School of Agriculture, Food and Ecosystem Sciences - Theses
Permanent URI for this collection
Search Results
1 - 4 of 4
-
ItemA study of salinity tolerance in field pea( 2013)Preliminary research was aimed at identification of parental germplasm that could be used for improvement of tolerance to toxic effects of sodium chloride (NaCl) in field pea. An initial screening experiment of 780 globally-distributed Pisum L. accessions identified significant variation in response to applied NaCl, based on plant symptoms. Lines with relatively higher tolerance as compared to commercial varieties grown in Australia were most frequently identified within landraces originating from the central, eastern and southern provinces of China. The most tolerant identified accession was an unadapted landrace ‘ATC1836’ originating from Greece. Variation for salinity tolerance was validated using a sub-set of 70 accession lines. Salinity-induced toxicity symptoms were closely associated with reductions of plant growth rate, height, shoot and root dry matter and with increased concentration of Na+ at the plant growing tip. The level of salinity tolerance based on these factors varied substantially and provides an important basis for genetic improvement of field pea for Australia. Seven field pea genotypes that vary significantly for salinity tolerance showed a range of symptom development and growth responses over time under increasing levels of NaCl salinity applied using watering treatments. The genotypic responses were closely associated with Na+ accumulation in leaflet tissue on the lower plant and a parallel reduction in K+ concentration. Increasing salinity caused strong but variable inhibition of root and shoot dry matter accumulation and final grain yield for all genotypes. The genotype ATC1836 showed the highest relative tolerance based on measured parameters, but was comparatively slow growing. Three genotypes (03H090P-04HO2002, 03H556P-04HO2012, 99-410-2-14-2) with moderate tolerance obtained substantially more dry matter under the highest salinity treatment of (18 dsm-1) compared to the commercial variety ‘Kaspa’. The genotype OZP0812 was also able to maintain relatively higher growth rate at the lower salinity treatment level of 6 dsm-1. The high salinity tolerance of the landrace genotype ATC1836 that is evident at early growth stages was also apparent in this study at later ontogeny, on the basis of lower biomass reduction, reduced symptom development and delayed rate of Na+ accumulation in plant tissue. In this study, sodium accumulated more rapidly and to a higher degree, and symptoms developed faster on lower growth nodes when compared to the growing tip. Plant biomass and main plant height showed lower correlation with Na+ concentration in plant tissue than plant chlorosis. The taller genotype OZP0812 produced more biomass under conditions of increasing salinity than the dwarf genotypes Kaspa and OZP0809 and the landrace genotype ATC1836. Applied salinity exerted deleterious and varying effects on seed yield components such as reduced seed and pod set and seed size. The genotype OZP0812 maintained both higher seed yield and larger seed size compared to the salinity tolerant landrace genotype ATC1836, despite accumulation of more Na+ in plant tissue. Increased salinity resulted in earlier flowering and increased Na+ concentration in seed tissue. Segregation ratios for salinity tolerance were analysed in 3 field pea populations derived from crosses between the sensitive genotype Kaspa and the tolerant genotypes ATC1836, Parafield and Yarrum, revealing probable multigenic control. A comparatively higher proportion of tolerant progeny was observed in the ATC1836 x Kaspa population. However, a high degree of trangressive segregation for enhanced salinity tolerance was apparent in progeny from crosses of either Parafield or Yarrum with Kaspa, suggesting that parental combining abilities should also be assessed for improvement of salinity tolerance. Positive broad sense heritabilities for measures of symptom response to salinity, and repeatability of results between experiments and generations implied high potential for genetic gain from use of pot-based screening methods. Differences in assessment of salinity symptom response based on a numerical scale as compared to percentage plant necrosis were not significant. Variation for salinity tolerance within recombinant inbred lines (RILs) progeny derived from the Kaspa x Parafield cross was documented on the basis of rate of symptom development and a salinity tolerance index. A frequency analysis showed that the proportion of field pea germplasm with higher salinity tolerance in advanced yield testing nurseries in Australia had increased in the period 2005-2011. However, a multivariate canonical analysis based on 14 yield nurseries in 2011 indicated that the degree of salinity tolerance in advanced germplasm currently provides significantly less yield benefit than degree of boron toxicity tolerance, indicating a need for further pre-breeding efforts. Boron tolerant accessions as a group were higher yielding at 7 sites during 2011. All of these sites were in regions with highly alkaline sub-soils, and six sites had comparatively lower growing season rainfall. The high rainfall exception (Kingsford, South Australia) was affected by powdery mildew, for which resistance is positively linked with high boron tolerance. Genotypes with dual sensitivity to both boron and salinity mostly performed better at sites with higher rainfall in the growing season. For sites at which salinity tolerance was more important, the only sensitive genotypes that performed well were all early flowering (i.e. PBA Twilight). One boron sensitive genotype (119) showed specific adaptation across sites at which boron tolerance was important, and is hence suitable as a key parent for improving general adaptation of crop. Linkage maps based on molecular genetic marker polymorphism were constructed for RIL populations of Kaspa x Parafield and Kaspa x Yarrum populations. RIL progeny and parents from these populations were screened at the seedling growth stage for growth symptom responses to salinity stress imposed by adding NaCl in the watering solution at a concentration of 18 dsm-1. Phenotypic variation for salinity induced symptoms was normally distributed and increased with severity over time. A salinity index was developed to quantify variation for salinity tolerance and was used in concert with statistical correlation analysis to identify quantitative trait loci (QTLs) and flanking single nucleotide polymorphism (SNP) markers that could be useful for implementation of marker assisted selection (MAS) strategies. This thesis has identified valuable variation in salinity tolerance in Pisum for field pea breeding programs. A knowledge of critical growth responses at the seedling and reproductive growth stages for salinity tolerance now provides a guide to screening of populations for useful genetic variation or marker-tagged QTLs. Preliminary investigation has identified QTLs for seedling tolerance to salinity stress for implementation of MAS for the purposes of parent building and routine screening.
