Identification of a Dominant Chlorosis Phenotype Through a Forward Screen of the Triticum turgidum cv. Kronos TILLING Population

Identification and validation of two major QTLs for spikelet number per spike in wheat (Triticum aestivum L.)

The total number of spikelets (TSPN) and the number of fertile spikelets (FSPN) affect the final number of grains per spikelet in wheat. This study constructed a high-density genetic map using 55K single nucleotide polymorphism (SNP) arrays from a population of 152 recombinant inbred lines (RIL) from crossing the wheat accessions 10-A and B39. Twenty-four quantitative trait loci (QTLs) for TSPN and 18 QTLs for FSPN were localized based on the phenotype in 10 environments in 2019-2021. Two major QTLs, QTSPN/QFSPN.sicau-2D.4 (34.43-47.43 Mb) and QTSPN/QFSPN.sicau-2D.5(32.97-34.43 Mb), explained 13.97%-45.90% of phenotypic variation. Linked kompetitive allele-specific PCR (KASP) markers further validated these two QTLs and revealed that QTSPN.sicau-2D.4 had less effect on TSPN than QTSPN.sicau-2D.5 in 10-A×BE89 (134 RILs) and 10-A×Chuannong 16 (192 RILs) populations, and one population of Sichuan wheat (233 accessions). The alleles combination haplotype 3 with the allele from 10-A of QTSPN/QFSPN.sicau-2D.5 and the allele from B39 of QTSPN.sicau-2D.4 resulted in the highest number of spikelets. In contrast, the allele from B39 for both loci resulted in the lowest number of spikelets. Using bulk-segregant analysis-exon capture sequencing, six SNP hot spots that included 31 candidate genes were identified in the two QTLs. We identified Ppd-D1a from B39 and Ppd-D1d from 10-A and further analyzed Ppd-D1 variation in wheat. These results identified loci and molecular markers with potential utility for wheat breeding and laid a foundation for further fine mapping and cloning of the two loci.

Genetic approaches to exploit landraces for improvement of Triticum turgidum ssp. durum in the age of climate change

Addressing the challenges of climate change and durum wheat production is becoming an important driver for food and nutrition security in the Mediterranean area, where are located the major producing countries (Italy, Spain, France, Greece, Morocco, Algeria, Tunisia, Turkey, and Syria). One of the emergent strategies, to cope with durum wheat adaptation, is the exploration and exploitation of the existing genetic variability in landrace populations. In this context, this review aims to highlight the important role of durum wheat landraces as a useful genetic resource to improve the sustainability of Mediterranean agroecosystems, with a focus on adaptation to environmental stresses. We described the most recent molecular techniques and statistical approaches suitable for the identification of beneficial genes/alleles related to the most important traits in landraces and the development of molecular markers for marker-assisted selection. Finally, we outline the state of the art about landraces genetic diversity and signature of selection, already identified from these accessions, for adaptability to the environment.

Genetic Analysis of Adult Plant Resistance to Stripe Rust in Common Wheat Cultivar "Pascal"

Wheat stripe rust is an important foliar disease that affects the wheat yield globally. Breeding for resistant wheat varieties is one of the most economically and environmentally effective ways to control this disease. The common wheat (Triticum aestivum L.) cultivar "Pascal" exhibited susceptibility to stripe rust at the seedling stage but it showed high resistance to stripe rust at the adult plant stage over 20 years in Gansu, a hotspot of the disease in northwestern China. To understand the genetic mechanism of stripe rust resistance in this cultivar, a 55K SNP array was used to analyze the two parents and the 220 recombinant inbred lines (RILs) derived from the cross of "Huixianhong" × "Pascal." We detected three new stripe rust adult plant resistance (APR) quantitative trait locus (QTL) contributed by Pascal, viz. QYr.gaas-1AL, QYr.gaas-3DL, and QYr.gaas-5AS, using the inclusive composite interval mapping method. They were flanked by SNP markers AX-111218361-AX-110577861, AX-111460455-AX-108798599, and AX-111523523-AX-110028503, respectively, and explained the phenotypic variation ranging from 11.0 to 23.1%. Bulked segregant exome capture sequencing (BSE-Seq) was used for fine mapping of QYr.gaas-1AL and selection of candidate genes, TraesCS1A02G313700, TraesCS1A02G313800, and TraesCS1A02G314900 for QYr.gaas-1AL. KASP markers BSE-1A-12 and HXPA-3D for QYr.gaas-1AL and QYr.gaas-3DL were developed for breeders to develop durable stripe rust-resistant wheat varieties.

