Genome-wide association analyses of plant growth traits during the stem elongation phase in wheat

Temporal dynamics of genetic architecture governing leaf development in Populus

Leaf development is a multifaceted and dynamic process orchestrated by a myriad of genes to shape the proper size and morphology. The dynamic genetic network underlying leaf development remains largely unknown. Utilizing a synergistic genetic approach encompassing dynamic genome-wide association study (GWAS), time-ordered gene co-expression network (TO-GCN) analyses and gene manipulation, we explored the temporal genetic architecture and regulatory network governing leaf development in Populus. We identified 42 time-specific and 18 consecutive genes that displayed different patterns of expression at various time points. We then constructed eight TO-GCNs that covered the cell proliferation, transition, and cell expansion stages of leaf development. Integrating GWAS and TO-GCN, we postulated the functions of 27 causative genes for GWAS and identified PtoGRF9 as a key player in leaf development. Genetic manipulation via overexpression and suppression of PtoGRF9 revealed its primary influence on leaf development by modulating cell proliferation. Furthermore, we elucidated that PtoGRF9 governs leaf development by activating PtoHB21 during the cell proliferation stage and attenuating PtoLD during the transition stage. Our study provides insights into the dynamic genetic underpinnings of leaf development and understanding the regulatory mechanism of PtoGRF9 in this dynamic process.

Grain yield trade-offs in spike-branching wheat can be mitigated by elite alleles affecting sink capacity and post-anthesis source activity

Introducing variations in inflorescence architecture, such as the 'Miracle-Wheat' (Triticum turgidum convar. compositum (L.f.) Filat.) with a branching spike, has relevance for enhancing wheat grain yield. However, in the spike-branching genotypes, the increase in spikelet number is generally not translated into grain yield advantage because of reduced grains per spikelet and grain weight. Here, we investigated if such trade-offs might be a function of source-sink strength by using 385 recombinant inbred lines developed by intercrossing the spike-branching landrace TRI 984 and CIRNO C2008, an elite durum (T. durum L.) cultivar; they were genotyped using the 25K array. Various plant and spike architectural traits, including flag leaf, peduncle, and spike senescence rate, were phenotyped under field conditions for 2 consecutive years. On chromosome 5AL, we found a new modifier QTL for spike branching, branched headt3 (bht-A3), which was epistatic to the previously known bht-A1 locus. Besides, bht-A3 was associated with more grains per spikelet and a delay in flag leaf senescence rate. Importantly, favourable alleles, viz. bht-A3 and grain protein content (gpc-B1) that delayed senescence, are required to improve grain number and grain weight in the spike-branching genotypes. In summary, achieving a balanced source-sink relationship might minimize grain yield trade-offs in Miracle-Wheat.

Effects of genetic components of plant development on yield-related traits in wheat (Triticum aestivum L.) under stress-free conditions

The dynamics of plant development not only has an impact on ecological adaptation but also contributes to the realization of genetically determined yield potentials in various environments. Dissecting the genetic determinants of plant development becomes urgent due to the global climate change, which can seriously affect and even disrupt the locally adapted developmental patterns. In order to determine the role plant developmental loci played in local adaptation and yield formation, a panel of 188 winter and facultative wheat cultivars from diverse geographic locations were characterized with the 15K Illumina Single Nucleotide Polymorphism (SNP) chip and functional markers of several plant developmental genes and included into a multiseason field experiment. Genome-wide association analyses were conducted on five consecutive developmental phases spanning from the first node appearance to full heading together with various grain yield-related parameters. The panel was balanced for the PPD-D1 photoperiod response gene, which facilitated the analyses in the two subsets of photoperiod-insensitive and -sensitive genotypes in addition to the complete panel. PPD-D1 was the single highest source, explaining 12.1%-19.0% of the phenotypic variation in the successive developmental phases. In addition, 21 minor developmental loci were identified, each one explaining only small portions of the variance, but, together, their effects amounted to 16.6%-50.6% of phenotypic variance. Eight loci (2A_27, 2A_727, 4A_570, 5B_315, 5B_520, 6A_26, 7A_1-(VRN-A3), and 7B_732) were independent of PPD-D1. Seven loci were only detectable in the PPD-D1-insensitive genetic background (1A_539, 1B_487, 2D_649, 4A_9, 5A_584-(VRN-A1), 5B_571-(VRN-B1), and 7B_3-(VRN-B3)), and six loci were only detectable in the sensitive background, specifically 2A_740, 2D_25, 3A_579, 3B_414, 7A_218, 7A_689, and 7B_538. The combination of PPD-D1 insensitivity and sensitivity with the extremities of early or late alleles in the corresponding minor developmental loci resulted in significantly altered and distinct plant developmental patterns with detectable outcomes on some yield-related traits. This study examines the possible significance of the above results in ecological adaptation.

