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

Intelligent reprogramming of wheat for enhancement of fungal and nematode disease resistance using advanced molecular techniques

Wheat (Triticum aestivum L.) diseases are major factors responsible for substantial yield losses worldwide, which affect global food security. For a long time, plant breeders have been struggling to improve wheat resistance against major diseases by selection and conventional breeding techniques. Therefore, this review was conducted to shed light on various gaps in the available literature and to reveal the most promising criteria for disease resistance in wheat. However, novel techniques for molecular breeding in the past few decades have been very fruitful for developing broad-spectrum disease resistance and other important traits in wheat. Many types of molecular markers such as SCAR, RAPD, SSR, SSLP, RFLP, SNP, and DArT, etc., have been reported for resistance against wheat pathogens. This article summarizes various insightful molecular markers involved in wheat improvement for resistance to major diseases through diverse breeding programs. Moreover, this review highlights the applications of marker assisted selection (MAS), quantitative trait loci (QTL), genome wide association studies (GWAS) and the CRISPR/Cas-9 system for developing disease resistance against most important wheat diseases. We also reviewed all reported mapped QTLs for bunts, rusts, smuts, and nematode diseases of wheat. Furthermore, we have also proposed how the CRISPR/Cas-9 system and GWAS can assist breeders in the future for the genetic improvement of wheat. If these molecular approaches are used successfully in the future, they can be a significant step toward expanding food production in wheat crops.

Longer epidermal cells underlie a quantitative source of variation in wheat flag leaf size

The wheat flag leaf is the main contributor of photosynthetic assimilates to developing grains. Understanding how canopy architecture strategies affect source strength and yield will aid improved crop design. We used an eight-founder population to investigate the genetic architecture of flag leaf area, length, width and angle in European wheat. For the strongest genetic locus identified, we subsequently created a near-isogenic line (NIL) pair for more detailed investigation across seven test environments. Genetic control of traits investigated was highly polygenic, with colocalisation of replicated quantitative trait loci (QTL) for one or more traits identifying 24 loci. For QTL QFll.niab-5A.1 (FLL5A), development of a NIL pair found the FLL5A+ allele commonly conferred a c. 7% increase in flag and second leaf length and a more erect leaf angle, resulting in higher flag and/or second leaf area. Increased FLL5A-mediated flag leaf length was associated with: (1) longer pavement cells and (2) larger stomata at lower density, with a trend for decreased maximum stomatal conductance (G_smax ) per unit leaf area. For FLL5A, cell size rather than number predominantly determined leaf length. The observed trade-offs between leaf size and stomatal morphology highlight the need for future studies to consider these traits at the whole-leaf level.

Functional Allele Validation by Gene Editing to Leverage the Wealth of Genetic Resources for Crop Improvement

Advances in molecular technologies over the past few decades, such as high-throughput DNA marker genotyping, have provided more powerful plant breeding approaches, including marker-assisted selection and genomic selection. At the same time, massive investments in plant genetics and genomics, led by whole genome sequencing, have led to greater knowledge of genes and genetic pathways across plant genomes. However, there remains a gap between approaches focused on forward genetics, which start with a phenotype to map a mutant locus or QTL with the goal of cloning the causal gene, and approaches using reverse genetics, which start with large-scale sequence data and work back to the gene function. The recent establishment of efficient CRISPR-Cas-based gene editing promises to bridge this gap and provide a rapid method to functionally validate genes and alleles identified through studies of natural variation. CRISPR-Cas techniques can be used to knock out single or multiple genes, precisely modify genes through base and prime editing, and replace alleles. Moreover, technologies such as protoplast isolation, in planta transformation, and the use of developmental regulatory genes promise to enable high-throughput gene editing to accelerate crop improvement.

A combinatorial strategy to identify various types of QTLs for quantitative traits using extreme phenotype individuals in an F2 population

Theoretical and applied studies demonstrate the difficulty of detecting extremely over-dominant and small-effect genes for quantitative traits via bulked segregant analysis (BSA) in an F₂ population. To address this issue, we proposed an integrated strategy for mapping various types of quantitative trait loci (QTLs) for quantitative traits via a combination of BSA and whole-genome sequencing. In this strategy, the numbers of read counts of marker alleles in two extreme pools were used to predict the numbers of read counts of marker genotypes. These observed and predicted numbers were used to construct a new statistic, G_w, for detecting quantitative trait genes (QTGs), and the method was named dQTG-seq1. This method was significantly better than existing BSA methods. If the goal was to identify extremely over-dominant and small-effect genes, another reserved DNA/RNA sample from each extreme phenotype F₂ plant was sequenced, and the observed numbers of marker alleles and genotypes were used to calculate G_w to detect QTGs; this method was named dQTG-seq2. In simulated and real rice dataset analyses, dQTG-seq2 could identify many more extremely over-dominant and small-effect genes than BSA and QTL mapping methods. dQTG-seq2 may be extended to other heterogeneous mapping populations. The significance threshold of G_w in this study was determined by permutation experiments. In addition, a handbook for the R software dQTG.seq, which is available at https://cran.r-project.org/web/packages/dQTG.seq/index.html, has been provided in the supplemental materials for the users' convenience. This study provides a new strategy for identifying all types of QTLs for quantitative traits in an F₂ population.

