maximum of eight QTLs with a single QTL effect model whilst only a maximum of five QTLs were detected with an individual bi-parental mapping population of 100 individuals. When reducing the number of isolates in the MP-NAM to 200 individuals the number of QTLs detected remained the same for the MP-NAM population. This study confirms that MPPs such as MP-NAM populations can be successfully used in detecting QTLs in haploid fungal pathogens and that the power of QTL detection with MPPs is greater than with bi-parental mapping populations.

Genetics and breeding for resistance against four leaf spot diseases in wheat (Triticum aestivum L.)

In wheat, major yield losses are caused by a variety of diseases including rusts, spike diseases, leaf spot and root diseases. The genetics of resistance against all these diseases have been studied in great detail and utilized for breeding resistant cultivars. The resistance against leaf spot diseases caused by each individual necrotroph/hemi-biotroph involves a complex system involving resistance (R) genes, sensitivity (S) genes, small secreted protein (SSP) genes and quantitative resistance loci (QRLs). This review deals with resistance for the following four-leaf spot diseases: (i) Septoria nodorum blotch (SNB) caused by Parastagonospora nodorum; (ii) Tan spot (TS) caused by Pyrenophora tritici-repentis; (iii) Spot blotch (SB) caused by Bipolaris sorokiniana and (iv) Septoria tritici blotch (STB) caused by Zymoseptoria tritici.

Development of a MAGIC population and high-resolution quantitative trait mapping for nicotine content in tobacco

Multiparent Advanced Generation Inter-Cross (MAGIC) population is an ideal genetic and breeding material for quantitative trait locus (QTL) mapping and molecular breeding. In this study, a MAGIC population derived from eight tobacco parents was developed. Eight parents and 560 homozygous lines were genotyped by a 430K single-nucleotide polymorphism (SNP) chip assay and phenotyped for nicotine content under different conditions. Four QTLs associated with nicotine content were detected by genome-wide association mapping (GWAS), and one major QTL, named qNIC7-1, was mapped repeatedly under different conditions. Furthermore, by combining forward mapping, bioinformatics analysis and gene editing, we identified an ethylene response factor (ERF) transcription factor as a candidate gene underlying the major QTL qNIC7-1 for nicotine content in tobacco. A presence/absence variation (PAV) at qNIC7-1 confers changes in nicotine content. Overall, the large size of this MAGIC population, diverse genetic composition, balanced parental contributions and high levels of recombination all contribute to its value as a genetic and breeding resource. The application of the tobacco MAGIC population for QTL mapping and detecting rare allelic variation was demonstrated using nicotine content as a proof of principle.

Sorghum Ionomics Reveals the Functional SbHMA3a Allele that Limits Excess Cadmium Accumulation in Grains

Understanding uptake and redistribution of essential minerals or sequestering of toxic elements is important for optimized crop production. Although the mechanisms controlling mineral transport have been elucidated in rice and other species, little is understood in sorghum-an important C4 cereal crop. Here, we assessed the genetic factors that govern grain ionome profiles in sorghum using recombinant inbred lines (RILs) derived from a cross between BTx623 and NOG (Takakibi). Pairwise correlation and clustering analysis of 22 elements, measured in sorghum grains harvested under greenhouse conditions, indicated that the parental lines, as well as the RILs, show different ionomes. In particular, BTx623 accumulated significantly higher levels of cadmium (Cd) than NOG, because of differential root-to-shoot translocation factors between the two lines. Quantitative trait locus (QTL) analysis revealed a prominent QTL for grain Cd concentration on chromosome 2. Detailed analysis identified SbHMA3a, encoding a P1B-type ATPase heavy metal transporter, as responsible for low Cd accumulation in grains; the NOG allele encoded a functional HMA3 transporter (SbHMA3a-NOG) whose Cd-transporting activity was confirmed by heterologous expression in yeast. BTx623 possessed a truncated, loss-of-function SbHMA3a allele. The functionality of SbHMA3a in NOG was confirmed by Cd concentrations of F2 grains derived from the reciprocal cross, in which the NOG allele behaved in a dominant manner. We concluded that SbHMA3a-NOG is a Cd transporter that sequesters excess Cd in root tissues, as shown in other HMA3s. Our findings will facilitate the isolation of breeding cultivars with low Cd in grains or in exploiting high-Cd cultivars for phytoremediation.

An IBD-based mixed model approach for QTL mapping in multiparental populations

The identity-by-descent (IBD)-based mixed model approach introduced in this study can detect quantitative trait loci (QTLs) referring to the parental origin and simultaneously account for multilevel relatedness of individuals within and across families. This unified approach is proved to be a powerful approach for all kinds of multiparental population (MPP) designs. Multiparental populations (MPPs) have become popular for quantitative trait loci (QTL) detection. Tools for QTL mapping in MPPs are mostly developed for specific MPPs and do not generalize well to other MPPs. We present an IBD-based mixed model approach for QTL mapping in all kinds of MPP designs, e.g., diallel, Nested Association Mapping (NAM), and Multiparental Advanced Generation Intercross (MAGIC) designs. The first step is to compute identity-by-descent (IBD) probabilities using a general Hidden Markov model framework, called reconstructing ancestry blocks bit by bit (RABBIT). Next, functions of IBD information are used as design matrices, or genetic predictors, in a mixed model approach to estimate variance components for multiallelic genetic effects associated with parents. Family-specific residual genetic effects are added, and a polygenic effect is structured by kinship relations between individuals. Case studies of simulated diallel, NAM, and MAGIC designs proved that the advanced IBD-based multi-QTL mixed model approach incorporating both kinship relations and family-specific residual variances (IBD.MQMkin_F) is robust across a variety of MPP designs and allele segregation patterns in comparison to a widely used benchmark association mapping method, and in most cases, outperformed or behaved at least as well as other tools developed for specific MPP designs in terms of mapping power and resolution. Successful analyses of real data cases confirmed the wide applicability of our IBD-based mixed model methodology.

Genetic Architecture of Maize Rind Strength Revealed by the Analysis of Divergently Selected Populations

The strength of the stalk rind, measured as rind penetrometer resistance (RPR), is an important contributor to stalk lodging resistance. To enhance the genetic architecture of RPR, we combined selection mapping on populations developed by 15 cycles of divergent selection for high and low RPR with time-course transcriptomic and metabolic analyses of the stalks. Divergent selection significantly altered allele frequencies of 3,656 and 3,412 single- nucleotide polymorphisms (SNPs) in the high and low RPR populations, respectively. Surprisingly, only 110 (1.56%) SNPs under selection were common in both populations, while the majority (98.4%) were unique to each population. This result indicated that high and low RPR phenotypes are produced by biologically distinct mechanisms. Remarkably, regions harboring lignin and polysaccharide genes were preferentially selected in high and low RPR populations, respectively. The preferential selection was manifested as higher lignification and increased saccharification of the high and low RPR stalks, respectively. The evolution of distinct gene classes according to the direction of selection was unexpected in the context of parallel evolution and demonstrated that selection for a trait, albeit in different directions, does not necessarily act on the same genes. Tricin, a grass-specific monolignol that initiates the incorporation of lignin in the cell walls, emerged as a key determinant of RPR. Integration of selection mapping and transcriptomic analyses with published genetic studies of RPR identified several candidate genes including ZmMYB31, ZmNAC25, ZmMADS1, ZmEXPA2, ZmIAA41 and hk5. These findings provide a foundation for an enhanced understanding of RPR and the improvement of stalk lodging resistance.

