Genetic mapping and identification of Rht8-B1 that regulates plant height in wheat

doi:10.21203/rs.3.rs-2585481/v1

Download PDF

Research Article

Genetic mapping and identification of Rht8-B1 that regulates plant height in wheat

https://doi.org/10.21203/rs.3.rs-2585481/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 22 Jun, 2023

Read the published version in BMC Plant Biology →

You are reading this latest preprint version

Background

Plant Height (PH) and Spike Compactness (SC) are important agronomic traits that affect yield improvement in wheat crops. The identification of the loci or genes responsible for these traits is thus of great importance for marker-assisted selection in wheat breeding.

Results

In this study, we used a RIL population with 139 lines derived from crossing between the mutant Rht8-2 and the local wheat variety NongDa5181 (ND5181) to construct a high-density genetic linkage map by applying the Wheat 40K Panel. We identified 7 stable QTLs for PH (3) and SC (4) under two environments using the RIL population, and found that Rht8-B1 is the causal gene of qPH2B.1 by further genetic mapping, gene cloning and gene editing analyses. Our results further showed that two natural variants from GC to TT in the coding region of Rht8-B1 resulted in an amino acid change from G (ND5181) to V (Rht8-2) at the 175th position, reducing PH by 3.6%~6.2% in the RIL population. Moreover, gene editing analysis suggested that the height of T₂ generation in Rht8-B1 edited plants was reduced by 5.6%, and that the impact of Rht8-B1 on PH was significantly lower than Rht8-D1. Additionally, distribution analysis of Rht8-B1 in various wheat resources suggested that Rht8-B1b have not been widely utilized in modern wheat breeding

Conclusions

The combination of Rht8-B1b with other favorable Rht genes might be an alternative approach for developing lodging-resistant crops. Our study brings important information for marker-assisted selection in wheat breeding.

Wheat

plant height

Rht8-B1

QTL mapping

spike compactness

The global human population is predicted to continually expand and reach 10 billion by 2050, significantly increasing the need for the safe and reliable production of food. The improvement of crops using advanced technologies provides an effective strategy to meet the demand of food production in the future [1]. Wheat represents one of the most important staple crops worldwide, whereby the identification of quantitative trait loci (QTLs) important for agronomical traits, such as plant height (PH), and spikelet compactness (SC), offers critical information to ensure food security [2].

Plant height is tightly connected with lodging resistance and thus influences grain yield. To date, a total of 25 reduced height genes (Rht1-Rht25) have been documented in wheat [3] and classified into GA sensitive or insensitive dwarf genes based on response to GA treatment. The GA insensitive Rht-B1b (Rht1) and Rht-D1b (Rht2) genes on chromosome 4B and 4D encoding truncated DELLA proteins significantly increased the harvest index and resulted in the well-known ‘Green Revolution’ [4, 5]; their allelic variations such as Rht-B1c (Rht3) [6], Rht-B1e (Rht11) [7], Rht-B1p (Rht17) [8], and Rht-D1c (Rht10) [9] have been identified. Moreover, several GA sensitive dwarf genes including Rht8 [10, 11], Rht12 [12], Rht13 [13], Rht18 [14], and Rht24 [15], have been cloned or intensively studied in wheat. Rht12 was located on chromosome 5A and mutations in GA2oxA13 gene produced tall overgrowth phenotype in the Rht12 background [12]. A missense mutation of NB-LRR gene in Rht13 caused height reduction [13]. The dominant Rht18 gene was identified by isolating and sequencing chromosome 6A of overgrowth mutants, and the increased expression of GA2oxA9 caused reduction of active GA content and thus resulted in dwarf phenotype [14]. Map-based cloning suggested that GA2oxA9 was the causal gene of Rht24, which affected GA homeostasis and led to plant height reduction [15].

Since the Rht8 gene does not influence coleoptile length, it well complements Rht-B1b and Rht-D1b weakness, and has been widely used in wheat breeding for several decades [16, 17]. Rht8 was mapped on the short arm of chromosome 2D; and the SSR marker Xgwm261 was regarded as a perfect diagnostic marker for Rht8 previously [17, 18]. Using two wheat mutants Rht8-2 and Rht8-3 for construction of segregation populations, the Rht8 gene was cloned recently, and it encodes an RNase H-like protein that affects bioactive GA content and changes plant height [10]. Via a wheat variety containing Rht8 gene for map-based cloning, similar results were simultaneously obtained [11], and the results also showed that the dwarf allele of Rht8 were positively selected during wheat breeding [10, 11].

