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. 2015 Oct 19;14(5):1269–1280. doi: 10.1111/pbi.12492

TaGS5‐3A, a grain size gene selected during wheat improvement for larger kernel and yield

Lin Ma 1,2,†, Tian Li 2,†, Chenyang Hao 2, Yuquan Wang 2, Xinhong Chen 1,✉, Xueyong Zhang 2,✉
PMCID: PMC11389196  PMID: 26480952

Summary

Grain size is a dominant component of grain weight in cereals. Earlier studies have shown that OsGS5 plays a major role in regulating both grain size and weight in rice via promotion of cell division. In this study, we isolated TaGS5 homoeologues in wheat and mapped them on chromosomes 3A, 3B and 3D. Temporal and spatial expression analysis showed that TaGS5 homoeologues were preferentially expressed in young spikes and developing grains. Two alleles of TaGS5‐3A, TaGS5‐3A‐T and TaGS5‐3A‐G were identified in wheat accessions, and a functional marker was developed to discriminate them. Association analysis revealed that TaGS5‐3A‐T was significantly correlated with larger grain size and higher thousand kernel weight. Biochemical assays showed that TaGS5‐3A‐T possesses a higher enzymatic activity than TaGS5‐3A‐G. Transgenic rice lines overexpressing TaGS5‐3A‐T also exhibited larger grain size and higher thousand kernel weight than TaGS5‐3A‐G lines, and the transcript levels of cell cycle‐related genes in TaGS5‐3A‐T lines were higher than those in TaGS5‐3A‐G lines. Furthermore, systematic evolution analysis in diploid, tetraploid and hexaploid wheat showed that TaGS5‐3A underwent strong artificial selection during wheat polyploidization events and the frequency changes of two alleles demonstrated that TaGS5‐3A‐T was favoured in global modern wheat cultivars. These results suggest that TaGS5‐3A is a positive regulator of grain size and its favoured allele TaGS5‐3A‐T exhibits a larger potential application in wheat high‐yield breeding.

Keywords: TaGS 5, Serine carboxypeptidase, Grain size, Breeding selection, Triticum spp.

Introduction

Cereals, dominated by wheat, rice and maize, directly provide about 50% of human food calories. Increased cereal yield is one of the most important goals in breeding as worldwide demand for food increases and farmland resources decrease (Fischer and Edmeades, 2010). Grain weight, a major component of yield, is mainly determined by grain size and the degree of grain filling (Brocklehurst, 1977). In the last decade, functional genomic research in rice has promoted our understanding of grain size, and genes associated with grain size/weight were isolated through quantitative genetic studies and map‐based cloning (Zuo and Li, 2014). These genes are involved in the regulation of cell expansion and cell division, presumably via three major pathways, including ubiquitination‐mediated proteasomal degradation (GW2 and GW5/qSW5), G‐protein signalling (GS3 and DEP1), phytohormones (TGW6, CKX2 and GS6) and other unknown pathways (GS5 and GW8) (Huang et al., 2009; Ishimaru et al., 2013; Li et al., 2011, 2013; Mao et al., 2010; Shomura et al., 2008; Song et al., 2007; Sun et al., 2013; Wang et al., 2012).

So far, numerous quantitative trait loci (QTLs) associated with grain size/weight have been identified in tetraploid wheat (Blanco et al., 2001; Patil et al., 2013) and hexaploid wheat (Breseghello and Sorrells, 2006; Gegas et al., 2010), whereas it is difficult to directly isolate yield‐related genes by map‐based cloning strategies due to its huge and complex genome. Comparative genomics provides a possibility for cloning conserved genes among different cereals based on the gene synteny (Gale and Devos, 1998). Recently, a few wheat genes related to grain size/weight were successfully cloned using comparative genomics. For example, wheat sucrose synthase gene, TaSus1, was cloned and characterized, and the favoured haplotype of TaSus1 was closely correlated with higher thousand kernel weight (TKW) in two environments (Hou et al., 2014). TaGW2, an ortholog of rice OsGW2, was cloned and shown to be a negative regulator of TKW through RNA interference (RNAi) (Hong et al., 2014; Su et al., 2011). Therefore, in combination with completion of a draft wheat genome sequence (Brenchley et al., 2012; Jia et al., 2013; Ling et al., 2013), homology‐based cloning has become an efficient way to isolate grain size/weight genes in wheat.

Serine carboxypeptidases (SCPs), members of the α/β hydrolase proteins in the S_10 protein family, have been identified in a wide array of organisms (Breddam, 1986). Studies show that SCPs participate in various biological processes including mobilization of storage proteins (Degan et al., 1994), response to wounding (Moura et al., 2001), brassinosteroid‐insentive 1 (BRI1) signalling (Li et al., 2001), development of plant organs (Cercos et al., 2003; Dominguez et al., 2002), control of cell division (Li et al., 2011) and cell elongation (Bienert et al., 2012). For instance, OsGS5, a rice grain size gene that encodes a putative serine carboxypeptidase, was identified as a positive modulator upstream of the cell cycle genes. It promotes cell division by regulating cell cycle genes resulting in large grain size generated by an increased cell number (Li et al., 2011).

In this study, we cloned and characterized the wheat TaGS5 orthologs located on homoeologous group 3 chromosomes. Two alleles were identified in TaGS5‐3A, and the favoured or preferred one, TaGS5‐3A‐T, was associated with larger grain size and higher grain weight. Further study indicated that TaGS5‐3A‐T had higher enzymatic activity than its TaGS5‐3A‐G allele and as a consequence, might confer a stronger effect in promoting cell division. We recognized that the favoured allele, TaGS5‐3A‐T, which was the most frequent allele of TaGS5‐3A in wheat cultivars globally, had undergone strong positive selection in wheat breeding. Moreover, a functional marker was developed to distinguish the two alleles, providing a tool for marker‐assisted selection.

