scholarly journals Mapping Quantitative Trait Loci onto Chromosome-Scale Pseudomolecules in Flax

2020 ◽  
Vol 3 (2) ◽  
pp. 28 ◽  
Author(s):  
Frank M. You ◽  
Sylvie Cloutier
Keyword(s):  
Quantitative Trait Loci ◽  
Candidate Genes ◽  
Quantitative Trait ◽  
Quantitative Traits ◽  
Snp Markers ◽  
Genetic Maps ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Trait Loci ◽  
Genomic Regions

Quantitative trait loci (QTL) are genomic regions associated with phenotype variation of quantitative traits. To date, a total of 313 QTL for 31 quantitative traits have been reported in 14 studies on flax. Of these, 200 QTL from 12 studies were identified based on genetic maps, the scaffold sequences, or the pre-released chromosome-scale pseudomolecules. Molecular markers for QTL identification differed across studies but the most used ones were simple sequence repeats (SSRs) or single nucleotide polymorphisms (SNPs). To uniquely map the SSR and SNP markers from different references onto the recently released chromosome-scale pseudomolecules, methods with several scripts and database files were developed to locate PCR- and SNP-based markers onto the same reference, co-locate QTL, and scan genome-wide candidate genes. Using these methods, 195 out of 200 QTL were successfully sorted onto the 15 flax chromosomes and grouped into 133 co-located QTL clusters; the candidate genes that co-located with these QTL clusters were also predicted. The methods and tools presented in this article facilitate marker re-mapping to a new reference, genome-wide QTL analysis, candidate gene scanning, and breeding applications in flax and other crops.

scholarly journals Mapping Quantitative Trait Loci onto Chromosome-scale Pseudomolecules in Flax

2019 ◽  
Author(s):  
Frank M. You ◽  
Sylvie Cloutier
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Quantitative Traits ◽  
Snp Markers ◽  
Genetic Maps ◽  
Genome Wide ◽  
Trait Loci ◽  
Ssr And Snp Markers ◽  
Gene Scanning ◽  
Genomic Regions

Quantitative trait loci (QTL) are genomic regions associated with phenotype variation of quantitative traits in a population. To date, a total of 267 QTL for 29 quantitative traits have been reported in 13 studies on flax. Of these, 200 QTL from 12 studies were identified based on genetic maps, scaffold sequences, or pre-released chromosome-scale pseudomolecules. Molecular markers for QTL identification differed across studies but were mainly based on simple sequence repeat (SSR) or single nucleotide polymorphism (SNP) markers. This article provides methods with software tools and database files to uniquely map SSR and SNP markers from different references onto the recently released chromosome-scale pseudomolecules. Using these methods, 195 QTL were successfully sorted onto the 15 flax chromosomes and grouped into 133 co-located QTL clusters. Mapping of QTL from different studies to the same reference enables comparisons and facilitates genome-wide QTL analysis, candidate gene scanning, and breeding applications.

scholarly journals Genome-wide Association Study for Carcass Primal Cut Yields Using Single-step Bayesian Approach in Hanwoo Cattle

2021 ◽  
Vol 12 ◽  
Author(s):  
Masoumeh Naserkheil ◽  
Hossein Mehrban ◽  
Deukmin Lee ◽  
Mi Na Park
Keyword(s):  
Quantitative Trait Loci ◽  
Candidate Genes ◽  
Quantitative Trait ◽  
Single Step ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Trait Loci ◽  
Genomic Regions ◽  
Hanwoo Cattle