Genome wide association mapping for agronomic, fruit quality, and root architectural traits in tomato under organic farming conditions

BACKGROUND

Opportunity and challenges of the agriculture scenario of the next decades will face increasing demand for secure food through approaches able to minimize the input to cultivations. Large panels of tomato varieties represent a valuable resource of traits of interest under sustainable cultivation systems and for genome-wide association studies (GWAS). For mapping loci controlling the variation of agronomic, fruit quality, and root architecture traits, we used a heterogeneous set of 244 traditional and improved tomato accessions grown under organic field trials. Here we report comprehensive phenotyping and GWAS using over 37,300 SNPs obtained through double digest restriction-site associated DNA (dd-RADseq).

RESULTS

A wide range of phenotypic diversity was observed in the studied collection, with highly significant differences encountered for most traits. A variable level of heritability was observed with values up to 69% for morphological traits while, among agronomic ones, fruit weight showed values above 80%. Genotype by environment analysis highlighted the strongest genotypic effect for aboveground traits compared to root architecture, suggesting that the hypogeal part of tomato plants has been a minor objective for breeding activities. GWAS was performed by a compressed mixed linear model leading to 59 significantly associated loci, allowing the identification of novel genes related to flower and fruit characteristics. Most genomic associations fell into the region surrounding SUN, OVATE, and MYB gene families. Six flower and fruit traits were associated with a single member of the SUN family (SLSUN31) on chromosome 11, in a region involved in the increase of fruit weight, locules number, and fruit fasciation. Furthermore, additional candidate genes for soluble solids content, fruit colour and shape were found near previously reported chromosomal regions, indicating the presence of synergic and multiple linked genes underlying the variation of these traits.

CONCLUSIONS

Results of this study give new hints on the genetic basis of traits in underexplored germplasm grown under organic conditions, providing a framework for the development of markers linked to candidate genes of interest to be used in genomics-assisted breeding in tomato, in particular under low-input and organic cultivation conditions.

Unraveling the genetics of tomato fruit weight during crop domestication and diversification

KEY MESSAGE

Six novel fruit weight QTLs were identified in tomato using multiple bi-parental populations developed from ancestral accessions. Beneficial alleles at these loci arose in semi-domesticated subpopulations and were likely left behind. This study paves the way to introgress these alleles into breeding programs. The size and weight of edible organs have been strongly selected during crop domestication. Concurrently, human have also focused on nutritional and cultural characteristics of fruits and vegetables, at times countering selective pressures on beneficial size and weight alleles. Therefore, it is likely that novel improvement alleles for organ weight still segregate in ancestral germplasm. To date, five domestication and diversification genes affecting tomato fruit weight have been identified, yet the genetic basis for increases in weight has not been fully accounted for. We found that fruit weight increased gradually during domestication and diversification, and semi-domesticated subpopulations featured high phenotypic and nucleotide diversity. Columella and septum fruit tissues were proportionally increased, suggesting targeted selection. We developed twenty-one F2 populations with parents fixed for the known fruit weight genes, corresponding to putative key transitions from wild to fully domesticated tomatoes. These parents also showed differences in fruit weight attributes as well as the developmental timing of size increase. A subset of populations was targeted for QTL-seq, leading to the identification of six uncloned fruit weight QTLs. Three QTLs, located on chromosomes 1, 2 and 3, were subsequently validated by progeny testing. By exploring the segregation of the known fruit weight genes and the identified QTLs, we estimated that most beneficial alleles in the newly identified loci arose in semi-domesticated subpopulations from South America and were not likely transmitted to fully domesticated landraces. Therefore, these alleles could be incorporated into breeding programs using the germplasm and genetic resources identified in this study.

Genetic diversity of tomato response to heat stress at the QTL and transcriptome levels

Tomato is a widely cultivated crop, which can grow in many environments. However, temperature above 30°C impairs its reproduction, subsequently impacting fruit yield. We assessed the impact of high-temperature stress (HS) in two tomato experimental populations, a multi-parental advanced generation intercross (MAGIC) population and a core-collection (CC) of small-fruited tomato accessions. Both populations were evaluated for 11 traits related to yield components, phenology and fruit quality in optimal and HS conditions. HS significantly impacted all traits in both populations, but a few genotypes with stable yield under HS were identified. A plasticity index was computed for each individual to measure the extent of the heat impact for each trait. Quantitative trait loci (QTL) were detected in control and HS conditions as well as for plasticity index. Linkage and genome-wide association analyses in the MAGIC and CC populations identified a total of 98 and 166 QTLs, respectively. Taking the two populations together, 69 plasticity QTLs (pQTLs) were involved in tomato heat response for 11 traits. The transcriptome changes in the ovary of six genotypes with contrasted responses to HS were studied, and 837 genes differentially expressed according to the conditions were detected. Combined with previous transcriptome studies, these results were used to propose candidate genes for HS response QTLs.

Using chlorate as an analogue to nitrate to identify candidate genes for nitrogen use efficiency in barley

Nitrogen (N) is one of the most important macronutrients for crop growth and development. Large amounts of N fertilizers are applied exogenously to improve grain yield and quality, which has led to environmental pollution and high cost of production. Therefore, improvement of N use efficiency (NUE) is a very important aspect for sustainable agriculture. Here, a pilot experiment was firstly conducted with a set of barley genotypes with confirmed NUE to validate the fast NUE screening, using chlorate as an analogue to nitrate. High NUE genotypes were susceptible to chlorate-induced toxicity whereas the low NUE genotypes were tolerant. A total of 180 barley RILs derived from four parents (Compass, GrangeR, Lockyer and La Trobe) were further screened for NUE. Leaf chlorosis induced by chlorate toxicity was the key parameter observed which was later related to low-N tolerance of the RILs. There was a distinct variation in chlorate susceptibility of the RILs with leaf chlorosis in the oldest leaf ranging from 10 to 80%. A genome-wide association study (GWAS) identified 9 significant marker-trait associations (MTAs) conferring high chlorate sensitivity on chromosomes 2H (2), 3H (1), 4H (4), 5H (1) and Un (1). Genes flanking with these markers were retrieved as potential targets for genetic improvement of NUE. Genes encoding Ferredoxin 3, leucine-rich receptor-like protein kinase family protein and receptor kinase are responsive to N stress. MTA4H5468 which exhibits concordance with high NUE phenotype can further be explored under different genetic backgrounds and successfully applied in marker-assisted selection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01239-8.

Exploring genetic architecture for pod-related traits in soybean using image-based phenotyping

Mature pod color (PC) and pod size (PS) served as important characteristics are used in the soybean breeding programs. However, manual phenotyping of such complex traits is time-consuming, laborious, and expensive for breeders. Here, we collected pod images from two different populations, namely, a soybean association panel (SAP) consisting of 187 accessions and an inter-specific recombinant inbred line (RIL) population containing 284 RILs. An image-based phenotyping method was developed and used to extract the pod color- and size-related parameters from images. Genome-wide association study (GWAS) and linkage mapping were performed to decipher the genetic control of pod color- and size-related traits across 2 successive years. Both populations exhibited wide phenotypic variations and continuous distribution in pod color- and size-related traits, indicating quantitative polygenic inheritance of these traits. GWAS and linkage mapping approaches identified the two major quantitative trait loci (QTL) underlying the pod color parameters, i.e., qPC3 and qPC19, located to chromosomes 3 and 19, respectively, and 12 stable QTLs for pod size-related traits across nine chromosomes. Several genes residing within the genomic region of stable QTL were identified as potential candidates underlying these pod-related traits based on the gene annotation and expression profiling data. Our results provide the useful information for fine-mapping/map-based cloning of QTL and marker-assisted selection of elite varieties with desirable pod traits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01223-2.

