scholarly journals Genetic Variation in Adaptability and Pleiotropy in Budding Yeast

2017 ◽  
Author(s):  
Elizabeth R. Jerison ◽  
Sergey Kryazhimskiy ◽  
James Mitchell ◽  
Joshua S. Bloom ◽  
Leonid Kruglyak ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Complex Traits ◽  
Genetic Basis ◽  
Average Rate ◽  
Environmental Condition ◽  
Future Evolution ◽  
Naturally Occurring ◽  
Yeast Strains ◽  
Offspring Genotype ◽  
Specific Environmental Condition

AbstractEvolution can favor organisms that are more adaptable, provided that genetic variation in adaptability exists. Here, we quantify this variation among 230 offspring of a cross between diverged yeast strains. We measure the adaptability of each offspring genotype, defined as its average rate of adaptation in a specific environmental condition, and analyze the heritability, predictability, and genetic basis of this trait. We find that initial genotype strongly affects adaptability and can alter the genetic basis of future evolution. Initial genotype also affects the pleiotropic consequences of adaptation for fitness in a different environment. This genetic variation in adaptability and pleiotropy is largely determined by initial fitness, according to a rule of declining adaptability with increasing initial fitness, but several individual QTLs also have a significant idiosyncratic role. Our results demonstrate that both adaptability and pleiotropy are complex traits, with extensive heritable differences arising from naturally occurring variation.

scholarly journals Genetic variation in adaptability and pleiotropy in budding yeast

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Elizabeth R Jerison ◽  
Sergey Kryazhimskiy ◽  
James Kameron Mitchell ◽  
Joshua S Bloom ◽  
Leonid Kruglyak ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Complex Traits ◽  
Genetic Basis ◽  
Average Rate ◽  
Environmental Condition ◽  
Future Evolution ◽  
Naturally Occurring ◽  
Yeast Strains ◽  
Offspring Genotype ◽  
Specific Environmental Condition

Evolution can favor organisms that are more adaptable, provided that genetic variation in adaptability exists. Here, we quantify this variation among 230 offspring of a cross between diverged yeast strains. We measure the adaptability of each offspring genotype, defined as its average rate of adaptation in a specific environmental condition, and analyze the heritability, predictability, and genetic basis of this trait. We find that initial genotype strongly affects adaptability and can alter the genetic basis of future evolution. Initial genotype also affects the pleiotropic consequences of adaptation for fitness in a different environment. This genetic variation in adaptability and pleiotropy is largely determined by initial fitness, according to a rule of declining adaptability with increasing initial fitness, but several individual QTLs also have a significant idiosyncratic role. Our results demonstrate that both adaptability and pleiotropy are complex traits, with extensive heritable differences arising from naturally occurring variation.

scholarly journals Contextualizing genetic risk score for disease screening and rare variant discovery

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Dan Zhou ◽  
Dongmei Yu ◽  
Jeremiah M. Scharf ◽  
Carol A. Mathews ◽  
Lauren McGrath ◽  
...  
Keyword(s):  
Complex Traits ◽  
Genetic Basis ◽  
Clinical Decision Making ◽  
Genetic Risk Score ◽  
Sufficient Conditions ◽  
Clinical Decision ◽  
Generative Models ◽  
Variant Discovery ◽  
Models Of Disease ◽  
The Uk

AbstractStudies of the genetic basis of complex traits have demonstrated a substantial role for common, small-effect variant polygenic burden (PB) as well as large-effect variants (LEV, primarily rare). We identify sufficient conditions in which GWAS-derived PB may be used for well-powered rare pathogenic variant discovery or as a sample prioritization tool for whole-genome or exome sequencing. Through extensive simulations of genetic architectures and generative models of disease liability with parameters informed by empirical data, we quantify the power to detect, among cases, a lower PB in LEV carriers than in non-carriers. Furthermore, we uncover clinically useful conditions wherein the risk derived from the PB is comparable to the LEV-derived risk. The resulting summary-statistics-based methodology (with publicly available software, PB-LEV-SCAN) makes predictions on PB-based LEV screening for 36 complex traits, which we confirm in several disease datasets with available LEV information in the UK Biobank, with important implications on clinical decision-making.

scholarly journals Meta-QTL analysis and identification of candidate genes for quality, abiotic and biotic stress in durum wheat

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jose Miguel Soriano ◽  
Pasqualina Colasuonno ◽  
Ilaria Marcotuli ◽  
Agata Gadaleta
Keyword(s):  
Molecular Markers ◽  
Abiotic Stress ◽  
Durum Wheat ◽  
Candidate Genes ◽  
Biotic Stress ◽  
Qtl Analysis ◽  
Complex Traits ◽  
Genetic Basis ◽  
Agronomic Traits ◽  
Plant Performance