-
ItemStructural variations in the ovine genome: their detection and association with phenotypic traits( 2013)Growth and meat yield traits are important to the New Zealand sheep industry. Genomic selection (GS) of these traits uses information from high density ovine SNPs to produce estimated breeding values (EBVs). The aim of GS is to account for loci directly influencing the trait (quantitative trait loci, QTL). This relies on the assumption that high density SNPs tag QTL effects via linkage disequilibrium (LD), however, it is unlikely that all QTL are adequately tagged by high density SNPs. Copy number variants (CNVs) are a type of genetic variant that may not be well tagged by SNPs and have been shown to be involved in phenotypic variation. To date, there has been little published work on CNVs in the sheep genome. While there is a well known example of a CNV affecting coat colour (agouti) in sheep, little is known of how CNVs affect phenotypic variation of production traits. The studies in this thesis employed multiple methods to identify CNVs in the sheep genome. Animals (including trios) were assayed on a Roche NimbleGen 2.1M CGH array. CNV calls from trios were used along with known false-positive calls to build a logistic regression to predict the probability calls from the 2.1M CGH array were correct. 3,488 autosomal CNVRs were identified. On a large scale, CNVRs were hard to accurately detect without using a combination of approaches. CNVRs were verified against CNVRs detected with the Roche NimbleGen 385K CGH array, Illumina OvineSNP50 BeadChip and Illumina HiSeq 2000 sequence data. Results of this work contribute a comprehensive resource of CNV regions to the literature on sheep CNVs. Given the importance of growth and meat yield traits in the New Zealand sheep industry, and the possibly unaccounted effects of CNVs on these traits, an association analysis was carried out with these traits and loci that potentially represent CNVs. Firstly, it was determined that EBVs produced by Sheep Improvement Limited (SIL) were appropriate to use as the dependent variable in the association analysis. Loci that potentially represent CNVs were SNPs from the Illumina OvineSNP50 BeadChip that were previously discarded from GS and genome wide association studies (GWAS) because they could not be genotyped. Reasons why these SNPs can’t be genotyped include the presence of the SNP in a CNV. Raw data from these SNPs were tested to determine if they were associated with the growth and meat yield traits. Seventeen associations, involving nine SNPs, were detected and validated in independent datasets. Two SNPs were in CNVRs detected using the CNV detection methods described above - one involved the agouti CNV. Raw data from this SNP was associated with ultrasonic eye muscle depth. Associations remained significant after fitting genotypes of flanking SNPs (from surrounding ~1Mb of sequence) used in GS and GWAS, suggesting that the effect of these associations are not accounted for in GS or GWAS. Including information from these SNPs in GS could improve the reliability of EBVs, contributing to genetic improvement of growth and meat yield traits in the New Zealand sheep industry.
