scholarly journals Neutral mutation as the source of genetic variation in life history traits

2005 ◽  
Vol 86 (1) ◽  
pp. 53-63 ◽  
Author(s):  
KRUNOSLAV BRČIĆ-KOSTIĆ
Keyword(s):  
Genetic Variation ◽  
Life History ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Life History Traits ◽  
Balancing Selection ◽  
Evolutionary Genetics ◽  
Relative Fitness ◽  
Adaptive Genetic Variation ◽  
Trait Loci

The mechanism underlying the maintenance of adaptive genetic variation is a long-standing question in evolutionary genetics. There are two concepts (mutation–selection balance and balancing selection) which are based on the phenotypic differences between alleles. Mutation – selection balance and balancing selection cannot properly explain the process of gene substitution, i.e. the molecular evolution of quantitative trait loci affecting fitness. I assume that such loci have non-essential functions (small effects on fitness), and that they have the potential to evolve into new functions and acquire new adaptations. Here I show that a high amount of neutral polymorphism at these loci can exist in real populations. Consistent with this, I propose a hypothesis for the maintenance of genetic variation in life history traits which can be efficient for the fixation of alleles with very small selective advantage. The hypothesis is based on neutral polymorphism at quantitative trait loci and both neutral and adaptive gene substitutions. The model of neutral – adaptive conversion (NAC) assumes that neutral alleles are not neutral indefinitely, and that in specific and very rare situations phenotypic (relative fitness) differences between them can appear. In this paper I focus on NAC due to phenotypic plasticity of neutral alleles. The important evolutionary consequence of NAC could be the increased adaptive potential of a population. Loci responsible for adaptation should be fast evolving genes with minimally discernible phenotypic effects, and the recent discovery of genes with such characteristics implicates them as suitable candidates for loci involved in adaptation.

Localization of quantitative trait loci for diapause and other photoperiodically regulated life history traits important in adaptation to seasonally varying environments

2015 ◽  
Vol 24 (11) ◽  
pp. 2809-2819 ◽  
Author(s):  
Venera I. Tyukmaeva ◽  
Paris Veltsos ◽  
Jon Slate ◽  
Emma Gregson ◽  
Hannele Kauranen ◽  
...  
Keyword(s):  
Life History ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Life History Traits ◽  
Trait Loci ◽  
Varying Environments

scholarly journals Mapping of quantitative trait loci for life history traits segregating within common frog populations

Heredity ◽  
2019 ◽  
Vol 122 (6) ◽  
pp. 800-808 ◽  
Author(s):  
Gemma Palomar ◽  
Anti Vasemägi ◽  
Freed Ahmad ◽  
Alfredo G. Nicieza ◽  
José Manuel Cano
Keyword(s):  
Life History ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Life History Traits ◽  
Common Frog ◽  
Trait Loci

Quantitative trait loci define genes and pathways underlying genetic variation in longevity

2006 ◽  
Vol 41 (10) ◽  
pp. 1046-1054 ◽  
Author(s):  
Robert J. Shmookler Reis ◽  
Ping Kang ◽  
Srinivas Ayyadevara
Keyword(s):  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Trait Loci

Markers, maps and the detection of trait loci

1996 ◽  
Vol 1996 ◽  
pp. 50-50
Author(s):  
C.S. Haley
Keyword(s):  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Genetic Markers ◽  
Quantitative Trait ◽  
Coat Colour ◽  
Combined Effects ◽  
Potential Interest ◽  
Naturally Occurring ◽  
Trait Loci ◽  
Modern Breeding

Naturally occurring genetic variation is the basis for differences in performance and appearance between and within different breeds and lines of livestock. In a few instances (e.g. coat colour, polling) the genes (or loci) which control the variation between animals and breeds have a large enough effect to be individually recognisable. For many traits, however, the combined effects of many different genes act together to control quantitative differences between breeds and individuals within breeds (hence such genes are often referred to as quantitative trait loci or QTLs). Thus the dramatic successes of modern breeding result from generations of selection which has produced accumulated changes at a number of different loci. The genome contains up to 100,000 different genes and identifying those which contribute to variation in traits of interest is a difficult task. One first step is to identify regions of the genome containing loci of potential interest through their linkage to genetic markers.

Genetic variation underlying pod size and color traits of common bean depends on quantitative trait loci with epistatic effects

2014 ◽  
Vol 33 (4) ◽  
pp. 939-952 ◽  
Author(s):  
Fernando J. Yuste-Lisbona ◽  
Ana M. González ◽  
Carmen Capel ◽  
Manuel García-Alcázar ◽  
Juan Capel ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Common Bean ◽  
Quantitative Trait ◽  
Epistatic Effects ◽  
Color Traits ◽  
Trait Loci

scholarly journals Quantitative Trait Loci Variation for Growth and Obesity Between and Within Lines of Pigs (Sus scrofa)

Genetics ◽  
2003 ◽  
Vol 164 (2) ◽  
pp. 629-635 ◽  
Author(s):  
Yoshitaka Nagamine ◽  
Chris S Haley ◽  
Asheber Sewalem ◽  
Peter M Visscher
Keyword(s):  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Sus Scrofa ◽  
Strong Support ◽  
Wild Type ◽  
Porcine Genome ◽  
Trait Loci ◽  
Sib Families ◽  
Related Population

Abstract The hypothesis that quantitative trait loci (QTL) that explain variation between divergent populations also account for genetic variation within populations was tested using pig populations. Two regions of the porcine genome that had previously been reported to harbor QTL with allelic effects that differed between the modern pig and its wild-type ancestor and between the modern pig and a more distantly related population of Asian pigs were studied. QTL for growth and obesity traits were mapped using selectively genotyped half-sib families from five domesticated modern populations. Strong support was found for at least one QTL segregating in each population. For all five populations there was evidence of a segregating QTL affecting fatness in a region on chromosome 7. These findings confirm that QTL can be detected in highly selected commercial populations and are consistent with the hypothesis that the same chromosome locations that account for variation between populations also explain genetic variation within populations.

scholarly journals Linkage Analysis of Molecular Markers and Quantitative Trait Loci in Populations of Inbred Backcross Lines of Brassica napus L.

