scholarly journals Adaptation in outbred sexual yeast is repeatable, polygenic, and favors rare haplotypes

2021 ◽  
Author(s):  
Robert A. Linder ◽  
Behzad Zabanavar ◽  
Arundhati Majumder ◽  
Hannah Chiao-Shyan Hoang ◽  
Vanessa Genesaret Delgado ◽  
...  
Keyword(s):  
Rare Variants ◽  
Intermediate Frequency ◽  
Effective Population ◽  
Entire Genome ◽  
Frequency Shifts ◽  
Haplotype Blocks ◽  
Genome Wide ◽  
Population Sizes ◽  
Drug Treatments ◽  
Per Gene

AbstractWe describe the results of a 200 generation Evolve and Resequence (E&R) study initiated from an outbred dipliod recombined synthetic base population derived from 18 genetically diverse founders. Replicate populations were maintained at large effective population sizes (>105 individuals), exposed to several different chemical challenges over 12 weeks of evolution, and whole-genome resequenced. Weekly forced outcrossing implies a per gene per cell-division recombination rate higher than that achieved in Drosophila E&R studies. In 55 sexual populations we observe large fitness gains and highly repeatable patterns of genome-wide haplotype change within each chemical challenge. There was little evidence for pervasive pleiotropy, as evidenced by patterns of haplotype change between drug treatments. Within treatment adaptation appears highly polygenic with almost the entire genome showing significant consistent haplotype change. Finally, adaptation was almost always associated with only one of the 18 founder alleles, suggesting selection primarily acts on rare variants private to a founder or haplotype blocks harboring multiple mutations. This observation contradicts the notion that adaptation is often due to subtle frequency shifts at intermediate frequency variants.

scholarly journals Disease association with frequented regions of genotype graphs

2020 ◽  
Author(s):  
Samuel Hokin ◽  
Alan Cleary ◽  
Joann Mudge
Keyword(s):  
Rare Variants ◽  
Disease Risk ◽  
Association Studies ◽  
Disease Status ◽  
Disease Association ◽  
Genome Wide Association Studies ◽  
Entire Genome ◽  
Machine Learning Classification ◽  
Complementary Method ◽  
Genome Wide

Complex diseases, with many associated genetic and environmental factors, are a challenging target for genomic risk assessment. Genome-wide association studies (GWAS) associate disease status with, and compute risk from, individual common variants, which can be problematic for diseases with many interacting or rare variants. In addition, GWAS typically employ a reference genome which is not built from the subjects of the study, whose genetic background may differ from the reference and whose genetic characterization may be limited. We present a complementary method based on disease association with collections of genotypes, called frequented regions, on a pangenomic graph built from subjects' genomes. We introduce the pangenomic genotype graph, which is better suited than sequence graphs to human disease studies. Our method draws out collections of features, across multiple genomic segments, which are associated with disease status. We show that the frequented regions method consistently improves machine-learning classification of disease status over GWAS classification, allowing incorporation of rare or interacting variants. Notably, genomic segments that have few or no variants of genome-wide significance (p<5x10-8) provide much-improved classification with frequented regions, encouraging their application across the entire genome. Frequented regions may also be utilized for purposes such as choice of treatment in addition to prediction of disease risk.

scholarly journals The formation of avian montane diversity across barriers and along elevational gradients

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
José Martín Pujolar ◽  
Mozes P. K. Blom ◽  
Andrew Hart Reeve ◽  
Jonathan D. Kennedy ◽  
Petter Zahl Marki ◽  
...  
Keyword(s):  
Gene Flow ◽  
Population Differentiation ◽  
Bird Species ◽  
Geographic Area ◽  
Effective Population ◽  
Tropical Mountains ◽  
Mountainous Regions ◽  
Pleistocene Climate ◽  
Genome Wide ◽  
Population Sizes

AbstractTropical mountains harbor exceptional concentrations of Earth’s biodiversity. In topographically complex landscapes, montane species typically inhabit multiple mountainous regions, but are absent in intervening lowland environments. Here we report a comparative analysis of genome-wide DNA polymorphism data for population pairs from eighteen Indo-Pacific bird species from the Moluccan islands of Buru and Seram and from across the island of New Guinea. We test how barrier strength and relative elevational distribution predict population differentiation, rates of historical gene flow, and changes in effective population sizes through time. We find population differentiation to be consistently and positively correlated with barrier strength and a species’ altitudinal floor. Additionally, we find that Pleistocene climate oscillations have had a dramatic influence on the demographics of all species but were most pronounced in regions of smaller geographic area. Surprisingly, even the most divergent taxon pairs at the highest elevations experience gene flow across barriers, implying that dispersal between montane regions is important for the formation of montane assemblages.