Results

TaGS5 homoeologues are located on group 3 chromosomes

Based on the conserved sequences of OsGS5 (GenBank No. AEO37081.1) and orthologous genes in other species, primers TaGS5F/R were designed to amplify the TaGS5‐3A and TaGS5‐3D genomic and coding sequences (CDSs) from genomic DNA and mixed cDNA from Chinese Spring (Table S1). TaGS5‐3B genomic and CDS were obtained from wheat 3BSEQ (http://wheat-urgi.versailles.inra.fr/Projects/3BSeq) under accession numbers traes3bPseudomoleculeV1 and TRAES3BF152800010CFD_t1. The structures of the TaGS5 homoeologues were determined by aligning the genomic sequences and their corresponding CDSs (Figure 1). Both TaGS5‐3A and TaGS5‐3D consisted of ten exons and nine introns; their genomic sequence lengths were 3611 and 3705 bp, respectively, and CDSs were both 1446 bp, encoding putative 482 aa serine carboxypeptidases. Unexpectedly, the genomic structure of TaGS5‐3B was quite different from those of TaGS5‐3A and TaGS5‐3D due to large sequence insertions. TaGS5‐3B consists of seven exons and six introns, is 14 790 bp in length, and its CDS is 2625 bp, encoding a putative serine carboxypeptidase with 875 aa. These putative serine carboxypeptidases encoded by the TaGS5 homoeologues belong to the Peptidase_S10 family with a conserved pfam00450 domain (http://blast.ncbi.nlm.nih.gov/Blast.cgi) (Figure S1).

Figure 1.

Figure 1

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Exon–intron structure of the three TaGS5 homoeologues in Chinese Spring. Solid blocks indicate exons; lines between exons represent introns. Numbers under exons and introns denote size (bp).

The chromosomal locations of the TaGS5 homoeologues were determined in a set of Chinese Spring nulli‐tetrasomic lines using genome‐specific primers designed from sequence differences (Table S1). The TaGS5 homoeologues were located on chromosomes 3A, 3B and 3D, and designated as TaGS5‐3A, ‐3B and ‐3D, respectively (Figure S2).

TaGS5 homoeologues were preferentially expressed in young spikes and developing grains

We investigated the temporal and spatial expression patterns of the TaGS5 homoeologues through quantitative real‐time PCR (qRT‐PCR) using genome‐specific primers (Table S1). The homoeologues were ubiquitously expressed with similar patterns in various tissues (Figure 2), but showed higher expression in tender tissues such as seedlings, young spikes and developing grains than in established roots, stems and flag leaves at the heading stage. Expression of the TaGS5 homoeologues during grain development showed maximum levels in grains at 3 days postanthesis (DPA), and then gradually declined until 25 DPA. Thus, higher expression of TaGS5 homoeologues occurred in tender tissues might suggest a role in cell proliferation.

Figure 2.

Figure 2

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Temporal and spatial expression of TaGS5 homoeologues. SL, seedling leaf; SR, seedling root; HR, root at the heading stage; HS, stem at the heading stage; FL, flag leaf; 1 YS, 3 YS, 5 YS and 7 YS, young spikes of 1 cm, 3 cm, 5 cm and 7 cm in length; SP, spike at heading stage; various stages of grain development, including 1 DPA, 3 DPA, 5 DPA, 10 DPA, 15 DPA, 20 DPA and 25 DPA. The expression of TaGS5‐3A in the spike at heading stage was assumed to be 1.

Although TaGS5‐3A, TaGS5‐3B and TaGS5‐3D showed similar expression patterns, they had significantly different expression abundances (Figure 2). Compared to TaGS5‐3A and TaGS5‐3D, TaGS5‐3B was expressed at a much lower level. We therefore focused on characterization of TaGS5‐3A and TaGS5‐3D in the remainder of this study.

A SNP (G/T) at 2334 bp in TaGS5‐3A had a strong effect on grain size and TKW

To detect sequence variations of TaGS5‐3A, we analysed the coding and promoter regions in 36 Chinese wheat accessions varying in multiple grain traits (Table S2). Only one SNP (T/G) was identified at 2334 bp downstream of the ATG start codon in the sixth exon, and a cleaved amplified polymorphic site (CAPS) marker was developed based on the SNP (Figure 3a). Restriction endonuclease Fnu4HI cleaved the sequence only when the SNP site was G (Figure 3b). The PCR product of TaGS5‐3A‐T amplified by the genomic‐specific primer pair TaGS5‐3A‐CAPSF/R was 863 bp, whereas those of TaGS5‐3A‐G were 718 bp and 145 bp after enzyme digestion (Figure 3c). This CAPS marker was used for genetic mapping in a Xiaoyan 54 × Jing 411 recombinant inbred line (RIL) population (Ren et al., 2012), and TaGS5‐3A was mapped in a chromosome 3AS region flanked by barc67 (1.4 cM distal) and wmc388.1 (1.1 cM proximal) (Figure S3).

Figure 3.

Figure 3

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A CAPS marker based on SNP T/G in TaGS5‐3A. (a) The T/G SNP at 2334 bp is marked. (b) Sequences flanking the SNP in two different alleles. The rectangle and arrow represent recognition digestion sites of restriction endonuclease Fnu4HI. (c) PCR products restrictively digested by Fnu4HI.

