Genome-Wide Linkage Mapping of Quantitative Trait Loci for Late-Season Physiological and Agronomic Traits in Spring Wheat under Irrigated Conditions

Association Analysis of Tiller-Related Traits with EST-SSR Markers in Psathyrostachys juncea

Psathyrostachys juncea is a long-lived perennial Gramineae grass with dense basal tillers and soft leaves. It is used widely in cold and dry areas of Eurasia and North America to establish grazing pasture and is even used as an ideal plant for revegetation and ecological restoration. Plant architecture, especially tillering traits, is critical for bunch grasses in breeding programs, and these traits in plants are mostly quantitative traits. In this study, the genetic diversity, population structure, and linkage disequilibrium of 480 individual lines were analyzed using 127 pairs of the EST-SSR marker, and a significant association between ten plant-architecture-related traits of P. juncea and molecular markers was found. The results of the genetic diversity analysis showed that the number of observed alleles was 1.957, the number of effective alleles was 1.682, Shannon's information index was 0.554, observed heterozygosity was 0.353, expected heterozygosity was 0.379, and the polymorphism information content was 0.300. A total of 480 individual lines were clustered into five groups based on population genetic structure, principal coordinate analysis, and unweighted pair group method with arithmetic mean analysis (UPGMA). The linkage disequilibrium coefficient (r2) was between 0.00 and 0.68, with an average of 0.04, which indicated a relatively low level of linkage disequilibrium among loci. The results of the association analysis revealed 55 significant marker-trait associations (MTA). Moreover, nine SSR markers were associated with multiple traits. This study provides tools with promising applications in the molecular selection and breeding of P. juncea germplasm.

Identifying genomic regions determining shoot and root traits related to nitrogen uptake efficiency in a multiparent advanced generation intercross (MAGIC) winter wheat population in a high-throughput phenotyping facility

In the context of a continuously increasing human population that needs to be fed, with environmental protection in mind, nitrogen use efficiency (NUE) improvement is becoming very important. To understand the natural variation of traits linked to nitrogen uptake efficiency (UPE), one component of NUE, the multiparent advanced generation intercross (MAGIC) winter wheat population WM-800 was phenotyped under two contrasting nitrogen (N) levels in a high-throughput phenotyping facility for six weeks. Three biomass-related, three root-related, and two reflectance-related traits were measured weekly under each treatment. Subsequently, the population was genetically analysed using a total of 13,060 polymorphic haplotypes and singular SNPs for a genome-wide association study (GWAS). In total, we detected 543 quantitative trait loci (QTL) across all time points and traits, which were pooled into 42 stable QTL (sQTL; present in at least three of the six weeks). Besides Rht-B1 and Rht-D1, candidate genes playing a role in gibberellic acid-regulated growth and nitrate transporter genes from the NPF gene family, like NRT 1.1, were linked to sQTL. Two novel sQTL on chromosomes 5 A and 6D showed pleiotropic effects on several traits. The high number of N-specific sQTL indicates that selection for UPE is useful specifically under N-limited conditions.

Marker assisted improvement for leaf rust and moisture deficit stress tolerance in wheat variety HD3086

There is a significant yield reduction in the wheat crop as a result of different biotic and abiotic stresses, and changing climate, among them moisture deficit stress and leaf rust are the major ones affecting wheat worldwide. HD3086 is a high-yielding wheat variety that has been released for commercial cultivation under timely sown irrigated conditions in the Indo-Gangetic plains of India. Variety HD3086 provides a good, stable yield, and it is the choice of millions of farmers in India. It becomes susceptible to the most prevalent pathotypes 77-5 and 77-9 of Puccinia triticina (causing leaf rust) in the production environment and its potential yield cannot be realized under moisture deficit stress. The present study demonstrates the use of a marker-assisted back cross breeding approach to the successful transfer of leaf rust resistance gene Lr24 and QTLs linked to moisture deficit stress tolerance in the background of HD3086. The genotype HI1500 was used as a donor parent that possesses leaf rust-resistant gene Lr24, which confers resistance against the major pathotypes found in the production environment. It possesses inbuilt tolerance under abiotic stresses with superior quality traits. Foreground selection for gene Lr24 and moisture deficit stress tolerance QTLs linked to Canopy temperature (CT), Normal Differential Vegetation Index (NDVI) and Thousand Kernel Weight (TKW) in different generations of the backcrossing and selection. In BC2F2, foreground selection was carried out to identify homozygous lines based on the linked markers and were advanced following pedigree based phenotypic selection. The selected lines were evaluated against P. triticina pathotypes 77-5 and 77-9 under controlled conditions. Recurrent parent recovery of the selected lines ranged from 78-94%. The identified lines were evaluated for their tolerance to moisture stress under field conditions and their resistance to rust under artificial epiphytotic conditions for two years. In BC2F5 generation, eight positive lines for marker alleles were selected which showed resistance to leaf rust and recorded an improvement in component traits of moisture deficit stress tolerance such as CT, NDVI, TKW and yield compared to the recurrent parent HD3086. The derived line is named HD3471 and is nominated for national trials for testing and further release for commercial cultivation.

