MAGIC or multiparent advanced generation inter-crosses is an experimental method that increases the precision with which genetic markers are linked to quantitative trait loci (QTL). This method was first introduced by (Mott et al., 2000) in animals as an extension of the advanced intercrossing (AIC) approach suggested by (Darvasi and Soller , 1995)for fine mapping multiple QTLs for multiple traits. Advanced Intercrossed Lines (AILs) are generated by randomly and sequentially intercrossing a population initially originating from a cross between two inbred lines.
MAGIC involves multiple parents, called founder lines, rather than bi-parental control. AILs increase the recombination events in small chromosomal regions for the purpose of fine mapping. These lines are then cycled through multiple generations of outcrossing. Each generation of random mating reduces the extent of linkage disequilibrium (LD), allowing the QTL to be mapped more accurately.
Multiple inbred founder lines are inter-mated for several generations prior to creating inbred lines, resulting in a diverse population whose genomes are fine scale mosaics of contributions from all founders.
Association mapping, also known as "linkage disequilibrium mapping", is a method of mapping quantitative trait loci (QTLs) that takes advantage of linkage disequilibrium to link phenotypes to genotypes.Varioius strategey involved in association mapping is discussed in this presentation
Multiple inbred founder lines are inter-mated for several generations prior to creating inbred lines, resulting in a diverse population whose genomes are fine scale mosaics of contributions from all founders.
Association mapping, also known as "linkage disequilibrium mapping", is a method of mapping quantitative trait loci (QTLs) that takes advantage of linkage disequilibrium to link phenotypes to genotypes.Varioius strategey involved in association mapping is discussed in this presentation
Presentation delivered by Dr. Jesse Poland (Kansas State University, USA) at Borlaug Summit on Wheat for Food Security. March 25 - 28, 2014, Ciudad Obregon, Mexico.
http://www.borlaug100.org
Heterotic group “is a group of related or unrelated genotypes from the same or different populations, which display similar combining ability and heterotic response when crossed with genotypes from other genetically distinct germplasm groups.”
Introduction:
Proposed by Meuwissen et al. (2001)
GS is a specialized form of MAS, in which information from genotype data on marker alleles covering the entire genome forms the basis of selection.
The effects associated with all the marker loci, irrespective of whether the effects are significant or not, covering the entire genome are estimated.
The marker effect estimates are used to calculate the genomic estimated breeding values (GEBVs) of different individuals/lines, which form the basis of selection.
Why to go for genomic selection:
Marker-assisted selection (MAS) is well-suited for handling oligogenes and quantitative trait loci (QTLs) with large effects but not for minor QTLs.
MARS attempts to take into account small effect QTLs by combining trait phenotype data with marker genotype data into a combined selection index.
Based on markers showing significant association with the trait(s) and for this reason has been criticized as inefficient
The genomic selection (GS) scheme was to rectify the deficiency of MAS and MARS schemes. The GS scheme utilizes information from genome-wide marker data whether or not their associations with the concerned trait(s) are significant.
GEBV: GenomicEstimated Breeding Values-
The sum total of effects associated with all the marker alleles present in the individual and included in the GS model applied to the population under selection
Calculated on a single individual basis
Gene-assisted genomic selection:
A GS model that uses information about prior known QTLs, the targeted QTLs were accumulated in much higher frequencies than when the standard ridge regression was used
The sum total of effects associated with all the marker alleles present in the individual and included in the GS model applied to the population under selection
Calculated on a single individual basis
Population used:
Training population: used for training of the GS model and for obtaining estimates of the marker-associated effects needed for estimation of GEBVs of individuals/lines in the breeding population.
Breeding population: the population subjected to GS for achieving the desired improvement and isolation of superior lines for use as new varieties/parents of new improved hybrids.
Training population-
large enough: must be representative of the breeding population: max. trait variance with marker : by cluster analysis
should have either equal or comparable LD, LD decay rates with breeding populations
Updated by including individuals/lines from the breeding population
Training more than one generation
Low colinearity between markers is needed since high colinearity tends to reduce prediction accuracy of certain GS models. (colinearity disturbed by recombination)
Association genetics‟ or ‟association studies,” or ‟linkage disequilibrium mapping”.