Five plants per RIL for phenotyping traits of high or moderate heritability ensure the power of QTL mapping in a rice MAGIC population

Currently, the power of QTL mapping is mainly dependent on the quality of phenotypic data in a given population, regardless of the statistical method, as the quality of genotypic data is easily guaranteed in the laboratory. Increasing the sample size per line used for phenotyping is a good way to improve the quality of phenotypic data. However, accommodating a large-scale mapping population takes a large area of rice field, which frequently results in high costs and extra environmental noises. To acquire a reasonable small sample size without a penalty in mapping power, we conducted three experiments with a 4-way MAGIC population and measured phenotypes of 5, 10, and 20 plants per RIL. Three traits including heading date, plant height, and tillers per plant were focused. With SNP- and bin-based QTL mapping, 3 major and 3 minor QTLs for heading date with high heritability and 2 major QTLs for plant height with moderate heritability were commonly detected across the three experiments, but no QTL for tillers per plant with low heritability were commonly identified. In addition, bin-based QTL mapping was more powerful than SNP-based mapping and able to rank the genetic effects of parental alleles. Thus, 5 plants per RIL for phenotyping ensure the power of QTL mapping for traits of high or moderate heritability, and bin-based QTL mapping is recommended for multiparent populations.

Genome-wide association mapping of Hagberg falling number, protein content, test weight, and grain yield in U.K. wheat

Association mapping using crop cultivars allows identification of genetic loci of direct relevance to breeding. Here, 150 U.K. wheat (Triticum aestivum L.) cultivars genotyped with 23,288 single nucleotide polymorphisms (SNPs) were used for genome-wide association studies (GWAS) using historical phenotypic data for grain protein content, Hagberg falling number (HFN), test weight, and grain yield. Power calculations indicated experimental design would enable detection of quantitative trait loci (QTL) explaining ≥20% of the variation (PVE) at a relatively high power of >80%, falling to 40% for detection of a SNP with an R² ≥ .5 with the same QTL. Genome-wide association studies identified marker-trait associations for all four traits. For HFN (h ² = .89), six QTL were identified, including a major locus on chromosome 7B explaining 49% PVE and reducing HFN by 44 s. For protein content (h ² = 0.86), 10 QTL were found on chromosomes 1A, 2A, 2B, 3A, 3B, and 6B, together explaining 48.9% PVE. For test weight, five QTL were identified (one on 1B and four on 3B; 26.3% PVE). Finally, 14 loci were identified for grain yield (h ² = 0.95) on eight chromosomes (1A, 2A, 2B, 2D, 3A, 5B, 6A, 6B; 68.1% PVE), of which five were located within 16 Mbp of genetic regions previously identified as under breeder selection in European wheat. Our study demonstrates the utility of exploiting historical crop datasets, identifying genomic targets for independent validation, and ultimately for wheat genetic improvement.

Wheat genetic loci conferring resistance to stripe rust in the face of genetically diverse races of the fungus Puccinia striiformis f. sp. tritici

KEY MESSAGE

Analysis of a wheat multi-founder population identified 14 yellow rust resistance QTL. For three of the four most significant QTL, haplotype analysis indicated resistance alleles were rare in European wheat. Stripe rust, or yellow rust (YR), is a major fungal disease of wheat (Triticum aestivum) caused by Puccinia striiformis Westend f. sp. tritici (Pst). Since 2011, the historically clonal European Pst races have been superseded by the rapid incursion of genetically diverse lineages, reducing the resistance of varieties previously showing durable resistance. Identification of sources of genetic resistance to such races is a high priority for wheat breeding. Here we use a wheat eight-founder multi-parent population genotyped with a 90,000 feature single nucleotide polymorphism array to genetically map YR resistance to such new Pst races. Genetic analysis of five field trials at three UK sites identified 14 quantitative trait loci (QTL) conferring resistance. Of these, four highly significant loci were consistently identified across all test environments, located on chromosomes 1A (QYr.niab-1A.1), 2A (QYr.niab-2A.1), 2B (QYr.niab-2B.1) and 2D (QYr.niab-2D.1), together explaining ~ 50% of the phenotypic variation. Analysis of these four QTL in two-way and three-way combinations showed combinations conferred greater resistance than single QTL, and genetic markers were developed that distinguished resistant and susceptible alleles. Haplotype analysis in a collection of wheat varieties found that the haplotypes associated with YR resistance at three of these four major loci were rare (≤ 7%) in European wheat, highlighting their potential utility for future targeted improvement of disease resistance. Notably, the physical interval for QTL QYr.niab-2B.1 contained five nucleotide-binding leucine-rich repeat candidate genes with integrated BED domains, of which two corresponded to the cloned resistance genes Yr7 and Yr5/YrSp.

