Selective Mapping: A Strategy for Optimizing the Construction of High-Density Linkage Maps

Abstract Historically, linkage mapping populations have consisted of large, randomly selected samples of progeny from a given pedigree or cell lines from a panel of radiation hybrids. We demonstrate that, to construct a map with high genome-wide marker density, it is neither necessary nor desirable to genotype all markers in every individual of a large mapping population. Instead, a reduced sample of individuals bearing complementary recombinational or radiation-induced breakpoints may be selected for genotyping subsequent markers from a large, but sparsely genotyped, mapping population. Choosing such a sample can be reduced to a discrete stochastic optimization problem for which the goal is a sample with breakpoints spaced evenly throughout the genome. We have developed several different methods for selecting such samples and have evaluated their performance on simulated and actual mapping populations, including the Lister and Dean Arabidopsis thaliana recombinant inbred population and the GeneBridge 4 human radiation hybrid panel. Our methods quickly and consistently find much-reduced samples with map resolution approaching that of the larger populations from which they are derived. This approach, which we have termed selective mapping, can facilitate the production of high-quality, high-density genome-wide linkage maps.

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Advanced Strategies in Bulked Segregant Analysis and its Applications

Bhartiya Krishi Anusandhan Patrika ◽

10.18805/bkap327 ◽

2021 ◽

Author(s):

Harshavardan J. Hilli

Keyword(s):

Genetic Markers ◽

Mapping Population ◽

Bulked Segregant Analysis ◽

High Density ◽

Mutant Phenotype ◽

Linkage Maps ◽

Quick Method ◽

Reduced Time

Bulked segregant analysis (BSA) is a technique used to identify genetic markers associated with a mutant phenotype and is a quick method for identifying markers in particular genome regions. The paper focussed on Advanced methods which escape the requirement of genotyping all the individuals of the mapping population and generation of high-density linkage maps for mapping of the gene for the trait of interest. With the emergence of re-sequencing techniques, quick mapping of genes has become possible with reduced time and cost by using advanced methodologies like MutMap, MutMap+, MutMap-Gap, QTL-Seq, RNAseq BSA, NGS BSA and QTG seq. The procedure for various advanced BSA strategies has been described.

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Recent Advances in Molecular Genetic Linkage Maps of Cultivated Peanut

Peanut Science ◽

10.3146/ps13-03.1 ◽

2013 ◽

Vol 40 (2) ◽

pp. 95-106 ◽

Cited By ~ 12

Author(s):

Baozhu Guo ◽

Manish K. Pandey ◽

Guohao He ◽

Xinyou Zhang ◽

Boshou Liao ◽

...

Keyword(s):

Genetic Linkage ◽

High Density ◽

Genetic Maps ◽

Linkage Maps ◽

Consensus Map ◽

Genetic Linkage Maps ◽

Marker Loci ◽

Cultivated Peanut ◽

Peanut Genome ◽

Mapping Populations

ABSTRACT The competitiveness of peanuts in domestic and global markets has been threatened by losses in productivity and quality that are attributed to diseases, pests, environmental stresses and allergy or food safety issues. Narrow genetic diversity and a deficiency of polymorphic DNA markers severely hindered construction of dense genetic maps and quantitative trait loci (QTL) mapping in order to deploy linked markers in marker-assisted peanut improvement. The U.S. Peanut Genome Initiative (PGI) was launched in 2004, and expanded to a global effort in 2006 to address these issues through coordination of international efforts in genome research beginning with molecular marker development and improvement of map resolution and coverage. Ultimately, a peanut genome sequencing project was launched in 2012 by the Peanut Genome Consortium (PGC). We reviewed the progress for accelerated development of peanut genomic resources in peanut, such as generation of expressed sequenced tags (ESTs) (252,832 ESTs as December 2012 in the public NCBI EST database), development of molecular markers (over 15,518 SSRs), and construction of peanut genetic linkage maps, in particular for cultivated peanut. Several consensus genetic maps have been constructed, and there are examples of recent international efforts to develop high density maps. An international reference consensus genetic map was developed recently with 897 marker loci based on 11 published mapping populations. Furthermore, a high-density integrated consensus map of cultivated peanut and wild diploid relatives also has been developed, which was enriched further with 3693 marker loci on a single map by adding information from five new genetic mapping populations to the published reference consensus map.