A single nucleotide deletion in the third exon of FT-D1 increases the spikelet number and delays heading date in wheat (Triticum aestivum L.)

The spikelet number and heading date are two crucial and correlated traits for yield in wheat. Here, a quantitative trait locus (QTL) analysis was conducted in F₈ recombinant inbred lines (RILs) derived from crossing two common wheats with different spikelet numbers. A total of 15 stable QTL influencing total spikelet number (TSN) and heading date (HD) were detected. Notably, FT-D1, a well-known flowering time gene in wheat, was located within the finely mapped interval of a major QTL on 7DS (QTsn/Hd.cau-7D). A causal indel of one G in the third exon of FT-D1 was significantly associated with total spikelet number and heading date. Consistently, CRISPR/Cas9 mutant lines with homozygous mutations in FT-D1 displayed an increase in total spikelet number and heading date when compared with wild type. Moreover, one simple and robust marker developed according to the polymorphic site of FT-D1 revealed that this one G indel had been preferentially selected to adapt to different environments. Collectively, these data provide further insights into the genetic basis of spikelet number and heading date, and the diagnostic marker of FT-D1 will be useful for marker-assisted pyramiding in wheat breeding.

Comprehensive evaluation of mapping complex traits in wheat using genome-wide association studies

Genome-wide association studies (GWAS) are effectively applied to detect the marker trait associations (MTAs) using whole genome-wide variants for complex quantitative traits in different crop species. GWAS has been applied in wheat for different quality, biotic and abiotic stresses, and agronomic and yield-related traits. Predictions for marker-trait associations are controlled with the development of better statistical models taking population structure and familial relatedness into account. In this review, we have provided a detailed overview of the importance of association mapping, population design, high-throughput genotyping and phenotyping platforms, advancements in statistical models and multiple threshold comparisons, and recent GWA studies conducted in wheat. The information about MTAs utilized for gene characterization and adopted in breeding programs is also provided. In the literature that we surveyed, as many as 86,122 wheat lines have been studied under various GWA studies reporting 46,940 loci. However, further utilization of these is largely limited. The future breakthroughs in area of genomic selection, multi-omics-based approaches, machine, and deep learning models in wheat breeding after exploring the complex genetic structure with the GWAS are also discussed. This is a most comprehensive study of a large number of reports on wheat GWAS and gives a comparison and timeline of technological developments in this area. This will be useful to new researchers or groups who wish to invest in GWAS.

Fine Mapping of qd1, a Dominant Gene that Regulates Stem Elongation in Bread Wheat

