scholarly journals Whole-genome modeling accurately predicts quantitative traits, as revealed in plants

2015 ◽  
Author(s):  
Laurent Gentzbittel ◽  
Cécile Ben ◽  
Mélanie Mazurier ◽  
Min-Gyoung Shin ◽  
Martin Triska ◽  
...  
Keyword(s):  
Phenotypic Variation ◽  
Symbiotic Nitrogen Fixation ◽  
Natural Populations ◽  
Whole Genome ◽  
Population Admixture ◽  
Admixture Proportion ◽  
Genome Wide ◽  
Polygenic Adaptation ◽  
In The Wild ◽  
Wild Legume

AbstractMany adaptive events in natural populations, as well as response to artificial selection, are caused by polygenic action. Under selective pressure, the adaptive traits can quickly respond via small allele frequency shifts spread across numerous loci. We hypothesize that a large proportion of current phenotypic variation between individuals may be best explained by population admixture.We thus consider the complete, genome-wide universe of genetic variability, spread across several ancestral populations originally separated. We experimentally confirmed this hypothesis by predicting the differences in quantitative disease resistance levels among accessions in the wild legume Medicago truncatula. We discovered also that variation in genome admixture proportion explains most of phenotypic variation for several quantitative functional traits, but not for symbiotic nitrogen fixation. We shown that positive selection at the species level might not explain current, rapid adaptation.These findings prove the infinitesimal model as a mechanism for adaptation of quantitative phenotypes. Our study produced the first evidence that the whole-genome modeling of DNA variants is the best approach to describe an inherited quantitative trait in a higher eukaryote organism and proved the high potential of admixture-based analyses. This insight contribute to the understanding of polygenic adaptation, and can accelerate plant and animal breeding, and biomedicine research programs.

scholarly journals Whole genome resequencing data enables a targeted SNP panel for conservation and aquaculture of Oreochromis cichlid fishes

2021 ◽  
Author(s):  
Adam Ciezarek ◽  
Antonia Ford ◽  
Graham Etherington ◽  
Kasozi Nasser ◽  
Milan Malinsky ◽  
...  
Keyword(s):  
Native Species ◽  
Cichlid Fish ◽  
Snp Markers ◽  
Whole Genome ◽  
The Novel ◽  
Genome Resequencing ◽  
Genome Wide ◽  
In The Wild ◽  
Snp Panel ◽  
Whole Genome Resequencing

Cichlid fish of the genus Oreochromis form the basis of the global tilapia aquaculture and fisheries industry. Non-native farmed tilapia populations are known to be widely distributed across Africa and to hybridize with native Oreochromis species. However, many species are difficult to distinguish morphologically, hampering attempts to maintain good quality farmed strains or to identify pure populations of native species. Here, we describe the development of a single nucleotide polymorphism (SNP) genotyping panel from whole-genome resequencing data that enables targeted species identification in Tanzania. We demonstrate that an optimized panel of 96 genome-wide SNPs based on FST outliers performs comparably to whole genome resequencing in distinguishing species and identifying hybrids. We also show this panel outperforms microsatellite-based and phenotype-based classification methods. Case studies indicate several locations where introduced aquaculture species have become established in the wild, threatening native Oreochromis species. The novel SNP markers identified here represent an important resource for assessing broodstock purity and helping to conserve unique endemic biodiversity, and in addition potentially for assessing broodstock purity in hatcheries.

scholarly journals Spatio-Temporal Ecological and Evolutionary Dynamics in Natural Butterfly Populations (2015 Field Season)

2015 ◽  
Vol 38 ◽  
pp. 29-32
Author(s):  
Zachariah Gompert ◽  
Lauren Lucas
Keyword(s):  
Genetic Variation ◽  
Natural Selection ◽  
Molecular Evolution ◽  
Natural Populations ◽  
Spatial And Temporal Variation ◽  
Long Term Study ◽  
Genome Wide ◽  
In The Wild ◽  
Long Term Studies

