Showing papers in "Theoretical and Applied Genetics in 2022"

Meta-QTLs, ortho-meta-QTLs and candidate genes for grain yield and associated traits in wheat (Triticum aestivum L.)

Abstract: In wheat, 2852 major QTLs of 8998 QTLs available for yield and related traits were used for meta-analysis; 141 meta-QTLs were identified, which included 13 breeder's MQTLs and 24 ortho-MQTLs; 1202 candidate genes and 50 homologues of genes for yield from other cereals were also identified. Meta-QTL analysis was conducted using 2852 of the 8998 known QTLs, retrieved from 230 reports published during 1999-2020 (including 19 studies on tetraploid wheat) for grain yield (GY) and the following ten component traits: (i) grain weight (GWei), (ii) grain morphology-related traits (GMRTs), (iii) grain number (GN), (iv) spikes-related traits (SRTs), (v) plant height (PH), (vi) tiller number (TN), (vii) harvest index (HI), (viii) biomass yield (BY), (ix) days to heading/flowering and maturity (DTH/F/M), and (x) grain filling duration (GFD). The study resulted in the identification of 141 meta-QTLs (MQTLs), with an average confidence interval (CI) of 1.4 cM as against a CI of > 12.1 cM (8.8 fold reduction) in the QTLs that were used. The corresponding physical length of CI ranged from 0.01 Mb to 661.9 Mb (mean, 31.5 Mb). Seventy-seven (77) of these 141 MQTLs overlapped marker-trait associations (MTAs) reported in genome-wide association studies. Also, 63 MQTLs (each based on at least 10 QTLs) were considered stable and robust, with 13 MQTLs described as breeder's MQTLs (selected based on small CI, large LOD, and high level of phenotypic variation explained). Thirty-five yield-related genes from rice, barley, and maize were also utilized to identify 50 wheat homologues in MQTLs. Further, the use of synteny and collinearity allowed the identification of 24 ortho-MQTLs which were common among the wheat, barley, rice, and maize. The results of the present study should prove useful for wheat breeding and future basic research in cereals including wheat, barley, rice, and maize.

Host plant resistance for fall armyworm management in maize: relevance, status and prospects in Africa and Asia

Abstract: Abstract Key message Sustainable control of fall armyworm (FAW) requires implementation of effective integrated pest management (IPM) strategies, with host plant resistance as a key component. Significant opportunities exist for developing and deploying elite maize cultivars with native genetic resistance and/or transgenic resistance for FAW control in both Africa and Asia. Abstract The fall armyworm [ Spodoptera frugiperda (J.E. Smith); FAW] has emerged as a serious pest since 2016 in Africa, and since 2018 in Asia, affecting the food security and livelihoods of millions of smallholder farmers, especially those growing maize. Sustainable control of FAW requires implementation of integrated pest management strategies, in which host plant resistance is one of the key components. Significant strides have been made in breeding elite maize lines and hybrids with native genetic resistance to FAW in Africa, based on the strong foundation of insect-resistant tropical germplasm developed at the International Maize and Wheat Improvement Center, Mexico. These efforts are further intensified to develop and deploy elite maize cultivars with native FAW tolerance/resistance and farmer-preferred traits suitable for diverse agro-ecologies in Africa and Asia. Independently, genetically modified Bt maize with resistance to FAW is already commercialized in South Africa, and in a few countries in Asia (Philippines and Vietnam), while efforts are being made to commercialize Bt maize events in additional countries in both Africa and Asia. In countries where Bt maize is commercialized, it is important to implement a robust insect resistance management strategy. Combinations of native genetic resistance and Bt maize also need to be explored as a path to more effective and sustainable host plant resistance options. We also highlight the critical gaps and priorities for host plant resistance research and development in maize, particularly in the context of sustainable FAW management in Africa and Asia.

