Individual Genetic Variation

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Inter-individual genetic variation in the temperature response of Leptosphaeria species pathogenic on oilseed rape

Inter-individual genetic variation in the temperature response of Leptosphaeria species pathogenic on oilseed rape

In replicate 1, the petioles of the lowest two leaves of the three plants in each pot were all inoculated with the same isolate. Temperature in the glasshouse was high on the day of inoculation, reaching a maximum of 30 °C. Mean glasshouse temperature (mean of minimum and maximum temperatures) during the following week was 26.6 °C ± 2.1 °C. In replicate 2, only the lowest leaf petiole was inoculated to initiate one canker per plant. Individual plants within each pot were inoculated with a different isolate in a partially-balanced block design. Pots with inoculated plants were placed in a Latin square design within the plastic coverings. Separate pots containing three control plants, inoculated with sterile water, were incubated beneath a separate plastic covering to prevent contamination from inoculated plants. Plants remained in a controlled environment at 20 °C ± 1 °C.
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Characterisation of the global transcriptional response to heat shock and the impact of individual genetic variation

Characterisation of the global transcriptional response to heat shock and the impact of individual genetic variation

Our results are necessarily exploratory given the mod- est sample size of this study requiring further validation and functional characterisation to establish mechanism. If functionally validated, the geographic distribution of the major and minor alleles of rs12207548 suggests se- lection may be operating on such variants. We recognise that there may be cell type-specific differences in heat shock response not captured by our analysis in LCLs, in- cluding differences in HSF binding from the K562 cell line, and that there may also be population specific differ- ences in terms of regulatory variants with the data pre- sented here generated in cells from individuals of African ancestry. We elected to follow a focused high-level ap- proach in this paper as we are not adequately powered for a systematic QTL analysis of all individual genes.
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Inter-individual genetic variation in the temperature response of Leptosphaeria species pathogenic on oilseed rape

Inter-individual genetic variation in the temperature response of Leptosphaeria species pathogenic on oilseed rape

The rate of evolutionary adaptation to an altered temperature depends on how large the additive variance is in relevant phe- notypic traits, relative to the variance caused by the differences between the environments experienced by each individual. The additive genetic variance will be less than the variance due to all genotypic differences that we measured in the work reported here, because epistatic effects will be only partly inherited fol- lowing sex, which breaks up associations between loci. In a natu- ral setting, the rate of evolution of temperature response depends on the environmental variance in growth rate, which determines heritability. This is presumably affected by host cultivar, position of the initial infection on the leaf, and numerous factors such as fertility, rainfall, age of leaf at infection, insect damage, and the extent of host defence triggering. Even if we further assume the genotypic variance between isolates was mostly due to additive effects, with negligible epistatic effects, the heritability is likely to be small and, therefore, the likely change between years in the population mean of T opt , R max , T min or in ability to grow at high temperatures is small.
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Molecular and cellular studies in evolutionary physiology of natural vertebrate populations: influences of individual variation and genetic components on sampling and measurements

Molecular and cellular studies in evolutionary physiology of natural vertebrate populations: influences of individual variation and genetic components on sampling and measurements

Organisms with a short generation time, such as bacteria (e.g. Bennett and Lenski, 1999) and Drosophila (e.g. Feder et al., 2002), are often used to study the combination of physiological responses (traits), their genetic variation and evolvability, since the responses of multiple generations to selective forces (e.g. environmental conditions) can be followed in selection experiments relatively easily and rapidly. However, even though the use of vertebrates in evolutionary physiological studies is hampered by the fact that their generation times are long, making it difficult to follow the heritability of responses across generations, there are some reasons, why vertebrate studies are important. First, much of the ecological and evolutionary literature is on vertebrates, and therefore it is helpful if, in addition to studies on invertebrates with short generation times, studies on vertebrates are carried out so that the conclusions based on invertebrates can be related to vertebrate systems. Second, vertebrates are much more visible than invertebrates, whereby they appear more often in public conservation interests. Third, some vertebrates are economically important or used in production biology, both in agri- and aquaculture. Fourth, mammalian studies are considered to be especially relevant for human systems. Notably, medical studies are the best source of genetic information on vertebrates. Apart from medical studies, there are very few functional studies (especially at the cellular and molecular level) on individual genetic variation that have been frequently cited, even within a single generation of a population, although individual variability is important for any population response. This is probably because many of the vertebrate studies with information about differences between individuals are on non-mammalian animals such as lizards and snakes (e.g. Bennett, 1980; Arnold, 1983). Notably, however, Garland’s group have subjected mice to controlled treadmill exercise over many generations, and have followed the performance of animals, focusing additionally on several components of muscle function (Dumke et al., 2001; Gomes et al., 2004; Bronikowski et al., 2006; Garland and Kelly, 2006). Examples of cellular and molecular studies on non-mammalian vertebrates that have considered interindividual differences include those of Crawford’s group, who have studied the evolution of gene expression in Fundulus heteroclitus (Whitehead and Crawford, 2006a; Whitehead and Crawford, 2006b).
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Genetic variation in bulls divergent for fertility

