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

QTL Mapping of Yield-Related Traits in Tetraploid Wheat Based on Wheat55K SNP Array

To enhance the understanding of yield-related traits in tetraploid wheat, it is crucial to investigate and identify genes that govern superior yield characteristics. This study utilized the wheat55K single nucleotide polymorphism array to genotype a recombinant inbred line (RIL) population consisting of 120 lines developed through the crossbreeding of two tetraploid wheat varieties, Qin Hei-1 (QH-1) and Durum Wheat (DW). An investigation and analysis were conducted on 11 yield-related traits, including peduncle length (PL), neck length (NL), spike length (SL), flowering date (FD), heading date (HD), thousand-kernel weight (TKW), kernel area ratio (KAR), kernel circumference (KC), kernel length (KL), kernel width (KW), and kernel length-width ratio (KL-WR), over a period of three years in two locations, Yang Ling, Shaanxi, and Lin He, Inner Mongolia. The analysis identified nine stable loci among eight agronomic traits, named QSL.QD-1A.1, QNL.QD-4B.2, QPL.QD-4B.1, QFD.QD-2B, QHD.QD-2B.1, QHD.QD-4B, QKC.QD-4B.2, QKL-WR.QD-4B.6, and QKL.QD-4B.2. Among them, the additive effects of three QTLs, QSL.QD-1A.1, QNL.QD-4B.2, and QFD.QD-2B, were positive, indicating that the enhancing alleles at these loci were derived from the parent line QH-1. These three QTLs showed significant positive effects on the phenotypes of the population materials. Furthermore, potential functional genes were identified within the mapping intervals of QSL.QD-1A.1 and QNL.QD-4B.2, which regulate the development of spike length and neck length, respectively. These results provide potential QTLs and candidate genes, which broaden the genetic basis of agronomic traits related to yield, such as SL, NL, PL, and FD, and benefits for wheat breeding and improvement.

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

KEY MESSAGE

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

Fine mapping of a major QTL, qKl-1BL controlling kernel length in common wheat

KEY MESSAGE

A major stable QTL, qKl-1BL, for kernel length of wheat was narrowed down to a 2.04-Mb interval on chromosome 1BL; the candidate genes were predicated and the genetic effects on yield-related traits were characterized. As a key factor influencing kernel weight, wheat kernel shape is closely related to yield formation, and in turn affects both wheat processing quality and market value. Fine mapping of the major quantitative trait loci (QTL) for kernel shape could provide genetic resources and a theoretical basis for the genetic improvement of wheat yield-related traits. In this study, a major QTL for kernel length (KL) on 1BL, named qKl-1BL, was identified from the recombinant inbred lines (RIL) in multiple environments based on the genetic map and physical map, with 4.76-21.15% of the phenotypic variation explained. To fine map qKl-1BL, the map-based cloning strategy was used. By using developed InDel markers, the near-isogenic line (NIL) pairs and eight key recombinants were identified from a segregating population containing 3621 individuals derived from residual heterozygous lines (RHLs) self-crossing. In combination with phenotype identification, qKl-1BL was finely positioned into a 2.04-Mb interval, KN1B:698.15-700.19 Mb, with eight differentially expressed genes enriched at the key period of kernel elongation. Based on transcriptome analysis and functional annotation information, two candidate genes for qKl-1BL controlling kernel elongation were identified. Additionally, genetic effect analysis showed that the superior allele of qKl-1BL from Jing411 could increase KL, thousand kernel weight (TKW), and yield per plant (YPP) significantly, as well as kernel bulk density and stability time. Taken together, this study identified a QTL interval for controlling kernel length with two possible candidate genes, which provides an important basis for qKl-1BL cloning, functional analysis, and application in molecular breeding programs.

Quantitative Trait Loci Mapping Identified Candidate Genes Involved in Plant Height Regulation in Rice

Rice plant height is an agricultural trait closely related to biomass, lodging tolerance, and yield. Identifying quantitative trait loci (QTL) regions related to plant height regulation and developing strategies to screen potential candidate genes can improve agricultural traits in rice. In this study, a double haploid population (CNDH), derived by crossing 'Cheongcheong' and 'Nagdong' individuals, was used, and a genetic map was constructed with 222 single-sequence repeat markers. In the RM3482-RM212 region on chromosome 1, qPh1, qPh1-1, qPh1-3, qPh1-5, and qPh1-6 were identified for five consecutive years. The phenotypic variance explained ranged from 9.3% to 13.1%, and the LOD score ranged between 3.6 and 17.6. OsPHq1, a candidate gene related to plant height regulation, was screened in RM3482-RM212. OsPHq1 is an ortholog of gibberellin 20 oxidase 2, and its haplotype was distinguished by nine SNPs. Plants were divided into two groups based on their height, and tall and short plants were distinguished and clustered according to the expression level of OsPHq1. QTLs and candidate genes related to plant height regulation, and thus, biomass regulation, were screened and identified in this study, but the molecular mechanism of the regulation remains poorly known. The information obtained in this study will help develop molecular markers for marker-assisted selection and breeding through rice plant height control.

Unraveling the genetic basis of grain number-related traits in a wheat-Agropyron cristatum introgressed line through high-resolution linkage mapping

BACKGROUND

Grain number per spike (GNS) is a pivotal determinant of grain yield in wheat. Pubing 3228 (PB3228), a wheat-Agropyron cristatum germplasm, exhibits a notably higher GNS.

RESULTS

In this study, we developed a recombinant inbred line (RIL) population derived from PB3228/Gao8901 (PG-RIL) and constructed a high-density genetic map comprising 101,136 loci, spanning 4357.3 cM using the Wheat 660 K SNP array. The genetic map demonstrated high collinearity with the wheat assembly IWGSC RefSeq v1.0. Traits related to grain number and spikelet number per spike were evaluated in seven environments for quantitative trait locus (QTL) analysis. Five environmentally stable QTLs were detected in at least three environments. Among these, two major QTLs, QGns-4A.2 and QGns-1A.1, associated with GNS, exhibited positive alleles contributed by PB3228. Further, the conditional QTL analysis revealed a predominant contribution of PB3228 to the GNS QTLs, with both grain number per spikelet (GNSL) and spikelet number per spike (SNS) contributing to the overall GNS trait. Four kompetitive allele-specific PCR (KASP) markers that linked to QGns-4A.2 and QGns-1A.1 were developed and found to be effective in verifying the QTL effect within a diversity panel. Compared to previous studies, QGns-4A.2 exhibited stability across different trials, while QGns-1A.1 represents a novel QTL. The results from unconditional and conditional QTL analyses are valuable for dissecting the genetic contribution of the component traits to GNS at the individual QTL level and for understanding the genetic basis of the superior grain number character in PB3228. The KASP markers can be utilized in marker-assisted selection for enhancing GNS.

