Pre-harvest sprouting (PHS) is a common phenomenon in the wheat (Triticum aestivum L.) producing areas of South Africa and has been well-documented over the past two decades (Barnard et al., 1997; Barnard, 2001; Barnard and Bona, 2004; Barnard and Smith, 2009). It has been a serious production constraint especially in the summer rainfall regions where rain occurs frequently just prior to or during harvest time. It is well-documented that PHS negatively affects the grain quality and ultimately flour quality. As a result, the price that farmers can get for their crop at harvest is severely affected (Barnard, 2001; Liu et al., 2008).

Research has shown that extensive genotypic variation exists for PHS in South African cultivars, indicating that progress in the development of cultivars with improved sprouting tolerance is feasible (Barnard et al., 1997, 2005; Barnard, 2001). The PHS tolerance levels in South African wheat cultivars has improved significantly over the years as a result of successful breeding (Smit et al., 2010). These winter wheat cultivars can be categorized into three major groups, namely cultivars that are highly tolerant to PHS, cultivars that are highly susceptible to PHS and a third moderate group that includes cultivars that are strongly influenced by the environment (Barnard and Smith, 2009). According to Biddulph et al. (2005) environment, and specifically moisture stress, can have a large effect on dormancy expression. Drought conditions combined with high temperatures during grain filling, tend to increase dormancy in wheat (Mares and Mrva, 2014).

PHS is a complex trait controlled by multiple genes or QTL (Bailey et al., 1999; Mares et al., 2005; Yang et al., 2007) where trait expression is significantly influenced by environmental conditions (Trethowan et al., 1996; Johansson, 2002). This complicates the accurate prediction of the stability of a cultivar in terms of PHS tolerance.

In the past decade, a number of QTL for PHS tolerance have been identified and mapped across all 21 wheat chromosomes in a number of wheat cultivars from different parts of the world (Mori et al., 2005; Ogbonnaya et al., 2007; Chen et al., 2008; Mohan et al., 2009; Jaiswal et al., 2012; Singh et al., 2012; Graybosch et al., 2013). These QTL analyses in wheat led to the identification of markers linked closely with desirable alleles of different QTL (Mares et al., 2005; Chen et al., 2008; Liu et al., 2008; Fofana et al., 2009; Kulwal et al., 2010, 2012). The chromosomes containing the most common and stable major QTL for PHS tolerance are 3A (Kulwal et al., 2005) and 4A (Mares et al., 2005; Mori et al., 2005; Ogbonnaya et al., 2007; Chen et al., 2008; Imtiaz et al., 2008; Zhang et al., 2008). A number of robust reliable simple-sequence repeat (SSR) markers have been associated to a number of these specific QTL for PHS tolerance in specific cultivar backgrounds. However, the characterization and validation of the true phenotypic effects of these QTL individually or in combination in diverse germplasm remains a challenge due to the genetic complexity of the PHS tolerance trait.

The major QTL on chromosome 4A was identified and mapped in 2000 (Flintham, 2000), which is now referred to as the Phs1-A1 locus (Shorinola et al., 2016). Recently, the Phs1-A1 region was fine mapped and new tightly molecular markers with MAS potential were identified. However, the causal gene underpinning the Ph1-A1 locus is still unclear (Barrero et al., 2015; Shorinola et al., 2016). In 2008, a major QTL on chromosome 3A, named Qphs.pseru-3AS, was characterized and mapped from the white wheat cultivar Rio Blanco (Liu et al., 2008). In recent years, some important candidate genes which control PHS tolerance at these (3A and 4A) loci and others have been identified (Liu et al., 2013; Cabral et al., 2014; Barrero et al., 2015; Shorinola et al., 2016; Zhou et al., 2017). Importantly, the TaPHS1 gene, which forms an integral part of the major QTL on chromosome 3A (Qphs.pseru-3AS), which confers PHS tolerance, was cloned and characterized further. Two important, functional SNP mutations within the third and fourth exons of the TaPHS1 gene-coding region, were identified. Both SNP mutations occurred together in all PHS susceptible cultivars covering a set of diverse genetic backgrounds and are considered critical for future PHS tolerant cultivar development (Liu et al., 2013).

The aim of this study was to characterize a collection of South African wheat cultivars for their known PHS tolerance QTL on chromosomes 3A and 4A and to compare marker haplotype combinations observed with the original PHS cultivar scoring averages. In this study, we aim to validate whether these markers could be used during MAS to select for better PHS tolerant cultivars and to determine if it would be possible to predict a cultivar's potential PHS tolerant class based solely on marker haplotypes.

