Major QTL for Seven Yield-Related Traits in Common Wheat (Triticum aestivum L.)

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

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

Mining of QTLs for Spring Bread Wheat Spike Productivity by Comparing Spring Wheat Cultivars Released in Different Decades of the Last Century

Genome-wide association studies (GWAS) are among the genetic tools for the mining of genomic loci associated with useful agronomic traits. The study enabled us to find new genetic markers associated with grain yield as well as quality. The sample under study consisted of spring wheat cultivars developed in different decades of the last century. A panel of 186 accessions was evaluated at VIR's experiment station in Pushkin across a 3-year period of field trials. In total, 24 SNPs associated with six productivity characteristics were revealed. Along with detecting significant markers for each year of the field study, meta-analyses were conducted. Loci associated with useful yield-related agronomic characteristics were detected on chromosomes 4A, 5A, 6A, 6B, and 7B. In addition to previously described regions, novel loci associated with grain yield and quality were identified during the study. We presume that the utilization of contrast cultivars which originated in different breeding periods allowed us to identify new markers associated with useful agronomic characteristics.

A High-Resolution Linkage Map Construction and QTL Analysis for Morphological Traits in Anthurium (Anthurium andraeanum Linden)

Anthurium andraeanum Linden is a prominent ornamental plant belonging to the family Araceae and is cultivated worldwide. The morphology characteristics are crucial because they significantly impact ornamental values, commercial properties, and the efficiency of space utilization in production. However, only a few related investigations have been conducted in anthurium to date. In this study, an F1 genetic segregation population containing 160 progenies was generated through hybridization between potted and cut anthurium varieties. Fifteen morphological traits were assessed and revealed substantial levels of genetic variation and widespread positive correlation. Based on specific length amplified fragment (SLAF) sequencing technology, 8171 single nucleotide polymorphism (SNP) markers were developed, and the high-density linkage map of 2202.27 cM in length distributed on 15 linkage groups was constructed successfully, with an average distance of 0.30 cM. Using the inclusive composite interval mapping (ICIM) method, 59 QTLs related to 15 key morphological traits were successfully identified, which explained phenotypic variance (PVE) ranging from 6.21% to 17.74%. Thirty-three of those associated with 13 traits were designated as major QTLs with PVE > 10%. These findings offer valuable insights into the genetic basis of quantitative traits and are beneficial for molecular marker-assisted selection (MAS) in anthurium breeding.

Genome-wide association mapping in elite winter wheat breeding for yield improvement

Increased grain yield (GY) is the primary breeding target of wheat breeders. We performed the genome-wide association study (GWAS) on 168 elite winter wheat lines from an ongoing breeding program to identify the main determinants of grain yield. Sequencing of Diversity Array Technology fragments (DArTseq) resulted in 19,350 single-nucleotide polymorphism (SNP) and presence-absence variation (PAV) markers. We identified 15 main genomic regions located in ten wheat chromosomes (1B, 2B, 2D, 3A, 3D, 5A, 5B, 6A, 6B, and 7B) that explained from 7.9 to 20.3% of the variation in grain yield and 13.3% of the yield stability. Loci identified in the reduced genepool are important for wheat improvement using marker-assisted selection. We found marker-trait associations between three genes involved in starch biosynthesis and grain yield. Two starch synthase genes (TraesCS2B03G1238800 and TraesCS2D03G1048800) and a sucrose synthase gene (TraesCS3D03G0024300) were found in regions of QGy.rut-2B.2, QGy.rut-2D.1, and QGy.rut-3D, respectively. These loci and other significantly associated SNP markers found in this study can be used for pyramiding favorable alleles in high-yielding varieties or to improve the accuracy of prediction in genomic selection.

