A novel genetic map of wheat: utility for mapping QTL for yield under different nitrogen treatments

Characterization of a wheat stable QTL for spike length and its genetic effects on yield-related traits

Spike length (SL) is one of the most important agronomic traits affecting yield potential and stability in wheat. In this study, a major stable quantitative trait locus (QTL) for SL, i.e., qSl-2B, was detected in multiple environments in a recombinant inbred line (RIL) mapping population, KJ-RILs, derived from a cross between Kenong 9204 (KN9204) and Jing 411 (J411). The qSl-2B QTL was mapped to the 60.06-73.06 Mb region on chromosome 2B and could be identified in multiple mapping populations. An InDel molecular marker in the target region was developed based on a sequence analysis of the two parents. To further clarify the breeding use potential of qSl-2B, we analyzed its genetic effects and breeding selection effect using both the KJ-RIL population and a natural mapping population, which consisted of 316 breeding varieties/advanced lines. The results showed that the qSl-2B alleles from KN9204 showed inconsistent genetic effects on SL in the two mapping populations. Moreover, in the KJ-RILs population, the additive effects analysis of qSl-2B showed that additive effect was higher when both qSl-2D and qSl-5A harbor negative alleles under LN and HN. In China, a moderate selection utilization rate for qSl-2B was found in the Huanghuai winter wheat area and the selective utilization rate for qSl-2B continues to increase. The above findings provided a foundation for the genetic improvement of wheat SL in the future via molecular breeding strategies.

Quantitative trait loci detection for three tiller-related traits and the effects on wheat (Triticum aestivum L.) yields

KEY MESSAGE

A total of 38 putative additive QTLs and 55 pairwise putative epistatic QTLs for tiller-related traits were reported, and the candidate genes underlying qMtn-KJ-5D, a novel major and stable QTL for maximum tiller number, were characterized. Tiller-related traits play an important role in determining the yield potential of wheat. Therefore, it is important to elucidate the genetic basis for tiller number when attempting to use genetic improvement as a tool for enhancing wheat yields. In this study, a quantitative trait locus (QTL) analysis of three tiller-related traits was performed on the recombinant inbred lines (RILs) of a mapping population, referred to as KJ-RILs, that was derived from a cross between the Kenong 9204 (KN9204) and Jing 411 (J411) lines. A total of 38 putative additive QTLs and 55 pairwise putative epistatic QTLs for spike number per plant (SNPP), maximum tiller number (MTN), and ear-bearing tiller rate (EBTR) were detected in eight different environments. Among these QTLs with additive effects, three major and stable QTLs were first documented herein. Almost all but two pairwise epistatic QTLs showed minor interaction effects accounting for no more than 3.0% of the phenotypic variance. The genetic effects of two colocated major and stable QTLs, i.e., qSnpp-KJ-5D.1 and qMtn-KJ-5D, for yield-related traits were characterized. The breeding selection effect of the beneficial allele for the two QTLs was characterized, and its genetic effects on yield-related traits were evaluated. The candidate genes underlying qMtn-KJ-5D were predicted based on multi-omics data, and TraesKN5D01HG00080 was identified as a likely candidate gene. Overall, our results will help elucidate the genetic architecture of tiller-related traits and can be used to develop novel wheat varieties with high yields.

Heat Stress-Tolerant Quantitative Trait Loci Identified Using Backcrossed Recombinant Inbred Lines Derived from Intra-Specifically Diverse Aegilops tauschii Accessions

In the face of climate change, bringing more useful alleles and genes from wild relatives of wheat is crucial to develop climate-resilient varieties. We used two populations of backcrossed recombinant inbred lines (BIL1 and BIL2), developed by crossing and backcrossing two intra-specifically diverse Aegilops tauschii accessions from lineage 1 and lineage 2, respectively, with the common wheat cultivar 'Norin 61'. This study aimed to identify quantitative trait loci (QTLs) associated with heat stress (HS) tolerance. The two BILs were evaluated under heat stress environments in Sudan for phenology, plant height (PH), grain yield (GY), biomass (BIO), harvest index (HI), and thousand-kernel weight (TKW). Grain yield was significantly correlated with BIO and TKW under HS; therefore, the stress tolerance index (STI) was calculated for these traits as well as for GY. A total of 16 heat-tolerant lines were identified based on GY and STI-GY. The QTL analysis performed using inclusive composite interval mapping identified a total of 40 QTLs in BIL1 and 153 QTLs in BIL2 across all environments. We detected 39 QTLs associated with GY-STI, BIO-STI, and TKW-STI in both populations (14 in BIL1 and 25 in BIL2). The QTLs associated with STI were detected on chromosomes 1A, 3A, 5A, 2B, 4B, and all the D-subgenomes. We found that QTLs were detected only under HS for GY on chromosome 5A, TKW on 3B and 5B, PH on 3B and 4B, and grain filling duration on 2B. The higher number of QTLs identified in BIL2 for heat stress tolerance suggests the importance of assessing the effects of intraspecific variation of Ae. tauschii in wheat breeding as it could modulate the heat stress responses/adaptation. Our study provides useful genetic resources for uncovering heat-tolerant QTLs for wheat improvement for heat stress environments.