Delaying or delivering: identification of novel NAM-1 alleles that delay senescence to extend wheat grain fill duration

Senescence is a complex trait under genetic and environmental control, in which resources are remobilized from vegetative tissue into grain. Delayed senescence, or 'staygreen' traits, can confer stress tolerance, with extended photosynthetic activity hypothetically sustaining grain filling. The genetics of senescence regulation are largely unknown, with senescence variation often correlated with phenological traits. Here, we confirm staygreen phenotypes of two Triticum aestivum cv. Paragon ethyl methane sulfonate mutants previously identified during a forward genetic screen and selected for their agronomic performance, similar phenology, and differential senescence phenotypes. Grain filling experiments confirmed a positive relationship between onset of senescence and grain fill duration, reporting an associated ~14% increase in final dry grain weight for one mutant (P<0.05). Recombinant inbred line (RIL) populations segregating for the timing of senescence were developed for trait mapping purposes and phenotyped over multiple years under field conditions. Quantification and comparison of senescence metrics aided RIL selection, facilitating exome capture-enabled bulk segregant analysis (BSA). Using BSA we mapped our two staygreen traits to two independent, dominant, loci of 4.8 and 16.7 Mb in size encompassing 56 and 142 genes, respectively. Combining association analysis with variant effect prediction, we identified single nucleotide polymorphisms encoding self-validating mutations located in NAM-1 homoeologues, which we propose as gene candidates.

Identification of a major and stable QTL on chromosome 5A confers spike length in wheat (Triticum aestivum L.)

Spike length (SL) is the key determinant of plant architecture and yield potential. In this study, 193 recombinant inbred lines (RILs) derived from a cross between 13F10 and Chuanmai 42 (CM42) were evaluated for spike length in six environments. Sixty RILs consisting of 30 high and 30 low SLs were genotyped using the bulked segregant analysis exome sequencing (BSE-Seq) analysis for preliminary quantitative trait locus (QTL) mapping. A 6.69 Mb (518.43-525.12 Mb) region on chromosome 5AL was found to have a significant effect on the SL trait. Fifteen competitive allele-specific PCR (KASP) markers were successfully converted from the single nucleotide polymorphisms (SNPs) in the SL target region. Combined with four novel simple sequence repeat (SSR) markers, a genetic linkage map spanning 21.159 cM was constructed. The mapping result confirmed the identity of a major and stable QTL named QSl.cib-5A in the targeted region that explained 7.88-26.60% of the phenotypic variation in SL. QSl.cib-5A was narrowed to a region of 4.84 cM interval corresponding to a 4.67 Mb (516.60-521.27 Mb) physical region in the Chinese Spring RefSeq v2.0 containing 17 high-confidence genes with 25 transcripts. In addition, this QTL exhibited pleiotropic effects on spikelet density (SD), with the phenotypic variances proportion ranging from 11.34 to 19.92%. This study provides a foundational step for cloning the QSl.cib-5A, which is involved in the regulation of spike morphology in common wheat.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01249-6.