Genetics ◽  
1999 ◽  
Vol 153 (2) ◽  
pp. 949-964 ◽  
Author(s):  
David V Butruille ◽  
Raymond P Guries ◽  
Thomas C Osborn
Keyword(s):  
Genetic Variation ◽  
Brassica Napus ◽  
Quantitative Trait Loci ◽  
Qtl Analysis ◽  
Quantitative Trait ◽  
Agronomic Traits ◽  
Pedigree Structure ◽  
Inbred Backcross Lines ◽  
Trait Loci ◽  
Inbred Backcross

Abstract Backcross populations are often used to study quantitative trait loci (QTL) after they are initially discovered in balanced populations, such as F2, BC1, or recombinant inbreds. While the latter are more powerful for mapping marker loci, the former have the reduced background genetic variation necessary for more precise estimation of QTL effects. Many populations of inbred backcross lines (IBLs) have been developed in plant and animal systems to permit simultaneous study and dissection of quantitative genetic variation introgressed from one source to another. Such populations have a genetic structure that can be used for linkage estimation and discovery of QTL. In this study, four populations of IBLs of oilseed Brassica napus were developed and analyzed to map genomic regions from the donor parent (a winter-type cultivar) that affect agronomic traits in spring-type inbreds and hybrids. Restriction fragment length polymorphisms (RFLPs) identified among the IBLs were used to calculate two-point recombination fractions and LOD scores through grid searches. This information allowed the enrichment of a composite genetic map of B. napus with 72 new RFLP loci. The selfed and hybrid progenies of the IBLs were evaluated during two growing seasons for several agronomic traits. Both pedigree structure and map information were incorporated into the QTL analysis by using a regression approach. The number of QTL detected for each trait and the number of effective factors calculated by using biometrical methods were of similar magnitude. Populations of IBLs were shown to be valuable for both marker mapping and QTL analysis.

scholarly journals Multiple Interval Mapping for Quantitative Trait Loci

Genetics ◽  
1999 ◽  
Vol 152 (3) ◽  
pp. 1203-1216
Author(s):  
Chen-Hung Kao ◽  
Zhao-Bang Zeng ◽  
Robert D Teasdale
Keyword(s):  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Genetic Parameters ◽  
Interval Mapping ◽  
Ratio Test ◽  
Data Set ◽  
Multiple Interval Mapping ◽  
Total Genetic Variation ◽  
Trait Loci

Abstract A new statistical method for mapping quantitative trait loci (QTL), called multiple interval mapping (MIM), is presented. It uses multiple marker intervals simultaneously to fit multiple putative QTL directly in the model for mapping QTL. The MIM model is based on Cockerham's model for interpreting genetic parameters and the method of maximum likelihood for estimating genetic parameters. With the MIM approach, the precision and power of QTL mapping could be improved. Also, epistasis between QTL, genotypic values of individuals, and heritabilities of quantitative traits can be readily estimated and analyzed. Using the MIM model, a stepwise selection procedure with likelihood ratio test statistic as a criterion is proposed to identify QTL. This MIM method was applied to a mapping data set of radiata pine on three traits: brown cone number, tree diameter, and branch quality scores. Based on the MIM result, seven, six, and five QTL were detected for the three traits, respectively. The detected QTL individually contributed from ∼1 to 27% of the total genetic variation. Significant epistasis between four pairs of QTL in two traits was detected, and the four pairs of QTL contributed ∼10.38 and 14.14% of the total genetic variation. The asymptotic variances of QTL positions and effects were also provided to construct the confidence intervals. The estimated heritabilities were 0.5606, 0.5226, and 0.3630 for the three traits, respectively. With the estimated QTL effects and positions, the best strategy of marker-assisted selection for trait improvement for a specific purpose and requirement can be explored. The MIM FORTRAN program is available on the worldwide web (http://www.stat.sinica.edu.tw/~chkao/).

scholarly journals Widespread methylation quantitative trait loci and their role in schizophrenia risk

2020 ◽  
Author(s):  
Kira A. Perzel Mandell ◽  
Nicholas J. Eagles ◽  
Richard Wilton ◽  
Amanda J. Price ◽  
Stephen A. Semick ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Human Brain ◽  
Quantitative Trait ◽  
Functional Regions ◽  
Gene Environment ◽  
Trait Loci ◽  
Genome Bisulfite Sequencing ◽  
Methylation Quantitative Trait Loci

AbstractDNA methylation (DNAm) regulates gene expression and may represent gene-environment interactions. Using whole genome bisulfite sequencing, we surveyed DNAm in a large sample (n=344) of human brain tissues. We identify widespread genetic influence on local methylation levels throughout the genome, with 76% of SNPs and 38% of CpGs being part of methylation quantitative trait loci (meQTLs). These associations can further be clustered into regions that are differentially methylated by a given SNP, highlighting putative functional regions that explain much of the heritability associated with risk loci. Furthermore, some CpH sites associated with genetic variation. We have established a comprehensive, single base resolution view of association between genetic variation and genomic methylation, and implicate schizophrenia GWAS-associated variants as influencing the epigenetic plasticity of the brain.One-sentence summaryMost genetic variants associated with DNA methylation levels, and implicated schizophrenia GWAS variants in the human brain.

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