scholarly journals Consensus Genetic Linkage Map Construction Based on One Common Parental Line for QTL Mapping in Wheat

Agronomy ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 227
Author(s):  
Xin Hu ◽  
Yingquan Zhang ◽  
Jingjuan Zhang ◽  
Shahidul Islam ◽  
Maoyun She ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Positional Cloning ◽  
Coat Color ◽  
Physical Map ◽  
Wheat Breeding ◽  
Snp Markers ◽  
Genetic Maps ◽  
Parental Line ◽  
Seed Color ◽  
Consensus Map

The consensus map is used for the verification of marker order, quantitative trait locus (QTL) mapping and molecular marker-assisted selection (MAS) in wheat breeding. In this study, a wheat consensus genetic map named as Sp7A_G7A, was constructed using 5643 SNP markers in two double haploid (DH) populations of Spitfire × Bethlehem-7AS (Sp7A) and Gregory × Bethlehem-7AS (G7A), covering 4376.70 cM of 21 chromosomes (chr) with an average interval of 0.78 cM. The collinearity of the linkage maps with the consensus map of Con_map_Wang2014 and the physical map of wheat reference genome (IWGSC RefSeq v1.0) were analyzed based on the Spearman rank correlation coefficients. As results, the three constructed genetic maps of Sp7A, G7A and Sp7A_G7A showed high collinearity with the Con_map_Wang2014 and the physical map, and importantly, the collinearity level between our constructed maps and the wheat physical map is higher than that between the Con_map_Wang2014 and the physical map. The seed coat color QTL detected in both populations under multiple environments were on the region (745.73–760.14 Mbp) of the seed color gene R-B1/Tamyb10-B1 (TraesCS3B02G515900, 3B: 757,918,264–757,920,082 bp). The validated consensus map will be beneficial for QTL mapping, positional cloning, meta-QTL analysis and wheat breading.

scholarly journals Construction of Consensus Genetic Map With Applications in Gene Mapping of Wheat (Triticum aestivum L.) Using 90K SNP Array

2021 ◽  
Vol 12 ◽  
Author(s):  
Pingping Qu ◽  
Jiankang Wang ◽  
Weie Wen ◽  
Fengmei Gao ◽  
Jindong Liu ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Genetic Information ◽  
Physical Map ◽  
Recombinant Inbred Lines ◽  
Snp Array ◽  
Triticum Aestivum L ◽  
Kernel Weight ◽  
Consensus Map ◽  
Phenotypic Data ◽  
Putative Gene

Wheat is one of the most important cereal crops worldwide. A consensus map combines genetic information from multiple populations, providing an effective alternative to improve the genome coverage and marker density. In this study, we constructed a consensus map from three populations of recombinant inbred lines (RILs) of wheat using a 90K single nucleotide polymorphism (SNP) array. Phenotypic data on plant height (PH), spike length (SL), and thousand-kernel weight (TKW) was collected in six, four, and four environments in the three populations, and then used for quantitative trait locus (QTL) mapping. The mapping results obtained using the constructed consensus map were compared with previous results obtained using individual maps and previous studies on other populations. A simulation experiment was also conducted to assess the performance of QTL mapping with the consensus map. The constructed consensus map from the three populations spanned 4558.55 cM in length, with 25,667 SNPs, having high collinearity with physical map and individual maps. Based on the consensus map, 21, 27, and 19 stable QTLs were identified for PH, SL, and TKW, much more than those detected with individual maps. Four PH QTLs and six SL QTLs were likely to be novel. A putative gene called TraesCS4D02G076400 encoding gibberellin-regulated protein was identified to be the candidate gene for one major PH QTL located on 4DS, which may enrich genetic resources in wheat semi-dwarfing breeding. The simulation results indicated that the length of the confidence interval and standard errors of the QTLs detected using the consensus map were much smaller than those detected using individual maps. The consensus map constructed in this study provides the underlying genetic information for systematic mapping, comparison, and clustering of QTL, and gene discovery in wheat genetic study. The QTLs detected in this study had stable effects across environments and can be used to improve the wide adaptation of wheat cultivars through marker-assisted breeding.