The cultivars that were assessed in this study were released by three different seed companies and represented diverse genetic backgrounds and growth types. All wheat cultivars grown in South Africa are red wheat types with exceptional bread making quality characteristics (Smit et al., 2010).

The PHS tolerance levels in South African wheat cultivars has steadily improved directly or indirectly through wheat breeding over the past 25 years (Barnard et al., 2005; Smit et al., 2010). As a result of continuous evaluations and adaptations to the respective breeding programmes, the PHS tolerance of cultivars improved to such an extent that only three of the dryland cultivars that are currently commercially available, have poor PHS tolerance compared to the almost 60% of cultivars with poor PHS tolerance in 1991 (Barnard et al., 1997). It is well-known that environmental conditions during grain filling can have a large effect on the expression of dormancy (Biddulph et al., 2007). Research by Biddulph et al. (2005, 2007) has shown that drought conditions during grain filling might increase dormancy in certain cultivars (Mares and Mrva, 2014). These phenomena could explain the high variation in the PHS levels of the moderate group of cultivars, especially in the dryland production regions where sporadic periods of moisture stress and high temperatures are experienced. Opposed to the higher PHS levels in dryland cultivars, it has been shown over many years that cultivars grown under irrigated conditions in South Africa do not display the same levels of tolerance. However, in these irrigated production areas moisture stress is not a factor. Previous research by Biddulph et al. (2007) has shown that a reduction in dormancy can occur when the water supply was high during the later stages of grain filling. Therefore, the sufficient supply of water at critical growth stages might reduce dormancy, possibly explaining the lower levels of PHS observed in irrigation cultivars in South Africa.

This study was the first to investigate the distribution and effect of known major QTL for PHS tolerance in South African wheat cultivars. The well-documented 3A and 4A QTL (Kulwal et al., 2005, 2012; Mares et al., 2005; Chao et al., 2010; Cao et al., 2016) were targeted for further investigation after initial screenings with several SSR markers.

According to the data from this study, the South African PHS tolerant check, Elands, compares favorably with the international sources. Based on pedigree comparisons there are no known PHS tolerance donor to confer tolerance. Data from this study are the first indication of the underlining genetic basis of the PHS tolerance in this cultivar to be predominantly as a result of the TaPHS1 gene and other additive QTL combinations. From SSR haplotying it appears that different alleles of the contributing genes of the Phs1-A1 locus (4A QTL) might be different from the international PHS tolerant donors.

According to previous research the 3A Qphs.pseru-3AS (Kulwal et al., 2005; Liu et al., 2008, 2011) and 4A QTL regions (Flintham, 2000; Mares et al., 2005; Ogbonnaya et al., 2007; Chen et al., 2008; Zhang et al., 2008; Graybosch et al., 2013; Cabral et al., 2014) contribute significantly to the partial PHS tolerance conferred by multiple genes. Additional common and stable QTL for PHS tolerance are 2A (Mohan et al., 2009), 2B (Chao et al., 2016; Fakthongphan et al., 2016), 3B, 3D (Kulwal et al., 2004; Ogbonnaya et al., 2007; Fofana et al., 2009; Jaiswal et al., 2012), 4B (Kulwal et al., 2012; Cao et al., 2016), 5A (Groos et al., 2002), 6B and 7D (Roy et al., 1999). Similar to other genetic studies that suggest that genes linked with PHS tolerance are mostly located on chromosome 3A and 4A (Graybosch et al., 2013; Cabral et al., 2014), it became clear from the current study that the effects of the 3A and 4A QTL on the phenotypic variation of PHS of South African cultivars are most important.

The four SSR markers, Barc57, Barc12, Wmc650, and DuPw004 used to haplotype the studied material, identified clear single favorable marker alleles across diverse genetic backgrounds, which can be considered for MAS. The same markers for the 3A QTL region were used during the fine mapping and cloning of candidate gene TaPHS1 (Liu et al., 2013). These markers have also been used successfully during the positional mapping of these QTL in previous studies (Singh et al., 2012; Tyagi and Gupta, 2012; Cao et al., 2016). The allelic variation identified with the four SSR markers strongly suggests the presence of different allelic versions of candidate genes or presence of novel mutations at the 3A and 4A QTL regions. The 13 haplotypes identified for the 3A QTL, as well as the 10 haplotypes for the 4A QTL, represented cultivars from all three PHS tolerance classes (tolerant, moderate and susceptible). In other mapping studies, an explained phenotypic variation for a single allele linked to PHS tolerance ranged between 15 and 45% (Hori et al., 2010; Chang et al., 2011; Liu et al., 2011). In the current study the OPV (%) range (higher than 40%) which was calculated in nine out of the 13 haplotypes for the 3A QTL and six out of the 10 haplotypes for the 4A QTL, indicated significant contributions by favorable haplotypes toward PHS tolerance. This OPV (%) range of up to almost 60% suggests the additive effect of the contribution of candidate genes within both the 3A and 4A QTL regions. From these combined analyses, it is therefore clear that additive haplotype combinations can be targeted during MAS.