Tool to resolve complex trait variation down to the sequence level by exploiting historical and evolutionary recombination events at the population level.
Natural population surveyed to determine MTA using LD.
It comprises on mating designs used in plant breeding programs. 6 basic mating designs are briefly explained in it with their requirements as well limiting factors...
Quantitative trait loci (QTL) analysis and its applications in plant breedingPGS
Abstract
Many agriculturally important traits such as grain yield, protein content and relative disease resistance are controlled by many genes and are known as quantitative traits (also polygenic or complex traits). A quantitative trait depends on the cumulative actions of many genes and the environment. The genomic regions that contain genes associated with a quantitative trait are known as quantitative trait loci (QTLs). Thus, a QTL could be defined as a genomic region responsible for a part of the observed phenotypic variation for a quantitative trait. A QTL can be a single gene or a cluster of linked genes that affect the trait. The effects of individual QTLs may differ from each other and change from environment to environment. The genetics of a quantitative trait can often be deduced from the statistical analysis of several segregating populations. Recently, by using molecular markers, it is feasible to analyze quantitative traits and identify individual QTLs or genes controlling the traits of interest in breeding programs.
Development of First Multiparent Advanced Generation Inter-cross (MAGIC) Popu...ICRISAT
Pigeonpea is the sixth most important legume crop in the world and it is a rich source of proteins. Conventional methods of breeding varieties with higher yield and inbuilt resistance are time consuming and cumbersome process. Molecular breeding with the help of genome wide sequence information will be helpful in achieving the goal in less time with high precision.
24 June 2015
Presentation delivered by Dr. Jesse Poland (Kansas State University, USA) at Borlaug Summit on Wheat for Food Security. March 25 - 28, 2014, Ciudad Obregon, Mexico.
http://www.borlaug100.org
Heterotic group “is a group of related or unrelated genotypes from the same or different populations, which display similar combining ability and heterotic response when crossed with genotypes from other genetically distinct germplasm groups.”
Introduction:
Proposed by Meuwissen et al. (2001)
GS is a specialized form of MAS, in which information from genotype data on marker alleles covering the entire genome forms the basis of selection.
The effects associated with all the marker loci, irrespective of whether the effects are significant or not, covering the entire genome are estimated.
The marker effect estimates are used to calculate the genomic estimated breeding values (GEBVs) of different individuals/lines, which form the basis of selection.
Why to go for genomic selection:
Marker-assisted selection (MAS) is well-suited for handling oligogenes and quantitative trait loci (QTLs) with large effects but not for minor QTLs.
MARS attempts to take into account small effect QTLs by combining trait phenotype data with marker genotype data into a combined selection index.
Based on markers showing significant association with the trait(s) and for this reason has been criticized as inefficient
The genomic selection (GS) scheme was to rectify the deficiency of MAS and MARS schemes. The GS scheme utilizes information from genome-wide marker data whether or not their associations with the concerned trait(s) are significant.
GEBV: GenomicEstimated Breeding Values-
The sum total of effects associated with all the marker alleles present in the individual and included in the GS model applied to the population under selection
Calculated on a single individual basis
Gene-assisted genomic selection:
A GS model that uses information about prior known QTLs, the targeted QTLs were accumulated in much higher frequencies than when the standard ridge regression was used
The sum total of effects associated with all the marker alleles present in the individual and included in the GS model applied to the population under selection
Calculated on a single individual basis
Population used:
Training population: used for training of the GS model and for obtaining estimates of the marker-associated effects needed for estimation of GEBVs of individuals/lines in the breeding population.
Breeding population: the population subjected to GS for achieving the desired improvement and isolation of superior lines for use as new varieties/parents of new improved hybrids.
Training population-
large enough: must be representative of the breeding population: max. trait variance with marker : by cluster analysis
should have either equal or comparable LD, LD decay rates with breeding populations
Updated by including individuals/lines from the breeding population
Training more than one generation
Low colinearity between markers is needed since high colinearity tends to reduce prediction accuracy of certain GS models. (colinearity disturbed by recombination)
Association genetics‟ or ‟association studies,” or ‟linkage disequilibrium mapping”.
