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Identification of a Novel Allele of TaCKX6a02 Associated with Grain Size, Filling Rate and Weight of Common Wheat

  • Jie Lu ,

    Contributed equally to this work with: Jie Lu, Cheng Chang

    Affiliation College of Agronomy, Anhui Agricultural University, Key Laboratory of Wheat Biology and Genetic Improvement on Southern Yellow & Huai River Valley, the Ministry of Agriculture, Hefei, 230036, China

  • Cheng Chang ,

    Contributed equally to this work with: Jie Lu, Cheng Chang

    Affiliation College of Agronomy, Anhui Agricultural University, Key Laboratory of Wheat Biology and Genetic Improvement on Southern Yellow & Huai River Valley, the Ministry of Agriculture, Hefei, 230036, China

  • Hai-Ping Zhang,

    Affiliation College of Agronomy, Anhui Agricultural University, Key Laboratory of Wheat Biology and Genetic Improvement on Southern Yellow & Huai River Valley, the Ministry of Agriculture, Hefei, 230036, China

  • Sheng-Xing Wang,

    Affiliation College of Agronomy, Anhui Agricultural University, Key Laboratory of Wheat Biology and Genetic Improvement on Southern Yellow & Huai River Valley, the Ministry of Agriculture, Hefei, 230036, China

  • Genlou Sun ,

    genlou.sun@smu.ca(GS); machuanxi@ahau.edu.cn(CXM)

    Affiliations College of Agronomy, Anhui Agricultural University, Key Laboratory of Wheat Biology and Genetic Improvement on Southern Yellow & Huai River Valley, the Ministry of Agriculture, Hefei, 230036, China, Department of Biology, Saint Mary’s University, Halifax, NS, B3H3C3, Canada

  • Shi-He Xiao,

    Affiliation Institute of Crop Sciences, National Wheat Improvement Centre/The National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China

  • Chuan-Xi Ma

    genlou.sun@smu.ca(GS); machuanxi@ahau.edu.cn(CXM)

    Affiliation College of Agronomy, Anhui Agricultural University, Key Laboratory of Wheat Biology and Genetic Improvement on Southern Yellow & Huai River Valley, the Ministry of Agriculture, Hefei, 230036, China

Identification of a Novel Allele of TaCKX6a02 Associated with Grain Size, Filling Rate and Weight of Common Wheat

  • Jie Lu, 
  • Cheng Chang, 
  • Hai-Ping Zhang, 
  • Sheng-Xing Wang, 
  • Genlou Sun, 
  • Shi-He Xiao, 
  • Chuan-Xi Ma
PLOS
x

Abstract

Cytokinin oxidase (CKX) plays a crucial role in plant growth and development by reversibly inactivating cytokinin (CTK). Twenty-four primer pairs, designed from ESTs of the TaCKX genes family of common wheat, were used to identify their allelic variations associated with grain size, weight, and filling rate in 169 recombinant inbred lines (RIL) derived from Jing 411 × Hongmangchun 21. TaCKX6a02, a member of TaCKX gene family, amplified by primer pair T31–32, showed a close association with grain traits in this RIL population. Statistical analysis indicated that allelic variation of TaCKX6a02 had significant correlation with grain size, weight, and filling rate (GFR; P < 0.001) under varied environments. The TaCKX6a02-D1a allele from Jing411 significantly increased grain size, weight and grain filling rate, compared with TaCKX6a02-D1b from Hongmangchun 21. TaCKX6a02 was located on chromosome 3DS in the interval of Xbarc1119 and Xbarc1162, with a genetic distance of 1.4 cM. The location was further confirmed using Chinese Spring nulli–tetrasomic lines. A major QTL (quantitative trait locus) tightly linked to TaCKX6a02 was detected in the RIL population, explaining 17.1~38.2% of phenotype variations for grain size, weight, GFRmax and GFRmean in different environments. In addition, significant effects of variations of TaCKX6a02 on grain weight and GFR were further validated by association analysis among 102 wheat varieties in two cropping seasons. 12.8~35.1% of phenotypic variations were estimated for these genotypes. A novel 29-bp InDel behind the stop codon was detected by DNA sequence analysis between the two alleles of TaCKX6a02-D1. The gene-specific marker, TKX3D, was designed according to the novel variation, and can be used in marker-assisted selection (MAS) for grain size, weight, and GFR in common wheat.

Introduction

As one of the key phytohormones synthesized in the root, cytokinin (CTK) regulates many important plant processes by controlling cell division and tissue differentiation [19]. Many researches indicate that CTK plays an important regulatory role in crop yield and related traits. Firstly, cytokinin is one key hormone in controlling grain size and weight by regulating endosperm cell numbers of crops [1014]. Secondly, CTK also can enhance grain weight by regulating grain filling patterns of crops [1518]. The endogenous CTK (Z+ZR) content of grain at the early grain filling stage has a close relationship with thousand-grain-weight (TGW) via regulation of starch synthase (SSase) and starch branching enzyme (Q-enzyme) activities in rice [19]. CTK also can maintain chloroplast stability of flag leaf after anthesis, significantly improving grain filling and weight [20, 21]. For other yield-related traits, such as effective tiller emergence, spikelet and floret aspects, and fertile floret and kernel numbers, CTK is generally regarded as a positive regulator [2225].