Previous study suggested that Rht8 not only reduced plant height but also significantly decreased spike length and thus increased spike compactness by analysis of near isogenic lines [19] and transgenic plants [11]. The modification of spike length or spikelet compactness plays an important role in the improvement of yield potential in wheat [20, 21]; and identification of its associated QTLs are critical for wheat improvement during the breeding process. In hexaploid wheat, spike morphology is regulated by three major genes, including Q, C (Compactum) and S (Sphaerococcum) located on chromosomes 5A, 2D and 3D [22–24]. These genes exert pleiotropic effects on spikelet compactness and length, plant height and grain shape. To date, a high number of QTLs associated with spike morphology have been identified on nearly all wheat chromosomes [25]. Additionally, the VRN, Ppd and Eps genes are also involved in spike length and development, and affect spikelet compactness in wheat [26–28].

In the present study, we dissected the genetic control of PH and SC by QTL mapping using a recombinant inbred line (RIL) population derived from the crossing between the wheat variety ND5181 and the mutant line Rht8-2 and identified natural variation in the homoeologous gene Rht8 that contributes to PH change for qPH2B.1. The linked markers and genes influencing PH and SC identified here can be applied to molecular breeding and promote wheat production.

Plant materials and phenotypic evaluation

We established an F₇ RIL population comprising 139 lines derived from a cross between wheat cultivar NongDa5181 (ND5181) and the mutant Rht8-2 using a single seed descend method. The RIL population and their parents were planted in Zhongpuchang and Changping experimental fields in the Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, China, during 2021–2022 crop season. PH and SC were evaluated in this study. PH and SC were measured at maturity with 8 replicates for each line [29].

Genotyping and QTL mapping

Genomic DNA of the RIL population and parent lines were extracted and assessed as previously described [29]. The DNA samples were hybridized to the GenoBaits Wheat 40K Panel containing 202971 markers. Genotyping was performed at the MOLBREEDING (Shijiazhuang) Biotech Co., Ltd. (http://www.molbreeding.com). A total of 15258 homozygote SNPs were selected from ND5181 and Rht8-2 for follow-up analyses. The BIN and MAP functions of IciMapping 4.1 were used to remove redundant markers and construct the genetic map, respectively. The genetic linkage map included 1847 Bin markers across 21 chromosomes. The threshold of the logarithm of odds (LOD) score was set to 2.5, and the Kosambi map function was used to calculate the map distance from recombination frequencies. Composite interval mapping (ICIM) on IciMapping 4.1 was selected to identify QTLs for PH and SC. The mean values of the phenotypic traits in each line were used for QTL analysis. QTLs detected in two environments were regard as stable QTL.

KASP marker development and QTL validation

We developed the KASP assay based on the SNPs identified within or around ND5181 and Rht8-2 from the genotyping 40K SNP array. The online primer design pipeline PolyMarker (http://polymarker.tgac.ac.uk/) was used to design specific primers. The KASP assays were performed as previously described [29]. End-point fluorescence data were screened using the microplate reader FLUOstar Omega SNP (BMG LABTECH, Germany) and analyzed by the Klustering Caller Software. The KASP markers were tested with the two parents and then the developed polymorphic KASP markers were used for the identification of genotypes in the F₇ RIL population. QTL analysis was conducted using IciMapping 4.1.

Cloning and sequencing of Rht8-B1

Genome specific primers were designed to amplify the full length of Rht8-B1. The genomic DNA of ND5181 and Rht8-2 were extracted and amplified by PCR as follows: total volume 20 µL, including buffer 10 µL, dNTP 4 µL, genomic DNA 1 µL, forward primer 0.8 µL, reverse primer 0.8 µL, KOD FX 0.4 µL and ddH₂O 3 µL. The reaction conditions were 94 ℃ for 2 min, followed by 32 cycles of 98 ℃ for 10 s, annealing at 65 ℃ for 20 s, and 68 ℃ for 2 min, with a final extension of 68 ℃ for 5 min. The PCR products were sequenced at the Shanghai Sangon Biotech Co., Ltd. (https://www.sangon.com/).

Generating Rht8-B1 and Rht8-D1 mutants by gene editing

For CRISPR/Cas9-based gene editing, sgRNA target sequences and plant transformations were performed as previously described [10]. We sequenced T₂ plants and validated the mutations produced by CRISPR/Cas9-based gene editing. Single mutants of Rht8-B1 and Rht8-D1 were successfully selected, and the height of edited and WT plants recorded and compared.

Quantitative RT-PCR

Quantitative RT-PCR was performed according to our previous report [30]. Briefly, total RNA was isolated from the first internode below spike by using TRNzol-A⁺ Reagent (Tiangen Biotech), and was then purified using the RNA purification kit (Tiangen). The first-strand cDNA was synthesized using iScript cDNA synthesis kit (Bio-Rad), and the SsoFast EvaGreen Supermix Kit (Bio-Rad) was used for quantitative RT-PCR. This experiment was conducted on a CFX 96 Real-Time System (Bio-Rad) following the manufacturer’s instruction. The actin gene was used as an internal control and primers used for quantitative RT-PCR are listed in Supplementary table 5.