The study of evolution in natural populations has advanced our understanding of the origin and maintenance of biological diversity. For example, long term studies of wild populations indicate that natural selection can cause rapid and dramatic changes in traits, but that in some cases these evolutionary changes are quickly reversed when periodic variation in weather patterns or the biotic environment cause the optimal trait value to change (e.g., Reznick et al. 1997, Grant and Grant 2002). In fact, spatial and temporal variation in the strength and nature of natural selection could explain the high levels of genetic variation found in many natural populations (Gillespie 1994, Siepielski et al. 2009). Long term studies of evolution in the wild could also be informative for biodiversity conservation and resource management, because, for example, data on short term evolutionary responses to annual fluctuations in temperature or rainfall could be used to predict longer term evolution in response to directional climate change. Most previous research on evolution in the wild has considered one or a few observable traits or genes (e.g., Kapan 2001, Grant and Grant 2002, Barrett et al. 2008). We believe that more general conclusions regarding the rate and causes of evolutionary change in the wild and selection’s contribution to the maintenance of genetic variation could be obtained by studying genome-wide molecular evolution in a suite of natural populations. Thus, in 2012 we began a long term study of genome-wide molecular evolution in a series of natural butterfly populations in the Greater Yellowstone Area (GYA). This study will allow us to quantify the contribution of environment-dependent natural selection to evolution in these butterfly populations and determine whether selection consistently favors the same alleles across space and through time.

scholarly journals Spatio-Temporal Evolutionary Dynamics in Natural Butterfly Populations (2012 Field Season)

2012 ◽  
Vol 35 ◽  
pp. 73-76
Author(s):  
Zachariah Gompert ◽  
Lauren Lucas
Keyword(s):  
Genetic Variation ◽  
Natural Selection ◽  
Molecular Evolution ◽  
Natural Populations ◽  
Spatial And Temporal Variation ◽  
Long Term Study ◽  
Genome Wide ◽  
In The Wild ◽  
Long Term Studies

The study of evolution in natural populations has advanced our understanding of the origin and maintenance of biological diversity. For example, long term studies of wild populations indicate that natural selection can cause rapid and dramatic changes in traits, but that in some cases these evolutionary changes are quickly reversed when periodic variation in weather patterns or the biotic environment cause the optimal trait value to change (e.g., Reznick et al. 1997; Grant and Grant 2002). In fact, spatial and temporal variation in the strength and nature of natural selection could explain the high levels of genetic variation found in many natural populations (Gillespie 1994; Siepielski et al. 2009). Long term studies of evolution in the wild could also be informative for biodiversity conservation and resource management, because, for example, data on short term evolutionary responses to annual fluctuations in temperature or rainfall could be used to predict longer term evolution in response to directional climate change. Most previous research on evolution in the wild has considered one or a few observable traits or genes (Kapan 2001; Grant and Grant 2002; Barrett et al. 2008). We believe that more general conclusions regarding the rate and causes of evolutionary change in the wild and selection’s contribution to the maintenance of genetic variation could be obtained by studying genome-wide molecular evolution in a suite of natural populations. Thus, we have begun a long term study of genome-wide molecular evolution in a series of natural butterfly populations in the Greater Yellowstone Area (GYA). This study will allow us to quantify the contribution of environment-dependent natural selection to evolution in these butterfly populations and determine whether selection consistently favors the same alleles across space and through time.

scholarly journals Association Mapping across Numerous Traits Reveals Patterns of Functional Variation in Maize

2014 ◽  
Author(s):  
Jason G Wallace ◽  
Peter Bradbury ◽  
Nengyi Zhang ◽  
Yves Gibon ◽  
Mark Stitt ◽  
...  
Keyword(s):  
Phenotypic Variation ◽  
Copy Number Variants ◽  
Natural Populations ◽  
Nucleotide Polymorphisms ◽  
Functional Variation ◽  
Single Nucleotide ◽  
Gene By Environment Interactions ◽  
Genome Wide ◽  
Intergenic Regions ◽  
Regulatory Functions