Genetic variation in bulls divergent for fertility

One limiting factor in evaluating bull fertility is a lack of detailed bull fertility phenotypic data (Carthy et al., 2016). Daughter pregnancy rate (DPR) is a common bull fertility phenotype used. DPR is a measure of a sire’s daughter’s ability to become pregnant, rather than a measure of his own ability to get cows pregnant. This may result in under-reporting of sub-fertility. DPR does not accurately measure male fertility, as additional effects need to be accounted for, including AI technician and cow health. Statistical models may provide more accurate assessments of male fertility given high-quality phenotypic data. Berry et al. suggest a benefit of using a statistical model to better estimate the performance of service bulls (Berry et al., 2011a). The study identified correlations between rankings of service bulls on male fertility differs when systematic environmental, as well as genetic effects, are accounted for in a mixed model. Sub-fertility may be caused by low libido, sperm quality, sperm quantity, sperm defects, or physical defects affecting bull motility and mating ability (Teagasc, 2016a). Use of sub-fertile bulls will result in low pregnancy rates, an extended calving interval, and increased culling of cows for infertility reasons. Sub-fertile bulls can go undetected in the herd for large periods of the breeding season, unless constant vigilance is maintained. In addition, bull breeding soundness evaluations may need to be performed (Teagasc, 2016b).
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A Genetic Interpretation of the Variation in Inbreeding Depression

A Genetic Interpretation of the Variation in Inbreeding Depression

such as additive-by-dominance and dominance-by-domi- for selection to act upon and reduce inbreeding load. nance epistasis (Crow and Kimura 1970, pp. 78–80). The problem with this perspective is that inbreeding The among-line variance also increases owing to the seg- complicates the concept of heritability by changing the regation among lines of these genetic factors as well as nature of the regression of parents on offspring. Indeed, the additive and additive-by-additive epistatic genetic vari- Falconer (1985, p. 337) states that the concept of ances (Cockerham and Weir 1968; Goodnight 1988). breeding value, from which narrow sense heritability Inbreeding depression (ID) is believed to play an is measured, has “no useful meaning when mating is important but complicated role in the evolution of mat- nonrandom.” Although the change in the parent-off- ing systems (e.g., Holsinger 1988; Uyenoyama et al. spring regression can be predicted for particular cases 1993). For example, in the evolution of selfing and (e.g., for selfing, see Wright and Cockerham 1986), outcrossing in plants, inbreeding initially selects against the variance components affecting selective response in selfing lineages by lowering mean fitness. However, if inbred populations are different from those contribut- the genes responsible for ID are purged by selection ing to ␴ 2
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The genetic architecture of interspecific variation in mimulus.

The genetic architecture of interspecific variation in mimulus.

Some variation in the expression of the gene was found in segregating families (Figure 2), indicating that there are probably other genes modifying its expression, [r]

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GENETIC VARIATION IN CHAETAE NUMBER OF TRIBOLIUM

GENETIC VARIATION IN CHAETAE NUMBER OF TRIBOLIUM

If a n upper limit near six chaetae initially existed for the male phenotype (the slow initial response suggested this to be the case), this threshold was clearly broken b[r]

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Genetic variation in Aciphylla glaucescens (Apiaceae)

Genetic variation in Aciphylla glaucescens (Apiaceae)