Identification and validation of new quantitative trait loci for spike-related traits in two RIL populations

Wheat (Triticum aestivum L.) is one of the most important cereal crops for ensuring food security worldwide. Identification of major quantitative trait loci (QTL) for spike-related traits is important for improvement of yield potential in wheat breeding. In this study, by using the wheat 55K single nucleotide polymorphism (SNP) array and diversity array technology (DArT), two recombinant inbred line populations derived from crosses avocet/chilero and avocet/huites were used to map QTL for kernel number per spike (KNS), total spikelet number per spike (TSS), fertile spikelet number per spike (FSS), and spike compactness (SC). Forty-two QTLs were identified on chromosomes 2A (4), 2B (3), 3A (2), 3B (7), 5A (11), 6A (4), 6B, and 7A (10), explaining 3.13-21.80% of the phenotypic variances. Twelve QTLs were detected in multi-environments on chromosomes 2A, 3B (2), 5A (4), 6A (3), 6B, and 7A, while four QTL clusters were detected on chromosomes 3A, 3B, 5A, and 7A. Two stable and new QTL clusters, QKns/Tss/Fss/SC.haust-5A and QKns/Tss/Fss.haust-7A, were detected in the physical intervals of 547.49-590.46 Mb and 511.54-516.15 Mb, accounting for 7.53-14.78% and 7.01-20.66% of the phenotypic variances, respectively. High-confidence annotated genes for QKns/Tss/Fss/SC.haust-5A and QKns/Tss/Fss.haust-7A were more highly expressed in spike development. The results provide new QTL and molecular markers for marker-assisted breeding in wheat.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01401-4.

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.

Longer epidermal cells underlie a quantitative source of variation in wheat flag leaf size

The wheat flag leaf is the main contributor of photosynthetic assimilates to developing grains. Understanding how canopy architecture strategies affect source strength and yield will aid improved crop design. We used an eight-founder population to investigate the genetic architecture of flag leaf area, length, width and angle in European wheat. For the strongest genetic locus identified, we subsequently created a near-isogenic line (NIL) pair for more detailed investigation across seven test environments. Genetic control of traits investigated was highly polygenic, with colocalisation of replicated quantitative trait loci (QTL) for one or more traits identifying 24 loci. For QTL QFll.niab-5A.1 (FLL5A), development of a NIL pair found the FLL5A+ allele commonly conferred a c. 7% increase in flag and second leaf length and a more erect leaf angle, resulting in higher flag and/or second leaf area. Increased FLL5A-mediated flag leaf length was associated with: (1) longer pavement cells and (2) larger stomata at lower density, with a trend for decreased maximum stomatal conductance (G_smax ) per unit leaf area. For FLL5A, cell size rather than number predominantly determined leaf length. The observed trade-offs between leaf size and stomatal morphology highlight the need for future studies to consider these traits at the whole-leaf level.

Genome-wide association analysis of spike and kernel traits in the U.S. hard winter wheat

A better understanding of the genetic control of spike and kernel traits that have higher heritability can help in the development of high-yielding wheat varieties. Here, we identified the marker-trait associations (MTAs) for various spike- and kernel-related traits in winter wheat (Triticum aestivum L.) through genome-wide association studies (GWAS). An association mapping panel comprising 297 hard winter wheat accessions from the U.S. Great Plains was evaluated for eight spike- and kernel-related traits in three different environments. A GWAS using 15,590 single-nucleotide polymorphisms (SNPs) identified a total of 53 MTAs for seven spike- and kernel-related traits, where the highest number of MTAs were identified for spike length (16) followed by the number of spikelets per spike (15) and spikelet density (11). Out of 53 MTAs, 14 were considered to represent stable quantitative trait loci (QTL) as they were identified in multiple environments. Five multi-trait MTAs were identified for various traits including the number of spikelets per spike (NSPS), spikelet density (SD), kernel width (KW), and kernel area (KA) that could facilitate the pyramiding of yield-contributing traits. Further, a significant additive effect of accumulated favorable alleles on the phenotype of four spike-related traits suggested that breeding lines and cultivars with a higher number of favorable alleles could be a valuable resource for breeders to improve yield-related traits. This study improves the understanding of the genetic basis of yield-related traits in hard winter wheat and provides reliable molecular markers that will facilitate marker-assisted selection (MAS) in wheat breeding programs.

