Premisas para la aplicación de la estrategia diseñada

In addition to protein identification form gel bands, the whole soluble proteomic profile in the bottom of the stem was analysed from both Ningyou 7 and Tapidor DH. Peptides were extracted from the protein mixture using FASP methodology as described above. The identified peptides and proteins were visualised and analysed using Scaffold as previously described. Figure 4.5 shows an overview of protein identified using Scaffold.

Figure 4.5 Overview of protein identification using Scaffold.

From left to right, column show the protein names or cluster of the identified proteins with a coloured threshold legends (green is above 95 %). Followed by accession number, molecular weight, T-test probability, quantification profile and the samples identified (Ningyou 7 in brown and Tapidor DH in purple). This picture was generated using scaffold v4.5.

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Under the described thresholds, more than 1650 proteins were identified in Ningyou 7 and more than 1600 in Tapidor DH (Figure 4.6). 1261 of these proteins are shared between Ningyou 7 and Tapidor DH; 399 proteins were only identified in Tapidor DH, and 347 proteins were identified only in Ningyou 7.

Figure 4.6 Number of identified proteins in Ningyou 7 (N) and Tapidor DH (T).

The number of shared proteins between the both genotypes are in yellow. To the left of the shared portion (N) is the number proteins identified only in cultivar Ningyou 7, and to the right (T) is the number proteins identified only in cultivar Tapidor DH.

This represents a significant difference (T-test, P <0.01, Scaffold v4.5) between Ningyou 7 and Tapidor DH related to presence of some proteins was observed. Figure 4.7 shows the quantitative differences between the both genotypes in terms of the total number of identified spectra for each protein.

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Figure 4.7 Quantitative difference between the genotypes Ningyou 7 and Tapidor DH.

Volcano plot (T-test, P <0.01) shows quantitative differences between Ningyou 7 (N) and Tapidor DH (T). Horizontal axis represents the log2 of the fold change in the total numbers of spectra that were identified. Green squares indicate proteins that show a significant difference in abundance. The top left square (A) indicate more abundant proteins in T compared with N, and vice versa in the top left right square (B).

Two examples of these differences between Ningyou 7 and Tapidor DH in the abundance of indole-3-acetonitrile nitrilase (NIT2) and myosin-like protein are shown in Figure 4.8. The myosin-like protein was expressed in 3-fold higher in Ningyou 7 than Tapidor DH. In contrast, the NIT2 was not expressed in Ningyou 7, but significant expression was occurred in Tapidor DH in the bottom of the stem at the beginning of flowering.

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Figure 4.8 Differences in the expression of two identified proteins between Ningyou 7 and Tapidor DH.

The expression of myosin-like protein (A), and the expression of NIT2 (B) between Ningyou 7 (N) and Tapidor DH (T). The left figure of each of them represents biological replications and the figure to the right represents the mean value of the total spectra. Error bars represents standard error (n = 3 and 4). Pink represents Ningyou 7 and purple represents Tapidor DH. 0 10 20 30 40 50 60 N T To ta l s p ec tr a Genotype 0 2 4 6 8 10 12 14 N T To ta l s p e ctr a Genotype A B

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4.5

Discussion

The results show that there was a considerable difference in the proteins found at different stages of development in both the roots and stems of both Tapidor and Ningyou 7. The most important point was with regards to the 23 kDa protein identified previously by Rossato et al. (2001) as a crucial vegetative storage protein. A 23 kDa protein was identified in the Tapidor DH plants that accumulated at both the rosette and flowering stages as shown in Figure 4.2 (page 159), this contrasted with the results from the Ningyou 7 plants in which the corresponding band was absent, however two other proteins of a slightly lower molecular mass were detected (21 and 22 kDa) Figure 4.1 (page 158).

This shows that there is an apparent difference in the proteins produced and potentially stored between these two mapping population parental lines suggesting that this could be genetically mapped if these proteins can be accurately quantified in the TNDH population derived from these lines. This would make this a trait amenable for QTL analysis. Such an approach will be described in chapter 4.

The hypothesis that the 23 kDa protein might play an important role in N storage for use in seed formation was supported by the deflowering and depodding experiments. In this case following approximately a month of flowering, the 23 kDa band disappeared (control plants) and then reappeared in the deflowered plants by the end of flowering. There were also key differences observed between taproots and lateral roots which contradict the findings of Rossato et al. (2001); Rossato et al. (2002a); Rossato et al. (2002b); Noquet et al. (2004) who detected this protein only in the taproots in a different oilseed rape variety (Capitol).