Breeding Canola (Brassica napus L.) for Protein in Feed and Food

Interest in canola (Brassica napus L.). In response to this interest, scientists have been tasked with altering and optimizing the protein production chain to ensure canola proteins are safe for consumption and economical to produce. Specifically, the role of plant breeders in developing suitable varieties with the necessary protein profiles is crucial to this interdisciplinary endeavour. In this article, we aim to provide an overarching review of the canola protein chain from the perspective of a plant breeder, spanning from the genetic regulation of seed storage proteins in the crop to advancements of novel breeding technologies and their application in improving protein quality in canola. A review on the current uses of canola meal in animal husbandry is presented to underscore potential limitations for the consumption of canola meal in mammals. General discussions on the allergenic potential of canola proteins and the regulation of novel food products are provided to highlight some of the challenges that will be encountered on the road to commercialization and general acceptance of canola protein as a dietary protein source.

Genome-wide association studies: assessing trait characteristics in model and crop plants

GWAS involves testing genetic variants across the genomes of many individuals of a population to identify genotype–phenotype association. It was initially developed and has proven highly successful in human disease genetics. In plants genome-wide association studies (GWAS) initially focused on single feature polymorphism and recombination and linkage disequilibrium but has now been embraced by a plethora of different disciplines with several thousand studies being published in model and crop species within the last decade or so. Here we will provide a comprehensive review of these studies providing cases studies on biotic resistance, abiotic tolerance, yield associated traits, and metabolic composition. We also detail current strategies of candidate gene validation as well as the functional study of haplotypes. Furthermore, we provide a critical evaluation of the GWAS strategy and its alternatives as well as future perspectives that are emerging with the emergence of pan-genomic datasets.

Crop breeding for a changing climate: integrating phenomics and genomics with bioinformatics

Safeguarding crop yields in a changing climate requires bioinformatics advances in harnessing data from vast phenomics and genomics datasets to translate research findings into climate smart crops in the field. Climate change and an additional 3 billion mouths to feed by 2050 raise serious concerns over global food security. Crop breeding and land management strategies will need to evolve to maximize the utilization of finite resources in coming years. High-throughput phenotyping and genomics technologies are providing researchers with the information required to guide and inform the breeding of climate smart crops adapted to the environment. Bioinformatics has a fundamental role to play in integrating and exploiting this fast accumulating wealth of data, through association studies to detect genomic targets underlying key adaptive climate-resilient traits. These data provide tools for breeders to tailor crops to their environment and can be introduced using advanced selection or genome editing methods. To effectively translate research into the field, genomic and phenomic information will need to be integrated into comprehensive clade-specific databases and platforms alongside accessible tools that can be used by breeders to inform the selection of climate adaptive traits. Here we discuss the role of bioinformatics in extracting, analysing, integrating and managing genomic and phenomic data to improve climate resilience in crops, including current, emerging and potential approaches, applications and bottlenecks in the research and breeding pipeline.

Regions of Chromosome 2A of Bread Wheat (Triticum aestivum L.) Associated with Variation in Physiological and Agronomical Traits under Contrasting Water Regimes

Understanding the genetic architecture of drought tolerance is of great importance for overcoming the negative impact of drought on wheat yield. Earlier, we discovered the critical role of chromosome 2A for the drought-tolerant status of wheat spring cultivar Saratovskaya 29. A set of 92 single-chromosome recombinant double haploid (SCRDH) lines were obtained in the genetic background of Saratovskaya 29. The lines carry fragments of chromosome 2A from the drought-sensitive cultivar Yanetzkis Probat. The SCRDH lines were used to identify regions on chromosome 2A associated with the manifestation of physiological and agronomical traits under distinct water supply, and to identify candidate genes that may be associated with adaptive gene networks in wheat. Genotyping was done with Illumina Infinium 15k wheat array using 590 SNP markers with 146 markers being polymorphic. In four identified regions of chromosome 2A, 53 out of 58 QTLs associated with physiological and agronomic traits under contrasting water supply were mapped. Thirty-nine candidate genes were identified, of which 18 were transcription factors. The region 73.8-78.1 cM included the largest number of QTLs and candidate genes. The variation in SNPs associated with agronomical and physiological traits revealed among the SCRDH lines may provide useful information for drought related marker-assisted breeding.

Genetic mapping of pollen fertility restoration QTLs in rye (Secale cereale L.) with CMS Pampa

Cytoplasmic male sterility (CMS) is a widely applied plant breeding tool for hybrid seed production. The phenomenon is often caused by chimeric genes with altered open reading frames (ORFs) located in the mitochondrial genomes and expressed as novel genotoxic products that induce pollen abortion. The fertility of CMS plants can be restored by nuclear-encoded genes that inhibit the action of ORFs responsible for pollen sterility. A recombinant inbred line (RIL) mapping population S64/04/01, encompassing 175 individuals, was used for genetic map construction and identification of quantitative trait loci (QTLs) responsible for fertility restoration in rye (Secale cereale L.) with CMS Pampa. The genetic map of all seven rye chromosomes included 15,516 SNP and silicoDArT markers and covered 1070.5 cm. Individual QTLs explaining 60% and 5.5% of the fertility trait’s phenotypic variance were mapped to chromosomes 4R (QRft-4R) and 5R (QRft-5R), respectively. Association mapping identified markers with the highest R² value of 0.58 (p value = 2.21E-28). Markers showing the highest associations with the trait were also mapped to the 4R chromosome within the QRft-4R region. Based on marker sequence homology, putative genes involved in pollen fertility restoration were suggested. Five silicoDArTs were converted into PCR-based markers for further breeding purposes.