The importance of meat and carcass quality is growing in beef cattle production to meet both producer and consumer demands. Primal cut yields, which reflect the body compositions of carcass, could determine the carcass grade and, consequently, command premium prices. Despite its importance, there have been few genome-wide association studies on these traits. This study aimed to identify genomic regions and putative candidate genes related to 10 primal cut traits, including tenderloin, sirloin, striploin, chuck, brisket, top round, bottom round, shank, flank, and rib in Hanwoo cattle using a single-step Bayesian regression (ssBR) approach. After genomic data quality control, 43,987 SNPs from 3,745 genotyped animals were available, of which 3,467 had phenotypic records for the analyzed traits. A total of 16 significant genomic regions (1-Mb window) were identified, of which five large-effect quantitative trait loci (QTLs) located on chromosomes 6 at 38–39 Mb, 11 at 21–22 Mb, 14 at 6–7 Mb and 26–27 Mb, and 19 at 26–27 Mb were associated with more than one trait, while the remaining 11 QTLs were trait-specific. These significant regions were harbored by 154 genes, among which TOX, FAM184B, SPP1, IBSP, PKD2, SDCBP, PIGY, LCORL, NCAPG, and ABCG2 were noteworthy. Enrichment analysis revealed biological processes and functional terms involved in growth and lipid metabolism, such as growth (GO:0040007), muscle structure development (GO:0061061), skeletal system development (GO:0001501), animal organ development (GO:0048513), lipid metabolic process (GO:0006629), response to lipid (GO:0033993), metabolic pathways (bta01100), focal adhesion (bta04510), ECM–receptor interaction (bta04512), fat digestion and absorption (bta04975), and Rap1 signaling pathway (bta04015) being the most significant for the carcass primal cut traits. Thus, identification of quantitative trait loci regions and plausible candidate genes will aid in a better understanding of the genetic and biological mechanisms regulating carcass primal cut yields.

scholarly journals Mapping Quantitative Trait Loci Associated With Graft (In)Compatibility in Apricot (Prunus armeniaca L.)

2021 ◽  
Vol 12 ◽  
Author(s):  
Ana Pina ◽  
Patricia Irisarri ◽  
Pilar Errea ◽  
Tetyana Zhebentyayeva
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Woody Plants ◽  
Molecular Mechanisms ◽  
Prunus Persica ◽  
Snp Markers ◽  
Genetic Maps ◽  
Phenotypic Data ◽  
Trait Loci ◽  
Genomic Regions

Graft incompatibility (GI) between the most popular Prunus rootstocks and apricot cultivars is one of the major problems for rootstock usage and improvement. Failure in producing long-leaving healthy grafts greatly affects the range of available Prunus rootstocks for apricot cultivation. Despite recent advances related to the molecular mechanisms of a graft-union formation between rootstock and scion, information on genetic control of this trait in woody plants is essentially missing because of a lack of hybrid crosses, segregating for the trait. In this study, we have employed the next-generation sequencing technology to generate the single-nucleotide polymorphism (SNP) markers and construct parental linkage maps for an apricot F1 population “Moniqui (Mo)” × “Paviot (Pa)” segregating for ability to form successful grafts with universal Prunus rootstock “Marianna 2624”. To localize genomic regions associated with this trait, we genotyped 138 individuals from the “Mo × Pa” cross and constructed medium-saturated genetic maps. The female “Mo” and male “Pa” maps were composed of 557 and 501 SNPs and organized in eight linkage groups that covered 780.2 and 690.4 cM of genetic distance, respectively. Parental maps were aligned to the Prunus persica v2.0 genome and revealed a high colinearity with the Prunus reference map. Two-year phenotypic data for characters associated with unsuccessful grafting such as necrotic line (NL), bark and wood discontinuities (BD and WD), and an overall estimate of graft (in)compatibility (GI) were collected for mapping quantitative trait loci (QTLs) on both parental maps. On the map of the graft-compatible parent “Pa”, two genomic regions on LG5 (44.9–60.8 cM) and LG8 (33.2–39.2 cM) were associated with graft (in)compatibility characters at different significance level, depending on phenotypic dataset. Of these, the LG8 QTL interval was most consistent between the years and supported by two significant and two putative QTLs. To our best knowledge, this is the first report on QTLs for graft (in)compatibility in woody plants. Results of this work will provide a valuable genomic resource for apricot breeding programs and facilitate future efforts focused on candidate genes discovery for graft (in)compatibility in apricot and other Prunus species.

scholarly journals A Fine mapping quantitative trait loci that underlie resistance to soybean sudden death syndrome using NILs and SNPs.