scholarly journals Physical Mapping of QTL in Four Spring Wheat Populations under Conventional and Organic Management Systems. I. Earliness

Plants ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 853
Author(s):  
Kassa Semagn ◽  
Muhammad Iqbal ◽  
Hua Chen ◽  
Enid Perez-Lara ◽  
Darcy H. Bemister ◽  
...  
Keyword(s):  
Spring Wheat ◽  
Physical Map ◽  
Interval Mapping ◽  
Snp Markers ◽  
Genetic Maps ◽  
Management Systems ◽  
Nucleotide Polymorphisms ◽  
Phenotypic Data ◽  
Organic Management ◽  
Hard Red Spring Wheat

In previous studies, we reported quantitative trait loci (QTL) associated with the heading, flowering, and maturity time in four hard red spring wheat recombinant inbred line (RIL) populations but the results are scattered in population-specific genetic maps, which is challenging to exploit efficiently in breeding. Here, we mapped and characterized QTL associated with these three earliness traits using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map. Our data consisted of (i) 6526 single nucleotide polymorphisms (SNPs) and two traits evaluated at five conventionally managed environments in the ‘Cutler’ × ‘AC Barrie’ population; (ii) 3158 SNPs and two traits evaluated across three organic and seven conventional managements in the ‘Attila’ × ‘CDC Go’ population; (iii) 5731 SilicoDArT and SNP markers and the three traits evaluated at four conventional and organic management systems in the ‘Peace’ × ‘Carberry’ population; and (iv) 1058 SNPs and two traits evaluated across two conventionally and organically managed environments in the ‘Peace’ × ‘CDC Stanley’ population. Using composite interval mapping, the phenotypic data across all environments, and the IWGSC RefSeq v2.0 physical maps, we identified a total of 44 QTL associated with days to heading (11), flowering (10), and maturity (23). Fifteen of the 44 QTL were common to both conventional and organic management systems, and the remaining QTL were specific to either the conventional (21) or organic (8) management systems. Some QTL harbor known genes, including the Vrn-A1, Vrn-B1, Rht-A1, and Rht-B1 that regulate photoperiodism, flowering time, and plant height in wheat, which lays a solid basis for cloning and further characterization.

Genetic mapping and a new PCR-based marker linked to a dwarfing gene in oat (Avena sativa L.)

Genome ◽  
2018 ◽  
Vol 61 (7) ◽  
pp. 497-503
Author(s):  
Jun Zhao ◽  
Xueqin Tang ◽  
Charlene P. Wight ◽  
Nicholas A. Tinker ◽  
Yunfeng Jiang ◽  
...  
Keyword(s):  
Avena Sativa ◽  
Positional Cloning ◽  
Ssr Marker ◽  
Bulked Segregant Analysis ◽  
Snp Markers ◽  
Consensus Map ◽  
Mapping Data ◽  
Dwarfing Gene ◽  
Production Environments ◽  
Simple Sequence

Short straw is a desired trait in cultivated hexaploid oat (Avena sativa L.) for some production environments. Marker-assisted selection, a key tool for achieving this objective, is limited by a lack of mapping data and available markers. Here, bulked-segregant analysis was used to identify PCR-based markers associated with a dwarfing gene. Genetic analysis identified a monogenic dominant inheritance of one dwarfing gene from WAOAT2132, temporarily designated DwWA. A simple sequence repeat (SSR) marker (AME117) that was already available and a new codominant PCR-based marker (bi17) developed by homologous cloning in the present study were both associated with the dwarfing gene. The two markers were located 21 and 1.2 cM from DwWA, respectively. The bi17 marker was mapped to neighboring SNP markers on chromosome 18D of the oat consensus map. Since Dw6 was previously mapped on chromosome 18, and since our new marker bi17 is also diagnostic for NILs generated for Dw6, there is strong evidence that the dwarfing gene identified in WAOAT2132 is Dw6. The newly developed markers could find applications in the identification of this gene in oat germplasm and in the fine mapping or positional cloning of the gene.

scholarly journals Heterogeneity in Rates of Recombination Across the Mouse Genome