BIOSYS-1.7 (Swofford and Selander, 1989) was used to analyse data. A locus was considered polymorphic if the frequency of the most common allele did not exceed 0.95. The following genetic parameters were estimated: mean number of alleles per locus (A p ), percent polymorphic loci (P), and expected panmictic heterozygosity or gene diversity, (H e ) (unbiased estimate according to Nei 1978). Wright’s (1965) F- statistics (F IT , F IS and F ST ) were calculated over all populations of A. glaucescens and for each pair of populations over all polymorphic loci. From this an indirect measure of gene flow (N m ), assuming an island model of population structure, was derived from the relationship of neutral alleles: N m = ((1/F ST )-1)/4 (Wright, 1951). Information on the sex of individuals sampled from the Black Birch population allowed analysis of relative contributions of the separate sexes to the genetic structure of this population. Genotype
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Genetic variation of traits in natural enemies

Genetic variation of traits in natural enemies

List of 69 studies examining the genetic heritability of traits in biological control agents. 797[r]

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Mutation models and quantitative genetic variation.

Mutation models and quantitative genetic variation.

Because mutation does not change the mean of allelic effects and the increase of the genetic variance is expected to be constant, the model is also called t h e [r]

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Identifying genetic variation contributing to keratoconus

Identifying genetic variation contributing to keratoconus

cases and 626 unaffected controls with genome-wide genotyping data. To appropriately capture the association peaks during fine-mapping, variants across the surrounding gene were included for intronic loci, whereas the region encompassing the flanking genes were included for intergenic loci. Strong association peaks were observed at all loci except the previously reported RAB3GAP1 locus, thus this locus was not further analysed. To further assess variation carried on the risk-associated haplotypes at remaining loci, keratoconus patients carrying the risk allele for the top SNP determined in Aim 2 were selected for re-sequencing in Aim 3. A total of 178 cases and 62 controls were re-sequenced across the five loci. Variants at each locus were filtered to identify those that were carried on the risk-associated haplotype; in high LD with the top SNP as measured by D’ to ensure the capture of both common and rare variants; and were more common in the cases compared to the controls and all populations available in Genome Aggregation Database (gnomAD). These variants were further prioritised based on deleteriousness/pathogenicity predictions and whether or not the variant was likely to disrupt a regulatory region. This analysis identified putatively functional variants at all five loci, and proposed rs79728429 as a functional variant at the FOXO1 (rs2721051) locus. From this work, it was further hypothesised that that rs79728429 alters the expression of a novel uncharacterised gene, AL133318.1, and that this altered expression in the cornea confers an increased susceptibility to keratoconus at this locus.
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Genetic variation in natural populations of Daphnia .

Genetic variation in natural populations of Daphnia .

Loci were numbered in order of increasing mobility. Alleles were designated slow (S), medium (M) or fast (F) depending on their relative rate of migration from the origin. If variation was detected at a particular locus the sample size was increased to 144 or more. In addition* at least 24 females from each pond were isolated in 100 ml plastic beakers and maintained as described in Chapter II. Mortal­ ity due to transfer from pond water to artificial medium was negligible.

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Bayesian nonparametric models of genetic variation

Bayesian nonparametric models of genetic variation

Bayesian nonparametric statistics were first developed in the late 70s to provide prior distributions which have both arbitrarily large support and also tractable posteriors. Recently, the development of the nonparametric hierarchical Dirichlet process ( Teh et al. , 2006 ) has allowed a wide variety of classical statistical tools (such as HMMs) to make use of Bayesian nonparametric priors. This has lead to a resurgence of interest in Bayesian nonparametric models, and much insight into the latent structure of the data to which these models have been applied. Methodologically, the models presented in this thesis are some of the most sophisticated applications of Bayesian nonparametrics to genetics that has been derived to date. Further, we have made available the code for the BNPPHASE model, and have provided a detailed description of these methods which are of interest to the broader bioinformatics and population genetics community. We have presented three new Bayesian nonparametric clustering models (BNPPHASE, DFCP and WFP). The BNPPHASE and DFCP models are motivated by the genetic process and have similarities to many popular models currently used in statistical genetics. We explored these models through applications to various sources of data such as simulated bottlenecks, X chromosomes from The Thousand Genomes Project, SNP data from the HapMap Project and also SNP data from the SeattleSNPs project. We showed that genotype imputation accuracy for our nonparametric models was often better than that of the related parametric models, and we were able to interpret the latent variables of the BNPPHASE model as founders in population bottlenecks or as rescaled versions of the time to most recent common ancestor. To illustrate the versatility of Bayesian nonparametric models, we also applied the WFP model to predict votes and to uncover political blocs in data from the Canadian House of Parliament.
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Genetic Variation for Waterlogging Tolerance in Cotton