Genetic and molecular control of grain yield in maize

Understanding the genetic and molecular basis of grain yield is important for maize improvement. Here, we identified 49 consensus quantitative trait loci (cQTL) controlling maize yield-related traits using QTL meta-analysis. Then, we collected yield-related traits associated SNPs detected by association mapping and identified 17 consensus significant loci. Comparing the physical positions of cQTL with those of significant SNPs revealed that 47 significant SNPs were located within 20 cQTL regions. Furthermore, intensive reviews of 31 genes regulating maize yield-related traits found that the functions of many genes were conservative in maize and other plant species. The functional conservation indicated that some of the 575 maize genes (orthologous to 247 genes controlling yield or seed traits in other plant species) might be functionally related to maize yield-related traits, especially the 49 maize orthologous genes in cQTL regions, and 41 orthologous genes close to the physical positions of significant SNPs. In the end, we prospected on the integration of the public sources for exploring the genetic and molecular mechanisms of maize yield-related traits, and on the utilization of genetic and molecular mechanisms for maize improvement.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01214-3.

Allelic composition of carotenoid metabolic genes in 13 founders influences carotenoid composition in juice sac tissues of fruits among Japanese citrus breeding population

To enrich carotenoids, especially β-cryptoxanthin, in juice sac tissues of fruits via molecular breeding in citrus, allele mining was utilized to dissect allelic variation of carotenoid metabolic genes and identify an optimum allele on the target loci characterized by expression quantitative trait (eQTL) analysis. SNPs of target carotenoid metabolic genes in 13 founders of the Japanese citrus breeding population were explored using the SureSelect target enrichment method. An independent allele was determined based on the presence or absence of reliable SNPs, using trio analysis to confirm inheritability between parent and offspring. Among the 13 founders, there were 7 PSY alleles, 7 HYb alleles, 11 ZEP alleles, 5 NCED alleles, and 4 alleles for the eQTL that control the transcription levels of PDS and ZDS among the ancestral species, indicating that some founders acquired those alleles from them. The carotenoid composition data of 263 breeding pedigrees in juice sac tissues revealed that the phenotypic variance of carotenoid composition was similar to that in the 13 founders, whereas the mean of total carotenoid content increased. This increase in total carotenoid content correlated with the increase in either or both β-cryptoxanthin and violaxanthin in juice sac tissues. Bayesian statistical analysis between allelic composition of target genes and carotenoid composition in 263 breeding pedigrees indicated that PSY-a and ZEP-e alleles at PSY and ZEP loci had strong positive effects on increasing the total carotenoid content, including β-cryptoxanthin and violaxanthin, in juice sac tissues. Moreover, the pyramiding of these alleles also increased the β-cryptoxanthin content. Interestingly, the offset interaction between the alleles with increasing and decreasing effects on carotenoid content and the epistatic interaction among carotenoid metabolic genes were observed and these interactions complexed carotenoid profiles in breeding population. These results revealed that allele composition would highly influence the carotenoid composition in citrus fruits. The allelic genotype information for the examined carotenoid metabolic genes in major citrus varieties and the trio-tagged SNPs to discriminate the optimum alleles (PSY-a and ZEP-e) from the rest would promise citrus breeders carotenoid enrichment in fruit via molecular breeding.

Integrating multi-omics data for crop improvement

Our agricultural systems are now in urgent need to secure food for a growing world population. To meet this challenge, we need a better characterization of plant genetic and phenotypic diversity. The combination of genomics, transcriptomics and metabolomics enables a deeper understanding of the mechanisms underlying the complex architecture of many phenotypic traits of agricultural relevance. We review the recent advances in plant genomics to see how these can be integrated with broad molecular profiling approaches to improve our understanding of plant phenotypic variation and inform crop breeding strategies.

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.

GWAS Based on RNA-Seq SNPs and High-Throughput Phenotyping Combined with Climatic Data Highlights the Reservoir of Valuable Genetic Diversity in Regional Tomato Landraces

Tomato (Solanum lycopersicum L.) is a widely used model plant species for dissecting out the genomic bases of complex traits to thus provide an optimal platform for modern "-omics" studies and genome-guided breeding. Genome-wide association studies (GWAS) have become a preferred approach for screening large diverse populations and many traits. Here, we present GWAS analysis of a collection of 115 landraces and 11 vintage and modern cultivars. A total of 26 conventional descriptors, 40 traits obtained by digital phenotyping, the fruit content of six carotenoids recorded at the early ripening (breaker) and red-ripe stages and 21 climate-related variables were analyzed in the context of genetic diversity monitored in the 126 accessions. The data obtained from thorough phenotyping and the SNP diversity revealed by sequencing of ripe fruit transcripts of 120 of the tomato accessions were jointly analyzed to determine which genomic regions are implicated in the expressed phenotypic variation. This study reveals that the use of fruit RNA-Seq SNP diversity is effective not only for identification of genomic regions that underlie variation in fruit traits, but also of variation related to additional plant traits and adaptive responses to climate variation. These results allowed validation of our approach because different marker-trait associations mapped on chromosomal regions where other candidate genes for the same traits were previously reported. In addition, previously uncharacterized chromosomal regions were targeted as potentially involved in the expression of variable phenotypes, thus demonstrating that our tomato collection is a precious reservoir of diversity and an excellent tool for gene discovery.

Morphoagronomic characterization and whole-genome resequencing of eight highly diverse wild and weedy S. pimpinellifolium and S. lycopersicum var. cerasiforme accessions used for the first interspecific tomato MAGIC population

The wild Solanum pimpinellifolium (SP) and the weedy S. lycopersicum var. cerasiforme (SLC) are largely unexploited genetic reservoirs easily accessible to breeders, as they are fully cross-compatible with cultivated tomato (S. lycopersicum var. lycopersicum). We performed a comprehensive morphological and genomic characterization of four wild SP and four weedy SLC accessions, selected to maximize the range of variation of both taxa. These eight accessions are the founders of the first tomato interspecific multi-parent advanced generation inter-cross (MAGIC) population. The morphoagronomic characterization was carried out with 39 descriptors to assess plant, inflorescence, fruit and agronomic traits, revealing the broad range of diversity captured. Part of the morphological variation observed in SP was likely associated to the adaptation of the accessions to different environments, while in the case of SLC to both human activity and adaptation to the environment. Whole-genome resequencing of the eight accessions revealed over 12 million variants, ranging from 1.2 to 1.9 million variants in SLC and from 3.1 to 4.8 million in SP, being 46.3% of them (4,897,803) private variants. The genetic principal component analysis also confirmed the high diversity of SP and the complex evolutionary history of SLC. This was also reflected in the analysis of the potential footprint of common ancestors or old introgressions identified within and between the two taxa. The functional characterization of the variants revealed a significative enrichment of GO terms related to changes in cell walls that would have been negatively selected during domestication and breeding. The comprehensive morphoagronomic and genetic characterization of these accessions will be of great relevance for the genetic analysis of the first interspecific MAGIC population of tomato and provides valuable knowledge and tools to the tomato community for genetic and genomic studies and for breeding purposes.