Mining Aegilops tauschii genetic diversity in the background of bread wheat revealed a novel QTL for seed dormancy

Due to the low genetic diversity in the current wheat germplasm, gene mining from wild relatives is essential to develop new wheat cultivars that are more resilient to the changing climate. Aegilops tauschii, the D-genome donor of bread wheat, is a great gene source for wheat breeding; however, identifying suitable genes from Ae. tauschii is challenging due to the different morphology and the wide intra-specific variation within the species. In this study, we developed a platform for the systematic evaluation of Ae. tauschii traits in the background of the hexaploid wheat cultivar 'Norin 61' and thus for the identification of QTLs and genes. To validate our platform, we analyzed the seed dormancy trait that confers resistance to preharvest sprouting. We used a multiple synthetic derivative (MSD) population containing a genetic diversity of 43 Ae. tauschii accessions representing the full range of the species. Our results showed that only nine accessions in the population provided seed dormancy, and KU-2039 from Afghanistan had the highest level of seed dormancy. Therefore, 166 backcross inbred lines (BILs) were developed by crossing the synthetic wheat derived from KU-2039 with 'Norin 61' as the recurrent parent. The QTL mapping revealed one novel QTL, Qsd.alrc.5D, associated with dormancy explaining 41.7% of the phenotypic variation and other five unstable QTLs, two of which have already been reported. The Qsd.alrc.5D, identified for the first time within the natural variation of wheat, would be a valuable contribution to breeding after appropriate validation. The proposed platform that used the MSD population derived from the diverse Ae. tauschii gene pool and recombinant inbred lines proved to be a valuable platform for mining new and important QTLs or alleles, such as the novel seed dormancy QTL identified here. Likewise, such a platform harboring genetic diversity from wheat wild relatives could be a useful source for mining agronomically important traits, especially in the era of climate change and the narrow genetic diversity within the current wheat germplasm.

Genetic regions determine tolerance to nitrogen deficiency in European elite bread wheats grown under contrasting nitrogen stress scenarios

KEY MESSAGE

Clustering 24 environments in four contrasting nitrogen stress scenarios enabled the detection of genetic regions determining tolerance to nitrogen deficiency in European elite bread wheats. Increasing the nitrogen use efficiency of wheat varieties is an important goal for breeding. However, most genetic studies of wheat grown at different nitrogen levels in the field report significant interactions with the genotype. The chromosomal regions possibly involved in these interactions are largely unknown. The objective of this study was to quantify the response of elite bread wheat cultivars to different nitrogen field stress scenarios and identify genomic regions involved in this response. For this purpose, 212 elite bread wheat varieties were grown in a multi-environment trial at different nitrogen levels. Genomic regions associated with grain yield, protein concentration and grain protein deviation responses to nitrogen deficiency were identified. Environments were clustered according to adjusted means for grain yield, yield components and grain protein concentration. Four nitrogen availability scenarios were identified: optimal condition, moderate early deficiency, severe late deficiency, and severe continuous deficiency. A large range of tolerance to nitrogen deficiency was observed among varieties, which were ranked differently in different nitrogen deficiency scenarios. The well-known negative correlation between grain yield and grain protein concentration also existed between their respective tolerance indices. Interestingly, the tolerance indices for grain yield and grain protein deviation were either null or weakly positive meaning that breeding for the two traits should be less difficult than expected. Twenty-two QTL regions were identified for the tolerance indices. By selecting associated markers, these regions may be selected separately or combined to improve the tolerance to N deficiency within a breeding programme.

Characterization and fine mapping analysis of a major stable QTL qKnps-4A for kernel number per spike in wheat

KEY MESSAGE

A major stable QTL for kernel number per spike was narrowed down to a 2.19-Mb region containing two potential candidate genes, and its effects on yield-related traits were characterized. Kernel number per spike (KNPS) in wheat is a key yield component. Dissection and characterization of major stable quantitative trait loci (QTLs) for KNPS would be of considerable value for the genetic improvement of yield potential using molecular breeding technology. We had previously reported a major stable QTL controlling KNPS, qKnps-4A. In the current study, primary fine-mapping analysis, based on the primary mapping population, located qKnps-4A to an interval of approximately 6.8-Mb from 649.0 to 655.8 Mb on chromosome 4A refering to 'Kenong 9204' genome. Further fine-mapping analysis based on a secondary mapping population narrowed qKnps-4A to an approximately 2.19-Mb interval from 653.72 to 655.91 Mb. Transcriptome sequencing, gene function annotation analysis and homologous gene related reports showed that TraesKN4A01HG38570 and TraesKN4A01HG38590 were most likely to be candidate genes of qKnps-4A. Phenotypic analysis based on paired near-isogenic lines in the target region showed that qKnps-4A increased KNPS mainly by increasing the number of central florets per spike. We also evaluated the effects of qKnps-4A on other yield-related traits. Moreover, we dissected the QTL cluster of qKnps-4A and qTkw-4A and proved that the phenotypic effects were probably due to close linkage of two or more genes rather than pleiotropic effects of a single gene. This study provides molecular marker resource for wheat molecular breeding designed to improve yield potential, and lay the foundation for gene functional analysis of qKnps-4A.

QTL Mapping of Agronomic and Physiological Traits at the Seedling and Maturity Stages under Different Nitrogen Treatments in Barley

Nitrogen (N) stress seriously constrains barley (Hordeum vulgare L.) production globally by influencing its growth and development. In this study, we used a recombinant inbred line (RIL) population of 121 crosses between the variety Baudin and the wild barley accession CN4027 to detect QTL for 27 traits at the seedling stage in hydroponic culture trials and 12 traits at the maturity stage in field trials both under two N treatments, aiming to uncover favorable alleles for N tolerance in wild barley. In total, eight stable QTL and seven QTL clusters were detected. Among them, the stable QTL Qtgw.sau-2H located in a 0.46 cM interval on the chromosome arm 2HL was a novel QTL specific for low N. Notably, Clusters C4 and C7 contained QTL for traits at both the seedling and maturity stages. In addition, four stable QTLs in Cluster C4 were identified. Furthermore, a gene (HORVU2Hr1G080990.1) related to grain protein in the interval of Qtgw.sau-2H was predicted. Correlation analysis and QTL mapping showed that different N treatments significantly affected agronomic and physiological traits at the seedling and maturity stages. These results provide valuable information for understanding N tolerance as well as breeding and utilizing the loci of interest in barley.

