A High-Density Consensus Map of Common Wheat Integrating Four Mapping Populations Scanned by the 90K SNP Array

Genotype-Specific Activation of Autophagy during Heat Wave in Wheat

Recycling of unnecessary or dysfunctional cellular structures through autophagy plays a critical role in cellular homeostasis and environmental resilience. Therefore, the autophagy trait may have been unintentionally selected in wheat breeding programs for higher yields in arid climates. This hypothesis was tested by measuring the response of three common autophagy markers, ATG7, ATG8, and NBR1, to a heat wave under reduced soil moisture content in 16 genetically diverse spring wheat landraces originating from different geographical locations. We observed in the greenhouse trials that ATG8 and NBR1 exhibited genotype-specific responses to a 1 h, 40 °C heat wave, while ATG7 did not show a consistent response. Three genotypes from Uruguay, Mozambique, and Afghanistan showed a pattern consistent with higher autophagic activity: decreased or stable abundance of both ATG8 and NBR1 proteins, coupled with increased transcription of ATG8 and NBR1. In contrast, three genotypes from Pakistan, Ethiopia, and Egypt exhibited elevated ATG8 protein levels alongside reduced or unaltered ATG8 transcript levels, indicating a potential suppression or no change in autophagic activity. Principal component analysis demonstrated a correlation between lower abundance of ATG8 and NBR1 proteins and higher yield in the field trials. We found that (i) the combination of heat and drought activated autophagy only in several genotypes, suggesting that despite being a resilience mechanism, autophagy is a heat-sensitive process; (ii) higher autophagic activity correlates positively with greater yield; (iii) the lack of autophagic activity in some high-yielding genotypes suggests contribution of alternative stress-resilient mechanisms; and (iv) enhanced autophagic activity in response to heat and drought was independently selected by wheat breeding programs in different geographic locations.

Exploring the genetic architecture of powdery mildew resistance in wheat through QTL meta-analysis

Powdery mildew (PM), caused by Blumeria graminis f. sp. tritici, poses a significant threat to wheat production, necessitating the development of genetically resistant varieties for long-term control. Therefore, exploring genetic architecture of PM in wheat to uncover important genomic regions is an important area of wheat research. In recent years, the utilization of meta-QTL (MQTL) analysis has gained prominence as an essential tool for unraveling the complex genetic architecture underlying complex quantitative traits. The aim of this research was to conduct a QTL meta-analysis to pinpoint the specific genomic regions in wheat responsible for governing PM resistance. This study integrated 222 QTLs from 33 linkage-based studies using a consensus map with 54,672 markers. The analysis revealed 39 MQTLs, refined to 9 high-confidence MQTLs (hcMQTLs) with confidence intervals of 0.49 to 12.94 cM. The MQTLs had an average physical interval of 41.00 Mb, ranging from 0.000048 Mb to 380.71 Mb per MQTL. Importantly, 18 MQTLs co-localized with known resistance genes like Pm2, Pm3, Pm8, Pm21, Pm38, and Pm41. The study identified 256 gene models within hcMQTLs, providing potential targets for marker-assisted breeding and genomic prediction programs to enhance PM resistance. These MQTLs would serve as a foundation for fine mapping, gene isolation, and functional genomics studies, facilitating a deeper understanding of molecular mechanisms. The identification of candidate genes opens up exciting possibilities for the development of PM-resistant wheat varieties after validation.

Molecular characterization of QTL for grain zinc and iron concentrations in wheat landrace Chinese Spring

KEY MESSAGE

Three stable QTL for grain zinc concentration were identified in wheat landrace Chinese Spring. Favorable alleles were more frequent in landraces than in modern wheat cultivars. Wheat is a major source of dietary energy for the growing world population. Developing cultivars with enriched zinc and iron can potentially alleviate human micronutrient deficiency. In this study, a recombinant inbred line (RIL) population with 245 lines derived from cross Zhou 8425B/Chinese Spring was used to detect quantitative trait loci (QTL) for grain zinc concentration (GZnC) and grain iron concentration (GFeC) across four environments. Three stable QTL for GZnC with all favorable alleles from Chinese Spring were identified on chromosomes 3BL, 5AL, and 5BL. These QTL explaining maxima of 8.7%, 5.8%, and 7.1% of phenotypic variances were validated in 125 resequenced wheat accessions encompassing both landraces and modern cultivars using six kompetitive allele specific PCR (KASP) assays. The frequencies of favorable alleles for QGZnCzc.caas-3BL, QGZnCzc.caas-5AL and QGZnCzc.caas-5BL were higher in landraces (90.4%, 68.0%, and 100.0%, respectively) compared to modern cultivars (45.9%, 35.4%, and 40.9%), suggesting they were not selected in breeding programs. Candidate gene association studies on GZnC in the cultivar panel further delimited the QTL into 8.5 Mb, 4.1 Mb, and 47.8 Mb regions containing 46, 4, and 199 candidate genes, respectively. The 5BL QTL located in a region where recombination was suppressed. Two stable and three less stable QTL for GFeC with favorable alleles also from Chinese Spring were identified on chromosomes 4BS (Rht-B1a), 4DS (Rht-D1a), 1DS, 3AS, and 6DS. This study sheds light on the genetic basis of GZnC and GFeC in Chinese Spring and provides useful molecular markers for wheat biofortification.

Genome-wide linkage mapping of root system architecture-related traits in common wheat (Triticum aestivum L.)

Identifying loci for root system architecture (RSA) traits and developing available markers are crucial for wheat breeding. In this study, RSA-related traits, including total root length (TRL), total root area (TRA), and number of root tips (NRT), were evaluated in the Doumai/Shi4185 recombinant inbred line (RIL) population under hydroponics. In addition, both the RILs and parents were genotyped using the wheat 90K single-nucleotide polymorphism (SNP) array. In total, two quantitative trait loci (QTLs) each for TRL (QTRL.caas-4A.1 and QTRL.caas-4A.2), TRA (QTRA.caas-4A and QTRA.caas-4D), and NRT (QNRT.caas-5B and QNRT.caas-5D) were identified and each explaining 5.94%-9.47%, 6.85%-7.10%, and 5.91%-10.16% phenotypic variances, respectively. Among these, QTRL.caas-4A.1 and QTRA.caas-4A overlapped with previous reports, while QTRL.caas-4A.2, QTRA.caas-4D, QNRT.caas-5B, and QNRT.caas-5D were novel. The favorable alleles of QTRL.caas-4A.1, QTRA.caas-4A, and QTRA.caas-5B were contributed by Doumai, whereas the favorable alleles of QTRL.caas-4A.2, QTRA.caas-4D, and QTRA.caas-5D originated from Shi 4185. Additionally, two competitive allele-specific PCR (KASP) markers, Kasp_4A_RL (QTRA.caas-4A) and Kasp_5D_RT (QNRT.caas-5D), were developed and validated in 165 wheat accessions. This study provides new loci and available KASP markers, accelerating wheat breeding for higher yields.

Precisely mapping a major QTL for grain weight on chromosome 5B of the founder parent Chuanmai42 in the wheat-growing region of southwestern China

KEY MESSAGE

QTgw.saas-5B was validated as a major thousand-grain weight-related QTL in a founder parent used for wheat breeding and then precisely mapped to a 0.6 cM interval. Increasing the thousand-grain weight (TGW) is considered to be one of the most important ways to improve yield, which is a core objective among wheat breeders. Chuanmai42, which is a wheat cultivar with high TGW and a high and stable yield, is a parent of more than 30 new varieties grown in southwestern China. In this study, a Chuanmai42-derived recombinant inbred line (RIL) population was used to dissect the genetic basis of TGW. A major QTL (QTgw.saas-5B) mapped to the Xgwm213-Xgwm540 interval on chromosome 5B of Chuanmai42 explained up to 20% of the phenotypic variation. Using 71 recombinants with a recombination in the QTgw.saas-5B interval identified from a secondary RIL population comprising 1818 lines constructed by crossing the QTgw.saas-5B near-isogenic line with the recurrent parent Chuannong16, QTgw.saas-5B was delimited to a 0.6 cM interval, corresponding to a 21.83 Mb physical interval in the Chinese Spring genome. These findings provide the foundation for QTgw.saas-5B cloning and its use in molecular marker-assisted breeding.

