Genetic dissection of grain architecture-related traits in a winter wheat population

Abstract Background The future productivity of wheat (T. aestivum L.) as the most grown crop worldwide is of utmost importance for global food security. Thousand kernel weight (TKW) in wheat is closely associated with grain architecture-related traits, e.g. kernel length (KL), kernel width (KW), kernel area (KA), kernel diameter ratio (KDR), and factor form density (FFD). Discovering the genetic architecture of natural variation in these traits, identifying QTL and candidate genes are the main aims of this study. Therefore, grain architecture-related traits in 261 worldwide winter accessions over three field-year experiments were evaluated. Results Genome-wide association analysis using 90K SNP array in FarmCPU model revealed several interesting genomic regions including 17 significant SNPs passing false discovery rate threshold and strongly associated with the studied traits. Four of associated SNPs were physically located inside candidate genes within LD interval e.g. BobWhite_c5872_589 (602,710,399 bp) found to be inside TraesCS6A01G383800 (602,699,767–602,711,726 bp). Further analysis reveals the four novel candidate genes potentially involved in more than one grain architecture-related traits with a pleiotropic effects e.g. TraesCS6A01G383800 gene on 6A encoding oxidoreductase activity was associated with TKW and KA. The allelic variation at the associated SNPs showed significant differences betweeen the accessions carying the wild and mutated alleles e.g. accessions carying C allele of BobWhite_c5872_589, TraesCS6A01G383800 had significantly higher TKW than the accessions carying T allele. Interestingly, these genes were highly expressed in the grain-tissues, demonstrating their pivotal role in controlling the grain architecture. Conclusions These results are valuable for identifying regions associated with kernel weight and dimensions and potentially help breeders in improving kernel weight and architecture-related traits in order to increase wheat yield potential and end-use quality.

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Dissection of Genetic Basis Underpinning Kernel Weight-Related Traits in Common Wheat

Plants ◽

10.3390/plants10040713 ◽

2021 ◽

Vol 10 (4) ◽

pp. 713

Author(s):

Shunda Li ◽

Liang Wang ◽

Yaning Meng ◽

Yuanfeng Hao ◽

Hongxin Xu ◽

...

Keyword(s):

Recombinant Inbred Lines ◽

Wheat Yield ◽

Snp Array ◽

Kernel Weight ◽

Yield Potential ◽

Phenotypic Variance ◽

Genetic Dissection ◽

Single Nucleotide ◽

Grain Width ◽

Potential Improvement

Genetic dissection kernel weight-related traits is of great significance for improving wheat yield potential. As one of the three major yield components of wheat, thousand kernel weight (TKW) was mainly affected by grain length (GL) and grain width (GW). To uncover the key loci for these traits, we carried out a quantitative trait loci (QTL) analysis of an F6 recombinant inbred lines (RILs) population derived from a cross of Henong 5290 (small grain) and 06Dn23 (big grain) with a 50 K single nucleotide polymorphism (SNP) array. A total of 17 stable and big effect QTL, including 5 for TKW, 8 for GL and 4 for GW, were detected on the chromosomes 1B, 2A, 2B, 2D, 4B, 5A, 6A and 6D, respectively. Among these, there were two co-located loci for three traits that were mapped on the chromosome 4BS and 6AL. The QTL on 6AL was the most stable locus and explained 15.4–24.8%, 4.1–8.8% and 15.7–24.4% of TKW, GW and GL variance, respectively. In addition, two more major QTL of GL were located on chromosome arm 2BL and 2DL, accounting for 9.7–17.8% and 13.6–19.8% of phenotypic variance, respectively. In this study, we found one novel co-located QTL associated with GL and TKW in 2DL, QGl.haaf-2DL.2/QTkw.haaf-2DL.2, which could explain 13.6–19.8% and 9.8–10.7% phenotypic variance, respectively. Genetic regions and linked markers of these stable QTL will help to further refine mapping of the corresponding loci and marker-assisted selection (MAS) breeding for wheat grain yield potential improvement.

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Appraising the Genetic Architecture of Kernel Traits in Hexaploid Wheat Using GWAS

International Journal of Molecular Sciences ◽

10.3390/ijms21165649 ◽

2020 ◽

Vol 21 (16) ◽

pp. 5649

Author(s):

Ali Muhammad ◽

Weicheng Hu ◽

Zhaoyang Li ◽

Jianguo Li ◽

Guosheng Xie ◽

...