Identification and cross-validation of genetic loci conferring resistance to Septoria nodorum blotch using a German multi-founder winter wheat population

We identified allelic variation at two major loci, QSnb.nmbu-2A.1 and QSnb.nmbu-5A.1, showing consistent and additive effects on SNB field resistance. Validation of QSnb.nmbu-2A.1 across genetic backgrounds further highlights its usefulness for marker-assisted selection. Septoria nodorum blotch (SNB) is a disease of wheat (Triticum aestivum and T. durum) caused by the necrotrophic fungal pathogen Parastagonospora nodorum. SNB resistance is a typical quantitative trait, controlled by multiple quantitative trait loci (QTL) of minor effect. To achieve increased plant resistance, selection for resistance alleles and/or selection against susceptibility alleles must be undertaken. Here, we performed genetic analysis of SNB resistance using an eight-founder German Multiparent Advanced Generation Inter-Cross (MAGIC) population, termed BMWpop. Field trials and greenhouse testing were conducted over three seasons in Norway, with genetic analysis identifying ten SNB resistance QTL. Of these, two QTL were identified over two seasons: QSnb.nmbu-2A.1 on chromosome 2A and QSnb.nmbu-5A.1 on chromosome 5A. The chromosome 2A BMWpop QTL co-located with a robust SNB resistance QTL recently identified in an independent eight-founder MAGIC population constructed using varieties released in the United Kingdom (UK). The validation of this SNB resistance QTL in two independent multi-founder mapping populations, regardless of the differences in genetic background and agricultural environment, highlights the value of this locus in SNB resistance breeding. The second robust QTL identified in the BMWpop, QSnb.nmbu-5A.1, was not identified in the UK MAGIC population. Combining resistance alleles at both loci resulted in additive effects on SNB resistance. Therefore, using marker assisted selection to combine resistance alleles is a promising strategy for improving SNB resistance in wheat breeding. Indeed, the multi-locus haplotypes determined in this study provide markers for efficient tracking of these beneficial alleles in future wheat genetics and breeding activities.

Fine-Mapping of a Wild Genomic Region Involved in Pod and Seed Size Reduction on Chromosome A07 in Peanut (Arachis hypogaea L.)

Fruit and seed size are important yield component traits that have been selected during crop domestication. In previous studies, Advanced Backcross Quantitative Trait Loci (AB-QTL) and Chromosome Segment Substitution Line (CSSL) populations were developed in peanut by crossing the cultivated variety Fleur11 and a synthetic wild allotetraploid (Arachis ipaensis × Arachis duranensis)^4x. In the AB-QTL population, a major QTL for pod and seed size was detected in a ~5 Mb interval in the proximal region of chromosome A07. In the CSSL population, the line 12CS_091, which carries the QTL region and that produces smaller pods and seeds than Fleur11, was identified. In this study, we used a two-step strategy to fine-map the seed size QTL region on chromosome A07. We developed new SSR and SNP markers, as well as near-isogenic lines (NILs) in the target QTL region. We first located the QTL in ~1 Mb region between two SSR markers, thanks to the genotyping of a large F₂ population of 2172 individuals and a single marker analysis approach. We then used nine new SNP markers evenly distributed in the refined QTL region to genotype 490 F₃ plants derived from 88 F₂, and we selected 10 NILs. The phenotyping of the NILs and marker/trait association allowed us to narrowing down the QTL region to a 168.37 kb chromosome segment, between the SNPs Aradu_A07_1148327 and Aradu_A07_1316694. This region contains 22 predicted genes. Among these genes, Aradu.DN3DB and Aradu.RLZ61, which encode a transcriptional regulator STERILE APETALA-like (SAP) and an F-box SNEEZY (SNE), respectively, were of particular interest. The function of these genes in regulating the variation of fruit and seed size is discussed. This study will contribute to a better knowledge of genes that have been targeted during peanut domestication.

QTL mapping for soybean (Glycine max L.) leaf chlorophyll-content traits in a genotyped RIL population by using RAD-seq based high-density linkage map

BACKGROUND

Different soybean (Glycine max L.) leaf chlorophyll-content traits are considered to be significantly linked to soybean yield. To map the quantitative trait loci (QTLs) of soybean leaf chlorophyll-content traits, an advanced recombinant inbred line (RIL, ZH, Zhonghuang 24 × Huaxia 3) population was adopted to phenotypic data acquisitions for the target traits across six distinct environments (seasons and soybean growth stages). Moreover, the restriction site-associated DNA sequencing (RAD-seq) based high-density genetic linkage map of the RIL population was utilized for QTL mapping by carrying out the composite interval mapping (CIM) approach.

RESULTS

Correlation analyses showed that most traits were correlated with each other under specific chlorophyll assessing method and were regulated both by hereditary and environmental factors. In this study, 78 QTLs for soybean leaf chlorophyll-content traits were identified. Furthermore, 13 major QTLs and five important QTL hotspots were classified and highlighted from the detected QTLs. Finally, Glyma01g15506, Glyma02g08910, Glyma02g11110, Glyma07g15960, Glyma15g19670 and Glyma15g19810 were predicted from the genetic intervals of the major QTLs and important QTL hotspots.