Classification of CRISPR/Cas system and its application in tomato breeding

Abstract: Remarkable diversity in the domain of genome loci architecture, structure of effector complex, array of protein composition, mechanisms of adaptation along with difference in pre-crRNA processing and interference have led to a vast scope of detailed classification in bacterial and archaeal CRISPR/Cas systems, their intrinsic weapon of adaptive immunity. Two classes: Class 1 and Class 2, several types and subtypes have been identified so far. While the evolution of the effector complexes of Class 2 is assigned solely to mobile genetic elements, the origin of Class 1 effector molecules is still in a haze. Majority of the types target DNA except type VI, which have been found to target RNA exclusively. Cas9, the single effector protein, has been the primary focus of CRISPR-mediated genome editing revolution and is an integral part of Class 2 (type II) system. The present review focuses on the different CRISPR types in depth and the application of CRISPR/Cas9 for epigenome modification, targeted base editing and improving traits such as abiotic and biotic stress tolerance, yield and nutritional aspects of tomato breeding.

Classification of CRISPR/Cas system and its application in tomato breeding

Abstract: Remarkable diversity in the domain of genome loci architecture, structure of effector complex, array of protein composition, mechanisms of adaptation along with difference in pre-crRNA processing and interference have led to a vast scope of detailed classification in bacterial and archaeal CRISPR/Cas systems, their intrinsic weapon of adaptive immunity. Two classes: Class 1 and Class 2, several types and subtypes have been identified so far. While the evolution of the effector complexes of Class 2 is assigned solely to mobile genetic elements, the origin of Class 1 effector molecules is still in a haze. Majority of the types target DNA except type VI, which have been found to target RNA exclusively. Cas9, the single effector protein, has been the primary focus of CRISPR-mediated genome editing revolution and is an integral part of Class 2 (type II) system. The present review focuses on the different CRISPR types in depth and the application of CRISPR/Cas9 for epigenome modification, targeted base editing and improving traits such as abiotic and biotic stress tolerance, yield and nutritional aspects of tomato breeding.

Meta-QTLs for multiple disease resistance involving three rusts in common wheat (Triticum aestivum L.)

Abstract: In wheat, multiple disease resistance meta-QTLs (MDR-MQTLs) and underlying candidate genes for the three rusts were identified which may prove useful for development of resistant cultivars. Rust diseases in wheat are a major threat to global food security. Therefore, development of multiple disease-resistant cultivars (resistant to all three rusts) is a major goal in all wheat breeding programs worldwide. In the present study, meta-QTLs and candidate genes for multiple disease resistance (MDR) involving all three rusts were identified using 152 individual QTL mapping studies for resistance to leaf rust (LR), stem rust (SR), and yellow rust (YR). From these 152 studies, a total of 1,146 QTLs for resistance to three rusts were retrieved, which included 368 QTLs for LR, 291 QTLs for SR, and 487 QTLs for YR. Of these 1,146 QTLs, only 718 QTLs could be projected onto the consensus map saturated with 2, 34,619 markers. Meta-analysis of the projected QTLs resulted in the identification of 86 MQTLs, which included 71 MDR-MQTLs. Ten of these MDR-MQTLs were referred to as the 'Breeders' MQTLs'. Seventy-eight of the 86 MQTLs could also be anchored to the physical map of the wheat genome, and 54 MQTLs were validated by marker-trait associations identified during earlier genome-wide association studies. Twenty MQTLs (including 17 MDR-MQTLs) identified in the present study were co-localized with 44 known R genes. In silico expression analysis allowed identification of several differentially expressed candidate genes (DECGs) encoding proteins carrying different domains including the following: NBS-LRR, WRKY domains, F-box domains, sugar transporters, transferases, etc. The introgression of these MDR loci into high-yielding cultivars should prove useful for developing high yielding cultivars with resistance to all the three rusts.