Characterization of the Resistance to Powdery Mildew and Leaf Rust Carried by the Bread Wheat Cultivar Victo

Leaf rust and powdery mildew are two important foliar diseases in wheat. A recombinant inbred line (RIL) population, obtained by crossing two bread wheat cultivars (‘Victo’ and ‘Spada’), was evaluated for resistance to the two pathogens at seedling stage. Upon developing a genetic map of 8726 SNP loci, linkage analysis identified three resistance Quantitative Trait Loci (QTLs), with ‘Victo’ contributing the resistant alleles to all loci. One major QTL (QPm.gb-7A) was detected in response to Blumeria graminis on chromosome 7A, which explained 90% of phenotypic variation (PV). The co-positional relationship with known powdery mildew (Pm) resistance loci suggested that a new source of resistance was identified in T. aestivum. Two QTLs were detected in response to Puccinia triticina: a major gene on chromosome 5D (QLr.gb-5D), explaining a total PV of about 59%, and a minor QTL on chromosome 2B (QLr.gb-2B). A positional relationship was observed between the QLr.gb-5D with the known Lr1 gene, but polymorphisms were found between the cloned Lr1 and the corresponding ‘Victo’ allele, suggesting that QLr.gb-5D could represent a new functional Lr1 allele. Lastly, upon anchoring the QTL on the T. aestivum reference genome, candidate genes were hypothesized on the basis of gene annotation and in silico gene expression analysis.

Identification and Validation of New Stable QTLs for Grain Weight and Size by Multiple Mapping Models in Common Wheat

Improvement of grain weight and size is an important objective for high-yield wheat breeding. In this study, 174 recombinant inbred lines (RILs) derived from the cross between Jing 411 and Hongmangchun 21 were used to construct a high-density genetic map by specific locus amplified fragment sequencing (SLAF-seq). Three mapping methods, including inclusive composite interval mapping (ICIM), genome-wide composite interval mapping (GCIM), and a mixed linear model performed with forward-backward stepwise (NWIM), were used to identify QTLs for thousand grain weight (TGW), grain width (GW), and grain length (GL). In total, we identified 30, 15, and 18 putative QTLs for TGW, GW, and GL that explain 1.1-33.9%, 3.1%-34.2%, and 1.7%-22.8% of the phenotypic variances, respectively. Among these, 19 (63.3%) QTLs for TGW, 10 (66.7%) for GW, and 7 (38.9%) for GL were consistent with those identified by genome-wide association analysis in 192 wheat varieties. Five new stable QTLs, including 3 for TGW (Qtgw.ahau-1B.1, Qtgw.ahau-4B.1, and Qtgw.ahau-4B.2) and 2 for GL (Qgl.ahau-2A.1 and Qgl.ahau-7A.2), were detected by the three aforementioned mapping methods across environments. Subsequently, five cleaved amplified polymorphic sequence (CAPS) markers corresponding to these QTLs were developed and validated in 180 Chinese mini-core wheat accessions. In addition, 19 potential candidate genes for Qtgw.ahau-4B.2 in a 0.31-Mb physical interval were further annotated, of which TraesCS4B02G376400 and TraesCS4B02G376800 encode a plasma membrane H+-ATPase and a serine/threonine-protein kinase, respectively. These new QTLs and CAPS markers will be useful for further marker-assisted selection and map-based cloning of target genes.

