scholarly journals Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

2015 ◽  
Author(s):  
Joshua S Bloom ◽  
Iulia Kotenko ◽  
Meru J Sadhu ◽  
Sebastian Treusch ◽  
Frank W Albert ◽  
...  
Keyword(s):  
Quantitative Traits ◽  
Pairwise Interaction ◽  
Genetic Interactions ◽  
Phenotypic Variance ◽  
Trait Variation ◽  
Small Individual ◽  
Relative Contribution ◽  
Yeast Strains ◽  
Significant Additive Effect ◽  
Interaction Variance

Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here, we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL-QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL-QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies.

scholarly journals Temporal uniformity of the spontaneous mutational variance of quantitative traits in Drosophila melanogaster

2000 ◽  
Vol 75 (1) ◽  
pp. 47-51 ◽  
Author(s):  
AURORA GARCÍA-DORADO ◽  
JESUS FERNÁNDEZ ◽  
CARLOS LÓPEZ-FANJUL
Keyword(s):  
Drosophila Melanogaster ◽  
Morphological Traits ◽  
Quantitative Traits ◽  
Wing Length ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Bristle Number ◽  
Sib Mating ◽  
Mutational Variance ◽  
Interaction Variance

Spontaneous mutations were allowed to accumulate over 209 generations in more than 100 lines, all of them independently derived from a completely homozygous population of Drosophila melanogaster and subsequently maintained under strong inbreeding (equivalent to full-sib mating). Traits scored were: abdominal (AB) and sternopleural (ST) bristle number, wing length (WL) and egg-to-adult viability (V). On two occasions – early (generations 93–122) and late (generations 169–209) – ANOVA estimates of the mutational variance and the mutational line × generation interaction variance were obtained. Mutational heritabilities of morphological traits ranged from 2 × 10−4 to 2 × 10−3 and the mutational coefficient of variation of viability was 0·01. For AB, WL and V, temporal uniformity of the mutational variance was observed. However, a fluctuation of the mutational heritability of ST was detected and could be ascribed to random genotype × environment interaction.

scholarly journals Genetic yield control in sugar beet hybrids obtained by diallel crosses

2021 ◽  
Author(s):  
M. O. Kornieieva
Keyword(s):  
Genetic Analysis ◽  
Sugar Beet ◽  
Genetic Control ◽  
Quantitative Traits ◽  
Gene Interaction ◽  
Source Material ◽  
Specific Gene ◽  
Ecological Plasticity ◽  
Economically Valuable Traits ◽  
Significant Additive Effect

Purpose. The aim of our study was to determine the combination ability of the studied pollinators and identify the genetic control of the yield sign in interline diallel hybrids of sugar beet. Methods. The source material was homozygous as a result self-pollination. The combination ability and genetic control of quantitative traits were determined by the Hayman model. Results. Genetic analysis revealed that sugar beet pollinator line demonstrated genetic control of yield in diallel sugar beet hybrids by 14 genes and gene groups. Lines (BZ 1 and BZ 4) with high general combination ability demonstrated a significant additive effect of genes were selected. The effects of specific combination ability, which significantly affected the yield of heterosis hybrids, were revealed. Their share of influence was 36.4 and 23.8%, respectively. High-yielding hybrid combinations of parent genotypes were selected. They are transferred to reproduction and testing for ecological plasticity. Conclusions. Genetic control of the yield sign in diallel hybrids is found based on the Hаyman model. The influence of the combination ability of sugar beet pollinators was determined and the best parent genotype pairs were selected. According to the effects of specific gene interaction, the best combinations have been identified that can be used as sources of economically valuable traits.

scholarly journals Rare variants contribute disproportionately to quantitative trait variation in yeast

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Joshua S Bloom ◽  
James Boocock ◽  
Sebastian Treusch ◽  
Meru J Sadhu ◽  
Laura Day ◽  
...  
Keyword(s):  
Quantitative Trait ◽  
Negative Selection ◽  
Rare Variants ◽  
Population Level ◽  
Sequencing Data ◽  
Trait Variation ◽  
Yeast Strains ◽  
Fertile Ground ◽  
Variant Frequency ◽  
The Relationship

