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.

Genes and Quantitative Trait Loci Mapping for Major Agronomic Traits in Brassica napus L.

2018 ◽  
pp. 41-85 ◽  
Author(s):  
Régine Delourme ◽  
Anne Laperche ◽  
Anne-Sophie Bouchet ◽  
Mélanie Jubault ◽  
Sophie Paillard ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Agronomic Traits ◽  
Quantitative Trait Loci Mapping ◽  
Brassica Napus L ◽  
Trait Loci

scholarly journals Mapping quantitative trait loci in inbred backcross lines of Lycopersicon pimpinellifolium (LA1589)

Genome ◽  
2002 ◽  
Vol 45 (6) ◽  
pp. 1189-1202 ◽  
Author(s):  
Sami Doganlar ◽  
Anne Frary ◽  
Hsin-Mei Ku ◽  
Steven D Tanksley
Keyword(s):  
Quantitative Trait Loci ◽  
Lycopersicon Esculentum ◽  
Quantitative Trait ◽  
Interspecific Cross ◽  
Tomato Production ◽  
Significant Qtls ◽  
Wild Allele ◽  
Inbred Backcross Lines ◽  
Trait Loci ◽  
Inbred Backcross

Although tomato has been the subject of extensive quantitative trait loci (QTLs) mapping experiments, most of this work has been conducted on transient populations (e.g., F2 or backcross) and few homozygous, permanent mapping populations are available. To help remedy this situation, we have developed a set of inbred backcross lines (IBLs) from the interspecific cross between Lycopersicon esculentum cv. E6203 and L. pimpinellifolium (LA1589). A total of 170 BC2F1 plants were selfed for five generations to create a set of homozygous BC2F6 lines by single-seed descent. These lines were then genotyped for 127 marker loci covering the entire tomato genome. These IBLs were evaluated for 22 quantitative traits. In all, 71 significant QTLs were identified, 15% (11/71) of which mapped to the same chromosomal positions as QTLs identified in earlier studies using the same cross. For 48% (34/71) of the detected QTLs, the wild allele was associated with improved agronomic performance. A number of new QTLs were identified including several of significant agronomic importance for tomato production: fruit shape, firmness, fruit color, scar size, seed and flower number, leaf curliness, plant growth, fertility, and flowering time. To improve the utility of the IBL population, a subset of 100 lines giving the most uniform genome coverage and map resolution was selected using a randomized greedy algorithm as implemented in the software package MapPop (http://www.bio.unc.edu/faculty/vision/lab/mappop/). The map, phenotypic data, and seeds for the IBL population are publicly available (http://soldb.cit.cornell.edu) and will provide tomato geneticists and breeders with a genetic resource for mapping, gene discovery, and breeding.Key words: tomato, Lycopersicon esculentum, IBLs, QTL, mapping.

scholarly journals Quantitative Trait Loci Associated with Rotylenchulus reniformis Host Suitability in Soybean

2020 ◽  
Vol 110 (9) ◽  
pp. 1511-1521
Author(s):  
Juliet Wilkes ◽  
Christopher Saski ◽  
Mariola Klepadlo ◽  
Benjamin Fallen ◽  
Paula Agudelo
Keyword(s):  
Quantitative Trait Loci ◽  
Qtl Analysis ◽  
Quantitative Trait ◽  
The United States ◽  
Host Suitability ◽  
Reniform Nematode ◽  
Rotylenchulus Reniformis ◽  
Chromosome 18 ◽  
Nematode Reproduction ◽  
Trait Loci

Reniform nematode (Rotylenchulus reniformis) is a yield-limiting pathogen of soybean (Glycine max) in the southeastern region of the United States. A population of 250 recombinant inbred lines (RIL) (F2:8) developed from a cross between reniform nematode resistant soybean cultivar Forrest and susceptible cultivar Williams 82 was utilized to identify regions associated with host suitability. A genetic linkage map was constructed using single-nucleotide polymorphism markers generated by genotyping-by-sequencing. The phenotype was measured in the RIL population and resistance was characterized using normalized and transformed nematode reproduction indices in an optimal univariate cluster analysis. Quantitative trait loci (QTL) analysis using normalized phenotype scores identified two QTLs on each arm of chromosome 18 (rrn-1 and rrn-2). The same QTL analysis performed with log10(x) transformed phenotype data also identified two QTLs: one on chromosome 18 overlapping the same region in the other analysis (rrn-1), and one on chromosome 11 (rrn-3). While rrn-1 and rrn-3 have been reported associated with reduced reproduction of reniform nematode, this is the first report of the rrn-2 region associated with host suitability to reniform nematode. The resistant parent allele at rrn-2 showed an inverse relationship with the resistance phenotype, correlating with an increase in nematode reproduction or host suitability. Several candidate genes within these regions corresponded with host plant defense systems. Interestingly, a characteristic pathogen resistance gene with a leucine-rich repeat was discovered within rrn-2. These genetic markers can be used by soybean breeders in marker-assisted selection to develop lines with resistance to reniform nematode.