CONCLUSIONS

Five environmentally stable QTLs related to grain number and spikelet number per spike were identified. PB3228 contributed to the majority of the QTLs associated with GNS.

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

KEY MESSAGE

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

Identification of major QTLs for yield-related traits with improved genetic map in wheat

INTRODUCTION

Identification of stable major quantitative trait loci (QTLs) for yield-related traits is important for yield potential improvement in wheat breeding.

METHODS

In the present study, we genotyped a recombinant inbred line (RIL) population using the Wheat 660K SNP array and constructed a high-density genetic map. The genetic map showed high collinearity with the wheat genome assembly. Fourteen yield-related traits were evaluated in six environments for QTL analysis.

RESULTS AND DISCUSSION

A total of 12 environmentally stable QTLs were identified in at least three environments, explaining up to 34.7% of the phenotypic variation. Of these, QTkw-1B.2 for thousand kernel weight (TKW), QPh-2D.1 (QSl-2D.2/QScn-2D.1) for plant height (PH), spike length (SL) and spikelet compactness (SCN), QPh-4B.1 for PH, and QTss-7A.3 for total spikelet number per spike (TSS) were detected in at least five environments. A set of Kompetitive Allele Specific PCR (KASP) markers were converted based on the above QTLs and used to genotype a diversity panel comprising of 190 wheat accessions across four growing seasons. QPh-2D.1 (QSl-2D.2/QScn-2D.1), QPh-4B.1 and QTss-7A.3 were successfully validated. Compared with previous studies, QTkw-1B.2 and QPh-4B.1 should be novel QTLs. These results provided a solid foundation for further positional cloning and marker-assisted selection of the targeted QTLs in wheat breeding programs.

Fine mapping of reduced height locus RHT26 in common wheat

We fine mapped RHT26 for plant height in wheat, confirmed its genetic effects in a panel of wheat cultivars and predicted candidate genes. Development of wheat cultivars with appropriate plant height (PH) is an important goal in breeding. Utilization of semi-dwarfing genes Rht-B1b and Rht-D1b triggered wheat Green Resolution in the 1960s. Since these genes also bring unfavorable features, such as reduced coleoptile length and grain weight, it is necessary to identify alternative reduced height genes without yield penalty. Here we constructed a high-density genetic map of a recombinant inbred line population derived from the cross of Zhongmai175 and Lunxuan987 and detected a stable genetic locus for PH, designated RHT26, on chromosome arm 3DL in all of six environments, accounting for 6.8-14.0% of the phenotypic variances. RHT26 was delimited to an approximate 1.4 Mb physical interval (517.1-518.5 Mb) using secondary mapping populations derived from 22 heterozygous recombinant plants and 24 kompetitive allele-specific PCR markers. Eleven high-confidence genes were annotated in the physical interval according to the Chinese Spring reference genome, and four of them were predicted as candidates for RHT26 based on genome and transcriptome sequencing analyses. We also confirmed that RHT26 had significant effects on PH, but not grain yield in a panel of wheat cultivars; its dwarfing allele has been frequently used in wheat breeding. These findings lay a sound foundation for map-based cloning of RHT26 and provide a breeding-applicable tool for marker-assisted selection.

The selection and application of peduncle length QTL QPL_6D.1 in modern wheat (Triticum aestivum L.) breeding

QPL_6D.1b displayed an additive effect with Rht-B1b and Rht-D1b in reducing wheat plant height and peduncle length, which confers shorter peduncle length and more kernels per spike, and had been broadly selected by Chinese modern wheat cultivars. Peduncle length (PL), as the key component of wheat plant height (PH), plays critical role in determining wheat lodging resistance and wheat pathogen resistance; then, its breeding selection and genetic basis remain largely unclear. Here the PH and PL were investigated in 406 wheat accessions in eight environments. In this study, a PL preferentially QTL QPL_6D.1 was identified in six environments by GWAS, which explained 13.6-24.2% of wheat PL variations in natural population. The allele QPL_6D.1b displayed a significantly additive effect with Rht-B1b and Rht-D1b in controlling PH and PL and could freely combined with Rht-B1b and Rht-D1b in current wheat cultivars. Haplotypic analysis demonstrates the QPL_6D.1b has been selected by Chinese modern wheat cultivar and confers shorter PL and more kernels per spike, highlighting its potentials in wheat breeding.

A 'wiring diagram' for sink strength traits impacting wheat yield potential

Identifying traits for improving sink strength is a bottleneck to increasing wheat yield. The interacting processes determining sink strength and yield potential are reviewed and visualized in a set of 'wiring diagrams', covering critical phases of development (and summarizing known underlying genetics). Using this framework, we reviewed and assembled the main traits determining sink strength and identified research gaps and potential hypotheses to be tested for achieving gains in sink strength. In pre-anthesis, grain number could be increased through: (i) enhanced spike growth associated with optimized floret development and/or a reduction in specific stem-internode lengths and (ii) improved fruiting efficiency through an accelerated rate of floret development, improved partitioning between spikes, or optimized spike cytokinin levels. In post-anthesis, grain, sink strength could be augmented through manipulation of grain size potential via ovary size and/or endosperm cell division and expansion. Prospects for improving spike vascular architecture to support all rapidly growing florets, enabling the improved flow of assimilate, are also discussed. Finally, we considered the prospects for enhancing grain weight realization in relation to genetic variation in stay-green traits as well as stem carbohydrate remobilization. The wiring diagrams provide a potential workspace for breeders and crop scientists to achieve yield gains in wheat and other field crops.

Identification and validation of plant height, spike length and spike compactness loci in common wheat (Triticum aestivum L.)

