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Genetic dissection of wheat nitrogen use efficiency related traits

Zhao, Yun (2019) Genetic dissection of wheat nitrogen use efficiency related traits. PhD thesis, Murdoch University.

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Abstract

Nitrogen is not only an essential element for wheat development, but also a major determinant for wheat yield and protein quality. It is vital to improve wheat nitrogen use efficiency (NUE) as nitrogen is the most important component of all fertilizers that are provided for the pursuit of a higher wheat yield and better protein quality. Wheat NUE is an important quantitative trait that is very complex and easily influenced by the environment and its controlling network is still not clear. In the current study, a wheat doubled haploid (DH) population was used to study the genetic variations of NUE and its controlling mechanism in wheat. Through quantitative genetic locus (QTL) mapping method, a suite of QTLs associated with NUE related traits as well as yield and yield component traits under different nitrogen rates and different environmental conditions were obtained.

For yield components, results showed major QTLs for seed number per main spike (SN) were located on 3A and 5A, the SN QTL on 3A was detected in three environments and explained 32.16% of phenotypic variation. QTLs for thousand kernel weight (TKW) were detected on 2A, 2D, 4A, 4B, 5A, 6A and 7D. The most significant TKW QTL was located at 123 cM on 2A, with LOD and PVE of 16.93 and 20.35%, respectively. Major QTL for grain weight (GW) was located on 5A, with LOD and PVE of 4.42 and 13.26%, respectively. Important QTLs related to grain protein content (GPC) were identified on 1B, 2D, 4B and 5A, GPC QTL on 5A was the most significant, with logarithm of odds (LOD) and phenotypic variation explained (PVE) of 11.36 and 17.04%, respectively.

Important NUE related QTLs identified in this study were QTL for Straw protein content (SPC) on 3B, QTL for nitrogen Harvest index (NHI) on 1B, 2B, 5A and 6B. QTL for nitrogen utilization efficiency for grain yield (NUtE) on 1B, 3A and 6B.

Besides the large numbers of QTLs identified related to each trait investigated in this study, several chromosome regions were identified to be associated with multiple traits and were detected in multiple environments, including a QTL cluster located at 131 cM at 1B, associated with GPC, SPC and NUtE; QTL cluster located at 111-115 cM on 3A associated with TKW, SN and NUtE; QTL cluster located at 153-155 cM on 4B associated with kernel traits and GPC. Compared with other QTLs that were only detected in single environment, these QTL regions deserve more attention. Metabolites profiling of over 1000 metabolites in mature wheat kernels were carried out to facilitate the candidate gene identification for those regions and other important traits. Because of the causal relationships between metabolites and their closely correlated traits, metabolites identified to be colocalized with these genetic regions will assist further narrowing down these regions harbouring the underlying candidate genes.

A single gene controlled major QTL for stem diameter that is positively correlated with grain yield was located on Chromosome 3BL. A list of candidate genes was generated from search of wheat reference map using the flanking markers of this QTL. TaCOMT gene was suggested as one of the candidate genes for stem diameter, further confirmation of the genetic function work is needed.

Many modern commercial wheat cultivars contain 1B.1R translocation due to its high yield and disease resistance characteristics despite its negative impact on breadmaking quality caused by the Sec-1 locus on rye 1R chromosome. Wheat gliadins are important parts of wheat storage proteins that determine the extensibility of wheat gluten, which is crucial for breadmaking. In the current study, the gliadin constituent dynamics across the population were studied via reverse phase high-performance liquid chromatography (RP-HPLC) and size exclusion high-performance liquid chromatography (SE-HPLC) to reveal the 1B.1R impacts on seed gliadin compositions. The two parental lines differ in 1B.1R genotype and with High molecular weight glutenin subunits (HMW-GS) composition, ie., 2*, 17+18, 2+12, vs 2*, 7+9, 5+10. Results from SE-HPLC indicated that lines with 1B.1R translocation showed significantly lower SDS-unextractable polymeric protein (UPP) percentage, Ratio of polymeric proteins to monomeric proteins (P/M) and Ratio of glutenin proteins to gliadin proteins (Glu/Gli). However, this undesirable effect was significantly alleviated by HMW-GS 17+18 in one growing environments. The population RP-HPLC profiles could be clearly distinguished into two groups, with lines containing 1B.1R showed more individual proteins originated from the rye translocation. To elucidate the genetic mechanism behind the chromatograph pattern, QTL-mapping analysis was carried out to detect the underlying genetic factors controlling the gliadin components and the results indicated that some gliadin fractions were controlled by gene loci other than the Sec-1 locus. This study provided new insights into maintaining a balanced grain yield and quality through utilising the 1B.1R translocation line in wheat breeding.

Item Type: Thesis (PhD)
Murdoch Affiliation: Agricultural Sciences
Australia-China Joint Centre for Wheat Improvement (ACCWI)
Supervisor(s): Ma, Wujun and Islam, Shahidul
URI: http://researchrepository.murdoch.edu.au/id/eprint/57397
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