Keyword(s):

Genetic Architecture ◽

Genome Wide Association Study ◽

Snp Array ◽

Significant Snps ◽

Kernel Weight ◽

Snp Markers ◽

Kernel Length ◽

A Genome ◽

Genetic Mechanisms ◽

Kernel Traits

Kernel morphology is one of the major yield traits of wheat, the genetic architecture of which is always important in crop breeding. In this study, we performed a genome-wide association study (GWAS) to appraise the genetic architecture of the kernel traits of 319 wheat accessions using 22,905 single nucleotide polymorphism (SNP) markers from a wheat 90K SNP array. As a result, 111 and 104 significant SNPs for Kernel traits were detected using four multi-locus GWAS models (mrMLM, FASTmrMLM, FASTmrEMMA, and pLARmEB) and three single-locus models (FarmCPU, MLM, and MLMM), respectively. Among the 111 SNPs detected by the multi-locus models, 24 SNPs were simultaneously detected across multiple models, including seven for kernel length, six for kernel width, six for kernels per spike, and five for thousand kernel weight. Interestingly, the five most stable SNPs (RAC875_29540_391, Kukri_07961_503, tplb0034e07_1581, BS00074341_51, and BobWhite_049_3064) were simultaneously detected by at least three multi-locus models. Integrating these newly developed multi-locus GWAS models to unravel the genetic architecture of kernel traits, the mrMLM approach detected the maximum number of SNPs. Furthermore, a total of 41 putative candidate genes were predicted to likely be involved in the genetic architecture underlining kernel traits. These findings can facilitate a better understanding of the complex genetic mechanisms of kernel traits and may lead to the genetic improvement of grain yield in wheat.

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

Genes ◽

10.3390/genes12040604 ◽

2021 ◽

Vol 12 (4) ◽

pp. 604

Author(s):

Paolo Vitale ◽

Fabio Fania ◽

Salvatore Esposito ◽

Ivano Pecorella ◽

Nicola Pecchioni ◽

...

Keyword(s):

Candidate Genes ◽

Recombinant Inbred Lines ◽

Snp Array ◽

Heading Date ◽

Tiller Number ◽

Genetic Maps ◽

Yield Potential ◽

Adaptation To Climate Change ◽

Map Resolution ◽

Mapping Populations

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.

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Identification of quantitative trait loci for kernel traits in a wheat cultivar Chuannong16

BMC Genetics ◽

10.1186/s12863-019-0782-4 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 10

Author(s):

Jian Ma ◽

Han Zhang ◽

Shuiqin Li ◽

Yaya Zou ◽

Ting Li ◽

...

Keyword(s):

Genetic Map ◽

Quantitative Trait ◽

Agronomic Traits ◽

Snp Array ◽

Kernel Weight ◽

Phenotypic Variance ◽

Kernel Length ◽

Kasp Marker ◽

Kernel Traits ◽

Major Qtl

Abstract Background Kernel length (KL), kernel width (KW) and thousand-kernel weight (TKW) are key agronomic traits in wheat breeding. Chuannong16 (‘CN16’) is a commercial cultivar with significantly longer kernels than the line ‘20828’. To identify and characterize potential alleles from CN16 controlling KL, the previously developed recombinant inbred line (RIL) population derived from the cross ‘20828’ × ‘CN16’ and the genetic map constructed by the Wheat55K SNP array and SSR markers were used to perform quantitative trait locus/loci (QTL) analyses for kernel traits. Results A total of 11 putative QTL associated with kernel traits were identified and they were located on chromosomes 1A (2 QTL), 2B (2 QTL), 2D (3 QTL), 3D, 4A, 6A, and 7A, respectively. Among them, three major QTL, QKL.sicau-2D, QKW.sicau-2D and QTKW.sicau-2D, controlling KL, KW and TKW, respectively, were detected in three different environments. Respectively, they explained 10.88–18.85%, 17.21–21.49% and 10.01–23.20% of the phenotypic variance. Further, they were genetically mapped in the same interval on chromosome 2DS. A previously developed kompetitive allele-specific PCR (KASP) marker KASP-AX-94721936 was integrated in the genetic map and QTL re-mapping finally located the three major QTL in a 1- cM region flanked by AX-111096297 and KASP-AX-94721936. Another two co-located QTL intervals for KL and TKW were also identified. A few predicted genes involved in regulation of kernel growth and development were identified in the intervals of these identified QTL. Significant relationships between kernel traits and spikelet number per spike and anthesis date were detected and discussed. Conclusions Three major and stably expressed QTL associated with KL, KW, and TKW were identified. A KASP marker tightly linked to these three major QTL was integrated. These findings provide information for subsequent fine mapping and cloning the three co-localized major QTL for kernel traits.