scholarly journals The Genetic Basis of the Interspecific Differences in Wing Size in Nasonia (Hymenoptera; Pteromalidae): Major Quantitative Trait Loci and Epistasis

Genetics ◽  
2002 ◽  
Vol 161 (2) ◽  
pp. 673-684
Author(s):  
J Gadau ◽  
R E Page ◽  
J H Werren
Keyword(s):  
Quantitative Trait Loci ◽  
Qtl Analysis ◽  
Quantitative Trait ◽  
Wing Length ◽  
Size Difference ◽  
Phenotypic Variance ◽  
Wing Size ◽  
Epistatic Interactions ◽  
Trait Loci ◽  
Wing Width

Abstract There is a 2.5-fold difference in male wing size between two haplodiploid insect species, Nasonia vitripennis and N. giraulti. The haploidy of males facilitated a full genomic screen for quantitative trait loci (QTL) affecting wing size and the detection of epistatic interactions. A QTL analysis of the interspecific wing-size difference revealed QTL with major effects and epistatic interactions among loci affecting the trait. We analyzed 178 hybrid males and initially found two major QTL for wing length, one for wing width, three for a normalized wing-size variable, and five for wing seta density. One QTL for wing width explains 38.1% of the phenotypic variance, and the same QTL explains 22% of the phenotypic variance in normalized wing size. This corresponds to a region previously introgressed from N. giraulti into N. vitripennis that accounts for 44% of the normalized wing-size difference between the species. Significant epistatic interactions were also found that affect wing size and density of setae on the wing. Screening for pairwise epistatic interactions between loci on different linkage groups revealed four additional loci for wing length and four loci for normalized wing size that were not detected in the original QTL analysis. We propose that the evolution of smaller wings in N. vitripennis males is primarily the result of major mutations at few genomic regions and involves epistatic interactions among some loci.

scholarly journals Wheat genetic resources – how to exploit?

2011 ◽  
Vol 47 (Special Issue) ◽  
pp. S43-S48 ◽  
Author(s):  
A. Börner ◽  
K. Neumann ◽  
B. Kobiljski
Keyword(s):  
Quantitative Trait Loci ◽  
Genetic Resources ◽  
Quantitative Trait ◽  
Molecular Mapping ◽  
Agronomic Traits ◽  
Wide Spectrum ◽  
Plant Genetic Resources ◽  
Germplasm Collections ◽  
Food And Agriculture ◽  
Trait Loci

It is estimated that world-wide existing germplasm collections contain about 7.5 million accessions of plant genetic resources for food and agriculture. Wheat (Triticum and Aegilops) represents the biggest group comprising 900 000 accessions. However, such a huge number of accessions is hindering a successful exploitation of the germplasm. The creation of core collections representing a wide spectrum of the genetic variation of the whole assembly may help to overcome the problem. Here we demonstrate the successful utilisation of such a core collection for the identification and molecular mapping of genes (Quantitative Trait Loci) determining the agronomic traits flowering time and grain yield, exploiting a marker-trait-association based technique. Significant marker-trait associations were obtained and are presented. The intrachromosomal location of many of these associations coincided with those of already identified major genes or quantitative trait loci, but others were detected in regions where no known genes have been located to date.

Genetics of Soybean Agronomic Traits: II. Interactions between Yield Quantitative Trait Loci in Soybean

Crop Science ◽  
1999 ◽  
Vol 39 (6) ◽  
pp. 1652-1657 ◽  
Author(s):  
J. H. Orf ◽  
K. Chase ◽  
F. R. Adler ◽  
L. M. Mansur ◽  
K. G. Lark
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Agronomic Traits ◽  
Trait Loci

scholarly journals Quantitative trait loci for agronomic traits in an elite barley population for Mediterranean conditions

2013 ◽  
Vol 33 (2) ◽  
pp. 249-265 ◽  
Author(s):  
Elsayed Mansour ◽  
Ana M. Casas ◽  
M. Pilar Gracia ◽  
José Luis Molina-Cano ◽  
Marian Moralejo ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Agronomic Traits ◽  
Trait Loci ◽  
Barley Population ◽  
Mediterranean Conditions

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
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