BACKGROUND

Plant height (PH), spike length (SL) and spike compactness (SCN) are important agronomic traits in wheat due to their strong correlations with lodging and yield. Thus, dissection of their genetic basis is essential for the improvement of plant architecture and yield potential in wheat breeding. The objective of this study was to map quantitative trait loci (QTL) for PH, SL and SCN in a recombinant inbred line (RIL) population derived from the cross 'PuBing3228 × Gao8901' (PG-RIL) and to evaluate the potential values of these QTL to improve yield.

RESULTS

In the current study, Five, six and ten stable QTL for PH, SL, and SCN, respectively, were identified in at least two individual environments. Five major QTL QPh.cas-5A.3, QPh.cas-6A, QSl.cas-6B.2, QScn.cas-2B.2 and QScn.cas-6B explained 5.58-25.68% of the phenotypic variation. Notably, two, three and three novel stable QTL for PH, SL and SCN were identified in this study, which could provide further insights into the genetic factors that shape PH and spike morphology in wheat. Conditional QTL analysis revealed that QTL for SCN were mainly affected by SL. Moreover, a Kompetitive Allele Specific PCR (KASP) marker tightly linked to stable major QTL QPh.cas-5A.3 was developed and verified using the PG-RIL population and a natural population.

CONCLUSIONS

Twenty-one stable QTL related to PH, SL, and SCN were identified. These stable QTL and the user-friendly marker KASP8750 will facilitate future studies involving positional cloning and marker-assisted selection in breeding.

A major quantitative trait locus for wheat total root length associated with precipitation distribution

Optimizing root system architecture (RSA) allows crops to better capture water and nutrients and adapt to harsh environment. Parental reproductive environment (PRE) has been reported to significantly affect growth and development throughout the life cycle of the next generation. In this study, 10 RSA-related traits were evaluated in seedling stage from five independent hydroponic tests using seeds harvested from five different PREs. Based on the Wheat55K SNP array-based genetic map, quantitative trait loci (QTL) for these traits were detected in a recombinant inbred line population. Twenty-eight putative QTL for RSA-related traits were detected, covering thirteen chromosomal regions. A major QTL, QTrl.sicau-2SY-4D for total root length (TRL), which was likely independent of PREs, explained 15.81-38.48% of phenotypic variations and was located at 14.96-19.59 Mb on chromosome arm 4DS. Interestingly, it showed pleiotropic effects on TRL, root area, root volume, root forks, root dry weight, and shoot dry weight. The functional marker KASP-Rht-D1 for Rht-D1 was used to genotype 2SY population and remapping QTL for TRL showed that QTrl.sicau-2SY-4D was not linked to Rht-D1. The kompetitive allele-specific PCR (KASP) marker, KASP-AX-110527441 linked to this major QTL, was developed and used to successfully validate its effect in three different genetic populations. Further analysis suggested that the positive allele at QTrl.sicau-2SY-4D was mainly utilized in wheat breeding of northwest China where precipitation was significantly lower, indicating that wheat requires longer TRL to capture water and nutrients in arid or semi-arid regions due to deficient precipitation. Additionally, four genes (TraesCS4D03G0059800, TraesCS4D03G0057800, TraesCS4D03G0064000, and TraesCS4D03G0064400) possibly related to root development were predicted in physical interval of QTrl.sicau-2SY-4D. Taken together, these results enrich our understanding on the genetic basis of RSA and provide a potentially valuable TRL QTL for wheat breeding.

Rhizobial-Host Interactions and Symbiotic Nitrogen Fixation in Legume Crops Toward Agriculture Sustainability

Symbiotic nitrogen fixation (SNF) process makes legume crops self-sufficient in nitrogen (N) in sharp contrast to cereal crops that require an external input by N-fertilizers. Since the latter process in cereal crops results in a huge quantity of greenhouse gas emission, the legume production systems are considered efficient and important for sustainable agriculture and climate preservation. Despite benefits of SNF, and the fact that chemical N-fertilizers cause N-pollution of the ecosystems, the focus on improving SNF efficiency in legumes did not become a breeder’s priority. The size and stability of heritable effects under different environment conditions weigh significantly on any trait useful in breeding strategies. Here we review the challenges and progress made toward decoding the heritable components of SNF, which is considerably more complex than other crop allelic traits since the process involves genetic elements of both the host and the symbiotic rhizobial species. SNF-efficient rhizobial species designed based on the genetics of the host and its symbiotic partner face the test of a unique microbiome for its success and productivity. The progress made thus far in commercial legume crops with relevance to the dynamics of host–rhizobia interaction, environmental impact on rhizobial performance challenges, and what collectively determines the SNF efficiency under field conditions are also reviewed here.

Utilization of a Wheat55K SNP array-derived high-density genetic map for high-resolution mapping of quantitative trait loci for important kernel-related traits in common wheat

This study mapped QTLs associated with kernel-related traits by high-density genetic map. Five new major and stable QTLs for KL, KDR, SN, and KWPS were mapped in multiple environments. In the present study, a recombinant inbred line population including 371 lines derived from the cross of Chuannong18 and T1208 was genotyped using the Wheat55K single nucleotide polymorphism array. A novel high-density genetic map consisting of 11,583 markers spanning 4192.62 cM and distributed across 21 wheat chromosomes was constructed. QTLs for important kernel-related traits were mapped in multiple environments. A total of 96 and 151 QTLs were mapped by using the ICIM method and the MET method, respectively. And a total of 114 digenic epistatic QTLs were also detected across 21 chromosomes, and the epistatic effects of each trait were analyzed. BLAST analysis showed that 23 QTLs for different kernel-related traits were first time mapped and five of them were major and stable QTLs for kernel diameter ratio (121.34-126.83 cM on 4BS), spike number per square meter (71.32-73.84 cM on 2DS), kernel weight per spike (71.32-75.26 cM on 2DS), and kernel length (16.78-31.64 cM on 6A and 51.63-58.40 cM on 3D), respectively. Fifteen QTL clusters that contained 58 QTLs were also detected, and all most stable QTLs were contained in these QTL clusters. Significant correlations between different traits were detected and discussed. These results lay the foundation for fine mapping and cloning of the gene(s) underlying the stable QTLs detected in this study.