After genotyping the Chinese mini‐core collection (MCC) (Table S3), a suitable population for detection of major QTLs controlling yield traits (Hao et al., 2008), with the developed CAPS marker, we performed an association analysis between phenotypes and genotypes, and significant differences were detected in grain traits including 1000‐kernel weight (TKW), kernel length (KL), kernel width (KW) and kernel thickness (KT) between TaGS5‐3A‐T and TaGS5‐3A‐G in both landraces and modern cultivars in MCC (Table 1). In landraces, TaGS5‐3A‐T exhibited a significantly higher TKW than TaGS5‐3A‐G in all three environments (P < 0.01), and the phenotypic differences between the two alleles were 6.28, 7.81 and 6.65 g in 2002, 2005 and 2010, respectively (Table 1). These differences likely resulted from significant differences in grain size components (KL, KW and KT), which were significantly larger in TaGS5‐3A‐T (P < 0.01, except for KW in 2002 and KT in 2010). In modern cultivars, the differences between the two alleles were not as significant as in landraces, and significant differences were detected in only two environments (P < 0.05) (Table 1). These less significant differences might be due to the smaller number of modern cultivars (Table S3). Compared with that, we used a larger scale of modern cultivars (MC) (Table S3) (Hao et al., 2008) to confirm it and significant differences in TKW were present among modern cultivars in three environments (P < 0.01) (Table 1). The mean differences between the two alleles were 3.3, 2.3 and 2.3 g in 2002, 2005 and 2010, respectively (Table 1). Although the differences in kernel size were significant only in 2005, the mean kernel size of TaGS5‐3A‐T was larger than that of TaGS5‐3A‐G in all 3 years (Table 1).

Table 1.

Grain traits' comparisons between TaGS5‐3A‐T and TaGS5‐3A‐G in Chinese mini‐core collection (MCC) and modern cultivars (MC) in three environments

2002LY 2005LY 2010SY
TaGS5‐3A‐T TaGS5‐3A‐G P value TaGS5‐3A‐T TaGS5‐3A‐G P value TaGS5‐3A‐T TaGS5‐3A‐G P value
Landraces (MCC)
TKW (g) 39.10 ± 2.03 32.82 ± 0.54 0.000** 37.35 ± 1.79 29.54 ± 0.46 0.000** 38.07 ± 1.79 31.42 ± 0.44 0.000**
KL (mm) 0.67 ± 0.02 0.62 ± 0.00 0.001** 0.67 ± 0.01 0.62 ± 0.00 0.001** 0.70 ± 0.01 0.65 ± 0.00 0.000**
KW (mm) 0.31 ± 0.01 0.29 ± 0.00 0.077 0.31 ± 0.00 0.29 ± 0.00 0.000** 0.31 ± 0.00 0.30 ± 0.00 0.005**
KT (mm) 0.28 ± 0.01 0.26 ± 0.00 0.001** 0.29 ± 0.01 0.27 ± 0.00 0.000** 0.29 ± 0.00 0.29 ± 0.00 0.162
Modern cultivars (MCC)
TKW (g) 41.99 ± 0.77 39.15 ± 1.26 0.045* 38.60 ± 0.83 36.23 ± 1.09 0.096 40.24 ± 0.81 36.69 ± 1.19 0.013*
KL (mm) 0.66 ± 0.01 0.66 ± 0.01 0.624 0.67 ± 0.00 0.66 ± 0.00 0.200 0.69 ± 0.00 0.68 ± 0.00 0.265
KW (mm) 0.33 ± 0.00 0.32 ± 0.00 0.446 0.32 ± 0.00 0.31 ± 0.00 0.169 0.32 ± 0.00 0.31 ± 0.00 0.142
KT (mm) 0.28 ± 0.00 0.27 ± 0.00 0.146 0.29 ± 0.00 0.29 ± 0.00 0.579 0.29 ± 0.00 0.29 ± 0.00 0.760
Modern cultivars (MC)
TKW (g) 43.58 ± 0.44 40.29 ± 0.76 0.000** 40.77 ± 0.40 37.07 ± 0.72 0.000** 40.71 ± 0.38 38.41 ± 0.67 0.001**
KL (mm) 0.67 ± 0.00 0.67 ± 0.00 0.616 0.69 ± 0.00 0.68 ± 0.00 0.033* 0.69 ± 0.00 0.68 ± 0.00 0.112
KW (mm) 0.34 ± 0.00 0.33 ± 0.00 0.136 0.33 ± 0.00 0.32 ± 0.00 0.003** 0.33 ± 0.00 0.32 ± 0.00 0.039*
KT (mm) 0.29 ± 0.00 0.29 ± 0.00 0.711 0.29 ± 0.00 0.28 ± 0.00 0.028* 0.31 ± 0.00 0.30 ± 0.00 0.161
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TKW, thousand kernel weight; KL, kernel length; KW, kernel width; KT, kernel thickness; 2002LY, Luoyang (2002); 2005LY, Luoyang (2005); 2010SY, Shunyi (2010).

*P < 0.05, **P < 0.01.

The MCC and MC populations were verified successfully in candidate gene‐based association analysis (Hou et al., 2014; Su et al., 2011). To verify the results in the genetic populations, we tested an F3:5 segregating population derived from the cross Shi 4185 × Shijiazhuang 8 (Wang et al., 2015). The results showed that TaGS5‐3A‐T was associated with higher TKW not only in the germplasms examined, but also in the segregating population. The mean TKW of TaGS5‐3A‐T and TaGS5‐3A‐G over three environments in modern cultivars were 41.69 and 38.59 g (Figure 4a), and the mean TKW of TaGS5‐3A‐T over four environments was significantly higher than that of TaGS5‐3A‐G (45.41 g in TaGS5‐3A‐T, 43.74 g in TaGS5‐3A‐G) (Figure 4b). These various results confirmed that TaGS5‐3A‐T is a favoured allele of TaGS5‐3A associated with larger grain size and higher TKW.

Figure 4.

Figure 4

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TKW comparisons of TaGS5‐3A‐T and TaGS5‐3A‐G in two different populations. (a) A population of 344 modern cultivars. (b) An F3:5 segregation populations derived from Shijiazhuang 8 × Shi 4185. Letters on the boxes indicate significant differences between the alleles at P < 0.01.

