scholarly journals Substitution mapping of the major quantitative trait loci controlling stigma exsertion rate from Oryza glumaepatula

2020 ◽  
Author(s):  
Quanya Tan ◽  
Tuo Zou ◽  
Mingmin Zheng ◽  
Yuerong Ni ◽  
Xin Luan ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Chromosome 1 ◽  
Oryza Species ◽  
Rice Seed ◽  
Substitution Mapping ◽  
Trait Loci ◽  
Stigma Exsertion ◽  
Stigma Exsertion Rate ◽  
Wild Oryza Species

Abstract Background: Stigma exsertion rate (SER) is a key determinant for the outcrossing ability of male sterility lines (MSLs) in hybrid rice seed production. In the process of domestication, the outcrossing ability of cultivated rice varieties decreased, while that of wild Oryza species kept strong. Here, we detected the quantitative trait loci (QTLs) controlling SER using a set of single-segment substitution lines (SSSLs) derived from O. glumaepatula , a wild Oryza species. Results: Seven QTLs for SER were located on 5 chromosomes. qSER-1a and qSER-1b were located on chromosome 1. qSER-3a and qSER-3b were mapped on chromosome 3, and qSER-3b was further located at an estimated interval of 898.8kb by secondary substitution mapping. qSER-5 , qSER-9 and qSER-10 were identified on chromosomes 5, 9 and 10, respectively, and qSER-9 was delimited to an estimated region of 551.9kb by secondary substitution mapping. The additive effects of the 7 QTLs ranged from 10.6% to 14.8%, which were higher than those of most loci for SER reported previously. Conclusions: qSER-1a and qSER-1b are novel loci for SER on chromosome 1. All of the 7 QTLs have major effects on SER. The major QTLs of SER will help to develop MSLs with strong outcrossing ability.

scholarly journals Substitution mapping of the major quantitative trait loci controlling stigma exsertion rate from Oryza glumaepatula

2020 ◽  
Author(s):  
Quanya Tan ◽  
Tuo Zou ◽  
Mingmin Zheng ◽  
Yuerong Ni ◽  
Xin Luan ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Chromosome 1 ◽  
Rice Seed ◽  
Cultivated Rice ◽  
Rice Varieties ◽  
Substitution Mapping ◽  
Trait Loci ◽  
Stigma Exsertion ◽  
Stigma Exsertion Rate

Abstract Background: Stigma exsertion rate (SER) is a key determinant for outcrossing ability of male sterility lines (MSLs) in hybrid rice seed production. Outcrossing ability in cultivated rice varieties has diminished during the process of domestication, while wild Oryza species keep strong outcrossing ability. Here, we detected the quantitative trait loci (QTLs) controlling SER using a set of single-segment substitution lines (SSSLs) derived from O. glumaepatula, a wild Oryza species.Results: Seven QTLs for SER, qSER-1a, qSER-1b, qSER-3a, qSER-3b, qSER-5, qSER-9 and qSER-10, were located on 5 chromosomes. qSER-1a and qSER-1b were located on chromosome 1. qSER-3a and qSER-3b were mapped on chromosome 3, and qSER-3b was further located at an interval of 931.0kb by secondary substitution mapping. qSER-5, qSER-9 and qSER-10 were identified on chromosomes 5, 9 and 10, respectively, and qSER-9 was delimited to a region of 608.2kb by secondary substitution mapping. The additive effects of the 7 QTLs ranged from 10.6% to 14.8%, and the additive contribution variances explained by each of the QTLs were from 36.3% to 50.6%, which were higher than those of most loci for SER reported previously.Conclusions: qSER-1a and qSER-1b were novel loci for SER on chromosome 1. All of the 7 QTLs had major effects on SER. The major QTLs of SER will help to develop MSLs with strong outcrossing ability.

Genetic mapping and validation of quantitative trait loci for stigma exsertion rate in rice

2014 ◽  
Vol 34 (4) ◽  
pp. 2131-2138 ◽  
Author(s):  
Pingbo Li ◽  
Fuchun Feng ◽  
Qinglu Zhang ◽  
Yuan Chao ◽  
Guanjun Gao ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Genetic Mapping ◽  
Quantitative Trait ◽  
Trait Loci ◽  
Stigma Exsertion ◽  
Stigma Exsertion Rate

scholarly journals Genetic mapping of quantitative trait loci for the stigma exsertion rate in rice (Oryza sativa L.)