Plant Tolerance to Drought Stress with Emphasis on Wheat

Environmental stresses, such as drought, have negative effects on crop yield. Drought is a stress whose impact tends to increase in some critical regions. However, the worldwide population is continuously increasing and climate change may affect its food supply in the upcoming years. Therefore, there is an ongoing effort to understand the molecular processes that may contribute to improving drought tolerance of strategic crops. These investigations should contribute to delivering drought-tolerant cultivars by selective breeding. For this reason, it is worthwhile to review regularly the literature concerning the molecular mechanisms and technologies that could facilitate gene pyramiding for drought tolerance. This review summarizes achievements obtained using QTL mapping, genomics, synteny, epigenetics, and transgenics for the selective breeding of drought-tolerant wheat cultivars. Synthetic apomixis combined with the msh1 mutation opens the way to induce and stabilize epigenomes in crops, which offers the potential of accelerating selective breeding for drought tolerance in arid and semi-arid regions.

Comprehensive meta-QTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheat

BACKGROUND

Yellow or stripe rust, caused by the fungus Puccinia striiformis f. sp. tritici (Pst) is an important disease of wheat that threatens wheat production. Since developing resistant cultivars offers a viable solution for disease management, it is essential to understand the genetic basis of stripe rust resistance. In recent years, meta-QTL analysis of identified QTLs has gained popularity as a way to dissect the genetic architecture underpinning quantitative traits, including disease resistance.

RESULTS

Systematic meta-QTL analysis involving 505 QTLs from 101 linkage-based interval mapping studies was conducted for stripe rust resistance in wheat. For this purpose, publicly available high-quality genetic maps were used to create a consensus linkage map involving 138,574 markers. This map was used to project the QTLs and conduct meta-QTL analysis. A total of 67 important meta-QTLs (MQTLs) were identified which were refined to 29 high-confidence MQTLs. The confidence interval (CI) of MQTLs ranged from 0 to 11.68 cM with a mean of 1.97 cM. The mean physical CI of MQTLs was 24.01 Mb, ranging from 0.0749 to 216.23 Mb per MQTL. As many as 44 MQTLs colocalized with marker-trait associations or SNP peaks associated with stripe rust resistance in wheat. Some MQTLs also included the following major genes- Yr5, Yr7, Yr16, Yr26, Yr30, Yr43, Yr44, Yr64, YrCH52, and YrH52. Candidate gene mining in high-confidence MQTLs identified 1,562 gene models. Examining these gene models for differential expressions yielded 123 differentially expressed genes, including the 59 most promising CGs. We also studied how these genes were expressed in wheat tissues at different phases of development.

CONCLUSION

The most promising MQTLs identified in this study may facilitate marker-assisted breeding for stripe rust resistance in wheat. Information on markers flanking the MQTLs can be utilized in genomic selection models to increase the prediction accuracy for stripe rust resistance. The candidate genes identified can also be utilized for enhancing the wheat resistance against stripe rust after in vivo confirmation/validation using one or more of the following methods: gene cloning, reverse genetic methods, and omics approaches.

A Wheat 660 K SNP array-based high-density genetic map facilitates QTL mapping of flag leaf-related traits in wheat

A high-density genetic map containing 122,620 SNP markers was constructed, which facilitated the identification of eight major flag leaf-related QTL in relatively narrow intervals. The flag leaf plays an important role in photosynthetic capacity and yield potential in wheat. In this study, we used a recombinant inbred line population containing 188 lines derived from a cross between 'Lankao86' (LK86) and 'Ermangmai' to construct a genetic map using the Wheat 660 K single-nucleotide polymorphism (SNP) array. The high-density genetic map contains 122,620 SNP markers spanning 5185.06 cM. It shows good collinearity with the physical map of Chinese Spring and anchors multiple sequences of previously unplaced scaffolds onto chromosomes. Based on the high-density genetic map, we identified seven, twelve, and eight quantitative trait loci (QTL) for flag leaf length (FLL), width (FLW), and area (FLA) across eight environments, respectively. Among them, three, one, and four QTL for FLL, FLW, and FLA are major and stably express in more than four environments. The physical distance between the flanking markers for QFll.igdb-3B/QFlw.igdb-3B/QFla.igdb-3B is only 444 kb containing eight high confidence genes. These results suggested that we could directly map the candidate genes in a relatively small region by the high-density genetic map constructed with the Wheat 660 K array. Furthermore, the identification of environmentally stable QTL for flag leaf morphology laid a foundation for the following gene cloning and flag leaf morphology improvement.

Impact of "Green Revolution" gene Rht-B1b on coleoptile length of wheat

Wheat coleoptile is a sheath-like structure that helps to deliver the first leaf from embryo to the soil surface. Here, a RIL population consisting of 245 lines derived from Zhou 8425B × Chinese Spring cross was genotyped by the high-density Illumina iSelect 90K assay for coleoptile length (CL) QTL mapping. Three QTL for CL were mapped on chromosomes 2BL, 4BS and 4DS. Of them, two major QTL QCL.qau-4BS and QCL.qau-4DS were detected, which could explain 9.1%-22.2% of the phenotypic variances across environments on Rht-B1 and Rht-D1 loci, respectively. Several studies have reported that Rht-B1b may reduce the length of wheat CL but no study has been carried out at molecular level. In order to verify that the Rht-B1 gene is the functional gene for the 4B QTL, an overexpression line Rht-B1b-OE and a CRISPR/SpCas9 line Rht-B1b-KO were studied. The results showed that Rht-B1b overexpression could reduce the CL, while loss-of-function of Rht-B1b would increase the CL relative to that of the null transgenic plants (TNL). To dissect the underlying regulatory mechanism of Rht-B1b on CL, comparative RNA-Seq was conducted between Rht-B1b-OE and TNL. Transcriptome profiles revealed a few key pathways involving the function of Rht-B1b in coleoptile development, including phytohormones, circadian rhythm and starch and sucrose metabolism. Our findings may facilitate wheat breeding for longer coleoptiles to improve seedling early vigor for better penetration through the soil crust in arid regions.

Genome-Wide Association Analysis Identified Variants Associated with Body Measurement and Reproduction Traits in Shaziling Pigs

With the increasing popularity of genomic sequencing, breeders pay more attention to identifying the crucial molecular markers and quantitative trait loci for improving the body size and reproduction traits that could affect the production efficiency of pig-breeding enterprises. Nevertheless, for the Shaziling pig, a well-known indigenous breed in China, the relationship between phenotypes and their corresponding genetic architecture remains largely unknown. Herein, in the Shaziling population, a total of 190 samples were genotyped using the Geneseek Porcine 50K SNP Chip, obtaining 41857 SNPs for further analysis. For phenotypes, two body measurement traits and four reproduction traits in the first parity from the 190 Shaziling sows were measured and recorded, respectively. Subsequently, a genome-wide association study (GWAS) between the SNPs and the six phenotypes was performed. The correlation between body size and reproduction phenotypes was not statistically significant. A total of 31 SNPs were found to be associated with body length (BL), chest circumference (CC), number of healthy births (NHB), and number of stillborns (NSB). Gene annotation for those candidate SNPs identified 18 functional genes, such as GLP1R, NFYA, NANOG, COX7A2, BMPR1B, FOXP1, SLC29A1, CNTNAP4, and KIT, which exert important roles in skeletal morphogenesis, chondrogenesis, obesity, and embryonic and fetal development. These findings are helpful to better understand the genetic mechanism for body size and reproduction phenotypes, while the phenotype-associated SNPs could be used as the molecular markers for the pig breeding programs.