Furthermore, we also found a SNP (T/C) at 3533 bp downstream of the ATG start codon in the last intron in TaGS5‐3D and a CAPS marker was developed to discriminate two alleles of TaGS5‐3D (Figure S4). Association analysis detected no significant difference in TKW or grain size between TaGS5‐3D‐T and TaGS5‐3D‐C in MCC or in MC (data not shown).

The mis‐sense mutation caused by SNP (G/T) led to a significant difference in enzymatic activity

To explore reasons for the phenotypic differences between TaGS5‐3A‐T and TaGS5‐3A‐G, their protein products were aligned (Figure S5). The SNP (T/G) at 2334 bp is a mis‐sense mutation causing a substitution of alanine (ALA) by serine (SER). We predicted the structures and functional features of the two proteins by PredictProtein (https://www.predictprotein.org/) and found that substitution of ALA by SER caused changes in protein‐binding regions (Figure S6), suggesting that different binding characteristics between TaGS5‐3A‐T and TaGS5‐3A‐G may cause variations in enzyme activity.

To confirm this hypothesis, we expressed TaGS5‐3A‐T and TaGS5‐3A‐G in Schizosaccharomyces pombe (S. pombe) using the pREP1 vector as reported (Maundrell, 1990). The S. pombe carrying pREP1‐TaGS5‐3A‐T or pREP1‐TaGS5‐3A‐G exhibited higher total serine carboxypeptidase activities than the pREP1 vector control (Figure 5a), confirming that TaGS5‐3A is actually a serine carboxypeptidase in wheat. The total activity for TaGS5‐3A‐T was approximately 50% higher than that for TaGS5‐3A‐G (Figure 5a). Similar results were obtained using T2 generation transgenic rice lines (Figure 5b). These results indicated that the mis‐sense mutation in TaGS5‐3A affected serine carboxypeptidase activity and that TaGS5‐3A‐T conferred higher activity than TaGS5‐3A‐G.

Figure 5.

Figure 5

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Enzyme activities of TaGS5‐3A‐T and TaGS5‐3A‐G. Allele‐T and Allele‐G represent pREP1:TaGS5‐3A‐T and pREP1:TaGS5‐3A‐G, respectively. Allele‐T (OE) and Allele‐G (OE) represent transgenic lines overexpressing TaGS5‐3A‐T and TaGS5‐3A‐G, respectively. (a) Enzyme activity of total protein in S. pombe. (b) Enzyme activity of total protein in transformed rice.

Overexpression of TaGS5‐3A in rice showed increased grain size and TKW by affecting genes in the cell cycle

As reported previously (Li et al., 2011), OsGS5 is a yield‐related gene controlling grain size and weight. The high homology of OsGS5 and TaGS5‐3A suggests a similar function (Figure S1). To confirm this, we transformed TaGS5‐3A‐T and TaGS5‐3A‐G into rice under control of an endosperm‐specific promoter cloned from the wheat HMW‐GS gene 1Bx7 OE (Geng et al., 2014). Grain trait analyses of two transgenic lines showed that T2 TaGS5‐3A (OE) lines (transgenic lines overexpressing TaGS5‐3A) had increased grain size and TKW compared to wild type (Figure 6, Table 2). Moreover, TKW, KL and KW of TaGS5‐3A‐T (OE) lines were clearly superior to TaGS5‐3A‐G (OE) lines (Figure 6, Table 2), providing further evidence that TaGS5‐3A‐T is a favoured allele of TaGS5‐3A in regard to yield.

Figure 6.

Figure 6

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Grain traits of transgenic lines. (a) Grains of wild type and transgenic rice. Comparisons between wild type and two transgenic lines; (b) TKW, (c) KL, (d) KW. Different capital and small letters indicate significant differences at P = 0.01 (A, B, C) and P = 0.05 (a, b), respectively.

Table 2.

Grain traits' comparisons between rice transgenic lines and wild type

TKW (g) KL (mm) KW (mm)
WT 23.92 ± 0.29A 6.76 ± 0.03A 3.33 ± 0.02A
Allele‐T (OE) 27.16 ± 0.33B 7.27 ± 0.06B 3.62 ± 0.04Ba
Allele‐G (OE) 25.90 ± 0.24C 7.16 ± 0.05B 3.43 ± 0.02Bb
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Allele‐T (OE) and allele‐G (OE) represent transgenic lines overexpressing TaGS5‐3A‐T and TaGS5‐3A‐G, respectively.

TKW, thousand kernel weight; KL, kernel length; KW, kernel width.

Different capital and small letters indicate significant differences at P = 0.01 and P = 0.05, respectively.

TaGS5‐3A was classified as a type II serine carboxypeptidase (Figure S1), whose functions are closely related to cell division (Li et al., 2011). The expression pattern of TaGS5‐3A also implied that it might play a role in rapid cell proliferation similar to its ortholog in rice (Figure 2). We therefore investigated the expression levels of 20 genes involved in the cell cycle in the TaGS5‐3A transgenic lines. As expected, the transcript levels of 7 genes, viz. H1, CYCLazm, CYCT1, CAK1A, CYCA2.1, MCM4 and CYCB2.1, were significantly elevated in the transgenic lines compared to wild type (Figure 7). Except for MCM4, these genes in the TaGS5‐3A‐T (OE) lines showed consistently higher expression levels than those in TaGS5‐3A‐G (OE) lines, although not all differences between them were statistically significant (Figure 7). These results suggested that TaGS5‐3A positively regulates grain size by promoting cell division, and that the favoured allele TaGS5‐3A‐T is more effective than the alternative allele in regulating genes involved in the cell cycle.

Figure 7.

Figure 7

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Relative expression levels of OsGS5, TaGS5 and cell cycle genes in wild type and transgenic lines. Different capital and small letters indicate significant differences at P = 0.01 and P = 0.05, respectively.

