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 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 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 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.

Comparative analysis of QTLs affecting plant height and flowering among closely-related diploid and polyploid genomes

Genome ◽  
2002 ◽  
Vol 45 (5) ◽  
pp. 794-803 ◽  
Author(s):  
Ray Ming ◽  
Terrye A. Del Monte ◽  
Eduardo Hernandez ◽  
Paul H Moore ◽  
James E Irvine ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Plant Height ◽  
Dna Markers ◽  
Quantitative Trait ◽  
Saccharum Officinarum ◽  
Genetic Maps ◽  
Interspecific Crosses ◽  
Number Of Genes ◽  
Trait Loci ◽  
Genomic Regions

Quantitative trait loci (QTLs) affecting plant height and flowering were studied in the two Saccharum species from which modern sugarcane cultivars are derived. Two segregating populations derived from interspecific crosses between Saccharum officinarum and Saccharum spontaneum were genotyped with 735 DNA markers. Among the 65 significant associations found between these two traits and DNA markers, 35 of the loci were linked to sugarcane genetic maps and 30 were unlinked DNA markers. Twenty-one of the 35 mapped QTLs were clustered in eight genomic regions of six sugarcane homologous groups. Some of these could be divergent alleles at homologous loci, making the actual number of genes implicated in these traits much less than 35. Four QTL clusters controlling plant height in sugarcane corresponded closely to four of the six plant-height QTLs previously mapped in sorghum. One QTL controlling flowering in sugarcane corresponded to one of three flowering QTLs mapped in sorghum. The correspondence in locations of QTLs affecting plant height and flowering in sugarcane and sorghum reinforce the notion that the simple sorghum genome is a valuable "template" for molecular dissection of the much more complex sugarcane genome.Key words: DNA markers, genetic map, quantitative trait loci, Saccharum.

scholarly journals Identification of quantitative trait loci governing early germination and seedling vigor traits related to weed competitive ability in rice

Euphytica ◽  
2020 ◽  
Vol 216 (10) ◽  
Author(s):  
Niña Gracel B. Dimaano ◽  
Jauhar Ali ◽  
Anumalla Mahender ◽  
Pompe C. Sta. Cruz ◽  
Aurora M. Baltazar ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Competitive Ability ◽  
Snp Markers ◽  
Limiting Factor ◽  
Seedling Vigor ◽  
Backcross Population ◽  
Trait Loci ◽  
Early Seedling ◽  
Genomic Regions

Abstract Weed competitive ability (WCA) is vital for the improvement of grain yield under direct-seeded and aerobic rice ecosystems where weeds are a major limiting factor. Early seed germination (ESG) and early seedling vigor (ESV) are the crucial traits for WCA. This study attempted to map the quantitative trait loci (QTLs) and hotspot regions governing ESG and ESV traits. A total of 167 BC1F5 selective introgression lines developed from an early backcross population involving Weed Tolerant Rice 1 (WTR-1) as the recipient parent and Y-134 as the donor parent were phenotyped for ESG and ESV traits. Analysis of variance revealed significant differences in ESG-related traits except for root length and in ESV-related traits except for plant height at 7 days after sowing. A total of 677-high quality single nucleotide polymorphism (SNP) markers were used to analyze the marker-trait association from a 6 K SNP genotyping array. Forty-three QTLs were identified on all chromosomes, except on chromosomes 4 and 8. Thirty QTLs were contributed by a desirable allele from Y-134, whereas 13 QTLs were from WTR-1. Twenty-eight of the identified genetic loci associated with ESG and ESV traits were novel. Two QTL hotspot regions were mapped on chromosomes 11 and 12. The genomic regions of QTL hotspots were fine-tuned and a total of 13 putative candidate genes were discovered on chromosomes 11 and 12 collectively. The mapped QTLs will be useful in advancing the marker aided-selection schemes and breeding programs for the development of rice cultivars with WCA traits.

scholarly journals A Genome-Wide Association Study Identifies Protein Quantitative Trait Loci (pQTLs)

PLoS Genetics ◽  
2008 ◽  
Vol 4 (5) ◽  
pp. e1000072 ◽  
Author(s):  
David Melzer ◽  
John R. B. Perry ◽  
Dena Hernandez ◽  
Anna-Maria Corsi ◽  
Kara Stevens ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Association Study ◽  
Quantitative Trait ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome ◽  
Trait Loci

scholarly journals Bayesian Model Selection for Genome-Wide Epistatic Quantitative Trait Loci Analysis

Genetics ◽  
2005 ◽  
Vol 170 (3) ◽  
pp. 1333-1344 ◽  
Author(s):  
Nengjun Yi ◽  
Brian S. Yandell ◽  
Gary A. Churchill ◽  
David B. Allison ◽  
Eugene J. Eisen ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Model Selection ◽  
Quantitative Trait ◽  
Bayesian Model ◽  
Bayesian Model Selection ◽  
Genome Wide ◽  
Trait Loci ◽  
Selection For

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.

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