Genetic dissection of quantitative trait loci for flag leaf size in bread wheat (Triticum aestivum L.)

Flag leaf size is a crucial trait influencing plant architecture and yield potential in wheat. A recombinant inbred line (RIL) population derived from the cross of W7268 and Chuanyu 12 was employed to identify quantitative trait loci (QTL) controlling flag leaf length (FLL), flag leaf width (FLW), and flag leaf area (FLA) in six environments and the best linear unbiased estimator (BLUE) datasets. Using a 55 K SNP-based genetic map, six major and stable QTL were detected with 6.33-53.12% of explained phenotypic variation. Except for QFlw.cib-4B.3, the other five major QTL were co-located within two intervals on chromosomes 2B and 2D, namely QFll/Fla.cib-2B and QFll/Flw/Fla.cib-2D, respectively. Their interactions and effects on the corresponding traits and yield-related traits were also assessed based on flanking markers. QFll/Fla.cib-2B showed pleiotropic effects on spikelet number per spike (SNS). QFlw.cib-4B.3 and QFll/Flw/Fla.cib-2D had effects on grain number per spike (GNS) and thousand-grain weight (TGW). Comparison analysis suggested that QFll/Fla.cib-2B was likely a new locus. Two candidate genes, TraesCS2B03G0222800 and TraesCS2B03G0230000, associated with leaf development within the interval of QFll/Fla.cib-2B were identified based on expression-pattern analysis, gene annotation, ortholog analysis, and sequence variation. The major QTL and markers reported here provide valuable information for understanding the genetic mechanism underlying flag leaf size as well as breeding utilization in wheat.

Genome-wide meta-analysis of QTL for morphological related traits of flag leaf in bread wheat

Flag leaf is an important organ for photosynthesis of wheat plants, and a key factor affecting wheat yield. In this study, quantitative trait loci (QTL) for flag leaf morphological traits in wheat reported since 2010 were collected to investigate the genetic mechanism of these traits. Integration of 304 QTLs from various mapping populations into a high-density consensus map composed of various types of molecular markers as well as QTL meta-analysis discovered 55 meta-QTLs (MQTL) controlling morphological traits of flag leaves, of which 10 MQTLs were confirmed by GWAS. Four high-confidence MQTLs (MQTL-1, MQTL-11, MQTL-13, and MQTL-52) were screened out from 55 MQTLs, with an average confidence interval of 0.82 cM and a physical distance of 9.4 Mb, according to the definition of hcMQTL. Ten wheat orthologs from rice (7) and Arabidopsis (3) that regulated leaf angle, development and morphogenesis traits were identified in the hcMQTL region using comparative genomics, and were speculated to be potential candidate genes regulating flag leaf morphological traits in wheat. The results from this study provides valuable information for fine mapping and molecular markers assisted selection to improve morphological characters in wheat flag leaf.

Genome-wide meta-QTL analyses provide novel insight into disease resistance repertoires in common bean

BACKGROUND

Common bean (Phaseolus vulgaris) is considered a staple food in a number of developing countries. Several diseases attack the crop leading to substantial economic losses around the globe. However, the crop has rarely been investigated for multiple disease resistance traits using Meta-analysis approach.