Tool to resolve complex trait variation down to the sequence level by exploiting historical and evolutionary recombination events at the population level.
Natural population surveyed to determine MTA using LD.
It comprises on mating designs used in plant breeding programs. 6 basic mating designs are briefly explained in it with their requirements as well limiting factors...
Quantitative trait loci (QTL) analysis and its applications in plant breedingPGS
Abstract
Many agriculturally important traits such as grain yield, protein content and relative disease resistance are controlled by many genes and are known as quantitative traits (also polygenic or complex traits). A quantitative trait depends on the cumulative actions of many genes and the environment. The genomic regions that contain genes associated with a quantitative trait are known as quantitative trait loci (QTLs). Thus, a QTL could be defined as a genomic region responsible for a part of the observed phenotypic variation for a quantitative trait. A QTL can be a single gene or a cluster of linked genes that affect the trait. The effects of individual QTLs may differ from each other and change from environment to environment. The genetics of a quantitative trait can often be deduced from the statistical analysis of several segregating populations. Recently, by using molecular markers, it is feasible to analyze quantitative traits and identify individual QTLs or genes controlling the traits of interest in breeding programs.
Development of First Multiparent Advanced Generation Inter-cross (MAGIC) Popu...ICRISAT
Pigeonpea is the sixth most important legume crop in the world and it is a rich source of proteins. Conventional methods of breeding varieties with higher yield and inbuilt resistance are time consuming and cumbersome process. Molecular breeding with the help of genome wide sequence information will be helpful in achieving the goal in less time with high precision.
24 June 2015
Introduction to association mapping and tutorial using tasselAwais Khan
This presentation introduces association mapping/linkage disequilibrium mapping and also includes a tutorial showing association mapping analysis using TASSEL software.
Learn all about the latest developments in the
CGI (Computer Generated Imaging) and see how 3D documentation helps to
speed up visualisation processes and improves quality of animated imaging.
3D laser scanners from FARO use laser technology to deliver highly detailed 3D Documentation. 3D images of complex environments and geometries can be generated in mere minutes. Use them for accident reconstruction, 3D modelling of process plants, architectural preservation tasks, digital factory layouts or deformation monitoring.
SCENE 5.0 Scandatenverarbeitung in einer neuen DimensionFARO_Europe
Die 3D-Laserscanner von FARO liefern mithilfe modernster Lasertechnologie äußerst detailreiche 3D-Dokumente. In nur wenigen Minuten entstehen 3D-Bilder von komplexen Umgebungen und geometrischen Elementen. Sie können für die Unfallrekonstruktion, die 3D-Modellierung von Anlagen, architektonische Erhaltungsprojekte, digitale Fabriklayouts oder zur Überwachung von Verformungen genutzt werden.
TNAU CRMD - A Customer Relationship Management datahouse for TNAUSenthil Natesan
Every great business starts with a great relationship. Every great relationship starts with You.
The strategy for establishing, developing and maintaining these relationships is CRM. (Customer Relationship Management).
The system that support this strategy is TNAU CRMD software.
TNAU CRMD offers unrivalled flexibility to design CRM applications and processes based on our needs.
3D laser scanners from FARO use laser technology to deliver highly detailed 3D Documentation. 3D images of complex environments and geometries can be generated in mere minutes. Use them for accident reconstruction, 3D modelling of process plants, architectural preservation tasks, digital factory layouts or deformation monitoring.
In this presentation, we will delve into the principles of QTL mapping and explore various strategies for mapping QTLs in plants. We will also discuss the advantages and limitations, and provide insights into how QTL mapping is advancing our understanding of genetics.