Distribution analysis of Rht8-B1b in wheat accessions

A total of 305 worldwide accessions with genotypic information obtained from the Wheat Union Database (http://wheat.cau.edu.cn/WheatUnion/) were used for analysis of allelic variation in Rht8-B1 [31–34]. The frequency of Rht8-B1b in wheat accessions from different geographical regions was calculated according to the number of accessions carrying Rht8-B1b alleles.

Accession numbers

Sequence data of Rht8-B1a and Rht8-B1b are deposited in the GenBank data libraries with the following accession numbers, OQ512875 and OQ512876, respectively.

Phenotypic variation of two parent lines and the RIL population

We have previously identified a semi-dwarf wheat mutant line Rht8-2 with high yield potential [10]. To explore QTLs associated with important agronomic traits, we constructed a RIL population including 139 lines derived from the crossing between the wheat variety ND5181and the mutant line Rht8-2. The two parent lines showed significant differences in Plant Height (PH) and Spike Compactness (SC) under two environmental conditions (Fig. 1A). Specifically, compared to ND5181, Rht8-2 decreased PH by 11 cm, and increased SC by 0.45 (Fig. 1; Table S1). In the RIL population, the PH and SC of RILs displayed an obviously transgressive segregation. These three traits showed normal distributions under two environmental conditions, suggesting they are controlled by multiple genes (Fig. 2). Pairwise correlation analysis between PH and SC indicated a significantly negative correlation between PH and SC in the RIL population under the two environmental conditions (Table S2).

QTL mapping analysis

A total of 23 QTLs associated with PH and SC were detected under the two environmental conditions on chromosomes 1A, 1B, 2B, 2D, 3A, 3B, 4B, 5A, 5B, 6B, 6D, 7A, 7B, and 7D, respectively. Among these QTLs, qPH2B.1, qPH2D, qPH4B, qSC1B, qSC2B.1, qSC2D.1, qSC7D, could be stably detected in the two environments (Fig. 3; Table 1).

Table 1

QTLs associated with plant height (PH), heading date (HD), and spikelet compactness (SC) in the Zhongpuchang and Changping environments identified with IciMapping 4.1.
Environment	Trait Name	QTL	Chromosome	Left Marker	Right Marker	LOD	PVE (%)	Add
Zhongpuchang	PH	qPH2B.1	2B	A44806	A44812	11.4684	7.994	2.5902
		qPH2B.2	2B	A48303	A48463	8.2893	5.5607	2.1144
		qPH2D	2D	A61464	A61529	22.651	19.2436	4.0568
		qPH3A	3A	A69302	A69519	5.8247	3.943	-1.7645
		qPH4B	4B	A112983	A113076	30.1221	29.7012	-4.901
		qPH7B.1	7B	A193948	A194156	10.2915	6.9504	2.414
		qPH7B.2	7B	A194789	A194814	3.9033	2.449	-1.4358
	SC	qSC1B	1B	A18513	A19081	5.0487	3.7798	0.0687
		qSC2B.1	2B	A44792	A44806	24.5623	24.9755	-0.1801
		qSC2B.2	2B	A45030	A45063	11.673	9.482	0.1119
		qSC2D.1	2D	A61140	A61372	13.6018	13.006	-0.1288
		qSC2D.2	2D	A64193	A64287	5.4426	3.9538	-0.0703
		qSC7B	7B	A193641	A193948	3.9214	2.7592	-0.058
		qSC7D	7D	A202015	A202077	2.7953	1.9425	0.0493
Changping	PH	qPH2B.1	2B	A44792	A44806	4.0065	2.1155	1.6056
		qPH2B.3	2B	A56299	A56338	5.2987	2.8879	1.9184
		qPH2D	2D	A61464	A61529	23.5792	17.8166	4.7225
		qPH3B	3B	A94610	A94625	4.2256	2.2634	-1.6462
		qPH4B	4B	A112816	A112833	40.1532	41.7687	-7.0218
		qPH5A	5A	A133195	A133216	7.5183	4.2383	2.6582
		qPH5B	5B	A134432	A141070	5.1174	3.5318	-2.0132
		qPH7A	7A	A179460	A179521	6.4762	3.6198	2.132
	SC	qSC1A	1A	A7344	A7362	4.4992	4.6783	-0.0555
		qSC1B	1B	A18513	A19081	6.2316	6.9554	0.0686
		qSC2B.1	2B	A44757	A44782	12.7453	14.9828	-0.1018
		qSC2D.1	2D	A61578	A61731	19.362	27.6476	-0.1415
		qSC6B	6B	A161877	A161905	3.8673	3.9563	0.0521
		qSC6D	6D	A174738	A174762	3.3927	3.504	0.0514
		qSC7B	7B	A192944	A193088	3.8252	3.8496	-0.0502
		qSC7D	7D	A202015	A202077	5.3974	5.6152	0.0617