Stem elongation is a critical phase for yield determination and, as a major trait, is targeted for manipulation for improvement in bread wheat (Triticum aestivum L.). In a previous study, we characterized a mutant showing rapid stem elongation but with no effect on plant height at maturity. The present study aimed to finely map the underlying mutated gene, qd1, in this mutant. By analyzing an F₂ segregating population consisting of 606 individuals, we found that the qd1 gene behaved in a dominant manner. Moreover, by using the bulked segregant RNA sequencing (BSR-seq)-based linkage analysis method, we initially mapped the qd1 gene to a 13.55 Mb region on chromosome 4B (from 15.41 to 28.96 Mb). This result was further confirmed in F₂ and BC₃F₂ segregating populations. Furthermore, by using transcriptome sequencing data, we developed 14 Kompetitive Allele-Specific PCR (KASP) markers and then mapped the qd1 gene to a smaller and more precise 5.08 Mb interval from 26.80 to 31.88 Mb. To develop additional markers to finely map the qd1 gene, a total of 4,481 single-nucleotide polymorphisms (SNPs) within the 5.08 Mb interval were screened, and 25 KASP markers were developed based on 10x-depth genome resequencing data from both wild-type (WT) and mutant plants. The qd1 gene was finally mapped to a 1.33 Mb interval from 28.86 to 30.19 Mb on chromosome 4B. Four candidate genes were identified in this region. Among them, the expression pattern of only TraesCS4B02G042300 in the stems was concurrent with the stem development of the mutant and WT. The qd1 gene could be used in conjunction with molecular markers to manipulate stem development in the future.

Uncovering genomic regions controlling plant architectural traits in hexaploid wheat using different GWAS models

Wheat is a major food crop worldwide. The plant architecture is a complex trait mostly influenced by plant height, tiller number, and leaf morphology. Plant height plays a crucial role in lodging and thus affects yield and grain quality. In this study, a wheat population was genotyped by using Illumina iSelect 90K single nucleotide polymorphism (SNP) assay and finally 22,905 high-quality SNPs were used to perform a genome-wide association study (GWAS) for plant architectural traits employing four multi-locus GWAS (ML-GWAS) and three single-locus GWAS (SL-GWAS) models. As a result, 174 and 97 significant SNPs controlling plant architectural traits were detected by ML-GWAS and SL-GWAS methods, respectively. Among these SNP makers, 43 SNPs were consistently detected, including seven across multiple environments and 36 across multiple methods. Interestingly, five SNPs (Kukri_c34553_89, RAC875_c8121_1490, wsnp_Ex_rep_c66315_64480362, Ku_c5191_340, and tplb0049a09_1302) consistently detected across multiple environments and methods, played a role in modulating both plant height and flag leaf length. Furthermore, candidate SNPs (BS00068592_51, Kukri_c4750_452 and BS00022127_51) constantly repeated in different years and methods associated with flag leaf width and number of tillers. We also detected several SNPs (Jagger_c6772_80, RAC875_c8121_1490, BS00089954_51, Excalibur_01167_1207, and Ku_c5191_340) having common associations with more than one trait across multiple environments. By further appraising these GWAS methods, the pLARmEB and FarmCPU models outperformed in SNP detection compared to the other ML-GWAS and SL-GWAS methods, respectively. Totally, 152 candidate genes were found to be likely involved in plant growth and development. These finding will be helpful for better understanding of the genetic mechanism of architectural traits in wheat.

Transcriptome Analysis Reveals a Potential Role of Benzoxazinoid in Regulating Stem Elongation in the Wheat Mutant qd

The stems of cereal crops provide both mechanical support for lodging resistance and a nutrient supply for reproductive organs. Elongation, which is considered a critical phase for yield determination in winter wheat (Triticum aestivum L.), begins from the first node detectable to anthesis. Previously, we characterized a heavy ion beam triggered wheat mutant qd, which exhibited an altered stem elongation pattern without affecting mature plant height. In this study, we further analyzed mutant stem developmental characteristics by using transcriptome data. More than 40.87 Mb of clean reads including at least 36.61 Mb of unique mapped reads were obtained for each biological sample in this project. We utilized our transcriptome data to identify 124,971 genes. Among these genes, 4,340 differentially expressed genes (DEG) were identified between the qd and wild-type (WT) plants. Compared to their WT counterparts, qd plants expressed 2,462 DEGs with downregulated expression levels and 1878 DEGs with upregulated expression levels. Using DEXSeq, we identified 2,391 counting bins corresponding to 1,148 genes, and 289 of them were also found in the DEG analysis, demonstrating differences between qd and WT. The 5,199 differentially expressed genes between qd and WT were employed for GO and KEGG analyses. Biological processes, including protein-DNA complex subunit organization, protein-DNA complex assembly, nucleosome organization, nucleosome assembly, and chromatin assembly, were significantly enriched by GO analysis. However, only benzoxazinoid biosynthesis pathway-associated genes were enriched by KEGG analysis. Genes encoding the benzoxazinoid biosynthesis enzymes Bx1, Bx3, Bx4, Bx5, and Bx8_9 were confirmed to be differentially expressed between qd and WT. Our results suggest that benzoxazinoids could play critical roles in regulating the stem elongation phenotype of qd.