The phytohormone, CTK, is under strict control mainly regulated by cytokinin oxidase (CKX). The CKX is considered to be only known phytohormone enzyme that can inactivate CTK irreversibly by cleaving its N6-side chain in a single enzymatic step [26]. Hence, cytokinin oxidase (CKX) genes have been proven to have a close relationship with crop yield through regulation of endogenous CTK. Ashikari et al. isolated the rice CKX gene (OsCKX2) and confirmed that reduced expression caused CTK accumulation in inflorescence meristems and increased the number of reproductive organs, resulting in enhanced grain yield [27]. As graminaceous crops, wheat, rice, barley (Hordeum vulgare L.), maize (Zea mays), and Sorghum spp. show large similarity and co-linearity between their genomes; therefore, wheat CKX genes are also involved in the regulation of grain yield. Zalewski et al. confirmed that seed numbers per plant and seed weight are improved by silencing the HvCKX1 gene in barley and the TaCKX1 gene in wheat [28]. Two putative CKX genes of wheat (TaCKX2.1 and TaCKX2.2) have been cloned and are presumed to relate to grain number per spike [29]. TaCKX6 is confirmed to have a significant association with the grain weight of common wheat [30]. Based on sequences analysis of ESTs available from the NCBI (www.ncbi.nlm.nih.gov), wheat CKX genes are proved to belong to a large gene-family containing at least 13 members [31]. So far, seven wheat CKX genes have been isolated: TaCKX1 on chromosome 3A [32], TaCKX2 on 7A or 7B [33], and TaCKX2.1, TaCKX2.2 [29], TaCKX3 [34], TaCKX5 [35], and TaCKX6 [30] on 3DS. However, little research was carried out to investigate the effects of allelic variations of TaCKX genes on grain filling, size, and grain weight of wheat simultaneously. The objectives of this study are to: (1) identify allelic variations of CKX genes for grain filling, grain size, and grain weight based on all TaCKX ESTs, mRNA, and DNA sequences available in the NCBI; and (2) develop a gene-specific marker for TaCKX6a02 and validate its association with grain traits.

Materials and Methods

Plant Materials

One hundred and sixty-nine recombinant inbred lines (RILs) were developed from a cross between Jing 411 and Hongmangchun 21 by single-seed descent (F2:8 generation). Jing 411 is a high-yield winter wheat variety with a larger grain size; its TGW averaged 47.6 g over five cropping seasons (2006~2007, 2007~2008, 2008~2009, 2009~2010 and 2010~2011). Hongmangchun 21 is a Chinese low-yield landrace, with an average TGW of 19.7 g across the five cropping seasons (Table 1). The two parents show large differences in yield-related traits, including grain size, grain weight, and grain filling (Table 1). One hundred and two wheat varieties from different wheat production regions of China showing large variation in grain filling, size, and weight were used for validation of the gene marker (Table 1).

Field trials

The RILs and their parents were grown in randomized complete blocks, with two replicates at the Changping Experimental Station of Chinese Academy of Agricultural Sciences (Beijing: 39°54'N, 116°28'E) in the 2006~2007 and 2007~2008 cropping seasons, and the Experimental Station of Anhui Agricultural University (Hefei; 31°58'N, 117°24'E) during the 2008~2009, 2009~2010 and 2010~2011 cropping seasons. The 102 wheat varieties were also grown in randomized complete blocks with two replicates during the 2011~2012 and 2012~2013 cropping seasons at the Experimental Station of Anhui Agricultural University.

Each plot contained three 2.0-m rows spaced 25 cm apart, with 40 plants in each row. Field management followed common practices for wheat production, and the flowering time was recorded for each line.

Recording of data for grain size, weight, and grain filling rate

Grain size and weight were determined in all seasons and locations. TGW was evaluated by weighing two samples of 1000 kernels from each genotype. Grain size, including length and width, was recorded after harvesting using the method described by Sun et al. [36], with minor modifications. Two sets of 50 grains, from each variety or RIL, were lined up length-wise along a ruler with a precision of 0.1 mm, and the average length of the samples defined as grain length (GL). The average width of the two sets of grains laid breadth-wise was defined as grain width (GW). The thickness (GT) of two sets of 20 grains was measured using vernier calipers (Kraftwelle, China) with a precision of 0.01 mm, using the method described by Dholakia et al. [37].

GFRmax and GFRmean were determined for the RILs during the 2009~2010 and 2010~2011 cropping seasons, and 102 wheat varieties during the 2011~2012 and 2012~2013 cropping seasons at the Experimental Station of Anhui Agricultural University respectively, following the method described by Wang et al. (2008) [38]. Seven tagged spikes from each line were sampled at 5-day intervals from anthesis to maturity. The grains were then separated from the glumes, kept at 105°C for 10 min, and then at 70°C until reaching a constant weight. At this stage, the total number of grains was counted, and the weight recorded. Grain filling rates were calculated as described by Wang et al. [38].

Genomic DNA extraction and PCR amplification

Genomic DNA was extracted from two kernels per line in accordance with Kang et al. [39]. PCR reactions were conducted using a TC412 Thermocycler (Barloworld Scientific, UK). Twenty-four primer pairs (S1 Table) were designed to characterize allelic variations of TaCKX genes in wheat using DNAMAN (Version 6.0) software (Lynnon Biosoft, San Ramon, CA, USA) based on EST and mRNA sequences available from the NCBI.

The PCR profile was as follows: denaturation at 94°C for 5 min; followed by 40 cycles of denaturation at 95°C for 1 min, annealing at 50~60°C for 1 min 20 s, and extension at 72°C for 2 min; with a final extension for 8 min at 72°C. The annealing temperature was modulated based on the primer pair. Each 15-μl PCR reaction contained 40 ng of genomic DNA, 10 pmol of each primer, 200 mM dNTPs, 1×PCR buffer, and 1 U Taq DNA polymerase (Shanghai Sangon Biological Engineering Technology & Services, Shanghai, China). PCR products were separated by 7% PAGE containing 4 M Urea.