Three stable QTLs associated with PH were identified on chromosomes 2B, 2D, and 4B in the two environments. The major QTL qPH4B showed higher LOD scores (30.1 and 40.2) that explained 29.7% and 41.8% of the phenotypic variation, respectively. In addition, qPH2D were identified with LOD scores 22.7 and 23.6 under the two environments and accounted for 19.2% and 17.8% of the phenotypic variation, respectively; while qPH2B.1 had LOD scores 11.5 and 4.0 explained 7.9% and 2.1% of the phenotypic variation, respectively, being detected on the two environments. Finally, the qPH4B allele from ND5181 decreased PH, while the Rht8-2 allele in qPH2D and qPH2B.1 reduced PH (Table 1).

And, we identified four stable QTLs associated with SC on chromosomes 1B, 2B, 2D and 7D in the two environments. qSC2B.1 was detected in both environments with LOD scores 24.6 and 12.7, explaining 25.0% and 15.0% of the phenotypic variation, respectively. qSC2D.1 with LOD scores 13.6 and 19.4 was also identified in two environments and explained 13.0% and 27.6% of the phenotypic variation, respectively. qSC1B, with LOD scores 5.0 and 6.2, explained 3.8% and 7.0% of the phenotypic variation, respectively and was detected in the two environments. Finally, qSC7D with LOD scores 2.8 and 5.4 explained 1.9% and 5.6% of the phenotypic variation, respectively. Among these QTLs in ND5181, the qSC1B and qSC7D alleles increased SC and the qSC2B.1 and qSC2D.1 alleles decreased SC (Table 1).

Rht8-B1 is the candidate gene of qPH2B.1

To validate the mapped region of qPH2B.1, we successfully developed 9 KASP makers around this region based on 660K SNP array analysis between the ND5181 and Rht8-2 varieties, and delimited it to a physical interval of 3.5 Mb between markers 2B-4 and 2B-5. This QTL showed a LOD score of 3.4 and explained 11.8% of the observed phenotypic variation (Fig. 4). Given that this region included Rht8-B1 (TraesCS2B02G073600), an homoeologous gene to Rht8, we sequenced the region and uncover two genetic variants (39418567–39418568, GC to TT) in the coding region of the gene that resulted in an amino acid change from G (ND5181) to V (Rht8-2) at the 175th position. We then analyzed the effects of Rht8-B1 on PH and SC in the RIL population, and found that TT alleles reduced PH by 6.2% and 3.6%, shortened spike length by 6.6% and 4.7%, and increased SC by 5.8% and 6.3% in the Zhongpuchang and Changping field experiments, respectively (Fig. 4).

Rht8-B1 exhibited a lower impact on PH reduction than Rht8-D1

We compared the effects of Rht8-B1 and previously reported Rht8-D1 on PH reduction by knocking out both genes in a Fielder background and evaluating the PH of the T₂ lines. The results showed that the PH of edited plants was significantly lower than control plants. Specifically, edited Rht8-B1 and Rht8-D1 plants showed a PH reduction of 5.6% and 17.5%, respectively, suggesting a lower impact of Rht8-B1 than Rht8-D1 (Fig. 5A, B).

Expression comparison of Rht8-B1 and Rht8-D 1

In order to examine the difference of expression pattern between Rht8-B1 and Rht8-D1, we analyzed their transcript level using Hexaploid Wheat Expression Dataset [35], and found that both genes were highly expressed in stem at the jointing stage, while the expression of Rht8-D1 was significantly higher than that of Rht8-B1 (Fig. 6A). Our previous study suggested that the frameshift mutation in Rht8-D1 caused dwarfism phenotype in Rht8-2 and its expression was significantly decreased in the mutant compared to that of WT [10]. To investigate the effects of mutation of Rht8-D1 on the B subgenome of Rht8, we analyzed the expression of Rht8-B1 in the first internode below spike of the mutant Rht8-2 and WT. The results showed that the expression of Rht8-B1 was remarkably increased in Rht8-2 (Fig. 6B), indicating that the mutation of Rht8-D1 affected the transcript expression of Rht8-B1.

Distribution of Rht8-B1 in wheat varieties worldwide

We used a total of 305 worldwide accessions from the Wheat Union Database (http://wheat.cau.edu.cn/WheatUnion/), including 193 accessions from China and 112 accessions from other countries, for the analysis of Rht8-B1 allelic variation. Among these, 68 Chinese accessions (35.2%) contained the Rht8-B1b TT alleles, compared to only 6 accessions (5.4%) in other countries (Fig. 7). In China, we analyzed 118 modern varieties and 75 landrace accessions, with 20.3% and 58.7% with Rht8-B1b alleles, respectively (Table S3). These results suggest Rht8-B1b alleles were not widely used historically for wheat breeding.