Development of diagnostic molecular markers for marker-assisted breeding against bacterial wilt in tomato

Bacterial wilt, caused by the Ralstonia pseudosolanacearum species complex, is an important vascular disease that limits tomato production in tropical and subtropical regions. Two major quantitative trait loci (QTL) of bacterial wilt resistance on chromosome 6 (Bwr-6) and 12 (Bwr-12) were previously identified in Solanum lycopersicum 'Hawaii 7996'; however, marker-assisted breeding for bacterial wilt resistance is not well established. To dissect the QTL, six cleaved amplified polymorphic sites (CAPS) and derived CAPS (dCAPS) markers within the Bwr-6 region and one dCAPS marker near Bwr-12 were developed, and resistance levels in 117 tomato cultivars were evaluated. Two markers, RsR6-5 on chromosome 6 and RsR12-1 on chromosome 12, were selected based on the genotypic and phenotypic analysis. The combination of RsR6-5 and RsR12-1 effectively distinguishes resistant and susceptible cultivars. Furthermore, the efficiency of the two markers was validated in the F3 generation derived from the F2 population between E6203 (susceptible) and Hawaii 7998 (resistant). Resistant alleles at both loci led to the resistance to bacterial wilt. These markers will facilitate marker-assisted breeding of tomato resistant to bacterial wilt.

Genetic mapping using a wheat multi-founder population reveals a locus on chromosome 2A controlling resistance to both leaf and glume blotch caused by the necrotrophic fungal pathogen Parastagonospora nodorum

KEY MESSAGE

A locus on wheat chromosome 2A was found to control field resistance to both leaf and glume blotch caused by the necrotrophic fungal pathogen Parastagonospora nodorum. The necrotrophic fungal pathogen Parastagonospora nodorum is the causal agent of Septoria nodorum leaf blotch and glume blotch, which are common wheat (Triticum aestivum L.) diseases in humid and temperate areas. Susceptibility to Septoria nodorum leaf blotch can partly be explained by sensitivity to corresponding P. nodorum necrotrophic effectors (NEs). Susceptibility to glume blotch is also quantitative; however, the underlying genetics have not been studied in detail. Here, we genetically map resistance/susceptibility loci to leaf and glume blotch using an eight-founder wheat multiparent advanced generation intercross population. The population was assessed in six field trials across two sites and 4 years. Seedling infiltration and inoculation assays using three P. nodorum isolates were also carried out, in order to compare quantitative trait loci (QTL) identified under controlled conditions with those identified in the field. Three significant field resistance QTL were identified on chromosomes 2A and 6A, while four significant seedling resistance QTL were detected on chromosomes 2D, 5B and 7D. Among these, QSnb.niab-2A.3 for field resistance to both leaf blotch and glume blotch was detected in Norway and the UK. Colocation with a QTL for seedling reactions against culture filtrate from a Norwegian P. nodorum isolate indicated the QTL could be caused by a novel NE sensitivity. The consistency of this QTL for leaf blotch at the seedling and adult plant stages and culture filtrate infiltration was confirmed by haplotype analysis. However, opposite effects for the leaf blotch and glume blotch reactions suggest that different genetic mechanisms may be involved.

QTL-seq reveals genomic regions associated with spikelet fertility in response to a high temperature in rice (Oryza sativa L.)

The QTL-seq approach was used to identify QTLs for spikelet fertility under heat stress in rice. QTLs were detected on chromosomes 1, 2 and 3. Rice is a staple food of more than half of the global population. Rice production is increasingly affected by extreme environmental fluctuations caused by climate change. Increasing temperatures that exceed the optimum temperature adversely affect rice growth and development, especially during reproductive stages. Heat stress during the reproductive stages has a large effect on spikelet fertility; hence, the yield decreases. To sustain rice yields under increasing temperatures, the development of rice varieties for heat tolerance is necessary. In this study, we applied the QTL-seq approach to rapidly identify QTLs for spikelet fertility under heat stress (air temperature of 40-45 °C) based on two DNA pools, each consisting of 25 individual plants that exhibited a heat-tolerant or heat-sensitive phenotype from an F₂ population of a cross between M9962 (heat tolerant) and Sinlek (heat sensitive). Three QTLs, qSF1, qSF2 and qSF3, were detected on chromosomes 1, 2 and 3, respectively, according to the highest contrasting SNP index between the two bulks. The QTLs identified in this study were found to overlap or were linked to QTLs previously identified in other crosses using conventional QTL mapping. A few highly abundant and anther-specific genes that contain nonsynonymous variants were identified within the QTLs and were proposed to be potential candidate genes. These genes could be targets in rice breeding programs for heat tolerance.

Mapping of resistance to corn borers in a MAGIC population of maize

BACKGROUND

Corn borers constitute an important pest of maize around the world; in particular Sesamia nonagrioides Lefèbvre, named Mediterranean corn borer (MCB), causes important losses in Southern Europe. Methods of selection can be combined with transgenic approaches to increase the efficiency and durability of the resistance to corn borers. Previous studies of the genetic factors involved in resistance to MCB have been carried out using bi-parental populations that have low resolution or using association inbred panels that have a low power to detect rare alleles. We developed a Multi-parent Advanced Generation InterCrosses (MAGIC) population to map with high resolution the genetic determinants of resistance to MCB.

RESULTS

We detected multiple single nucleotide polymorphisms (SNPs) of low effect associated with resistance to stalk tunneling by MCB. We dissected a wide region related to stalk tunneling in multiple studies into three smaller regions (at ~ 150, ~ 155, and ~ 165 Mb in chromosome 6) that closely overlap with regions associated with cell wall composition. We also detected regions associated with kernel resistance and agronomic traits, although the co-localization of significant regions between traits was very low. This indicates that it is possible the concurrent improvement of resistance and agronomic traits.

CONCLUSIONS

We developed a mapping population which allowed a finer dissection of the genetics of maize resistance to corn borers and a solid nomination of candidate genes based on functional information. The population, given its large variability, was also adequate to map multiple traits and study the relationship between them.

Mapping of genomic regions associated with arsenic toxicity stress in a backcross breeding populations of rice (Oryza sativa L.)

BACKGROUND

Arsenic (As) is an unwanted toxic mineral that threatens the major rice-growing regions in the world, especially in South Asia. Rice production in Bangladesh and India depends on As-contaminated groundwater sources for irrigating paddy fields, resulting in elevated amounts of As in the topsoil. Arsenic accumulating in rice plants has a significant negative effect on human and animal health. Here, we present a quantitative trait locus (QTL) mapping study to identify candidate genes conferring As toxicity tolerance and accumulation in rice (Oryza sativa L.) seedlings. An early backcross breeding population consisting of 194 lines derived from a cross between WTR1 (indica) and Hao-an-nong (japonica) was grown in hydroponics for 25 days, from the seventh day exposed to an environmentally relevant concentration of 10 ppm As.

RESULTS

Arsenic toxicity leads to significantly negative plant responses, including reduced biomass, stunted plant growth, reduced leaf chlorophyll content, and increased shoot As concentration ranging from 9 to 20 mg kg- 1. Marker-trait association was determined for seven As-related traits using 704 single nucleotide polymorphism (SNP) markers generated from a 6 K SNP-array. One QTL was mapped on chromosome 1 for relative chlorophyll content, two QTLs for As content in roots were mapped on chromosome 8, and six QTLs for As content in shoots were mapped on chromosomes 2, 5, 6, and 9. Using the whole-genome sequence of the parents, we narrowed down the number of candidate genes associated with the QTL intervals based on the existence of a non-synonymous mutation in genes between the parental lines. Also, by using publicly available gene expression profiles for As stress, we further narrowed down the number of candidate genes in the QTL intervals by comparing the expression profiles of genes under As stress and control conditions. Twenty-five genes showing transcription regulation were considered as candidate gene nominees for As toxicity-related traits.

CONCLUSIONS

Our study provides insight into the genetic basis of As tolerance and uptake in the early seedling stage of rice. Comparing our findings with the previously reported QTLs for As toxicity stress in rice, we identified some novel and co-localized QTLs associated with As stress. Also, the mapped QTLs harbor gene models of known function associated with stress responses, metal homeostasis, and transporter activity in rice. Overall, our findings will assist breeders with initial marker information to develop suitable varieties for As-contaminated ecosystems.

