Application of a canonical transformation to detection of quantitative trait loci with the aid of genetic markers in a multi-trait experiment

1996 ◽  
Vol 92 (8) ◽  
pp. 998-1002 ◽  
Author(s):  
J. I. Weller ◽  
G. R. Wiggans ◽  
P. M. VanRaden ◽  
M. Ron
Keyword(s):  
Quantitative Trait Loci ◽  
Genetic Markers ◽  
Canonical Transformation ◽  
Quantitative Trait ◽  
Trait Loci

Application of a canonical transformation to detection of quantitative trait loci with the aid of genetic markers in a multi-trait experiment

1996 ◽  
Vol 92 (8) ◽  
pp. 998-1002 ◽  
Author(s):  
J. I. Weller ◽  
G. R. Wiggans ◽  
P. M. VanRaden ◽  
M. Ron
Keyword(s):  
Quantitative Trait Loci ◽  
Genetic Markers ◽  
Canonical Transformation ◽  
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.

A Program to Detect Linkage between Genetic Markers and Nonadditive Quantitative Trait Loci

1991 ◽  
Vol 82 (5) ◽  
pp. 435-435 ◽  
Author(s):  
E. A. Carbonell ◽  
T. M. Gerig
Keyword(s):  
Quantitative Trait Loci ◽  
Genetic Markers ◽  
Quantitative Trait ◽  
Trait Loci

scholarly journals Fine mapping of quantitative trait loci using selected overlapping recombinant chromosomes, in an interspecies cross of tomato.

Genetics ◽  
1990 ◽  
Vol 124 (3) ◽  
pp. 735-742 ◽  
Author(s):  
A H Paterson ◽  
J W DeVerna ◽  
B Lanini ◽  
S D Tanksley
Keyword(s):  
Quantitative Trait Loci ◽  
Genetic Markers ◽  
Quantitative Trait ◽  
Soluble Solids ◽  
Domestic Species ◽  
Substitution Mapping ◽  
Solids Concentration ◽  
Small Fruit ◽  
Trait Loci ◽  
Soluble Solids Concentration

Abstract Quantitative trait loci (QTLs) have been mapped to small intervals along the chromosomes of tomato (Lycopersicon esculentum), by a method we call substitution mapping. The size of the interval to which a QTL can be mapped is determined primarily by the number and spacing of previously mapped genetic markers in the region surrounding the QTL. We demonstrate the method using tomato genotypes carrying chromosomal segments from Lycopersicon chmielewskii, a wild relative of tomato with high soluble solids concentration but small fruit and low yield. Different L. chmielewskii chromosomal segments carrying a common restriction fragment length polymorphism were identified, and their regions of overlap determined using all available genetic markers. The effect of these chromosomal segments on soluble solids concentration, fruit mass, yield, and pH, was determined in the field. Many overlapping chromosomal segments had very different phenotypic effects, indicating QTLs affecting the phenotype(s) to lie in intervals of as little as 3 cM by which the segments differed. Some associations between different traits were attributed to close linkage between two or more QTLs, rather than pleiotropic effects of a single QTL: in such cases, recombination should separate desirable QTLs from genes with undesirable effects. The prominence of such trait associations in wide crosses appears partly due to infrequent reciprocal recombination between heterozygous chromosomal segments flanked by homozygous regions. Substitution mapping is particularly applicable to gene introgression from wild to domestic species, and generally useful in narrowing the gap between linkage mapping and physical mapping of QTLs.

Bayesian analysis of linkage between genetic markers and quantitative trait loci. I. Prior knowledge

1993 ◽  
Vol 85 (8) ◽  
pp. 953-960 ◽  
Author(s):  
I. Hoeschele ◽  
P. M. VanRaden
Keyword(s):  
Quantitative Trait Loci ◽  
Bayesian Analysis ◽  
Prior Knowledge ◽  
Genetic Markers ◽  
Quantitative Trait ◽  
Trait Loci

Statistical analysis of a linkage experiment in barley involving quantitative trait loci for height and ear-emergence time and two genetic markers on chromosome 4

1992 ◽  
Vol 85 (1) ◽  
pp. 120-126 ◽  
Author(s):  
C. A. Hackett ◽  
R. P. Ellis ◽  
B. P. Forster ◽  
J. W. McNicol ◽  
M. Macaulay
Keyword(s):  
Statistical Analysis ◽  
Quantitative Trait Loci ◽  
Genetic Markers ◽  
Quantitative Trait ◽  
Chromosome 4 ◽  
Emergence Time ◽  
Trait Loci

Transcriptomics–genomics data integration and expression quantitative trait loci analyses in oocyte donors and embryo recipients for improving invitro production of dairy cattle embryos

2019 ◽  
Vol 31 (1) ◽  
pp. 55
Author(s):  
H. N. Kadarmideen ◽  
G. Mazzoni
Keyword(s):  
Quantitative Trait Loci ◽  
Candidate Genes ◽  
Genetic Markers ◽  
Quantitative Trait ◽  
Molecular Mechanisms ◽  
Cyclin B1 ◽  
Expression Quantitative Trait Loci ◽  
Entire Genome ◽  
Trait Loci ◽  
Transcriptomics Data

In this paper we first provide a brief review of main results from our previously published studies on genome-wide gene expression (transcriptomics) in donor and recipient cattle used in invitro production (IVP) of embryos and embryo transfer (ET). Then, we present novel results from applying integrative systems genomics and biological analyses where transcriptomics data are combined with genomic data in both donor and recipient cattle to map expression quantitative trait loci (eQTLs). The eQTLs are genetic markers that can regulate or control the expression of genes in the entire genome, via complex molecular mechanisms, and thus can act as a powerful tool for genomic and gene-assisted selection. We identified significant eQTLs potentially controlling the expression of 13 candidate genes for donor cow quality (IVP parameters; e.g. cyclin B1 (CCNB1), outer dense fiber of sperm tails 2 like (ODF2L)) and 19 candidate genes for recipient cows quality (endometrial receptivity; e.g. ER membrane protein complex subunit 9 (EMC9), mannosidase beta (MANBA), peptidase inhibitor 16 (PI16)). Annotation and colocation of detected eQTLs show that some of the eQTLs are in the same genomic regions previously reported as QTLs for reproduction-related traits. However, eQTLs and the candidate genes identified should be further validated in larger populations before implementation as genetic markers or used in genomic selection for improving IVP and ET performance.

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