Current Progress and Future Prospect of Wheat Genetics Research towards an Enhanced Nitrogen Use Efficiency

To improve the yield and quality of wheat is of great importance for food security worldwide. One of the most effective and significant approaches to achieve this goal is to enhance the nitrogen use efficiency (NUE) in wheat. In this review, a comprehensive understanding of the factors involved in the process of the wheat nitrogen uptake, assimilation and remobilization of nitrogen in wheat were introduced. An appropriate definition of NUE is vital prior to its precise evaluation for the following gene identification and breeding process. Apart from grain yield (GY) and grain protein content (GPC), the commonly recognized major indicators of NUE, grain protein deviation (GPD) could also be considered as a potential trait for NUE evaluation. As a complex quantitative trait, NUE is affected by transporter proteins, kinases, transcription factors (TFs) and micro RNAs (miRNAs), which participate in the nitrogen uptake process, as well as key enzymes, circadian regulators, cross-talks between carbon metabolism, which are associated with nitrogen assimilation and remobilization. A series of quantitative genetic loci (QTLs) and linking markers were compiled in the hope to help discover more efficient and useful genetic resources for breeding program. For future NUE improvement, an exploration for other criteria during selection process that incorporates morphological, physiological and biochemical traits is needed. Applying new technologies from phenomics will allow high-throughput NUE phenotyping and accelerate the breeding process. A combination of multi-omics techniques and the previously verified QTLs and molecular markers will facilitate the NUE QTL-mapping and novel gene identification.

Development and marker-trait relationships of functional markers for glutamine synthetase GS1 and GS2 homoeogenes in bread wheat

GS1 and GS2 genes encode, respectively, the main cytosolic and the plastidic isoforms of glutamine synthetase (GS). In the present study, the wheat GS1 and GS2 homoeogenes located in the A, B and D genome chromosomes have been sequenced in a group of 15 bread wheat varieties including landraces, old commercial varieties and modern cultivars. Phenotypic characterization by multi-environment field trials detected significant effects of specific GS homoeogenes on three of the seven agronomic and grain quality traits analyzed. Based on the gene sequence polymorphisms found, biallelic molecular markers that could facilitate marker-assisted breeding were developed for genes GS1A, GS2A and GS2D. The remaining genes encoding main wheat GS were excluded because of being monomorphic (GS1D) or too polymorphic (GS1B and GS2B) in the sequencing panel varieties. A collection of 187 Spanish bread wheat landraces was genotyped for these gene-based molecular markers. Data analyses conducted with phenotypic records reported for this germplasm collection in López-Fernández et al. (Plants-Basel 10: 620, 2021) have revealed the beneficial influence of some individual alleles on thousand-kernel weight (TKW), kernels per spike (KS) and grain protein content. Furthermore, genetic interactions between GS1A, a cytosolic GS isoform coding gene, and GS2A or GS2D, plastidic GS enzyme coding genes, were found to affect TKW and KS. The finding that some alleles at one locus may mask the effect of positive alleles at hypostatic GS loci should be kept in mind if gene pyramiding strategies are attempted for the improvement of N-use efficiency-related traits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01354-0.

Preliminary Dissection of Grain Yield and Related Traits at Differential Nitrogen Levels in Diverse Pre-Breeding Wheat Germplasm Through Association Mapping

Development of nutrient efficient cultivars depends on effective identification and utilization of genetic variation. We characterized a set of 276 pre-breeding lines (PBLs) for several traits at different levels of nitrogen application. These PBLs originate from synthetic wheats and landraces. We witnessed significant variation in various traits among PBLs to different nitrogen doses. There was ~ 4-18% variation range in different agronomic traits in response to nitrogen application, with the highest variation for the biological yield (BY) and the harvest index. Among various agronomic traits measured, plant height, tiller number, and BY showed a positive correlation with nitrogen applications. GWAS analysis detected 182 marker-trait associations (MTAs) (at p-value < 0.001), out of which 8 MTAs on chromosomes 5D, 4A, 6A, 1B, and 5B explained more than 10% phenotypic variance. Out of all, 40 MTAs observed for differential nitrogen application response were contributed by the synthetic derivatives. Moreover, 20 PBLs exhibited significantly higher grain yield than checks and can be selected as potential donors for improved plant nitrogen use efficiency (pNUE).

Identification of a novel major QTL from Chinese wheat cultivar Ji5265 for Fusarium head blight resistance in greenhouse