CONCLUSIONS

The detected QTLs and candidate genes may facilitate to gain a better understanding of the hereditary basis of soybean leaf chlorophyll-content traits and may be valuable to pave the way for the marker-assisted selection (MAS) breeding of the target traits.

Genetic Analysis Using a Multi-Parent Wheat Population Identifies Novel Sources of Septoria Tritici Blotch Resistance

Zymoseptoria tritici is the causative fungal pathogen of septoria tritici blotch (STB) disease of wheat (Triticum aestivum L.) that continuously threatens wheat crops in Ireland and throughout Europe. Under favorable conditions, STB can cause up to 50% yield losses if left untreated. STB is commonly controlled with fungicides; however, a combination of Z. tritici populations developing fungicide resistance and increased restrictions on fungicide use in the EU has led to farmers relying on fewer active substances. Consequently, this serves to drive the emergence of Z. tritici resistance against the remaining chemistries. In response, the use of resistant wheat varieties provides a more sustainable disease management strategy. However, the number of varieties offering an adequate level of resistance against STB is limited. Therefore, new sources of resistance or improved stacking of existing resistance loci are needed to develop varieties with superior agronomic performance. Here, we identified quantitative trait loci (QTL) for STB resistance in the eight-founder "NIAB Elite MAGIC" winter wheat population. The population was screened for STB response in the field under natural infection for three seasons from 2016 to 2018. Twenty-five QTL associated with STB resistance were identified in total. QTL either co-located with previously reported QTL or represent new loci underpinning STB resistance. The genomic regions identified and the linked genetic markers serve as useful resources for STB resistance breeding, supporting rapid selection of favorable alleles for the breeding of new wheat cultivars with improved STB resistance.

Genetic Characterization of a Wheat Association Mapping Panel Relevant to Brazilian Breeding Using a High-Density Single Nucleotide Polymorphism Array

Bread wheat (Triticum aestivum L.) is one of the world’s most important crops. Maintaining wheat yield gains across all of its major production areas is a key target toward underpinning global food security. Brazil is a major wheat producer in South America, generating grain yields of around 6.8 million tons per year. Here, we establish and genotype a wheat association mapping resource relevant to contemporary Brazilian wheat breeding programs. The panel of 558 wheat accessions was genotyped using an Illumina iSelect 90,000 single nucleotide polymorphism array. Following quality control, the final data matrix consisted of 470 accessions and 22,475 polymorphic genetic markers (minor allele frequency ≥5%, missing data <5%). Principal component analysis identified distinct differences between materials bred predominantly for the northern Cerrado region, compared to those bred for southern Brazilian agricultural areas. We augmented the genotypic data with 26 functional Kompetitive Allele-Specific PCR (KASP) markers to identify the allelic combinations at genes with previously known effects on agronomically important traits in the panel. This highlighted breeding targets for immediate consideration – notably, increased Fusarium head blight resistance via the Fhb1 locus. To demonstrate the panel’s likely future utility, genome-wide association scans for several phenotypic traits were undertaken. Significant (Bonferroni corrected P < 0.05) marker-trait associations were detected for Fusarium kernel damage (a proxy for type 2 Fusarium resistance), identifying previously known quantitative trait loci in the panel. This association mapping panel represents an important resource for Brazilian wheat breeding, allowing future genetic studies to analyze multiple agronomic traits within a single genetically diverse population.

Combining focused identification of germplasm and core collection strategies to identify genebank accessions for central European soybean breeding

Environmental adaptation of crops is essential for reliable agricultural production and an important breeding objective. Genebanks provide genetic variation for the improvement of modern varieties, but the selection of suitable germplasm is frequently impeded by incomplete phenotypic data. We address this bottleneck by combining a Focused Identification of Germplasm Strategy (FIGS) with core collection methodology to select soybean (Glycine max) germplasm for Central European breeding from a collection of >17,000 accessions. By focussing on adaptation to high-latitude cold regions, we selected an "environmental precore" of 3,663 accessions using environmental data and compared the Donor opulation of Environments (DPE) in Asia and the Target Population of Environments (TPE) in Central Europe in the present and 2070. Using single nucleotide polymorphisms, we reduced the precore into two diverse core collections of 183 and 366 accessions to serve as diversity panels for evaluation in the TPE. Genetic differentiation between precore and non-precore accessions revealed genomic regions that control maturity, and novel candidate loci for environmental adaptation, demonstrating the potential of diversity panels for studying adaptation. Objective-driven core collections have the potential to increase germplasm utilization for abiotic adaptation by breeding for a rapidly changing climate, or de novo adaptation of crops to expand cultivation ranges.