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A 1BL/1RS translocation contributing to kernel length increase in three wheat recombinant inbred line populations

Czech Journal of Genetics and Plant Breeding ◽

10.17221/79/2019-cjgpb ◽

2020 ◽

Vol 56 (No. 2) ◽

pp. 43-51

Author(s):

Shui Qin Li ◽

Hua Ping Tang ◽

Han Zhang ◽

Yang Mu ◽

Xiu Jin Lan ◽

...

Keyword(s):

In Situ Hybridization ◽

Inbred Line ◽

Recombinant Inbred Line ◽

Recombinant Inbred ◽

Wheat Yield ◽

Kernel Weight ◽

Translocation Line ◽

Wheat Kernel ◽

Kernel Length

The 1BL/1RS wheat-rye translocation has been widely utilized in wheat genetic improvement and breeding programs. Our understanding on the effects of the 1BL/1RS translocation on wheat kernel size (e.g. length and width) is limited despite of numerous studies reporting about the effects on kernel weight. Here, we identified a wheat 1BL/1RS translocation line 88-1643 with higher kernel length (KL) using fluorescence in situ hybridization (FISH), genomic in situ hybridization (GISH) and molecular markers. To detect the possible role of the 1BL/1RS translocation in KL, kernel width (KW), and thousand-kernel weight (TKW), three recombinant inbred line (RIL) populations were constructed by crossing 88-1643 and three other wheat lines. As expected, the results showed that the values of KL in lines carrying 1RS were significantly higher than those carrying 1BS in three RIL populations at multiple environments, indicating that a major and stably expressed allele or gene responsible for increasing KL is most likely located on 1RS from 88-1643. Additionally, in one RIL population, the increased KL contributed significantly to the increase in TKW. Collectively, the 1BL/1RS translocation reported here is of interest to reveal molecular mechanism of the gene controlling KL and will be useful for improving wheat yield.

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Genetic Mapping and Validation of Loci for Kernel-Related Traits in Wheat (Triticum aestivum L.)

Frontiers in Plant Science ◽

10.3389/fpls.2021.667493 ◽

2021 ◽

Vol 12 ◽

Author(s):

Xiangru Qu ◽

Jiajun Liu ◽

Xinlin Xie ◽

Qiang Xu ◽

Huaping Tang ◽

...

Keyword(s):

Single Nucleotide Polymorphism Array ◽

Wheat Yield ◽

Kernel Weight ◽

Width Ratio ◽

Wheat Cultivars ◽

Major Qtls ◽

Kernel Length ◽

Huai River ◽

Chinese Wheat ◽

Kernel Traits

Kernel size (KS) and kernel weight play a key role in wheat yield. Phenotypic data from six environments and a Wheat55K single-nucleotide polymorphism array–based constructed genetic linkage map from a recombinant inbred line population derived from the cross between the wheat line 20828 and the line SY95-71 were used to identify quantitative trait locus (QTL) for kernel length (KL), kernel width (KW), kernel thickness (KT), thousand-kernel weight (TKW), kernel length–width ratio (LWR), KS, and factor form density (FFD). The results showed that 65 QTLs associated with kernel traits were detected, of which the major QTLs QKL.sicau-2SY-1B, QKW.sicau-2SY-6D, QKT.sicau-2SY-2D, and QTKW.sicau-2SY-2D, QLWR.sicau-2SY-6D, QKS.sicau-2SY-1B/2D/6D, and QFFD.sicau-2SY-2D controlling KL, KW, KT, TKW, LWR, KS, and FFD, and identified in multiple environments, respectively. They were located on chromosomes 1BL, 2DL, and 6DS and formed three QTL clusters. Comparison of genetic and physical interval suggested that only QKL.sicau-2SY-1B located on chromosome 1BL was likely a novel QTL. A Kompetitive Allele Specific Polymerase chain reaction (KASP) marker, KASP-AX-109379070, closely linked to this novel QTL was developed and used to successfully confirm its effect in two different genetic populations and three variety panels consisting of 272 Chinese wheat landraces, 300 Chinese wheat cultivars most from the Yellow and Huai River Valley wheat region, and 165 Sichuan wheat cultivars. The relationships between kernel traits and other agronomic traits were detected and discussed. A few predicted genes involved in regulation of kernel growth and development were identified in the intervals of these identified major QTL. Taken together, these stable and major QTLs provide valuable information for understanding the genetic composition of kernel yield and provide the basis for molecular marker–assisted breeding.

