1.QTL analysis for some quantitative traits in bread wheat.
Kumar Gupta PUSHPENDRA ; Singh Balyan HARINDRA ; Laxminarayan Kulwal PAWAN ; Kumar NEERAJ ; Kumar AJAY ; Rouf Mir REYAZUL ; Mohan AMITA ; Kumar JITENDRA
Journal of Zhejiang University. Science. B 2007;8(11):807-814
Quantitative trait loci (QTL) analysis was conducted in bread wheat for 14 important traits utilizing data from four different mapping populations involving different approaches of QTL analysis. Analysis for grain protein content (GPC) suggested that the major part of genetic variation for this trait is due to environmental interactions. In contrast, pre-harvest sprouting tolerance (PHST) was controlled mainly by main effect QTL (M-QTL) with very little genetic variation due to environmental interactions; a major QTL for PHST was detected on chromosome arm 3AL. For grain weight, one QTL each was detected on chromosome arms 1AS, 2BS and 7AS. QTL for 4 growth related traits taken together detected by different methods ranged from 37 to 40; nine QTL that were detected by single-locus as well as two-locus analyses were all M-QTL. Similarly, single-locus and two-locus QTL analyses for seven yield and yield contributing traits in two populations respectively allowed detection of 25 and 50 QTL by composite interval mapping (CIM), 16 and 25 QTL by multiple-trait composite interval mapping (MCIM) and 38 and 37 QTL by two-locus analyses. These studies should prove useful in QTL cloning and wheat improvement through marker aided selection.
Bread
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Chromosome Mapping
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Quantitative Trait Loci
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genetics
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Triticum
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genetics
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growth & development
2.QTL analysis of flag leaf in barley (Hordeum vulgare L.) for morphological traits and chlorophyll content.
Da-wei XUE ; Ming-can CHEN ; Mei-xue ZHOU ; Song CHEN ; Ying MAO ; Guo-ping ZHANG
Journal of Zhejiang University. Science. B 2008;9(12):938-943
To understand genetic patterns of the morphological and physiological traits in flag leaf of barley, a double haploid (DH) population derived from the parents Yerong and Franklin was used to determine quantitative trait loci (QTL) controlling length, width, length/width, and chlorophyll content of flag leaves. A total of 9 QTLs showing significantly additive effect were detected in 8 intervals on 5 chromosomes. The variation of individual QTL ranged from 1.9% to 20.2%. For chlorophyll content expressed as SPAD value, 4 QTLs were identified on chromosomes 2H, 3H and 6H; for leaf length and width, 2 QTLs located on chromosomes 5H and 7H, and 2 QTLs located on chromosome 5H were detected; and for length/width, 1 QTL was detected on chromosome 7H. The identification of these QTLs associated with the properties of flag leaf is useful for barley improvement in breeding programs.
Chlorophyll
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analysis
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Chromosome Mapping
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Hordeum
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genetics
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Phenotype
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Plant Leaves
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genetics
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Quantitative Trait Loci
3.Fine mapping of multiple interacting quantitative trait loci using combined linkage disequilibrium and linkage information.
Journal of Zhejiang University. Science. B 2007;8(11):787-791
Quantitative trait loci (QTL) and their additive, dominance and epistatic effects play a critical role in complex trait variation. It is often infeasible to detect multiple interacting QTL due to main effects often being confounded by interaction effects. Positioning interacting QTL within a small region is even more difficult. We present a variance component approach nested in an empirical Bayesian method, which simultaneously takes into account additive, dominance and epistatic effects due to multiple interacting QTL. The covariance structure used in the variance component approach is based on combined linkage disequilibrium and linkage (LDL) information. In a simulation study where there are complex epistatic interactions between QTL, it is possible to simultaneously fine map interacting QTL using the proposed approach. The present method combined with LDL information can efficiently detect QTL and their dominance and epistatic effects, making it possible to simultaneously fine map main and epistatic QTL.
Chromosome Mapping
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Epistasis, Genetic
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Genetic Linkage
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Humans
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Linkage Disequilibrium
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Monte Carlo Method
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Quantitative Trait Loci
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genetics
4.Mapping of QTL associated with rice cooking quality and candidate gene analysis.
Qiaona LE ; Ziwen HUANG ; Ruohui DAI ; Sanfeng LI ; Mengjia LI ; Yuan FANG ; Yuexing WANG ; Yuchun RAO
Chinese Journal of Biotechnology 2024;40(1):122-136
Excavating the quantitative trait locus (QTL) associated with rice cooking quality, analyzing candidate genes, and improving cooking quality-associated traits of rice varieties by genetic breeding can effectively improve the taste of rice. In this study, we used the indica rice HZ, the japonica rice Nekken2 and 120 recombinant inbred lines (RILs) populations constructed from them as experimental materials to measure the gelatinization temperature (GT), gel consistency (GC) and amylose content (AC) of rice at the maturity stage. We combined the high-density genetic map for QTL mapping. A total of 26 QTLs associated with rice cooking quality (1 QTL associated with GT, 13 QTLs associated with GC, and 12 QTLs associated with AC) were detected, among which the highest likelihood of odd (LOD) value reached 30.24. The expression levels of candidate genes in the localization interval were analyzed by quantitative real-time polymerase chain reaction (qRT-PCR), and it was found that the expression levels of six genes were significantly different from that in parents. It was speculated that the high expression of LOC_Os04g20270 and LOC_Os11g40100 may greatly increase the GC of rice, while the high expression of LOC_Os01g04920 and LOC_Os02g17500 and the low expression of LOC_Os03g02650 and LOC_Os05g25840 may reduce the AC. The results lay a molecular foundation for the cultivation of new high-quality rice varieties, and provide important genetic resources for revealing the molecular regulation mechanism of rice cooking quality.
