Mapping of Main-Effect and Epistatic Quantitative Trait Loci for Internal Egg Traits in an F2 Resource Population of Chickens

2014 ◽  
Author(s):  
Tatsuhiko Goto ◽  
Akira Ishikawa ◽  
Naoki Goto ◽  
Masahide Nishibori ◽  
Tetsuya Umino ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Resource Population ◽  
Main Effect ◽  
Trait Loci ◽  
Egg Traits

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.

Quantitative trait loci analysis for growth and carcass traits in a Meishan × Duroc F2 resource population

2003 ◽  
Vol 81 (12) ◽  
pp. 2938-2949 ◽  
Author(s):  
S. Sato ◽  
Y. Oyamada ◽  
K. Atsuji ◽  
T. Nade ◽  
Shin-ichi Sato ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Carcass Traits ◽  
Resource Population ◽  
Trait Loci

Mapping of quantitative trait loci for mycoplasma and tetanus antibodies and interferon-gamma in a porcine F2 Duroc × Pietrain resource population

2010 ◽  
Vol 21 (7-8) ◽  
pp. 409-418 ◽  
Author(s):  
Muhammad Jasim Uddin ◽  
Christine Grosse-Brinkhaus ◽  
Mehmet Ulas Cinar ◽  
Elisabeth Jonas ◽  
Dawit Tesfaye ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Interferon Gamma ◽  
Quantitative Trait ◽  
Resource Population ◽  
Trait Loci ◽  
Tetanus Antibodies

Quantitative trait loci for porcine baseline erythroid traits at three growth ages in a White Duroc × Erhualian F2 resource population

2008 ◽  
Vol 19 (9) ◽  
pp. 640-646 ◽  
Author(s):  
Zhengzhi Zou ◽  
Jun Ren ◽  
Xueming Yan ◽  
Xiang Huang ◽  
Shujin Yang ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Resource Population ◽  
Trait Loci

Molecular mapping of quantitative trait loci for kernel morphology traits in a non-1BL.1RS×1BL.1RS wheat cross

2011 ◽  
Vol 62 (8) ◽  
pp. 625 ◽  
Author(s):  
Yonggui Xiao ◽  
Shengmei He ◽  
Jun Yan ◽  
Yong Zhang ◽  
Yelun Zhang ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Grain Yield ◽  
Quantitative Trait ◽  
Molecular Mapping ◽  
Length Ratio ◽  
Phenotypic Variance ◽  
Kernel Length ◽  
Main Effect ◽  
Trait Loci ◽  
Kernel Morphology

The improvement of kernel morphology traits is an important goal in common wheat (Triticum aestivum L.) breeding programs because of their close relationship with grain yield and milling quality. The aim of this study was to map quantitative trait loci (QTL) for kernel morphology traits using 240 recombinant inbred lines derived from a cross between the non-1BL.1RS translocation cv. PH 82-2 and the 1BL.1RS translocation cv. Neixiang 188, grown in six environments in China. Inclusive composite interval mapping identified 71 main-effect QTL on 16 chromosomes for seven kernel morphology traits measured by digital imaging, viz. kernel length, width, perimeter, area, shape factor, factor form-density and width/length ratio. Each of these loci explained from 2.6 to 28.2% of the phenotypic variation. Eight QTL clusters conferring the largest effects on kernel weight and kernel morphology traits were detected on chromosomes 1BL.1RS (2), 2A, 4A, 4B, 6B, 6D and 7A. Fourteen epistatic QTL were identified for all kernel morphology traits except kernel width/length ratio, involving 24 main-effect QTL distributed on 13 chromosomes, and explaining 2.5–8.3% of the phenotypic variance. Five loci, viz. Sec-1 on 1BL.1RS, Glu-B1 on 1BL, Xcfe53 on 2A, Xwmc238 on 4B, and Xbarc174 on 7A, were detected consistently across environments, and their linked DNA markers may be used for marker-assisted selection in breeding for improved wheat kernel traits and grain yield.

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 Overdominance and Epistasis Are Important for the Genetic Basis of Heterosis in Brassica rapa

HortScience ◽  
2007 ◽  
Vol 42 (5) ◽  
pp. 1207-1211 ◽  
Author(s):  
De-Kun Dong ◽  
Jia-Shu Cao ◽  
Kai Shi ◽  
Le-Cheng Liu
Keyword(s):  
Quantitative Trait Loci ◽  
Brassica Rapa ◽  
Quantitative Trait ◽  
Genetic Basis ◽  
Phenotypic Variance ◽  
Epistasis Analysis ◽  
Main Effect ◽  
Trait Loci ◽  
Component Traits ◽  
The Cross

To investigate the genetic basis of heterosis in Brassica rapa, an F2 population was produced from the cross of B. rapa L. subsp. chinensis (L.) Hanelt and B. rapa L. subsp. rapifera Metzg. Trait performances of the F1 hybrid showed evident mid parent heterosis, which varied from 18.55% to 101.62% for the 11 traits investigated. A total of 23 main effect quantitative trait loci (QTLs) were detected for biomass and its component traits, which could explain 4.38% to 47.80% of the phenotypic variance, respectively. Sixty-five percent of these QTLs showed obvious overdominance. Epistasis analysis detected 444 two-locus interactions for the 11 traits at the threshold of P < 0.005. Some of them remained significant when more stringent threshold were set. These results suggested that overdominance and epistasis might play an important role as the genetic basis of heterosis in B. rapa.

Sign in / Sign up

Export Citation Format

Share Document