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This highlights the importance of looking at all possible tissues to determine the site of accumulation and fate of storage proteins in particular. The other finding was that at the bottom of the stem there are also clear differences between the parent lines. In Tapidor DH, the amount of the 23 kDa putative storage protein was lower than that found in the roots and also the amount of this protein in this part of the plant did not vary in amount when measured at different plant growth stages unlike the pattern detected in the roots. This finding also contrasts with the aforementioned studies sine this protein was not detected in the stem.

The study of Schjoerring et al. (1995) investigating N remobilisation within OSR under field conditions, showed that silique walls possessed the maximum content of N on the 25th _{day prior to harvest which correspond to the stage GS 6.4 when the}

silique walls samples for the second time in the present study. When the siliques were studied at this stage, the SDS-PAGE gel of the soluble protein profile in Figure 4.4 (lane C2 silique walls) illustrated a relative abundance in protein quantity. Moreover, it was found that at maturity which occurred after about three months of flowering there was a large accumulation of three proteins. When these proteins were separated from the gel and analysed using the tandem mass spectrometry, they were all found to be putative seed storage proteins. These proteins were present in the siliques walls even at harvest when seed development was completed and the siliques dry. These proteins were found in both parents and suggest that this is a source of Nitrogen loss which it might be possible to address. This might be supported by the finding of Wagstaff et al. (2009) who reported the significant up-regulated seed storage proteins in the senescing pod walls of Arabidopsis and the finding of Koeslin-Findeklee and Horst (2016) who illustrated that silique walls contained a great proportion (~26 %)

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of the total shoot N at maturity. Furthermore, The increasing accumulation of the ~35 kDa protein in the inflorescence stems adjacent to the siliques during seed development GS 6.4 and senescence in the both genotypes could also reported as a source of N loss and the possibility for further work to be considered. This protein could possess glucanase activity as was identified by MS/MS.

Mass spectrophotometric analysis of various bands which showed clear differences between the parent lines or in different life stages allowed us to identify a number of proteins which might shed light on the proteins involved in nitrogen storage. Interestingly none of the proteins correspond to that suggested by the French group. One of the main dominant proteins identified as a putative 23 kDa VSP is a trypsin inhibitor which is in agreement with the study of Tian et al. (2007) and Liu et al.

(2009b) who reported the trypsin inhibition activity of the LcVSP1 (22 kDa) in L. chinensis and the 23 kDa VSP in S. mukorassi,respectively. It was illustrated that N remobilisation associated with OSR leaf senescence is accompanied with disappearance of trypsin inhibition activity (Etienne et al., 2007). Furthermore, one of the main dominant proteins identified in the 22 kDa protein band (a concomitant band to the 23 kDa Protein band in Tapidor DH) is water-soluble chlorophyll protein Table 4.1 (page 162). It was reported that this protein involved in N remobilisation in OSR young leaves under N starvation conditions and possessed protease inhibition activity by which leaf senescence is delayed (Desclos et al., 2008; Avice and Etienne, 2014). Moreover, Avice et al. (2003) demonstrated that the 32 kDa VSP observed in taproot of M. sativa possessed class III chitinase activity and could plays a role in plant protection against pathogenesis. In the present study, one of the proteins identified as a putative 23 kDa VSP within lateral root is chitinase.

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Continuous removal of pods resulted in a significant increase in the shoot length comparing to the control plants, in agreement with Noquet et al. (2004) whom reported that flowers and pods removal contributed to the shoot growth. Furthermore, continuous removal of flowers, during the seed development stages compared with the control plants, has increased the formation of new shoots and delayed the senescence in contrast to the control plants. Since N uptake decreases after the onset of flowering (Jensen et al., 1997; Gabrielle et al., 1998; Rossato et al., 2001; Malagoli et al., 2004; Zhang et al., 2010; Ulas et al., 2013) or after the early stages of the seed development (Malagoli et al., 2005a; Gombert et al., 2010), and the N storage reserves are the major source to support the increasing requirements of N for the growing shoots (depodded plants) or the formation of new shoots (deflowered plants), it might explain to some extent the lack of the increasing accumulation of the putative VSPs during seed filling stages in the depodded plants and after two months of flowering in the deflowered plants.