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Mapping of markers related to self-incompatibility, disease resistance, and quality traits in Lolium perenne L.

Genome ◽

10.1139/g08-051 ◽

2008 ◽

Vol 51 (8) ◽

pp. 644-656 ◽

Cited By ~ 3

Author(s):

Inge Van Daele ◽

Hilde Muylle ◽

Erik Van Bockstaele ◽

Isabel Roldán-Ruiz

Keyword(s):

Disease Resistance ◽

Lolium Perenne ◽

Mapping Population ◽

Sugar Content ◽

Quality Traits ◽

Linkage Maps ◽

Self Incompatibility ◽

Length Polymorphisms ◽

Map Alignment ◽

Mapping Populations

Several linkage maps, mainly based on anonymous markers, are now available for Lolium perenne . The saturation of these maps with markers derived from expressed sequences would provide information useful for QTL mapping and map alignment. Therefore, we initiated a study to develop and map DNA markers in genes related to self-incompatibility, disease resistance, and quality traits such as digestibility and sugar content in two L. perenne families. In total, 483 and 504 primer pairs were designed and used to screen the ILGI and CLO-DvP mapping populations, respectively, for length polymorphisms. Finally, we were able to map 67 EST markers in at least one mapping population. Several of these markers coincide with previously reported QTL regions for the traits considered or are located in the neighbourhood of the self-incompatibility loci, S and Z. The markers developed expand the set of gene-derived markers available for genetic mapping in ryegrasses.

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Genomic Resource Development for Hydrangea (Hydrangea macrophylla (Thunb.) Ser.)—A Transcriptome Assembly and a High-Density Genetic Linkage Map

Horticulturae ◽

10.3390/horticulturae7020025 ◽

2021 ◽

Vol 7 (2) ◽

pp. 25

Author(s):

Xingbo Wu ◽

Amanda M. Hulse-Kemp ◽

Phillip A. Wadl ◽

Zach Smith ◽

Keithanne Mockaitis ◽

...

Keyword(s):

Genetic Resources ◽

Linkage Map ◽

Genetic Linkage ◽

Genetic Linkage Map ◽

Mapping Population ◽

High Density ◽

Linkage Maps ◽

Map Construction ◽

Hydrangea Macrophylla ◽

Genetic Linkage Maps

Hydrangea (Hydrangea macrophylla) is an important ornamental crop that has been cultivated for more than 300 years. Despite the economic importance, genetic studies for hydrangea have been limited by the lack of genetic resources. Genetic linkage maps and subsequent trait mapping are essential tools to identify and make markers available for marker-assisted breeding. A transcriptomic study was performed on two important cultivars, Veitchii and Endless Summer, to discover simple sequence repeat (SSR) markers and an F1 population based on the cross ‘Veitchii’ × ‘Endless Summer’ was established for genetic linkage map construction. Genotyping by sequencing (GBS) was performed on the mapping population along with SSR genotyping. From an analysis of 42,682 putative transcripts, 8780 SSRs were identified and 1535 were validated in the mapping parents. A total of 267 polymorphic SSRs were selected for linkage map construction. The GBS yielded 3923 high quality single nucleotide polymorphisms (SNPs) in the mapping population, resulting in a total of 4190 markers that were used to generate maps for each parent and a consensus map. The consensus linkage map contained 1767 positioned markers (146 SSRs and 1621 SNPs), spanned 1383.4 centiMorgans (cM), and was comprised of 18 linkage groups, with an average mapping interval of 0.8 cM. The transcriptome information and large-scale marker development in this study greatly expanded the genetic resources that are available for hydrangea. The high-density genetic linkage maps presented here will serve as an important foundation for quantitative trait loci mapping, map-based gene cloning, and marker-assisted selection of H. macrophylla.