scholarly journals Evaluation of Linkage Disequilibrium, Effective Population Size and Haplotype Block Structure in Chinese Cattle

Animals ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 83 ◽  
Author(s):  
Lei Xu ◽  
Bo Zhu ◽  
Zezhao Wang ◽  
Ling Xu ◽  
Ying Liu ◽  
...  
Keyword(s):  
Linkage Disequilibrium ◽  
Genomic Selection ◽  
Haplotype Block ◽  
Block Structure ◽  
Effective Population ◽  
Chinese Cattle ◽  
Genome Wide ◽  
Population Sizes ◽  
Haplotype Block Structure ◽  
Selection For

Understanding the linkage disequilibrium (LD) across the genome, haplotype structure, and persistence of phase between breeds can enable us to appropriately design and implement the genome-wide association (GWAS) and genomic selection (GS) in beef cattle. We estimated the extent of genome-wide LD, haplotype block structure, and the persistence of phase in 10 Chinese cattle population using high density BovinHD BeadChip. The overall LD measured by r2 between adjacent SNPs were 0.60, 0.67, 0.58, 0.73, and 0.71 for South Chinese cattle (SCHC), North Chinese cattle (NCC), Southwest Chinese cattle (SWC), Simmental (SIM), and Wagyu (WAG). The highest correlation (0.53) for persistence of phase across groups was observed for SCHC vs. SWC at distances of 0–50 kb, while the lowest correlation was 0.13 for SIM vs. SCHC at the same distances. In addition, the estimated current effective population sizes were 27, 14, 31, 34, and 43 for SCHC, NCC, SWC, SIM, and WAG, respectively. Our result showed that 58K, 87K, 95K, 52K, and 52K markers were required for implementation of GWAS and GS in SCHC, NCC, SWC, SIM, and WAG, respectively. Also, our findings suggested that the implication of genomic selection for multipopulation with high persistence of phase is feasible for Chinese cattle.

scholarly journals Genome-Wide Linkage Disequilibrium and the Extent of Effective Population Sizes in Six Chinese Goat Populations Using a 50K Single Nucleotide Polymorphism Panel

Animals ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 350 ◽  
Author(s):  
Haile Berihulay ◽  
Rabiul Islam ◽  
Lin Jiang ◽  
Yuehui Ma
Keyword(s):  
Linkage Disequilibrium ◽  
Genetic Parameter ◽  
Genetic Selection ◽  
Chromosome 1 ◽  
Effective Population ◽  
Genome Wide ◽  
Population Sizes ◽  
Trait Locus ◽  
D Values ◽  
Genome Wide Linkage Disequilibrium

Genome-wide linkage disequilibrium is a useful parameter to study quantitative trait locus (QTL) mapping and genetic selection. In many genomic methodologies, effective population size is an important genetic parameter because of its relationship to the loss of genetic variation, increases in inbreeding, the accumulation of mutations, and the effectiveness of selection. In this study, a total of 193 individuals were genotyped to assess the extent of LD and Ne in six Chinese goat populations using the SNP 50K BeadChip. Across the determined autosomal chromosomes, we found an average of 0.02 and 0.23 for r2 and D’ values, respectively. The average r2 between all the populations varied little and ranged from 0.055 r2 for the Jining Grey to 0.128 r2 for the Guangfeng, with an overall mean of 0.083. Across the 29 autosomal chromosomes, minor allele frequency (MAF) was highest on chromosome 1 (0.321) and lowest on chromosome 25 (0.309), with an average MAF of 0.317, and showing the lowest (25.5% for Louping) and highest (28.8% for Qingeda) SNP proportions at MAF values > 0.3. The inbreeding coefficient ranged from 0.064 to 0.085, with a mean of 0.075 for all the autosomes. The Jining Grey and Qingeda populations showed higher Ne estimates, highlighting that these animals could have been influenced by artificial selection. Furthermore, a declining recent Ne was distinguished for the Arbas Cashmere and Guangfeng populations, and their estimated values were closer to 64 and 95, respectively, 13 generations ago, which indicates that these breeds were exposed to strong selection. This study provides an insight into valuable genetic information and will open up the opportunity for further genomic selection analysis of Chinese goat populations.