Temperature response of wheat affects final height and the timing of stem elongation under field conditions

In wheat, temperature affects the timing and intensity of stem elongation. Genetic variation for this process is therefore important for adaptation. This study investigates the genetic response to temperature fluctuations during stem elongation and its relationship to phenology and height. Canopy height of 315 wheat genotypes (GABI wheat panel) was scanned twice weekly in the field phenotyping platform (FIP) of ETH Zurich using a LIDAR. Temperature response was modelled using linear regressions between stem elongation and mean temperature in each measurement interval. This led to a temperature-responsive (slope) and a temperature-irresponsive (intercept) component. The temperature response was highly heritable (H2=0.81) and positively related to a later start and end of stem elongation as well as final height. Genome-wide association mapping revealed three temperature-responsive and four temperature-irresponsive quantitative trait loci (QTLs). Furthermore, putative candidate genes for temperature-responsive QTLs were frequently related to the flowering pathway in Arabidopsis thaliana, whereas temperature-irresponsive QTLs corresponded to growth and reduced height genes. In combination with Rht and Ppd alleles, these loci, together with the loci for the timing of stem elongation, accounted for 71% of the variability in height. This demonstrates how high-throughput field phenotyping combined with environmental covariates can contribute to a smarter selection of climate-resilient crops.

Temperature response of wheat affects final height and the timing of stem elongation under field conditions

In wheat, temperature affects the timing and intensity of stem elongation. Genetic variation for this process is therefore important for adaptation. This study investigates the genetic response to temperature fluctuations during stem elongation and its relationship to phenology and height. Canopy height of 315 wheat genotypes (GABI wheat panel) was scanned twice weekly in the field phenotyping platform (FIP) of ETH Zurich using a LIDAR. Temperature response was modelled using linear regressions between stem elongation and mean temperature in each measurement interval. This led to a temperature-responsive (slope) and a temperature-irresponsive (intercept) component. The temperature response was highly heritable (H2=0.81) and positively related to a later start and end of stem elongation as well as final height. Genome-wide association mapping revealed three temperature-responsive and four temperature-irresponsive quantitative trait loci (QTLs). Furthermore, putative candidate genes for temperature-responsive QTLs were frequently related to the flowering pathway in Arabidopsis thaliana, whereas temperature-irresponsive QTLs corresponded to growth and reduced height genes. In combination with Rht and Ppd alleles, these loci, together with the loci for the timing of stem elongation, accounted for 71% of the variability in height. This demonstrates how high-throughput field phenotyping combined with environmental covariates can contribute to a smarter selection of climate-resilient crops.

Linkage mapping identifies a non-synonymous mutation in FLOWERING LOCUS T (FT-B1) increasing spikelet number per spike

Total spikelet number per spike (TSN) is a major component of spike architecture in wheat (Triticumaestivum L.). A major and consistent quantitative trait locus (QTL) was discovered for TSN in a doubled haploid spring wheat population grown in the field over 4 years. The QTL on chromosome 7B explained up to 20.5% of phenotypic variance. In its physical interval (7B: 6.37–21.67 Mb), the gene FLOWERINGLOCUST (FT-B1) emerged as candidate for the observed effect. In one of the parental lines, FT-B1 carried a non-synonymous substitution on position 19 of the coding sequence. This mutation modifying an aspartic acid (D) into a histidine (H) occurred in a highly conserved position. The mutation was observed with a frequency of ca. 68% in a set of 135 hexaploid wheat varieties and landraces, while it was not found in other plant species. FT-B1 only showed a minor effect on heading and flowering time (FT) which were dominated by a major QTL on chromosome 5A caused by segregation of the vernalization gene VRN-A1. Individuals carrying the FT-B1 allele with amino acid histidine had, on average, a higher number of spikelets (15.1) than individuals with the aspartic acid allele (14.3) independent of their VRN-A1 allele. We show that the effect of TSN is not mainly related to flowering time; however, the duration of pre-anthesis phases may play a major role.