Quantitative Trait Loci
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Oryza/genetics*
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Plant Breeding
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Cooking
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Genetic Association Studies
5.Numerical taxonomy of agronomic trait in cultivated Lonicera japonica.
Shan-Shan ZHANG ; Lu-Qi HUANG ; Yuan YUAN ; Ping CHEN
China Journal of Chinese Materia Medica 2014;39(8):1379-1385
Sixty-three morphological traits from 743 specimens of the 41 taxa within the cultivated Lonicera japonica were observed and measured, such as the height of plants, the length of leaf, the width of leaf, the length of anther, the alabastrum's number of one branch, the color of alabastrum and so on. A numerical taxonomy is presented by using the cluster analysis, principal components analysis (PCA) and factor analysis. Sixteen of 63 characters were screened by means of PCA and used for cluster analysis of 41 taxa with the method of Ward linkage and average euclidean distance. The cluster analysis showed that the 41 taxa could be divided into 5 groups when the Euclidean distance coefficient was 11.84. The factor analysis indicated that the shape of leaf, color of alabastrum, the pilosity and color of twiggery were of significance for the cultivated L. japonica classification. The results of this study will be a base for the core collection and breeding of L. japonica.
Breeding
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China
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Flowers
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chemistry
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classification
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genetics
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Lonicera
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chemistry
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classification
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genetics
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growth & development
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Plant Leaves
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chemistry
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classification
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genetics
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Quantitative Trait Loci
6.Field experiment of F1 generation and superior families selection of Dendrobium officinale.
Xiao-Ling ZHANG ; Jin-Ping SI ; Ling-Shang WU ; Ying-Ying GUO ; Jie YU ; Lin-Hua WANG
China Journal of Chinese Materia Medica 2013;38(22):3861-3865
Based on randomized block design of experiment, agronomic traits and yields of 14 F1 generations of Dendrobium officinale were determined. The results showed that the differences in agronomic traits and yields among families were significant, and the hybrid vigor was obvious. Families of 6b x 2a, 9 x 66 and 78 x 69 were selected with the remarkable superiority of yields, agronomic traits and product customization. Correlation analysis between agronomic traits and yields showed that plant height, stem diameter, leaf number, blade length and blade width were all significantly correlated with biological yields and economic yields. Among which, stem diameter, leaf number and blade length were the most significant, and an optimal linear regression model could be established. When the number of shoots was fewer than 4.5, both biological yields and economic yields increased with the increasing number of shoots, but it could not much affect yields when the number of shoots was larger than 4.5. Shoots number, stem diameter and leaf index were basic stability when compared biennial traits to annual, which could be used for early selection.
Biomass
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Dendrobium
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genetics
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growth & development
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Hybridization, Genetic
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Plant Leaves
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genetics
;
growth & development
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Plant Stems
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genetics
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growth & development
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Quantitative Trait Loci
7.Use of stochastic simulations to investigate the power and design of a whole genome association study using single nucleotide polymorphism arrays in farm animals.
Journal of Zhejiang University. Science. B 2007;8(11):802-806
This paper presents a quick, easy to implement and versatile way of using stochastic simulations to investigate the power and design of using single nucleotide polymorphism (SNP) arrays for genome-wide association studies in farm animals. It illustrates the methodology by discussing a small example where 6 experimental designs are considered to analyse the same resource consisting of 6,006 animals with pedigree and phenotypic records: (1) genotyping the 30 most widely used sires in the population and all of their progeny (515 animals in total), (2) genotyping the 100 most widely used sires in the population and all of their progeny (1,102 animals in total), genotyping respectively (3) 515 and (4) 1,102 animals selected randomly or genotyping respectively (5) 515 and (6) 1,102 animals from the tails of the phenotypic distribution. Given the resource at hand, designs where the extreme animals are genotyped perform the best, followed by designs selecting animals at random. Designs where sires and their progeny are genotyped perform the worst, as even genotyping the 100 most widely used sires and their progeny is not as powerful of genotyping 515 extreme animals.
Animals
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Animals, Domestic
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genetics
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Computer Simulation
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Gene Frequency
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Genotype
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Linkage Disequilibrium
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Polymorphism, Single Nucleotide
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Quantitative Trait Loci
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Stochastic Processes
8.Mapping of quantitative trait loci using the skew-normal distribution.