A high-density integrated map for grapevine based on three mapping populations genotyped by the Vitis18K SNP chip

We present a high-density integrated map for grapevine, allowing refinement and improved understanding of the grapevine genome, while demonstrating the applicability of the Vitis18K SNP chip for linkage mapping. The improvement of grapevine through biotechnology requires identification of the molecular bases of target traits by studying marker-trait associations. The Vitis18K SNP chip provides a useful genotyping tool for genome-wide marker analysis. Most linkage maps are based on single mapping populations, but an integrated map can increase marker density and show order conservation. Here we present an integrated map based on three mapping populations. The parents consist of the well-known wine cultivars 'Cabernet Sauvignon', 'Corvina' and 'Rhine Riesling', the lesser-known wine variety 'Deckrot', and a table grape selection, G1-7720. Three high-density population maps with an average inter-locus gap ranging from 0.74 to 0.99 cM were developed. These maps show high correlations (0.9965-0.9971) with the reference assembly, containing only 93 markers with large order discrepancies compared to expected physical positions, of which a third is consistent across multiple populations. Moreover, the genetic data aid the further refinement of the grapevine genome assembly, by anchoring 104 yet unanchored scaffolds. From these population maps, an integrated map was constructed which includes 6697 molecular markers and reduces the inter-locus gap distance to 0.60 cM, resulting in the densest integrated map for grapevine thus far. A small number of discrepancies, mainly of short distance, involve 88 markers that remain conflictual across maps. The integrated map shows similar collinearity to the reference assembly (0.9974) as the single maps. This high-density map increases our understanding of the grapevine genome and provides a useful tool for its further characterization and the dissection of complex traits.

QTL analysis identified two major all-internodes solidness loci from a completely solid-stemmed spring wheat line

The culms of solid-stemmed wheat cultivars are filled with "pith" - a parenchymatous tissue largely composed of soft, spongy, and compact parenchyma cells. Breeding solid-stemmed cultivars is the most effective way to decrease the detrimental impact of wheat stem sawfly (WSS), Cephus cinctus Norton (Hymenoptera: Cephidae) on wheat production. Although a major solid stem gene has been previously identified from durum wheat, it produces an intermediate level of stem solidness in common wheat which is insufficient to provide the required level of WSS resistance. The maximum resistance is achieved when stems are totally filled with pith. Thus, to identify a secondary source of solidness in common wheat, we developed three mapping populations from wheat cvs. Sadash, 'AAC Innova' and 'AAC Cameron', each crossed separately with P2711, a completely solid-stemmed hexaploid wheat breeding line. All populations were genotyped using either wheat 15K or 90K Infinium iSelect SNP Assay and high-density linkage maps were generated from individual populations along with consensus maps for chromosomes 3B and 3D from all populations. 'Sadash/P2711' and 'AAC Innova/P2711' populations were subjected to extensive phenotyping in ≥3 environments followed by quantitative trait loci (QTL) analyses using population-specific and consensus linkage maps. We identified two major solid stem QTLs in the distal regions of chromosome arms 3BL and 3DL in both populations in addition to several population-specific or common minor QTLs. Internode-specific QTL analyses detected both major QTLs of chromosomes 3B and 3D across internodes, from top to bottom of the stalk, but minor QTLs were largely detected in upper or middle internodes. Our results suggest that both major QTLs are sufficient to develop highly solid-stemmed cvs; however, the minor loci, which additively enhance the pith expression, can be coupled with major genes to achieve a complete solid stem phenotype in common wheat. Comparative and haplotype analyses showed that the 3B locus is homoeologous to 3D, the former being mapped to a 1.1 Mb genomic region. Major QTLs identified in this study can be incorporated in modern wheat cultivars to achieve maximum WSS resistance from high pith expression.

Identification of quantitative trait loci of agronomic traits in bread wheat using a Pamyati Azieva × Paragon mapping population harvested in three regions of Kazakhstan

Background

Although genome-wide association studies (GWAS) are an increasingly informative tool in the mining of new quantitative trait loci (QTLs), a classical biparental mapping approach is still a powerful, widely used method to search the unique genetic factors associated with important agronomic traits in bread wheat.

Methods

In this study, a newly constructed mapping population of Pamyati Azieva (Russian Federation) × Paragon (UK), consisting of 94 recombinant inbred lines (RILs), was tested in three different regions of Kazakhstan with the purpose of QTL identification for key agronomic traits. The RILs were tested in 11 environments of two northern breeding stations (Petropavlovsk, North Kazakhstan region, and Shortandy, Aqmola region) and one southeastern station (Almalybak, Almaty region). The following eight agronomic traits were studied: heading days, seed maturation days, plant height, spike length, number of productive spikes, number of kernels per spike, thousand kernel weight, and yield per square meter. The 94 RILs of the PAxP cross were genotyped using Illumina's iSelect 20K single nucleotide polymorphism (SNP) array and resulted in the identification of 4595 polymorphic SNP markers.

Results

The application of the QTL Cartographer statistical package allowed the identification of 53 stable QTLs for the studied traits. A survey of published studies related to common wheat QTL identification suggested that 28 of those 53 QTLs were presumably novel genetic factors. The SNP markers for the identified QTLs of the analyzed agronomic traits of common wheat can be efficiently applied in ongoing breeding activities in the wheat breeding community using a marker-assisted selection approach.

Patterns of genetic variation and QTLs controlling grain traits in a collection of global wheat germplasm revealed by high-quality SNP markers

BACKGROUND

Establish a molecular breeding program involved assembling a diverse germplasm collection and generating accurate genotypes to characterize their genetic potential and associate them with agronomic traits. In this study, we acquired over eight hundred wheat accessions from international gene banks and assessed their genetic relatedness using high-quality SNP genotypes. Understanding the scope of genomic variation in this collection allows the breeders to utilize the genetic resources efficiently while improving wheat yield and quality.

RESULTS

A wheat diversity panel comprising 39 durum wheat, 60 spelt wheat, and 765 bread wheat accessions was genotyped on iSelect 90 K wheat SNP arrays. A total of 57,398 SNP markers were mapped to IWGSC RefSeq v2.1 assembly, over 30,000 polymorphic SNPs in the A, B, D genomes were used to analyze population structure and diversity, the results revealed the separation of the three species and the differentiation of CIMMYT improved breeding lines and landraces or widely grown cultivars. In addition, several chromosomal regions under selection were detected. A subset of 280 bread wheat accessions was evaluated for grain traits, including grain length, width, surface area, and color. Genome-wide association studies (GWAS) revealed that several chromosomal regions were significantly linked to known quantitative trait loci (QTL) controlling grain-related traits. One of the SNP peaks at the end of chromosome 7A was in strong linkage disequilibrium (LD) with WAPO-A1, a gene that governs yield components.

CONCLUSIONS

Here, the most updated and accurate physical positions of SNPs on 90 K genotyping array are provided for the first time. The diverse germplasm collection and associated genotypes are available for the wheat researchers to use in their molecular breeding program. We expect these resources to broaden the genetic basis of original breeding and pre-breeding materials and ultimately identify molecular markers associated with important agronomic traits which are evaluated in diverse environmental conditions.

Identification of QTL for Stem Traits in Wheat (Triticum aestivum L.)

Lodging in wheat (Triticum aestivum L.) is a complicated phenomenon that is influenced by physiological, genetics, and external factors. It causes a great yield loss and reduces grain quality and mechanical harvesting efficiency. Lodging resistance is contributed by various traits, including increased stem strength. The aim of this study was to map quantitative trait loci (QTL) controlling stem strength-related features (the number of big vascular bundles, stem diameter, stem wall thickness) using a doubled haploid (DH) population derived from a cross between Baiqimai and Neixiang 5. Field experiments were conducted during 2020-2022, and glasshouse experiments were conducted during 2021-2022. Significant genetic variations were observed for all measured traits, and they were all highly heritable. Fifteen QTL for stem strength-related traits were identified on chromosomes 2D, 3A, 3B, 3D, 4B, 5A, 6B, 7A, and 7D, respectively, and 7 QTL for grain yield-related traits were identified on chromosomes 2B, 2D, 3D, 4B, 7A, and 7B, respectively. The superior allele of the major QTL for the number of big vascular bundle (VB) was independent of plant height (PH), making it possible to improve stem strength without a trade-off of PH, thus improving lodging resistance. VB also showed positive correlations with some of the yield components. The result will be useful for molecular marker-assisted selection (MAS) for high stem strength and high yield potential.

Sink Strength Promoting Remobilization of Non-Structural Carbohydrates by Activating Sugar Signaling in Rice Stem during Grain Filling

The remobilization of non-structural carbohydrates (NSCs) in the stem is essential for rice grain filling so as to improve grain yield. We conducted a two-year field experiment to deeply investigate their relationship. Two large-panicle rice varieties with similar spikelet size, CJ03 and W1844, were used to conduct two treatments (removing-spikelet group and control group). Compared to CJ03, W1844 had higher 1000-grain weight, especially for the grain growth of inferior spikelets (IS) after removing the spikelet. These results were mainly ascribed to the stronger sink strength of W1844 than that of CJ03 contrasting in the same group. The remobilization efficiency of NSC in the stem decreased significantly after removing the spikelet for both CJ03 and W1844, and the level of sugar signaling in the T6P-SnRK1 pathway was also significantly changed. However, W1844 outperformed CJ03 in terms of the efficiency of carbon reserve remobilization under the same treatments. More precisely, there was a significant difference during the early grain-filling stage in terms of the conversion of sucrose and starch. Interestingly, the sugar signaling of the T6P and SnRK1 pathways also represented an obvious change. Hence, sugar signaling may be promoted by sink strength to remobilize the NSCs of the rice stem during grain filling to further advance crop yield.