TaGS5‐3A‐T is favoured in global wheat breeding and has undergone strong positive selection

Previous studies have illustrated that favoured alleles progressively accumulate by breeding (Barrero et al., 2011). To determine whether the favoured allele TaGS5‐3A‐T was selected in wheat breeding, we investigated the geographic distribution of TaGS5‐3A‐T and TaGS5‐3A‐G in Chinese wheat landraces and current modern cultivars in Chinese wheat production area. The results showed that TaGS5‐3A‐T was positively selected in breeding (Figure 8a,b), especially in production zones I, II and III, main production zones in China (Zhang et al., 2002). This demonstrated that TaGS5‐3A‐T has undergone stronger artificial selection in the areas that have stronger and more prolonged breeding histories. Further evidence showing that TaGS5‐3A‐T underwent strong positive selection in Chinese wheat breeding is provided in Figure 9. The frequency of TaGS5‐3A‐T showed a continuous increase consistent with increasing TKW since the 1940s (Hao et al., 2008) (Figure 9). This selection occurred earlier in Europe and North America where the favoured allele dominated even in the 1940s (data not shown).

Figure 8.

Figure 8

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Distributions of TaGS5‐3A‐T and TaGS5‐3A‐G alleles in different ecological regions; (a) 154 landraces from 10 Chinese ecological zones; (b) modern cultivars in 10 Chinese ecological zones; (c) global wheat cultivars from I, North America; II, CIMMYT; III, Europe; IV, former USSR; V, China; VI, Australia.

Figure 9.

Figure 9

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Frequencies of TaGS5‐3A‐T, TaGS5‐3A‐G and TKW changes over decades in Chinese modern cultivars from the 1940s to 1990s.

To evaluate the global geographic distribution of the two alleles, their frequencies were determined in cultivar collections from North America, CIMMYT, Europe, former USSR, China and Australia (Figure 8c). The frequencies of TaGS5‐3A‐T in the six regions were 69.9%, 26.4%, 77.7%, 60.2%, 67.7% and 38.7%, respectively. The favoured allele appeared to be more frequent in North America, Europe, China and former USSR. The likely explanation for the lower frequencies in CIMMYT and Australian materials is that the strategies for achieving higher yields might be different from other regions because of relatively limited water resources (Jiang et al., 2015). The results demonstrated that TaGS5‐3A‐T was the predominant allele of TaGS5‐3A in global wheat cultivars and selection pressures on TaGS5‐3A‐T differed in degree in different regions of the world.

The diversity of TaGS5‐3A dramatically declined during wheat polyploidization events

To survey the evolutionary history of TaGS5‐3A, we analysed TaGS5‐3A in wheat progenitor accessions. The results showed that during both polyploidization events, diversity in TaGS5‐3A dramatically declined (Table 3). Sequence similarities in TaGS5‐3A among diploids, tetraploids and hexaploid landraces were 99.72%, 99.88% and 99.97%, respectively. Nucleotide diversity (π) in hexaploid landraces was 0.06 × 10−3, approximately one‐thirteenth of that in tetraploids (0.8 × 10−3); the π value in tetraploids was one‐third that of diploids (2.21 × 10−3) (Figure 10a). Furthermore, genetic differentiation (F ST) was 0.828 between diploids and hexaploid landraces, 0.557 between diploids and tetraploids, and 0.381 between tetraploids and hexaploid landraces (Figure 10b). Moreover, the F ST between hexaploid landraces and wild tetraploids was 0.926, much higher than that between hexaploid landraces and cultivated tetraploids (0.303) (Figure S7), indicating that selection on TaGS5‐3A had occurred during domestication of tetraploids. The haplotype diversity (Hd) of TaGS5‐3A was 0.227 in hexaploid landraces, much lower than in diploids (0.913) and tetraploids (0.709). Compared to landraces, nucleotide and haplotype diversity in modern cultivars had slightly increased (Table 3, Figure 10), probably reflecting the wide geographic sources of germplasm used by present‐day breeders (Cornille et al., 2012). These results confirmed that TaGS5‐3A underwent selection during each polyploidization event (Hou et al., 2014; Lin et al., 2014).

Table 3.

Diversity in TaGS5‐3A among diploid, tetraploid and hexaploid (landraces and modern cultivars) wheat accessions

S Hd π Hap Sequence similarity (%) Frequency of (T) at mutation site (%)
Diploid 26 0.913 0.00221 12 99.76 0
Tetraploid 19 0.709 0.0008 12 99.88 5.76
Hexaploid (landraces) 1 0.227 0.00006 2 99.72 12.98
Hexaploid (modern cultivars) 1 0.438 0.00012 2 99.72 67.73
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S, number of polymorphic sites; Hd, haplotypes (gene) diversity; π, nucleotide diversity; Hap, number of haplotypes.

Figure 10.

Figure 10

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Nucleotide diversity (π) and genetic distances at TaGS5‐3A between diploid, tetraploid and hexaploid accessions (a) nucleotide diversity (π) (b) genetic distances between pairs of populations ( F ST ). DI, diploids; TE, tetraploids; LA, landraces; MC, modern cultivars; the colour gradient presents F ST values from dark (1.0) to light grey (0.0), and P values between populations were <0.05.

Haplotype relationships were also analysed by Network 4.5 (www.fluxus-engineering.com), and the result was shown in Figure 11. Eleven haplotypes in diploids formed two subgroups separately containing Triticum urartu and einkorn accessions, and 13 haplotypes detected in tetraploids, hexaploids and T. urartu clustered into a third subgroup, indicating that T. urartu was indeed the direct donor of the A genome in polyploid wheat. TaGS5‐3A‐T (Hap‐17), derived from a mis‐sense mutation at 2334 bp in TaGS5‐3A‐G (Hap‐16), had a frequency of 5.88% in tetraploid wheat, and its frequency increased to 12.98% in hexaploid landraces, but after 100 years of breeding, it was 67.73%, indicating strong selection at this locus during wheat improvement (Table 3, Figure 11). The network also showed dramatic reductions in numbers of haplotypes at TaGS5‐3A during polyploidization.