Candidate Genes and Quantitative Trait Loci for Grain Yield and Seed Size in Durum Wheat

Grain yield (YLD) is affected by thousand kernel weight (TKW) which reflects the combination of grain length (GL), grain width (GW) and grain area (AREA). Grain weight is also influenced by heading time (HT) and plant height (PH). To detect candidate genes and quantitative trait loci (QTL) of yield components, a durum wheat recombinant inbred line (RIL) population was evaluated in three field trials. The RIL was genotyped with a 90K single nucleotide polymorphism (SNP) array and a high-density genetic linkage map with 5134 markers was obtained. A total of 30 QTL were detected including 23 QTL grouped in clusters on 1B, 2A, 3A, 4B and 6B chromosomes. A QTL cluster on 2A chromosome included a major QTL for HT co-located with QTL for YLD, TKW, GL, GW and AREA, respectively. The photoperiod sensitivity (Ppd-A1) gene was found in the physical position of this cluster. Serine carboxypeptidase, Big grain 1 and β-fructofuranosidase candidate genes were mapped in clusters containing QTL for seed size. This study showed that yield components and phenological traits had higher inheritances than grain yield, allowing an accurate QTL cluster detection. This was a requisite to physically map QTL on durum genome and to identify candidate genes affecting grain yield.

Genome-wide association study of yield and related traits in common wheat under salt-stress conditions

BACKGROUND

Soil salinization is a major threat to wheat production. It is essential to understand the genetic basis of salt tolerance for breeding and selecting new salt-tolerant cultivars that have the potential to increase wheat yield.

RESULT

In this study, a panel of 191 wheat accessions was subjected to genome wide association study (GWAS) to identify SNP markers linked with adult-stage characters. The population was genotyped by Wheat660K SNP array and eight phenotype traits were investigated under low and high salinity environments for three consecutive years. A total of 389 SNPs representing 11 QTLs were significantly associated with plant height, spike number, spike length, grain number, thousand kernels weight, yield and biological mass under different salt treatments, with the phenotypic explanation rate (R²) ranging from 9.14 to 50.45%. Of these, repetitive and pleiotropic loci on chromosomes 4A, 5A, 5B and 7A were significantly linked to yield and yield related traits such as thousand kernels weight, spike number, spike length, grain number and so on under low salinity conditions. Spike length-related loci were mainly located on chromosomes 1B, 3B, 5B and 7A under different salt treatments. Two loci on chromosome 4D and 5A were related with plant height in low and high salinity environment, respectively. Three salt-tolerant related loci were confirmed to be important in two bi-parental populations. Distribution of favorable haplotypes indicated that superior haplotypes of pleiotropic loci on group-5 chromosomes were strongly selected and had potential for increasing wheat salt tolerance. A total of 14 KASP markers were developed for nine loci associating with yield and related traits to improve the selection efficiency of wheat salt-tolerance breeding.

CONCLUSION

Utilizing a Wheat660K SNPs chip, QTLs for yield and its related traits were detected under salt treatment in a natural wheat population. Important salt-tolerant related loci were validated in RIL and DH populations. This study provided reliable molecular markers that could be crucial for marker-assisted selection in wheat salt tolerance breeding programs.

Mapping QTL for agronomic traits under two levels of salt stress in a new constructed RIL wheat population

QTL for 15 agronomic traits under two levels of salt stress in dry salinity field were mapped in a new constructed RIL population utilizing a Wheat55K SNP array. Furthermore, eight QTL were validated in a collected natural population. Soil salinity is one of the major abiotic stresses causing serious impact on crop growth, development and yield. As one of the three most important crops in the world, bread wheat (Triticum aestivum L.) is severely affected by salinity, too. In this study, an F₇ recombinant inbred line (RIL) population derived from a cross between high-yield wheat cultivar Zhongmai 175 and salt-tolerant cultivar Xiaoyan 60 was constructed. The adult stage performances of the RIL population and their parent lines under low and high levels of salt stress were evaluated for three consecutive growing seasons. Utilizing a Wheat55K SNP array, a high-density genetic linkage map spinning 3250.71 cM was constructed. QTL mapping showed that 90 stable QTL for 15 traits were detected, and they were distributed on all wheat chromosomes except 4D, 6B and 7D. These QTL individually explained 2.34-32.43% of the phenotypic variation with LOD values ranging from 2.68 to 47.15. It was found that four QTL clusters were located on chromosomes 2D, 3D, 4B and 6A, respectively. Notably, eight QTL from the QTL clusters were validated in a collected natural population. Among them, QPh-4B was deduced to be an allele of Rht-B1. In addition, three kompetitive allele-specific PCR (KASP) markers derived from SNPs were successfully designed for three QTL clusters. This study provides an important base for salt-tolerant QTL (gene) cloning in wheat, and the markers, especially the KASP markers, will be useful for marker-assisted selection in salt-tolerant wheat breeding.

Characterization of near-isogenic lines confirmed QTL and revealed candidate genes for plant height and yield-related traits in common wheat

Plant height (PH) is closely associated with yield-related traits and environmental adaptation. Seven pairs of near-isogenic lines (NILs) targeting four QTL on 3AL, 4BL, 4AS, and 7AL wheat chromosome arms were assessed for PH and four yield-related traits including yield per plant (Y/P), grain number per spike (G/S), thousand kernel weight (TKW), and biomass per plant (B/P). Significant differences were observed in the NIL pairs for the measured traits. NIL pairs targeting the 3AL QTL differed significantly in PH, G/S, and TKW; NILs targeting the 4BL QTL differed significantly in PH, Y/P, and B/P; NIL pairs targeting the 4AS QTL differed significantly in all the traits; and NIL pairs targeting the 7AL QTL differed significantly in PH. A 90 K SNP genotyping assay of the NILs detected nineteen SNPs associated with fourteen functional genes. Among them, eight candidate genes are related to Rht proteins, four genes are related to hormone pathways and two genes are related to carbohydrate synthesis and transport. By searching the interval marker physical positions, it was found that the four targeted QTL in this study overlapped with eight previously reported QTL for PH, TKW, biomass, and yield. Correlation analysis revealed that PH significantly and positively correlated with B/P and G/S. The SNP and candidate gene information is potentially useful for marker-assisted selection in breeding programs, and the four targeted QTL are proved to be critical genomic regions controlling the investigated agronomic traits, which can be further fine mapped to identify the underlying genes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-020-01196-8.