2017 ◽  
Vol 16 (7) ◽  
pp. 1423-1431 ◽  
Author(s):  
Md Habibur Rahman ◽  
Ying-xin ZHANG ◽  
Lian-ping SUN ◽  
Ke-qin ZHANG ◽  
Md Sazzadur Rahman ◽  
...  
Keyword(s):  
Oryza Sativa ◽  
Quantitative Trait Loci ◽  
Genetic Mapping ◽  
Quantitative Trait ◽  
Oryza Sativa L ◽  
Trait Loci ◽  
Stigma Exsertion ◽  
Stigma Exsertion Rate

scholarly journals Identification of Quantitative Trait Loci Influencing Traits Related to Energy Balance in Selection and Inbred Lines of Mice

Genetics ◽  
1999 ◽  
Vol 152 (2) ◽  
pp. 699-711 ◽  
Author(s):  
D E Moody ◽  
D Pomp ◽  
M K Nielsen ◽  
L D Van Vleck
Keyword(s):  
Quantitative Trait Loci ◽  
Energy Balance ◽  
Heat Loss ◽  
Quantitative Trait ◽  
Subcutaneous Fat ◽  
High Heat ◽  
Chromosome 1 ◽  
Direct Calorimetry ◽  
Resource Population ◽  
Trait Loci

Abstract Energy balance is a complex trait with relevance to the study of human obesity and maintenance energy requirements of livestock. The objective of this study was to identify, using unique mouse models, quantitative trait loci (QTL) influencing traits that contribute to variation in energy balance. Two F2 resource populations were created from lines of mice differing in heat loss measured by direct calorimetry as an indicator of energy expenditure. The HB F2 resource population originated from a cross between a noninbred line selected for high heat loss and an inbred line with low heat loss. Evidence for significant QTL influencing heat loss was found on chromosomes 1, 2, 3, and 7. Significant QTL influencing body weight and percentage gonadal fat, brown fat, liver, and heart were also identified. The LH F2 resource population originated from noninbred lines of mice that had undergone divergent selection for heat loss. Chromosomes 1 and 3 were evaluated. The QTL for heat loss identified on chromosome 1 in the HB population was confirmed in the LH population, although the effect was smaller. The presence of a QTL influencing 6-wk weight was also confirmed. Suggestive evidence for additional QTL influencing heat loss, percentage subcutaneous fat, and percentage heart was found for chromosome 1.

Detection of quantitative trait loci for locomotion and osteochondrosis-related traits in Large White ✕ Meishan pigs

2003 ◽  
Vol 76 (2) ◽  
pp. 155-165 ◽  
Author(s):  
G.J. Lee ◽  
A.L. Archibald ◽  
G.B. Garth ◽  
A.S. Law ◽  
D. Nicholson ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Chromosome 1 ◽  
Chromosome 15 ◽  
Large White ◽  
Chromosome 13 ◽  
Genome Wide ◽  
A Genome ◽  
Trait Loci ◽  
Gait Score

AbstractData from the F2 generation of a Large White (LW) ✕ Meishan (MS) crossbred population were analysed to detect quantitative trait loci (QTL) for leg and gait scores, osteochondrosis and physis scores. Legs, feet and gait score were assessed in 308 F2 animals at 85 ( + 5) kg and osteochondrosis and physis scores were recorded for the right foreleg after slaughter. A genome scan was performed using 111 genetic markers chosen to span the genome that were genotyped on the F2 animals and their F1 parents and purebred grandparents. A QTL on chromosome 1 affecting gait score was significant at the genome-wide significance level. Additional QTL significant at the chromosome-wide 5% threshold level (approx. equivalent to the genome-wide suggestive level) were detected on chromosome 1 for front feet and back legs scores, on chromosome 13 for front legs and front feet scores, on chromosome 14 for front legs, front feet and back legs scores and on chromosome 15 for back feet score. None of the QTL for osteochondrosis score exceeded the chromosome-wide suggestive level, but one chromosome-wide QTL for physis score was found on chromosome 7. On chromosome 1, gait and front feet scores mapped to the middle of the chromosome and showed additive effects in favour of the LW alleles and no dominance effects. The QTL for back legs score mapped to the distal end of the chromosome and showed a dominant effect and no additive effect. On chromosomes 14 and 15, the LW allele was again superior to the MS allele. On chromosome 13, there were both additive and dominance effects in favour of the MS allele. The MS alleles on chromosome 13 may have potential for introgression into a commercial LW population. The other putative QTLs identified may have value in marker-assisted selection in LW or MS-synthetic populations.