Semi-dwarf wheat usually possesses high lodging resistance with high yield stability [4]. The identification of novel genes regulating PH is pivotal for improving lodging resistance in wheat breeding. In this study, we identified Rht8-B1 as a novel regulator of plant height by genetic mapping and gene editing analyses. By combining mapping with the Wheat40K array and developing molecular markers, qPH2B.1 was mapped between the markers 2B-4 and 2B-5 within a physical position of 36.5–40.0 Mb on chromosome 2B of the Chinese Spring reference genome v1.0 (Fig. 4A). The Rht8-B1 gene was located to position ~ 39.4 Mb on chromosome 2B, suggesting it is the candidate gene for qPH2B.1. Genotyping analysis of Rht8-B1 in the RIL population showed genetic variants associated with PH (Fig. 4B). Further gene editing of Rht8-B1 validated its function on the regulation of PH (Fig. 5). These results suggest Rht8-B1 is the causal gene of qPH2B.1.

We recently identified Rht8 on chromosome 2D (Rht8-D1) that encodes a Ribonuclease H-like protein and modifies PH by regulating the bioactive GA content using map-based cloning with two dwarfing mutants Rht8-2 and Rht8-3 [10]. Here, we used Rht8-2 for the construction of the RIL population and found a major QTL – qPH2D – on chromosome 2D with a high LOD score value that contributes to phenotypic variation, probably representing Rht8-D1. In contrast to the Rht8-D1 (qPH2D) locus, QTL mapping revealed the qPH2B.1 had a minor impact on PH (Fig. 3, 4A), which is consistent with gene editing results (Fig. 5) and reports by Chai et al. [11]. The higher impact of Rht8-D1 on height reduction is also accordance with the higher expression of Rht8-D1 in the stem (Fig. 6A). Previous studies extensively investigated the function of the Rht8 orthologous gene TAC4/ sg2 in rice [36, 37]. A stop-gain mutation in TAC4 led to a greater tiller angle and a dwarf phenotype that may result from changes in IAA content and distribution. In addition, an 8 bp-deletion in sg2 resulted in a smaller grain phenotype due to repressed cell expansion in spikelet hulls and a semi-dwarf phenotype. These observations indicate that orthologous genes to Rht8 affect multiple agronomic traits and play different roles and functions, highlighting the need for further exploration of the effects of Rht8-B1 and Rht8-D1 on PH reduction in the future.

The semidwarf Rht8-B1b allele has high potential for utilization in wheat breeding. By analyzing the genetic sequence of Rht8-B1 in the mutant Rht8-2 and wildtype (WT) variety Jing411, we found the Rht8-B1b allele was derived from the WT, indicating that it is a natural variation. Importantly, the distribution of the Rht8-B1b allele in global wheat varieties suggests it has not been widely utilized historically in wheat breeding outside of China (Fig. 7). Similar to Rht8-D1b, the Rht8-B1b allele had no effects on thousand grain weight. Several studies suggested dwarf or semidwarf genes are associated with a decrease in thousand grain weight and ultimately affect wheat yield [38–40]. The combination of Rht8-B1b and other dwarf genes in wheat breeding can thus be an alternative approach for developing high lodging resistant wheat.

We found consistency between the stable QTLs associated with PH and SC detected in this study and previous reports. For example, Rht-B1b was located at ~ 30.8 Mb on chromosome 4B within the chromosomal region corresponding to qPH4B [5]; qSC2D.1 was identified between molecular markers A61578 and A61731 in positions 20.8–30.3 Mb, closely linked to the Rht8-D1 reported to significantly reduce spike length by Chai et al. [11]; qSC7D was located between molecular markers A202015 and A202077 in positions 584.5-588.2 Mb, closely linked to the WAPO1-7D that regulates spikelet number per spike [41]. We also identified several putatively novel QTLs for PH and SC, including qPH7B.1 on chromosome 7BL with LOD score 10.3 that explained 7.0% of the phenotypic variation in PH; and qSC1B located on the long arm of chromosome 1B between molecular markers A18513 and A19081, which is associated with SC.

We identified 7 stable QTLs for PH and SC under two environments using a RIL population in this study. We used mapping and gene editing analyses and found that Rht8-B1 is the causal gene of qPH2B.1 and affects PH variation. Rht8-B1 showed lower effects on PH than Rht8-D1 and has not been widely utilized in wheat breeding. This implies that combining Rht8-B1b with other favorable Rht genes has great potential for breeding lodging resistant wheat varieties. Our study revealed novel linked markers and QTLs that provide important information for marker-assisted selection in wheat breeding.