Identificación de polimorfismos en el gen <i>RXAM1</i> de yuca y su asociación con la resistencia a la bacteriosis vascular

La yuca (Manihot esculenta Crantz) es un cultivo importante en regiones del trópico que proporciona alimento para cerca de 1000 millones de personas en todo el mundo. La enfermedad bacteriana más importante es la bacteriosis vascular causada por Xanthomonas axonopodis pv. manihotis (Xam). Recientemente se logró identificar un gen de resistencia denominado RXAM1, el cual codifica para una proteína que posee un dominio LRR (Leucine-Rich Repeat) extracelular y un dominio STK (Serine Threonine Kinase) citoplasmático. RXAM1 colocaliza con un QTL que explica el 13 % de la resistencia a la cepa CIO136 de Xam. En este trabajo se evaluó la respuesta a la infección con la cepa XamCIO136 en diez diferentes variedades de yuca lo cual permitió identificar que las variedades TMS60444, SG10735, MCOL1522, MCOL1505 y MCOL2215 fueron susceptibles, mientras que CM6438-14, CM523-7 y MBRA902 se comportaron como resistentes. Así mismo se identificaron polimorfismos tipo SNPs (Single Nucleotide Polymorphism) en el gen RXAM1 en el mismo grupo de variedades. Las variedades SG10735, CM6438-14, TMS6044 y MBRA685 presentaron el mayor nivel de polimorfismos, mientras que las variedades CM523-7, CM2177-2 y MCOL1522 fueron menos polimórficas para este gen. Los análisis estadísticos no permitieron identificar una asociación significativa entre el fenotipo y los polimorfismos identificados. Este estudio representa un primer esfuerzo con miras a asociar variantes alélicas con el fenotipo de respuesta a la bacteriosis vascular.

The Position and Complex Genomic Architecture of Plant T-DNA Insertions Revealed by 4SEE

The integration of T-DNA in plant genomes is widely used for basic research and agriculture. The high heterogeneity in the number of integration events per genome, their configuration, and their impact on genome integrity highlight the critical need to detect the genomic locations of T-DNA insertions and their associated chromosomal rearrangements, and the great challenge in doing so. Here, we present 4SEE, a circular chromosome conformation capture (4C)-based method for robust, rapid, and cost-efficient detection of the entire scope of T-DNA locations. Moreover, by measuring the chromosomal architecture of the plant genome flanking the T-DNA insertions, 4SEE outlines their associated complex chromosomal aberrations. Applying 4SEE to a collection of confirmed T-DNA lines revealed previously unmapped T-DNA insertions and chromosomal rearrangements such as inversions and translocations. Uncovering such events in a feasible, robust, and cost-effective manner by 4SEE in any plant of interest has implications for accurate annotation and phenotypic characterization of T-DNA insertion mutants and transgene expression in basic science applications as well as for plant biotechnology.

A roadmap for gene functional characterisation in crops with large genomes: Lessons from polyploid wheat

Understanding the function of genes within staple crops will accelerate crop improvement by allowing targeted breeding approaches. Despite their importance, a lack of genomic information and resources has hindered the functional characterisation of genes in major crops. The recent release of high-quality reference sequences for these crops underpins a suite of genetic and genomic resources that support basic research and breeding. For wheat, these include gene model annotations, expression atlases and gene networks that provide information about putative function. Sequenced mutant populations, improved transformation protocols and structured natural populations provide rapid methods to study gene function directly. We highlight a case study exemplifying how to integrate these resources. This review provides a helpful guide for plant scientists, especially those expanding into crop research, to capitalise on the discoveries made in Arabidopsis and other plants. This will accelerate the improvement of crops of vital importance for food and nutrition security.

Genome-Wide Association Study in Two Cohorts from a Multi-generational Mouse Advanced Intercross Line Highlights the Difficulty of Replication Due to Study-Specific Heterogeneity

There has been extensive discussion of the "Replication Crisis" in many fields, including genome-wide association studies (GWAS). We explored replication in a mouse model using an advanced intercross line (AIL), which is a multigenerational intercross between two inbred strains. We re-genotyped a previously published cohort of LG/J x SM/J AIL mice (F34; n = 428) using a denser marker set and genotyped a new cohort of AIL mice (F39-43; n = 600) for the first time. We identified 36 novel genome-wide significant loci in the F34 and 25 novel loci in the F39-43 cohort. The subset of traits that were measured in both cohorts (locomotor activity, body weight, and coat color) showed high genetic correlations, although the SNP heritabilities were slightly lower in the F39-43 cohort. For this subset of traits, we attempted to replicate loci identified in either F34 or F39-43 in the other cohort. Coat color was robustly replicated; locomotor activity and body weight were only partially replicated, which was inconsistent with our power simulations. We used a random effects model to show that the partial replications could not be explained by Winner's Curse but could be explained by study-specific heterogeneity. Despite this heterogeneity, we performed a mega-analysis by combining F34 and F39-43 cohorts (n = 1,028), which identified four novel loci associated with locomotor activity and body weight. These results illustrate that even with the high degree of genetic and environmental control possible in our experimental system, replication was hindered by study-specific heterogeneity, which has broad implications for ongoing concerns about reproducibility.

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.