-
ItemGenetic variation in the bovine myostatin gene and its effect on muscularity( 2010)Retail beef yield (RBY) refers to the amount of saleable meat from an animal, and is an economically important trait for the beef industry. The gross components that determine RBY are skeletal muscle, bone and fat content: Skeletal muscle is the most abundant tissue and has high economic value. The propensity to develop muscle mass is heritable and it is controlled by many genes. Genetic variation within these genes can influence differences in muscle mass. The studies within this thesis, further investigated the effect of genetic variation in the myostatin (MSTN) gene on muscle mass in cattle. MSTN was selected as a candidate for further investigation because of its important role in muscle development. Previous studies have found loss-of-function mutations in MSTN that are responsible for extreme increases in muscle mass, known as double muscling, and a high level of genetic variability. The primary objective of this thesis was to determine if MSTN polymorphisms which have not been implicated in double muscling, are also contributing to variation in muscularity. Genetic variation in bovine MSTN was examined in a sub-population of Angus cattle. Eighteen polymorphisms were identified and the haplotype diversity was inferred. From the phased haplotypes the extent of linkage disequilibrium between the polymorphisms was determined, which provided a tag SNP genotyping strategy using six MSTN polymorphisms. Large cattle populations (Herds A to E) were genotyped at each of the tag SNP sites. Haplotypes were inferred from the genotypic data, and were then used to test associations with quantitative indices for muscularity. The results from Herd A used as the discovery population showed that haplotypes 2 and 7 had a moderate effect on eye muscle area relative to double muscling heterozygotes and haplotypes 8 and 9 had a small effect. Similar trends were observed for these haplotypes in the validation population compromising Herds B to E. The effect of the MSTN haplotypes was also examined for other carcass, meat quality and feed efficiency traits. Significant associations were found for almost all traits examined, but their effects could not be proven as casual and requires further validation. Differences in gene expression between the MSTN haplotypes were also investigated to provide biological support for the quantitative associations. The data from this study did not provide convincing support for the quantitative associations, which may have been biased by measurements between assays, differences in splicing or because the differences in eye muscle area are not due to MSTN. The effect of the MSTN splice variant warrants further investigation since a favourable role has been demonstrated previously in sheep A historical perspective on recent selection pressure for double mutations has also been provided. The time to the most recent common ancestor was investigated for multiple MSTN mutations responsible for double muscling. The long regions of haplotype homozygosity that were found associated with the double muscling mutations indicate the time to the most recent common ancestor occurred is consistent with the first reports of double muscling approximately 200 years ago. The studies within this thesis have further contributed to the elucidation of the biology of muscling. It has been demonstrated that other MSTN polymorphisms, not implicated in double muscling, are also contributing to variation in muscle mass. This knowledge will add value to current methods for estimating the genetic merit of beef cattle and may offer more practical genomic selection alternative to improve muscling in beef cattle.
-
ItemAspects of statistical modelling for genomic selection( 2010)The research reported in this thesis investigated aspects of statistical models used for genomic selection. The importance of, and, interest in genomic selection is driven by the desire to increase the rate of genetic gain for commercially important traits. Genomic selection could increase the rate of genetic gain by increasing the accuracy of selection through the inclusion of DNA markers. Multiple methods and models have been proposed for implementing genomic selection. All methods have to overcome the problem that the number of DNA markers (p) is typically much larger than the number of phenotypic records (n) i.e. the p>n problem. One approach to this problem is to use Bayesian Inference which allows for an oversaturated model. Two simulation studies and a large data study were undertaken to gain a comprehensive understanding of what makes a robust and accurate Bayesian prediction model. Results from the simulation studies indicated that the match between the assumed QTL distribution and the true QTL distribution had an effect on the accuracy of the direct genomic values (DGV) produced by the different Bayesian models. Some of the models producing accurate DGV were computationally demanding. Subsequently, a novel Bayesian model using Stochastic Search Variable Selection (SSVS) for genomic selection was developed (Bayes SSVS). This model was demonstrated to produce accurate DGV and be computationally efficient. In contrast to the results from simulated studies, the results from a real dairy cattle data study showed a general equality in the accuracy of prediction across the various Bayesian models including Bayes SSVS. The exception was for traits with atypical genetic architectures such as fat percentage in milk where Bayes SSVS and other model selection approaches performed better than other approaches assuming that all markers equally contributed to the total genetic variation. The thesis also sought to explore the potential of genomic selection for improving novel traits that have been traditionally very difficult to select for. Energy Balance (EB) is a minimally recorded trait as the cost and measurement logistics mean it can only recorded on experimental farms. Using EB as a case study, it was demonstrated that genomic selection could provide the opportunity to select for EB and other minimally recorded through the accurate prediction of DGV. Additionally, selection for EB could be a valuable tool in finding a balance between production and non- production traits. Another attractive feature of some of the Bayesian models for genomic selection is they can be used to map QTL. Consequently, the establishment of significance when using multi-locus models for genome wide association studies was explored using a permutation testing approach. Three examples demonstrated that the permutation testing approach could correctly identify QTL. Two specialised approaches, permuting within strata, are presented. One approach accounted for a structured pedigree satisfying the condition of exchangeability. The second approach enabled the identification of secondary moderate QTL in the presence of a major QTL. The effect of the number of permutations needed was also examined; confirming previous results. This method was shown to provide accurate identification of QTL when compared with current approaches.