Abstract
The productivity and profitability of sheep farming enterprises depends on many factors including those that contribute to reproductive efficiency, like conception and other reproductive parameters. Australia is the largest global exporter of sheep meat and wool products with global demands expected to continue to increase. As such, improving reproductive efficiency, by improving associated traits like conception outcomes, in Australian sheep flocks is crucial. Host genetics, on both the ewe and ram sides, and environmental factors influence conception outcomes. On the ram-side, semen associated traits like spermatozoal motility are known to influence conception outcomes. Past studies involving routinely assessed semen traits, like spermatozoal motility, indicate that they can influence conception outcomes and have low to moderate heritability estimates, which is indicative that genetic variation contributes to the phenotypic variability observed in these traits. However, these studies involved sheep breeds that are not commonly found in Australia. Furthermore, there has been relatively few studies focused on ram-side traits in comparison to ewe-side traits, particularly in the context of identifying genetic determinants underlying variability in traits associated with reproductive efficiency. Therefore, this thesis aimed to characterize the influence of ram-side factors on conception outcomes and identify genomic and transcriptomic determinants underlying variation in routinely assessed ram semen traits.
Artificial insemination (AI) is widely used in seedstock sheep enterprises as it affords a variety of benefits including ensuring that each ewe is inseminated, the ability to use semen from genetically superior rams from outside of the flock, and reduced lambing periods. However, poor conception outcomes following AI have a significant negative influence on the productivity and profitability of sheep farming enterprises. Given a single ram may inseminate several ewes naturally or hundreds of ewes via AI annually, investigating ram-side factors that contribute to conception outcomes following AI is warranted. Therefore, the research presented in Chapter 2 investigated the influence of a key ram-side factor, spermatozoal motility, on conception outcomes following on-farm AI in sheep. A total of 2,608 insemination records were used to perform logistic mixed-model regression and ordinal regression to investigate the influence of spermatozoal motility on conception outcomes (binary variable) and pregnancy scan count (ordinal variable), respectively, following on-farm AI in sheep. Fixed effects included AI site, type of semen used for insemination, spermatozoal motility, and ewe age, and a random polygenic effect was also fit. The results of Chapter 2 indicate that AI site (P-value <0.001) and spermatozoal motility (P-value = 0.024) significantly influenced conception outcomes following on-farm AI. While age of the ewe (P-value <0.001) and AI site (P-value <0.001) had a significant influence on pregnancy scan count, with spermatozoal motility approaching significance (P-value = 0.079). Given this, the aim of Chapter 3 was to determine whether genetic variance contributed to the phenotypic variability observed in routinely assessed ram semen traits. Ram semen traits like volume, gross motility, concentration, and percent post-thaw motility were found to be low to moderately heritable (0.081 – 0.170) and highly repeatable (0.412 – 0.527). Given that variability in routinely assessed ram semen traits was found to be heritable, the aim of Chapter 4 was to identify genomic regions underlying the variability observed in these routinely assessed ram semen traits. A genome-wide association study (GWAS) was performed using retrospective phenotypes for ram semen volume, gross motility, concentration, and percent post-thaw motility (results presented in Chapter 4). Thirty-five quantitative trait loci (QTL) located on 16 chromosomes were associated with ram semen traits, with several positional and putative candidates identified within significantly associated genomic regions. Finally, given that there is evidence in the literature indicating that spermatozoal transcripts could influence both conception and early embryonic development, Chapter 5 aimed to characterize the spermatozoal transcriptome of three sheep breeds common to Australia, as well as investigate whether there are differences in the spermatozoal transcriptome between ejaculates of varied quality. A total of 754 differentially expressed genes (DEGs) were identified between breed contrasts (Merino, Dohne, and Poll Dorset), and relatively low- and high-quality ejaculates. Several of the DEGs identified were previously reported to influence spermatogenesis, conception, and embryonic development. Overall, the findings reported in this thesis offer novel insights into genetic and transcriptomic determinants underlying variability observed in ram semen traits, which in turn, may be used to develop novel strategies to improve reproductive efficiency in sheep farming enterprises.
Artificial insemination (AI) is widely used in seedstock sheep enterprises as it affords a variety of benefits including ensuring that each ewe is inseminated, the ability to use semen from genetically superior rams from outside of the flock, and reduced lambing periods. However, poor conception outcomes following AI have a significant negative influence on the productivity and profitability of sheep farming enterprises. Given a single ram may inseminate several ewes naturally or hundreds of ewes via AI annually, investigating ram-side factors that contribute to conception outcomes following AI is warranted. Therefore, the research presented in Chapter 2 investigated the influence of a key ram-side factor, spermatozoal motility, on conception outcomes following on-farm AI in sheep. A total of 2,608 insemination records were used to perform logistic mixed-model regression and ordinal regression to investigate the influence of spermatozoal motility on conception outcomes (binary variable) and pregnancy scan count (ordinal variable), respectively, following on-farm AI in sheep. Fixed effects included AI site, type of semen used for insemination, spermatozoal motility, and ewe age, and a random polygenic effect was also fit. The results of Chapter 2 indicate that AI site (P-value <0.001) and spermatozoal motility (P-value = 0.024) significantly influenced conception outcomes following on-farm AI. While age of the ewe (P-value <0.001) and AI site (P-value <0.001) had a significant influence on pregnancy scan count, with spermatozoal motility approaching significance (P-value = 0.079). Given this, the aim of Chapter 3 was to determine whether genetic variance contributed to the phenotypic variability observed in routinely assessed ram semen traits. Ram semen traits like volume, gross motility, concentration, and percent post-thaw motility were found to be low to moderately heritable (0.081 – 0.170) and highly repeatable (0.412 – 0.527). Given that variability in routinely assessed ram semen traits was found to be heritable, the aim of Chapter 4 was to identify genomic regions underlying the variability observed in these routinely assessed ram semen traits. A genome-wide association study (GWAS) was performed using retrospective phenotypes for ram semen volume, gross motility, concentration, and percent post-thaw motility (results presented in Chapter 4). Thirty-five quantitative trait loci (QTL) located on 16 chromosomes were associated with ram semen traits, with several positional and putative candidates identified within significantly associated genomic regions. Finally, given that there is evidence in the literature indicating that spermatozoal transcripts could influence both conception and early embryonic development, Chapter 5 aimed to characterize the spermatozoal transcriptome of three sheep breeds common to Australia, as well as investigate whether there are differences in the spermatozoal transcriptome between ejaculates of varied quality. A total of 754 differentially expressed genes (DEGs) were identified between breed contrasts (Merino, Dohne, and Poll Dorset), and relatively low- and high-quality ejaculates. Several of the DEGs identified were previously reported to influence spermatogenesis, conception, and embryonic development. Overall, the findings reported in this thesis offer novel insights into genetic and transcriptomic determinants underlying variability observed in ram semen traits, which in turn, may be used to develop novel strategies to improve reproductive efficiency in sheep farming enterprises.
Original language | English |
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Qualification | Doctor of Philosophy |
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Place of Publication | Australia |
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Publication status | Published - 2024 |