2018 ◽  
pp. 583-591
Author(s):  
Yi Chen Lee ◽  
M Javed Iqbal ◽  
Victor N Njiti ◽  
Stella Kantartzi ◽  
David A. Lightfoot
Keyword(s):  
Quantitative Trait Loci ◽  
Sudden Death ◽  
Candidate Genes ◽  
Quantitative Trait ◽  
Soybean Cyst Nematode ◽  
Snp Markers ◽  
Sudden Death Syndrome ◽  
Isogenic Line ◽  
Trait Loci ◽  
Glycine Max L

Soybean (Glycine max (L.) Merr.) cultivars differ in their resistance to sudden death syndrome (SDS), caused by Fusarium virguliforme. Breeding for improving SDS response has been challenging, due to interactions among the 18-42 known resistance loci. Four quantitative trait loci (QTL) for resistance to SDS (cqRfs–cqRfs3) were clustered within 20 cM of the rhg1 locus underlying resistance to soybean cyst nematode (SCN) on Chromosome (Chr.) 18. Another locus on Chr. 20 (cqRfs5) was reported to interact with this cluster. The aims here were to compare the inheritance of resistance to SDS in a near isogenic line (NIL) population that was fixed for resistance to SCN but segregated at two of the four loci (cqRfs1 and cqRfs) for SDS resistance; to examine the interaction with the locus on Chr. 20; and to identify candidate genes underlying QTL. Used were; a NIL population derived from residual heterozygosity in an F5:7 recombinant inbred line EF60 (lines 1-38); SDS response data from two locations and years; four segregating microsatellite and 1,500 SNP markers. Polymorphic regions were found from 2,788 Kbp to 8,938 Kbp on Chr. 18 and 33,100 Kbp to 34,943 Kbp on Chr. 20 that were significantly (0.005 < P > 0.0001) associated with resistance to SDS. The QTL fine maps suggested that the two loci on Chr. 18 were three loci (cqRfs1, cqRfs, and cqRfs19). Candidate genes were inferred.  An epistatic interaction was inferred between Chr. 18 and Chr. 20 loci. Therefore, SDS resistance QTL were both complex and interacting.

scholarly journals Multi-trait GWAS using high-density genotypes identifies genes associated with body traits in Nile tilapia

2020 ◽  
Author(s):  
Grazyella Yoshida ◽  
José Manuel Yáñez
Keyword(s):  
Quantitative Trait Loci ◽  
Candidate Genes ◽  
Quantitative Trait ◽  
Nile Tilapia ◽  
Statistical Power ◽  
Association Studies ◽  
Genotype Imputation ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Trait Loci

Abstract Background: Body traits are generally controlled by several genes in vertebrates (i.e. polygenes), which in turn make them difficult to identify through association mapping. Increasing the power of association studies by combining approaches such as genotype imputation and multi-trait analysis improves the ability to detect quantitative trait loci associated with polygenic traits, such as body traits. Results: A multi-trait genome-wide association study (mtGWAS) was performed to identify quantitative trait loci (QTL) and genes associated with body traits in Nile tilapia (Oreochromos niloticus) using genotypes imputed to whole-genome sequence (WGS). To increase the statistical power of mtGWAS for the detection of genetic associations, summary statistics from single-trait genome-wide association studies (stGWAS) for eight different body traits recorded in 1,309 animals were used. The mtGWAS increased the statistical power from the original sample size from 13% to 44%, depending on the trait analyzed. The better resolution of the WGS data combined with the increased power of the mtGWAS approach, allowed the detection of significant markers not previously found in the stGWAS. Some lead single nucleotide polymorphisms (SNPs) were found within important functional candidate genes previously associated with growth-related traits. For instance, we identified SNP within the α1,6-fucosyltransferase (FUT8), solute carrier family 4 member 2 (SLC4A2), A disintegrin and metalloproteinase with thrombospondin motifs 9 (ADAMTS9) and heart development protein with EGF like domains 1 (HEG1) genes, which have been associated with average daily gain in sheep, osteopetrosis in cattle, chest size in goats, and growth and meat quality in sheep, respectively. Conclusions: The high-resolution mtGWAS presented, allowed identification of significant SNPs, linked to strong functional candidate genes, associated with body traits in Nile tilapia. These results provide further insights about the genetic variants and genes underlying body trait variation in cichlid fish with high accuracy and strong statistical support.