A novel high-density grapevine (Vitis vinifera L.) integrated linkage map using GBS in a half-diallel population

A half-diallel population involving five elite grapevine cultivars was generated and genotyped by GBS, and highly-informative segregation data was used to construct a high-density genetic map for Vitis vinifera L. Grapevine is one of the most relevant fruit crops in the world. Deeper genetic knowledge could assist modern grapevine breeding programs to develop new wine grape varieties able to face climate change effects. To assist in the rapid identification of markers for crop yield components, grape quality traits and adaptation potential, we generated a large Vitis vinifera L. population (N = 624) by crossing five red wine cultivars in a half-diallel scheme, which was subsequently sequenced by an efficient GBS procedure. A high number of fully informative genetic variants was detected using a novel mapping approach capable of reconstructing local haplotypes from adjacent biallelic SNPs, which were subsequently used to construct the densest consensus genetic map available for the cultivated grapevine to date. This 1378.3-cM map integrates 10 bi-parental consensus maps and orders 4437 markers in 3353 unique positions on 19 chromosomes. Markers are well distributed all along the grapevine reference genome, covering up to 98.8% of its genomic sequence. Additionally, a good agreement was observed between genetic and physical orders, adding confidence in the quality of this map. Collectively, our results pave the way for future genetic studies (such as fine QTL mapping) aimed to understand the complex relationship between genotypic and phenotypic variation in the cultivated grapevine. In addition, the method used (which efficiently delivers a high number of fully informative markers) could be of interest to other outbred organisms, notably perennial fruit crops.

QTLs for Resistance to Fusarium Ear Rot in a Multiparent Advanced Generation Intercross (MAGIC) Maize Population

Alternative approaches to linkage and association mapping using inbred panels may allow further insights into loci involved in resistance to Fusarium ear rot and lead to the discovery of suitable markers for breeding programs. Here, the suitability of a maize multiparent advanced-generation intercross population for detecting quantitative trait loci (QTLs) associated with Fusarium ear rot resistance was evaluated and found to be valuable in uncovering genomic regions containing resistance-associated loci in temperate materials. In total, 13 putative minor QTLs were located over all of the chromosomes, except chromosome 5, and frequencies of favorable alleles for resistance to Fusarium ear rot were, in general, high. These findings corroborated the quantitative characteristic of resistance to Fusarium ear rot in which many loci have small additive effects. Present and previous results indicate that crucial regions such as 210 to 220 Mb in chromosome 3 and 166 to 173 Mb in chromosome 7 (B73-RefGen-v2) contain QTLs for Fusarium ear rot resistance and fumonisin content.

Genetic and environmental perturbations lead to regulatory decoherence

Correlation among traits is a fundamental feature of biological systems that remains difficult to study. To address this problem, we developed a flexible approach that allows us to identify factors associated with inter-individual variation in correlation. We use data from three human cohorts to study the effects of genetic and environmental variation on correlations among mRNA transcripts and among NMR metabolites. We first show that environmental exposures (infection and disease) lead to a systematic loss of correlation, which we define as 'decoherence'. Using longitudinal data, we show that decoherent metabolites are better predictors of whether someone will develop metabolic syndrome than metabolites commonly used as biomarkers of this disease. Finally, we demonstrate that correlation itself is under genetic control by mapping hundreds of 'correlation quantitative trait loci (QTLs)'. Together, this work furthers our understanding of how and why coordinated biological processes break down, and points to a potential role for decoherence in disease.

Editorial note

This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Trait discovery and editing in tomato

Tomato (Solanum lycopersicum), which is used for both processing and fresh markets, is a major crop species that is the top ranked vegetable produced over the world. Tomato is also a model species for research in genetics, fruit development and disease resistance. Genetic resources available in public repositories comprise the 12 wild related species and thousands of landraces, modern cultivars and mutants. In addition, high quality genome sequences are available for cultivated tomato and for several wild relatives, hundreds of accessions have been sequenced, and databases gathering sequence data together with genetic and phenotypic data are accessible to the tomato community. Major breeding goals are productivity, resistance to biotic and abiotic stresses, and fruit sensorial and nutritional quality. New traits, including resistance to various biotic and abiotic stresses and root architecture, are increasingly being studied. Several major mutations and quantitative trait loci (QTLs) underlying traits of interest in tomato have been uncovered to date and, thanks to new populations and advances in sequencing technologies, the pace of trait discovery has considerably accelerated. In recent years, clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 gene editing (GE) already proved its remarkable efficiency in tomato for engineering favorable alleles and for creating new genetic diversity by gene disruption, gene replacement, and precise base editing. Here, we provide insight into the major tomato traits and underlying causal genetic variations discovered so far and review the existing genetic resources and most recent strategies for trait discovery in tomato. Furthermore, we explore the opportunities offered by CRISPR/Cas9 and their exploitation for trait editing in tomato.

Usefulness of a Multiparent Advanced Generation Intercross Population With a Greatly Reduced Mating Design for Genetic Studies in Winter Wheat

Multiparent advanced generation intercross (MAGIC) populations were recently developed to allow the high-resolution mapping of quantitative traits. We present a genetic linkage map of an elite but highly diverse eight-founder MAGIC population in common wheat (Triticum aestivum L.). Our MAGIC population is composed of 394 F6:8 recombinant inbred lines lacking significant signatures of population structure. The linkage map included 5435 SNP markers distributed over 2804 loci and spanning 5230 cM. The analysis of population parameters, including genetic structure, kinship, founder probabilities, and linkage disequilibrium and congruency to other maps indicated appropriate construction of both the population and the genetic map. It was shown that eight-founder MAGIC populations exhibit a greater number of loci and higher recombination rates, especially in the pericentromeric regions, compared to four-founder MAGIC, and biparental populations. In addition, our greatly simplified eight-parental MAGIC mating design with an additional eight-way intercross step was found to be equivalent to a MAGIC design with all 210 possible four-way crosses regarding the levels of missing founder assignments and the number of recombination events. Furthermore, the MAGIC population captured 71.7% of the allelic diversity available in the German wheat breeding gene pool. As a proof of principle, we demonstrated the application of the resource for quantitative trait loci mapping analyzing seedling resistance to powdery mildew. As wheat is a crop with many breeding objectives, this resource will allow scientists and breeders to carry out genetic studies for a wide range of breeder-relevant parameters in a single genetic background and reveal possible interactions between traits of economic importance.

Four Parent Maize (FPM) Population: Effects of Mating Designs on Linkage Disequilibrium and Mapping Quantitative Traits

Multiparent advanced generation inter-cross (MAGIC) populations can provide improved genetic mapping resolution by increasing allelic diversity and effective recombination. The Four Parent Maize (FPM; L.) population implemented five different mating designs used in MAGIC and bi-parental populations to compare empirical effects on genetic resolution and power of quantitative trait locus (QTL) detection; the combined population here comprised of 1149 individuals with 118,509 genetic markers. Measurements were recorded for plant height (PH), ear height (EH), days to anthesis (DTA) and silking (DTS) in seven environments, spanning three years. Linkage disequilibrium (LD) analysis of subpopulations indicated MAGIC population designs should incorporate generations of intermating to overcome initial LD increase caused by population admixture in a non-intermated four parent population (4way0sib). A 3- to 4-fold increase in genetic resolution (<0.8) and a 2.5-fold decrease in the extent of LD decay (<0.2) compared to the biparental populations was found for the four parent cross at the third generation of intermating (4way3sib). Power of QTL detection was affected to a greater extent by sample size rather than by mating designs. The FPM power simulations indicated that MAGIC populations have the ability to meet or exceed the mapping power of nested association panels with fewer individuals and diversity inputs. Using association mapping software we identified 2, 5, 7, and 6 QTL for PH, EH, DTA, and DTS, respectively. The FPM population is a valuable resource for quantifying empirical improvements of parent number, intermating, and the number of progeny for QTL linkage mapping.