Breeding for disease resistance in soybean: a global perspective

Abstract: This review provides a comprehensive atlas of QTLs, genes, and alleles conferring resistance to 28 important diseases in all major soybean production regions in the world. Breeding disease-resistant soybean [Glycine max (L.) Merr.] varieties is a common goal for soybean breeding programs to ensure the sustainability and growth of soybean production worldwide. However, due to global climate change, soybean breeders are facing strong challenges to defeat diseases. Marker-assisted selection and genomic selection have been demonstrated to be successful methods in quickly integrating vertical resistance or horizontal resistance into improved soybean varieties, where vertical resistance refers to R genes and major effect QTLs, and horizontal resistance is a combination of major and minor effect genes or QTLs. This review summarized more than 800 resistant loci/alleles and their tightly linked markers for 28 soybean diseases worldwide, caused by nematodes, oomycetes, fungi, bacteria, and viruses. The major breakthroughs in the discovery of disease resistance gene atlas of soybean were also emphasized which include: (1) identification and characterization of vertical resistance genes reside rhg1 and Rhg4 for soybean cyst nematode, and exploration of the underlying regulation mechanisms through copy number variation and (2) map-based cloning and characterization of Rps11 conferring resistance to 80% isolates of Phytophthora sojae across the USA. In this review, we also highlight the validated QTLs in overlapping genomic regions from at least two studies and applied a consistent naming nomenclature for these QTLs. Our review provides a comprehensive summary of important resistant genes/QTLs and can be used as a toolbox for soybean improvement. Finally, the summarized genetic knowledge sheds light on future directions of accelerated soybean breeding and translational genomics studies.

Improvement of genomic prediction in advanced wheat breeding lines by including additive-by-additive epistasis

Abstract: Including additive and additive-by-additive epistasis in a NOIA parametrization did not yield orthogonal partitioning of genetic variances, nevertheless, it improved predictive ability in a leave-one-out cross-validation for wheat grain yield. Additive-by-additive epistasis is the principal non-additive genetic effect in inbred wheat lines and is potentially useful for developing cultivars based on total genetic merit; nevertheless, its practical benefits have been highly debated. In this article, we aimed to (i) evaluate the performance of models including additive and additive-by-additive epistatic effects for variance components (VC) estimation of grain yield in a wheat-breeding population, and (ii) to investigate whether including additive-by-additive epistasis in genomic prediction enhance wheat grain yield predictive ability (PA). In total, 2060 sixth-generation (F6) lines from Nordic Seed A/S breeding company were phenotyped in 21 year-location combinations in Denmark, and genotyped using a 15 K-Illumina-BeadChip. Three models were used to estimate VC and heritability at plot level: (i) "I-model" (baseline), (ii) "I + GA-model", extending I-model with an additive genomic effect, and (iii) "I + GA + GAA-model", extending I + GA-model with an additive-by-additive genomic effects. The I + GA-model and I + GA + GAA-model were based on the Natural and Orthogonal Interactions Approach (NOIA) parametrization. The I + GA + GAA-model failed to achieve orthogonal partition of genetic variances, as revealed by a change in estimated additive variance of I + GA-model when epistasis was included in the I + GA + GAA-model. The PA was studied using leave-one-line-out and leave-one-breeding-cycle-out cross-validations. The I + GA + GAA-model increased PA significantly (16.5%) compared to the I + GA-model in leave-one-line-out cross-validation. However, the improvement due to including epistasis was not observed in leave-one-breeding-cycle-out cross-validation. We conclude that epistatic models can be useful to enhance predictions of total genetic merit. However, even though we used the NOIA parameterization, the variance partition into orthogonal genetic effects was not possible.

Phenomic selection in wheat breeding: identification and optimisation of factors influencing prediction accuracy and comparison to genomic selection

Abstract: Phenomic selection is a promising alternative or complement to genomic selection in wheat breeding. Models combining spectra from different environments maximise the predictive ability of grain yield and heading date of wheat breeding lines. Phenomic selection (PS) is a recent breeding approach similar to genomic selection (GS) except that genotyping is replaced by near-infrared (NIR) spectroscopy. PS can potentially account for non-additive effects and has the major advantage of being low cost and high throughput. Factors influencing GS predictive abilities have been intensively studied, but little is known about PS. We tested and compared the abilities of PS and GS to predict grain yield and heading date from several datasets of bread wheat lines corresponding to the first or second years of trial evaluation from two breeding companies and one research institute in France. We evaluated several factors affecting PS predictive abilities including the possibility of combining spectra collected in different environments. A simple H-BLUP model predicted both traits with prediction ability from 0.26 to 0.62 and with an efficient computation time. Our results showed that the environments in which lines are grown had a crucial impact on predictive ability based on the spectra acquired and was specific to the trait considered. Models combining NIR spectra from different environments were the best PS models and were at least as accurate as GS in most of the datasets. Furthermore, a GH-BLUP model combining genotyping and NIR spectra was the best model of all (prediction ability from 0.31 to 0.73). We demonstrated also that as for GS, the size and the composition of the training set have a crucial impact on predictive ability. PS could therefore replace or complement GS for efficient wheat breeding programs.