How variants with different frequencies contribute to trait variation is a central question in genetics. We use a unique model system to disentangle the contributions of common and rare variants to quantitative traits. We generated ~14,000 progeny from crosses among 16 diverse yeast strains and identified thousands of quantitative trait loci (QTLs) for 38 traits. We combined our results with sequencing data for 1011 yeast isolates to show that rare variants make a disproportionate contribution to trait variation. Evolutionary analyses revealed that this contribution is driven by rare variants that arose recently, and that negative selection has shaped the relationship between variant frequency and effect size. We leveraged the structure of the crosses to resolve hundreds of QTLs to single genes. These results refine our understanding of trait variation at the population level and suggest that studies of rare variants are a fertile ground for discovery of genetic effects.

scholarly journals Estimation of environmental and genetic contributions to telomere length variation in a wild mammal

2020 ◽  
Author(s):  
Sil H. J. van Lieshout ◽  
Alex Sparks ◽  
Amanda Bretman ◽  
Chris Newman ◽  
Christina D. Buesching ◽  
...  
Keyword(s):  
Telomere Length ◽  
Individual Variation ◽  
Evolutionary Dynamics ◽  
Meles Meles ◽  
Length Variation ◽  
Phenotypic Variance ◽  
Parental Age ◽  
Transgenerational Effects ◽  
Wild Mammal ◽  
Relative Contribution

Understanding individual variation in fitness-related traits requires separating the environmental and genetic determinants. Telomeres are protective caps at the ends of chromosomes that are thought to be a biomarker of senescence as their length predicts mortality risk and reflect the physiological consequences of environmental conditions. The relative contribution of genetic and environmental factors to individual variation in telomere length is however unclear, yet important for understanding its evolutionary dynamics. In particular, the evidence for transgenerational effects, in terms of parental age at conception, on telomere length is mixed. Here, we investigate the heritability of telomere length, using the ‘animal model’, and parental age at conception effects on offspring telomere length in a wild population of European badgers (Meles meles). While we found no heritability of telomere length, our power to detect heritability was low and a repeatability of 2% across individual lifetimes provides a low upper limit to ordinary heritability. However, year (25%) and cohort (3%) explained greater proportions of the phenotypic variance in telomere length. There was no support for parental age at conception effects, or for longitudinal within-parental age effects on offspring telomere length. Our results indicate a lack of transgenerational effects through parental age at conception and a low potential for evolutionary change in telomere length in this population. Instead, we provide evidence that individual variation in telomere length is largely driven by environmental variation in this wild mammal.

scholarly journals The Relative Contributions of Socioeconomic and Genetic Factors to Variations in Body Mass Index Among Young Adults

2020 ◽  
Vol 189 (11) ◽  
pp. 1333-1341 ◽  
Author(s):  
Rockli Kim ◽  
Adam M Lippert ◽  
Robbee Wedow ◽  
Marcia P Jimenez ◽  
S V Subramanian
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Ordinary Least Squares ◽  
Shared Environment ◽  
Phenotypic Variance ◽  
Adult Health ◽  
Least Squares Regression ◽  
Differential Distribution ◽  
Polygenic Score ◽  
Relative Contribution

Abstract In light of recent findings on the small proportion of variance in body mass index (BMI) explained by shared environment, and growing interests in the role of genetic susceptibility, we assessed the relative contribution of socioeconomic status (SES) and genome-wide polygenic score for BMI to explaining variation in BMI. Our final analytic sample included 4,918 White and 1,546 Black individuals from the US National Longitudinal Study of Adolescent to Adult Health Wave IV (2007–2008) who had complete measures on BMI, demographics, SES, genetic data, and health behaviors. We used ordinary least-squares regression to assess variation in log(BMI) as a function of the aforementioned predictors, independently and mutually adjusted. All analyses were stratified by race/ethnicity in the main analysis, and further by sex. The age-adjusted variation in log(BMI) was 0.055 among Whites and 0.066 among Blacks. The contribution of SES and polygenic score ranged from less than1% to 6% and from 2% to 8%, respectively, and majority of the variation (87%–96%) in log(BMI) remained unexplained. Differential distribution of socioeconomic resources, stressors, and buffers may interact to produce systematically larger variation in vulnerable populations. More understanding of the contribution of biological, genetic, and environmental factors, as well as stochastic elements, in diverse phenotypic variance is needed in population health sciences.