Haplotype-based allele mining in the Japan-MAGIC rice population

Multi-parent advanced generation inter-cross (MAGIC) lines have broader genetic variation than bi-parental recombinant inbred lines. Genome-wide association study (GWAS) using high number of DNA polymorphisms such as single-nucleotide polymorphisms (SNPs) is a popular tool for allele mining in MAGIC populations, in which the associations of phenotypes with SNPs are investigated; however, the effects of haplotypes from multiple founders on phenotypes are not considered. Here, we describe an improved method of allele mining using the newly developed Japan-MAGIC (JAM) population, which is derived from eight high-yielding rice cultivars in Japan. To obtain information on the haplotypes in the JAM lines, we predicted the haplotype blocks in the whole chromosomes using 16,345 SNPs identified via genotyping-by-sequencing analysis. Using haplotype-based GWAS, we clearly detected the loci controlling the glutinous endosperm and culm length traits. Information on the alleles of the eight founders, which was based on the effects of mutations revealed by the analysis of next-generation sequencing data, was used to narrow down the candidate genes and reveal the associations between alleles and phenotypes. The haplotype-based allele mining (HAM) proposed in this study is a promising approach to the detection of allelic variation in genes controlling agronomic traits in MAGIC populations.

SSR-based association mapping of fiber quality in upland cotton using an eight-way MAGIC population

The quality of fiber is significant in the upland cotton industry. As complex quantitative traits, fiber quality traits are worth studying at a genetic level. To investigate the genetic architecture of fiber quality traits, we conducted an association analysis using a multi-parent advanced generation inter-cross (MAGIC) population developed from eight parents and comprised of 960 lines. The reliable phenotypic data for six major fiber traits of the MAGIC population were collected from five environments in three locations. Phenotypic analysis showed that the MAGIC lines have a wider variation amplitude and coefficient than the founders. A total of 284 polymorphic SSR markers among eight parents screened from a high-density genetic map were used to genotype the MAGIC population. The MAGIC population showed abundant genetic variation and fast linkage disequilibrium (LD) decay (0.76 cM, r² > 0.1), which revealed the advantages of high efficiency and power in QTL exploration. Association mapping via a mixed linear model identified 52 significant loci associated with six fiber quality traits; 14 of them were mapped in reported QTL regions with fiber-related or other agronomic traits. Nine markers demonstrated the pleiotropism that controls more than two fiber traits. Furthermore, two SSR markers, BNL1231 and BNL3452, were authenticated as hotspots that were mapped with multi-traits. In addition, we provided candidate regions and screened six candidate genes for identified loci according to the LD decay distance. Our results provide valuable QTL for further genetic mapping and will facilitate marker-based breeding for fiber quality in cotton.

Comparative Genome-Wide-Association Mapping Identifies Common Loci Controlling Root System Architecture and Resistance to Aphanomyces euteiches in Pea

Combining plant genetic resistance with architectural traits that are unfavorable to disease development is a promising strategy for reducing epidemics. However, few studies have identified root system architecture (RSA) traits with the potential to limit root disease development. Pea is a major cultivated legume worldwide and has a wide level of natural genetic variability for plant architecture. The root pathogen Aphanomyces euteiches is a major limiting factor of pea crop yield. This study aimed to increase the knowledge on the diversity of loci and candidate genes controlling RSA traits in pea and identify RSA genetic loci associated with resistance to A. euteiches which could be combined with resistance QTL in breeding. A comparative genome wide association (GWA) study of plant architecture and resistance to A. euteiches was conducted at the young plant stage in a collection of 266 pea lines contrasted for both traits. The collection was genotyped using 14,157 SNP markers from recent pea genomic resources. It was phenotyped for ten root, shoot and overall plant architecture traits, as well as three disease resistance traits in controlled conditions, using image analysis. We identified a total of 75 short-size genomic intervals significantly associated with plant architecture and overlapping with 46 previously detected QTL. The major consistent intervals included plant shoot architecture or flowering genes (PsLE, PsTFL1) with putative pleiotropic effects on root architecture. A total of 11 genomic intervals were significantly associated with resistance to A. euteiches confirming several consistent previously identified major QTL. One significant SNP, mapped to the major QTL Ae-Ps7.6, was associated with both resistance and RSA traits. At this marker, the resistance-enhancing allele was associated with an increased total root projected area, in accordance with the correlation observed between resistance and larger root systems in the collection. Seven additional intervals associated with plant architecture overlapped with GWA intervals previously identified for resistance to A. euteiches. This study provides innovative results about genetic interdependency of root disease resistance and RSA inheritance. It identifies pea lines, QTL, closely-linked markers and candidate genes for marker-assisted-selection of RSA loci to reduce Aphanomyces root rot severity in future pea varieties.

Water Deficit and Salinity Stress Reveal Many Specific QTL for Plant Growth and Fruit Quality Traits in Tomato

Quality is a key trait in plant breeding, especially for fruit and vegetables. Quality involves several polygenic components, often influenced by environmental conditions with variable levels of genotype × environment interaction that must be considered in breeding strategies aiming to improve quality. In order to assess the impact of water deficit and salinity on tomato fruit quality, we evaluated a multi-parent advanced generation intercross (MAGIC) tomato population in contrasted environmental conditions over 2 years, one year in control vs. drought condition and the other in control vs. salt condition. Overall 250 individual lines from the MAGIC population-derived from eight parental lines covering a large diversity in cultivated tomato-were used to identify QTL in both experiments for fruit quality and yield component traits (fruit weight, number of fruit, Soluble Solid Content, firmness), phenology traits (time to flower and ripe) and a vegetative trait, leaf length. All the traits showed a large genotype variation (33-86% of total phenotypic variation) in both experiments and high heritability whatever the year or treatment. Significant genotype × treatment interactions were detected for five of the seven traits over the 2 years of experiments. QTL were mapped using 1,345 SNP markers. A total of 54 QTL were found among which 15 revealed genotype × environment interactions and 65% (35 QTL) were treatment specific. Confidence intervals of the QTL were projected on the genome physical map and allowed identifying regions carrying QTL co-localizations, suggesting pleiotropic regulation. We then applied a strategy for candidate gene detection based on the high resolution mapping offered by the MAGIC population, the allelic effect of each parental line at the QTL and the sequence information of the eight parental lines.

Cruz MT, Kumar A. Association Mapping of Yield and Yield-related Traits Under Reproductive Stage Drought Stress in Rice (Oryza sativa L.)

BACKGROUND

The identification and introgression of major-effect QTLs for grain yield under drought are some of the best and well-proven approaches for improving the drought tolerance of rice varieties. In the present study, we characterized Malaysian rice germplasm for yield and yield-related traits and identified significant trait marker associations by structured association mapping.

RESULTS

The drought screening was successful in screening germplasm with a yield reduction of up to 60% and heritability for grain yield under drought was up to 78%. There was a wider phenotypic and molecular diversity within the panel, indicating the suitability of the population for quantitative trait loci (QTL) mapping. Structure analyses clearly grouped the accessions into three subgroups with admixtures. Linkage disequilibrium (LD) analysis revealed that LD decreased with an increase in distance between marker pairs and the LD decay varied from 5-20 cM. The Mixed Linear model-based structured association mapping identified 80 marker trait associations (MTA) for grain yield (GY), plant height (PH) and days to flowering (DTF). Seven MTA were identified for GY under drought stress, four of these MTA were consistently identified in at least two of the three analyses. Most of these MTA identified were on chromosomes 2, 5, 10, 11 and 12, and their phenotypic variance (PV) varied from 5% to 19%. The in silico analysis of drought QTL regions revealed the association of several drought-responsive genes conferring drought tolerance. The major-effect QTLs are useful in marker-assisted QTL pyramiding to improve drought tolerance.