Capturing and Selecting Senescence Variation in Wheat

Senescence is a highly quantitative trait, but in wheat the genetics underpinning senescence regulation remain relatively unknown. To select senescence variation and ultimately identify novel genetic regulators, accurate characterization of senescence phenotypes is essential. When investigating senescence, phenotyping efforts often focus on, or are limited to, the visual assessment of flag leaves. However, senescence is a whole-plant process, involving remobilization and translocation of resources into the developing grain. Furthermore, the temporal progression of senescence poses challenges regarding trait quantification and description, whereupon the different models and approaches applied result in varying definitions of apparently similar metrics. To gain a holistic understanding of senescence, we phenotyped flag leaf and peduncle senescence progression, alongside grain maturation. Reviewing the literature, we identified techniques commonly applied in quantification of senescence variation and developed simple methods to calculate descriptive and discriminatory metrics. To capture senescence dynamism, we developed the idea of calculating thermal time to different flag leaf senescence scores, for which between-year Spearman's rank correlations of r ≥ 0.59, P < 4.7 × 10-5 (TT70), identify as an accurate phenotyping method. Following our experience of senescence trait genetic mapping, we recognized the need for singular metrics capable of discriminating senescence variation, identifying thermal time to flag leaf senescence score of 70 (TT70) and mean peduncle senescence (MeanPed) scores as most informative. Moreover, grain maturity assessments confirmed a previous association between our staygreen traits and grain fill extension, illustrating trait functionality. Here we review different senescence phenotyping approaches and share our experiences of phenotyping two independent recombinant inbred line (RIL) populations segregating for staygreen traits. Together, we direct readers toward senescence phenotyping methods we found most effective, encouraging their use when investigating and discriminating senescence variation of differing genetic bases, and aid trait selection and weighting in breeding and research programs alike.

High-Resolution Mapping of the Novel Early Leaf Senescence Gene Els2 in Common Wheat

Early leaf senescence negatively impacts the grain yield in wheat (Triticum aestivum L.). Induced mutants provide an important resource for mapping and cloning of genes for early leaf senescence. In our previous study, Els2, a single incomplete dominance gene, that caused early leaf senescence phenotype in the wheat mutant LF2099, had been mapped on the long arm of chromosome 2B. The objective of this study was to develop molecular markers tightly linked to the Els2 gene and construct a high-resolution map surrounding the Els2 gene. Three tightly linked single-nucleotide polymorphism (SNP) markers were obtained from the Illumina Wheat 90K iSelect SNP genotyping array and converted to Kompetitive allele-specific polymerase chain reaction (KASP) markers. To saturate the Els2 region, the Axiom® Wheat 660K SNP array was used to screen bulked extreme phenotype DNA pools, and 9 KASP markers were developed. For fine mapping of the Els2 gene, these KASP markers and previously identified polymorphic markers were analyzed in a large F₂ population of the LF2099 × Chinese Spring cross. The Els2 gene was located in a 0.24-cM genetic region flanked by the KASP markers AX-111643885 and AX-111128667, which corresponded to a physical interval of 1.61 Mb in the Chinese Spring chromosome 2BL containing 27 predicted genes with high confidence. The study laid a foundation for a map-based clone of the Els2 gene controlling the mutation phenotype and revealing the molecular regulatory mechanism of wheat leaf senescence.

Exome sequencing of bulked segregants identified a novel TaMKK3-A allele linked to the wheat ERA8 ABA-hypersensitive germination phenotype