A large-scale genomic association analysis identifies the candidate causal genes conferring stripe rust resistance under multiple field environments

The incorporation of resistance genes into wheat commercial varieties is the ideal strategy to combat stripe or yellow rust (YR). In a search for novel resistance genes, we performed a large-scale genomic association analysis with high-density 660K single nucleotide polymorphism (SNP) arrays to determine the genetic components of YR resistance in 411 spring wheat lines. Following quality control, 371 972 SNPs were screened, covering over 50% of the high-confidence annotated gene space. Nineteen stable genomic regions harbouring 292 significant SNPs were associated with adult-plant YR resistance across nine environments. Of these, 14 SNPs were localized in the proximity of known loci widely used in breeding. Obvious candidate SNP variants were identified in certain confidence intervals, such as the cloned gene Yr18 and the major locus on chromosome 2BL, despite a large extent of linkage disequilibrium. The number of causal SNP variants was refined using an independent validation panel and consideration of the estimated functional importance of each nucleotide polymorphism. Interestingly, four natural polymorphisms causing amino acid changes in the gene TraesCS2B01G513100 that encodes a serine/threonine protein kinase (STPK) were significantly involved in YR responses. Gene expression and mutation analysis confirmed that STPK played an important role in YR resistance. PCR markers were developed to identify the favourable TraesCS2B01G513100 haplotype for marker-assisted breeding. These results demonstrate that high-resolution SNP-based GWAS enables the rapid identification of putative resistance genes and can be used to improve the efficiency of marker-assisted selection in wheat disease resistance breeding.

Silencing of TaCKX1 Mediates Expression of Other TaCKX Genes to Increase Yield Parameters in Wheat

TaCKX, Triticum aestivum (cytokinin oxidase/dehydrogenase) family genes influence the development of wheat plants by the specific regulation of cytokinin content in different organs. However, their detailed role is not known. The TaCKX1, highly and specifically expressed in developing spikes and in seedling roots, was silenced by RNAi-mediated gene silencing via Agrobacterium tumefaciens and the effect of silencing was investigated in 7 DAP (days after pollination) spikes of T₁ and T₂ generations. Various levels of TaCKX1 silencing in both generations influence different models of co-expression with other TaCKX genes and parameters of yield-related traits. Only a high level of silencing in T₂ resulted in strong down-regulation of TaCKX11 (3), up-regulation of TaCKX2.1, 2.2, 5, and 9 (10), and a high yielding phenotype. This phenotype is characterized by a higher spike number, grain number, and grain yield, but lower thousand grain weight (TGW). The content of most of cytokinin forms in 7 DAP spikes of silenced T₂ lines increased from 23% to 76% compared to the non-silenced control. The CKs cross talk with other phytohormones. Each of the tested yield-related traits is regulated by various up- or down-regulated TaCKX genes and phytohormones. The coordinated effect of TaCKX1 silencing on the expression of other TaCKX genes, phytohormone levels in 7 DAP spikes, and yield-related traits in silenced T₂ lines is presented.

