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 Identification of main-effect quantitative trait loci (QTLs) for low-temperature stress tolerance germination- and early seedling vigor-related traits in rice (Oryza sativa L.)

2020 ◽  
Vol 40 (1) ◽  
Author(s):  
S. Najeeb ◽  
J. Ali ◽  
A. Mahender ◽  
Y.L. Pang ◽  
J. Zilhas ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Low Temperature ◽  
Quantitative Trait ◽  
Root Length ◽  
Stress Index ◽  
Multiple Traits ◽  
Main Effect ◽  
Trait Loci ◽  
Early Seedling ◽  
Genomic Regions

AbstractAn attempt was made in the current study to identify the main-effect and co-localized quantitative trait loci (QTLs) for germination and early seedling growth traits under low-temperature stress (LTS) conditions in rice. The plant material used in this study was an early backcross population of 230 introgression lines (ILs) in BCIF7 generation derived from the Weed Tolerant Rice-1 (WTR-1) (as the recipient) and Haoannong (HNG) (as the donor). Genetic analyses of LTS tolerance revealed a total of 27 main-effect quantitative trait loci (M-QTLs) mapped on 12 chromosomes. These QTLs explained more than 10% of phenotypic variance (PV), and average PV of 12.71% while employing 704 high-quality SNP markers. Of these 27 QTLs distributed on 12 chromosomes, 11 were associated with low-temperature germination (LTG), nine with low-temperature germination stress index (LTGS), five with root length stress index (RLSI), and two with biomass stress index (BMSI) QTLs, shoot length stress index (SLSI) and root length stress index (RLSI), seven with seed vigor index (SVI), and single QTL with root length (RL). Among them, five significant major QTLs (qLTG(I)1, qLTGS(I)1–2, qLTG(I)5, qLTGS(I)5, and qLTG(I)7) mapped on chromosomes 1, 5, and 7 were associated with LTG and LTGS traits and the PV explained ranged from 16 to 23.3%. The genomic regions of these QTLs were co-localized with two to six QTLs. Most of the QTLs were growth stage-specific and found to harbor QTLs governing multiple traits. Eight chromosomes had more than four QTLs and were clustered together and designated as promising LTS tolerance QTLs (qLTTs), as qLTT1, qLTT2, qLTT3, qLTT5, qLTT6, qLTT8, qLTT9, and qLTT11. A total of 16 putative candidate genes were identified in the major M-QTLs and co-localized QTL regions distributed on different chromosomes. Overall, these significant genomic regions of M-QTLs are responsible for multiple traits and this suggested that these could serve as the best predictors of LTS tolerance at germination and early seedling growth stages. Furthermore, it is necessary to fine-map these regions and to find functional markers for marker-assisted selection in rice breeding programs for cold tolerance.

scholarly journals Identification of Quantitative Trait Loci Associated with Nutrient Use Efficiency Traits, Using SNP Markers in an Early Backcross Population of Rice (Oryza sativa L.)

2019 ◽  
Vol 20 (4) ◽  
pp. 900 ◽  
Author(s):  
Zilhas Jewel ◽  
Jauhar Ali ◽  
Anumalla Mahender ◽  
Jose Hernandez ◽  
Yunlong Pang ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Grain Yield ◽  
Quantitative Trait ◽  
Nutrient Use Efficiency ◽  
Snp Markers ◽  
Rice Cultivars ◽  
Backcross Population ◽  
Nutrient Use ◽  
Trait Loci ◽  
Use Efficiency

The development of rice cultivars with nutrient use efficiency (NuUE) is highly crucial for sustaining global rice production in Asia and Africa. However, this requires a better understanding of the genetics of NuUE-related traits and their relationship to grain yield. In this study, simultaneous efforts were made to develop nutrient use efficient rice cultivars and to map quantitative trait loci (QTLs) governing NuUE-related traits in rice. A total of 230 BC1F5 introgression lines (ILs) were developed from a single early backcross population involving Weed Tolerant Rice 1, as the recipient parent, and Hao-an-nong, as the donor parent. The ILs were cultivated in field conditions with a different combination of fertilizer schedule under six nutrient conditions: minus nitrogen (–N), minus phosphorus (–P), (–NP), minus nitrogen phosphorus and potassium (–NPK), 75% of recommended nitrogen (75N), and NPK. Analysis of variance revealed that significant differences (p < 0.01) were noted among ILs and treatments for all traits. A high-density linkage map was constructed by using 704 high-quality single nucleotide polymorphism (SNP) markers. A total of 49 main-effect QTLs were identified on all chromosomes, except on chromosome 7, 11 and 12, which are showing 20.25% to 34.68% of phenotypic variation. With further analysis of these QTLs, we refined them to four top hotspot QTLs (QTL harbor-I to IV) located on chromosomes 3, 5, 9, and 11. However, we identified four novel putative QTLs for agronomic efficiency (AE) and 22 QTLs for partial factor productivity (PFP) under –P and 75N conditions. These interval regions of QTLs, several transporters and genes are located that were involved in nutrient uptake from soil to plant organs and tolerance to biotic and abiotic stresses. Further, the validation of these potential QTLs, genes may provide remarkable value for marker-aided selection and pyramiding of multiple QTLs, which would provide supporting evidence for the enhancement of grain yield and cloning of NuUE tolerance-responsive genes in rice.

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 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.

Mapping of quantitative trait loci controlling seedling vigor in rice (Oryza sativa L.) under submergence

Euphytica ◽  
2012 ◽  
Vol 192 (1) ◽  
pp. 63-75 ◽  
Author(s):  
O. E. Manangkil ◽  
H. T. T. Vu ◽  
N. Mori ◽  
S. Yoshida ◽  
C. Nakamura
Keyword(s):  
Oryza Sativa ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Oryza Sativa L ◽  
Seedling Vigor ◽  
Trait Loci

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.

Sign in / Sign up

Export Citation Format

Share Document