Genetic Variation for Waterlogging Tolerance in Cotton

in Australia, periodic waterlogging through- out the cotton growing season can cause pro- duction losses of up to 10%. There is limited information on the genetic variation in cotton for waterlogging tolerance. The aim of this study was to identify methods to evaluate physiological responses under waterlogging conditions that may lead to identifying waterlogging tolerant and sensitive cotton cultivars. A field experiment was conducted in narrabri, north-western new South Wales using thirteen upland cotton (Gossypium hirsutum l.) cultivars (georgia King, mcnair 1032, PD93057, lA 887, Codetec 401, DP 16, DP 90, Coker 315, Cim 443, gohar 87, Sicot 71, Sicot 73 and Sicot 80) and one Gossypium barbadense cultivar (Pima A-8) originating from diverse environmental regions. Parameters measured to assess response to waterlogging included: SPAD (leaf colour) readings, leaf nutritional status, leaf photosynthetic rate, plant and root morphology, and final yield. Leaf SPAD readings, nitrogen and potassium concentrations were reduced in waterlogged treatments compared to the respec- tive controls, and varied with cultivar. leaf phos- phorus, calcium, magnesium, manganese and sulphur concentrations were reduced in the wa- terlogged treatment compared to the respective controls in all cultivars. Waterlogging increased leaf total iron concentration in all cultivars. no aerenchyma on cotton roots were observed in this study. leaf SPAD readings, nitrogen and potassium concentrations suggested that the most waterlogging tolerant cultivars were gohar 87,
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Genetic contribution to individual variation in binocular rivalry rate

Genetic contribution to individual variation in binocular rivalry rate

The heritability and genetics of individual variation in human colour vision are well understood, with molecular and physiological mechanisms in the retina particularly well characterised 1 . In contrast, very little is known about the heritability and mechanisms of individual variation for any post-retinal visual processing phenomena 2 . Binocular rivalry (BR) is a well-studied perceptual phenomenon that occurs when dissimilar images are presented in corresponding locations of the two eyes 3 . To resolve the resulting visual ambiguity, perception alternates every few seconds between the conflicting images, at a rate that is relatively stable within individuals but that varies widely between individuals 4,5 . The determinants and mechanisms of individual variation in BR rate have yet to be elucidated. Here, using a large genetically informative sample, we present evidence demonstrating a substantial genetic contribution to an individual’s BR rate. One hundred and twenty-eight monozygotic (MZ) and 220 dizygotic (DZ) twin pairs, and 26 unpaired co-twins, reported BR with orthogonal drifting gratings, over 21 minutes of viewing. Correlations for BR rate in MZ and DZ twins were 0.51 and 0.19, respectively. Genetic modelling showed 52% of the variance in BR rate was accounted for by additive genetic factors in the best fitting model. This is the first study to report a substantial genetic contribution to individual variation in BR rate, and furthermore, is the first large study to do so for any post- retinal visual processing phenomena. The results have important implications for understanding BR mechanisms, and suggest that genetic and molecular approaches to investigating the phenomenon should be vigorously pursued. The results also have important clinical and pathophysiological implications because BR rate is abnormally slow in bipolar disorder 4-6 , a common psychiatric condition known to be highly heritable 7 .
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Effects of Genetic Drift and Gene Flow on the Selective Maintenance of Genetic Variation

Effects of Genetic Drift and Gene Flow on the Selective Maintenance of Genetic Variation

is only one of these factors, and the frequency patterns are easily confounded by these other factors, it is not surprising that the Ewens–Watterson test (Ewens 1972; Watterson 1977, 1978), designed to detect selection based on allele-frequency data, has a low power, especially in a spatial model (Gillespie 1991; Star et al. 2007a). Nevertheless, genetic drift and finite populations have some interesting effects on the proportion of frequency vectors that can be distinguished from neutrality. For smaller populations, the combined effect of genetic drift and a lower number of mutants encountered results in a reduction of rare alleles. Therefore, the remaining alleles are likely to have a more even frequency distribution, which results in more vectors being rejected from neutrality for being considered too even. This effect is especially strong when spatial structure is ignored, and all frequencies are pooled. In contrast, for larger populations, the higher number of mutants encountered results in more rare alleles and more skewed frequency distributions. Genetic drift further increases this number of rare alleles by the introduction of slightly deleterious alleles. While the increase in skewed frequency distributions obviously reduces the number of allele-frequency vectors that can be distinguished for being
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Functional impact of genetic variation on gene expression