Phenomic selection in wheat breeding: identification and optimisation of factors influencing prediction accuracy and comparison to genomic selection

Abstract: Phenomic selection is a promising alternative or complement to genomic selection in wheat breeding. Models combining spectra from different environments maximise the predictive ability of grain yield and heading date of wheat breeding lines. Phenomic selection (PS) is a recent breeding approach similar to genomic selection (GS) except that genotyping is replaced by near-infrared (NIR) spectroscopy. PS can potentially account for non-additive effects and has the major advantage of being low cost and high throughput. Factors influencing GS predictive abilities have been intensively studied, but little is known about PS. We tested and compared the abilities of PS and GS to predict grain yield and heading date from several datasets of bread wheat lines corresponding to the first or second years of trial evaluation from two breeding companies and one research institute in France. We evaluated several factors affecting PS predictive abilities including the possibility of combining spectra collected in different environments. A simple H-BLUP model predicted both traits with prediction ability from 0.26 to 0.62 and with an efficient computation time. Our results showed that the environments in which lines are grown had a crucial impact on predictive ability based on the spectra acquired and was specific to the trait considered. Models combining NIR spectra from different environments were the best PS models and were at least as accurate as GS in most of the datasets. Furthermore, a GH-BLUP model combining genotyping and NIR spectra was the best model of all (prediction ability from 0.31 to 0.73). We demonstrated also that as for GS, the size and the composition of the training set have a crucial impact on predictive ability. PS could therefore replace or complement GS for efficient wheat breeding programs.

A cool climate perspective on grapevine breeding: climate change and sustainability are driving forces for changing varieties in a traditional market

Abstract: A multitude of diverse breeding goals need to be combined in a new cultivar, which always forces to compromise. The biggest challenge grapevine breeders face is the extraordinarily complex trait of wine quality, which is the all-pervasive and most debated characteristic. Since the 1920s, Germany runs continuous grapevine breeding programmes. This continuity was the key to success and lead to various new cultivars on the market, so called PIWIs. Initially, introduced pests and diseases such as phylloxera, powdery and downy mildew were the driving forces for breeding. However, preconceptions about the wine quality of new resistant selections impeded the market introduction. These preconceptions are still echoing today and may be the reason in large parts of the viticultural community for: (1) ignoring substantial breeding progress, and (2) sticking to successful markets of well-known varietal wines or blends (e.g. Chardonnay, Cabernet Sauvignon, Riesling). New is the need to improve viticulture´s sustainability and to adapt to changing environmental conditions. Climate change with its extreme weather will impose the need for a change in cultivars in many wine growing regions. Therefore, a paradigm shift is knocking on the door: new varieties (PIWIs) versus traditional varieties for climate adapted and sustainable viticulture. However, it will be slow process and viticulture is politically well advised to pave the way to variety innovation. In contrast to the widely available PIWIs, competitive cultivars created by means of new breeding technologies (NBT, e.g. through CRISPR/Cas) are still decades from introduction to the market.

Adult plant stem rust resistance in durum wheat Glossy Huguenot: mapping, marker development and validation

Abstract: Adult plant stem rust resistance locus, QSrGH.cs-2AL, was identified in durum wheat Glossy Huguenot and mendelised as Sr63. Markers closely linked with Sr63 were developed. An F3 population from a Glossy Huguenot (GH)/Bansi cross used in a previous Australian study was advanced to F6 for molecular mapping of adult plant stem rust resistance. Maturity differences among F6 lines confounded assessments of stem rust response. GH was crossed with a stem rust susceptible F6 recombinant inbred line (RIL), GHB14 (M14), with similar maturity and an F6:7 population was developed through single seed descent method. F7 and F8 RILs were tested along with the parents at different locations. The F6 individual plants and both parents were genotyped using the 90 K single nucleotide polymorphism (SNP) wheat array. Stem rust resistance QTL on the long arms of chromosomes 1B (QSrGH.cs-1BL) and 2A (QSrGH.cs-2AL) were detected. QSrGH.cs-1BL and QSrGH.cs-2AL were both contributed by GH and explained 22% and 18% adult plant stem rust response variation, respectively, among GH/M14 RIL population. RILs carrying combinations of these QTL reduced more than 14% stem rust severity compared to those that possessed QSrGH.cs-1BL and QSrGH.cs-2AL individually. QSrGH.cs1BL was demonstrated to be the same as Sr58/Lr46/Yr29/Pm39 through marker genotyping. Lines lacking QSrGH.cs-1BL were used to Mendelise QSrGH.cs-2AL. Based on genomic locations of previously catalogued stem rust resistance genes and the QSrGH.cs-2AL map, it appeared to represent a new APR locus and was permanently named Sr63. SNP markers associated with Sr63 were converted to kompetetive allele-specific PCR (KASP) assays and were validated on a set of durum cultivars.