A novel major QTL for FHB resistance was mapped to a 6.8 Mb region on chromosome 2D in a Chinese wheat cultivar Ji5265, and diagnostic KASP markers were developed for detecting it in a worldwide wheat collection. Fusarium head blight (FHB) is a serious disease in wheat (Triticum aestivum L.) and causes significant reductions in grain yield and quality worldwide. Breeding for FHB resistance is the most effective strategy to minimize the losses caused by FHB; therefore, identification of major quantitative trait loci (QTLs) conferring FHB resistance and development of diagnostic markers for the QTLs are prerequisites for marker-assisted selection (MAS). Ji5265 is a Chinese wheat cultivar resistant to FHB in multiple environments. An F₆ population of 179 recombinant inbred lines (RILs) was developed from Ji5265 × Wheaton. The population was genotyped by genotyping-by-sequencing (GBS) and phenotyped for FHB Type II resistance in greenhouses. A major QTL, designated as QFhb-2DL, was mapped in a 6.8 Mb region between the markers GBS10238 and GBS12056 on the long arm of chromosome 2D in Ji5265 and explained ~ 30% of the phenotypic variation for FHB resistance. The effect of QFhb-2DL on FHB resistance was validated using near-isogenic lines (NILs) derived from residual heterozygotes from an F₆ RIL of Ji5265 × Wheaton. The two flanking markers were converted into Kompetitive allele-specific PCR (KASP) markers (KASP10238 and KASP12056) and validated to be diagnostic in a collection of 2,065 wheat accessions. These results indicate that QFhb-2DL is a novel major QTL for resistance to FHB spread within a spike (Type II) and the two KASP markers can be used for MAS to improve wheat FHB resistance in wheat breeding programs.

Identification of Main-Effect and Environmental Interaction QTL and Their Candidate Genes for Drought Tolerance in a Wheat RIL Population Between Two Elite Spring Cultivars

Understanding the genetics of drought tolerance can expedite the development of drought-tolerant cultivars in wheat. In this study, we dissected the genetics of drought tolerance in spring wheat using a recombinant inbred line (RIL) population derived from a cross between a drought-tolerant cultivar, ‘Reeder’ (PI613586), and a high-yielding but drought-susceptible cultivar, ‘Albany.’ The RIL population was evaluated for grain yield (YLD), grain volume weight (GVW), thousand kernel weight (TKW), plant height (PH), and days to heading (DH) at nine different environments. The Infinium 90 k-based high-density genetic map was generated using 10,657 polymorphic SNP markers representing 2,057 unique loci. Quantitative trait loci (QTL) analysis detected a total of 11 consistent QTL for drought tolerance-related traits. Of these, six QTL were exclusively identified in drought-prone environments, and five were constitutive QTL (identified under both drought and normal conditions). One major QTL on chromosome 7B was identified exclusively under drought environments and explained 13.6% of the phenotypic variation (PV) for YLD. Two other major QTL were detected, one each on chromosomes 7B and 2B under drought-prone environments, and explained 14.86 and 13.94% of phenotypic variation for GVW and YLD, respectively. One novel QTL for drought tolerance was identified on chromosome 2D. In silico expression analysis of candidate genes underlaying the exclusive QTLs associated with drought stress identified the enrichment of ribosomal and chloroplast photosynthesis-associated proteins showing the most expression variability, thus possibly contributing to stress response by modulating the glycosyltransferase (TraesCS6A01G116400) and hexosyltransferase (TraesCS7B01G013300) unique genes present in QTL 21 and 24, respectively. While both parents contributed favorable alleles to these QTL, unexpectedly, the high-yielding and less drought-tolerant parent contributed desirable alleles for drought tolerance at four out of six loci. Regardless of the origin, all QTL with significant drought tolerance could assist significantly in the development of drought-tolerant wheat cultivars, using genomics-assisted breeding approaches.

Wheat FRIZZY PANICLE activates VERNALIZATION1-A and HOMEOBOX4-A to regulate spike development in wheat

Kernel number per spike determined by the spike or inflorescence development is one important agricultural trait for wheat yield that is critical for global food security. While a few important genes for wheat spike development were identified, the genetic regulatory mechanism underlying supernumerary spikelets (SSs) is still unclear. Here, we cloned the wheat FRIZZY PANICLE (WFZP) gene from one local wheat cultivar. WFZP is specifically expressed at the sites where the spikelet meristem and floral meristem are initiated, which differs from the expression patterns of its homologs FZP/BD1 in rice and maize, indicative of its functional divergence during species differentiation. Moreover, WFZP directly activates VERNALIZATION1 (VRN1) and wheat HOMEOBOX4 (TaHOX4) to regulate the initiation and development of spikelet. The haplotypes analysis showed that the favourable alleles of WFZP associated with spikelet number per spike (SNS) were preferentially selected during breeding. Our findings provide insights into the molecular and genetic mechanisms underlying wheat spike development and characterize the WFZP as elite resource for wheat molecular breeding with enhanced crop yield.

Genetic regulation of the traits contributing to wheat nitrogen use efficiency

High nitrogen application aimed at increasing crop yield is offset by higher production costs and negative environmental consequences. For wheat, only one third of the applied nitrogen is utilized, which indicates there is scope for increasing Nitrogen Use Efficiency (NUE). However, achieving greater NUE is challenged by the complexity of the trait, which comprises processes associated with nitrogen uptake, transport, reduction, assimilation, translocation and remobilization. Thus, knowledge of the genetic regulation of these processes is critical in increasing NUE. Although primary nitrogen uptake and metabolism-related genes have been well studied, the relative influence of each towards NUE is not fully understood. Recent attention has focused on engineering transcription factors and identification of miRNAs acting on expression of specific genes related to NUE. Knowledge obtained from model species needs to be translated into wheat using recently-released whole genome sequences, and by exploring genetic variations of NUE-related traits in wild relatives and ancient germplasm. Recent findings indicate the genetic basis of NUE is complex. Pyramiding various genes will be the most effective approach to achieve a satisfactory level of NUE in the field.