scholarly journals Multi-trait GWAS using imputed high-density genotypes from whole-genome sequencing identifies genes associated with body traits in Nile tilapia

2020 ◽  
Author(s):  
Grazyella Yoshida ◽  
José Manuel Yáñez
Keyword(s):  
Quantitative Trait Loci ◽  
Candidate Genes ◽  
Quantitative Trait ◽  
Nile Tilapia ◽  
Statistical Power ◽  
Association Studies ◽  
Genome Wide Association ◽  
Whole Genome ◽  
Genome Wide ◽  
Trait Loci

Abstract Background: Body traits are generally controlled by several genes in vertebrates (i.e. polygenes), which in turn make them difficult to identify through association mapping. Increasing the power of association studies by combining approaches such as genotype imputation and multi-trait analysis improves the ability to detect quantitative trait loci associated with polygenic traits, such as body traits. Results: A multi-trait genome-wide association study (mtGWAS) was performed to identify quantitative trait loci (QTL) and genes associated with body traits in Nile tilapia (Oreochromos niloticus) using genotypes imputed to whole-genome sequence (WGS). To increase the statistical power of mtGWAS for the detection of genetic associations, summary statistics from single-trait genome-wide association studies (stGWAS) for eight different body traits recorded in 1,309 animals were used. The mtGWAS increased the statistical power from the original sample size from 13% to 44%, depending on the trait analyzed. The better resolution of the WGS data combined with the increased power of the mtGWAS approach, allowed the detection of significant markers not previously found in the stGWAS. Some lead single nucleotide polymorphisms (SNPs) were found within important functional candidate genes previously associated with growth-related traits. For instance, we identified SNP within the α1,6-fucosyltransferase (FUT8), solute carrier family 4 member 2 (SLC4A2), A disintegrin and metalloproteinase with thrombospondin motifs 9 (ADAMTS9) and heart development protein with EGF like domains 1 (HEG1) genes, which have been associated with average daily gain in sheep, osteopetrosis in cattle, chest size in goats, and growth and meat quality in sheep, respectively. Conclusions: The high-resolution mtGWAS presented, allowed identification of significant SNPs, linked to strong functional candidate genes, associated with body traits in Nile tilapia. These results provide further insights about the genetic variants and genes underlying body trait variation in cichlid fish with high accuracy and strong statistical support.

scholarly journals Common Expression Quantitative Trait Loci Shared by Histone Genes

2017 ◽  
Vol 2017 ◽  
pp. 1-14
Author(s):  
Hanseol Kim ◽  
Yujin Suh ◽  
Chaeyoung Lee
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Genome Wide Association Study ◽  
Histone Genes ◽  
Expression Quantitative Trait Loci ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
A Genome ◽  
Trait Loci ◽  
Cycle Dependent

A genome-wide association study (GWAS) was conducted to examine expression quantitative trait loci (eQTLs) for histone genes. We examined common eQTLs for multiple histone genes in 373 European lymphoblastoid cell lines (LCLs). A linear regression model was employed to identify single-nucleotide polymorphisms (SNPs) associated with expression of the histone genes, and the number of eQTLs was determined by linkage disequilibrium analysis. Additional associations of the identified eQTLs with other genes were also examined. We identified 31 eQTLs for 29 histone genes through genome-wide analysis using 29 histone genes (P<2.97×10−10). Among them, 12 eQTLs were associated with the expression of multiple histone genes. Transcriptome-wide association analysis using the identified eQTLs showed their associations with additional 80 genes (P<4.75×10−6). In particular, expression of RPPH1, SCARNA2, and SCARNA7 genes was associated with 26, 25, and 23 eQTLs, respectively. This study suggests that histone genes shared 12 common eQTLs that might regulate cell cycle-dependent transcription of histone and other genes. Further investigations are needed to elucidate the transcriptional mechanisms of these genes.