Soybean genetic resources contributing to sustainable protein production

Abstract: Abstract Key message Genetic resources contributes to the sustainable protein production in soybean. Abstract Soybean is an important crop for food, oil, and forage and is the main source of edible vegetable oil and vegetable protein. It plays an important role in maintaining balanced dietary nutrients for human health. The soybean protein content is a quantitative trait mainly controlled by gene additive effects and is usually negatively correlated with agronomic traits such as the oil content and yield. The selection of soybean varieties with high protein content and high yield to secure sustainable protein production is one of the difficulties in soybean breeding. The abundant genetic variation of soybean germplasm resources is the basis for overcoming the obstacles in breeding for soybean varieties with high yield and high protein content. Soybean has been cultivated for more than 5000 years and has spread from China to other parts of the world. The rich genetic resources play an important role in promoting the sustainable production of soybean protein worldwide. In this paper, the origin and spread of soybean and the current status of soybean production are reviewed; the genetic characteristics of soybean protein and the distribution of resources are expounded based on phenotypes; the discovery of soybean seed protein-related genes as well as transcriptomic, metabolomic, and proteomic studies in soybean are elaborated; the creation and utilization of high-protein germplasm resources are introduced; and the prospect of high-protein soybean breeding is described.

Dissection of the practical soybean breeding pipeline by developing ZDX1, a high-throughput functional array

Abstract: We developed the ZDX1 high-throughput functional soybean array for high accuracy evaluation and selection of both parents and progeny, which can greatly accelerate soybean breeding. Microarray technology facilitates rapid, accurate, and economical genotyping. Here, using resequencing data from 2214 representative soybean accessions, we developed the high-throughput functional array ZDX1, containing 158,959 SNPs, covering 90.92% of soybean genes and sites related to important traits. By application of the array, a total of 817 accessions were genotyped, including three subpopulations of candidate parental lines, parental lines and their progeny from practical breeding. The fixed SNPs were identified in progeny, indicating artificial selection during the breeding process. By identifying functional sites of target traits, novel soybean cyst nematode-resistant progeny and maturity-related novel sources were identified by allele combinations, demonstrating that functional sites provide an efficient method for the rapid screening of desirable traits or gene sources. Notably, we found that the breeding index (BI) was a good indicator for progeny selection. Superior progeny were derived from the combination of distantly related parents, with at least one parent having a higher BI. Furthermore, new combinations based on good performance were proposed for further breeding after excluding redundant and closely related parents. Genomic best linear unbiased prediction (GBLUP) analysis was the best analysis method and achieved the highest accuracy in predicting four traits when comparing SNPs in genic regions rather than whole genomic or intergenic SNPs. The prediction accuracy was improved by 32.1% by using progeny to expand the training population. Collectively, a versatile assay demonstrated that the functional ZDX1 array provided efficient information for the design and optimization of a breeding pipeline for accelerated soybean breeding.