Identification of quantitative trait loci associated with nitrogen use efficiency in winter wheat

Maintaining winter wheat (Triticum aestivum L.) productivity with more efficient nitrogen (N) management will enable growers to increase profitability and reduce the negative environmental impacts associated with nitrogen loss. Wheat breeders would therefore benefit greatly from the identification and application of genetic markers associated with nitrogen use efficiency (NUE). To investigate the genetics underlying N response, two bi-parental mapping populations were developed and grown in four site-seasons under low and high N rates. The populations were derived from a cross between previously identified high NUE parents (VA05W-151 and VA09W-52) and a shared common low NUE parent, ‘Yorktown.’ The Yorktown × VA05W-151 population was comprised of 136 recombinant inbred lines while the Yorktown × VA09W-52 population was comprised of 138 doubled haploids. Phenotypic data was collected on parental lines and their progeny for 11 N-related traits and genotypes were sequenced using a genotyping-by-sequencing platform to detect more than 3,100 high quality single nucleotide polymorphisms in each population. A total of 130 quantitative trait loci (QTL) were detected on 20 chromosomes, six of which were associated with NUE and N-related traits in multiple testing environments. Two of the six QTL for NUE were associated with known photoperiod (Ppd-D1 on chromosome 2D) and disease resistance (FHB-4A) genes, two were reported in previous investigations, and one QTL, QNue.151-1D, was novel. The NUE QTL on 1D, 6A, 7A, and 7D had LOD scores ranging from 2.63 to 8.33 and explained up to 18.1% of the phenotypic variation. The QTL identified in this study have potential for marker-assisted breeding for NUE traits in soft red winter wheat.

Reference Genome Anchoring of High-Density Markers for Association Mapping and Genomic Prediction in European Winter Wheat

In this study, we anchored genotyping-by-sequencing data to the International Wheat Genome Sequencing Consortium Reference Sequence v1.0 assembly to generate over 40,000 high quality single nucleotide polymorphism markers on a panel of 376 elite European winter wheat varieties released between 1946 and 2007. We compared association mapping and genomic prediction accuracy for a range of productivity traits with previous results based on lower density dominant DArT markers. The results demonstrate that the availability of RefSeq v1.0 supports higher precision trait mapping and provides the density of markers required to obtain accurate predictions of traits controlled by multiple small effect loci, including grain yield.

A combined association mapping and t-test analysis of SNP loci and candidate genes involving in resistance to low nitrogen traits by a wheat mutant population

Crop productivity is highly dependent on the application of N fertilizers, but ever-increasing N application is causing serious environmental impacts. To facilitate the development of new wheat cultivars that can thrive in low N growth conditions, key loci and genes associated with wheat responses to low N must be identified. In this GWAS and t-test study of 190 M6 mutant wheat lines (Jing 411-derived) based on genotype data from the wheat 660k SNP array, we identified a total of 221 significant SNPs associated four seedling phenotypic traits that have been implicated in resistance to low N: relative root length, relative shoot length, relative root weight, and relative shoot weight. Notably, we detected large numbers of significantly associated SNP in what appear to be genomic 'hotspots' for resistance to low N on chromosomes 2A and 6B, strongly suggesting that these regions are functionally related to the resistance phenotypes that we observed in some of the mutant lines. Moreover, the candidate genes, including genes encoding high-affinity nitrate transporter 2.1, gibberellin responsive protein, were identified for resistance to low N. This study raises plausible mechanistic hypotheses that can be evaluated in future applied or basic efforts by breeders or plant biologists seeking to develop new high-NUE wheat cultivars.

Identification of QTL regions for seedling root traits and their effect on nitrogen use efficiency in wheat (Triticum aestivum L.)

QTL for a wheat ideotype root system and its plasticity to nitrogen deficiency were characterized. Root system architecture-related traits (RRTs) and their plasticity to nitrogen availability are important for nitrogen acquisition and yield formation in wheat (Triticum aestivum L.). In this study, quantitative trait loci (QTL) analysis was conducted under different nitrogen conditions, using the seedlings of 188 recombinant inbred lines derived from a cross between Kenong 9204 and Jing 411. Fifty-three QTL for seven RRTs and fourteen QTL for the plasticity of these RRTs to nitrogen deficiency were detected. Thirty of these QTL were mapped in nine clusters on chromosomes 2B, 2D, 3A, 3D, 6B, 6D, 7A and 7B. Six of these nine clusters were also colocated with loci for nitrogen use efficiency (NUE)-related traits (NRTs). Among them, three QTL clusters (C2B, C6D and C7B) were highlighted, considering that they individually harbored three stable robust QTL (i.e., QMrl-2B.1, QdRs-6D and QMrl-7B). C2B and C7B stably contributed to the optimal root system, and C6D greatly affected the plasticity of RRTs in response to nitrogen deficiency. However, strong artificial selection was only observed for C7B in 574 derivatives of Kenong 9204. Covariance analysis identified QMrl-7B as the major contributor in C7B that affected the investigated NRTs in mature plants. Phenotypic analysis indicated that thousand kernel weight might represent a "concomitant" above-ground trait of the "hidden" RRTs controlled by C7B, which are used for breeding selection. Dissecting these QTL regions with potential breeding value will ultimately facilitate the selection of donor lines with both high yield and NUE in wheat breeding programs.