Phenotypic variation in natural populations results from a combination of genetic effects, environmental effects, and gene-by-environment interactions. Despite the vast amount of genomic data becoming available, many pressing questions remain about the nature of genetic mutations that underlie functional variation. We present the results of combining genome-wide association analysis of 41 different phenotypes in ~5,000 inbred maize lines to analyze patterns of high-resolution genetic association among of 28.9 million single-nucleotide polymorphisms (SNPs) and ~800,000 copy-number variants (CNVs). We show that genic and intergenic regions have opposite patterns of enrichment, minor allele frequencies, and effect sizes, implying tradeoffs among the probability that a given polymorphism will have an effect, the detectable size of that effect, and its frequency in the population. We also find that genes tagged by GWAS are enriched for regulatory functions and are ~50% more likely to have a paralog than expected by chance, indicating that gene regulation and neofunctionalization are strong drivers of phenotypic variation. These results will likely apply to many other organisms, especially ones with large and complex genomes like maize.

scholarly journals Spatio-temporal Ecological and Evolutionary Dynamics in Natural Butterfly Populations (2013 Field Season)

2013 ◽  
Vol 36 ◽  
pp. 146-149
Author(s):  
Zachariah Gompert ◽  
Lauren Lucas
Keyword(s):  
Genetic Variation ◽  
Natural Selection ◽  
Molecular Evolution ◽  
Natural Populations ◽  
Spatial And Temporal Variation ◽  
Long Term Study ◽  
Genome Wide ◽  
In The Wild ◽  
Long Term Studies

The study of evolution in natural populations has advanced our understanding of the origin and maintenance of biological diversity. For example, long term studies of wild populations indicate that natural selection can cause rapid and dramatic changes in traits, but that in some cases these evolutionary changes are quickly reversed when periodic variation in weather patterns or the biotic environment cause the optimal trait value to change (e.g., Reznick et al. 1997, Grant and Grant 2002). In fact, spatial and temporal variation in the strength and nature of natural selection could explain the high levels of genetic variation found in many natural populations (Gillespie 1994, Siepielski et al. 2009). Long term studies of evolution in the wild could also be informative for biodiversity conservation and resource management, because, for example, data on short term evolutionary responses to annual fluctuations in temperature or rainfall could be used to predict longer term evolution in response to directional climate change. Most previous research on evolution in the wild has considered one or a few observable traits or genes (Kapan 2001, Grant and Grant 2002, Barrett et al. 2008). We believe that more general conclusions regarding the rate and causes of evolutionary change in the wild and selection’s contribution to the maintenance of genetic variation could be obtained by studying genome-wide molecular evolution in a suite of natural populations. Thus, we have begun a long term study of genome-wide molecular evolution in a series of natural butterfly populations in the Greater Yellowstone Area (GYA). This study will allow us to quantify the contribution of environment-dependent natural selection to evolution in these butterfly populations and determine whether selection consistently favors the same alleles across space and through time.

Phenotypic variation and covariation among natural populations ofArabidopsis thalianain North Xinjiang

2010 ◽  
Vol 18 (5) ◽  
pp. 497
Author(s):  
Li Lei ◽  
Liu Tong ◽  
Liu Bin ◽  
Liu Zhongquan ◽  
Si Langming ◽  
...  
Keyword(s):  
Phenotypic Variation ◽  
Natural Populations ◽  
North Xinjiang

scholarly journals Comprehensive Genome-Wide Association Analysis Reveals the Genetic Basis of Root System Architecture in Soybean

2020 ◽  
Vol 11 ◽  
Author(s):  
Waldiodio Seck ◽  
Davoud Torkamaneh ◽  
François Belzile
Keyword(s):  
Root System ◽  
System Architecture ◽  
Phenotypic Variation ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Primary Root ◽  
Root System Architecture ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Genome Wide

Increasing the understanding genetic basis of the variability in root system architecture (RSA) is essential to improve resource-use efficiency in agriculture systems and to develop climate-resilient crop cultivars. Roots being underground, their direct observation and detailed characterization are challenging. Here, were characterized twelve RSA-related traits in a panel of 137 early maturing soybean lines (Canadian soybean core collection) using rhizoboxes and two-dimensional imaging. Significant phenotypic variation (P < 0.001) was observed among these lines for different RSA-related traits. This panel was genotyped with 2.18 million genome-wide single-nucleotide polymorphisms (SNPs) using a combination of genotyping-by-sequencing and whole-genome sequencing. A total of 10 quantitative trait locus (QTL) regions were detected for root total length and primary root diameter through a comprehensive genome-wide association study. These QTL regions explained from 15 to 25% of the phenotypic variation and contained two putative candidate genes with homology to genes previously reported to play a role in RSA in other species. These genes can serve to accelerate future efforts aimed to dissect genetic architecture of RSA and breed more resilient varieties.