Association mapping approaches for tagging quality traits in maizeSenthil Natesan
Association mapping has been widely used to study the genetic basis of complex traits in human and animal systems and is a very efficient and effective method for confirming candidate genes or for identifying new genes (Altshuler et al., 2008). Association mapping is now being increasingly used in a wide range of plants (Rafalski, 2010), where it appears to be more powerful than in humans or animals (Zhu et al., 2008). Unlike linkage mapping, association mapping can explore all the recombination events and mutations in a given population and with a higher resolution (Yu and Buckler, 2006). However, association mapping has a lower power to detect rare alleles in a population, even those with large effects, than linkage mapping (Hill et al., 2008). Yan et al., (2010) demonstrated that the gene encoding β-carotene hydroxylase 1 (crtRB1) underlies a principal quantitative trait locus associated with β-carotene concentration and conversion in maize kernels has been identified through candidate gene strategy of association mapping.
QTL is a gene or the chromosomal region that affects a quantitative trait, which should be polymorphic (have allelic variation) to have an effect in a population, must be linked to a polymorphic marker allele to be detected. The QTL mapping consists of 4 steps, like the development of mapping population, generation of polymorphic marker data set among the parents, construction of linkage map, and finally the QTL analysis
All the above steps are described in these slides very briefly along with two case studies.
Strategies for mapping of genes for agronomic traits in plantstusharamodugu
The genomic regions associated with the expression of a quantitative trait is referred to as quantitative trait loci (QTL).
A QTL may contain one or more genes affecting the concerned quantitative trait.
Sax(1923) reported linkage between seed coat colour and seed size, which are qualitative and quantitative traits in common bean and the work highlighted the basic principles for mapping of polygenes based on the detection of association between a quantitative trait phenotype and a genetic marker.
Thoday (1961) explored this QTL concept further by combining elaborate cytogenetic techniques with genetic analysis to map QTLs for several quantitative traits in Drosophila
Role of molecular marker play a significant supplementary role in enhancing yield along with conventional plant breeding methods. the result obtain through molecular method are more accurate and at genotypic level. It had wider applications in field of plant breeding, biotechnology, physiology, pathology, entamology, etc. The mapping information obtained from these markers had created a revolution in the sequencing sector and open many pathways for developments, innovations and research.
Centre of innovation, Agricultural College and Research Institute,MaduraiSenthil Natesan
Establishment Central Instrumentation facility with the cost of 6.03 crore to take up multidisciplinary research project at AC&RI,Madurai. The analytical platform includes UP-HPLC for amino acid analysis, XRF for micronutrient analysis and GC-MS for metabolic profiling. The imaging facilities like upright, inverted and Florence microscope established for imaging pathogen & Insects. The molecular biology lab with real time PCR will help for the gene expression studies.
The agriculture sector employs nearly half of the workforce in the country. However, it contributes to 17.5% of the GDP (at current prices in 2015-16).Agriculture sector’s contribution has decreased from more than 50% of GDP in the 1950s to 15.4% in 2015-16 (at constant prices). This slides discuss about Indian agriculture status and problems and solutions.
paper presented during the National seminar on Challanges and Innovative approaches in Crop Improvement at AC&RI, Madurai. during December 16-17, 2014 .Germplasm conservation in Oil Palm by Dr P. Murugesan Indian Institute of Oil Palm Research
Improvement of Medicinal Plants: Challenges and Innovative ApproachesSenthil Natesan
Paper Presented during the National seminar on Challenges and Innovative approaches in crop improvement held at AC&RI, Madurai , TNAU by
Dr.P. Manivel, Directorate of Medicinal and Aromatic Plants Research, Boriavi-387310, Anand, Gujarat
Genomics platform for agriculture-CAT lectureSenthil Natesan
The popular lecture for the undergraduate students of agriculture to know about the application of biotechnology in agriculture science graduates. Some of the major break through inventions how it impact on agriculture research and development
Castor is an oilseed plant which is earning attention on researchers in recent days. Because of this, the gemplasms of ancient varieties were now recovered and grown in trial fields for getting genetically superior variety.
As a result, in Castor and Tapioca research station there a variety named YRCH (Yethapur Ricinus Communis Hybrid) with all desired traits which are essential for a plant both phenotypically and genetically was developed.