Genetic dissection of the mechanism of flowering time based on an environmentally stable and specific QTL in Brassica napus

Flowering time is an important agronomic trait that is highly influenced by the environment. To elucidate the genetic mechanism of flowering time in rapeseed (Brassica napus L.), a genome-wide QTL analysis was performed in a doubled haploid population grown in winter, semi-winter and spring ecological conditions. Fifty-five consensus QTLs were identified after combining phenotype and genomic data, including 12 environment-stable QTLs and 43 environment-specific QTLs. Importantly, six major QTLs for flowering time were identified, of which two were considered environment-specific QTLs in spring ecological condition and four were considered environment-stable QTLs in winter and semi-winter ecological conditions. Through QTL comparison, 18 QTLs were colocalized with QTLs from six other published studies. Combining the candidate genes with their functional annotation, in 49 of 55 consensus QTLs, 151 candidate genes in B. napus corresponding to 95 homologous genes in Arabidopsis thaliana related to flowering were identified, including BnaC03g32910D (CO), BnaA02g12130D (FT) and BnaA03g13630D (FLC). Most of the candidate genes were involved in different flowering regulatory pathways. Based on re-sequencing and differences in sequence annotation between the two parents, we found that regions containing some candidate genes have numerous non-frameshift InDels and many non- synonymous mutations, which might directly lead to gene functional variation. Flowering time was negativly correlated with seed yield and thousand seed weight based on a QTL comparison of flowering time and seed yield traits, which has implications in breeding new early-maturing varieties of B. napus. Moreover, a putative flowering regulatory network was constructed, including the photoperiod, circadian clock, vernalization, autonomous and gibberellin pathways. Multiple copies of genes led to functional difference among the different copies of homologous genes, which also increased the complexity of the flowering regulatory networks. Taken together, the present results not only provide new insights into the genetic regulatory network underlying the control of flowering time but also improve our understanding of flowering time regulatory pathways in rapeseed.

A Genome-wide View of Transcriptome Dynamics During Early Spike Development in Bread Wheat

Wheat spike development is a coordinated process of cell proliferation and differentiation with distinctive phases and architecture changes. However, the dynamic alteration of gene expression in this process remains enigmatic. Here, we characterized and dissected bread wheat spike into six developmental stages, and used genome-wide gene expression profiling, to investigate the underlying regulatory mechanisms. High gene expression correlations between any two given stages indicated that wheat early spike development is controlled by a small subset of genes. Throughout, auxin signaling increased, while cytokinin signaling decreased. Besides, many genes associated with stress responses highly expressed during the double ridge stage. Among the differentially expressed genes (DEGs), were identified 375 transcription factor (TF) genes, of which some homologs in rice or Arabidopsis are proposed to function in meristem maintenance, flowering time, meristem initiation or transition, floral organ development or response to stress. Gene expression profiling demonstrated that these genes had either similar or distinct expression pattern in wheat. Several genes regulating spike development were expressed in the early spike, of which Earliness per se 3 (Eps-3) was found might function in the initiation of spikelet meristem. Our study helps uncover important genes associated with apical meristem morphology and development in wheat.

Integrated genomics, physiology and breeding approaches for improving nitrogen use efficiency in potato: translating knowledge from other crops

Potato plays a key role in global food and nutritional security. Potato is an N fertiliser-responsive crop, producing high tuber yields. However, excessive use of N can result in environmental damage and high production costs, hence improving nitrogen use efficiency (NUE) of potato plants is one of the sustainable options to address these issues and increase yield. Advanced efforts have been undertaken to improve NUE in other plants like Arabidopsis, rice, wheat and maize through molecular and physiological approaches. Conversely, in potato, NUE studies have predominantly focussed on agronomy or soil management, except for a few researchers who have measured gene expression and proteins relevant to N uptake or metabolism. The focus of this review is to adapt knowledge gained from other plants to inform investigation of N metabolism and associated traits in potato with the aim of improving potato NUE using integrated genomics, physiology and breeding methods.

QTL Detection for Kernel Size and Weight in Bread Wheat (Triticum aestivum L.) Using a High-Density SNP and SSR-Based Linkage Map

High-density genetic linkage maps are essential for precise mapping quantitative trait loci (QTL) in wheat (Triticum aestivum L.). In this study, a high-density genetic linkage map consisted of 6312 SNP and SSR markers was developed to identify QTL controlling kernel size and weight, based on a recombinant inbred line (RIL) population derived from the cross of Shixin828 and Kenong2007. Seventy-eight putative QTL for kernel length (KL), kernel width (KW), kernel diameter ratio (KDR), and thousand kernel weight (TKW) were detected over eight environments by inclusive composite interval mapping (ICIM). Of these, six stable QTL were identified in more than four environments, including two for KL (qKL-2D and qKL-6B.2), one for KW (qKW-2D.1), one for KDR (qKDR-2D.1) and two for TKW (qTKW-5A and qTKW-5B.2). Unconditional and multivariable conditional QTL mapping for TKW with respect to TKW component (TKWC) revealed that kernel dimensions played an important role in regulating the kernel weight. Seven QTL-rich genetic regions including seventeen QTL were found on chromosomes 1A (2), 2D, 3A, 4B and 5B (2) exhibiting pleiotropic effects. In particular, clusters on chromosomes 2D and 5B possessing significant QTL for kernel-related traits were highlighted. Markers tightly linked to these QTL or clusters will eventually facilitate further studies for fine mapping, candidate gene discovery and marker-assisted selection (MAS) in wheat breeding.