Using bulked segregant analysis of exome sequence, we fine-mapped the ABA-hypersensitive mutant ERA8 in a wheat backcross population to the TaMKK3-A locus of chromosome 4A. Preharvest sprouting (PHS) is the germination of mature grain on the mother plant when it rains before harvest. The ENHANCED RESPONSE TO ABA8 (ERA8) mutant increases seed dormancy and, consequently, PHS tolerance in soft white wheat 'Zak.' ERA8 was mapped to chromosome 4A in a Zak/'ZakERA8' backcross population using bulked segregant analysis of exome sequenced DNA (BSA-exome-seq). ERA8 was fine-mapped relative to mutagen-induced SNPs to a 4.6 Mb region containing 70 genes. In the backcross population, the ERA8 ABA-hypersensitive phenotype was strongly linked to a missense mutation in TaMKK3-A-G1093A (LOD 16.5), a gene associated with natural PHS tolerance in barley and wheat. The map position of ERA8 was confirmed in an 'Otis'/ZakERA8 but not in a 'Louise'/ZakERA8 mapping population. This is likely because Otis carries the same natural PHS susceptible MKK3-A-A660^S allele as Zak, whereas Louise carries the PHS-tolerant MKK3-A-C660^R allele. Thus, the variation for grain dormancy and PHS tolerance in the Louise/ZakERA8 population likely resulted from segregation of other loci rather than segregation for PHS tolerance at the MKK3 locus. This inadvertent complementation test suggests that the MKK3-A-G1093A mutation causes the ERA8 phenotype. Moreover, MKK3 was a known ABA signaling gene in the 70-gene 4.6 Mb ERA8 interval. None of these 70 genes showed the differential regulation in wild-type Zak versus ERA8 expected of a promoter mutation. Thus, the working model is that the ERA8 phenotype results from the MKK3-A-G1093A mutation.

Combining a New Exome Capture Panel With an Effective varBScore Algorithm Accelerates BSA-Based Gene Cloning in Wheat

The discovery of functional genes underlying agronomic traits is of great importance for wheat improvement. Here we designed a new wheat exome capture probe panel based on IWGSC RefSeq v1.0 genome sequence information and developed an effective algorithm, varBScore, that can sufficiently reduce the background noise in gene mapping and identification. An effective method, termed bulked segregant exome capture sequencing (BSE-Seq) for identifying causal mutations or candidate genes was established by combining the use of a newly designed wheat exome capture panel, sequencing of bulked segregant pools from segregating populations, and the robust algorithm varBScore. We evaluated the effectiveness of varBScore on SNP calling using the published dataset for mapping and cloning the yellow rust resistance gene Yr7 in wheat. Furthermore, using BSE-Seq, we rapidly identified a wheat yellow leaf mutant gene, ygl1, in an ethyl methanesulfonate (EMS) mutant population and found that a single mutation of G to A at 921 position in the wild type YGL1 gene encoding magnesium-chelatase subunit chlI caused the leaf yellowing phenotype. We further showed that mutation of YGL1 through CRISPR/Cas9 gene editing led to a yellow phenotype on the leaves of transgenic wheat, indicating that ygl1 is the correct causal gene responsible for the mutant phenotype. In summary, our approach is highly efficient for discovering causal mutations and gene cloning in wheat.

Genetic Screening for Mutants with Altered Seminal Root Numbers in Hexaploid Wheat Using a High-Throughput Root Phenotyping Platform

Roots are the main channel for water and nutrient uptake in plants. Optimization of root architecture provides a viable strategy to improve nutrient and water uptake efficiency and maintain crop productivity under water-limiting and nutrient-poor conditions. We know little, however, about the genetic control of root development in wheat, a crop supplying 20% of global calorie and protein intake. To improve our understanding of the genetic control of seminal root development in wheat, we conducted a high-throughput screen for variation in seminal root number using an exome-sequenced mutant population derived from the hexaploid wheat cultivar Cadenza. The screen identified seven independent mutants with homozygous and stably altered seminal root number phenotypes. One mutant, Cadenza0900, displays a recessive extra seminal root number phenotype, while six mutants (Cadenza0062, Cadenza0369, Cadenza0393, Cadenza0465, Cadenza0818 and Cadenza1273) show lower seminal root number phenotypes most likely originating from defects in the formation and activation of seminal root primordia. Segregation analysis in F2 populations suggest that the phenotype of Cadenza0900 is controlled by multiple loci whereas the Cadenza0062 phenotype fits a 3:1 mutant:wild-type segregation ratio characteristic of dominant single gene action. This work highlights the potential to use the sequenced wheat mutant population as a forward genetic resource to uncover novel variation in agronomic traits, such as seminal root architecture.