Functional impact of genetic variation on gene expression

The three chapters presented in this thesis provide significant new insights into the extent of genetic variation and its link and potential implication for gene expression regulation. Each of the three chapters approaches the topic from a different angle, each providing unique views on the functional consequences of genetic variation in natural populations. In the first project we specifically looked at the extent of copy number variation in Cynomolgus monkey and used gene expression changes to assess their potential implications for the organism. Even though this species is very widely used in biomedical and pharmaceutical research, the extent of ge- netic variation and especially copy number variation within these animals has not been studied extensively so far. We find considerable copy number variation among the sampled individu- als, which comes not unexpected, because unlike inbred laboratory mice strains, Cynomolgus monkeys used in pharmaceutical research are regularly captured in wild population across the world. In line with other studies [39], we discover predominately small variants of a few kilo- bases length as expected in healthy individuals from natural populations. The detected copy number variation clearly separates our individuals according to populations. This indicates a diverse genetic background in pharmaceutical studies when using Cynomolgus monkeys orig- inating from different populations. Our results show that part of this variation is linked gene expression changes in vitally important tissues. Multiple copy number polymorphisms and as- sociated gene expression changes within a cluster of olfactory receptor genes on chromosome 7 demonstrate intraspecific functional variation in a region well known for genomic rearrange- ments [45, 46, 152].
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Assessing genetic variation in growth and development of potato

Assessing genetic variation in growth and development of potato

Yin and Van Laar (2005), along the aforementioned lines of thinking, presented a crop model, GECROS (Genotype‐by‐Environment interaction on CROp growth Simulator), to overcome some of the weaknesses of earlier crop models. GECROS captures traits of genotype‐specific responses to environment based on quantitative descriptions of complex traits related to the phenology, root system development, photosynthesis, stomatal conductance, and stay‐green traits. GECROS uses new algorithms to summarise current knowledge of individual physiological processes and their interactions and feedback mechanisms (Chapter 5). It attempts to model each sub‐process at a consistent level of detail, so that no process is overemphasised or requires too many parameters and similarly no process is treated in a trivial manner, unless unavoidable because of lack of understanding. GECROS also tries to maintain a balance between robust model structure, high computational efficiency, and accurate model output. The model can be used for examining responses of biomass and dry matter production in arable crops to both environmental and genotypic characteristics.
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Intra  and inter individual variation in flight direction in a migratory butterfly co vary with individual mobility

Intra and inter individual variation in flight direction in a migratory butterfly co vary with individual mobility

Interestingly, although individuals showed a general tendency to orientate in northern directions, inter-individual variation in flight direction was found both between and within families, which may have several non-exclusive origins. Flight direction may be inherited in P. brassicae (and may possibly be due to parental effects), which would be consistent with the studies of Spieth and colleagues (Spieth and Kaschuba-Holtgrave, 1996; Spieth and Cordes, 2012). In the sister species Pieris rapae, Baker also concluded that migratory direction was a selected and inherited trait that was independent of the mother’s orientation and was determined solely by the male parent (Baker, 1968). Alternatively, variation can reflect different responses to environmental cues not measured in our experiment (daytime, wind, larvae density, etc.). Nevertheless, tests were performed under very similar conditions (temperature, sunshine, position of the experimental cage), individuals were bred under similar conditions, and orientation was highly repeatable in this species [see our results and those of Spieth and colleagues (Spieth and Kaschuba-Holtgrave, 1996; Spieth et al., 1998)]. This gives more credit to the inheritance hypothesis than to the environmental hypothesis. Interestingly, both innate and environmentally induced orientation have been described in migrating birds (Pasinelli et al., 2004; Ogonowski and Conway, 2009) and flight direction depends greatly on the flight direction of the mother. Other experiments are now needed to enable conclusions to be drawn on the mode of inheritance of flight direction in P.brassicae, especially as inherited traits related to migration and dispersal have been suggested to have both a genetic (Spieth and Cordes, 2012) and a non-genetic basis (Ducatez et al., 2012a) in this species.
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