scholarly journals Optimizing the power to identify the genetic basis of complex traits with Evolve and Resequence studies

2019 ◽  
Author(s):  
Christos Vlachos ◽  
Robert Kofler
Keyword(s):  
Complex Traits ◽  
Quantitative Traits ◽  
Genetic Basis ◽  
Optimal Selection ◽  
Selection Regime ◽  
Higher Power ◽  
Powerful Approach ◽  
Selection For ◽  
Generation Sequencing

AbstractEvolve and Resequence (E&R) studies are frequently used to dissect the genetic basis of quantitative traits. By subjecting a population to truncating selection for several generations and estimating the allele frequency differences between selected and non-selected populations using Next Generation Sequencing, the loci contributing to the selected trait may be identified. The role of different parameters, such as, the population size or the number of replicate populations have been examined in previous works. However, the influence of the selection regime, i.e. the strength of truncating selection during the experiment, remains little explored. Using whole genome, individual based forward simulations of E&R studies, we found that the power to identify the causative alleles may be maximized by gradually increasing the strength of truncating selection during the experiment. Notably, such an optimal selection regime comes at no or little additional cost in terms of sequencing effort and experimental time. Interestingly, we also found that a selection regime which optimizes the power to identify the causative loci is not necessarily identical to a regime that maximizes the phenotypic response. Finally, our simulations suggest that an E&R study with an optimized selection regime may have a higher power to identify the genetic basis of quantitative traits than a GWAS, highlighting that E&R is a powerful approach for finding the loci underlying complex traits.

scholarly journals Optimizing the Power to Identify the Genetic Basis of Complex Traits with Evolve and Resequence Studies

2019 ◽  
Vol 36 (12) ◽  
pp. 2890-2905 ◽  
Author(s):  
Christos Vlachos ◽  
Robert Kofler
Keyword(s):  
Complex Traits ◽  
Quantitative Traits ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Selection Regime ◽  
Genome Wide ◽  
A Genome ◽  
Higher Power ◽  
Powerful Approach ◽  
Next Generation Sequencing Ngs

Abstract Evolve and resequence (E&R) studies are frequently used to dissect the genetic basis of quantitative traits. By subjecting a population to truncating selection for several generations and estimating the allele frequency differences between selected and nonselected populations using next-generation sequencing (NGS), the loci contributing to the selected trait may be identified. The role of different parameters, such as, the population size or the number of replicate populations has been examined in previous works. However, the influence of the selection regime, that is the strength of truncating selection during the experiment, remains little explored. Using whole genome, individual based forward simulations of E&R studies, we found that the power to identify the causative alleles may be maximized by gradually increasing the strength of truncating selection during the experiment. Notably, such an optimal selection regime comes at no or little additional cost in terms of sequencing effort and experimental time. Interestingly, we also found that a selection regime which optimizes the power to identify the causative loci is not necessarily identical to a regime that maximizes the phenotypic response. Finally, our simulations suggest that an E&R study with an optimized selection regime may have a higher power to identify the genetic basis of quantitative traits than a genome-wide association study, highlighting that E&R is a powerful approach for finding the loci underlying complex traits.

scholarly journals Epistasis for Three Grain Yield Components in Rice (Oryxa sativa L.)

Genetics ◽  
1997 ◽  
Vol 145 (2) ◽  
pp. 453-465 ◽  
Author(s):  
Zhikang Li ◽  
Shannon R M Pinson ◽  
William D Park ◽  
Andrew H Paterson ◽  
James W Stansel
Keyword(s):  
Grain Yield ◽  
Complex Traits ◽  
Yield Components ◽  
Genetic Basis ◽  
Kernel Weight ◽  
Progeny Testing ◽  
Grain Yield Components ◽  
Main Effects ◽  
Grain Number Per Panicle