Figure 11.

Figure 11

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Haplotype networks of TaGS5‐3A. Colours represent different species. Each cycle represents a haplotype and the cycle size is proportional to the number of accessions for a given haplotype. Lines between haplotypes indicate likely mutational steps.

Discussion

TaGS5‐3A might regulate grain size through promoting cell division in the early stage of grain development

OsGS5, a putative serine carboxypeptidase, was shown to positively regulate grain size by increasing cell number. Transgenic lines overexpressing OsGS5 had increased grain width and grain weight compared to wild type and the expression levels of genes regulating the cell cycle were significantly elevated in transgenic lines, demonstrating that OsGS5 putatively functions as a positive modulator upstream of the cell cycle genes, and that it promotes cell division by regulating the cell cycle genes (Li et al., 2011). In this research, we cloned and characterized TaGS5‐3A, an ortholog of rice OsGS5, and the high homology of OsGS5 and TaGS5‐3A suggested similar functions (Figure S1). Transgenic rice overexpressing TaGS5‐3A exhibited larger grain size and higher TKW than wild type and the expression levels of some genes involved in cell cycle in transgenic lines were also elevated above those in wild type (Figures 6 and 7). Combined with its expression pattern in wheat (Figure 2), TaGS5‐3A may be a positive regulator of cell division during endosperm development, similar to its rice ortholog.

In rice, diversity in OsGS5 occurs in both the promoter and coding regions. Phenotypic variation in that species was caused by different expression levels of OsGS5 resulting from polymorphisms in the promoter region (Li et al., 2011). Similar regulatory patterns have been observed in some other yield‐related genes (Zuo and Li, 2014). A good example is that polymorphisms in the promoter regions of TaGW2‐6A and TaGW2‐6B affected their expression levels and were associated with variation in TKW over two environments (Qin et al., 2014; Su et al., 2011). A SNP in the promoter region of maize ZmGW2‐CHR4 was significantly associated with KW and hundred kernel weight (HKW), but the expression level in that case was negatively correlated with KW (Li et al., 2010). In the present work variation in grain characteristics was caused by a mis‐sense mutation in the sixth exon of TaGS5‐3A (Figure 3). The mutation resulted in two alleles with different enzymatic activities. TaGS5‐3A‐T with higher enzymatic activity had a stronger effect on grain development than TaGS5‐3A‐G, as verified in association analysis and transformation assays (Table 1, Figures 4 and 6). A similar example was identified in TaSus1‐7A where TaSus1‐7A‐Hap‐5 caused by a mutation exhibited lower enzyme activity than other haplotypes at the same locus with the mutation conferring smaller grain and being negatively selected in wheat breeding (Hou et al., 2014).

TaGS5‐3A‐T has undergone strong selection in wheat improvement

Common wheat has undergone selection by humans for about 8000 years since it arose by natural hybridization between wild tetraploid wheat (AB) and the diploid Ae. tauschii (D). Earlier, a spontaneous amphiploidization between diploid wild wheat T. urartu (A) and an unidentified diploid Aegilops species (B) resulted in the allotetraploid Triticum dicoccoides (AB) (Doebley et al., 2006; Marcussen et al., 2014). During domestication and improvement, common wheat experienced strong selection that reduced genetic diversity compared to its wild ancestors, especially for genes controlling agronomic traits (Haudry et al., 2007).

Evolution analysis on OsGS5 in rice showed different patterns in subspecies indica and japonica. OsGS5‐1 and OsGS5‐3 were prevalent in indica, and OsGS5‐2 was predominated in japonica varieties, indicating that OsGS5 might have been more strongly selected during or following differentiation of indica and japonica (Lu et al., 2013). In the present day, we investigated TaGS5‐3A sequences among diploids, tetraploids and hexaploids to investigate the evolution events occurring within the gene. There were two instances of dramatic declines in nucleotide diversity (π) and haplotype diversity (Hd), and the high F ST value (Table 3, Figure 10) indicated that strong selection occurred at TaGS5‐3A during tetraploidization and hexaploidization. Meanwhile, the frequency of the favoured allele TaGS5‐3A‐T dramatically increased suggesting strong artificial selection on the locus during wheat breeding (Figures 8 and 9). Variation in allele frequency among the 10 Chinese ecological zones, as well as globally, reflects a history of breeding by selection for higher yield (Barrero et al., 2011). We conclude that TaGS5‐3A‐T was artificially selection in wheat improvement and consequently became the dominant allele in improved cultivars, indicating that GS5 had a parallel evolution in wheat and rice (Doebley et al., 2006; Meyer and Purugganan, 2013).

Potential application of the TaGS5‐3A molecular marker in selection for high TKW in wheat

Marker‐assisted selection (MAS) is a cost‐effective practice to bring about genetic improvement (Gupta et al., 2010). Recently, many functional markers for traits, including genes for stress resistance, protein content and quality, starch characteristics, vernalization response, height and other agronomic traits have been documented for variety development and germplasm enhancement through MAS (Liu et al., 2012).