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Chromosome regions affecting body weight in egg layers

Agricultural and Food Science ◽

10.2137/145960607782219355 ◽

2008 ◽

Vol 16 (2) ◽

pp. 177 ◽

Cited By ~ 1

Author(s):

M. HONKATUKIA ◽

M. TUISKULA-HAAVISTO ◽

J. VILKKI

Keyword(s):

Body Weight ◽

Feed Intake ◽

Egg Production ◽

Mapping Population ◽

Genome Wide ◽

Adult Body Weight ◽

Parent Of Origin ◽

Chromosome Regions ◽

Mapping Populations ◽

Good Agreement

We have previously mapped quantitative trait loci (QTL) affecting egg production and quality traits using a reciprocal cross of two divergent egg-layer lines. The lines differ also in body weight, and we initially identified genome-wide significant Mendelian QTL for adult body weight at 40 weeks of age and feed intake at 3236 weeks of age. In addition, QTL with parent-of-origin effects were detected for feed intake and body weight. In the present study, a total of five body weight traits (weight at 16, 20, 24, 40 and 60 weeks of age) have been analysed in the same mapping population. New QTL affecting body weight at different ages were found on chromosomes 1, 4, 5, 6, and 13. Both Mendelian QTL and loci with parent-of-origin expression were found. Our findings are in good agreement with the results of previous studies on different mapping populations. The results elucidate the most important chromosome regions affecting weight in poultry in general and may add to the understanding of such loci among domestic animals.;

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Faculty Opinions recommendation of High-density sex-specific linkage maps of a European tree frog (Hyla arborea) identify the sex chromosome without information on offspring sex.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.725792646.793510088 ◽

2015 ◽

Author(s):

Deborah Charlesworth

Keyword(s):

Sex Chromosome ◽

High Density ◽

Tree Frog ◽

Linkage Maps ◽

Hyla Arborea ◽

Offspring Sex

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P6017 A high density genome-wide scan for genetic risk factors of insect bite hypersensitivity (IBH): A Horsegene Project Initiative

Journal of Animal Science ◽

10.2527/jas2016.94supplement4156a ◽

2016 ◽

Vol 94 (suppl_4) ◽

pp. 156-157

Author(s):

B. D. Velie ◽

M. Shrestha ◽

L. Francois ◽

A. Schurink ◽

A. Stinckens ◽

...

Keyword(s):

Risk Factors ◽

Genetic Risk ◽

Genetic Risk Factors ◽

High Density ◽

Genome Wide ◽

Insect Bite Hypersensitivity ◽

Genome Wide Scan

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QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents

Genes ◽

10.3390/genes12040604 ◽

2021 ◽

Vol 12 (4) ◽

pp. 604

Author(s):

Paolo Vitale ◽

Fabio Fania ◽

Salvatore Esposito ◽

Ivano Pecorella ◽

Nicola Pecchioni ◽

...

Keyword(s):

Candidate Genes ◽

Recombinant Inbred Lines ◽

Snp Array ◽

Heading Date ◽

Tiller Number ◽

Genetic Maps ◽

Yield Potential ◽

Adaptation To Climate Change ◽

Map Resolution ◽

Mapping Populations

Traits such as plant height (PH), juvenile growth habit (GH), heading date (HD), and tiller number are important for both increasing yield potential and improving crop adaptation to climate change. In the present study, these traits were investigated by using the same bi-parental population at early (F2 and F2-derived F3 families) and late (F6 and F7, recombinant inbred lines, RILs) generations to detect quantitative trait loci (QTLs) and search for candidate genes. A total of 176 and 178 lines were genotyped by the wheat Illumina 25K Infinium SNP array. The two genetic maps spanned 2486.97 cM and 3732.84 cM in length, for the F2 and RILs, respectively. QTLs explaining the highest phenotypic variation were found on chromosomes 2B, 2D, 5A, and 7D for HD and GH, whereas those for PH were found on chromosomes 4B and 4D. Several QTL detected in the early generations (i.e., PH and tiller number) were not detected in the late generations as they were due to dominance effects. Some of the identified QTLs co-mapped to well-known adaptive genes (i.e., Ppd-1, Vrn-1, and Rht-1). Other putative candidate genes were identified for each trait, of which PINE1 and PIF4 may be considered new for GH and TTN in wheat. The use of a large F2 mapping population combined with NGS-based genotyping techniques could improve map resolution and allow closer QTL tagging.

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