Sequencing of PCR fragments and statistical analysis

Purification and sequencing of PCR products, from two independent samples per wheat genotype was performed by Shanghai Sangon Biological Engineering Technology & Services. Pfu Taq DNA polymerase (Shanghai Sangon Biological Engineering Technology & Services, Shanghai, China) with high fidelity was used to avoid false priming; all TaCKX alleles were sequenced from both strands. Sequence alignment and characterization were completed using DNAMAN software. Data analysis of grain traits was conducted using SPSS software version 13.0 (IBM Software Group, Armonk, NY, USA).

Chromosomes assignment of TaCKX gene

A set of Chinese Spring nulli–tetrasomic lines was used to determine the location of TaCKX gene. PCR amplification and separation of products was as described above.

SSR marker screening and QTL analysis for grain weight and grain filling

Simple sequence repeat (SSR) markers, including the BARC, GWM, WMC, CFA, and CFD series were used to screen the two parents, and two bulks containing five high-grain-weight lines and five low-grain-weight lines, respectively [40]. Candidate polymorphic markers between the bulks were analyzed further in a subset of 40 RILs, including 20 lines with high-grain-weight and 20 with low-grain-weight, to confirm the polymorphism. The polymorphic markers were then used for genotyping the entire RIL population. The linkage map was constructed using Map Manager QTXb20 Version 3.0 [41]. Recombination fractions were converted into centimorgans (cM) using the Kosambi function [42]. Composite interval mapping (CIM) was performed for QTL analysis using Windows Cartographer 2.5 software (http://statgen.ncsu.edu/qtlcart/WQTLCart.htm) in accordance with the methods described by Zeng [43]. A QTL was declared when the LOD score was > 2.5 in at least two cropping seasons, and calculated from 2,000 permutations at a probability of 0.01.

Analysis of correlation between TaCKX alleles and grain traits

When analyzing the correlation between TaCKX alleles and grain traits in the RILs population and wheat varieties, the Jing 411 allele was scored as “1” and the Hongmangchun 21 allele as “0”. Spearman rank correlation analysis and t-test were performed to test the association significance between allelic variation and grain traits, as described in previous studies [4446]. The effect of TaCKX variation on the variability of grain traits was estimated by R2 based on the General Linear Model [4446]. The significance of the effect was evaluated using the GLM at 0.05, 0.01, and 0.001 levels of probability. Grain trait data analyses were conducted using SPSS software version 13.0.

Results

Correlation analysis between different grain traits

In this study, the grain traits of RILs such as GL, GW, GT, TGW, GFRmean, and GFRmax showed wide variations (Table 1). Grain size (GL, GW, and GT) had a significant correlation with grain weight (P < 0.001); and grain filling also showed a significant correlation with grain weight (P < 0.001; S2 Table). These results suggested that grain weight is not only determined by grain size but also by GFR. Grain weight showed closer relationship with grain size than grain filling.

Identification of allelic variations in TaCKX associated with grain traits

Of the 24 primer pairs developed from wheat CKX genes (Galuszka et al. 2004)[31], six pairs including T3–4 (TaCKX1), T5–6 (TaCKX2a), T13–14 (TaCKX3), T19–20 (TaCKX4), T25–26 (TaCKX5b), and T31–32 (TaCKX6a02) showed good polymorphism between the two parents. To identify TaCKX genes associated with grain traits, spearman rank correlation analysis and t-test were performed based on the mean performance of grain traits of RILs in the five environments. The results indicated that the allelic variation of TaCKX6a02 had a significant correlation with grain size, grain weight, and GFR in the RIL population (P < 0.001; Table 2). The alleles of the A- and B-type patterns shown in Fig 1 were named TaCKX6a02-D1a and TaCKX6a02-D1b, respectively. The marker used for identifying the allelic variation of TaCKX6a02-D1 was designated as CKX3D. RILs carrying TaCKX6a02-D1a had significantly higher values for grain size, weight and grain filling than TaCKX6a02-D1b (Table 2), indicating that the TaCKX6a02-D1a allele could improve grain traits.

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Fig 1. Allelic variation of TaCKX6a02 in the RIL population of Jing 411/Hongmangchun 21.

Lane Nos. (1) Jing 411; (2) JH1; (3) Hongmangchun 21; (4) JH19; (5) JH31; (6) JH38; (7) JH2; (8) JH3; (9) JH4; (10) JH5; (11) JH73; (12) JH9; (13) JH10; (14) JH12; (15) JH75; (16) JH79; (17) JH81; (18) JH103; (19) JH105; (20) JH13; (21) JH107; (22) JH113; (23) JH15; (24) JH118; (25) JH120; (26) JH125; (27) JH129; and (28) JH130. In the figure, JH1, JH19, JH31, JH38, etc., represent individual names of the RIL population. Two types of alleles, TaCKX6a02-D1a (Jing 411) and TaCKX6a02-D1b (Hongmangchun 21) are marked with the letters “A” and “B”, respectively.

https://doi.org/10.1371/journal.pone.0144765.g001

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Table 2. Analysis of grain traits between two alleles of TaCKX6a02, and Spearman correlations and t-test between the allelic variation of TaCKX6a02 and grain traits in the RILs and natural population.

https://doi.org/10.1371/journal.pone.0144765.t002

Chromosome location of TaCKX6a02

Previous studies indicated that wheat CKX genes belong to a large gene-family, distributed on several chromosomes, including 3A, 3B, 3D, 7A, and 7B; hence, it was necessary to locate TaCKX6a02 before performing genetic linkage analysis in the RIL population. In this study, the chromosome location of TaCKX6a02 was identified using Chinese Spring nulli–tetrasomics. The PCR products were amplified in N3AT3B, N3AT3D, N3BT3A, and N3BT3D, but were not present in N3DT3A or N3DT3B (S1 Fig), indicating that the TaCKX6a02 gene is located on chromosome 3D.