High-throughput SNP markers for authentication of Korean wheat cultivars based on seven complete plastomes and the nuclear genome

Wheat (Triticum aestivum) has diverse uses in the food industry, and different cultivars have unique properties; therefore, it is important to select the optimal cultivar for the intended end use. Here, to establish an identification system for Korean wheat cultivars, we obtained the complete plastome sequences of seven major Korean cultivars. Additionally, the open access database CerealsDB was queried to discover single-copy genomic single-nucleotide polymorphisms (SNPs) in the hexaploid wheat genome. Ten SNPs were developed into allele-specific PCR (ASP) markers, and eight of the SNPs used for ASP markers were converted into TaqMan high-throughput genotyping markers. Phylogenetic analysis using SNP genotypes revealed the genetic diversity and relationships among 137 wheat lines from around the world, including 35 Korean cultivars. This research thus presents a high-throughput authentication system for Korean wheat cultivars that may promote food industry uses of Korean wheat.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10068-022-01043-w.

Main effect and epistatic QTL affecting spike shattering and association with plant height revealed in two spring wheat (Triticum aestivum L.) populations

A major QTL on chromosome arm 4BS was associated with reduced spike shattering and reduced plant height in coupling phase, and a second major QTL associated with reduced spike shattering was detected on chromosome arm 5AL in the same wheat variety Carberry. Spike shattering can cause severe grain yield loss in wheat. Development of cultivars with reduced shattering but having easy mechanical threshability is the target of wheat breeding programs. This study was conducted to determine quantitative trait loci (QTL) associated with shattering resistance, and epistasis among QTL in the populations Carberry/AC Cadillac and Carberry/Thatcher. Response of the populations to spike shattering was evaluated near Swift Current, SK, in four to five environments. Plant height data recorded in different locations and years were used to determine the relationship of the trait with spike shattering. Each population was genotyped and mapped with the wheat 90 K Illumina iSelect SNP array. Main effect QTL were analyzed by MapQTL 6, and epistatic interactions between main effect QTL were determined by QTLNetwork 2.0. Correlations between height and shattering ranged from 0.15 to 0.49. Carberry contributed two major QTL associated with spike shattering on chromosome arms 4BS and 5AL, detected in both populations. Carberry also contributed two minor QTL on 7AS and 7AL. AC Cadillac contributed five minor QTL on 1AL, 2DL, 3AL, 3DL and 7DS. Nine epistatic QTL interactions were identified, out of which the most consistent and synergistic interaction, that reduced the expression of shattering, occurred between 4BS and 5AL QTL. The 4BS QTL was consistently associated with reduced shattering and reduced plant height in the coupling phase. The present findings shed light on the inheritance of shattering resistance and provide genetic markers for manipulating the trait to develop wheat cultivars.

Identification and mapping of QTL associated with some traits related for drought tolerance in wheat using SSR markers

Background

Wheat is the most important crop around the world. Drought stresses affect wheat production and their characterization. Most of the traits that are affected by drought are quantitative traits, so detection of the quantitative trait’s loci (QTLs) related to these traits is very important for breeder and wheat producers. In this trend, 285 F2 individuals from crosses between four bread wheat genotypes (Triticum aestivum L.), i.e., Sakha93, Sids1, Sakha94, and Gemmiza9, were used for identified QTLs associated with plant height (PH) and leaf wilting (LW). Single marker analysis and composite interval mapping (CIM) were used.

Results

A total of 116 QTLs loci were detected which covered 19 chromosomes out of the 21 chromosomes of wheat. PH and LW had 74 and 42 QTLs loci, respectively. On the other hand, chromosome 7A showed to bear the highest number of QTLs loci (15 loci). While chromosome 1A beard the highest number of QTLs loci related to PH (10 loci), chromosome 2B and 7A beard the highest number of QTLs related LW. We highly recommend our finding to help breeders in wheat breeding programs to improve plant height and leaf wilting.

Conclusion

Our investigation concluded that SSR markers have high efficiency in the identification of QTLs related to abiotic stress; also the CIM method had more advanced priority for QTLs mapping.

Construction of transgenic detection system of Brassica napus L. based on single nucleotide polymorphism chip

Brassica napus L. is a vital oil crop in China. As auxiliary tools for rapeseed breeding, transgenic technologies play a considerable role in heterosis, variety improvement, and pest resistance. Research on transgenic detection technologies is of great significance for the introduction, supervision, and development of transgenic rapeseed in China. However, the transgenic detection methods currently in use are complex and time-consuming, with low output. A single nucleotide polymorphism (SNP) chip can effectively overcome such limitations. In the present study, we collected 40 transgenic elements and designed 291 probes. The probe sequences were submitted to Illumina Company, and the Infinium chip technology was used to prepare SNP chips. In the present Brassica napus transgenic detection experiment, 84 high-quality probes of 17 transgenic elements were preliminarily screened, and genotyping effect was optimised for the probe signal value. Ultimately, a transgenic detection system for B. napus was developed. The developed system has the advantages of simple operation, minimal technical errors, and stable detection outcomes. A transgenic detection sensitivity test revealed that the probe designed could accurately detect 1% of transgenic samples and had high detection sensitivity. In addition, in repeatability tests, the CaMV35S promoter coefficient of variation was approximately 3.58%. Therefore, the SNP chip had suitable repeatability in transgene detection. The SNP chip developed could be used to construct transgenic detection systems for B. napus.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-03062-6.

Resistance of the Wheat Cultivar ‘Renan’ to Septoria Leaf Blotch Explained by a Combination of Strain Specific and Strain Non-Specific QTL Mapped on an Ultra-Dense Genetic Map

Quantitative resistance is considered more durable than qualitative resistance as it does not involve major resistance genes that can be easily overcome by pathogen populations, but rather a combination of genes with a lower individual effect. This durability means that quantitative resistance could be an interesting tool for breeding crops that would not systematically require phytosanitary products. Quantitative resistance has yet to reveal all of its intricacies. Here, we delve into the case of the wheat/Septoria tritici blotch (STB) pathosystem. Using a population resulting from a cross between French cultivar Renan, generally resistant to STB, and Chinese Spring, a cultivar susceptible to the disease, we built an ultra-dense genetic map that carries 148,820 single nucleotide polymorphism (SNP) markers. Phenotyping the interaction was done with two different Zymoseptoria tritici strains with contrasted pathogenicities on Renan. A linkage analysis led to the detection of three quantitative trait loci (QTL) related to resistance in Renan. These QTL, on chromosomes 7B, 1D, and 5D, present with an interesting diversity as that on 7B was detected with both fungal strains, while those on 1D and 5D were strain-specific. The resistance on 7B was located in the region of Stb8 and the resistance on 1D colocalized with Stb19. However, the resistance on 5D was new, so further designated Stb20q. Several wall-associated kinases (WAK), nucleotide-binding and leucine-rich repeats (NB-LRR) type, and kinase domain carrying genes were present in the QTL regions, and some of them were expressed during the infection. These results advocate for a role of Stb genes in quantitative resistance and for resistance in the wheat/STB pathosystem being as a whole quantitative and polygenic.

A high-resolution consensus linkage map for barley based on GBS-derived genotypes

As genotyping-by-sequencing (GBS) is widely used in barley genetic studies, the translation of the physical position of GBS-derived SNPs into accurate genetic positions has become relevant. The main aim of this study was to develop a high-resolution consensus linkage map based on GBS-derived SNPs. The construction of this integrated map involved 11 bi-parental populations composed of 3743 segregating progenies. We adopted a uniform set of SNP-calling and filtering conditions to identify 50 875 distinct SNPs segregating in at least one population. These SNPs were grouped into 18 580 non-redundant SNPs (bins). The resulting consensus linkage map spanned 1050.1 cM, providing an average density of 17.7 bins and 48.4 SNPs per cM. The consensus map is characterized by the absence of large intervals devoid of marker coverage (significant gaps), the largest interval between bins was only 3.7 cM and the mean distance between adjacent bins was 0.06 cM. This high-resolution linkage map will contribute to several applications in genomic research, such as providing useful information on the recombination landscape for QTLs/genes identified via GWAS or ensuring a uniform distribution of SNPs when developing low-cost genotyping tools offering a limited number of markers.