In this study, a CAPS marker was developed to distinguish the two alleles of TaGS5‐3A, and accessions carrying TaGS5‐3A‐T exhibited significantly higher TKW than those carrying TaGS5‐3A‐G in both established germplasm and segregating populations (Figure 4). Although the frequency of TaGS5‐3A‐T was higher among modern cultivars globally, further increases are still feasible in regions where the allele occurs at lower frequencies, including Australia, CIMMYT and Chinese ecological zones V, VI and VII. Functional markers related to higher TKW so far reported are available for TaGW2‐6A‐Hap‐A, TaGW2‐6B‐Hap‐1, TaSus2‐2A‐Hap‐A and TaSus1‐7B‐Hap‐T (Hou et al., 2014; Qin et al., 2014; Su et al., 2011). As combinations of these favoured alleles or haplotypes usually show additive effects, selection based on multiple markers will be more effective than selection for single markers in yield improvement (Wang et al., 2012). This study provides an important functional marker for MAS in improving TKW, and it can be used alone or in combination with other markers.

Experimental procedures

Plant materials

Two Chinese wheat (Triticum aestivum L.) germplasm subpopulations comprising 251 accessions from the Chinese wheat mini‐core collection (MCC) and 344 modern cultivars released since the 1940s (Hao et al., 2008) were used for association studies of phenotypic traits and markers (Table S3). The MCC population consisted of 154 landraces, 82 modern cultivars and 15 introduced lines, representing 70.1% of the genetic diversity in the Chinese national collection of 23 100 accessions (Hao et al., 2008). Phenotypic traits for the two populations, including 1000‐kernel weight (TKW), kernel length (KL), kernel width (KW) and kernel thickness (KT), were measured on grains produced at Luoyang, Henan Province, in 2002 and 2005, and at Shunyi, Beijing, in 2010. A segregating population (F3:5) derived from Shi 4185 × Shijiazhuang 8 (Wang et al., 2015) was used for confirming the significant difference on TKW detected in the germplasm populations.

Four hundred and thirty‐three cultivars from North America, 53 from CIMMYT, 364 from Europe, 78 from the former USSR and 62 from Australia were used to investigate the geographic distribution of alleles (Table S4). These cultivars represent major cultivars released in the last century (Hou et al., 2014). For evolutionary studies, we used 22 diploid accessions with the A genome and 51 tetraploid accessions with genomes AB or AG (Table S5). A set of nulli‐tetrasomic lines of Chinese Spring was employed to determine the chromosomal location of TaGS5. Genetic mapping of TaGS5‐3A was carried out on a recombinant inbred line (RIL) population developed from Xiaoyan54 × Jing411 (Ren et al., 2012).

DNA and RNA extraction

Genomic DNA from all plant materials was extracted from young leaves by the CTAB method. Total RNA was extracted from various plant tissues using TIANGENRNA Plant Plus Reagent (Tiangen, Beijing, China). cDNA synthesized with the SuperScriptII system (Invitrogen, Madison, WI, USA) according to the manufacturer's instructions was diluted eight times for subsequent quantitative real‐time PCR (qRT‐PCR).

Primers and PCR amplification

All primers used in this study were designed by Primer Premier 5.0 software (http://www.premierbiosoft.com/) and are listed in Table S1. PCR was performed in total volumes of 15 μL, including 50 ng DNA, 1 μL 10 mm forward and reverse primers, 0.24 μL of 25 mm dNTP, 7.5 μL GC bufferI and 0.15 μL LA Taq polymerase (Takara, Dalian, China). For PCR, samples were incubated at 94 °C for 4 min, followed by 35 cycles of 94 °C for 35 s, annealing for 35 s and 72 °C for extension (30 s–3 min), with a final extension for 10 min. The annealing temperature and extension time depended on the primer sets and the length of PCR products.

Expression analysis

Quantitative real‐time PCR (qRT‐PCR) was carried out with SYBR Premix Ex‐Taq (Takara, Dalian, China) on a 7500 Real‐Time PCR system (Applied Biosystems, Foster City, CA, USA). RT‐PCR was performed in total volumes of 20 μL, containing 2 μL of cDNA, 1 μL 2 mm gene‐specific primers, 0.4 μL ROX Reference Dye (50×) and 10 μL of 2 × SYBR Premix Ex‐Taq. The relative expression of each gene is presented as a fold‐change calculated using the comparative C T method (Livak and Schmittgen, 2001). Each measurement was determined in at least two independent biological samples with three replicates for each sample.

SNP detection and functional marker development

Thirty‐six wheat cultivars were initially chosen for detecting sequence variation (Table S2). Genome‐specific fragments were cloned into the pEASY‐T1 simple vector and transformed to DH5α competent Escherichia coli cells according to the manufacturer's instructions (TransGen Biotech, Beijing, China). Positive clones were selected for sequencing on a 3730XI DNA Analyzer (Applied Biosystem). Sequence alignments were performed by DNAMAN (http://www.lynnon.com/), and SNPs were identified by DNASTAR (http://www.dnastar.com/). Development of a functional marker was based on the SNP. Briefly, genome‐specific fragments were amplified by the corresponding primers and then separated by electrophoresis in agarose gels after digestion by specific restriction end‐nucleases. All the restriction end‐nucleases used in this study were purchased from New England Biolabs (Beverly, MA, USA).

Enzyme assays

Serine carboxypeptidase activity assays were based on a previous method with some modification (Mikola, 1986). In brief, the reaction was started by addition of the specific substrate, 1.82 mm N‐benzyloxycarbonyl‐l‐alanyl‐l‐Arg (Synthesized by Sangon Biotech, Shanghai, China). After incubation for 100 min at 30 °C, the released C‐terminal Ala‐Arg was measured using 2,4,6‐trinitrobenzene sulphonic acid (TNBS) reagent, prepared by mixing three volumes of 5% sodium tetraborate with one volume of 0.2% TNBS. TNBS reagent (2 mL) was added to the samples, and the mixture was incubated for 1 h at 30 °C, followed by acidification by addition of 1 mL of 1 m acetic acid. The released C‐terminal amino acids Ala‐Arg were measured at 340 nm. A standard curve was produced using standard Ala‐Arg.