QTL Detection for Kernel Size and Weight in Bread Wheat (Triticum aestivum L.) Using a High-Density SNP and SSR-Based Linkage Map

High-density genetic linkage maps are essential for precise mapping quantitative trait loci (QTL) in wheat (Triticum aestivum L.). In this study, a high-density genetic linkage map consisted of 6312 SNP and SSR markers was developed to identify QTL controlling kernel size and weight, based on a recombinant inbred line (RIL) population derived from the cross of Shixin828 and Kenong2007. Seventy-eight putative QTL for kernel length (KL), kernel width (KW), kernel diameter ratio (KDR), and thousand kernel weight (TKW) were detected over eight environments by inclusive composite interval mapping (ICIM). Of these, six stable QTL were identified in more than four environments, including two for KL (qKL-2D and qKL-6B.2), one for KW (qKW-2D.1), one for KDR (qKDR-2D.1) and two for TKW (qTKW-5A and qTKW-5B.2). Unconditional and multivariable conditional QTL mapping for TKW with respect to TKW component (TKWC) revealed that kernel dimensions played an important role in regulating the kernel weight. Seven QTL-rich genetic regions including seventeen QTL were found on chromosomes 1A (2), 2D, 3A, 4B and 5B (2) exhibiting pleiotropic effects. In particular, clusters on chromosomes 2D and 5B possessing significant QTL for kernel-related traits were highlighted. Markers tightly linked to these QTL or clusters will eventually facilitate further studies for fine mapping, candidate gene discovery and marker-assisted selection (MAS) in wheat breeding.

Genotyping-by-Sequencing Derived High-Density Linkage Map and its Application to QTL Mapping of Flag Leaf Traits in Bread Wheat

Winter wheat parents ‘Harry’ (drought tolerant) and ‘Wesley’ (drought susceptible) were used to develop a recombinant inbred population with future goals of identifying genomic regions associated with drought tolerance. To precisely map genomic regions, high-density linkage maps are a prerequisite. In this study genotyping-by- sequencing (GBS) was used to construct the high-density linkage map. The map contained 3,641 markers distributed on 21 chromosomes and spanned 1,959 cM with an average distance of 1.8 cM between markers. The constructed linkage map revealed strong collinearity in marker order across 21 chromosomes with POPSEQ-v2.0, which was based on a high-density linkage map. The reliability of the linkage map for QTL mapping was demonstrated by co-localizing the genes to previously mapped genomic regions for two highly heritable traits, chaff color, and leaf cuticular wax. Applicability of linkage map for QTL mapping of three quantitative traits, flag leaf length, width, and area, identified 21 QTLs in four environments, and QTL expression varied across the environments. Two major stable QTLs, one each for flag leaf length (Qfll.hww-7A) and flag leaf width (Qflw.hww-5A) were identified. The map constructed will facilitate QTL and fine mapping of quantitative traits, map-based cloning, comparative mapping, and in marker-assisted wheat breeding endeavors.

Utilization of a Wheat660K SNP array-derived high-density genetic map for high-resolution mapping of a major QTL for kernel number

In crop plants, a high-density genetic linkage map is essential for both genetic and genomic researches. The complexity and the large size of wheat genome have hampered the acquisition of a high-resolution genetic map. In this study, we report a high-density genetic map based on an individual mapping population using the Affymetrix Wheat660K single-nucleotide polymorphism (SNP) array as a probe in hexaploid wheat. The resultant genetic map consisted of 119 566 loci spanning 4424.4 cM, and 119 001 of those loci were SNP markers. This genetic map showed good collinearity with the 90 K and 820 K consensus genetic maps and was also in accordance with the recently released wheat whole genome assembly. The high-density wheat genetic map will provide a major resource for future genetic and genomic research in wheat. Moreover, a comparative genomics analysis among gramineous plant genomes was conducted based on the high-density wheat genetic map, providing an overview of the structural relationships among theses gramineous plant genomes. A major stable quantitative trait locus (QTL) for kernel number per spike was characterized, providing a solid foundation for the future high-resolution mapping and map-based cloning of the targeted QTL.

Utilization of a Wheat660K SNP array-derived high-density genetic map for high-resolution mapping of a major QTL for kernel number

In crop plants, a high-density genetic linkage map is essential for both genetic and genomic researches. The complexity and the large size of wheat genome have hampered the acquisition of a high-resolution genetic map. In this study, we report a high-density genetic map based on an individual mapping population using the Affymetrix Wheat660K single-nucleotide polymorphism (SNP) array as a probe in hexaploid wheat. The resultant genetic map consisted of 119 566 loci spanning 4424.4 cM, and 119 001 of those loci were SNP markers. This genetic map showed good collinearity with the 90 K and 820 K consensus genetic maps and was also in accordance with the recently released wheat whole genome assembly. The high-density wheat genetic map will provide a major resource for future genetic and genomic research in wheat. Moreover, a comparative genomics analysis among gramineous plant genomes was conducted based on the high-density wheat genetic map, providing an overview of the structural relationships among theses gramineous plant genomes. A major stable quantitative trait locus (QTL) for kernel number per spike was characterized, providing a solid foundation for the future high-resolution mapping and map-based cloning of the targeted QTL.

Characterization of the temporal and spatial expression of wheat (Triticum aestivum L.) plant height at the QTL level and their influence on yield-related traits

The temporal and spatial expression patterns of stable QTL for plant height and their influences on yield were characterized. Plant height (PH) is a complex trait in wheat (Triticum aestivum L.) that includes the spike length (SL) and the internode lengths from the first to the fifth internode, which are counted from the top and abbreviated as FIRITL, SECITL, THIITL, FOUITL, and FIFITL, respectively. This study identified eight putative additive quantitative trait loci (QTL) for PH. In addition, unconditional and conditional QTL mapping were used to analyze the temporal and spatial expression patterns of five stable QTL for PH. qPh-3A mainly regulated SL, FIRITL, and FIFITL to affect PH during the booting-heading stage (BS-HS); qPh-3D regulated all internode lengths to affect PH, especially during the BS-HS; before HS, qPh-4B mainly affected FIRITL, SECITL, THIITL, and FOUITL and qPh-5A.1 mainly affected SECITL, THIITL, and FOUITL to regulate PH; and qPh-6B mainly regulated FIRITL to affect the PH after the booting stage (BS). qPhdv-4B, a QTL for the response of PH to nitrogen stress, was stable and co-localized with qPh-4B. All five stable QTL, except for qPh-3A, were related to the 1000 kernel weight and yield per plant. Regions of qPh-3A, qPh-3D, qPh-4B, qPh-5A.1, and qPh-6B showed synteny to parts of rice chromosomes 1, 1, 3, 9, and 2, respectively. Based on comparative genomics analysis, Rht-B1b was cloned and mapped in the CI of qPh-4B. This report provides useful information for fine mapping of the stable QTL for PH and the genetic improvement of wheat plant type.