Advances in Omics Approaches for Abiotic Stress Tolerance in Tomato

Tomato, one of the most important crops worldwide, has a high demand in the fresh fruit market and processed food industries. Despite having considerably high productivity, continuous supply as per the market demand is hard to achieve, mostly because of periodic losses occurring due to biotic as well as abiotic stresses. Although tomato is a temperate crop, it is grown in almost all the climatic zones because of widespread demand, which makes it challenge to adapt in diverse conditions. Development of tomato cultivars with enhanced abiotic stress tolerance is one of the most sustainable approaches for its successful production. In this regard, efforts are being made to understand the stress tolerance mechanism, gene discovery, and interaction of genetic and environmental factors. Several omics approaches, tools, and resources have already been developed for tomato growing. Modern sequencing technologies have greatly accelerated genomics and transcriptomics studies in tomato. These advancements facilitate Quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS). However, limited efforts have been made in other omics branches like proteomics, metabolomics, and ionomics. Extensive cataloging of omics resources made here has highlighted the need for integration of omics approaches for efficient utilization of resources and a better understanding of the molecular mechanism. The information provided here will be helpful to understand the plant responses and the genetic regulatory networks involved in abiotic stress tolerance and efficient utilization of omics resources for tomato crop improvement.

A Genetic Dissection of Natural Variation for Stomatal Abundance Traits in Arabidopsis

Stomatal abundance varies widely across natural populations of Arabidopsis thaliana, and presumably affects plant performance because it influences water and CO2 exchange with the atmosphere and thence photosynthesis and transpiration. In order to determine the genetic basis of this natural variation, we have analyzed a recombinant inbred line (RIL) population derived from the wild accession Ll-0 and the reference strain Landsberg erecta (Ler), which show low and high stomatal abundance, respectively. Quantitative trait locus (QTL) analyses of stomatal index, stomatal density, and pavement cell density measured in the adaxial cotyledon epidermis, identified five loci. Three of the genomic regions affect all traits and were named MID (Modulator of Cell Index and Density) 1 to 3. MID2 is a large-effect QTL overlapping with ERECTA (ER), the er-1 allele from Ler increasing all trait values. Additional analyses of natural and induced loss-of-function er mutations in different genetic backgrounds revealed that ER dysfunctions have differential and opposite effects on the stomatal index in adaxial and abaxial cotyledon epidermis and confirmed that ER is the gene underlying MID2. Ll-0 alleles at MID1 and MID3 displayed moderate and positive effects on the various traits. Furthermore, detailed developmental studies tracking primary and satellite stomatal lineages show that MID3-Ll-0 allele promotes the spacing divisions that initiate satellite lineages, while the ER allele limits them. Finally, expression analyses suggest that ER and MID3 modulate satellization through partly different regulatory pathways. Our characterization of MID3 indicates that genetic modulation of satellization contributes to the variation for stomatal abundance in natural populations, and subsequently that this trait might be involved in plant adaptation.

Genomic index selection provides a pragmatic framework for setting and refining multi-objective breeding targets in Miscanthus

BACKGROUND

Miscanthus has potential as a biomass crop but the development of varieties that are consistently superior to the natural hybrid M. × giganteus has been challenging, presumably because of strong G × E interactions and poor knowledge of the complex genetic architectures of traits underlying biomass productivity and climatic adaptation. While linkage and association mapping studies are starting to generate long lists of candidate regions and even individual genes, it seems unlikely that this information can be translated into effective marker-assisted selection for the needs of breeding programmes. Genomic selection has emerged as a viable alternative, and prediction accuracies are moderate across a range of phenological and morphometric traits in Miscanthus, though relatively low for biomass yield per se.

METHODS

We have previously proposed a combination of index selection and genomic prediction as a way of overcoming the limitations imposed by the inherent complexity of biomass yield. Here we extend this approach and illustrate its potential to achieve multiple breeding targets simultaneously, in the absence of a priori knowledge about their relative economic importance, while also monitoring correlated selection responses for non-target traits. We evaluate two hypothetical scenarios of increasing biomass yield by 20 % within a single round of selection. In the first scenario, this is achieved in combination with delaying flowering by 44 d (roughly 20 %), whereas, in the second, increased yield is targeted jointly with reduced lignin (-5 %) and increased cellulose (+5 %) content, relative to current average levels in the breeding population.

KEY RESULTS

In both scenarios, the objectives were achieved efficiently (selection intensities corresponding to keeping the best 20 and 4 % of genotypes, respectively). However, the outcomes were strikingly different in terms of correlated responses, and the relative economic values (i.e. value per unit of change in each trait compared with that for biomass yield) of secondary traits included in selection indices varied considerably.

CONCLUSIONS

Although these calculations rely on multiple assumptions, they highlight the need to evaluate breeding objectives and explicitly consider correlated responses in silico, prior to committing extensive resources. The proposed approach is broadly applicable for this purpose and can readily incorporate high-throughput phenotyping data as part of integrated breeding platforms.

Genome-wide association analysis of nutrient traits in the oyster Crassostrea gigas: genetic effect and interaction network

Background

Oyster is rich in glycogen and free amino acids and is called “the milk of sea”. To understand the main genetic effects of these traits and the genetic networks underlying their correlation, we have conducted the whole genome resequencing with 427 oysters collected from the world-wide scale.

Results

After association analysis, 168 clustered significant single nucleotide polymorphism (SNP) loci were identified for glycogen content and 17 SNPs were verified with 288 oyster individuals in another wide populations. These were the most important candidate loci for oyster breeding. Among 24 genes in the 100-kb regions of the leading SNP loci, cytochrome P450 17A1 (CYP17A1) contained a non-synonymous SNP and displayed higher expressions in high glycogen content individuals. This might enhance the gluconeogenesis process by the transcriptionally regulating the expression of phosphoenolpyruvate carboxykinase (PEPCK) and glucose 6-phosphatase (G6Pase). Also, for amino acids content, 417 clustered significant SNPs were identified. After genetic network analysis, three node SNP regions were identified to be associated with glycogen, protein, and Asp content, which might explain their significant correlation.