AbstractThe genetic improvement of durum wheat and enhancement of plant performance often depend on the identification of stable quantitative trait loci (QTL) and closely linked molecular markers. This is essential for better understanding the genetic basis of important agronomic traits and identifying an effective method for improving selection efficiency in breeding programmes. Meta-QTL analysis is a useful approach for dissecting the genetic basis of complex traits, providing broader allelic coverage and higher mapping resolution for the identification of putative molecular markers to be used in marker-assisted selection. In the present study, extensive QTL meta-analysis was conducted on 45 traits of durum wheat, including quality and biotic and abiotic stress-related traits. A total of 368 QTL distributed on all 14 chromosomes of genomes A and B were projected: 171 corresponded to quality-related traits, 127 to abiotic stress and 71 to biotic stress, of which 318 were grouped in 85 meta-QTL (MQTL), 24 remained as single QTL and 26 were not assigned to any MQTL. The number of MQTL per chromosome ranged from 4 in chromosomes 1A and 6A to 9 in chromosome 7B; chromosomes 3A and 7A showed the highest number of individual QTL (4), and chromosome 7B the highest number of undefined QTL (4). The recently published genome sequence of durum wheat was used to search for candidate genes within the MQTL peaks. This work will facilitate cloning and pyramiding of QTL to develop new cultivars with specific quantitative traits and speed up breeding programs.

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.

scholarly journals The genomics of adaptation

2012 ◽  
Vol 279 (1749) ◽  
pp. 5024-5028 ◽  
Author(s):  
Jacek Radwan ◽  
Wiesław Babik
Keyword(s):  
Genetic Variation ◽  
Natural Selection ◽  
Royal Society ◽  
Genetic Basis ◽  
Genomic Data ◽  
Evolutionary Change ◽  
Introductory Article ◽  
Technological Advances ◽  
A Genome ◽  
Genome Level

The amount and nature of genetic variation available to natural selection affect the rate, course and outcome of evolution. Consequently, the study of the genetic basis of adaptive evolutionary change has occupied biologists for decades, but progress has been hampered by the lack of resolution and the absence of a genome-level perspective. Technological advances in recent years should now allow us to answer many long-standing questions about the nature of adaptation. The data gathered so far are beginning to challenge some widespread views of the way in which natural selection operates at the genomic level. Papers in this Special Feature of Proceedings of the Royal Society B illustrate various aspects of the broad field of adaptation genomics. This introductory article sets up a context and, on the basis of a few selected examples, discusses how genomic data can advance our understanding of the process of adaptation.

scholarly journals QTL analysis of self-selected macronutrient diet intake: fat, carbohydrate, and total kilocalories

2002 ◽  
Vol 11 (3) ◽  
pp. 205-217 ◽  
Author(s):  
Brenda K. Smith Richards ◽  
Brenda N. Belton ◽  
Angela C. Poole ◽  
James J. Mancuso ◽  
Gary A. Churchill ◽  
...  
Keyword(s):  
Body Weight ◽  
Qtl Analysis ◽  
Genetic Basis ◽  
Body Weight Gain ◽  
Macronutrient Intake ◽  
Naturally Occurring ◽  
Trait Locus ◽  
Diet Intake ◽  
Insight Into ◽  
Protein Quantitative Trait Locus

The present study investigated the inheritance of dietary fat, carbohydrate, and kilocalorie intake traits in an F2 population derived from an intercross between C57BL/6J (fat-preferring) and CAST/EiJ (carbohydrate-preferring) mice. Mice were phenotyped for self-selected food intake in a paradigm which provided for 10 days a choice between two macronutrient diets containing 78/22% of energy as a composite of either fat/protein or carbohydrate/protein. Quantitative trait locus (QTL) analysis identified six significant loci for macronutrient intake: three for fat intake on chromosomes (Chrs) 8 ( Mnif1), 18 ( Mnif2), and X ( Mnif3), and three for carbohydrate intake on Chrs 17 ( Mnic1), 6 ( Mnic2), and X ( Mnic3). An absence of interactions among these QTL suggests the existence of separate mechanisms controlling the intake of fat and carbohydrate. Two significant QTL for cumulative kilocalorie intake, adjusted for baseline body weight, were found on Chrs 17 ( Kcal1) and 18 ( Kcal2). Without body weight adjustment, another significant kcal locus appeared on distal Chr 2 ( Kcal3). These macronutrient and kilocalorie QTL, with the exception of loci on Chrs 8 and X, encompassed chromosomal regions influencing body weight gain and adiposity in this F2 population. These results provide new insight into the genetic basis of naturally occurring variation in nutrient intake phenotypes.

scholarly journals GWAS of three molecular traits highlights core genes and pathways alongside a highly polygenic background