A novel, validated, and plant height-independent QTL for spike extension length is associated with yield-related traits in wheat

A novel, stably expressed, and plant height-independent QTL for spike extension length on 5AS was identified and validated in different populations using a newly developed and tightly linked KASP marker. As an important component of plant height (PH), spike extension length (SEL) plays a significant role in formation of an ideotype in wheat. Despite the fact that numerous loci for SEL in wheat have been reported, our knowledge on PH-independent loci remains to be limited. In this study, two recombinant inbred line (RIL) populations genotyped using the Wheat55K SNP were used to detect quantitative trait loci (QTL) controlling SEL across six environments. A total of 30 QTL for SEL were detected in these two RIL populations, and four of them, i.e., QSEL.sicau-2CN-4D, QSEL.sicau-2SY-4B.2, QSEL.sicau-2SY-4D.1, and QSEL.sicau-2CN-5A, were stably expressed. Genetic and conditional QTL analysis showed that the first three were significantly associated with PH, while the last one, QSEL.sicau-2CN-5A, is independent of PH. Comparison of genetic and physical maps suggested that only QSEL.sicau-2CN-5A located on chromosome arm 5AS is likely a novel QTL. A Kompetitive Allele-Specific PCR (KASP) marker, KASP-AX-110413733, tightly linked to this novel QTL was developed to successfully confirm its effect in three different genetic populations. Further, in the interval where QSEL.sicau-2CN-5A was located on 'Chinese Spring' wheat reference genome, three promising genes mainly expressed in wheat stem were predicated and they all encode the cytochrome P450 that was demonstrated to be closely associated with SEL elongation in rice. In addition, significant correlations between SEL and PH, spikelet number per spike, and thousand-grain weight were also detected. Altogether, our results broaden our understanding on genetic basis of SEL and will be useful for marker-based selection of lines with different SELs and fine mapping the novel and PH-independent QTL QSEL.sicau-2CN-5A.

Identification and validation of quantitative trait loci for kernel traits in common wheat (Triticum aestivum L.)

BACKGROUND

Kernel weight and morphology are important traits affecting cereal yields and quality. Dissecting the genetic basis of thousand kernel weight (TKW) and its related traits is an effective method to improve wheat yield.

RESULTS

In this study, we performed quantitative trait loci (QTL) analysis using recombinant inbred lines derived from the cross 'PuBing3228 × Gao8901' (PG-RIL) to dissect the genetic basis of kernel traits. A total of 17 stable QTLs related to kernel traits were identified, notably, two stable QTLs QTkw.cas-1A.2 and QTkw.cas-4A explained the largest portion of the phenotypic variance for TKW and kernel length (KL), and the other two stable QTLs QTkw.cas-6A.1 and QTkw.cas-7D.2 contributed more effects on kernel width (KW). Conditional QTL analysis revealed that the stable QTLs for TKW were mainly affected by KW. The QTLs QTkw.cas-7D.2 and QKw.cas-7D.1 associated with TKW and KW were delimited to the physical interval of approximately 3.82 Mb harboring 47 candidate genes. Among them, the candidate gene TaFT-D1 had a 1 bp insertions/deletion (InDel) within the third exon, which might be the reason for diversity in TKW and KW between the two parents. A Kompetitive Allele-Specific PCR (KASP) marker of TaFT-D1 allele was developed and verified by PG-RIL and a natural population consisted of 141 cultivar/lines. It was found that the favorable TaFT-D1 (G)-allele has been positively selected during Chinese wheat breeding. Thus, these results can be used for further positional cloning and marker-assisted selection in wheat breeding programs.

CONCLUSIONS

Seventeen stable QTLs related to kernel traits were identified. The stable QTLs for thousand kernel weight were mainly affected by kernel width. TaFT-D1 could be the candidate gene for QTLs QTkw.cas-7D.2 and QKw.cas-7D.1.

Metabolomics analysis and metabolite-agronomic trait associations using kernels of wheat (Triticum aestivum) recombinant inbred lines

Plants produce numerous metabolites that are important for their development and growth. However, the genetic architecture of the wheat metabolome has not been well studied. Here, utilizing a high-density genetic map, we conducted a comprehensive metabolome study via widely targeted LC-MS/MS to analyze the wheat kernel metabolism. We further combined agronomic traits and dissected the genetic relationship between metabolites and agronomic traits. In total, 1260 metabolic features were detected. Using linkage analysis, 1005 metabolic quantitative trait loci (mQTLs) were found distributed unevenly across the genome. Twenty-four candidate genes were found to modulate the levels of different metabolites, of which two were functionally annotated by in vitro analysis to be involved in the synthesis and modification of flavonoids. Combining the correlation analysis of metabolite-agronomic traits with the co-localization of methylation quantitative trait locus (mQTL) and phenotypic QTL (pQTL), genetic relationships between the metabolites and agronomic traits were uncovered. For example, a candidate was identified using correlation and co-localization analysis that may manage auxin accumulation, thereby affecting number of grains per spike (NGPS). Furthermore, metabolomics data were used to predict the performance of wheat agronomic traits, with metabolites being found that provide strong predictive power for NGPS and plant height. This study used metabolomics and association analysis to better understand the genetic basis of the wheat metabolism which will ultimately assist in wheat breeding.

Functional QTL mapping and genomic prediction of canopy height in wheat measured using a robotic field phenotyping platform

Genetic studies increasingly rely on high-throughput phenotyping, but the resulting longitudinal data pose analytical challenges. We used canopy height data from an automated field phenotyping platform to compare several approaches to scanning for quantitative trait loci (QTLs) and performing genomic prediction in a wheat recombinant inbred line mapping population based on up to 26 sampled time points (TPs). We detected four persistent QTLs (i.e. expressed for most of the growing season), with both empirical and simulation analyses demonstrating superior statistical power of detecting such QTLs through functional mapping approaches compared with conventional individual TP analyses. In contrast, even very simple individual TP approaches (e.g. interval mapping) had superior detection power for transient QTLs (i.e. expressed during very short periods). Using spline-smoothed phenotypic data resulted in improved genomic predictive abilities (5-8% higher than individual TP prediction), while the effect of including significant QTLs in prediction models was relatively minor (<1-4% improvement). Finally, although QTL detection power and predictive ability generally increased with the number of TPs analysed, gains beyond five or 10 TPs chosen based on phenological information had little practical significance. These results will inform the development of an integrated, semi-automated analytical pipeline, which will be more broadly applicable to similar data sets in wheat and other crops.