Genetic architecture underpinning yield component traits in wheat

Genetic atlas, reliable QTL and candidate genes of yield component traits in wheat were figured out, laying concrete foundations for map-based gene cloning and dissection of regulatory mechanisms underlying yield. Mining genetic loci for yield is challenging due to the polygenic nature, large influence of environment and complex relationship among yield component traits (YCT). Many genetic loci related to wheat yield have been identified, but its genetic architecture and key genetic loci for selection are largely unknown. Wheat yield potential can be determined by three YCT, thousand kernel weight, kernel number per spike and spike number. Here, we summarized the genetic loci underpinning YCT from QTL mapping, association analysis and homology-based gene cloning. The major loci determining yield-associated agronomic traits, such as flowering time and plant height, were also included in comparative analyses with those for YCT. We integrated yield-related genetic loci onto chromosomes based on their physical locations. To identify the major stable loci for YCT, 58 QTL-rich clusters (QRC) were defined based on their distribution on chromosomes. Candidate genes in each QRC were predicted according to gene annotation of the wheat reference genome and previous information on validation of those genes in other species. Finally, a technological route was proposed to take full advantage of the resultant resources for gene cloning, molecular marker-assisted breeding and dissection of molecular regulatory mechanisms underlying wheat yield.

Marker-Trait Associations for Enhancing Agronomic Performance, Disease Resistance, and Grain Quality in Synthetic and Bread Wheat Accessions in Western Siberia

Exploiting genetically diverse lines to identify genes for improving crop performance is needed to ensure global food security. A genome-wide association study (GWAS) was conducted using 46,268 SNP markers on a diverse panel of 143 hexaploid bread and synthetic wheat to identify potential genes/genomic regions controlling agronomic performance (yield and 26 yield-related traits), disease resistance, and grain quality traits. From phenotypic evaluation, we found large genetic variation among the 35 traits and recommended five lines having a high yield, better quality, and multiple disease resistance for direct use in a breeding program. From a GWAS, we identified a total of 243 significant marker-trait associations (MTAs) for 35 traits that explained up to 25% of the phenotypic variance. Of these, 120 MTAs have not been reported in the literature and are potentially novel MTAs. In silico gene annotation analysis identified 116 MTAs within genes and of which, 21 MTAs were annotated as a missense variant. Furthermore, we were able to identify 23 co-located multi-trait MTAs that were also phenotypically correlated to each other, showing the possibility of simultaneous improvement of these traits. Additionally, most of the co-located MTAs were within genes. We have provided genomic fingerprinting for significant markers with favorable and unfavorable alleles in the diverse set of lines for developing elite breeding lines from useful trait-integration. The results from this study provided a further understanding of genetically complex traits and would facilitate the use of diverse wheat accessions for improving multiple traits in an elite wheat breeding program.

Identification and assessment of two major QTLs for dwarf bunt resistance in winter wheat line 'IDO835'

Two major dwarf bunt resistance QTLs were mapped to a known Bt9 locus and a novel locus. The associated KASP markers were developed and validated in other two populations. Dwarf bunt (DB), caused by Tilletia controversa J.G. Kühn, and common bunt (CB), caused by T. caries and T. foetida, are two destructive diseases that reduce grain yield and quality in wheat. Breeding for bunt-resistant cultivars is important in many wheat production areas, especially where organic wheat is grown. However, few molecular markers have been used in selection of bunt resistance. In the present study, a doubled haploid (DH) population derived from the bunt-resistant line 'IDO835' and the susceptible cultivar 'Moreland' was evaluated for DB resistance in a field nursery in Logan, Utah, for four growing seasons. The population was genotyped with the Illumina 90 K SNP iSelect marker platform. Two major QTLs were consistently identified on chromosomes 6DL (Q.DB.ui-6DL) and 7AL (Q.DB.ui-7AL), explaining up to 53% and 38% of the phenotypic variation, respectively. Comparative study suggested that Q.DB.ui-6DL was located in the same region as the CB resistance gene Bt9, and Q.DB.ui-7AL was located at a novel locus for bunt resistance. Based on Chinese Spring reference sequence and annotations (IWGSC RefSeq v1.1), both resistance QTLs were mapped to disease resistance gene-rich (NBS-LRR and kinase genes) regions. To validate the identified QTL and design user-friendly markers for MAS, five SNPs were converted to Kompetitive Allele-Specific PCR (KASP) markers and used to genotype two validation panels, including a DH population and a diverse winter wheat population from USDA-ARS National Small Grain Collection, as well as a Bt gene investigation panel, consisting of 15 bunt differential lines and 11 resistant lines.