2020 ◽  
Author(s):  
Nasa Sinnott-Armstrong ◽  
Sahin Naqvi ◽  
Manuel Rivas ◽  
Jonathan K Pritchard
Keyword(s):  
Complex Traits ◽  
Genetic Basis ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Biological Processes ◽  
Uk Biobank ◽  
The Core ◽  
Genome Wide ◽  
Core Genes

SummaryGenome-wide association studies (GWAS) have been used to study the genetic basis of a wide variety of complex diseases and other traits. However, for most traits it remains difficult to interpret what genes and biological processes are impacted by the top hits. Here, as a contrast, we describe UK Biobank GWAS results for three molecular traits—urate, IGF-1, and testosterone—that are biologically simpler than most diseases, and for which we know a great deal in advance about the core genes and pathways. Unlike most GWAS of complex traits, for all three traits we find that most top hits are readily interpretable. We observe huge enrichment of significant signals near genes involved in the relevant biosynthesis, transport, or signaling pathways. We show how GWAS data illuminate the biology of variation in each trait, including insights into differences in testosterone regulation between females and males. Meanwhile, in other respects the results are reminiscent of GWAS for more-complex traits. In particular, even these molecular traits are highly polygenic, with most of the variance coming not from core genes, but from thousands to tens of thousands of variants spread across most of the genome. Given that diseases are often impacted by many distinct biological processes, including these three, our results help to illustrate why so many variants can affect risk for any given disease.

scholarly journals A global analysis of CNVs in Chinese indigenous fine-wool sheep populations using whole-genome resequencing

2021 ◽  
Author(s):  
Chao Yuan ◽  
Zengkui Lu ◽  
Tingting Guo ◽  
Yaojing Yue ◽  
Xijun Wang ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Complex Traits ◽  
Phenotypic Diversity ◽  
Average Length ◽  
Global Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Nutrient Metabolism ◽  
Relaxin Family

Abstract Background Copy number variation (CNV) is an important source of genetic variation that has a significant influence on phenotypic diversity, economically important traits and the evolution of livestock species. In this study, the genome-wide CNV distribution characteristics of 32 fine-wool sheep from three breeds were analyzed using resequencing.Results A total of 1,747,604 CNVs were detected in this study, and 7,228 CNV regions (CNVR) were obtained after merging overlapping CNVs; these regions accounted for 2.17% of the sheep reference genome. The average length of the CNVRs was 4,307.17 bp. “Deletion” events took place more frequently than “duplication” or “both” events. The CNVRs obtained overlapped with previously reported sheep CNVRs to variable extents (4.39%–55.46%). Functional enrichment analysis showed that the CNVR-harboring genes were mainly involved in sensory perception systems, nutrient metabolism processes, and growth and development processes. Furthermore, 1,855 of the CNVRs were associated with 166 quantitative trait loci (QTL), including milk QTLs, carcass QTLs, and health-related QTLs, among others. In addition, the 32 fine-wool sheep were divided into horned and polled groups to analyze for the selective sweep of CNVRs, and it was found that the relaxin family peptide receptor 2 (RXFP2) gene was strongly influenced by selection.Conclusions In summary, we constructed a genomic CNV map for Chinese indigenous fine-wool sheep using resequencing, thereby providing a valuable genetic variation resource for sheep genome research, which will contribute to the study of complex traits in sheep.

scholarly journals Leveraging DNA methylation quantitative trait loci to characterize the relationship between methylomic variation, gene expression and complex traits

2018 ◽  
Author(s):  
Eilis Hannon ◽  
Tyler J Gorrie-Stone ◽  
Melissa C Smart ◽  
Joe Burrage ◽  
Amanda Hughes ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Common Genetic Variation ◽  
Online Data ◽  
The Relationship ◽  
Methylation Quantitative Trait Loci

ABSTRACTCharacterizing the complex relationship between genetic, epigenetic and transcriptomic variation has the potential to increase understanding about the mechanisms underpinning health and disease phenotypes. In this study, we describe the most comprehensive analysis of common genetic variation on DNA methylation (DNAm) to date, using the Illumina EPIC array to profile samples from the UK Household Longitudinal study. We identified 12,689,548 significant DNA methylation quantitative trait loci (mQTL) associations (P < 6.52x10-14) occurring between 2,907,234 genetic variants and 93,268 DNAm sites, including a large number not identified using previous DNAm-profiling methods. We demonstrate the utility of these data for interpreting the functional consequences of common genetic variation associated with > 60 human traits, using Summary data–based Mendelian Randomization (SMR) to identify 1,662 pleiotropic associations between 36 complex traits and 1,246 DNAm sites. We also use SMR to characterize the relationship between DNAm and gene expression, identifying 6,798 pleiotropic associations between 5,420 DNAm sites and the transcription of 1,702 genes. Our mQTL database and SMR results are available via a searchable online database (http://www.epigenomicslab.com/online-data-resources/) as a resource to the research community.

Sign in / Sign up

Export Citation Format

Share Document