QTL mapping for yield-related traits in wheat based on four RIL populations

Eight environmentally stable QTL for grain yield-related traits were detected by four RIL populations, and two of them were validated by a natural wheat population containing 580 diverse varieties or lines. Yield and yield-related traits are important factors in wheat breeding. In this study, four RIL populations derived from the cross of one common parent Yanzhan 1 (a Chinese domesticated cultivar) and four donor parents including Hussar (a British domesticated cultivar) and three semi-wild wheat varieties in China were phenotyped for 11 yield-related traits in eight environments. An integrated genetic map containing 2009 single-nucleotide polymorphism (SNP) markers generated from a 90 K SNP array was constructed to conduct quantitative trait loci (QTL) analysis. A total of 161 QTL were identified, including ten QTL for grain yield per plant (GYP) and yield components, 49 QTL for spike-related traits, 43 QTL for flag leaf-related traits, 22 QTL for plant height (PH), and 37 QTL for heading date and flowering date. Eight environmentally stable QTL were validated in individual RIL population where the target QTL was notably detected, and six of them had a significant effect on GYP. Furthermore, Two QTL, QSPS-2A.4 and QSL-4A.1, were also validated in a natural wheat population containing 580 diverse varieties or lines, which provided valuable resources for further fine mapping and genetic improvement in yield in wheat.

Amand P, Le HQ, Su Z, Bai G. Multiplex restriction amplicon sequencing: a novel next-generation sequencing-based marker platform for high-throughput genotyping

To enable rapid selection of traits in marker-assisted breeding, markers must be technically simple, low-cost, high-throughput and randomly distributed in a genome. We developed such a technology, designated as Multiplex Restriction Amplicon Sequencing (MRASeq), which reduces genome complexity by polymerase chain reaction (PCR) amplification of amplicons flanked by restriction sites. The first PCR primers contain restriction site sequences at 3'-ends, preceded by 6-10 bases of specific or degenerate nucleotide sequences and then by a unique M13-tail sequence which serves as a binding site for a second PCR that adds sequencing primers and barcodes to allow sample multiplexing for sequencing. The sequences of restriction sites and adjacent nucleotides can be altered to suit different species. Physical mapping of MRASeq SNPs from a biparental population of allohexaploid wheat (Triticum aestivum L.) showed a random distribution of SNPs across the genome. MRASeq generated thousands of SNPs from a wheat biparental population and natural populations of wheat and barley (Hordeum vulgare L.). This novel, next-generation sequencing-based genotyping platform can be used for linkage mapping to screen quantitative trait loci (QTL), background selection in breeding and many other genetics and breeding applications of various species.

QTL for spike-layer uniformity and their influence on yield-related traits in wheat

BACKGROUND

Common wheat (Triticum aestivum L.) is one of the most important food crops worldwide. Wheat spike-layer uniformity related traits (SLURTs) were complex traits that directly affect yield potential and appearance. In this study, quantitative trait locus (QTL) for five SLURTs among inter-tillers were first documented using a recombinant inbred line (RIL) mapping population derived from a cross between Kenong9204 and Jing411 (represented by KJ-RILs). Genetic relationships between SLURTs and yield were characterized in detail.

RESULTS

The trait phenotypic performances for the 188 KJ-RILs and their parents were evaluated in eight different environments. The genetic data included in a high-density genetic map derived from the Affymetrix 660 K SNP Array and the corresponding genotypes in each lines. Of 99 putative additive QTL 11 were stable across environments and 57 showed significant additive-by-environment interaction effects. These QTL individually explained 1.05-39.62% of the phenotypic variance, with log of odds (LOD) values ranging from 2.00 to 34.01. Genetic relationships between SLURTs and yield indicated that plants with slight uneven spike spatial distribution should be an ideotype for super high-yield in wheat.

CONCLUSIONS

The present study will provide assistance in understanding the genetic relationships between SLURTs and yield potential. The 11 stable QTL for SLURTs identified herein may facilitate breeding new wheat varieties with scientifically reasonable spike-layer distribution by marker assisted selection.

Dissection of Pleiotropic QTL Regions Controlling Wheat Spike Characteristics Under Different Nitrogen Treatments Using Traditional and Conditional QTL Mapping

Optimal spike characteristics are critical in improving the sink capacity and yield potential of wheat even in harsh environments. However, the genetic basis of their response to nitrogen deficiency is still unclear. In this study, quantitative trait loci (QTL) for six spike-related traits, including heading date (HD), spike length (SL), spikelet number (SN), spike compactness (SC), fertile spikelet number (FSN), and sterile spikelet number (SSN), were detected under two different nitrogen (N) supplies, based on a high-density genetic linkage map constructed by PCR markers, DArTs, and Affymetrix Wheat 660 K SNP chips. A total of 157 traditional QTLand 54 conditional loci were detected by inclusive composite interval mapping, among which three completely low N-stress induced QTL for SN and FSN (qSn-1A.1, qFsn-1B, and qFsn-7D) were found to maintain the desired spikelet fertility and kernel numbers even under N deficiency through pyramiding elite alleles. Twenty-eight stable QTL showing significant differencet in QTL detection model were found and seven genomic regions (R2D, R4A, R4B, R5A, R7A, R7B, and R7D) clustered by these stable QTL were highlighted. Among them, the effect of R4B on controlling spike characteristics might be contributed from Rht-B1. R7A harboring three major stable QTL (qSn-7A.2, qSc-7A, and qFsn-7A.3) might be one of the valuable candidate regions for further genetic improvement. In addition, the R7A was found to show syntenic with R7B, indicating the possibly exsting homoeologous candidate genes in both regions. The SNP markers involved with the above highlighted regions will eventually facilitate positional cloning or marker-assisted selection for the optimal spike characteristics under various N input conditions.