Expression of TaGS5‐3A in Schizosaccharomyces pombe

The coding sequences of TaGS5‐3A‐T and TaGS5‐3A‐G including the NdeI (5′) and BamHI (3′) restriction sites were first amplified. PCR products and pREP1 vector were digested with NdeI and BamHI, and then cloned into the binary pREP1 vector and verified by sequencing. Expression of the two alleles was induced in S. pombe in the absence of thiamine (‐thiamine) as reported (Maundrell, 1990). Total proteins were extracted and quantified according to the manufacturer's instructions (CWBIO, Beijing, China).

Transformation of TaGS5‐3A in rice

We overexpressed TaGS5‐3A‐T and TaGS5‐3A‐G driven by an endosperm‐specific vector in rice. To obtain the endosperm‐specific vector, we replaced the rice actin 1 promoter in a modified pCAMBIA2300 vector with an endosperm‐specific promoter that was cloned from the wheat high molecular weight glutenin subunit (HMW‐GS) 1Bx7OE (Geng et al., 2014). The coding sequences of the two alleles were introduced into the vector under control of the 1Bx7 OE promoter. The constructs were mobilized into Agrobacterium tumefacians strain EHA105 and then transferred into rice (Oryza sativa L. ssp. japonica) cv. Kitaake by Agrobacterium‐mediated transformation as described (Hiei et al., 1994). Phenotypic traits of T2 generation transgenic lines were measured on grains produced at Langfang, Hebei Province.

Statistical analyses

Variance analyses were performed on the SPSS System for Windows Version 12.0 (http://www-01.ibm.com/software/analytics/spss/). To determine phenotypic differences between genotypes, based on analysis of variance (one‐way ANOVA), we used the Tukey test at a significance level of P = 0.05. Genetic mapping of TaGS5 was performed with MAPMAKER/EXP 3.0 (Lander et al., 2009). Sequences were analysed by DNAMAN (http://www.lynnon.com/) software. Arleqiun 3.5.1.2 was used for determining genetic differentiation among populations by the (F ST) test (http://cmpg.unibe.ch/software/arlequin3/). Nucleotide diversities and haplotype variations were carried out by DnaSP 5.10 (http://www.ub.edu/dnasp/). Haplotype networks were constructed based on the TaGS5‐3A DNA sequences using the program Network 4.5 (www.fluxus-engineering.com).

Accession numbers

The accession numbers of sequences used in this study were listed in Table S6.

Supporting information

Figure S1 Clustering analysis of TaGS5 as well as representative serine carboxypeptidases with known functions from different species.

Figure S2 Chromosome locations of TaGS5 homoeologues. Genomic‐specific primers are shown on the left.

Figure S3 Genetic mapping of TaGS5‐3A in a Xiaoyan54 × Jing411 recombinant inbred line (RIL) population.

Figure S4 A CAPS marker based on SNP T/C in TaGS5‐3D.

Figure S5 Alignment TaGS5‐3A‐T and TaGS5‐3A‐G.

Figure S6 Binding sites and secondary structure of TaGS5‐3A‐T and TaGS5‐3A‐G predicted by PredictProtein.

Figure S7 Genetic distances in TaGS5‐3A between pairs of populations (F ST).

PBI-14-1269-s003.docx (643.5KB, docx)

Table S1 Primers used in this study

Table S3 Populations used for association analysis and distribution of alleles in the Chinese wheat gene pool

Table S4 Cultivars used in determination of frequency changes and geographic distributions of alleles in global wheat cultivars

Table S5 Diploid and tetraploid wheat accessions used in this study

Table S6 Accession numbers of sequences used in this study

PBI-14-1269-s002.xlsx (192.1KB, xlsx)

Table S2 Thirty‐six cultivars used for SNP detection and their genotypes of TaGS5‐3A and TaGS5‐3D

PBI-14-1269-s001.docx (24.9KB, docx)

Acknowledgements

We acknowledge constructive discussion with Dr HY Wang, Institute of Biotechnology, CAAS; help in genetic mapping from Dr DC Liu, Institute of Genetics and Developmental Biology, CAS; help with rice transformation from Dr JM Wan and Miss XP Guo, Institute of Crop Science, CAAS; and English editing by Dr. Robert A McIntosh, University of Sydney. This research was supported by the National Animal and Plant Transgenic Project (2013ZX08009‐001), Hi‐Tech Research and Development Program of China (2012AA10A308) and CAAS Innovation Project.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Figure S1 Clustering analysis of TaGS5 as well as representative serine carboxypeptidases with known functions from different species.

Figure S2 Chromosome locations of TaGS5 homoeologues. Genomic‐specific primers are shown on the left.

Figure S3 Genetic mapping of TaGS5‐3A in a Xiaoyan54 × Jing411 recombinant inbred line (RIL) population.

Figure S4 A CAPS marker based on SNP T/C in TaGS5‐3D.

Figure S5 Alignment TaGS5‐3A‐T and TaGS5‐3A‐G.

Figure S6 Binding sites and secondary structure of TaGS5‐3A‐T and TaGS5‐3A‐G predicted by PredictProtein.

Figure S7 Genetic distances in TaGS5‐3A between pairs of populations (F ST).

PBI-14-1269-s003.docx (643.5KB, docx)

Table S1 Primers used in this study

Table S3 Populations used for association analysis and distribution of alleles in the Chinese wheat gene pool

Table S4 Cultivars used in determination of frequency changes and geographic distributions of alleles in global wheat cultivars

Table S5 Diploid and tetraploid wheat accessions used in this study

Table S6 Accession numbers of sequences used in this study

PBI-14-1269-s002.xlsx (192.1KB, xlsx)

Table S2 Thirty‐six cultivars used for SNP detection and their genotypes of TaGS5‐3A and TaGS5‐3D

PBI-14-1269-s001.docx (24.9KB, docx)

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