The genetic basis for three grain yield components of rice, 1000 kernel weight (KW), grain number per panicle (GN), and grain weight per panicle (GWP), was investigated using restriction fragment length polymorphism markers and F4 progeny testing from a cross between rice subspecies japonica (cultivar Lemont from USA) and indica (cv. Teqing from China). Following identification of 19 QTL affecting these traits, we investigated the role of epistasis in genetic control of these phenotypes. Among 63 markers distributed throughout the genome that appeared to be involved in 79 highly significant (P < 0.001) interactions, most (46 or 73%) did not appear to have “main” effects on the relevant traits, but influenced the trait(s) predominantly through interactions. These results indicate that epistasis is an important genetic basis for complex traits such as yield components, especially traits of low heritability such as GN and GWP. The identification of epistatic loci is an important step toward resolution of discrepancies between quantitative trait loci mapping and classical genetic dogma, contributes to better understanding of the persistence of quantitative genetic variation in populations, and impels reconsideration of optimal mapping methodology and marker-assisted breeding strategies for improvement of complex traits.

DEFICIENCY OF LRBA: BIBLIOGRAPHICAL REVIEW AND CASE REPORT

2021 ◽  
Vol 100 (2) ◽  
pp. 192-203
Author(s):  
I.V. Kondratenko ◽  
◽  
S.S. Vakhlayrskaya ◽  
D.V. Rogozhin ◽  
◽  
...  
Keyword(s):  
Case Report ◽  
Genetic Basis ◽  
Clinical Manifestations ◽  
Main Role ◽  
Principles Of Treatment ◽  
The Subject ◽  
Next Generation Sequencing Ngs ◽  
Lrba Deficiency ◽  
Generation Sequencing

Since the description of the first primary immunodeficiencies (PIDs) in the 50–60s of the last century, they have been the subject of intensive research aimed at elucidating their etiology and finding effective treatments. The development of next-generation sequencing (NGS) methods made it possible to reveal the genetic basis of many new forms of PID, which were previously attributed to various syndromes due to their clinical and immunological characteristics. An example of such a PID is the LRBA (the lipopolysaccharide-responsive and beige-like anchor protein) deficiency, sometimes called LATAIE [LRBA deficiency with autoantibodies, regulatory T (Treg) cell defects, autoimmune infiltration, and enteropathy]. The article provides information on the main role of the LRBA molecule in the functions of immunocompetent cells, describes immunological disorders and clinical manifestations of LRBA deficiency and the principles of treatment of diseases. Two own observations of LRBA deficiency are presented.

scholarly journals Unravelling the complex genetic basis of growth in New Zealand silver trevally (Pseudocaranx georgianus)

2021 ◽  
Author(s):  
Noemie Valenza-Troubat ◽  
Sara Montanari ◽  
Peter Ritchie ◽  
Maren Wellenreuther
Keyword(s):  
Qtl Mapping ◽  
Complex Traits ◽  
Genetic Basis ◽  
Growth Traits ◽  
Association Studies ◽  
Snp Markers ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Powerful Approach ◽  
Trait Locus

AbstractGrowth directly influences production rate and therefore is one of the most important and well-studied trait in animal breeding. However, understanding the genetic basis of growth has been hindered by its typically complex polygenic architecture. Here, we performed quantitative trait locus (QTL) mapping and genome-wide association studies (GWAS) for 10 growth traits that were observed over two years in 1,100 F1 captive-bred trevally (Pseudocaranx georgianus). We constructed the first high-density linkage map for trevally, which included 19,861 single nucleotide polymorphism (SNP) markers, and discovered eight QTLs for height, length and weight on linkage groups 3, 14 and 18. Using GWAS, we further identified 113 SNP-trait associations, uncovering 10 genetic hot spots involved in growth. Two of the markers found in the GWAS co-located with the QTLs previously mentioned, demonstrating that combining QTL mapping and GWAS represents a powerful approach for the identification and validation of loci controlling complex traits. This is the first study of its kind for trevally. Our findings provide important insights into the genetic architecture of growth in this species and supply a basis for fine mapping QTLs, marker-assisted selection, and further detailed functional analysis of the genes underlying growth in trevally.

scholarly journals The evolution of group differences in changing environments

PLoS Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
pp. e3001072
Author(s):  
Arbel Harpak ◽  
Molly Przeworski
Keyword(s):  
Environmental Effects ◽  
Complex Traits ◽  
Genetic Basis ◽  
Rapid Evolution ◽  
Group Differences ◽  
Stabilizing Selection ◽  
Trait Variation ◽  
Fitness Consequences ◽  
The Face ◽  
Selection For