Ethics approval and consent to participate

Experimental research and field studies on plants including the collection of plant material are comply with relevant guidelines and regulation.

Consent for publication

Not applicable.

Availability of data and materials

All data generated or analyzed during this study are included in the main text article and its supplementary files. The variant data for this study have been deposited in the European Variation Archive (EVA) at EMBL-EBI under accession number PRJEB60409 (http:// www.ebi.ac.uk/eva/?eva-study=PRJEB60409).

Competing interests

The authors declare that they have no conflict of interest.

Funding

This work was financially supported by the National Key Research and Development Program of China (Grant No. 2022YFD1200700), the Crop Varietal Improvement and Insect Pests Control by Nuclear Radiation, the China Agriculture Research System of MOF and MARA (Grant No. CARS-03), and the Agricultural Science and Technology Innovation Program (Grant No. CAAS-ZDRW202002).

Author contributions

L. L. and X. L. conceived the project and revised the manuscript. C. Z., H. X, and M. F. conducted most of the experiments and analyzed the data. H. G., L. Z., Y. X., J. G., S. Z., Y. D. Y. L. helped in RIL population planting and data analysis. C. Z., and H. X. wrote the first draft of the manuscript. All authors have read and approved the final manuscript.

Acknowledgments

We thank the anonymous reviewers for constructive suggestions that helped to improve the manuscript.