Quantitative trait loci for insulin-like growth factor I, leptin, thyroxine, and corticosterone in genetically heterogeneous mice

2003 ◽  
Vol 15 (1) ◽  
pp. 44-51 ◽  
Author(s):  
James M. Harper ◽  
Andrzej T. Galecki ◽  
David T. Burke ◽  
Stephen L. Pinkosky ◽  
Richard A. Miller
Keyword(s):  
Quantitative Trait Loci ◽  
Growth Factor ◽  
Quantitative Trait ◽  
Chromosome 1 ◽  
Insulin Like Growth Factor ◽  
Factor I ◽  
Genotype Information ◽  
Igf I ◽  
Trait Loci ◽  
Growth Factor I

Genotype information was collected at 87 loci in a group of 1,108 UM-HET3 mice bred as the progeny of [BALB/cJ × C57BL/6J]F1 mothers and [C3H/HeJ × DBA/2J]F1 fathers, for which thyroxine (T4), insulin-like growth factor I (IGF-I), and leptin levels had been measured at 4 and 15 mo of age. The data provided significant evidence for quantitative trait loci (QTL) modulating IGF-I levels on chromosomes 1, 3, 8, 10, and 17; for loci affecting T4 on chromosomes 4, 15, and 17; and for leptin on chromosome 3. Fecal levels of corticosterone at 17 mo of age were influenced by a QTL on chromosome 1. Nine other gene/hormone associations reached a nominal P < 0.01, providing suggestive but not statistical evidence for additional QTL. QTL with an influence on a given hormone were in nearly all cases additive, with little or no evidence for epistasis. Of the 12 strongest QTL, 5 had effects that were age dependent, having more effect in 15-mo-old than in 4-mo-old mice in all but one case; the other QTL had effects that were apparently age-independent. These results show that the genetic controls over late-life hormone levels are complex and dependent on effects of genes that act both early and late in the life course.

In silico mapping of quantitative trait loci (QTL) regulating the milk ionome in mice identifies a milk iron locus on chromosome 1

2018 ◽  
Vol 29 (9-10) ◽  
pp. 632-655 ◽  
Author(s):  
Darryl L. Hadsell ◽  
Louise A. Hadsell ◽  
Monique Rijnkels ◽  
Yareli Carcamo-Bahena ◽  
Jerry Wei ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
In Silico ◽  
Chromosome 1 ◽  
In Silico Mapping ◽  
Trait Loci

scholarly journals Genetic mapping of two blood pressure quantitative trait loci on rat chromosome 1.

1996 ◽  
Vol 97 (3) ◽  
pp. 777-788 ◽  
Author(s):  
L Gu ◽  
H Dene ◽  
A Y Deng ◽  
B Hoebee ◽  
M T Bihoreau ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Quantitative Trait Loci ◽  
Genetic Mapping ◽  
Quantitative Trait ◽  
Chromosome 1 ◽  
Trait Loci

scholarly journals Genetic Mapping Identifies Consistent Quantitative Trait Loci for Yield Traits of Rice under Greenhouse Drought Conditions

Genes ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 62
Author(s):  
Niranjan Baisakh ◽  
Jonalyn Yabes ◽  
Andres Gutierrez ◽  
Venkata Mangu ◽  
Peiyong Ma ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Grain Yield ◽  
Drought Resistance ◽  
Quantitative Trait ◽  
Chromosome 1 ◽  
Phenotypic Variance ◽  
Yield Traits ◽  
Rice Varieties ◽  
Drought Tolerant ◽  
Trait Loci

Improving drought resistance in crops is imperative under the prevailing erratic rainfall patterns. Drought affects the growth and yield of most modern rice varieties. Recent breeding efforts aim to incorporate drought resistance traits in rice varieties that can be suitable under alternative irrigation schemes, such as in a (semi)aerobic system, as row (furrow-irrigated) rice. The identification of quantitative trait loci (QTLs) controlling grain yield, the most important trait with high selection efficiency, can lead to the identification of markers to facilitate marker-assisted breeding of drought-resistant rice. Here, we report grain yield QTLs under greenhouse drought using an F2:3 population derived from Cocodrie (drought sensitive) × Nagina 22 (N22) (drought tolerant). Eight QTLs were identified for yield traits under drought. Grain yield QTL under drought on chromosome 1 (phenotypic variance explained (PVE) = 11.15%) co-localized with the only QTL for panicle number (PVE = 37.7%). The drought-tolerant parent N22 contributed the favorable alleles for all QTLs except qGN3.2 and qGN5.1 for grain number per panicle. Stress-responsive transcription factors, such as ethylene response factor, WD40 domain protein, zinc finger protein, and genes involved in lipid/sugar metabolism were linked to the QTLs, suggesting their possible role in drought tolerance mechanism of N22 in the background of Cocodrie, contributing to higher yield under drought.

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