Linkage analysis of the TaCKX6a02 gene and functional marker development

Seventy-seven SSR markers on chromosome 3D were selected based on their chromosomal location. To analyze the genetic linkage of TaCKX6a02 on 3D, and to further evaluate its effect on the phenotypic variation of grain traits, the SSR markers were screened using their two parents and two bulks. Fourteen SSR markers and the gene-marker CKX3D showed good polymorphism in the mapping population. Genetic map analysis indicated that the 14 SSR markers were assigned in the same linkage group as the CKX3D region, spanning a genetic distance of 26 cM (Fig 2).

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Fig 2. Linkage map of TaCKX6a02 on chromosome 3DS of wheat.

The six shaded boxes represent the six traits of TGW, GW, GL, GT, GFRmax, and GFRmean, respectively.

https://doi.org/10.1371/journal.pone.0144765.g002

Through the analysis of CIM, a QTL controlling grain traits was identified in the marker interval of Xbarc1119 and Xbarc1162 on chromosome 3DS, with a genetic distance of 1.4 cM (Fig 2). The QTL co-segregated with TaCKX6a02, with LOD values ranging from 9.1 to 21.1 over five environments. The six grain traits, GL, GW, GT, TGW, GFRmax, and GFRmean were all associated with the same QTL closely linked to TaCKX6a02, Xbarc1119, and Xbarc1162.

The QTL mapped at CKX3D locus was detected across all five cropping seasons, and could explain 17.4~38.2% of phenotypic variations for grain size and grain weight (Table 3). Regarding grain filling traits, the locus also accounted for 17.1% and 22.2% of phenotypic variations of GFRmax and GFRmean, respectively, in the two environments (2009~2010 and 2010~2011 cropping seasons). Therefore, TaCKX6a02 could be considered as a candidate gene for grain filling, grain size, and grain weight in this population.

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Table 3. Summary of QTLs for grain traits in the RILs from the Jing 411/Hongmangchun 21 cross, across different environments.

https://doi.org/10.1371/journal.pone.0144765.t003

Validating effects of TaCKX6a02 variations on grain traits among 102 wheat varieties

To further confirm effects of TaCKX6a02 on grain traits, association analysis of allelic variations with grain traits were conducted among 102 wheat genotypes. In this natural population, 68.5% of varieties had the TaCKX6a02-D1a allele, while the remainder had TaCKX6a02-D1b (S3 table).

A wide variation of grain traits was observed among these wheat varieties (Table 1). The mean values of the six grain traits all showed significant differences (P < 0.001) between TaCKX6a02-D1a and TaCKX6a02-D1b (Table 2). The varieties with TaCKX6a02-D1a allele had significantly higher value of grain traits than those with TaCKX6a02-D1b allele. The association analysis showed that the allelic variation of TaCKX6a02 had a significant correlation with grain traits in natural population of wheat (P < 0.01 or 0.001; Table 2; S2 Fig). Phenotypic variations of grain traits explained by TaCKX6a02 ranged from 12.8~35.1% across the two cropping seasons (2011~2012, 2012~2013). Through analysis in different genetic background, RILs and natural population, TaCKX6a02 could be validated to have a significant effect on grain traits in common wheat.

Sequence analysis of TaCKX6a02

A 29-bp insertion in the 3′-untranslation region (3′-UTR) behind the TGA stop codon was detected in the Jing 411 allele of TaCKX6a02-D1a, compared with the Hongmangchun 21 allele TaCKX6a02-D1b (Fig 3). The sequence of TaCKX6a02-D1a was the same as the EST BQ235927 deposited at the NCBI (Galuszka et al. 2004) [31]. Other CKX genes on chromosome 3D, including TaCKX2.1 (FJ648070.1), TaCKX2.2 (GU084177.1), TaCKX2.3.1 (JF293079), TaCKX2.3.2 (JN128584), and TaCKX6-D1b (JQ797673) were also obtained by performing a BLAST search on the NCBI GenBank. Sequences between TaCKX6a02 and the above TaCKX genes were analyzed using DNAMAN software. The results revealed TaCKX6a02 shared a high identity with them in the open reading frame region (ORF), as shown in Fig 3. Through alignment analysis among them, TaCKX6a02 had higher homology with EST BQ235927 (99%), TaCKX2.3.1 (99%) and TaCKX2.3.2 (99%), than with TaCKX2.1 (92%), TaCKX2.2 (92%) and TaCKX6-D1b (92%) (S3 Fig). The TaCKXs on chromosome 3D could thus be divided into two groups according to their homology.

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Fig 3. Sequence alignment between TaCKX6a02 and TaCKX2.1, TaCKX2.2, TaCKX2.3.1, TaCKX2.3.2, and TaCKX6-D1b.