scholarly journals 229 DNA sequence assisted prediction: the uncomfortable truth

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 55-55
Author(s):  
Miguel Perez-Enciso
Keyword(s):  
Rare Variants ◽  
High Density ◽  
Whole Genome Sequence ◽  
Effective Population ◽  
Genotype Calling ◽  
Population Sizes ◽  
Improving Accuracy ◽  
Ngs Data ◽  
And Training ◽  
Risky Option

Abstract Using whole genome sequence for improving genomic prediction relative to that from high density SNP arrays has been well below expectations, despite some overoptimistic computer simulations. Why is this so? First, NGS data are massive, noisy and their computer bioinformatics analysis is expensive when applied to the scale needed in animal breeding. SNP calling is a tricky procedure that is especially sensitive to low depth sequencing. This makes it NGS data far more expensive than array genotyping. Second, rare variants are the most frequent class of variants. Population genetics theory dictates that the number of SNPs of a given frequency f is inversely proportional to f. For prediction purposes, it is clear that rare variants are not useful, because it is very likely that they do not segregate in both testing and training subpopulations. Third, sequence contains highly repetitive info, the number of new SNPs decreases quickly with adding new samples and, further, low effective population sizes in domestic animals makes it disequilibrium to be large. What can we do about it? First, high density data can be imputed up to sequence; this has a mild - and limited - effect on improving accuracy. Second, sequence at very low depth on numerous animals can be obtained. This is an extremely risky option that I discourage due to strong biases in heterozygous genotype calling. Third, predictions can be constructed using some sort of prior information (e.g., based on known causative genes or from GWAS studies) together with high density, perhaps custom designed arrays. I believe this is the most promising approach.

scholarly journals Dissecting the Effects of Selection and Mutation on Genetic Diversity in Three Wood White (Leptidea) Butterfly Species

2019 ◽  
Vol 11 (10) ◽  
pp. 2875-2886 ◽  
Author(s):  
Venkat Talla ◽  
Lucile Soler ◽  
Takeshi Kawakami ◽  
Vlad Dincă ◽  
Roger Vila ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Natural Selection ◽  
Nucleotide Diversity ◽  
Gene Annotation ◽  
Rate Variation ◽  
Butterfly Species ◽  
Relative Role ◽  
Effective Population ◽  
Genome Wide ◽  
Population Sizes

Abstract The relative role of natural selection and genetic drift in evolution is a major topic of debate in evolutionary biology. Most knowledge spring from a small group of organisms and originate from before it was possible to generate genome-wide data on genetic variation. Hence, it is necessary to extend to a larger number of taxonomic groups, descriptive and hypothesis-based research aiming at understanding the proximate and ultimate mechanisms underlying both levels of genetic polymorphism and the efficiency of natural selection. In this study, we used data from 60 whole-genome resequenced individuals of three cryptic butterfly species (Leptidea sp.), together with novel gene annotation information and population recombination data. We characterized the overall prevalence of natural selection and investigated the effects of mutation and linked selection on regional variation in nucleotide diversity. Our analyses showed that genome-wide diversity and rate of adaptive substitutions were comparatively low, whereas nonsynonymous to synonymous polymorphism and substitution levels were comparatively high in Leptidea, suggesting small long-term effective population sizes. Still, negative selection on linked sites (background selection) has resulted in reduced nucleotide diversity in regions with relatively high gene density and low recombination rate. We also found a significant effect of mutation rate variation on levels of polymorphism. Finally, there were considerable population differences in levels of genetic diversity and pervasiveness of selection against slightly deleterious alleles, in line with expectations from differences in estimated effective population sizes.

scholarly journals Exploring the Legacy of Central European Historical Winter Wheat Landraces

2021 ◽  
Author(s):  
András Cseh ◽  
Péter Poczai ◽  
Tibor Kiss ◽  
Krisztina Balla ◽  
Zita Berki ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Genome Wide Association Study ◽  
Snp Array ◽  
Genetic Erosion ◽  
Effective Population ◽  
Low Frequencies ◽  
Central European ◽  
Genome Wide ◽  
Population Sizes ◽  
Wheat Landraces