scholarly journals Multi-trait GWAS using imputed high-density genotypes from whole-genome sequencing identifies genes associated with body traits in Nile tilapia

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Grazyella M. Yoshida ◽  
José M. Yáñez
Keyword(s):  
Quantitative Trait Loci ◽  
Candidate Genes ◽  
Quantitative Trait ◽  
Nile Tilapia ◽  
Statistical Power ◽  
Association Studies ◽  
Genome Wide Association ◽  
Whole Genome ◽  
Genome Wide ◽  
Trait Loci

Abstract Background Body traits are generally controlled by several genes in vertebrates (i.e. polygenes), which in turn make them difficult to identify through association mapping. Increasing the power of association studies by combining approaches such as genotype imputation and multi-trait analysis improves the ability to detect quantitative trait loci associated with polygenic traits, such as body traits. Results A multi-trait genome-wide association study (mtGWAS) was performed to identify quantitative trait loci (QTL) and genes associated with body traits in Nile tilapia (Oreochromis niloticus) using genotypes imputed to whole-genome sequences (WGS). To increase the statistical power of mtGWAS for the detection of genetic associations, summary statistics from single-trait genome-wide association studies (stGWAS) for eight different body traits recorded in 1309 animals were used. The mtGWAS increased the statistical power from the original sample size from 13 to 44%, depending on the trait analyzed. The better resolution of the WGS data, combined with the increased power of the mtGWAS approach, allowed the detection of significant markers which were not previously found in the stGWAS. Some of the lead single nucleotide polymorphisms (SNPs) were found within important functional candidate genes previously associated with growth-related traits in other terrestrial species. For instance, we identified SNP within the α1,6-fucosyltransferase (FUT8), solute carrier family 4 member 2 (SLC4A2), A disintegrin and metalloproteinase with thrombospondin motifs 9 (ADAMTS9) and heart development protein with EGF like domains 1 (HEG1) genes, which have been associated with average daily gain in sheep, osteopetrosis in cattle, chest size in goats, and growth and meat quality in sheep, respectively. Conclusions The high-resolution mtGWAS presented here allowed the identification of significant SNPs, linked to strong functional candidate genes, associated with body traits in Nile tilapia. These results provide further insights about the genetic variants and genes underlying body trait variation in cichlid fish with high accuracy and strong statistical support.

scholarly journals Regional Heritability Mapping of Quantitative Trait Loci Controlling Traits Related to Growth and Productivity in Popcorn (Zea mays L.)

Plants ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1845
Author(s):  
Gabrielle Sousa Mafra ◽  
Janeo Eustáquio de Almeida Filho ◽  
Antônio Teixeira do Amaral Junior ◽  
Carlos Maldonado ◽  
Samuel Henrique Kamphorst ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Candidate Genes ◽  
Quantitative Trait ◽  
Recurrent Selection ◽  
Breeding Population ◽  
Genomic Region ◽  
Growth And Yield ◽  
Trait Loci ◽  
Ear Height ◽  
Genomic Regions

The method of regional heritability mapping (RHM) has become an important tool in the identification of quantitative trait loci (QTLs) controlling traits of interest in plants. Here, RHM was first applied in a breeding population of popcorn, to identify the QTLs and candidate genes involved in grain yield, plant height, kernel popping expansion, and first ear height, as well as determining the heritability of each significant genomic region. The study population consisted of 98 S1 families derived from the 9th recurrent selection cycle (C-9) of the open-pollinated variety UENF-14, which were genetically evaluated in two environments (ENV1 and ENV2). Seventeen and five genomic regions were mapped by the RHM method in ENV1 and ENV2, respectively. Subsequent genome-wide analysis based on the reference genome B73 revealed associations with forty-six candidate genes within these genomic regions, some of them are considered to be biologically important due to the proteins that they encode. The results obtained by the RHM method have the potential to contribute to knowledge on the genetic architecture of the growth and yield traits of popcorn, which might be used for marker-assisted selection in breeding programs.

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