Conclusion

Overall, this study provides insights into the genetic correlation among complex traits, which will facilitate future oyster functional studies and breeding through molecular design.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5971-z) contains supplementary material, which is available to authorized users.

μCT trait analysis reveals morphometric differences between domesticated temperate small grain cereals and their wild relatives

Wheat and barley are two of the founder crops domesticated in the Fertile Crescent, and currently represent crops of major economic importance in temperate regions. Due to impacts on yield, quality and end-use, grain morphometric traits remain an important goal for modern breeding programmes and are believed to have been selected for by human populations. To directly and accurately assess the three-dimensional (3D) characteristics of grains, we combine X-ray microcomputed tomography (μCT) imaging techniques with bespoke image analysis tools and mathematical modelling to investigate how grain size and shape vary across wild and domesticated wheat and barley. We find that grain depth and, to a lesser extent, width are major drivers of shape change and that these traits are still relatively plastic in modern bread wheat varieties. Significant changes in grain depth are also observed to be associated with differences in ploidy. Finally, we present a model that can accurately predict the wild or domesticated status of a grain from a given taxa based on the relationship between three morphometric parameters (length, width and depth) and suggest its general applicability to both archaeological identification studies and breeding programmes.

High-resolution mapping of quantitative trait loci controlling main floral stalk length in Chinese cabbage (Brassica rapa L. ssp. pekinensis)

BACKGROUND

For spring-type Chinese cabbage production, premature bolting refers to the excessive elongation of dwarf stems before harvesting. Although quantitative trait loci (QTL) mapping for bolting-related traits have been studied extensively, the main flower stalk length (MFSL) have been rarely investigated. Two inbred lines, 06-247 and He102, have significant differences in the MFSL. In this study, these two materials were selected as parental lines for the construction of a recombinant inbred line (RIL) mapping population. High-density mapping of QTL for the MFSL was performed based on the deep resequencing of parental lines and specific locus-amplified fragment sequencing (SLAF-Seq) of individual recombination inbred lines.

RESULTS

An F7 population consisting of 150 lines was developed. Deep resequencing of parental lines produced 21.08 gigabases, whereas SLAF-Seq produced an average of 428.35 million bases for each progeny. The total aligned data from the parental lines identified 1,082,885 high-quality single nucleotide polymorphisms (SNPs) between parental lines. Out of these, 5392 SNP markers with a segregation type of aa×bb and average integrity of > 99% were suitable for the genetic linkage map construction. The final map contained 10 linkage groups (LGs) was 1687.82 cM in length with an average distance of 0.32 cM between adjacent markers. Based on the high-density map, nine QTLs for MFSL were found to be distributed on seven chromosomes, and two major-effect QTLs were identified for the first time. The physical distance between adjacent markers of two major-effect QTLs was 44.37 kbp and 121.91 kbp, respectively. Approximately 2056 and 6769 SNP markers within confidence intervals were identified according to the results of parental line resequencing, which involved 24 and 199 mutant genes.

CONCLUSIONS

The linkage map constructed in this study has the highest density in Chinese cabbage to date. Two major-effect QTLs for MFSL in Chinese cabbage were also identified. Among these, a novel QTL associated with bolting mapped on LG A04 was identified based on MFSL. The results of this study provide an important platform for gene/QTL mapping and marker-assisted selection (MAS) breeding for bolting-resistant Chinese cabbage.

Genetic Dissection of Resistance to the Three Fungal Plant Pathogens Blumeria graminis, Zymoseptoria tritici, and Pyrenophora tritici-repentis Using a Multiparental Winter Wheat Population

Bread wheat (Triticum aestivum L.) is one of the world’s most important crop species. The development of new varieties resistant to multiple pathogens is an ongoing task in wheat breeding, especially in times of increasing demand for sustainable agricultural practices. Despite this, little is known about the relations between various fungal disease resistances at the genetic level, and the possible consequences for wheat breeding strategies. As a first step to fill this gap, we analyzed the genetic relations of resistance to the three fungal diseases – powdery mildew (PM), septoria tritici blotch (STB), and tan spot (TS) – using a winter wheat multiparent advanced generation intercross population. Six, seven, and nine QTL for resistance to PM, STB, and TS, respectively, were genetically mapped. Additionally, 15 QTL were identified for the three agro-morphological traits plant height, ear emergence time, and leaf angle distribution. Our results suggest that resistance to STB and TS on chromosome 2B is conferred by the same genetic region. Furthermore, we identified two genetic regions on chromosome 1AS and 7AL, which are associated with all three diseases, but not always in a synchronal manner. Based on our results, we conclude that parallel marker-assisted breeding for resistance to the fungal diseases PM, STB, and TS appears feasible. Knowledge of the genetic co-localization of alleles with contrasting effects for different diseases, such as on chromosome 7AL, allows the trade-offs of selection of these regions to be better understood, and ultimately determined at the genic level.