Two alleles sequences of Tackx6a02, TaCKX6a02-D1a) and TaCKX6a02-D1b were obtained from the reverse-complement sequences of PCR fragments of Jing 411 and Hongmangchun 21. The primer pair and stop codon are marked with arrows in the figure. The InDel sequence is boxed.

https://doi.org/10.1371/journal.pone.0144765.g003

Discussion

Homology ananlysis of CKX genes on chromosome 3D of wheat

Six CKX genes on chromosome 3D of wheat were identified following a BLAST search in NCBI using the TaCKX6a02 sequence, including an EST BQ235927, TaCKX2.1, TaCKX2.2, TaCKX2.3.1, TaCKX2.3.2, and TaCKX6-D1b. Alignment analysis revealed that TaCKX6a02, TaCKX2.3.1 and TaCKX2.3.2 are possibly the same CKX gene because of very high identity in sequence between them. However, the function of TaCKX2.3.1 and TaCKX2.3.2 had remained unknown until now. TaCKX2.1, TaCKX2.2 and TaCKX6-D1b also shared higher sequence homology among them, but had a lower identity with TaCKX6a02. For example, TaCKX6a02 had a large difference in sequence at the 3′-UTR, compared with TaCKX2.1 and TaCKX2.2. The main variation in TaCKX6a02, 29-bp InDel in the 3′-UTR, was also different from TaCKX6-D1b containing 18-bp InDel in intron 2 and 20-bp InDel in the third exon [30]. According to these analyses, these TaCKX genes were clearly divided into two groups.

Multiple CKX genes have been observed on chromosome 3DS of wheat; however, their functions varied. TaCKX2.1 and TaCKX2.2 are involved in the regulation of grain number per spike in wheat [29], similar to OsCKX2 in rice [27]. On the other hand, TaCKX6 [30] and TaCKX6a02 are associated with grain weight. Interestingly, these CKX genes have a relatively high sequence identity and all located on chromosome 3DS. Furthermore, TaCKX6 and TaCKX6a02 share a similar linkage interval on the genetic map. Based on sequence identity and linkage analysis, TaCKX6 and TaCKX6a02 may be different alleles of the CKX gene. Therefore, further study is to clone full length of TaCKX6a02 and compare its sequence with TaCKX6.

Allelic variation of TaCKX6a02

Gene mutations occurring in coding regions often affect function as a result of amino acid changes. However, the 5′-UTR [47, 48], 3′-UTR [4952], and intron [30, 53] also have important influences on gene function through regulating mRNA structure, stability, and accumulation during translation. Previous research has confirmed that an 18-bp InDel in the second intron of TaCKX6-D1b had a significant influence on the gene expression at eight days after pollination in common wheat [30]. In this study, a novel 29-bp InDel was found in the 3′-UTR of TaCKX6a02. Whether variation of TaCKX6a02 leads to enhancement of grain weight by directly increasing endogenous cytokinin levels, and what is the synergistic relationship between the two markers (C19L3⁄C19L4 and TKX3D) and grain weight are worthy of further study.

TaCKX6a02 locus for grain traits

As a complex trait, grain weight is controlled by multiple genes or loci widely distributing on the most of wheat chromosomes. On chromosome 3D, several QTLs for grain weight and related traits have been detected using varied populations, explaining 6~23% of phenotype variations in different environments [38, 5458]. In this study, the TaCKX6a02 locus for grain traits was closely linked to Xgwm341, Xwmc533, Xbarc1119, Xbarc1162, and Xcfd62 on chromosome 3DS; the linkage intervals were similar to the previous reports [55, 56]. However, these loci explained relatively less phenotypic variation of grain traits, compared with the TaCKX6a02 locus (17.1~38.2%). Zhang et al. [30] also reported that TaCKX6 was located on chromosome 3DS and linked to Xcfd70 and Xwmc533. This is very similar to TaCKX6a02. These results revealed that varied QTLs or loci for grain weight occurred on chromosome 3D of wheat.

Identification of genes for grain traits in wheat is receiving increased attention of researchers. At present, some genes for grain size and weight are known, including TaGW2 [5961], TaCKX6 [30], TaGS-D1 [62], 6-SFT-A2 [63]. In our study, TaCKX6a02 is also confirmed to tightly relate to grain size and weight by QTL and association analysis. Interestingly, the gene also has significant effect on grain filling rate of wheat simultaneously. The result suggests that TaCKX6a02 is likely involved both in regulating grain formation and the filling process of wheat. The influence of TaCKX6a02 on grain weight was probably due to its regulation on both grain size and filling. Therefore, findings of variations in TaCKX6a02 will help further understanding of complex mechanisms of grain weight. In addition, the TaCKX6a02-D1a is a predominant allele among modern varieties, and TaCKX6a02-D1b allele mainly distributes in local varieties or landraces of China in our study. These results show a strong selection of TaCKX6a02-D1a in breeding programs. Furthermore, the locus co-segregating with TaCKX6a02 shows good stability and reliability in varied environments and genetic backgrounds, and thus will help improve the accuracy and effectiveness of marker assisted selection for grain traits in wheat breeding.

Conclusions

TaCKXs belong to a big gene family, including at least 13 members in common wheat. Several TaCKX genes have been validated to relate to grain yield. In this research, TaCKX6a02 on chromosome 3DS was also identified to closely associate with grain size, filling and weight in a RIL population and natural population respectively. By sequence analysis, a novel allelic variation of TaCKX6a02 was observed, which contained a 29-bp InDel behind the stop codon. A gene-specific marker, TKX3D, was developed based on the InDel variation. The TKX3D locus could explain 12.8–38.2% of phenotypic variations in different environments.

Supporting Information

S2 Table. Correlation between the grain traits of RILs.

https://doi.org/10.1371/journal.pone.0144765.s002

(DOC)

S3 Table. The information of grain weight, allele of TaCKX6a02 and distributed region of 102 wheat varieties.

https://doi.org/10.1371/journal.pone.0144765.s003

(DOCX)

S1 Fig. Amplification of the TaCKX6a02 gene using the primer pair T31–32 in Chinese Spring nulli–tetrasomics.

https://doi.org/10.1371/journal.pone.0144765.s004

(TIF)

S2 Fig. Grains of 12 wheat varieties with large difference in grain size and weight.

https://doi.org/10.1371/journal.pone.0144765.s005

(TIF)

S3 Fig. Homology analysis of TaCKX genes.

https://doi.org/10.1371/journal.pone.0144765.s006

(TIF)

Acknowledgments

We thank Prof. Zhiyong Liu in Chinese Agricultural University for kindly providing a set of Chinese Spring nulli–tetrasomic lines and Xiu Ying Zhang in CAAS for kindly collecting the RILs population.