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Genetic Mapping by Integration of 55K SNP Array and KASP Markers Reveals Candidate Genes for Important Agronomic Traits in Hexaploid Wheat

Frontiers in Plant Science ◽

10.3389/fpls.2021.628478 ◽

2021 ◽

Vol 12 ◽

Author(s):

Hongchun Xiong ◽

Yuting Li ◽

Huijun Guo ◽

Yongdun Xie ◽

Linshu Zhao ◽

...

Keyword(s):

Candidate Genes ◽

Phenotypic Variation ◽

Agronomic Traits ◽

Recombinant Inbred Lines ◽

Wheat Yield ◽

Snp Array ◽

Heading Date ◽

Sequencing Data ◽

Gene Encoding ◽

Kasp Markers

Agronomic traits such as heading date (HD), plant height (PH), thousand grain weight (TGW), and spike length (SL) are important factors affecting wheat yield. In this study, we constructed a high-density genetic linkage map using the Wheat55K SNP Array to map quantitative trait loci (QTLs) for these traits in 207 recombinant inbred lines (RILs). A total of 37 QTLs were identified, including 9 QTLs for HD, 7 QTLs for PH, 12 QTLs for TGW, and 9 QTLs for SL, which explained 3.0–48.8% of the phenotypic variation. Kompetitive Allele Specific PCR (KASP) markers were developed based on sequencing data and used for validation of the stably detected QTLs on chromosomes 3A, 4B and 6A using 400 RILs. A QTL cluster on chromosome 4B for PH and TGW was delimited to a 0.8 Mb physical interval explaining 12.2–22.8% of the phenotypic variation. Gene annotations and analyses of SNP effects suggested that a gene encoding protein Photosynthesis Affected Mutant 68, which is essential for photosystem II assembly, is a candidate gene affecting PH and TGW. In addition, the QTL for HD on chromosome 3A was narrowed down to a 2.5 Mb interval, and a gene encoding an R3H domain-containing protein was speculated to be the causal gene influencing HD. The linked KASP markers developed in this study will be useful for marker-assisted selection in wheat breeding, and the candidate genes provide new insight into genetic study for those traits in wheat.

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Identification of quantitative trait loci for kernel traits in a wheat cultivar Chuannong16

10.21203/rs.2.14732/v1 ◽

2019 ◽

Author(s):

Jian Ma ◽

Han Zhang ◽

Shuiqin Li ◽

Yaya Zou ◽

Ting Li ◽

...

Keyword(s):