Yield-Related QTL Clusters and the Potential Candidate Genes in Two Wheat DH Populations

In the present study, four large-scale field trials using two doubled haploid wheat populations were conducted in different environments for two years. Grain protein content (GPC) and 21 other yield-related traits were investigated. A total of 227 QTL were mapped on 18 chromosomes, which formed 35 QTL clusters. The potential candidate genes underlying the QTL clusters were suggested. Furthermore, adding to the significant correlations between yield and its related traits, correlation variations were clearly shown within the QTL clusters. The QTL clusters with consistently positive correlations were suggested to be directly utilized in wheat breeding, including 1B.2, 2A.2, 2B (4.9–16.5 Mb), 2B.3, 3B (68.9–214.5 Mb), 4A.2, 4B.2, 4D, 5A.1, 5A.2, 5B.1, and 5D. The QTL clusters with negative alignments between traits may also have potential value for yield or GPC improvement in specific environments, including 1A.1, 2B.1, 1B.3, 5A.3, 5B.2 (612.1–613.6 Mb), 7A.1, 7A.2, 7B.1, and 7B.2. One GPC QTL (5B.2: 671.3–672.9 Mb) contributed by cultivar Spitfire was positively associated with nitrogen use efficiency or grain protein yield and is highly recommended for breeding use. Another GPC QTL without negatively pleiotropic effects on 2A (50.0–56.3 Mb), 2D, 4D, and 6B is suggested for quality wheat breeding.

Physical mapping of QTL associated with agronomic and end-use quality traits in spring wheat under conventional and organic management systems

Using phenotypic data of four biparental spring wheat populations evaluated at multiple environments under two management systems, we discovered 152 QTL and 22 QTL hotspots, of which two QTL accounted for up to 37% and 58% of the phenotypic variance, consistently detected in all environments, and fell within genomic regions harboring known genes. Identification of the physical positions of quantitative trait loci (QTL) would be highly useful for developing functional markers and comparing QTL results across multiple independent studies. The objectives of the present study were to map and characterize QTL associated with nine agronomic and end-use quality traits (tillering ability, plant height, lodging, grain yield, grain protein content, thousand kernel weight, test weight, sedimentation volume, and falling number) in hard red spring wheat recombinant inbred lines (RILs) using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map. We evaluated a total of 698 RILs from four populations derived from crosses involving seven parents at 3-8 conventionally (high N) and organically (low N) managed field environments. Using the phenotypic data combined across all environments per management, and the physical map between 1058 and 6526 markers per population, we identified 152 QTL associated with the nine traits, of which 29 had moderate and 2 with major effects. Forty-nine of the 152 QTL mapped across 22 QTL hotspot regions with each region coincident to 2-6 traits. Some of the QTL hotspots were physically located close to known genes. QSv.dms-1A and QPht.dms-4B.1 individually explained up to 37% and 58% of the variation in sedimentation volume and plant height, respectively, and had very large LOD scores that varied from 19.0 to 35.7 and from 16.7 to 55.9, respectively. We consistently detected both QTL in the combined and all individual environments, laying solid ground for further characterization and possibly for cloning.

The Bnapus50K array: a quick and versatile genotyping tool for Brassica napus genomic breeding and research

Rapeseed is a globally cultivated commercial crop, primarily grown for its oil. High-density single nucleotide polymorphism (SNP) arrays are widely used as a standard genotyping tool for rapeseed research, including for gene mapping, genome-wide association studies, germplasm resource analysis, and cluster analysis. Although considerable rapeseed genome sequencing data have been released, DNA arrays are still an attractive choice for providing additional genetic data in an era of high-throughput whole-genome sequencing. Here, we integrated re-sequencing DNA array data (32,216, 304 SNPs) from 505 inbred rapeseed lines, allowing us to develop a sensitive and efficient genotyping DNA array, Bnapus50K, with a more consistent genetic and physical distribution of probes. A total of 42,090 high-quality probes were filtered and synthesized, with an average distance between adjacent SNPs of 8 kb. To improve the practical application potential of this array in rapeseed breeding, we also added 1,618 functional probes related to important agronomic traits such as oil content, disease resistance, male sterility, and flowering time. The additional probes also included those specifically for detecting genetically modified material. These probes show a good detection efficiency and are therefore useful for gene mapping, along with crop variety improvement and identification. The novel Bnapus50K DNA array developed in this study could prove to be a quick and versatile genotyping tool for B. napus genomic breeding and research.

Construction of Consensus Genetic Map With Applications in Gene Mapping of Wheat (Triticum aestivum L.) Using 90K SNP Array

Wheat is one of the most important cereal crops worldwide. A consensus map combines genetic information from multiple populations, providing an effective alternative to improve the genome coverage and marker density. In this study, we constructed a consensus map from three populations of recombinant inbred lines (RILs) of wheat using a 90K single nucleotide polymorphism (SNP) array. Phenotypic data on plant height (PH), spike length (SL), and thousand-kernel weight (TKW) was collected in six, four, and four environments in the three populations, and then used for quantitative trait locus (QTL) mapping. The mapping results obtained using the constructed consensus map were compared with previous results obtained using individual maps and previous studies on other populations. A simulation experiment was also conducted to assess the performance of QTL mapping with the consensus map. The constructed consensus map from the three populations spanned 4558.55 cM in length, with 25,667 SNPs, having high collinearity with physical map and individual maps. Based on the consensus map, 21, 27, and 19 stable QTLs were identified for PH, SL, and TKW, much more than those detected with individual maps. Four PH QTLs and six SL QTLs were likely to be novel. A putative gene called TraesCS4D02G076400 encoding gibberellin-regulated protein was identified to be the candidate gene for one major PH QTL located on 4DS, which may enrich genetic resources in wheat semi-dwarfing breeding. The simulation results indicated that the length of the confidence interval and standard errors of the QTLs detected using the consensus map were much smaller than those detected using individual maps. The consensus map constructed in this study provides the underlying genetic information for systematic mapping, comparison, and clustering of QTL, and gene discovery in wheat genetic study. The QTLs detected in this study had stable effects across environments and can be used to improve the wide adaptation of wheat cultivars through marker-assisted breeding.

Genome-Wide Association Study for Body Length, Body Height, and Total Teat Number in Large White Pigs

Body length, body height, and total teat number are economically important traits in pig breeding, as these traits are usually associated with the growth, reproductivity, and longevity potential of piglets. Here, we report a genetic analysis of these traits using a population comprising 2,068 Large White pigs. A genotyping-by-sequencing (GBS) approach was used to provide high-density genome-wide SNP discovery and genotyping. Univariate and bivariate animal models were used to estimate heritability and genetic correlations. The results showed that heritability estimates for body length, body height, and total teat number were 0.25 ± 0.04, 0.11 ± 0.03, and 0.22 ± 0.04, respectively. The genetic correlation between body length and body height exhibited a strongly positive correlation (0.63 ± 0.15), while a positive but low genetic correlation was observed between total teat number and body length. Furthermore, we used two different genome-wide association study (GWAS) approaches: single-locus GWAS and weighted single-step GWAS (WssGWAS), to identify candidate genes for these traits. Single-locus GWAS detected 76, 13, and 29 significant single-nucleotide polymorphisms (SNPs) associated with body length, body height, and total teat number. Notably, the most significant SNP (S17_15781294), which is located 20 kb downstream of the BMP2 gene, explained 9.09% of the genetic variance for body length traits, and it also explained 9.57% of the genetic variance for body height traits. In addition, another significant SNP (S7_97595973), which is located in the ABCD4 gene, explained 8.92% of the genetic variance for total teat number traits. GWAS results for these traits identified some candidate genomic regions, such as SSC6: 14.96–15.02 Mb, SSC7: 97.18–98.18 Mb, SSC14: 128.29–131.15 Mb, SSC17: 15.39–17.27 Mb, and SSC17: 22.04–24.15 Mb, providing a starting point for further inheritance research. Most quantitative trait loci were detected by single-locus GWAS and WssGWAS. These findings reveal the complexity of the genetic mechanism of the three traits and provide guidance for subsequent genetic improvement through genome selection.