By studying the whole proteomic profile more than 1600 proteins were identified, at the beginning of flowering, in the bottom of the stem for each genotype. These proteins represent a fraction (1.66 %) of the total putative proteins coded by the B. napus

genome (Chalhoub et al., 2014). The abundance of these proteins varied significantly within each genotype which might reflect the importance of these proteins for the cell. Genotypic variation in the abundance of these proteins was also observed, as at least 347 proteins were detected in only one genotype. 1261 proteins were presented in both genotypes, of which 11 and 12 proteins were overexpressed in Tapidor DH and Ningyou 7, respectively (Figure 4.7). Proteins were expressed that represented members of the housekeeping protein groups used in the protein and gene expression

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studies. The most constant and abundant proteins from five families are; Bo8g065470.1, Bra016729 encoded glyceraldehyde-3-phsphate dehydrogenase, Bo9g169510.1, Bra008903 encoded tubulin beta chain, Bo2g133940.1, Bra014334 encoded 60S ribosomal protein L7, Bo6rg049540.1 encoded actin-2 and Bo3g039510.1 which encoded ubiquitin. Hence, these proteins accessions would be good choices as reference proteins in further study. Nonetheless, the expression patterns of these proteins interestingly varied among each family member. For example, the Bo5g016460.1 which encoded glyceraldehyde-3-phosphate dehydrogenase was not identified in Ningyou 7 in contrast to the Bo8g065470.1 protein. This results might raise concerns about using multiple copies of these housekeeping protein for normalisation of gene and protein expression data. The results clearly show the strength of studying protein expression but there are difficulties in this approach which still need to be overcome to make this a more commonly used approach.

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5

Chapter 5 Quantitative Traits Underlying

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5.1

Introduction

The principle of chromosomal segregation during the reproductive phase allows the identification of Quantitative Trait Loci (QTL) or genes that control traits of interest (Tanksley, 1993). This is mediated by a segregating population and suitable statistical algorithms that reveal the association between the genetic markers and the phenotypic data (Kearsey and Farquhar, 1998; Collard and Mackill, 2008). These mapping populations could also be tested under different environments by which the interaction between the genetic and environmental factor can be estimated (Vreugdenhil et al., 2005). The major challenge facing breeders after QTLs have been detected is the identification of the gene and the nucleotide polymorphisms by which the variation in the phenotypic trait is defined or closely associated markers to track introgressions (Collard et al., 2005; Vreugdenhil et al., 2005). Identification of QTLs in a mapping population is affected by many determining factors such as the genetic properties of the genomic regions that control traits, the mapping population size and the experimental design by which phenotypic data are generated (Asíns, 2002; Collard et al., 2005; Vreugdenhil et al., 2005).

QTLs have been mapped for a number of agronomic traits in B.napus L. These include QTLs associated with flowering time (Long et al., 2007; Wang et al., 2011a; Javed et al., 2016), seeds content of glucosinolates (Howell et al., 2003; Feng et al., 2012), seeds content of oil (Qiu et al., 2006; Jiang et al., 2014), yield and yield related traits (Quijada et al., 2006; Radoev et al., 2008; Shi et al., 2009; Bouchet et al., 2014), abiotic stress, resistance to diseases (Butruille et al., 1999; Zhao and Meng, 2003; Zhang et al., 2016a), seed (Ding et al., 2010) and shoot (Liu et al., 2009a) minerals concentration, N use efficiency (Miro, 2010), B use efficiency (Zhao et al., 2012), P

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use efficiency (Ding et al., 2012) and root morphology and architecture under P stress (Yang et al., 2010; Shi et al., 2013a).

As it was described in Chapter 1, OSR is characterised with poor N Use Efficiency. Hence, improvement in N use efficiency is a major priority for plant breeders. This could be possible through the potential optimisation of traits associated with N remobilisation efficiency (Bouchet et al., 2014). Nevertheless, QTL mapping for proteins associated with N remobilisation such as putative VSPs are very rare, essentially due to the difficulty in the identification of such proteins and then establishing the appropriate methodology required for an accurate quantitative analysis. N is significantly associated with plant biomass, architecture and yield related traits. Svečnjak and Rengel (2006a) reported that in oilseed rape the average shoot content of N was 2.7 % of the dry weight. Thus, more work is required to elucidate the genetic mechanism by which plants control these traits