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

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

A 55 K SNP array-based genetic map and its utilization in QTL mapping for productive tiller number in common wheat

A high-density genetic map constructed with a wheat 55 K SNP array was highly consistent with the physical map of this species and it facilitated the identification of a novel major QTL for productive tiller number. Productive tiller number (PTN) plays a key role in wheat grain yield. In this study, a recombinant inbred line population with 199 lines derived from a cross between '20828' and 'Chuannong16' was used to construct a high-density genetic map using wheat 55 K single nucleotide polymorphism (SNP) array. The constructed genetic map contains 12,109 SNP markers spanning 3021.04 cM across the 21 wheat chromosomes. The orders of the genetic and physical positions of these markers are generally in agreement, and they also match well with those based on the 660 K SNP array from which the one used in this study was derived. The ratios of SNPs located in each of the wheat deletion bins were similar among the wheat 9 K, 55 K, 90 K, 660 K and 820 K SNP arrays. Based on the constructed maps, a novel major quantitative trait locus QPtn.sau-4B for PTN was detected across multi-environments in a 0.55 cM interval on 4B and it explained 17.23-45.46% of the phenotypic variance. Twenty common genes in the physical interval between the flanking markers were identified on chromosome 4B of 'Chinese Spring' and wild emmer. These results indicate that wheat 55 K SNP array could be an ideal tool in primary mapping of target genes and the identification of QPtn.sau-4B laid a foundation for the following fine mapping and cloning work.

QTL Mapping of Six Spike and Stem Traits in Hybrid Population of Agropyron Gaertn. in Multiple Environments

Most Agropyron Gaertn. species are excellent sources of forage. The derivative lines of wheat-Agropyron cristatum show elite agronomic traits, and some are valuable for wheat breeding. The species of Agropyron Gaertn. was mainly recognized by the spike morphology in traditional taxon. Six traits, including spike length (SL), ear stem length (ESL), the second internodes length (SIL), spikelet number per spike (SNS), floret number per spikelet (FNS), and grain number per spikelet (GNS), are vital to morphology studies and also influences the forage crop yield. To elucidate the genetic basis of spike and stem traits, a quantitative trait locus (QTL) analysis was conducted in a cross-pollinated (CP) hybrid population derived from a cross between two diverse parents, Agropyron mongolicum Keng Z2098 and A. cristatum (L.) Gaertn. Z1842, evaluated across three ecotopes (Langfang, Changli, and Guyuan of Hebei, China) over 3 years (from 2014 to 2016). Construction of a high-density linkage map was based on 1,023 single-nucleotide polymorphism (SNP) markers, covering 907.8 cM of the whole Agropyron genome. A total of 306 QTLs with single QTL in different environments explaining 0.07-33.21% of the phenotypic variation were detected for study traits. Seven major-effect QTLs were identified, including one for ESL on chromosome 3, one for SIL on chromosome 5, three for SL (two on chromosome 2 and one on chromosome 4), and two for SNS on chromosomes 3 and 7. Also, seven stable QTLs, including four for ESL, one for SL, one for GNS, and one for FNS, were mainly mapped on chromosomes 2, 3, 4, 5, and 7, respectively, elucidating 0.25-14.98% of the phenotypic variations. On the use of Agropyron CP hybrid population to identify QTL determining spike and stem traits for the first time, these QTLs for six traits would provide a theoretical reference for the molecular marker-assisted selection in the improvement of forage and cereal crop species.

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.

Genome-wide association mapping in bread wheat subjected to independent and combined high temperature and drought stress

Most investigations to date aiming to identify the genetic basis of the stress response of wheat (Triticum aestivum L.) have focused on the response to single stress agents such as high temperature or drought, even though in the natural situation, these stresses tend often to occur together. Here, a panel of 108 spring type bread wheat cultivars was phenotyped for 15 yield and yield related traits for two years (2014/15 and 2015/16) under non-stressed conditions, under high temperature stress, under drought and under a combined high temperature and drought regime. The mean loss in grain yield caused by all stress regimes was 51.33%. Analysis of variance (ANOVA) of yield trait showed significant differences among genotypes environments and their interactions (G×E). All the studied traits had higher heritability values which ranged from 0.35-0.94 under [C], 0.58-0.95 under [D], 0.62-0.93 under [H] and 0.60-0.95 under [HD]. GWAS was performed by using 9,646 informative SNP markers and based on these polymorphic SNPs population structure analysis divided whole germplasm into five major sub-populations. Mixed model association analysis detected 503 marker-trait associations (MTAs) at P ≤0.001 while 329 MTAs crossed FDR ≤ 0.05 for all traits with phenotypic variances (R2) ranged from 24.83% to 12.51%. Seven new pleiotropic SNPs on chromosome 7D and IAAV8258 (86.91cM) and wsnp_Ex_c7168_12311649 (57.93cM) on chromosome 5A were most stable association in present study. Furthermore, candidate genes Psy and Sr25 (TG0040) were also significant in present study, these genes were previously mapped on 7A and 7D. The region on 7D was assiociated with 7DL.7Ag translocation from Lophopyrum carring rust resistance Yr16 and many other genes. Similarly region on chromosome 7A which was associated with Psy gene was linked with grain yellow pigment content QTLs. Favourable alleles controlling grain yield were of vital importance and incorporation of these alleles after validation through marker assisted selection and fine mapping could be helpful in wheat yield improvement stress and non-stress conditions.

Utilization of a Wheat55K SNP Array for Mapping of Major QTL for Temporal Expression of the Tiller Number

Maximum tiller number and productive tiller number are important traits for wheat grain yield, but research involving the temporal expression of tiller number at different quantitative trait loci (QTL) levels is limited. In the present study, a population set of 371 recombined inbred lines derived from a cross between Chuan-Nong18 and T1208 was used to construct a high-density genetic map using a Wheat55K SNP Array and to perform dynamic QTL analysis of the tiller number at four growth stages. A high-density genetic map containing 11,583 SNP markers and 59 SSR markers that spanned 4,513.95 cM and was distributed across 21 wheat chromosomes was constructed. A total of 28 single environmental QTL were identified in the recombined inbred lines population, and among these, seven QTL were stable and used for multi-environmental and dynamic analysis. These QTL were mapped to chromosomes 2D, 4A, 4D, 5A, 5D, and 7D, respectively. Each QTL explained 1.63-21.22% of the observed phenotypic variation, with an additive effect from -20.51 to 11.59. Dynamic analysis showed that cqTN-2D.2 can be detected at four growth stages of tillering, explaining 4.92-17.16% of the observed phenotypic variations and spanning 13.71 Mb (AX-109283238-AX-110544009: 82189047-95895626) according to the physical location of the flanking markers. The effects of the stable QTL were validated in the recombined inbred lines population, and the beneficial alleles could be utilized in future marker-assisted selection. Several candidate genes for MTN and PTN were predicted. The results provide a better understanding of the QTL selectively expressing the control of tiller number and will facilitate future map-based cloning. 9.17% SNP markers showed best hits to the Chinese Spring contigs. It was indicated that Wheat55K Array was efficient and valid to construct a high-density wheat genetic map.