Genetics ◽  
1996 ◽  
Vol 142 (2) ◽  
pp. 537-548 ◽  
Author(s):  
Michael W Nachman ◽  
Gary A Churchill
Keyword(s):  
Linkage Map ◽  
Genetic Map ◽  
Large Scale ◽  
Physical Map ◽  
Genetic Maps ◽  
Recombination Rates ◽  
Physical Maps ◽  
Genomic Patterns ◽  
Mary Lyon ◽  
Microsatellite Linkage

Abstract If loci are randomly distributed on a physical map, the density of markers on a genetic map will be inversely proportional to recombination rate. First proposed by MARY LYON, we have used this idea to estimate recombination rates from the Drosophila melanogaster linkage map. These results were compared with results of two other studies that estimated regional recombination rates in D. melanogaster using both physical and genetic maps. The three methods were largely concordant in identifying large-scale genomic patterns of recombination. The marker density method was then applied to the Mus musculus microsatellite linkage map. The distribution of microsatellites provided evidence for heterogeneity in recombination rates. Centromeric regions for several mouse chromosomes had significantly greater numbers of markers than expected, suggesting that recombination rates were lower in these regions. In contrast, most telomeric regions contained significantly fewer markers than expected. This indicates that recombination rates are elevated at the telomeres of many mouse chromosomes and is consistent with a comparison of the genetic and cytogenetic maps in these regions. The density of markers on a genetic map may provide a generally useful way to estimate regional recombination rates in species for which genetic, but not physical, maps are available.

scholarly journals A Consensus Map for Loblolly Pine (Pinus taeda L.). I. Construction and Integration of Individual Linkage Maps From Two Outbred Three-Generation Pedigrees

Genetics ◽  
1999 ◽  
Vol 151 (1) ◽  
pp. 321-330 ◽  
Author(s):  
Mitchell M Sewell ◽  
Bradley K Sherman ◽  
David B Neale
Keyword(s):  
Pinus Taeda ◽  
Loblolly Pine ◽  
Fragment Length Polymorphism ◽  
Random Amplified Polymorphic Dna ◽  
Mapping Function ◽  
Genetic Maps ◽  
Linkage Data ◽  
Linkage Maps ◽  
Consensus Map ◽  
Pinus Taeda L

Abstract A consensus map for loblolly pine (Pinus taeda L.) was constructed from the integration of linkage data from two unrelated three-generation outbred pedigrees. The progeny segregation data from restriction fragment length polymorphism, random amplified polymorphic DNA, and isozyme genetic markers from each pedigree were recoded to reflect the two independent populations of parental meioses, and genetic maps were constructed to represent each parent. The rate of meiotic recombination was significantly greater for males than females, as was the average estimate of genome length for males {1983.7 cM [Kosambi mapping function (K)]} and females [1339.5 cM(K)]. The integration of individual maps allows for the synthesis of genetic information from independent sources onto a single consensus map and facilitates the consolidation of linkage groups to represent the chromosomes (n = 12) of loblolly pine. The resulting consensus map consists of 357 unique molecular markers and covers ∼1300 cM(K).

scholarly journals Saturation Mapping of a Gene-Rich Recombination Hot Spot Region in Wheat

Genetics ◽  
2000 ◽  
Vol 154 (2) ◽  
pp. 823-835 ◽  
Author(s):  
Justin D Faris ◽  
Karri M Haen ◽  
Bikram S Gill
Keyword(s):  
Positional Cloning ◽  
Physical Map ◽  
Hot Spot ◽  
Chromosome Breakage ◽  
Small Chromosome ◽  
Gene Density ◽  
Chromosome 5B ◽  
High Gene ◽  
The Many ◽  
Recombination Hot Spots

AbstractPhysical mapping of wheat chromosomes has revealed small chromosome segments of high gene density and frequent recombination interspersed with relatively large regions of low gene density and infrequent recombination. We constructed a detailed genetic and physical map of one highly recombinant region on the long arm of chromosome 5B. This distally located region accounts for 4% of the physical size of the long arm and at least 30% of the recombination along the entire chromosome. Multiple crossovers occurred within this region, and the degree of recombination is at least 11-fold greater than the genomic average. Characteristics of the region such as gene order and frequency of recombination appear to be conserved throughout the evolution of the Triticeae. The region is more prone to chromosome breakage by gametocidal gene action than gene-poor regions, and evidence for genomic instability was implied by loss of gene collinearity for six loci among the homeologous regions. These data suggest that a unique level of chromatin organization exists within gene-rich recombination hot spots. The many agronomically important genes in this region should be accessible by positional cloning.