Author Contributions

Conceived and designed the experiments: CC JL CXM. Performed the experiments: JL CC HPZ SXW. Analyzed the data: CC JL HPZ. Contributed reagents/materials/analysis tools: HPZ CXM. Wrote the paper: CC JL GLS SHX.

References

  1. 1. Jeffrey CS. Postharvest changes in endogenous cytokinin and cytokinin efficacy in potato tubers in relation to bud endodormancy. Physiol Plantarum. 1998; 103: 59–69.
  2. 2. Khamlichi CR, Huntley R, Jacqmard A, James AH. Cytokinin activation of arabidopsis cell division through a D-type cyclin. Science. 1999; 283: 1541–4. pmid:10066178
  3. 3. Lee EG, Seo JS, Cha MH, Suh MC, and Sim WS. Cytokinin stimulates expression of the chloroplast ATP synthase VI Subunit Gene (atpl). J Plant Biol. 2002; 45: 71–6.
  4. 4. Gupta NK, Gupta S, Shukla DS and Deshmukh PS. Differential responses of BA injection on yield and specific grain growth in contrasting genotypes of wheat (Triticum aestivum L.). Plant Growth Regul. 2003; 40: 201–5.
  5. 5. Yang JC, Zhang JH, Wang ZQ and Zhu QS. Hormones in the grains in relation to sink strength and postanthesis development of spikelets in rice. Plant Growth Regul. 2003; 41: 185–95.
  6. 6. Riefler M, Novak O, Strnad M and Schmulling T. Arabidopsis cytokinin receptor mutants reveal functions in shoot growth, leaf senescence, seed size, germination, root development, and cytokinin metabolism. Plant Cell. 2006; 18: 40–54. pmid:16361392
  7. 7. Swartzberg D, Kirshner B, David DR, Yigal Elad Y, David Granot D. Botrytis cinerea induces senescence and is inhibited by autoregulated expression of the IPT gene. Eur J Plant Pathol. 2008; 120: 289–97.
  8. 8. Zubo YO, Yamburenko MV, Selivankina SY, Shakirova FM, Avalbaev AM, Kudryakova NV, et al. Cytokinin stimulates chloroplast transcription in detached barley leaves. Plant Physiol. 2008; 148: 1082–93. pmid:18715959
  9. 9. Subbaraj AK, Funnell KA, Woolley DJ. Dormancy and flowering are regulated by the reciprocal interaction between cytokinin and gibberellin in zantedeschia. J Plant Growth Regul. 2010; 29: 487–99.
  10. 10. Somers DJ, Isaac P, Edwards K. A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.). Theor Appl Genet. 2004; 109: 1105–14. pmid:15490101
  11. 11. Yang JC, Peng SB, Visperas RM, Sanico AL, Zhu QS & Gu SL. Grain filling pattern and cytokinin content in the grains and roots of rice. Plant Growth Regul. 2000; 30: 261–70.
  12. 12. Yang JC, Zhang JH, Huang ZL, Wang ZQ, Zhu QS and Liu LJ. Correlation of cytokinin levels in the endosperms and roots with cell number and cell division activity during endosperm development in rice. Ann Bot. 2002, 90: 369–77. pmid:12234149
  13. 13. Fan GQ, Yang WY, Shao QQ, Ren WJ, Liu F. Change of wheat starch content and endogenous hormone during seed developing and their relationship. J Triticeae Crops. 2007; 27: 327–30 (In Chinese with English abstract).
  14. 14. Javid MG, Sorooshzadeh A, Sanavy SA, Allahdadi I, Moradi F. Effects of the exogenous application of auxin and cytokinin on carbohydrate accumulation in grains of rice under salt stress. Plant Growth Regul. 2011; 65: 305–13.
  15. 15. Sivakumar T, Virendranath and Srivastava GC. Effects of benzyl adenine and abscisic acid on grain yield and yield components in Triticale and wheat. J Agron Crop Sci. 2001; 186: 43–6.
  16. 16. Li XJ, Zhi MX, Lu YZ. Changes of cytokinins content during the wheat grain development of different grain sizes. J Triticeae Crops. 2005; 25 (2): 42–5 (In Chinese with English abstract).
  17. 17. Zhao BH, Zhang HX, Zhu QS, Yang JC. Causes of poor grain plumpness of two-line hybrids and their relationships to contents of hormones in the rice grain. Scientia Agricultura Sin. 2006; 39: 477–86 (In Chinese with English abstract).
  18. 18. Li WY, Yin YP, Yan SH, Dai ZM, Liang TB, Wang ZL (2007) Hormonal changes in relation to filling characters in developing grains of two wheat cultivars differing in grain size. Acta Agri Boreali-Sinica. 2007; 22: 5–8 (In Chinese with English abstract).
  19. 19. Dong MH, Zhao BH, Wu XZ, Chen T, Yang JC. Difference in hormonal content and activities of key enzymes in the grains at different positions on a rice panicle during grain filling and their correlations with rice qualities. Sci Agric Sin. 2008; 41: 370–80 (In Chinese with English abstract).
  20. 20. Criado MV, Caputo C, Roberts IN, Castro MA, Barneix AJ. Cytokinin-induced changes of nitrogen remobilization and chloroplast ultrastructure in wheat (Triticum aestivum). J Plant Physiol. 2009; 166: 1775–85. pmid:19540618