Abstract Historical wheat landraces are rich sources of genetic diversity offering untapped reservoirs for broadening the genetic base of modern varieties. Using a 20K SNP array, we investigated the accessible genetic diversity in a Central European bread wheat landrace collection with great drought, heat stress tolerance and higher tillering capacity. We discovered distinct differences in the number of average polymorphisms between Central and Western European collections, and identified a set of novel rare alleles present at low frequencies in the historical collection. The detected polymorphisms were unevenly distributed along the wheat genome, and polymorphic markers co-localized with genes of great agronomic importance. The efficiency of the highly diverse population for Genome-Wide Association study was confirmed and two significant marker trait associations with seed hardness were identified on the 5DS chromosome arm. The geographical distribution of the inferred Bayesian clustering revealed six genetically homogenous ancestral groups among the collection, where the Central European core bared an admixed background originating from four ancestral groups. We evaluated the effective population sizes (Ne) of the Central European collection and assessed changes in diversity over time, which revealed a dramatic ~97% genetic erosion between 1955 and 2015.

scholarly journals Mitonuclear co-introgression opposes genetic differentiation between phenotypically divergent songbirds

2021 ◽  
Author(s):  
Ellen Nikelski ◽  
Alexander S. Rubtsov ◽  
Darren Irwin
Keyword(s):  
Sex Chromosome ◽  
Genomic Variation ◽  
Effective Population ◽  
Emberiza Citrinella ◽  
Genome Wide ◽  
Mitochondrial Functions ◽  
Species Pairs ◽  
Population Sizes ◽  
Nuclear Differentiation ◽  
Mtdna Introgression

Comparisons of genomic variation among closely related species often show more differentiation in mitochondrial DNA (mtDNA) and sex chromosomes than in autosomes, a pattern expected due to the relative effective population sizes of these genomic components. Differential introgression can cause some species pairs to deviate dramatically from this pattern. The yellowhammer (Emberiza citrinella) and the pine bunting (E. leucocephalos) are hybridizing avian sister species that differ greatly in appearance but show no mtDNA differentiation. This discordance might be explained by mtDNA introgression-a process that can select for co-introgression at nuclear genes with mitochondrial functions (mitonuclear genes). We investigated genome-wide nuclear differentiation between yellowhammers and pine buntings and compared it to what was seen previously in the mitochondrial genome. We found clear nuclear differentiation that was highly heterogeneous across the genome, with a particularly wide differentiation peak on the sex chromosome Z. We further tested for preferential introgression of mitonuclear genes and detected evidence for such biased introgression in yellowhammers. Mitonuclear co-introgression can remove post-zygotic incompatibilities between species and may contribute to the continued hybridization between yellowhammers and pine buntings despite their clear morphological and genetic differences. As such, our results highlight the potential ramifications of co-introgression in species evolution.

scholarly journals WFABC: a Wright-Fisher ABC-based approach for inferring effective population sizes and selection coefficients from time-sampled data

2014 ◽  
Author(s):  
Matthieu Foll ◽  
Hyunjin Shim ◽  
Jeffrey D. Jensen
Keyword(s):  
Genetic Parameters ◽  
Sampled Data ◽  
Effective Population ◽  
Sequencing Technologies ◽  
Genome Wide ◽  
Fisher Model ◽  
Serial Data ◽  
Population Sizes ◽  
Population Genetic Parameters ◽  
Abc Method

With novel developments in sequencing technologies, time-sampled data are becoming more available and accessible. Naturally, there have been efforts in parallel to infer population genetic parameters from these datasets. Here, we compare and analyze four recent approaches based on the Wright-Fisher model for inferring selection coefficients (s) given effective population size (Ne), with simulated temporal datasets. Furthermore, we demonstrate the advantage of a recently proposed ABC-based method that is able to correctly infer genome-wide average Ne from time-serial data, which is then set as a prior for inferring per-site selection coefficients accurately and precisely. We implement this ABC method in a new software and apply it to a classical time-serial dataset of the medionigra genotype in the moth Panaxia dominula. We show that a recessive lethal model is the best explanation for the observed variation in allele frequency by implementing an estimator of the dominance ratio (h).

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