RESULTS AND CONCLUSIONS

In this study, in order to identify the most reliable and stable quantitative trait loci (QTL) conveying disease resistance in common bean, we carried out a meta-QTL (MQTL) analysis using 152 QTLs belonging to 44 populations reported in 33 publications within the past 20 years. These QTLs were decreased into nine MQTLs and the average of confidence interval (CI) was reduced by 2.64 folds with an average of 5.12 cM in MQTLs. Uneven distribution of MQTLs across common bean genome was noted where sub-telomeric regions carry most of the corresponding genes and MQTLs. One MQTL was identified to be specifically associated with resistance to halo blight disease caused by the bacterial pathogen Pseudomonas savastanoi pv. phaseolicola, while three and one MQTLs were specifically associated with resistance to white mold and anthracnose caused by the fungal pathogens Sclerotinia sclerotiorum and Colletotrichum lindemuthianum, respectively. Furthermore, two MQTLs were detected governing resistance to halo blight and anthracnose, while two MQTLs were detected for resistance against anthracnose and white mold, suggesting putative genes governing resistance against these diseases at a shared locus. Comparative genomics and synteny analyses provide a valuable strategy to identify a number of well‑known functionally described genes as well as numerous putative novels candidate genes in common bean, Arabidopsis and soybean genomes.

Genome-wide association study for grain yield and component traits in bread wheat (Triticum aestivum L.)

Genomic regions governing days to heading (DH), grain filling duration (GFD), grain number per spike (GNPS), grain weight per spike (GWPS), plant height (PH), and grain yield (GY) were investigated in a set of 280 diverse bread wheat genotypes. The genome-wide association studies (GWAS) panel was genotyped using a 35K Axiom Array and phenotyped in five environments. The GWAS analysis showed a total of 27 Bonferroni-corrected marker-trait associations (MTAs) on 15 chromosomes representing all three wheat subgenomes. The GFD showed the highest MTAs (8), followed by GWPS (7), GY (4), GNPS (3), PH (3), and DH (2). Furthermore, 20 MTAs were identified with more than 10% phenotypic variation. A total of five stable MTAs (AX-95024590, AX-94425015, AX-95210025 AX-94539354, and AX-94978133) were identified in more than one environment and associated with the expression of DH, GFD, GNPS, and GY. Similarly, two novel pleiotropic genomic regions with associated MTAs i.e. AX-94978133 (4D) and AX-94539354 (6A) harboring co-localized QTLs governing two or more traits were also identified. In silico analysis revealed that the SNPs were located on important putative candidate genes such as F-box-like domain superfamily, Lateral organ boundaries, LOB, Thioredoxin-like superfamily Glutathione S-transferase, RNA-binding domain superfamily, UDP-glycosyltransferase family, Serine/threonine-protein kinase, Expansin, Patatin, Exocyst complex component Exo70, DUF1618 domain, Protein kinase domain involved in the regulation of grain size, grain number, growth and development, grain filling duration, and abiotic stress tolerance. The identified novel MTAs will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection (MAS).

Capturing Wheat Phenotypes at the Genome Level

Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.

Fine mapping of QFlw-5B, a major QTL for flag leaf width in common wheat (Triticum aestivum L.)

A major stable QTL for flag leaf width was narrowed down to 2.5 Mb region containing two predicated putative candidate genes, and its effects on yield-related traits was characterized. Flag leaf width (FLW) is important to production in wheat. In a previous study, a major quantitative trait locus for FLW (QFlw-5B) was detected on chromosome 5B, within an interval of 6.5 cM flanked by the markers of XwPt-9103 and Xbarc142, using a mapping population of recombinant inbred lines derived from a cross between Kenong9204 (KN9204) and Jing411 (J411) (denoted as KJ-RILs). The aim of this study was to fine map QFlw-5B and characterize its genetic effects on yield-related traits. Multiple near-isogenic lines (NILs) were developed using one residual heterozygous line for QFlw-5B. Five recombinants for QFlw-5B were identified, and its location was narrowed to a 2.5 Mb region based on combined phenotypic and genotypic data analysis. This region contained 27 predicted genes, two of which were considered as the most likely candidate genes for QFlw-5B. The FLW of NIL-KN9204 was significantly higher than that of NIL-J411 across all the tested environments. Meanwhile, significant increases in plant height, grain width and 1000-grain weight were observed in NIL-KN9204 compared with that in NIL-J411. These results indicate that QFlw-5B has great potential for marker-assisted selection in wheat breeding programs designed to improve both plant architecture and yield. This study also provides a basis for the map-based cloning of QFlw-5B.

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

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

Supplementary Information

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