  21. 21. Lazova G, Yonova P. Photosynthetic parameters were modified in wheat (Triticum aestivum L.) flag leaves by two phenylurea cytokinin. Inter J Plant Sci. 2010; 171: 809–17.
  22. 22. Liang ZX, and M XL.Studies on the effects of endogenous hormones on tiller development process of winter wheat. Acta Agron Sin. 1998; 24: 788–92 (In Chinese with English abstract).
  23. 23. Wei YM, Zheng YL. The influence of phytohormone on the duration of spike differentiation in multi spikelet wheat. J Triticeae Crops. 2000; 20: 35–8 (In Chinese with English abstract).
  24. 24. Wang ZL, Cao WX, Dai TB. Changes of endogenous plant hormones and soluble sugars and proteins during floret development and degeneration in wheat. Acta Agron Sin. 2001; 27 (4): 447–52 (In Chinese with English abstract).
  25. 25. Xu LN, Feng W, Sheng K, Zhu YJ, Ma DY and Guo TC. Difference of endogenous hormones in leaves between main stem and tillers and its effect on spike formation in large spike winter wheat cultivar lankao Aizao 8 under different plant densities. Acta Agron Sin. 2010; 36: 1596–604 (In Chinese with English abstract).
  26. 26. McGaw BA and Horgan R. Cytokinin catabolism and cytokinin oxidase. Phytochemistry. 1983; 22: 1103–5.
  27. 27. Ashikari M, Sakakibara H, Lin SY, Yamamoto T, Takashi T, Nishimura A, et al. Cytokinin oxidase regulates rice grain production. Science. 2005; 309: 741–5. pmid:15976269
  28. 28. Zalewski W, Galuszka P, Gasparis S, Orczyk W and Nadolska-Orczyk A. Silencing of the HvCKX1 gene decreases the cytokinin oxidase/dehydrogenase level in barley and leads to higher plant productivity. J Exp Bot. 2010; 61: 1839–51. pmid:20335409
  29. 29. Zhang JP, Liu WH, Yang XM, Gao AN, Li XQ, Xiaoyang Wu XY, Li LH. Isolation and characterization of two putative cytokinin oxidase genes related to grain number per spike phenotype in wheat. Mol Biol Rep. 2011; 38: 2337–47. pmid:21104150
  30. 30. Zhang L, Zhao YL, Gao LF, Zhao GY, Zhou RH, Zhang BS, and Jia JZ. TaCKX6-D1, the ortholog of rice OsCKX2, is associated with grain weight in hexaploid wheat. New Phytol. 2012; 195: 574–84. pmid:22670578
  31. 31. Galuszka P, Frébortová J, Werner T, Yamada M, Strnad M, Schmülling T, et al. Cytokinin oxidase/dehydrogenase genes in barley and wheat cloning and heterologous expression. Eur J Biochem. 2004; 271: 3990–4002. pmid:15479228
  32. 32. Feng DS, Wang HG, Zhang XS, Kong LR, Tian JC, Li XF (2008) Using an inverse PCR method to clone the wheat cytokinin oxidase/dehydrogenase gene TaCKX1. Plant Mol Biol Rep. 2008; 26:143–55.
  33. 33. Zhang L, Zhang BS, Zhou RH, Gao LF, Zhao GY, Song YX, and Jia JZ. Cloning and genetic mapping of cytokinin oxidase/dehydrogenase gene (TaCKX2) in wheat. Acta Agron Sin. 2007; 33:1419–25 (In Chinese with English abstract).
  34. 34. Ma X, Feng DS, Wang HG, Li XF, Kong LR. Cloning and expression analysis of wheat cytokinin oxidase/dehydrogenase gene TaCKX3. Plant Mol Biol Rep. 2011; 29: 98–105.
  35. 35. Zhang H, Tan GL, Yang LN, Yang JC, Zhang JH, Zhao BH. Hormones in the grains and roots in relation to post-anthesis development of inferior and superior spikelets in japonica/indica hybrid rice. Plant Physiol Biochem. 2008; 47: 195–204. pmid:19117763
  36. 36. Sun XY, Wu K, Zhao Y, Kong FM, Han GZ, Jiang HM, et al. QTL analysis of kernel shape and weight using recombinant inbred lines in wheat. Euphytica. 2009; 165: 615–24.
  37. 37. Dholakia BB, Ammiraju JSS, Singh H, Lagu MD, Roder MS, Rao VS, et al. Molecular marker analysis of kernel size and shape in bread wheat. Plant Breed. 2003; 122:392–5.
  38. 38. Wang RX, Hai L, Zhang XY, You GX, Yan CS, Xiao SH. QTL mapping for grain filling rate and yield-related traits in RILs of the Chinese winter wheat population Heshangmai×Yu8679. Theor Appl Genet. 2009; 118: 313–25. pmid:18853131
  39. 39. Kang HW, Cho YG, Yoon UH. A rapid DNA extraction method for RFLP and PCR analysis from a single dry seed. Plant Mol Biol Rep. 1998; 16:1–9.
  40. 40. Somers DJ, Isaac P, Edwards K. A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.). Theor Appl Genet. 2004; 109: 1105–14. pmid:15490101
  41. 41. Manly KF, Cudmore RH Jr, Meer JM. Map Manager QTX, cross-platform software for genetic mapping. Mamm Genome. 2001; 12: 930–2. pmid:11707780
  42. 42. Kosambi DD. The estimation of map distance from recombination values. Ann Eugen. 1994; 12: 172–5.