Quantitative Trait Loci Associated with Phenological Development, Low-Temperature Tolerance, Grain Quality, and Agronomic Characters in Wheat (Triticum aestivum L.)

Plants must respond to environmental cues and schedule their development in order to react to periods of abiotic stress and commit fully to growth and reproduction under favorable conditions. This study was initiated to identify SNP markers for characters expressed from the seedling stage to plant maturity in spring and winter wheat (Triticum aestivum L.) genotypes adapted to western Canada. Three doubled haploid populations with the winter cultivar ‘Norstar’ as a common parent were developed and genotyped with a 90K Illumina iSelect SNP assay and a 2,998.9 cM consensus map with 17,541 markers constructed. High heritability’s reflected large differences among the parents and relatively low genotype by environment interactions for all characters considered. Significant QTL were detected for the 15 traits examined. However, different QTL for days to heading in controlled environments and the field provided a strong reminder that growth and development are being orchestrated by environmental cues and caution should be exercised when extrapolating conclusions from different experiments. A QTL on chromosome 6A for minimum final leaf number, which determines the rate of phenological development in the seedling stage, was closely linked to QTL for low-temperature tolerance, grain quality, and agronomic characters expressed up to the time of maturity. This suggests phenological development plays a critical role in programming subsequent outcomes for many traits. Transgressive segregation was observed for the lines in each population and QTL with additive effects were identified suggesting that genes for desirable traits could be stacked using Marker Assisted Selection. QTL were identified for characters that could be transferred between the largely isolated western Canadian spring and winter wheat gene pools demonstrating the opportunities offered by Marker Assisted Selection to act as bridges in the identification and transfer of useful genes among related genetic islands while minimizing the drag created by less desirable genes.

QTL detection for wheat kernel size and quality and the responses of these traits to low nitrogen stress

QTLs for kernel characteristics and tolerance to N stress were identified, and the functions of ten known genes with regard to these traits were specified. Kernel size and quality characteristics in wheat (Triticum aestivum L.) ultimately determine the end use of the grain and affect its commodity price, both of which are influenced by the application of nitrogen (N) fertilizer. This study characterized quantitative trait loci (QTLs) for kernel size and quality and examined the responses of these traits to low-N stress using a recombinant inbred line population derived from Kenong 9204 × Jing 411. Phenotypic analyses were conducted in five trials that each included low- and high-N treatments. We identified 109 putative additive QTLs for 11 kernel size and quality characteristics and 49 QTLs for tolerance to N stress, 27 and 14 of which were stable across the tested environments, respectively. These QTLs were distributed across all wheat chromosomes except for chromosomes 3A, 4D, 6D, and 7B. Eleven QTL clusters that simultaneously affected kernel size- and quality-related traits were identified. At nine locations, 25 of the 49 QTLs for N deficiency tolerance coincided with the QTLs for kernel characteristics, indicating their genetic independence. The feasibility of indirect selection of a superior genotype for kernel size and quality under high-N conditions in breeding programs designed for a lower input management system are discussed. In addition, we specified the functions of Glu-A1, Glu-B1, Glu-A3, Glu-B3, TaCwi-A1, TaSus2, TaGS2-D1, PPO-D1, Rht-B1, and Ha with regard to kernel characteristics and the sensitivities of these characteristics to N stress. This study provides useful information for the genetic improvement of wheat kernel size, quality, and resistance to N stress.

Genetic Map of Triticale Integrating Microsatellite, DArT and SNP Markers

Triticale (×Triticosecale Wittm) is an economically important crop for fodder and biomass production. To facilitate the identification of markers for agronomically important traits and for genetic and genomic characteristics of this species, a new high-density genetic linkage map of triticale was constructed using doubled haploid (DH) population derived from a cross between cultivars 'Hewo' and 'Magnat'. The map consists of 1615 bin markers, that represent 50 simple sequence repeat (SSR), 842 diversity array technology (DArT), and 16888 DArTseq markers mapped onto 20 linkage groups assigned to the A, B, and R genomes of triticale. No markers specific to chromosome 7R were found, instead mosaic linkage group composed of 1880 highly distorted markers (116 bins) from 10 wheat chromosomes was identified. The genetic map covers 4907 cM with a mean distance between two bins of 3.0 cM. Comparative analysis in respect to published maps of wheat, rye and triticale revealed possible deletions in chromosomes 4B, 5A, and 6A, as well as inversion in chromosome 7B. The number of bin markers in each chromosome varied from 24 in chromosome 3R to 147 in chromosome 6R. The length of individual chromosomes ranged between 50.7 cM for chromosome 2R and 386.2 cM for chromosome 7B. A total of 512 (31.7%) bin markers showed significant (P < 0.05) segregation distortion across all chromosomes. The number of 8 the segregation distorted regions (SDRs) were identified on 1A, 7A, 1B, 2B, 7B (2 SDRs), 5R and 6R chromosomes. The high-density genetic map of triticale will facilitate fine mapping of quantitative trait loci, the identification of candidate genes and map-based cloning.