Genetic Map ◽

Quantitative Trait ◽

Agronomic Traits ◽

Snp Array ◽

Kernel Weight ◽

Phenotypic Variance ◽

Kernel Length ◽

Kasp Marker ◽

Kernel Traits ◽

Major Qtl

Abstract Background Kernel length (KL), kernel width (KW) and thousand-kernel weight (TKW) are key agronomic traits in wheat breeding. Chuannong16 (‘CN16’) is a commercial cultivar with significantly longer kernels that the line ‘20828’. To identify and characterize potential alleles from CN16 controlling KL, the previously developed recombinant inbred line (RIL) population derived from the cross ‘20828’ × ‘CN16’ and the genetic map constructed by the Wheat55K SNP array and SSR markers were used to perform quantitative trait locus/loci (QTL) analyses for kernel traits.Results A total of 11 putative QTL associated with kernel traits were identified and they were located on chromosomes 1A (2 QTL), 2B (2 QTL), 2D (3 QTL), 3D, 4A, 6A, and 7A, respectively. Among them, three major QTL, QKL.sicau-2D , QKW.sicau-2D and QTKW.sicau-2D , controlling KL, KW and TKW, respectively, were detected in three different environments. Respectively, they explained 10.88-18.85%, 17.21-21.49% and 10.01-23.20% of the phenotypic variance. Further, they were genetically mapped in the same interval on chromosome 2DS. A previously developed kompetitive allele-specific PCR (KASP) marker KASP-AX-94721936 was integrated in the genetic map and QTL re-mapping finally located the three major QTL in a 1- cM region flanked by AX-111096297 and KASP-AX-94721936 . Another two co-located QTL intervals for KL and TKW were also identified. A few predicated genes involved in regulation of kernel growth and development were identified in the intervals of these identified QTL. Significant relationships between kernel traits and spikelet number per spike and anthesis date were detected and discussed.Conclusions Three major and stably expressed QTL associated with KL, KW, and TKW were identified. A KASP marker tightly linked to these three major QTL was integrated. These findings provide information for subsequent fine mapping and cloning the three co-localized major QTL for kernel traits.

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Impact of Climate Change on Durum Wheat Yield

Agronomy ◽

10.3390/agronomy10060793 ◽

2020 ◽

Vol 10 (6) ◽

pp. 793 ◽

Cited By ~ 1

Author(s):

Erika Sabella ◽

Alessio Aprile ◽

Carmine Negro ◽

Francesca Nicolì ◽

Eliana Nutricati ◽

...

Keyword(s):

Climate Change ◽

Grain Yield ◽

Durum Wheat ◽

Wheat Yield ◽

Dry Weight ◽

High Temperature Stress ◽

Kernel Weight ◽

Climatic Conditions ◽

Yield Potential ◽

Plant Life Cycle

Climate change will inevitably affect agriculture. Simulations of the effects of climate change on the agronomic performance (plant height, biomass dry weight, number of spikes, grain weight, harvest index, and 1000-kernel weight) of nine durum wheat cultivars were performed to identify the genotypes that will have a greater yield potential over the next 50 years. Plants were grown in two Fitotron® CGR crop growth chambers: “room 2020” designed to reproduce the current climatic conditions (control) and “room 2070”, designed to simulate the expected climate for the year 2070 in the RCP8.5 scenario (800 ppm, elevated [CO2], and a temperature increase of 2.5 °C). The plant life cycle was clearly shorter in “room 2070” due to the physiological strategy of the plant to escape the high summer temperatures through early ripening of the kernels. Again, in “room 2070”, the modern cultivars Rusticano, San Carlo, and Simeto and the old cultivar Cappelli increased the grain yield. Surprisingly, Cappelli seemed to be particularly suitable for cultivation in an environment rich in atmospheric CO2 and under high temperature stress, since it produced a grain yield that was approximately three times higher than the other varieties.

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The indica nitrate reductase gene OsNR2 allele enhances rice yield potential and nitrogen use efficiency

Nature Communications ◽

10.1038/s41467-019-13110-8 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 19

Author(s):

Zhenyu Gao ◽

Yufeng Wang ◽

Guang Chen ◽

Anpeng Zhang ◽

Shenglong Yang ◽

...

Keyword(s):

Allelic Variation ◽

Yield Potential ◽

Nitrate Reductase Gene ◽

Gene Encoding ◽

Global Food Security ◽

Reductase Gene ◽

Rice Yields ◽

Use Efficiency ◽

Assimilation Capacity ◽

N Use

AbstractThe indica and japonica rice (Oryza sativa) subspecies differ in nitrate (NO3−) assimilation capacity and nitrogen (N) use efficiency (NUE). Here, we show that a major component of this difference is conferred by allelic variation at OsNR2, a gene encoding a NADH/NADPH-dependent NO3− reductase (NR). Selection-driven allelic divergence has resulted in variant indica and japonica OsNR2 alleles encoding structurally distinct OsNR2 proteins, with indica OsNR2 exhibiting greater NR activity. Indica OsNR2 also promotes NO3− uptake via feed-forward interaction with OsNRT1.1B, a gene encoding a NO3− uptake transporter. These properties enable indica OsNR2 to confer increased effective tiller number, grain yield and NUE on japonica rice, effects enhanced by interaction with an additionally introgressed indica OsNRT1.1B allele. In consequence, indica OsNR2 provides an important breeding resource for the sustainable increases in japonica rice yields necessary for future global food security.

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