Hickey LT, Hafeez AN, Robinson H, Jackson SA, Leal-Bertioli SCM, M.Tester, Gao CX, Godwin ID, Hayes BJ, Wulff BBH. Breeding crops to feed 10 billion. Nat Biotechnol 2019, 37(7):744-754.
Xiao J, Liu B, Yao YY, Guo ZF, Jia HY, Kong LR, Zhang AM, Ma WJ, Ni ZF, Xu SB et al. Wheat genomic study for genetic improvement of traits in China. Science China Life Sciences 2022, 65(9):1718-1775.
Mo YJ, Vanzetti LS, Hale I, Spagnolo EJ, Guidobaldi F, Al-Oboudi J, Odle N, Pearce S, Helguera M, Dubcovsky J. Identification and characterization of Rht25, a locus on chromosome arm 6AS affecting wheat plant height, heading time, and spike development. Theor Appl Genet 2018, 131(10):2021-2035.
Hedden P. The genes of the Green Revolution. Trends Genet 2003, 19:5-9.
Peng JR, Richards DE, Hartley NM, Murphy GP, Devos KM, Flintham JE, Harberd NP. 'Green revolution' genes encode mutant gibberellin response modulators. Nature 1999, 400:256-2611.
Wen W, Deng QY, Jia HY, Wei LZ, Wei JB, Wan HS, Yang LM, Cao WJ, Ma ZQ. Sequence variations of the partially dominant DELLA gene Rht-B1c in wheat and their functional impacts. J Exp Bot 2013, 64(11):3299-3312.
Divashuk MG, Vasilyev AV, Bespalova LA, Karlov GI. Identity of the Rht-11 and Rht-B1e reduced plant height genes. Russ J Genet 2012, 48(7):761-763.
Bazhenov MS, Divashuk MG, Amagai Y, Watanabe N, Karlov GI. Isolation of the dwarfing Rht-B1p (Rht17) gene from wheat and the development of an allele-specific PCR marker. Mol Breed 2015, 35(11):https://doi.org/10.1007/s11032-11015-10407-11031.
Li YY, Xiao JH, Wu JJ, Duan JL, Liu Y, Ye XG, Zhang X, Guo XP, Gu YQ, Zhang LC et al. A tandem segmental duplication (TSD) in green revolution gene Rht-D1b region underlies plant height variation. New Phytol 2012, 196(1):282-291.
Xiong HC, Zhou CY, Fu MY, Guo HJ, Xie YD, Zhao LS, Gu JY, Zhao SR, Ding YP, Li YT et al. Cloning and functional characterization of Rht8, a "Green Revolution" replacement gene in wheat. Mol Plant 2022, 15(3):373-376.
Chai LL, Xin MM, Dong CQ, Chen ZY, Zhai HJ, Zhuang JH, Cheng XJ, Wang NJ, Geng J, Wang XB et al. A natural variation in Ribonuclease H-like gene underlies Rht8 to confer "Green Revolution" trait in wheat. Mol Plant 2022, 15(3):377-380.
Buss W, Ford BA, Foo E, Schnippenkoetter W, Borrill P, Brooks B, Ashton AR, Chandler PM, Spielmeyer W. Overgrowth mutants determine the causal role of gibberellin GA2oxidaseA13 in Rht12 dwarfism of wheat. J Exp Bot 2020, 71(22):7171-7178.
Borrill P, Mago R, Xu TY, Ford B, Williams SJ, Derkx A, Bovill WD, Hyles J, Bhatt D, Xia XD et al. An autoactive NB-LRR gene causes Rht13 dwarfism in wheat. Proc Natl Acad Sci U S A 2022, 119(48):e2209875119.
Ford BA, Foo E, Sharwood R, Karafiatova M, Vrana J, MacMillan C, Nichols DS, Steuernagel B, Uauy C, Dolezel J et al. Rht18 semidwarfism in wheat is due to increased GA 2-oxidaseA9 expression and reduced GA content. Plant Physiol 2018, 177(1):168-180.
Tian XL, Xia XC, Xu DA, Liu YQ, Xie L, Hassan MA, Song J, Li FJ, Wang DS, Zhang Y et al. Rht24b, an ancient variation of TaGA2ox-A9, reduces plant height without yield penalty in wheat. New Phytol 2021, 233:738-750.
Botwright TL, Rebetzke GJ, Condon AG, Richards RA. Influence of the gibberellin-sensitive Rht8 dwarfing gene on leaf epidermal cell dimensions and early vigour in wheat (Triticum aestivum L.). Ann Bot 2005, 95(4):631-639.
Zhang XK, Yang SJ, Zhou Y, He ZH, Xia XC. Distribution of the Rht-B1b, Rht-D1b and Rht8 reduced height genes in autumn-sown Chinese wheats detected by molecular markers. Euphytica 2006, 152(1):109-116.
Korzun V, Roder M, W GM, J WA, Law CN. Genetic analysis of the dwarfing gene (Rht8) in wheat. Part I. Molecular mapping of Rht8 on the short arm of chromosome 2D of bread wheat (Triticum aestivum L.). Theor Appl Genet 1998, 96:1104-1109.
Kowalski AM, Gooding M, Ferrante A, Slafer GA, Orford S, Gasperini D, Griffiths S. Agronomic assessment of the wheat semi-dwarfing gene Rht8 in contrasting nitrogen treatments and water regimes. Field Crops Res 2016, 191:150-160.
Li T, Deng GB, Su Y, Yang Z, Tang YY, Wang JH, Qiu XB, Pu X, Li J, Liu ZH et al. Identification and validation of two major QTLs for spike compactness and length in bread wheat (Triticum aestivum L.) showing pleiotropic effects on yield-related traits. Theor Appl Genet 2021, 134(11):3625-3641.
Wu XY, Cheng RR, Xue SL, Kong ZX, Wan HS, Li GQ, Huang YL, Jia HY, Jia JZ, Zhang LX et al. Precise mapping of a quantitative trait locus interval for spike length and grain weight in bread wheat (Triticum aestivum L.). Mol Breed 2013, 33(1):129-138.
Fan XL, Cui F, Ji J, Zhang W, Zhao XQ, Liu JJ, Meng DY, Tong YP, Wang T, Li JM. Dissection of pleiotropic QTL regions controlling wheat spike characteristics under different nitrogen treatments using traditional and conditional QTL mapping. Front Plant Sci 2019, 10:187.
Johnson EB, Nalam VJ, Zemetra RS, Riera-Lizarazu O. Mapping the compactum locus in wheat (Triticum aestivum L.) and its relationship to other spike morphology genes of the Triticeae. Euphytica 2007, 163(2):193-201.