scholarly journals The Genetic Architecture of Ovariole Number in Drosophila melanogaster: Genes with Major, Quantitative, and Pleiotropic Effects

2017 ◽  
Vol 7 (7) ◽  
pp. 2391-2403 ◽  
Author(s):  
Amanda S Lobell ◽  
Rachel R Kaspari ◽  
Yazmin L Serrano Negron ◽  
Susan T Harbison
Keyword(s):  
Candidate Genes ◽  
Genome Wide Association Study ◽  
Natural Populations ◽  
Direct Role ◽  
Genome Wide ◽  
A Genome ◽  
Fitness Trait ◽  
Sleep Parameters ◽  
Activity Behavior ◽  
Ovariole Number

Abstract Ovariole number has a direct role in the number of eggs produced by an insect, suggesting that it is a key morphological fitness trait. Many studies have documented the variability of ovariole number and its relationship to other fitness and life-history traits in natural populations of Drosophila. However, the genes contributing to this variability are largely unknown. Here, we conducted a genome-wide association study of ovariole number in a natural population of flies. Using mutations and RNAi-mediated knockdown, we confirmed the effects of 24 candidate genes on ovariole number, including a novel gene, anneboleyn (formerly CG32000), that impacts both ovariole morphology and numbers of offspring produced. We also identified pleiotropic genes between ovariole number traits and sleep and activity behavior. While few polymorphisms overlapped between sleep parameters and ovariole number, 39 candidate genes were nevertheless in common. We verified the effects of seven genes on both ovariole number and sleep: bin3, blot, CG42389, kirre, slim, VAChT, and zfh1. Linkage disequilibrium among the polymorphisms in these common genes was low, suggesting that these polymorphisms may evolve independently.

Genome-wide association implicates numerous genes underlying ecological trait variation in natural populations ofPopulus trichocarpa

2014 ◽  
Vol 203 (2) ◽  
pp. 535-553 ◽  
Author(s):  
Athena D. McKown ◽  
Jaroslav Klápště ◽  
Robert D. Guy ◽  
Armando Geraldes ◽  
Ilga Porth ◽  
...  
Keyword(s):  
Natural Populations ◽  
Genome Wide Association ◽  
Trait Variation ◽  
Genome Wide

scholarly journals A curated dataset of modern and ancient high-coverage shotgun human genomes

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Pierpaolo Maisano Delser ◽  
Eppie R. Jones ◽  
Anahit Hovhannisyan ◽  
Lara Cassidy ◽  
Ron Pinhasi ◽  
...  
Keyword(s):  
Sequence Data ◽  
Whole Genome ◽  
Reference Dataset ◽  
High Coverage ◽  
Sample Distribution ◽  
Human Samples ◽  
Human Genomes ◽  
Genome Wide ◽  
Genome Wide Data ◽  
Computationally Intensive

AbstractOver the last few years, genome-wide data for a large number of ancient human samples have been collected. Whilst datasets of captured SNPs have been collated, high coverage shotgun genomes (which are relatively few but allow certain types of analyses not possible with ascertained captured SNPs) have to be reprocessed by individual groups from raw reads. This task is computationally intensive. Here, we release a dataset including 35 whole-genome sequenced samples, previously published and distributed worldwide, together with the genetic pipeline used to process them. The dataset contains 72,041,355 sites called across 19 ancient and 16 modern individuals and includes sequence data from four previously published ancient samples which we sequenced to higher coverage (10–18x). Such a resource will allow researchers to analyse their new samples with the same genetic pipeline and directly compare them to the reference dataset without re-processing published samples. Moreover, this dataset can be easily expanded to increase the sample distribution both across time and space.

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