scholarly journals A4Mb High Resolution BAC Contig on Bovine Chromosome1q12and Comparative Analysis With Human Chromosome21q22

2005 ◽  
Vol 6 (4) ◽  
pp. 194-203 ◽  
Author(s):  
Cord Drögemüller ◽  
Anne Wöhlke ◽  
Tosso Leeb ◽  
Ottmar Distl
Keyword(s):  
Positional Cloning ◽  
Physical Map ◽  
Dominant Gene ◽  
Bac Library ◽  
Exact Order ◽  
Bac Contig ◽  
Nucleotide Sequence Data ◽  
New Genes ◽  
Human Genes ◽  
First Time

The bovine RPCI-42 BAC library was screened to construct a sequence-ready ~4 Mb single contig of 92 BAC clones on BTA 1q12. The contig covers the region between the genesKRTAP8P1andCLIC6. This genomic segment in cattle is of special interest as it contains the dominant gene responsible for the hornless or polled phenotype in cattle. The construction of the BAC contig was initiated by screening the bovine BAC library with heterologous cDNA probes derived from 12 human genes of the syntenic region on HSA 21q22. Contig building was facilitated by BAC end sequencing and chromosome walking. During the construction of the contig, 165 BAC end sequences and 109 single-copy STS markers were generated. For comparative mapping of 25 HSA 21q22 genes, genomic PCR primers were designed from bovine EST sequences and the gene-associated STSs mapped on the contig. Furthermore, bovine BAC end sequence comparisons against the human genome sequence revealed significant matches to HSA 21q22 and allowed thein silicomapping of two new genes in cattle. In total, 31 orthologues of human genes located on HSA 21q22 were directly mapped within the bovine BAC contig, of which 16 genes have been cloned and mapped for the first time in cattle. In contrast to the existing comparative bovine–human RH maps of this region, these results provide a better alignment and reveal a completely conserved gene order in this 4 Mb segment between cattle, human and mouse. The mapping of known polled linked BTA 1q12 microsatellite markers allowed the integration of the physical contig map with existing linkage maps of this region and also determined the exact order of these markers for the first time. Our physical map and transcript map may be useful for positional cloning of the putative polled gene in cattle. The nucleotide sequence data reported in this paper have been submitted to EMBL and have been assigned Accession Numbers AJ698510–AJ698674.

scholarly journals fullsibQTL: an R package for QTL mapping in biparental populations of outcrossing species

2020 ◽  
Author(s):  
Rodrigo Gazaffi ◽  
Rodrigo R. Amadeu ◽  
Marcelo Mollinari ◽  
João R. B. F. Rosa ◽  
Cristiane H. Taniguti ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Open Source ◽  
Qtl Analysis ◽  
Source Code ◽  
R Package ◽  
Genetic Maps ◽  
Linkage Phase ◽  
Position Effects ◽  
Genetic Features ◽  
Outcrossing Species

ABSTRACTAccurate QTL mapping in outcrossing species requires software programs which consider genetic features of these populations, such as markers with different segregation patterns and different level of information. Although the available mapping procedures to date allow inferring QTL position and effects, they are mostly not based on multilocus genetic maps. Having a QTL analysis based in such maps is crucial since they allow informative markers to propagate their information to less informative intervals of the map. We developed fullsibQTL, a novel and freely available R package to perform composite interval QTL mapping considering outcrossing populations and markers with different segregation patterns. It allows to estimate QTL position, effects, segregation patterns, and linkage phase with flanking markers. Additionally, several statistical and graphical tools are implemented, for straightforward analysis and interpretations. fullsibQTL is an R open source package with C and R source code (GPLv3). It is multiplatform and can be installed from https://github.com/augusto-garcia/fullsibQTL.

scholarly journals Mapping and identification of yellow seed coat color genes in Brassica juncea L.