Sourdille P, Tixier MH, Charmet G, Gay G, Cadalen T, Bernard S, Bernard M. Location of genes involved in ear compactness in wheat (Triticum aestivum) by means of molecular markers. Mol Breed 2000, 6:247-255.
Hu JM, Wang XQ, Zhang GX, Jiang P, Chen WY, Hao YC, Ma X, Xu SS, Jia JZ, Kong LR et al. QTL mapping for yield-related traits in wheat based on four RIL populations. Theor Appl Genet 2020, 133(3):917-933.
Guedira M, Xiong M, Hao YF, Johnson J, Harrison S, Marshall D, Brown-Guedira G. Heading date QTL in winter wheat (Triticum aestivum L.) coincide with major developmental genes VERNALIZATION1 and PHOTOPERIOD1. PLoS One 2016, 11(5):e0154242.
Wang L, Niu JS, Li QY, Qin Z, Ni YJ, Xu HX. Allelic variance at the vernalization gene locus Vrn-D1 in a group of sister wheat (Triticum aestivum) lines and its effects on development. JAS 2014, 153(4):588-601.
Yan LL, Fu D, Li C, Blechl A, Tranquilli G, Bonafede M, Sanchez A, Valarik M, Yasuda S, Dubcovsky J. The wheat and barley vernalization gene VRN3 is an orthologue of FT. Proc Natl Acad Sci U S A 2006, 103:19581–19586.
Zhou CY, Xiong HC, Li YT, Guo HJ, Xie YD, Zhao LS, Gu JY, Zhao SR, Ding YP, Song XY et al. Genetic analysis and QTL mapping of a novel reduced height gene in common wheat (Triticum aestivum L.). Journal of Integrative Agriculture 2020, 19(7):1721-1730.
Xiong H, Zhou C, Guo H, Xie Y, Zhao L, Gu J, Zhao S, Ding Y, Liu L. Transcriptome sequencing reveals hotspot mutation regions and dwarfing mechanisms in wheat mutants induced by gamma-ray irradiation and EMS. J Radiat Res 2020, 61(1):44-57.
Hao CY, Jiao CZ, Hou J, Li T, Liu HX, Wang YQ, Zheng J, Liu H, Bi ZH, Xu FF et al. Resequencing of 145 landmark cultivars reveals asymmetric sub-genome selection and strong founder genotype effects on wheat breeding in China. Mol Plant 2020, 13(12):1733-1751.
Walkowiak S, Gao L, Monat C, Haberer G, Kassa MT, Brinton J, Ramirez-Gonzalez RH, Kolodziej MC, Delorean E, Thambugala D et al. Multiple wheat genomes reveal global variation in modern breeding. Nature 2020, 588(7837):277-283.
Yang ZZ, Wang ZH, Wang WX, Xie XM, Chai LL, Wang XB, Feng XB, Li JH, Peng HR, Su ZQ et al. ggComp enables dissection of germplasm resources and construction of a multiscale germplasm network in wheat. Plant Physiol 2022, 188(4):1950-1965.
Zhou Y, Zhao XB, Li YW, Xu J, Bi AY, Kang LP, Xu DX, Chen HF, Wang Y, Wang YG et al. Triticum population sequencing provides insights into wheat adaptation. Nat Genet 2020, 52(12):1412-1422.
International Wheat Genome Sequencing C. A chromosome-based draft sequence of the hexaploid bread wheat (Triticum aestivum) genome. Sci 2014, 345(6194):1251788.
Huang YS, Dong H, Mou CL, Wang P, Hao QX, Zhang M, Wu HM, Zhang FL, Ma TF, Miao R et al. Ribonuclease H-like gene Small Grain2 regulates grain size in rice through brassinosteroids signal pathway. J Integr Plant Biol 2022, 10:1883-1900.
Li H, Sun HY, Jiang JH, Sun XY, Tan LB, Sun CQ. TAC4 controls tiller angle by regulating the endogenous auxin content and distribution in rice. Plant Biotechnol J 2021, 19(1):64-73.
Casebow R, Hadley C, Uppal R, Addisu M, Loddo S, Kowalski A, Griffiths S, Gooding M. Reduced height (Rht) alleles affect wheat grain quality. PLoS One 2016, 11(5):e0156056.
Daoura BG, Chen L, Du YY, Hu YG. Genetic effects of dwarfing gene Rht-5 on agronomic traits in common wheat (Triticum aestivum L.) and QTL analysis on its linked traits. Field Crops Res 2014, 156:22-29.
Yang ZY, Zheng JC, Liu CY, Wang YS, Condon AG, Chen YF, Hu YG. Effects of the GA-responsive dwarfing gene Rht18 from tetraploid wheat on agronomic traits of common wheat. Field Crops Res 2015, 183:92-101.
Kuzay S, Xu YF, Zhang JL, Katz A, Pearce S, Su ZQ, Fraser M, Anderson JA, Brown-Guedira G, DeWitt N et al. Identification of a candidate gene for a QTL for spikelet number per spike on wheat chromosome arm 7AL by high-resolution genetic mapping. Theor Appl Genet 2019, 132(9):2689-2705.

No competing interests reported.

Supplementalmaterials.xlsx

Download PDF

Journal Publication

published 22 Jun, 2023

Read the published version in BMC Plant Biology →

Editorial decision: Major revision
20 Apr, 2023
Reviews received at journal
23 Mar, 2023
Reviewers agreed at journal
13 Mar, 2023
Reviewers invited by journal
12 Mar, 2023
Editor assigned by journal
07 Mar, 2023
Editor invited by journal
07 Mar, 2023
Submission checks completed at journal
07 Mar, 2023
First submitted to journal
14 Feb, 2023

You are reading this latest preprint version

Genetic mapping and identification of Rht8-B1 that regulates plant height in wheat

Status:

Journal Publication

Version 1

Abstract

Background

Results

Conclusions

Figures

Background

Materials And Methods

Plant materials and phenotypic evaluation

Genotyping and QTL mapping

KASP marker development and QTL validation

Quantitative RT-PCR

Accession numbers

Results

Phenotypic variation of two parent lines and the RIL population

QTL mapping analysis

Discussion

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1