Elucidating SNP-based genetic diversity and population structure of advanced breeding lines of bread wheat (Triticum aestivum L.)

Genetic diversity and population structure information are crucial for enhancing traits of interest and the development of superlative varieties for commercialization. The present study elucidated the population structure and genetic diversity of 141 advanced wheat breeding lines using single nucleotide polymorphism markers. A total of 14,563 high-quality identified genotyping-by-sequencing (GBS) markers were distributed covering 13.9 GB wheat genome, with a minimum of 1,026 SNPs on the homoeologous group four and a maximum of 2,838 SNPs on group seven. The average minor allele frequency was found 0.233, although the average polymorphism information content (PIC) and heterozygosity were 0.201 and 0.015, respectively. Principal component analyses (PCA) and population structure identified two major groups (sub-populations) based on SNPs information. The results indicated a substantial gene flow/exchange with many migrants (Nm = 86.428) and a considerable genetic diversity (number of different alleles, Na = 1.977; the number of effective alleles, Ne = 1.519; and Shannon's information index, I = 0.477) within the population, illustrating a good source for wheat improvement. The average PIC of 0.201 demonstrates moderate genetic diversity of the present evaluated advanced breeding panel. Analysis of molecular variance (AMOVA) detected 1% and 99% variance between and within subgroups. It is indicative of excessive gene traffic (less genetic differentiation) among the populations. These conclusions deliver important information with the potential to contribute new beneficial alleles using genome-wide association studies (GWAS) and marker-assisted selection to enhance genetic gain in South Asian wheat breeding programs.

QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents

Traits such as plant height (PH), juvenile growth habit (GH), heading date (HD), and tiller number are important for both increasing yield potential and improving crop adaptation to climate change. In the present study, these traits were investigated by using the same bi-parental population at early (F₂ and F₂-derived F₃ families) and late (F₆ and F₇, recombinant inbred lines, RILs) generations to detect quantitative trait loci (QTLs) and search for candidate genes. A total of 176 and 178 lines were genotyped by the wheat Illumina 25K Infinium SNP array. The two genetic maps spanned 2486.97 cM and 3732.84 cM in length, for the F₂ and RILs, respectively. QTLs explaining the highest phenotypic variation were found on chromosomes 2B, 2D, 5A, and 7D for HD and GH, whereas those for PH were found on chromosomes 4B and 4D. Several QTL detected in the early generations (i.e., PH and tiller number) were not detected in the late generations as they were due to dominance effects. Some of the identified QTLs co-mapped to well-known adaptive genes (i.e., Ppd-1, Vrn-1, and Rht-1). Other putative candidate genes were identified for each trait, of which PINE1 and PIF4 may be considered new for GH and TTN in wheat. The use of a large F₂ mapping population combined with NGS-based genotyping techniques could improve map resolution and allow closer QTL tagging.

Toward the Genetic Basis and Multiple QTLs of Kernel Hardness in Wheat

Kernel hardness is one of the most important single traits of wheat seed. It classifies wheat cultivars, determines milling quality and affects many end-use qualities. Starch granule surfaces, polar lipids, storage protein matrices and Puroindolines potentially form a four-way interaction that controls wheat kernel hardness. As a genetic factor, Puroindoline polymorphism explains over 60% of the variation in kernel hardness. However, genetic factors other than Puroindolines remain to be exploited. Over the past two decades, efforts using population genetics have been increasing, and numerous kernel hardness-associated quantitative trait loci (QTLs) have been identified on almost every chromosome in wheat. Here, we summarize the state of the art for mapping kernel hardness. We emphasize that these steps in progress have benefitted from (1) the standardized methods for measuring kernel hardness, (2) the use of the appropriate germplasm and mapping population, and (3) the improvements in genotyping methods. Recently, abundant genomic resources have become available in wheat and related Triticeae species, including the high-quality reference genomes and advanced genotyping technologies. Finally, we provide perspectives on future research directions that will enhance our understanding of kernel hardness through the identification of multiple QTLs and will address challenges involved in fine-tuning kernel hardness and, consequently, food properties.

A novel adult plant leaf rust resistance gene Lr2K38 mapped on wheat chromosome 1AL

Soft red winter wheat (SRWW) cultivar AGS 2038 has a high level of seedling and adult plant leaf rust (LR) resistance. To map and characterize LR resistance in AGS 2038, a recombinant inbred line (RIL) population consisting of 225 lines was developed from a cross between AGS 2038 and moderately resistant line UGA 111729. The parents and RIL population were phenotyped for LR response in three field environments at Plains and Griffin, GA, in the 2017-2018 and 2018-2019 growing seasons, one greenhouse environment at the adult-plant stage, and at seedling stage. The RIL population was genotyped with the Illumina iSelect 90K SNP marker array, and a total of 7667 polymorphic markers representing 1513 unique loci were used to construct a linkage map. Quantitative trait loci (QTL) analysis detected six QTL, QLr.ags-1AL, QLr.ags-2AS, QLr.ags-2BS1, QLr.ags-2BS2, QLr.ags-2BS3, and QLr.ags-2DS, for seedling and adult plant LR resistance. Of these, the major adult plant leaf rust resistance QTL, QLr.ags-1AL, was detected on all field and greenhouse adult plant tests and explained up to 34.45% of the phenotypic variation. QLr.ags-1AL, tightly flanked by IWB20487 and IWA4022 markers, was contributed by AGS 2038. Molecular marker analysis using a diagnostic marker linked to Lr59 showed that QLr.ags-1AL was different from Lr59, the only known LR resistance gene on 1AL. Therefore, the QTL was temporarily designated as Lr2K38. Lr2K38-linked marker IWB20487 was highly polymorphic among 30 SRWW lines and should be useful for selecting the Lr2K38 in wheat breeding programs.

Major genomic regions responsible for wheat yield and its components as revealed by meta-QTL and genotype-phenotype association analyses

MAIN CONCLUSION

Meta-QTL (MQTL) analysis was done for yield-related traits in wheat. Candidate genes were identified within the refined MQTL and further validated by genotype-phenotype association analysis. Extensive studies have been undertaken on quantitative trait locus/loci (QTL) for wheat yield and its component traits. This study conducted a meta-analysis of 381 QTL related to wheat yield under various environments, including irrigated, drought- and/or heat-stressed conditions. Markers flanking meta-QTL (MQTL) were mapped on the wheat reference genome for their physical positions. Putative candidate genes were examined for MQTL with a physical interval of less than 20 Mbp. A total of 86 MQTL were identified as responsible for yield, of which 34 were for irrigated environments, 39 for drought-stressed environments, 36 for heat-stressed environments, and 23 for both drought- and heat-stressed environments. The high-confidence genes within the physical positions of the MQTL flanking markers were screened in the reference genome RefSeq V1.0, which identified 210 putative candidate genes. The phenotypic data for 14 contrasting genotypes with either high or low yield performance-according to the Australian National Variety Trials-were associated with their genotypic data obtained through ddRAD sequencing, which validated 18 genes or gene clusters associated with MQTL that had important roles for wheat yield. The detected and refined MQTL and candidate genes will be useful for marker-assisted selection of high yield in wheat breeding.

Genome-Wide Association Mapping of Adult-Plant Resistance to Stripe Rust in Common Wheat (Triticum aestivum)

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a globally devastating disease of common wheat (Triticum aestivum L.), resulting in substantial economic losses. To identify effective resistance genes, a genome-wide association study was conducted on 120 common wheat lines from different wheat-growing regions of China using the wheat 90K iSelect SNP array. Seventeen loci were identified, explaining 9.5 to 21.8% of the phenotypic variation. Most of these genes were detected in the A (seven) and B (seven) genomes, with only three in the D genome. Among them, 11 loci were colocated with known resistance genes or quantitative trait loci reported previously, whereas the other six are likely new resistance loci. Annotation of flanking sequences of significantly associated SNPs indicated the presence of three important candidate genes, including E3 ubiquitin-protein ligase, F-box repeat protein, and disease resistance RPP13-like protein. This study increased our knowledge in understanding the genetic architecture for stripe rust resistance and identified wheat varieties with multiple resistance alleles, which are useful for improvement of stripe rust resistance in breeding.