BSA‑seq and genetic mapping reveals AhRt2 as a candidate gene responsible for red testa of peanut

Abstract: The candidate recessive gene AhRt2 responsible for red testa of peanut was identified through combined BSA-seq and linkage mapping approaches. The testa color of peanuts (Arachis hypogaea L.) is an important trait, and those with red testa are particularly popular owing to the high-anthocyanin content. However, the identification of genes underlying the regulation of the red testa trait in peanut are rarely reported. In order to fine map red testa gene, two F2:4 populations were constructed through the cross of YZ9102 (pink testa) with ZH12 (red testa) and ZH2 (red testa). Genetic analysis indicated that red testa was controlled by a single recessive gene named as AhRt2 (Red testa gene 2). Using BSA-seq approach, AhRt2 was preliminary identified on chromosome 12, which was further mapped to a 530-kb interval using 220 recombinant lines through linkage mapping. Furthermore, functional annotation, expression profiling, and the analyses of sequence variation confirmed that the anthocyanin reductase namely (Arahy.IK60LM) was the most likely candidate gene for AhRt2. It was found that a SNP in the third exon of AhRt2 altered the encoding amino acids, and was associated with red testa in peanut. In addition, a closely linked molecular marker linked with red testa trait in peanut was also developed for future studies. Our results provide valuable insight into the molecular mechanism underlying peanut testa color and present significant diagnostic marker resources for marker-assisted selected breeding in peanut.

Haplotype mapping uncovers unexplored variation in wild and domesticated soybean at the major protein locus cqProt-003

Abstract: Abstract Key message The major soy protein QTL, cqProt-003, was analysed for haplotype diversity and global distribution, and results indicate 304 bp deletion and variable tandem repeats in protein coding regions are likely causal candidates. Abstract Here, we present association and linkage analysis of 985 wild, landrace and cultivar soybean accessions in a pan genomic dataset to characterize the major high-protein/low-oil associated locus cqProt-003 located on chromosome 20. A significant trait-associated region within a 173 kb linkage block was identified, and variants in the region were characterized, identifying 34 high confidence SNPs, 4 insertions, 1 deletion and a larger 304 bp structural variant in the high-protein haplotype. Trinucleotide tandem repeats of variable length present in the second exon of gene Glyma.20G085100 are strongly correlated with the high-protein phenotype and likely represent causal variation. Structural variation has previously been found in the same gene, for which we report the global distribution of the 304 bp deletion and have identified additional nested variation present in high-protein individuals. Mapping variation at the cqProt-003 locus across demographic groups suggests that the high-protein haplotype is common in wild accessions (94.7%), rare in landraces (10.6%) and near absent in cultivated breeding pools (4.1%), suggesting its decrease in frequency primarily correlates with domestication and continued during subsequent improvement. However, the variation that has persisted in under-utilized wild and landrace populations holds high breeding potential for breeders willing to forego seed oil to maximize protein content. The results of this study include the identification of distinct haplotype structures within the high-protein population, and a broad characterization of the genomic context and linkage patterns of cqProt-003 across global populations, supporting future functional characterization and modification.

Fine mapping of powdery mildew resistance gene MlWE74 derived from wild emmer wheat (Triticum turgidum ssp. dicoccoides) in an NBS-LRR gene cluster

Abstract: Powdery mildew resistance gene MlWE74, originated from wild emmer wheat accession G-748-M, was mapped in an NBS-LRR gene cluster of chromosome 2BS. Wheat powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), is a globally devastating disease. Wild emmer wheat (Triticum turgidum var. dicoccoides) is a valuable genetic resource for improving disease resistance in common wheat. A powdery mildew resistance gene was transferred to hexaploid wheat line WE74 from wild emmer accession G-748-M. Genetic analysis revealed that the powdery mildew resistance in WE74 is controlled by a single dominant gene, herein temporarily designated MlWE74. Bulked segregant analysis (BSA) and molecular mapping delimited MlWE74 to the terminal region of chromosome 2BS flanking by markers WGGBD412 and WGGBH346 within a genetic interval of 0.25 cM and corresponding to 799.9 kb genomic region in the Zavitan reference sequence. Sequence annotation revealed two phosphoglycerate mutase-like genes, an alpha/beta-hydrolases gene, and five NBS-LRR disease resistance genes that could serve as candidates for map-based cloning of MlWE74. The geographical location analysis indicated that MlWE74 is mainly distributed in Rosh Pinna and Amirim regions, in the northern part of Israel, where environmental conditions are favorable to the occurrence of powdery mildew. Moreover, the co-segregated marker WGGBD425 is helpful in marker-assisted transfer of MlWE74 into elite cultivars.