2020 ◽  
Author(s):  
Zhen Huang ◽  
Yang Wang ◽  
Hong Lu ◽  
Xiang Liu ◽  
Lu Liu ◽  
...  
Keyword(s):  
Candidate Gene ◽  
Brassica Juncea ◽  
Seed Coat ◽  
Coat Color ◽  
Seed Color ◽  
Seed Coat Color ◽  
Flavonoid Pathway ◽  
Yellow Seed ◽  
Color Formation ◽  
Yellow Seed Coat

Abstract BackgroundYellow seed breeding is an effective method to improve the oil content in rapeseed. Yellow seed coat color formation is influenced by various factors, and no clear mechanisms are known. In this study, Bulked segregant RNA-Seq (BSR-Seq) of BC9 population of Wuqi mustard (yellow seed) and Wugong mustard (brown seed) was used to identity the candidate genes controlling the yellow seed color in Brassica juncea L.ResultsYellow seed coat color gene was mapped to chromosome A09, and differentially expressed genes (DEGs) between brown and yellow bulks enriched in the flavonoid pathway. A significant correlation between the expression of BjF3H and BjTT5 and the content of the seed coat color related indexes was identified. Two intron polymorphism (IP) markers linked to the target gene were developed around BjF3H. Therefore, BjF3H was considered as the candidate gene. The BjF3H coding sequences (CDS) of Wuqi mustard and Wugong mustard are 1071-1077bp, encoding protein of 356-358 amino acids. One amino acid change (254, F/V) was identified in the conserved domain. This mutation site was detected in four Brassica rapa (B. rapa) and six Brassica juncea (B. juncea) lines, but not in Brassica napus (B. napus).ConclusionsThe results indicated BjF3H is a candidate gene that related to yellow seed coat color formation in Brassica juncea and provided a comprehensive understanding of the yellow seed coat color mechanism.

scholarly journals Construction of a high-resolution genetic map and identification of quantitative trait loci for salt tolerance in jute (Corchous spp.)

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Zemao Yang ◽  
Youxin Yang ◽  
Zhigang Dai ◽  
Dongwei Xie ◽  
Qing Tang ◽  
...  
Keyword(s):  
Salt Stress ◽  
Salt Tolerance ◽  
Qtl Mapping ◽  
Genetic Map ◽  
Quantitative Trait ◽  
High Density ◽  
Genetic Maps ◽  
Interval Length ◽  
Phenotypic Variance ◽  
Qtls Mapping

Abstract Background Jute (Corchorus spp.) is the most important natural fiber crop after cotton in terms of cultivation area and production. Salt stress greatly restricts plant development and growth. A high-density genetic linkage map is the basis of quantitative trait locus (QTLs) mapping. Several high-density genetic maps and QTLs mapping related to salt tolerance have been developed through next-generation sequencing in many crop species. However, such studies are rare for jute. Only several low-density genetic maps have been constructed and no salt tolerance-related QTL has been mapped in jute to date. Results We developed a high-density genetic map with 4839 single nucleotide polymorphism markers spanning 1375.41 cM and an average distance of 0.28 cM between adjacent markers on seven linkage groups (LGs) using an F2 jute population, LGs ranged from LG2 with 299 markers spanning 113.66 cM to LG7 with 1542 markers spanning 350.18 cM. In addition, 99.57% of gaps between adjacent markers were less than 5 cM. Three obvious and 13 minor QTLs involved in salt tolerance were identified on four LGs explaining 0.58–19.61% of the phenotypic variance. The interval length of QTL mapping varied from 1.3 to 20.2 cM. The major QTL, qJST-1, was detected under two salt stress conditions that explained 11.81 and 19.61% of the phenotypic variation, respectively, and peaked at 19.3 cM on LG4. Conclusions We developed the first high-density and the most complete genetic map of jute to date using a genotyping-by-sequencing approach. The first QTL mapping related to salt tolerance was also carried out in jute. These results should provide useful resources for marker-assisted selection and transgenic breeding for salt tolerance at the germination stage in jute.

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