Automated Spike Detection in Diverse European Wheat Plants Using Textural Features and the Frangi Filter in 2D Greenhouse Images

Spike is one of the crop yield organs in wheat plants. Determination of the phenological stages, including heading time point (HTP), and area of spike from non-invasive phenotyping images provides the necessary information for the inference of growth-related traits. The algorithm previously developed by Qiongyan et al. for spike detection in 2-D images turns out to be less accurate when applied to the European cultivars that produce many more leaves. Therefore, we here present an improved and extended method where (i) wavelet amplitude is used as an input to the Laws texture energy-based neural network instead of original grayscale images and (ii) non-spike structures (e.g., leaves) are subsequently suppressed by combining the result of the neural network prediction with a Frangi-filtered image. Using this two-step approach, a 98.6% overall accuracy of neural network segmentation based on direct comparison with ground-truth data could be achieved. Moreover, the comparative error rate in spike HTP detection and growth correlation among the ground truth, the algorithm developed by Qiongyan et al., and the proposed algorithm are discussed in this paper. The proposed algorithm was also capable of significantly reducing the error rate of the HTP detection by 75% and improving the accuracy of spike area estimation by 50% in comparison with the Qionagyan et al. method. With these algorithmic improvements, HTP detection on a diverse set of 369 plants was performed in a high-throughput manner. This analysis demonstrated that the HTP of 104 plants (comprises of 57 genotypes) with lower biomass and tillering range (e.g., earlier-heading types) were correctly determined. However, fine-tuning or extension of the developed method is required for high biomass plants where spike emerges within green bushes. In conclusion, our proposed method allows significantly more reliable results for HTP detection and spike growth analysis to be achieved in application to European cultivars with earlier-heading types.

Invited review: Advances and applications of random regression models: From quantitative genetics to genomics

An important goal in animal breeding is to improve longitudinal traits; that is, traits recorded multiple times during an individual's lifetime or physiological cycle. Longitudinal traits were first genetically evaluated based on accumulated phenotypic expression, phenotypic expression at specific time points, or repeatability models. Until now, the genetic evaluation of longitudinal traits has mainly focused on using random regression models (RRM). Random regression models enable fitting random genetic and environmental effects over time, which results in higher accuracy of estimated breeding values compared with other statistical approaches. In addition, RRM provide insights about temporal variation of biological processes and the physiological implications underlying the studied traits. Despite the fact that genomic information has substantially contributed to increase the rates of genetic progress for a variety of economically important traits in several livestock species, less attention has been given to longitudinal traits in recent years. However, including genomic information to evaluate longitudinal traits using RRM is a feasible alternative to yield more accurate selection and culling decisions, because selection of young animals may be based on the complete pattern of the production curve with higher accuracy compared with the use of traditional parent average (i.e., without genomic information). Moreover, RRM can be used to estimate SNP effects over time in genome-wide association studies. Thus, by analyzing marker associations over time, regions with higher effects at specific points in time are more likely to be identified. Despite the advances in applications of RRM in genetic evaluations, more research is needed to successfully combine RRM and genomic information. Future research should provide a better understanding of the temporal variation of biological processes and their physiological implications underlying the longitudinal traits.

Whole-Genome Resequencing of a Worldwide Collection of Rapeseed Accessions Reveals the Genetic Basis of Ecotype Divergence

Rapeseed (Brassica napus), an important oilseed crop, has adapted to diverse climate zones and latitudes by forming three main ecotype groups, namely winter, semi-winter, and spring types. However, genetic variations underlying the divergence of these ecotypes are largely unknown. Here, we report the global pattern of genetic polymorphisms in rapeseed determined by resequencing a worldwide collection of 991 germplasm accessions. A total of 5.56 and 5.53 million single-nucleotide polymorphisms (SNPs) as well as 1.86 and 1.92 million InDels were identified by mapping reads to the reference genomes of "Darmor-bzh" and "Tapidor," respectively. We generated a map of allelic drift paths that shows splits and mixtures of the main populations, and revealed an asymmetric evolution of the two subgenomes of B. napus by calculating the genetic diversity and linkage disequilibrium parameters. Selective-sweep analysis revealed genetic changes in genes orthologous to those regulating various aspects of plant development and response to stresses. A genome-wide association study identified SNPs in the promoter regions of FLOWERING LOCUS T and FLOWERING LOCUS C orthologs that corresponded to the different rapeseed ecotype groups. Our study provides important insights into the genomic footprints of rapeseed evolution and flowering-time divergence among three ecotype groups, and will facilitate screening of molecular markers for accelerating rapeseed breeding.