Perspectives for integrated insect pest protection in oilseed rape breeding

Abstract: In the past, breeding for incorporation of insect pest resistance or tolerance into cultivars for use in integrated pest management schemes in oilseed rape/canola (Brassica napus) production has hardly ever been approached. This has been largely due to the broad availability of insecticides and the complexity of dealing with high-throughput phenotyping of insect performance and plant damage parameters. However, recent changes in the political framework in many countries demand future sustainable crop protection which makes breeding approaches for crop protection as a measure for pest insect control attractive again. At the same time, new camera-based tracking technologies, new knowledge-based genomic technologies and new scientific insights into the ecology of insect-Brassica interactions are becoming available. Here we discuss and prioritise promising breeding strategies and direct and indirect breeding targets, and their time-perspective for future realisation in integrated insect pest protection of oilseed rape. In conclusion, researchers and oilseed rape breeders can nowadays benefit from an array of new technologies which in combination will accelerate the development of improved oilseed rape cultivars with multiple insect pest resistances/tolerances in the near future.

Genomic selection for spot blotch in bread wheat breeding panels, full-sibs and half-sibs and index-based selection for spot blotch, heading and plant height

Abstract: Genomic selection is a promising tool to select for spot blotch resistance and index-based selection can simultaneously select for spot blotch resistance, heading and plant height. A major biotic stress challenging bread wheat production in regions characterized by humid and warm weather is spot blotch caused by the fungus Bipolaris sorokiniana. Since genomic selection (GS) is a promising selection tool, we evaluated its potential for spot blotch in seven breeding panels comprising 6736 advanced lines from the International Maize and Wheat Improvement Center. Our results indicated moderately high mean genomic prediction accuracies of 0.53 and 0.40 within and across breeding panels, respectively which were on average 177.6% and 60.4% higher than the mean accuracies from fixed effects models using selected spot blotch loci. Genomic prediction was also evaluated in full-sibs and half-sibs panels and sibs were predicted with the highest mean accuracy (0.63) from a composite training population with random full-sibs and half-sibs. The mean accuracies when full-sibs were predicted from other full-sibs within families and when full-sibs panels were predicted from other half-sibs panels were 0.47 and 0.44, respectively. Comparison of GS with phenotypic selection (PS) of the top 10% of resistant lines suggested that GS could be an ideal tool to discard susceptible lines, as greater than 90% of the susceptible lines discarded by PS were also discarded by GS. We have also reported the evaluation of selection indices to simultaneously select non-late and non-tall genotypes with low spot blotch phenotypic values and genomic-estimated breeding values. Overall, this study demonstrates the potential of integrating GS and index-based selection for improving spot blotch resistance in bread wheat.

Identification of QTLs affecting post-anthesis heat stress responses in European bread wheat

Abstract: The response of a large panel of European elite wheat varieties to post-anthesis heat stress is influenced by 17 QTL linked to grain weight or the stay-green phenotype. Heat stress is a critical abiotic stress for winter bread wheat (Triticum aestivum L.) especially at the flowering and grain filling stages, limiting its growth and productivity in Europe and elsewhere. The breeding of new high-yield and stress-tolerant wheat varieties requires improved understanding of the physiological and genetic bases of heat tolerance. To identify genomic areas associated with plant and grain characteristics under heat stress, a panel of elite European wheat varieties (N = 199) was evaluated under controlled conditions in 2016 and 2017. A split-plot design was used to test the effects of high temperature for ten days after flowering. Flowering time, leaf chlorophyll content, the number of productive spikes, grain number, grain weight and grain size were measured, and the senescence process was modeled. Using genotyping data from a 280 K SNP chip, a genome-wide association study was carried out to test the main effect of each SNP and the effect of SNP × treatment interaction. Genotype × treatment interactions were mainly observed for grain traits measured on the main shoots and tillers. We identified 10 QTLs associated with the main effect of at least one trait and seven QTLs associated with the response to post-anthesis heat stress. Of these, two main QTLs associated with the heat tolerance of thousand-kernel weight were identified on chromosomes 4B and 6B. These QTLs will be useful for breeders to improve grain yield in environments where terminal heat stress is likely to occur.