Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

Recent advances in molecular genetic techniques will make dense marker maps available and genotyping many individuals for these markers feasible. Here we attempted to estimate the effects of ∼50,000 marker haplotypes simultaneously from a limited number of phenotypic records. A genome of 1000 cM was simulated with a marker spacing of 1 cM. The markers surrounding every 1-cM region were combined into marker haplotypes. Due to finite population size (Ne = 100), the marker haplotypes were in linkage disequilibrium with the QTL located between the markers. Using least squares, all haplotype effects could not be estimated simultaneously. When only the biggest effects were included, they were overestimated and the accuracy of predicting genetic values of the offspring of the recorded animals was only 0.32. Best linear unbiased prediction of haplotype effects assumed equal variances associated to each 1-cM chromosomal segment, which yielded an accuracy of 0.73, although this assumption was far from true. Bayesian methods that assumed a prior distribution of the variance associated with each chromosome segment increased this accuracy to 0.85, even when the prior was not correct. It was concluded that selection on genetic values predicted from markers could substantially increase the rate of genetic gain in animals and plants, especially if combined with reproductive techniques to shorten the generation interval.

https://www.genetics.org/content/genetics/157/4/1819.full.pdf

Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps

The detection of genes that control quantitative characters is a problem of great interest to the genetic mapping community. Methods for locating these quantitative trait loci (QTL) relative to maps of genetic markers are now widely used. This paper addresses an issue common to all QTL mapping methods, that of determining an appropriate threshold value for declaring significant QTL effects. An empirical method is described, based on the concept of a permutation test, for estimating threshold values that are tailored to the experimental data at hand. The method is demonstrated using two real data sets derived from F(2) and recombinant inbred plant populations. An example using simulated data from a backcross design illustrates the effect of marker density on threshold values.

/pdf/empirical-threshold-values-for-quantitative-trait-mapping-336xyasfa9.pdf

Empirical threshold values for quantitative trait mapping.

The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.

/pdf/the-uk-biobank-resource-with-deep-phenotyping-and-genomic-2fs3jmksld.pdf

The UK Biobank resource with deep phenotyping and genomic data

QTL mapping designs for species in aquaculture

Comparative aspects of embryo survival between European and Chinese breeds.

BACKGROUND The Apolipoprotein E (APOE) e4 allele is the strongest genetic risk factor for late onset Alzheimer’s disease, while the e2 allele confers protection. Previous studies report differential DNA methylation of APOE between e4 and e2 carriers, but associations with epigenome-wide methylation have not previously been characterised. METHODS Using the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimer’s disease-free APOE e4 (n=2469) and e2 (n=1118) carriers from the two largest single-cohort DNA methylation samples profiled to date. Using a discovery, replication and meta-analysis study design, methylation differences were identified using epigenome-wide association analysis and differentially methylated region (DMR) approaches. Results were explored using pathway and methylation quantitative trait loci (meQTL) analyses. RESULTS We obtained replicated evidence for DNA methylation differences in a ~169kb region, which encompasses part of APOE and several upstream genes. Meta-analytic approaches identified DNA methylation differences outside of APOE: differentially methylated positions were identified in DHCR24, LDLR and ABCG1 (2.59 x 10−100≤P≤2.44 x 10−8) and DMRs were identified in SREBF2 and LDLR (1.63 x 10−4≤P≤3.01 x 10−2). Pathway and meQTL analyses implicated lipid-related processes and high density lipoprotein cholesterol was identified as a partial mediator of the methylation differences in ABCG1 and DHCR24. CONCLUSIONS APOE e4 vs. e2 carrier status is associated with epigenome-wide methylation differences in the blood. The loci identified are located in trans as well as cis to APOE and implicate genes involved in lipid homeostasis.

https://www.biorxiv.org/content/biorxiv/early/2020/09/14/815035.full.pdf

Identification of epigenome-wide DNA methylation differences between carriers of APOE ε4 and APOE ε2

SummaryFrom each of two populations of Drosophila melanogaster, collected two months previously, from Chateau Tahbilk, S. Australia and Groningen, The Netherlands, duplicate populations were initiated in each of four environments which differed in their degree of environmental heterogeneity. Differing combinations of three food media based on oatmeal/treacle, potato or fig were used to simulate levels of environmental heterogeneity within the populations. The polymorphic loci, Adh, Est-6, G-6pdh, α-Gpdh, Pgm, Lap-D and Aph in both the Chateau Tahbilk and Groningen derived populations and 6Pgdh, which was only polymorphic in the populations which came from Chateau Tahbilk, were monitored in the experiment. The populations maintained a size of about 2500 adults and were sampled after 16 and 32 generations.Large changes of phenotype frequency were shown by all loci. Despite a frequent divergence of phenotype frequencies between duplicate cages, systematic effects of occasion and environment were present and allele frequencies at many loci were shown to be changing at a faster rate than could be due to random genetic drift.Genetic heterozygosity differed between environments but was not positively correlated with degree of environmental heterogeneity.

The genetical response to natural selection by varied environments.

In this study the effect of artificial selection on BLUP EBV for production traits on the allele frequencies of a pleiotropic QTL affecting both production and disease susceptibility was investigated. Stochastic simulations were used to model artificial selection on a production trait that is controlled, in part, by a biallelic QTL that also controls susceptibility to disease. The QTL allele increasing production also increased susceptibility to disease. Different modes of action and proportions of variation accounted for by the QTL were assessed for the production trait. The main results indicated that alleles that confer susceptibility to the disease could be maintained in the population over a long period, depending on the mode of action of the QTL. In addition, the results of the study indicate that, under various conditions, it is possible to find pleiotropic QTL that control 2 traits despite these traits appearing to be uncorrelated. Therefore, in practice, an estimate of the genetic correlation between 2 traits may be misleading when the presence of such a QTL exists. The results of this study have implications for breeding programs. For example, if a pleiotropic QTL exists that favors heterozygotes for a production trait, it would be very difficult to remove disease susceptibility alleles via traditional selection methods.

/pdf/consequences-of-selection-for-improving-production-traits-on-1k5qd596k9.pdf

Chris Haley

Papers

QTL mapping designs for species in aquaculture

Comparative aspects of embryo survival between European and Chinese breeds.

Identification of epigenome-wide DNA methylation differences between carriers of APOE ε4 and APOE ε2

The genetical response to natural selection by varied environments.

Consequences of selection for improving production traits on the frequency of deleterious alleles for fitness.