scholarly journals Phenotypic variability in a population of globe artichoke

2014 ◽  
Vol 44 (11) ◽  
pp. 2003-2009
Author(s):  
Angélica Reolon da Costa ◽  
Simone Meredith Scheffer Basso ◽  
Magali Ferrari Grando ◽  
Vanina Pamela Cravero
Keyword(s):  
Clustering Analysis ◽  
Quantitative Traits ◽  
Phenotypic Variability ◽  
Fresh Mass ◽  
Globe Artichoke ◽  
Head Shape ◽  
Relative Contribution ◽  
Quantitative Characters ◽  
Selection For ◽  
Rural Producers

The existence of variability is a prerequisite for genetic improvement in plants. Globe artichoke is a high nutritious vegetable with medical value, representing a profitable alternative for rural producers. This research was conducted with the aim of evaluating the phenotypic variability in a commercial cultivar of artichoke (Cynara cardunculus var. scolymus L) established from seeds. Field plants were assessed when primary head reached commercial stage. An amount of 21 quantitative and 5 multicategoric characters were assessed. The quantitative data were submitted to multivariate analysis. For quantitative characters the distance between individuals varied from 3.0 to 50.9, revealing high intrapopulation variability. The greater relative contribution characters for genetic divergence were the primary head fresh mass (79.88%) and bottom fresh mass (8.43%). This indicates the possibility of plant selection for head quality in this population. The clustering analysis through UPGMA method, based on quantitative characters, allowed the formation of five groups. For multicategoric traits, the similarity among individuals varied from 1.22% to 100%. Within the existing population variability, it was possible to select plants with superior quantitative traits desirable for in natura consumption, as primary head fresh weight and length, bottom fresh mass, bract basis length and width, as well as non-quantitative traits as round head shape, absence of thorn and presence of violet color in the head.

scholarly journals The relative contribution of diet and genotype to bone development

2001 ◽  
Vol 60 (1) ◽  
pp. 45-52 ◽  
Author(s):  
Ann Prentice
Keyword(s):  
Bone Mineral ◽  
Bone Growth ◽  
Environmental Variability ◽  
Bone Development ◽  
Phenotypic Variance ◽  
Mineral Density ◽  
Bone Mineral Mass ◽  
Relative Contribution ◽  
Increased Risk ◽  
Mineral Mass

The present review addresses the relative contribution of diet and genotype to variability in human bone growth and mineralisation in the context of the aetiology of osteoporosis. Heritability studies indicate that 60–70 % of the variability in bone mineral mass or bone mineral density (BMD) can be accounted for by genetic variation. Cross-trait analyses suggest that a proportion of this variation reflects genetic influences on bone and body size, such as height and lean body mass. Candidate-gene studies have demonstrated associations between several genetic polymorphisms and bone mineral mass but, as yet, genotype determinations have proved unhelpful in identifying individuals at increased risk of osteoporosis. Variations in diet and other environmental factors contribute 30–40 % to total phenotypic variance in bone mineral mass or BMD. Correlations between intakes of individual nutrients and BMD have been reported, but these relationships are subject to confounding due to size. However, no specific dietary factor has been identified from prospective and twin studies as making a significant contribution to environmental variability in BMD or bone loss. This finding may reflect the difficulties in quantifying environmental exposures, both current and over a lifetime. In addition, the influence of diet on bone health may depend on the genotype of the individual. Optimisation of nutrition and lifestyle remains an attractive strategy for the reduction of fracture risk, but more research is required to fully define optimal dietary requirements.

scholarly journals Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Joshua S. Bloom ◽  
Iulia Kotenko ◽  
Meru J. Sadhu ◽  
Sebastian Treusch ◽  
Frank W. Albert ◽  
...  
Keyword(s):  
Quantitative Trait ◽  
Genetic Interactions ◽  
Additive Effects ◽  
Trait Variation
Sign in / Sign up

Export Citation Format

Share Document