The selection pressures that have shaped the evolution of complex traits in humans remain largely unknown, and in some contexts highly contentious, perhaps above all where they concern mean trait differences among groups. To date, the discussion has focused on whether such group differences have any genetic basis, and if so, whether they are without fitness consequences and arose via random genetic drift, or whether they were driven by selection for different trait optima in different environments. Here, we highlight a plausible alternative: that many complex traits evolve under stabilizing selection in the face of shifting environmental effects. Under this scenario, there will be rapid evolution at the loci that contribute to trait variation, even when the trait optimum remains the same. These considerations underscore the strong assumptions about environmental effects that are required in ascribing trait differences among groups to genetic differences.

Evidence of local adaptation and stabilizing selection on quantitative traits in populations of the multipurpose American species Acacia aroma (Fabaceae)

2019 ◽  
Vol 191 (1) ◽  
pp. 128-141 ◽  
Author(s):  
Carolina L Pometti ◽  
Cecilia F Bessega ◽  
Ana M Cialdella ◽  
Mauricio Ewens ◽  
Beatriz O Saidman ◽  
...  
Keyword(s):  
Quantitative Traits ◽  
Genetic Basis ◽  
Natural Populations ◽  
Tree Height ◽  
Phenotypic Traits ◽  
Stabilizing Selection ◽  
Trait Variation ◽  
Chaco Region ◽  
Neutral Genetic Variation ◽  
Selection For

Abstract Economically and ecologically important quantitative traits of Acacia aroma are related to life history and the size and shape of fruits and leaves. Substantial variation is observed for these traits in natural populations, suggesting a possible genetic basis that could be useful for selection programmes. Our objective was to detect signals of selection on 12 phenotypic traits in 170 individuals belonging to seven populations of A. aroma in the Chaco Region of Argentina. Phenotypic traits were compared with molecular markers assessed in the same populations. Here, we search for signatures of natural selection by comparing quantitative trait variation to neutral genetic variation through the PST–FST test. We further test for differences among populations for the 12 phenotypic traits, an association of phenotypic variation with environmental variables and geographical distance, and we compare the power of discrimination between the phenotypic and AFLP datasets. The PST–FST test suggested directional selection for tree height and stabilizing selection for the remaining traits. Analyses of variance showed significant differentiation for eight phenotypic traits. These results suggest selecting among provenances as a management strategy to improve tree height (which showed divergent selection), whereas significant genetic gain for the other traits might be obtained by selection within provenances.

scholarly journals Evidence of positive and negative selection associated with DNA methylation

2021 ◽  
Author(s):  
Charlie Hatcher ◽  
Gibran Hemani ◽  
Santiago Rodriguez ◽  
Tom R Gaunt ◽  
Daniel J Lawson ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Complex Traits ◽  
Functional Role ◽  
Joint Distribution ◽  
Negative Selection ◽  
Selection Coefficient ◽  
Parents And Children ◽  
Selection For ◽  
Avon Longitudinal Study

Signatures of negative selection are pervasive amongst complex traits and diseases. However, it is unclear whether such signatures exist for DNA methylation (DNAm) that has been proposed to have a functional role in disease. We estimate polygenicity, SNP-based heritability and model the joint distribution of effect size and minor allele frequency (MAF) to estimate a selection coefficient (S) for 2000 heritable DNAm sites in 1774 individuals from the Avon Longitudinal Study of Parents and Children. Additionally, we estimate S for meta stable epi alleles and DNAm sites associated with aging and mortality, birthweight and body mass index. Quantification of MAF-dependent genetic architectures estimated from genotype and DNAm reveal evidence of positive (S>0) and negative selection (S<0) and confirm previous evidence of negative selection for birthweight. Evidence of both negative and positive selection highlights the role of DNAm as an intermediary in multiple biological pathways with competing function.

scholarly journals Genome-wide analyses reveal the role of noncoding variation in complex traits during rice domestication

2019 ◽  
Vol 5 (12) ◽  
pp. eaax3619 ◽  
Author(s):  
X. M. Zheng ◽  
J. Chen ◽  
H. B. Pang ◽  
S. Liu ◽  
Q. Gao ◽  
...  
Keyword(s):  
Complex Traits ◽  
Starch Content ◽  
Noncoding Rnas ◽  
Rice Grains ◽  
Population Analyses ◽  
Genome Wide ◽  
Functional Consequences ◽  
Selection For ◽  
Rice Domestication