  43. 43. Zeng ZB. Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci. Proc Natl Acad Sci USA. 1993; 90: 10972–6. pmid:8248199
  44. 44. Hong YB, Li SX, Liu HY, Zhou GY, Chen XP, Wen SJ, et al. Correlation analysis of SSR markers and host resistance to Aspergillus flavus infection in Peanut (Arachis hypogaea L.). Mol Plant Breed. 2009; 7: 360–4 (In Chinese with English abstract).
  45. 45. Zhang HP, Chang C, You GX, Zhang XY, Yan CS, Xiao SH, et al. Identification of molecular markers associated with seed dormancy in mini core collections of Chinese wheat and landraces. Acta Agron Sin. 2010; 36: 1649–56.
  46. 46. Chang C, Zhang HP, Zhao QX, Feng JM, Si HQ, Lu J, et al. Rich allelic variations of Viviparous-1A and their associations with seed dormancy/pre-harvest sprouting of common wheat. Euphytica. 2011; 179: 343–53.
  47. 47. Paradkar MR & Marcotte WR. Changes in the wheat Em 5 'UTR affect reporter gene expression in vivo and in vitro. J Plant Physiol. 2001; 158: 929–34.
  48. 48. Kamo K, Kim AY, Park SH, Joung YH. The 5'UTR-intron of the Gladiolus polyubiquitin promoter GUBQ1 enhances translation efficiency in Gladiolus and Arabidopsis. BMC Plant Biol. 2012; 12 (79).
  49. 49. Monde RA, Greene JC, Stern DB. The sequence and secondary structure of the 3 '-UTR affect 3 '-end maturation, RNA accumulation, and translation in tobacco chloroplasts. Plant Mol Biol. 2000; 44: 529–42. pmid:11197327
  50. 50. Gandikota M, Birkenbihl RP, Hoehmann S, Cardon GH, Saedler H, Huijser P. The miRNA156/157 recognition element in the 3' UTR of the Arabidopsis SBP box gene SPL3 prevents early flowering by translational inhibition in seedlings. Plant J. 2007; 49: 683–93. pmid:17217458
  51. 51. Jia J, Yao P, Arif A, Fox PL. Regulation and dysregulation of 3 ' UTR-mediated translational control. Curr Opion Genet Develop. 2013; 23: 29–34.
  52. 52. Vignesh M, Nepolean T, Hossain F, Singh AK, Gupta HS. Sequence variation in 3'UTR region of crtRB1 gene and its effect on beta-carotene accumulation in maize kernel. J Plant Biochem Biotech. 2013; 22: 401–8.
  53. 53. Chang C, Zhang HP, Feng JM, Yin B, Si HQ, Ma CX. Identifying alleles of Viviparous-1B associated with pre-harvest sprouting in micro-core collections of Chinese wheat germplasm. Mol Breed. 2010; 25: 481–90.
  54. 54. Huang XQ, Kempf H, Ganal MW, Röder MS. Advanced backcross QTL analysis in progenies derived from a cross between a German elite winter wheat variety and a synthetic wheat (Triticum aestivum L.). Theor Appl Genet. 2004; 109: 933–43. pmid:15243706
  55. 55. McCartney CA, Somers DJ, Humphreys DG, Lukow O, Ames N, Noll J, et al. Mapping quantitative trait loci controlling agronomic traits in the spring wheat cross RL4452 × 'AC Domain'. Genome. 2005; 48: 870–83. pmid:16391693
  56. 56. Quarrie SA, Steed A, Calestani C, Semikhodskii A, Lebreton C, Chinoy C, et al. A high-density genetic map of hexaploid wheat (Triticum aestivum L.) from the cross Chinese Spring×SQ1 and its use to compare QTLs for grain yield across a range of environments. Theor Appl Genet. 2005; 110: 865–80. pmid:15719212
  57. 57. Narasimhamoorthy B, Gill BS, Fritz AK, Nelson JC, Brown-Guedira GL. Advanced backcross QTL analysis of a hard winter wheat×synthetic wheat population. Theor Appl Genet. 2006; 112: 787–96. pmid:16463062
  58. 58. Kumar N, Kulwal PL, Balyan HS, Gupta PK. QTL mapping for yield and yield contributing traits in two mapping populations of bread wheat. Mol Breed. 2007; 19: 163–77.
  59. 59. Su ZQ, Hao CY, Wang LF, Dong YC, Zhang XY. Identification and development of a functional marker of TaGW2 associated with grain weight in bread wheat (Triticum aestivum L.). Theor Appl Genet. 2011; 122: 211–23. pmid:20838758
  60. 60. Bednarek J, Boulaflous A, Girousse C, Ravel C, Tassy C, Barret P, et al. Down-regulation of the TaGW2 gene by RNA interference results in decreased grain size and weight in wheat. J Exp Bot. 2012; 63 (16): 5945–55. pmid:22996678
  61. 61. Zhang XY, Chen JS, Shi CL, Chen JN, Zheng FF, Tian JC. Function of TaGW2-6A and its effect on grain weight in wheat (Triticum aestivum L.). Euphytica. 2013; 192: 347–57.
  62. 62. Zhang YJ, Liu JD, Xia XC, He ZH. TaGS-D1, an ortholog of rice OsGS3, is associated with grain weight and grain length in common wheat. Mol Breeding. 2014; 34: 1097–107.
  63. 63. Yue AQ, Li A, Mao XG, Chang XP, Li RZ, Jing RL. Identification and development of a functional marker from 6-SFT-A2 associated with grain weight in wheat. Mol Breeding. 2015; 35: 63.