Elisabete FERNANDES ; António PACHECO ; Carlos PENHA-GONÇALVES
Journal of Zhejiang University. Science. B 2007;8(11):792-801
In standard interval mapping (IM) of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. When this assumption of normality is violated, the most commonly adopted strategy is to use the previous model after data transformation. However, an appropriate transformation may not exist or may be difficult to find. Also this approach can raise interpretation issues. An interesting alternative is to consider a skew-normal mixture model in standard IM, and the resulting method is here denoted as skew-normal IM. This flexible model that includes the usual symmetric normal distribution as a special case is important, allowing continuous variation from normality to non-normality. In this paper we briefly introduce the main peculiarities of the skew-normal distribution. The maximum likelihood estimates of parameters of the skew-normal distribution are obtained by the expectation-maximization (EM) algorithm. The proposed model is illustrated with real data from an intercross experiment that shows a significant departure from the normality assumption. The performance of the skew-normal IM is assessed via stochastic simulation. The results indicate that the skew-normal IM has higher power for QTL detection and better precision of QTL location as compared to standard IM and nonparametric IM.
Animals
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Chromosome Mapping
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methods
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Lod Score
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Mice
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Mice, Inbred BALB C
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Mice, Inbred C57BL
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Normal Distribution
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Quantitative Trait Loci
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genetics
9.Molecular mechanism and genetic basis of geoherbs.
Lu-Qi HUANG ; Lan-Ping GUO ; Juan HU ; Ai-Juan SHAO
China Journal of Chinese Materia Medica 2008;33(20):2303-2308
As products of interaction of time and space, geoherbs, which are essential parts of Chinese Materia Medica, were characterized in different morphology, unique habitat, continuous and changeable sites. The main fields in molecular mechanism of geoherbs focus on: biodiversity and molecular identification, genetic different and evolutionary genetics, geo-variation and environmental adaptation, germplasm and aimed genus choosing, expression and control of functional gene, gene transfer and bio-safety evaluation. The main tasks are to discover the genetic variation at molecular level, ascertain the molecular characteristics of geoherbs and the effect of environment on gene expression of geoherbs, confirm the genetic factors attribute to the forming of geoherbs, and find out the genetic basis of geoherbs at individual level and population level, respectively. This paper pointed out that the essential of geoherbs is continuers quantities variation at population level, geoherb's populations are different in gene frequency with the others'; geohersm are quantitative trait loci (QTL) controlled by multi - gene or combination with multiple-gene and major gene at individual level. It is very important to pay more attention to the scale effect of geoherbs, refer the theories and methods of quantities genetic, and concern more about the interaction of environment and gene in geoherbs' molecular mechanism research.
Drugs, Chinese Herbal
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adverse effects
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metabolism
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pharmacology
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Geography
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Plants, Medicinal
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classification
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genetics
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growth & development
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Quantitative Trait Loci
10.Genetic variability and interrelationships of mainly quantitative traits in Glycyrrhiza uralensis cultivated population.
Fulai YU ; Yuqiang FANG ; Wenquan WANG ; Qiuling WANG ; Fengbo LIU
China Journal of Chinese Materia Medica 2011;36(18):2457-2461
OBJECTIVEThe main aim of the research was to evaluate genetic variability and interrelationships of mainly quantitative traits in 2-year population, and provide a basis for high-yield breeding of Glycyrrhiza uralensis.
METHODFour genotype G. uralensis population were transplanting in four different environment using complete randomized block design with three replication, and the 10 quantitative traits, including plant height (PH), stem diameter (SD), tiller number (TN), taproot length (TRL), root length (RL), root diameter (RD), diameter of 20 cm below the root head (D20), taperingness (TR), lateral root number (LRN) and root fresh weight (RFW) were measured in field.
RESULTThe difference among population for all evaluated traits were significant (P<0.05) through Duncan's multiple range tests, and the coefficient of variation of RFW and LRN were above 25%. The analysis of variance was used to evaluate the traits of four populations across to four different environment Genotype, environment and their interaction effect were significant (P<0.05) or highly significant (P<0.01) for mainly evaluated traits. Simple correlation between traits showed that PH, SD, LRN, RL, RD and D20 had highly significant (P<0.01) and positive correlation with RFW. Results of the path coefficient analyses showed that D20 had the greatest positive direct effect on RFW, followed by the traits of PH and RL.
CONCLUSIONSelection for increased D20, RL and PH would be the best indirect selection traits for increasing root yield. Meanwhile, ample genetic variability exists in the G. uralensis 2-year population, it could be used for breeding improvement of root yield.
Breeding ; methods ; Environment ; Genes, Modifier ; Glycyrrhiza uralensis ; genetics ; growth & development ; metabolism ; Phenotype ; Plant Roots ; genetics ; metabolism ; Plant Stems ; genetics ; metabolism ; Plants, Medicinal ; chemistry ; Quantitative Trait Loci ; genetics ; Quantitative Trait, Heritable