Based on SSR haplotyping, cultivars were predicted to have a certain PHS tolerance. This is the first attempt to predict PHS tolerance based on molecular data in commercially available cultivars. In the case of dryland cultivars, this methodology predicted the correct PHS class in almost 77% of the time and 68% in the irrigation cultivars. Although some of the predictions based on SSR haplotyping classed cultivars incorrectly, in these cases cultivars were always classed in the group directly following or directly prior to that specific grouping and never two groupings apart. At no stage was a susceptible cultivar wrongly classed as tolerant or a tolerant cultivar wrongly classed as susceptible. The cultivars were always wrongly grouped between moderate and tolerant or moderate and susceptible classes.

Analyses based on SNP haplotyping were different, because only two PHS classing groups (tolerant and susceptible) were considered. In this case, cultivars that were phenotypically tolerant could be predicted through SNP haplotyping as susceptible or vice versa. Importantly, the SNP predictions were based solely on the contributions made by the TaPHS1 gene of the 3A QTL. The contributions of the 4A QTL, Phs1-A1 (Barrero et al., 2015; Shorinola et al., 2016), are unknown for these predictions and warrant further investigation on this germplasm. Predictions made with SNP data were more accurate than the SSR data with an improvement of almost 10% in both dryland and irrigation cultivars. Dryland cultivars were predicted correctly in 86% of the cases, while the irrigation cultivars were correct in 78% of cases. However, markers TaPHS1-646 and TaPHS1-666 were not completely diagnostic as mentioned by Liu et al. (2013), possibly due to the fact that South African cultivars might have novel mutations in and around the TaPHS1 gene.

With the SNP data it was harder to correctly predict tolerant cultivars than susceptible cultivars, possibly due to the masking effect of moderate cultivars, as well as the unknown effects of the 4A QTL and potential susceptibility factors. The accurate predictions of moderately tolerant cultivars remains a challenge. However, the data from this study has given more insight into the genetic variation within the moderate class, further emphasizing the complexity of the PHS traits influenced by the environment (Kulwal et al., 2012; Liu et al., 2013; Mares and Mrva, 2014). The high success rate of predicted values of almost 82% on average are indicative of the possible application of this methodology in future PHS screenings. It appears that these data could be a preliminary indication of a cultivar's potential PHS class. However, the lack of a universal PHS evaluation scale, as well as the theoretical cut-off PHS score between classes, might influence the prediction outcomes.

In future, the SNP markers (TaPHS1-646 and TaPHS1-666) specific to the 3A QTL can be used to select for better PHS tolerance cultivars. The newly published diagnostic markers for the Phs1-A1 locus need to be validated on this set of cultivars. Potentially the combination of using targeted MAS for TaPHS1 (3A) and Phs1-A1 (4A) with true diagnostic markers, may improve PHS class prediction accuracy in the future. It is envisaged that this methodology will be further fine-tuned and validated with in-season phenotyping screenings and leaf material sampling to assist with PHS tolerance classification and recommendations.

The fact that the phenotypic PHS screenings of the 96 cultivars were conducted over a 25-year period and at several wheat producing localities throughout the wheat production areas of South Africa, could also have influenced the outcome of the data. It has been reported that environmental effects play a significant role in the PHS tolerance or susceptibility of certain cultivars (Barnard, 2001; Barnard et al., 2005; Barnard and Smith, 2009).

The methodology explained in this study has the potential to be applied in a MAS approach to predict the PHS tolerance class during the development of germplasm, enabling breeders to select for and release cultivars with improved PHS tolerance.

Both authors have contributed to the work and agreed to be in the author list. SS is the molecular scientist and contributed molecular data and the interpretation thereof. AB, as the plant physiologist, contributed phenological PHS data and the interpretation thereof. Both authors contributed to the writing of the manuscript and preparing it for publication.