Stable QTLs for Plant Height on Chromosome A09 Identified From Two Mapping Populations in Peanut (Arachis hypogaea L.)

The peanut (Arachis hypogaea L.) is an important grain legume extensively cultivated worldwide, supplying edible oil and protein for human consumption. As in many other crops, plant height is a crucial factor in determining peanut architecture traits and has a unique effect on resistance to lodging and efficiency of mechanized harvesting as well as yield. Currently, the genetic basis underlying plant height remains unclear in peanut, which have hampered marker-assisted selection in breeding. In this study, we conducted a quantitative trait locus (QTL) analysis for peanut plant height by using two recombinant inbred line (RIL) populations including "Yuanza 9102 × Xuzhou 68-4 (YX)" and "Xuhua 13 × Zhonghua 6 (XZ)". In the YX population, 38 QTLs including 10 major QTLs from 9 chromosomes were detected in 4 environments, and 8 consensus QTLs integrated by meta-analysis expressed stably across multiple environments. In the XZ population, 3 major QTLs and seven minor QTLs from 6 chromosomes were detected across 3 environments. Generally, most major QTLs from the two populations were located on pseudomolecule chromosome 9 of Arachis duranesis (A09), indicating there would be key genes on A09 controlling plant height. Further analysis revealed that qPHA09.1a from the XZ population and one consensus QTL, cqPHA09.d from the YX population were co-localized in a reliable 3.4 Mb physical interval on A09, which harbored 161 genes including transcription factors and enzymes related to signaling transduction and cell wall formation. The major and stable QTLs identified in this study may be useful for further gene cloning and identification of molecular markers applicable for breeding.

Novel and major QTL for branch angle detected by using DH population from an exotic introgression in rapeseed (Brassica napus L.)

A high-density SNP map was constructed and several novel QTL for branch angle across six environments in Brassica napus were identified. Branch angle is a major determinant for the ideotype of a plant, while the mechanisms underlying this trait in Brassica napus remain elusive. Herein, we developed one doubled haploid population from a cross involving one Capsella bursa-pastoris derived B. napus intertribal introgression line with the compressed branches and wooden stems, and constructed a high-density SNP map covering the genetic distance of 2242.14 cM, with an average marker interval of 0.73 cM. After phenotypic measurements across six environments, the inclusive composite interval mapping algorithm was conducted to analyze the QTL associated with branch angle. In single-environment analysis, a total of 17 QTL were detected and mainly distributed on chromosomes A01, A03, A09 and C03. Of these, three major QTL, qBA.A03-2, qBA.C03-3 and qBA.C03-4 were steadily expressed, each explaining more than 10% of the phenotypic variation in at least two environments. Compared with other results on rapeseed branch angle, these major QTL were newly detected. In QTL by environment interactions (QEI) mapping, 10 QTL were identified, and the QTL average effect and QEI effect were estimated. Of these, 7 QTL were detected in both single-environment analysis and QEI mapping. Based on the physical positions of SNPs and the functional annotation of the Arabidopsis thaliana genome, 27 genes within the QTL regions were selected as candidate genes, including early auxin-responsive genes, small auxin-up RNA, auxin/indoleacetic acid and gretchenhagen-3. These results may pave the way for deciphering the genetic control of branch angle in B. napus.

Molecular mapping and genetic analysis of a QTL controlling spike formation rate and tiller number in wheat

Spike formation rate (SR), which is based on maximum tiller number per unit area and spike number per unit area, is an important yield-related trait in wheat. Increasing the spike formation rate reduces growth competition and wastage of photosynthate from ineffective tillers. Unfortunately, research studies involving quantitative trait locus (QTL) mapping for wheat spike formation rate are limited. In the present study, a set of 371 recombinant inbreed line (RIL) population, which were derived from 1BL/LRS wheat-rye translocation lines CN18 and T1208, was analysed by simple sequence repeat (SSR) markers. Genetic analysis showed that a stable and major QTL (QSR.sicau-4D) for spike formation rate was localized to chromosome 4D and explained 18.24% and 24.48% of the observed phenotypic variance in 2015 and 2016, respectively. This QTL was closely linked to SSR marker Xcfd23, and the genetic distance between the flank markers was 3.28cM. Furthermore, QSR.sicau-4D might be a novel pleiotropic QTL, which also controlled maximum tiller number per unit area (QMTN.sicau-4D) and tiller number during pre-winter per unit area (QTNW.sicau-4D). The marker Xcfd23 associated with SR may be utilized in marker-assisted selection in wheat breeding.

Characterization of Genetic Basis on Synergistic Interactions between Root Architecture and Biological Nitrogen Fixation in Soybean

Soybean [Glycine max (L.) Merr] is an important legume crop and its yield largely depends on root architecture (RA) and biological nitrogen fixation (BNF). However, the relationship between RA and BNF, and its genetics behind remain unclear. Here, two soybean genotypes contrasting in RA and their 175 F_9:11 recombinant inbred lines (RILs) were evaluated in field. The shallow-root parent, JD12, had better nodulation and higher yield than the deep-root parent, NF58. Strong correlations between shoot dry weight (SDW) and RA or BNF traits existed in the RILs, and the shallow-root group had more and heavier nodules, as well as higher SDW. After inoculating with rhizobia, roots became shallower and bigger, showing strong synergistic interactions between RA and BNF. In total, 70 QTLs were identified for the 21 tested traits. Among them, qBNF-RA-C2, qBNF-RA-O, and qBNF-RA-B1, were newly identified QTLs for BNF and/or RA traits in soybean, which co-located with the QTLs for SDW detected presently, and with the QTLs for yield identified previously. The results together suggest that there are synergistic interactions between RA and BNF, and the QTLs identified here could be used for breeding new soybean varieties with higher yields through optimization of RA traits and BNF capacity.