Deciphering the Genetics of Major End-Use Quality Traits in Wheat

Improving the end-use quality traits is one of the primary objectives in wheat breeding programs. In the current study, a population of 127 recombinant inbred lines (RILs) derived from a cross between Glenn (PI-639273) and Traverse (PI-642780) was developed and used to identify quantitative trait loci (QTL) for 16 end-use quality traits in wheat. The phenotyping of these 16 traits was performed in nine environments in North Dakota, USA. The genotyping for the RIL population was conducted using the wheat Illumina iSelect 90K SNP assay. A high-density genetic linkage map consisting of 7,963 SNP markers identified a total of 76 additive QTL (A-QTL) and 73 digenic epistatic QTL (DE-QTL) associated with these traits. Overall, 12 stable major A-QTL and three stable DE-QTL were identified for these traits, suggesting that both A-QTL and DE-QTL played an important role in controlling end-use quality traits in wheat. The most significant A-QTL (AQ.MMLPT.ndsu.1B) was detected on chromosome 1B for mixograph middle line peak time. The AQ.MMLPT.ndsu.1B A-QTL was located very close to the position of the Glu-B1 gene encoding for a subunit of high molecular weight glutenin and explained up to 24.43% of phenotypic variation for mixograph MID line peak time. A total of 23 co-localized QTL loci were detected, suggesting the possibility of the simultaneous improvement of the end-use quality traits through selection procedures in wheat breeding programs. Overall, the information provided in this study could be used in marker-assisted selection to increase selection efficiency and to improve the end-use quality in wheat.

QTL identification and KASP marker development for productive tiller and fertile spikelet numbers in two high-yielding hard white spring wheat cultivars

Selecting high-yielding wheat cultivars with more productive tillers per unit area (PTN) combined with more fertile spikelets per spike (fSNS) is difficult. QTL mapping of these traits may aid understanding of this bottleneck and accelerate precision breeding for high yield via marker-assisted selection. PTN and fSNS were assessed in four to five trials from 2015 to 2017 in a doubled haploid population derived from two high-yielding cultivars "UI Platinum" and "SY Capstone." Two QTL for PTN (QPTN.uia-4A and QPTN.uia-6A) and four QTL for fSNS (QfSNS.uia-4A, QfSNS.uia-5A, QfSNS.uia-6A, and QfSNS.uia-7A) were identified. The effects of the QTL were primarily additive and, therefore, pyramiding of multiple QTL may increase PTN and fSNS. However, the two QTL for PTN were positioned in the flanking regions for the two QTL for fSNS on chromosomes 4A and 6A, respectively, suggesting either possible pleiotropic effect of the same QTL or tightly linked QTL and explaining the difficulty of selecting both high PTN and fSNS in phenotypic selection. Kompetitive allele-specific PCR (KASP) markers for all identified QTL were developed and validated in a recombinant inbred line (RIL) population derived from the same two cultivars. In addition, KASP markers for three of the QTL (QPTN.uia-6A, QfSNS.uia-6A, and QfSNS.uia-7A) were further validated in a diverse spring wheat panel, indicating their usefulness under different genetic backgrounds. These KASP markers could be used by wheat breeders to select high PTN and fSNS.

QTL identification and KASP marker development for productive tiller and fertile spikelet numbers in two high-yielding hard white spring wheat cultivars

Selecting high-yielding wheat cultivars with more productive tillers per unit area (PTN) combined with more fertile spikelets per spike (fSNS) is difficult. QTL mapping of these traits may aid understanding of this bottleneck and accelerate precision breeding for high yield via marker-assisted selection. PTN and fSNS were assessed in four to five trials from 2015 to 2017 in a doubled haploid population derived from two high-yielding cultivars "UI Platinum" and "SY Capstone." Two QTL for PTN (QPTN.uia-4A and QPTN.uia-6A) and four QTL for fSNS (QfSNS.uia-4A, QfSNS.uia-5A, QfSNS.uia-6A, and QfSNS.uia-7A) were identified. The effects of the QTL were primarily additive and, therefore, pyramiding of multiple QTL may increase PTN and fSNS. However, the two QTL for PTN were positioned in the flanking regions for the two QTL for fSNS on chromosomes 4A and 6A, respectively, suggesting either possible pleiotropic effect of the same QTL or tightly linked QTL and explaining the difficulty of selecting both high PTN and fSNS in phenotypic selection. Kompetitive allele-specific PCR (KASP) markers for all identified QTL were developed and validated in a recombinant inbred line (RIL) population derived from the same two cultivars. In addition, KASP markers for three of the QTL (QPTN.uia-6A, QfSNS.uia-6A, and QfSNS.uia-7A) were further validated in a diverse spring wheat panel, indicating their usefulness under different genetic backgrounds. These KASP markers could be used by wheat breeders to select high PTN and fSNS.