Genomes carry millions of noncoding variants, and identifying the tiny fraction with functional consequences is a major challenge for genomics. We assessed the role of selection on long noncoding RNAs (lncRNAs) for domestication-related changes in rice grains. Among 3363 lncRNA transcripts identified in early developing panicles, 95% of those with differential expression (329 lncRNAs) between Oryza sativa ssp. japonica and wild rice were significantly down-regulated in the domestication event. Joint genome and transcriptome analyses reveal that directional selection on lncRNAs altered the expression of energy metabolism genes during domestication. Transgenic experiments and population analyses with three focal lncRNAs illustrate that selection on these loci led to increased starch content and grain weight. Together, our findings indicate that genome-wide selection for lncRNA down-regulation was an important mechanism for the emergence of rice domestication traits.

Anti-Myelin Oligodendrocyte Glycoprotein Encephalomyelitis and Extensive Longitudinal Transverse Myelitis Associated with Compound Heterozygous NLRP3 Missense Mutations in a Young Child

2020 ◽  
Author(s):  
Deirdre O'Sullivan ◽  
Michael Moore ◽  
Susan Byrne ◽  
Andreas O. Reiff ◽  
Susanna Felsenstein
Keyword(s):  
Young Child ◽  
Genetic Basis ◽  
Transverse Myelitis ◽  
Acute Disseminated Encephalomyelitis ◽  
Myelin Oligodendrocyte Glycoprotein ◽  
Compound Heterozygous ◽  
Missense Mutations ◽  
Childhood Onset

AbstractAcute disseminated encephalomyelitis in association with extensive longitudinal transverse myelitis is reported in a young child with positive anti-myelin oligodendrocyte glycoprotein (MOG) antibody with heterozygous NLRP3 missense mutations; p.(Arg488Lys) and p.(Ser159Ile). This case may well present an exceptional coincidence, but may describe a yet unrecognized feature of the spectrum of childhood onset cryopyrinopathies that contribute to the understanding of the genetic basis for anti-MOG antibody positive encephalomyelitis. Based on this observation, a larger scale study investigating the role of NLRP3 and other inflammasomes in this entity would provide important pathophysiological insights and potentially novel avenues for treatment.

Evolution and Selection of Quantitative Traits

2018 ◽  
Author(s):  
Bruce Walsh ◽  
Michael Lynch
Keyword(s):  
Mathematical Models ◽  
Quantitative Genetics ◽  
Complex Traits ◽  
Evolutionary Biology ◽  
Quantitative Traits ◽  
Specific Gene ◽  
Real World Data ◽  
Holistic Treatment ◽  
Genetics And Genomics ◽  
Selection Of

Quantitative traits—be they morphological or physiological characters, aspects of behavior, or genome-level features such as the amount of RNA or protein expression for a specific gene—usually show considerable variation within and among populations. Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on mathematical models of evolution in which many genes influence the trait and in which non-genetic factors may also be important. Evolution and Selection of Quantitative Traits presents a holistic treatment of the subject, showing the interplay between theory and data with extensive discussions on statistical issues relating to the estimation of the biologically relevant parameters for these models. Quantitative genetics is viewed as the bridge between complex mathematical models of trait evolution and real-world data, and the authors have clearly framed their treatment as such. This is the second volume in a planned trilogy that summarizes the modern field of quantitative genetics, informed by empirical observations from wide-ranging fields (agriculture, evolution, ecology, and human biology) as well as population genetics, statistical theory, mathematical modeling, genetics, and genomics. Whilst volume 1 (1998) dealt with the genetics of such traits, the main focus of volume 2 is on their evolution, with a special emphasis on detecting selection (ranging from the use of genomic and historical data through to ecological field data) and examining its consequences. This extensive work of reference is suitable for graduate level students as well as professional researchers (both empiricists and theoreticians) in the fields of evolutionary biology, genetics, and genomics. It will also be of particular relevance and use to plant and animal breeders, human geneticists, and statisticians.

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