Mapping of Major Fusarium Head Blight Resistance from Canadian Wheat cv. AAC Tenacious

Fusarium head blight (FHB) is one of the most devastating wheat disease due to its direct detrimental effects on grain-yield, quality and marketability. Resistant cultivars offer the most effective approach to manage FHB; however, the lack of different resistance resources is still a major bottleneck for wheat breeding programs. To identify and dissect FHB resistance, a doubled haploid wheat population produced from the Canadian spring wheat cvs AAC Innova and AAC Tenacious was phenotyped for FHB response variables incidence and severity, visual rating index (VRI), deoxynivalenol (DON) content, and agronomic traits days to anthesis (DTA) and plant height (PHT), followed by single nucleotide polymorphism (SNP) and simple sequence repeat (SSR) marker genotyping. A high-density map was constructed consisting of 10,328 markers, mapped on all 21 chromosomes with a map density of 0.35 cM/marker. Together, two major quantitative trait loci for FHB resistance were identified on chromosome 2D from AAC Tenacious; one of these loci on 2DS also colocated with loci for DTA and PHT. Another major locus for PHT, which cosegregates with locus for low DON, was also identified along with many minor and epistatic loci. QTL identified from AAC Tenacious may be useful to pyramid FHB resistance.

Mapping quantitative trait loci associated with leaf rust resistance in five spring wheat populations using single nucleotide polymorphism markers

Growing resistant wheat (Triticum aestivum L) varieties is an important strategy for the control of leaf rust, caused by Puccinia triticina Eriks. This study sought to identify the chromosomal location and effects of leaf rust resistance loci in five Canadian spring wheat cultivars. The parents and doubled haploid lines of crosses Carberry/AC Cadillac, Carberry/Vesper, Vesper/Lillian, Vesper/Stettler and Stettler/Red Fife were assessed for leaf rust severity and infection response in field nurseries in Canada near Swift Current, SK from 2013 to 2015, Morden, MB from 2015 to 2017 and Brandon, MB in 2016, and in New Zealand near Lincoln in 2014. The populations were genotyped with the 90K Infinium iSelect assay and quantitative trait loci (QTL) analysis was performed. A high density consensus map generated based on 14 doubled haploid populations and integrating SNP and SSR markers was used to compare QTL identified in different populations. AC Cadillac contributed QTL on chromosomes 2A, 3B and 7B (2 loci), Carberry on 1A, 2B (2 loci), 2D, 4B (2 loci), 5A, 6A, 7A and 7D, Lillian on 4A and 7D, Stettler on 2D and 6B, Vesper on 1B, 1D, 2A, 6B and 7B (2 loci), and Red Fife on 7A and 7B. Lillian contributed to a novel locus QLr.spa-4A, and similarly Carberry at QLr.spa-5A. The discovery of novel leaf rust resistance QTL QLr.spa-4A and QLr.spa-5A, and several others in contemporary Canada Western Red Spring wheat varieties is a tremendous addition to our present knowledge of resistance gene deployment in breeding. Carberry demonstrated substantial stacking of genes which could be supplemented with the genes identified in other cultivars with the expectation of increasing efficacy of resistance to leaf rust and longevity with little risk of linkage drag.

QTL mapping for quality traits using a high-density genetic map of wheat

Protein- and starch-related quality traits, which are quantitatively inherited and significantly influenced by the environment, are critical determinants of the end-use quality of wheat. We constructed a high-density genetic map containing 10,739 loci (5,399 unique loci) using a set of 184 recombinant inbred lines (RILs) derived from a cross of 'Tainong 18 × Linmai 6' (TL-RILs). In this study, a quantitative trait loci (QTLs) analysis was used to examine the genetic control of grain protein content, sedimentation value, farinograph parameters, falling number and the performance of the starch pasting properties using TL-RILs grown in a field for three years. A total of 106 QTLs for 13 quality traits were detected, distributed on the 21 chromosomes. Of these, 38 and 68 QTLs for protein- and starch-related traits, respectively, were detected in three environments and their average values (AV). Twenty-six relatively high-frequency QTLs (RHF-QTLs) that were detected in more than two environments. Twelve stable QTL clusters containing at least one RHF-QTL were detected and classified into three types: detected only for protein-related traits (type I), detected only for starch-related traits (type II), and detected for both protein- and starch-related traits (type III). A total of 339 markers flanked with 11 QTL clusters (all except C6), were found to be highly homologous with 282 high confidence (HC) and 57 low confidence (LC) candidate genes based on IWGSC RefSeq v 1.0. These stable QTLs and RHF-QTLs, especially those grouped into clusters, are credible and should be given priority for QTL fine-mapping and identification of candidate genes with which to explain the molecular mechanisms of quality development and inform marker-assisted breeding in the future.

Construction and integration of genetic linkage maps from three multi-parent advanced generation inter-cross populations in rice

BACKGROUND

The construction of genetic maps based on molecular markers is a crucial step in rice genetic and genomic studies. Pure lines derived from multiple parents provide more abundant genetic variation than those from bi-parent populations. Two four-parent pure-line populations (4PL1 and 4PL2) and one eight-parent pure-line population (8PL) were developed from eight homozygous indica varieties of rice by the International Rice Research Institute (IRRI). To the best of our knowledge, there have been no reports on linkage map construction and their integration in multi-parent populations of rice.

RESULTS

We constructed linkage maps for the three multi-parent populations and conducted quantitative trait locus (QTL) mapping for heading date (HD) and plant height (PH) based on the three maps by inclusive composite interval mapping (ICIM). An integrated map was built from the three individual maps and used for QTL projection and meta-analysis. QTL mapping of the three populations was also conducted based on the integrated map, and the mapping results were compared with those from meta-analysis. The three linkage maps developed for 8PL, 4PL1 and 4PL2 had 5905, 4354 and 5464 bins and were 1290.16, 1720.01 and 1560.30 cM in length, respectively. The integrated map was 3022.08 cM in length and contained 10,033 bins. Based on the three linkage maps, 3, 7 and 9 QTLs were detected for HD while 6, 9 and 10 QTLs were detected for PH in 8PL, 4PL1 and 4PL2, respectively. In contrast, 19 and 25 QTLs were identified for HD and PH by meta-analysis using the integrated map, respectively. Based on the integrated map, 5, 9, and 10 QTLs were detected for HD while 3, 10, and 12 QTLs were detected for PH in 8PL, 4PL1 and 4PL2, respectively. Eleven of these 49 QTLs coincided with those from the meta-analysis.

CONCLUSIONS

In this study, we reported the first rice linkage map constructed from one eight-parent recombinant inbred line (RIL) population and the first integrated map from three multi-parent populations, which provide essential information for QTL linkage mapping, meta-analysis, and map-based cloning in rice genetics and breeding.

Genetic diversity and population structure analysis based on the high density SNP markers in Ethiopian durum wheat (Triticum turgidum ssp. durum)

Background

Ethiopia has been considered as a center of diversity and the second possible center of domestication of durum wheat. Genetic diversity and population structure analysis in the existing Ethiopian durum wheat germplasm have enormous importance in enhancing breeding effort and for sustainable conservation. Hence, 192 Ethiopian durum wheat accessions comprising 167 landraces collected from major wheat-growing areas of the country and 25 improved varieties released from Debre Zeit and Sinana Agricultural Research Centers, Ethiopia in different years (1994–2010) were assembled for the current study.

Results

The panel was genotyped with a High-density 90 K wheat SNP array by Illumina and generated 15,338 polymorphic SNPs that were used to analyze the genetic diversity and to estimate the population structure. Varied values of genetic diversity indices were scored across chromosomes and genomes. Genome-wide mean values of Nei’s gene diversity (0.246) and polymorphism information content (0.203) were recorded signifying the presence of high genetic diversity within this collection. Minor allele frequency of the genome varied with a range of 0.005 to 0.5 scoring a mean value of 0.175. Improved varieties clustered separately to landraces in population structure analysis resulted from STRUCTURE, PCA and neighbor joining tree. Landraces clustering was irrespective of their geographical origin signifying the presence of higher admixture that could arise due to the existence of historical exchanges of seeds through informal seed system involving regional and countrywide farming communities in Ethiopia.