CONCLUSION

The results have clearly shown that structured association mapping is one of the feasible options to identify major-effect QTLs for drought tolerance-related traits in rice.

Association Mapping of Yield and Yield-related Traits Under Reproductive Stage Drought Stress in Rice (Oryza sativa L.)

BACKGROUND

The identification and introgression of major-effect QTLs for grain yield under drought are some of the best and well-proven approaches for improving the drought tolerance of rice varieties. In the present study, we characterized Malaysian rice germplasm for yield and yield-related traits and identified significant trait marker associations by structured association mapping.

RESULTS

The drought screening was successful in screening germplasm with a yield reduction of up to 60% and heritability for grain yield under drought was up to 78%. There was a wider phenotypic and molecular diversity within the panel, indicating the suitability of the population for quantitative trait loci (QTL) mapping. Structure analyses clearly grouped the accessions into three subgroups with admixtures. Linkage disequilibrium (LD) analysis revealed that LD decreased with an increase in distance between marker pairs and the LD decay varied from 5-20 cM. The Mixed Linear model-based structured association mapping identified 80 marker trait associations (MTA) for grain yield (GY), plant height (PH) and days to flowering (DTF). Seven MTA were identified for GY under drought stress, four of these MTA were consistently identified in at least two of the three analyses. Most of these MTA identified were on chromosomes 2, 5, 10, 11 and 12, and their phenotypic variance (PV) varied from 5% to 19%. The in silico analysis of drought QTL regions revealed the association of several drought-responsive genes conferring drought tolerance. The major-effect QTLs are useful in marker-assisted QTL pyramiding to improve drought tolerance.

CONCLUSION

The results have clearly shown that structured association mapping is one of the feasible options to identify major-effect QTLs for drought tolerance-related traits in rice.

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.

Approaches in Characterizing Genetic Structure and Mapping in a Rice Multiparental Population

Multi-parent Advanced Generation Intercross (MAGIC) populations are fast becoming mainstream tools for research and breeding, along with the technology and tools for analysis. This paper demonstrates the analysis of a rice MAGIC population from data filtering to imputation and processing of genetic data to characterizing genomic structure, and finally quantitative trait loci (QTL) mapping. In this study, 1316 S6:8 indica MAGIC (MI) lines and the eight founders were sequenced using Genotyping by Sequencing (GBS). As the GBS approach often includes missing data, the first step was to impute the missing SNPs. The observable number of recombinations in the population was then explored. Based on this case study, a general outline of procedures for a MAGIC analysis workflow is provided, as well as for QTL mapping of agronomic traits and biotic and abiotic stress, using the results from both association and interval mapping approaches. QTL for agronomic traits (yield, flowering time, and plant height), physical (grain length and grain width) and cooking properties (amylose content) of the rice grain, abiotic stress (submergence tolerance), and biotic stress (brown spot disease) were mapped. Through presenting this extensive analysis in the MI population in rice, we highlight important considerations when choosing analytical approaches. The methods and results reported in this paper will provide a guide to future genetic analysis methods applied to multi-parent populations.

Use of Natural Diversity and Biotechnology to Increase the Quality and Nutritional Content of Tomato and Grape

Improving fruit quality has become a major goal in plant breeding. Direct approaches to tackling fruit quality traits specifically linked to consumer preferences and environmental friendliness, such as improved flavor, nutraceutical compounds, and sustainability, have slowly been added to a breeder priority list that already includes traits like productivity, efficiency, and, especially, pest and disease control. Breeders already use molecular genetic tools to improve fruit quality although most advances have been made in producer and industrial quality standards. Furthermore, progress has largely been limited to simple agronomic traits easy-to-observe, whereas the vast majority of quality attributes, specifically those relating to flavor and nutrition, are complex and have mostly been neglected. Fortunately, wild germplasm, which is used for resistance against/tolerance of environmental stresses (including pathogens), is still available and harbors significant genetic variation for taste and health-promoting traits. Similarly, heirloom/traditional varieties could be used to identify which genes contribute to flavor and health quality and, at the same time, serve as a good source of the best alleles for organoleptic quality improvement. Grape (Vitis vinifera L.) and tomato (Solanum lycopersicum L.) produce fleshy, berry-type fruits, among the most consumed in the world. Both have undergone important domestication and selection processes, that have dramatically reduced their genetic variability, and strongly standardized fruit traits. Moreover, more and more consumers are asking for sustainable production, incompatible with the wide range of chemical inputs. In the present paper, we review the genetic resources available to tomato/grape breeders, and the recent technological progresses that facilitate the identification of genes/alleles of interest within the natural or generated variability gene pool. These technologies include omics, high-throughput phenotyping/phenomics, and biotech approaches. Our review also covers a range of technologies used to transfer to tomato and grape those alleles considered of interest for fruit quality. These include traditional breeding, TILLING (Targeting Induced Local Lesions in Genomes), genetic engineering, or NPBT (New Plant Breeding Technologies). Altogether, the combined exploitation of genetic variability and innovative biotechnological tools may facilitate breeders to improve fruit quality tacking more into account the consumer standards and the needs to move forward into more sustainable farming practices.

Genome-wide association mapping for seedling and field resistance to Puccinia striiformis f. sp. tritici in elite durum wheat

Genome-wide association analysis in tetraploid wheat revealed novel and diverse loci for seedling and field resistance to stripe rust in elite spring durum wheat accessions from worldwide. Improving resistance to stripe rust, caused by Puccinia striiformis f. sp. tritici, is a major objective for wheat breeding. To identify effective stripe rust resistance loci, a genome-wide association study (GWAS) was conducted using 232 elite durum wheat (Triticum turgidum ssp. durum) lines from worldwide breeding programs. Genotyping with the 90 K iSelect wheat single nucleotide polymorphism (SNP) array resulted in 11,635 markers distributed across the genome. Response to stripe rust infection at the seedling stage revealed resistant and susceptible accessions present in rather balanced frequencies for the six tested races, with a higher frequency of susceptible responses to United States races as compared to Italian races (61.1 vs. 43.1% of susceptible accessions). Resistance at the seedling stage only partially explained adult plant resistance, which was found to be more frequent with 67.7% of accessions resistant across six nurseries in the United States. GWAS identified 82 loci associated with seedling stripe rust resistance, five of which were significant at the false discovery rate adjusted P value <0.1 and 11 loci were detected for the field response at the adult plant stages in at least two environments. Notably, Yrdurum-1BS.1 showed the largest effect for both seedling and field resistance, and is therefore considered as a major locus for resistance in tetraploid wheat. Our GWAS study is the first of its kind for stripe rust resistance in tetraploid wheat and provides an overview of resistance in elite germplasm and reports new loci that can be used in breeding resistant cultivars.