Conclusions

Sustainable utilization and conservation of this rich Ethiopian durum wheat genetic resource is an irreplaceable means to cope up from the recurrent climate changes and biotic stresses happening widely and thereby able to keep meeting the demand of durum productivity for the ever-growing human population.

Genetic dissection of a major QTL for kernel weight spanning the Rht-B1 locus in bread wheat

Genetic dissection uncovered a major QTL QTKW.caas-4BS corresponding with a 483 kb deletion that included genes ZnF, EamA and Rht-B1. This deletion was associated with increased grain weight and semi-dwarf phenotype. Previous studies identified quantitative trait loci (QTL) for thousand kernel weight (TKW) in the region spanning the Rht-B1 locus in wheat (Triticum aestivum L.). We recently mapped a major QTL QTKW.caas-4BS for TKW spanning the Rht-B1 locus in a recombinant inbred line (RIL) population derived from Doumai/Shi 4185 using the wheat 90K array. The allele from Doumai at QTKW.caas-4BS significantly increased TKW and kernel number per spike, and conferred semi-dwarf trait, which was beneficial to improve grain yield without a penalty to lodging. To further dissect QTKW.caas-4BS, we firstly re-investigated the genotypes and phenotypes of the RILs and confirmed the QTL using cleaved amplified polymorphic sequence (CAPS) markers developed from flanking SNP markers IWA102 and IWB54814. The target sequences of the CAPS markers were used as queries to BLAST the wheat reference genome RefSeq v1.0 and hit an approximate 10.4 Mb genomic region. Based on genomic mining and SNP loci from the wheat 660K SNP array in the above genomic region, we developed eight new markers and narrowed QTKW.caas-4BS to a genetic interval of 1.5 cM. A 483 kb deletion in Doumai corresponded with QTKW.caas-4BS genetically, including three genes ZnF, EamA and Rht-B1. The other 15 genes with either differential expressions and/or sequence variations between parents were also potential candidate genes for QTKW.caas-4BS. The findings not only provide a toolkit for marker-assisted selection of QTKW.caas-4BS but also defined candidate genes for further functional analysis.

Genome-wide association study and quantitative trait loci mapping of seed dormancy in common wheat (Triticum aestivum L.)

Totally, 23 and 26 loci for the first count germination ratio and the final germination ratio were detected by quantitative trait loci (QTL) mapping and association mapping, respectively, which could be used to facilitate wheat pre-harvest sprouting breeding. Weak dormancy can cause pre-harvest sprouting in seeds of common wheat which significantly reduces grain yield. In this study, both quantitative trait loci (QTL) mapping and genome-wide association study (GWAS) were used to identify loci controlling seed dormancy. The analyses were based on a recombinant inbred line population derived from Zhou 8425B/Chinese Spring cross and 166 common wheat accessions. Inclusive composite interval mapping detected 8 QTL, while 45 loci were identified in the 166 wheat accessions by GWAS. Among these, four loci (Q_bifcgr.cas-3AS/Qfcgr.cas-3AS, Q_bifcgr.cas-6AL.1/Qfcgr.cas-6AL.1, Q_bifcgr.cas-7BL.2/Qfcgr.cas-7BL.2, and Q_bigr.cas-3DL/Qgr.cas-3DL) were detected in both QTL mapping and GWAS. In addition, 41 loci co-located with QTL reported previously, whereas 8 loci (Qfcgr.cas-5AL, Qfcgr.cas-6DS, Qfcgr.cas-7AS, Qgr.cas-3DS.1, Qgr.cas-3DS.2, Q_bigr.cas-3DL/Qgr.cas-3DL, Qgr.cas-4B, and Qgr.cas-5A) were likely to be new. Linear regression showed the first count germination ratio or the final germination ratio reduced while multiple favorable alleles increased. It is suggested that QTL pyramiding was effective to reduce pre-harvest sprouting risk. This study could enrich the research on pre-harvest sprouting and provide valuable information of marker exploration for wheat breeding programs.

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.

From markers to genome-based breeding in wheat

Recent technological advances in wheat genomics provide new opportunities to uncover genetic variation in traits of breeding interest and enable genome-based breeding to deliver wheat cultivars for the projected food requirements for 2050. There has been tremendous progress in development of whole-genome sequencing resources in wheat and its progenitor species during the last 5 years. High-throughput genotyping is now possible in wheat not only for routine gene introgression but also for high-density genome-wide genotyping. This is a major transition phase to enable genome-based breeding to achieve progressive genetic gains to parallel to projected wheat production demands. These advances have intrigued wheat researchers to practice less pursued analytical approaches which were not practiced due to the short history of genome sequence availability. Such approaches have been successful in gene discovery and breeding applications in other crops and animals for which genome sequences have been available for much longer. These strategies include, (i) environmental genome-wide association studies in wheat genetic resources stored in genbanks to identify genes for local adaptation by using agroclimatic traits as phenotypes, (ii) haplotype-based analyses to improve the statistical power and resolution of genomic selection and gene mapping experiments, (iii) new breeding strategies for genome-based prediction of heterosis patterns in wheat, and (iv) ultimate use of genomics information to develop more efficient and robust genome-wide genotyping platforms to precisely predict higher yield potential and stability with greater precision. Genome-based breeding has potential to achieve the ultimate objective of ensuring sustainable wheat production through developing high yielding, climate-resilient wheat cultivars with high nutritional quality.

Efficient algorithms for Longest Common Subsequence of two bucket orders to speed up pairwise genetic map comparison

Genetic maps order genetic markers along chromosomes. They are, for instance, extensively used in marker-assisted selection to accelerate breeding programs. Even for the same species, people often have to deal with several alternative maps obtained using different ordering methods or different datasets, e.g. resulting from different segregating populations. Having efficient tools to identify the consistency and discrepancy of alternative maps is thus essential to facilitate genetic map comparisons. We propose to encode genetic maps by bucket order, a kind of order, which takes into account the blurred parts of the marker order while being an efficient data structure to achieve low complexity algorithms. The main result of this paper is an O(n log(n)) procedure to identify the largest agreements between two bucket orders of n elements, their Longest Common Subsequence (LCS), providing an efficient solution to highlight discrepancies between two genetic maps. The LCS of two maps, being the largest set of their collinear markers, is used as a building block to compute pairwise map congruence, to visually emphasize maker collinearity and in some scaffolding methods relying on genetic maps to improve genome assembly. As the LCS computation is a key subroutine of all these genetic map related tools, replacing the current LCS subroutine of those methods by ours -to do the exact same work but faster- could significantly speed up those methods without changing their accuracy. To ease such transition we provide all required algorithmic details in this self contained paper as well as an R package implementing them, named LCSLCIS, which is freely available at: https://github.com/holtzy/LCSLCIS.

Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers

We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay. Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai × Shi 4185 (D × S), Gaocheng 8901 × Zhoumai 16 (G × Z) and Linmai 2 × Zhong 892 (L × Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5-32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

High throughput SNP discovery and genotyping in hexaploid wheat

Because of their abundance and their amenability to high-throughput genotyping techniques, Single Nucleotide Polymorphisms (SNPs) are powerful tools for efficient genetics and genomics studies, including characterization of genetic resources, genome-wide association studies and genomic selection. In wheat, most of the previous SNP discovery initiatives targeted the coding fraction, leaving almost 98% of the wheat genome largely unexploited. Here we report on the use of whole-genome resequencing data from eight wheat lines to mine for SNPs in the genic, the repetitive and non-repetitive intergenic fractions of the wheat genome. Eventually, we identified 3.3 million SNPs, 49% being located on the B-genome, 41% on the A-genome and 10% on the D-genome. We also describe the development of the TaBW280K high-throughput genotyping array containing 280,226 SNPs. Performance of this chip was examined by genotyping a set of 96 wheat accessions representing the worldwide diversity. Sixty-nine percent of the SNPs can be efficiently scored, half of them showing a diploid-like clustering. The TaBW280K was proven to be a very efficient tool for diversity analyses, as well as for breeding as it can discriminate between closely related elite varieties. Finally, the TaBW280K array was used to genotype a population derived from a cross between Chinese Spring and Renan, leading to the construction a dense genetic map comprising 83,721 markers. The results described here will provide the wheat community with powerful tools for both basic and applied research.