Fine mapping of a major QTL for awn length in barley using a multiparent mapping population

Awn length was mapped using a multiparent population derived from cv. Morex and four wild accessions. One QTL was fine mapped and candidate genes were identified in NILs by RNA-seq. Barley awns are photosynthetically active and contribute to grain yield. Awn length is variable among both wild and cultivated barley genotypes and many mutants with alterations in awn length have been identified. Here, we used a multiparent mapping population derived from cv. Morex and four genetically diverse wild barley lines to detect quantitative trait loci (QTLs) for awn length. Twelve QTLs, distributed over the barley genome, were identified with the most significant one located on chromosome arm 7HL (QTL AL7.1). The effect of AL7.1 was confirmed using near isogenic lines (NILs) and fine-mapped in two independent heterogeneous inbred families to a < 0.9 cM interval. With exception of a small effect on grain width, no other traits such as plant height or flowering time were affected by AL7.1. Variant calling on transcripts obtained from RNA sequencing reads in NILs was used to narrow down the list of candidate genes located in the interval. This data may be used for further characterization and unravelling of the mechanisms underlying natural variation in awn length.

Genome-Wide Association Mapping of Flowering and Ripening Periods in Apple

Deciphering the genetic control of flowering and ripening periods in apple is essential for breeding cultivars adapted to their growing environments. We implemented a large Genome-Wide Association Study (GWAS) at the European level using an association panel of 1,168 different apple genotypes distributed over six locations and phenotyped for these phenological traits. The panel was genotyped at a high-density of SNPs using the Axiom®Apple 480 K SNP array. We ran GWAS with a multi-locus mixed model (MLMM), which handles the putatively confounding effect of significant SNPs elsewhere on the genome. Genomic regions were further investigated to reveal candidate genes responsible for the phenotypic variation. At the whole population level, GWAS retained two SNPs as cofactors on chromosome 9 for flowering period, and six for ripening period (four on chromosome 3, one on chromosome 10 and one on chromosome 16) which, together accounted for 8.9 and 17.2% of the phenotypic variance, respectively. For both traits, SNPs in weak linkage disequilibrium were detected nearby, thus suggesting the existence of allelic heterogeneity. The geographic origins and relationships of apple cultivars accounted for large parts of the phenotypic variation. Variation in genotypic frequency of the SNPs associated with the two traits was connected to the geographic origin of the genotypes (grouped as North+East, West and South Europe), and indicated differential selection in different growing environments. Genes encoding transcription factors containing either NAC or MADS domains were identified as major candidates within the small confidence intervals computed for the associated genomic regions. A strong microsynteny between apple and peach was revealed in all the four confidence interval regions. This study shows how association genetics can unravel the genetic control of important horticultural traits in apple, as well as reduce the confidence intervals of the associated regions identified by linkage mapping approaches. Our findings can be used for the improvement of apple through marker-assisted breeding strategies that take advantage of the accumulating additive effects of the identified SNPs.

Model-Assisted Estimation of the Genetic Variability in Physiological Parameters Related to Tomato Fruit Growth under Contrasted Water Conditions

Drought stress is a major abiotic stress threatening plant and crop productivity. In case of fleshy fruits, understanding mechanisms governing water and carbon accumulations and identifying genes, QTLs and phenotypes, that will enable trade-offs between fruit growth and quality under Water Deficit (WD) condition is a crucial challenge for breeders and growers. In the present work, 117 recombinant inbred lines of a population of Solanum lycopersicum were phenotyped under control and WD conditions. Plant water status, fruit growth and composition were measured and data were used to calibrate a process-based model describing water and carbon fluxes in a growing fruit as a function of plant and environment. Eight genotype-dependent model parameters were estimated using a multiobjective evolutionary algorithm in order to minimize the prediction errors of fruit dry and fresh mass throughout fruit development. WD increased the fruit dry matter content (up to 85%) and decreased its fresh weight (up to 60%), big fruit size genotypes being the most sensitive. The mean normalized root mean squared errors of the predictions ranged between 16-18% in the population. Variability in model genotypic parameters allowed us to explore diverse genetic strategies in response to WD. An interesting group of genotypes could be discriminated in which (i) the low loss of fresh mass under WD was associated with high active uptake of sugars and low value of the maximum cell wall extensibility, and (ii) the high dry matter content in control treatment (C) was associated with a slow decrease of mass flow. Using 501 SNP markers genotyped across the genome, a QTL analysis of model parameters allowed to detect three main QTLs related to xylem and phloem conductivities, on chromosomes 2, 4, and 8. The model was then applied to design ideotypes with high dry matter content in C condition and low fresh mass loss in WD condition. The ideotypes outperformed the RILs especially for large and medium fruit-size genotypes, by combining high pedicel conductance and high active uptake of sugars. Interestingly, five small fruit-size RILs were close to the selected ideotypes, and likely bear interesting traits and alleles for adaptation to WD.

Association mapping reveals the genetic architecture of tomato response to water deficit: focus on major fruit quality traits

Water scarcity constitutes a crucial constraint for agriculture productivity. High-throughput approaches in model plant species identified hundreds of genes potentially involved in survival under drought, but few having beneficial effects on quality and yield. Nonetheless, controlled water deficit may improve fruit quality through higher concentration of flavor compounds. The underlying genetic determinants are still poorly known. In this study, we phenotyped 141 highly diverse small fruit tomato accessions for 27 traits under two contrasting watering conditions. A subset of 55 accessions exhibited increased metabolite contents and maintained yield under water deficit. Using 6100 single nucleotide polymorphisms (SNPs), association mapping revealed 31, 41, and 44 quantitative trait loci (QTLs) under drought, control, and both conditions, respectively. Twenty-five additional QTLs were interactive between conditions, emphasizing the interest in accounting for QTLs by watering regime interactions in fruit quality improvement. Combining our results with the loci previously identified in a biparental progeny resulted in 11 common QTLs and contributed to a first detailed characterization of the genetic determinants of response to water deficit in tomato. Major QTLs for fruit quality traits were dissected and candidate genes were proposed using expression and polymorphism data. The outcomes provide a basis for fruit quality improvement under deficit irrigation while limiting yield losses.

Genome-wide association mapping of partial resistance to Aphanomyces euteiches in pea

BACKGROUND

Genome-wide association (GWA) mapping has recently emerged as a valuable approach for refining the genetic basis of polygenic resistance to plant diseases, which are increasingly used in integrated strategies for durable crop protection. Aphanomyces euteiches is a soil-borne pathogen of pea and other legumes worldwide, which causes yield-damaging root rot. Linkage mapping studies reported quantitative trait loci (QTL) controlling resistance to A. euteiches in pea. However the confidence intervals (CIs) of these QTL remained large and were often linked to undesirable alleles, which limited their application in breeding. The aim of this study was to use a GWA approach to validate and refine CIs of the previously reported Aphanomyces resistance QTL, as well as identify new resistance loci.

METHODS

A pea-Aphanomyces collection of 175 pea lines, enriched in germplasm derived from previously studied resistant sources, was evaluated for resistance to A. euteiches in field infested nurseries in nine environments and with two strains in climatic chambers. The collection was genotyped using 13,204 SNPs from the recently developed GenoPea Infinium® BeadChip.

RESULTS

GWA analysis detected a total of 52 QTL of small size-intervals associated with resistance to A. euteiches, using the recently developed Multi-Locus Mixed Model. The analysis validated six of the seven previously reported main Aphanomyces resistance QTL and detected novel resistance loci. It also provided marker haplotypes at 14 consistent QTL regions associated with increased resistance and highlighted accumulation of favourable haplotypes in the most resistant lines. Previous linkages between resistance alleles and undesired late-flowering alleles for dry pea breeding were mostly confirmed, but the linkage between loci controlling resistance and coloured flowers was broken due to the high resolution of the analysis. A high proportion of the putative candidate genes underlying resistance loci encoded stress-related proteins and others suggested that the QTL are involved in diverse functions.

CONCLUSION

This study provides valuable markers, marker haplotypes and germplasm lines to increase levels of partial resistance to A. euteiches in pea breeding.