Triacylglycerols produced by plants are one of the most energy-rich and abundant forms of reduced carbon available from nature. Given their chemical similarities, plant oils represent a logical substitute for conventional diesel, a non-renewable energy source. However, as plant oils are too viscous for use in modern diesel engines, they are converted to fatty acid esters. Apart from seed oil vegetative tissue is potential source as bio mass for biofuel production, taking 15 tonnes per hectare as an average dry matter yield for a perennial grass, an oil content of 20– 25% by weight will produce about 3400 l of biodiesel (Heaton et al., 2004). There is growing interest in engineering green biomass to expand the production of plant oils as feed and biofuels. Here, we show that PHOSPHOLIPID: DIACYLGLYCEROL ACYLTRANSFERASE1 (PDAT1) is a critical enzyme involved in triacylglycerol (TAG) synthesis in leaves. Overexpression of PDAT1 increases leaf TAG accumulation, leading to oil droplet overexpansion through fusion. Ectopic expression of oleosin promotes the clustering of small oil droplets. Coexpression of PDAT1 with oleosin boosts leaf TAG content by up to 6.4% of the dry weight without affecting membrane lipid composition and plant growth. PDAT1 overexpression stimulates fatty acid synthesis (FAS) and increases fatty acid flux toward the prokaryotic glycerolipid pathway (Julian at al..2013). First, an Arabidopsis thaliana gene diacylglycerol acyltransferase (DGAT) coding for a key enzyme in triacylglycerol (TAG) biosynthesis, was expressed in tobacco under the control of a strong ribulose-biphosphate carboxylase small subunit promoter. This modification led to up to a 20-fold increase in TAG accumulation in tobacco leaves and translated into an overall of about a twofold increase in extracted fatty acids (FA) up to 5.8% of dry biomass in Nicotiana tabacum cv Wisconsin, and up to 6% in high-sugar tobacco variety NC-55 ( Andrianovet al 2010). Therefore Biotechnology has important and perhaps critical part to play in large-scale development of Biodiesel.
Vaccines have been revolutionary for the prevention of infectious diseases. Despite worldwide immunization of children against the six devastating diseases, 20% of infants are still left un-immunized; responsible for approximately two million unnecessary deaths every year, especially in the remote and impoverished parts of the globe. This is because of the constraints on vaccine production, distribution and delivery. One hundred percent coverage is desirable, because un-immunized populations in remote areas can spread infections and epidemics in the immunized safe areas, which have comparatively low herd immunity. For some infectious diseases, immunizations either do not exist or they are unreliable or very expensive. Immunization through DNA vaccines is an alternative but is an expensive approach, with disappointing immune response. Hence the search is on for cost-effective, easy-to-administer, easy-to-store, fail-safe and socio-culturally readily acceptable vaccines and their delivery systems. As Hippocrates said, Let thy food be thy medicine, scientists suggest that plants and plant viruses can be genetically engineered to produce vaccines against diseases such as dental caries; and life-threatening infections like diarrhea, AIDS, etc (Lal et al., 2007)
Cellular signal transduction pathways under abiotic stressSenthil Natesan
Abiotic stresses, especially cold, salinity and drought, are the primary causes of crop loss worldwide. Plant adaptation to environmental stresses is dependent upon the activation of cascades of molecular networks involved in stress perception, signal transduction, and the expression of specific stress-related genes and metabolites. Plants have stress-specific adaptive responses as well as responses which protect the plants from more than one environmental stress. There are multiple stress perception and signaling pathways, some of which are specific, but others may cross-talk at various steps (Knight & knight ,2001).Many cold induced pathways are activated to protect plants from deleterious effects of cold stress, but till date, most studied pathway is ICE-CBF-COR signaling pathway (Miura and Furumoto,2013 ) . The Salt-Overly-Sensitive (SOS) pathway, identified through isolation and study of the sos1, sos2, and sos3 mutants, is essential for maintaining favorable ion ratios in the cytoplasm and for tolerance of salt stress (shi .et al ,2002). Both ABA-dependent and -independent signaling pathways appear to be involved in osmotic stress tolerance (Nakashima and shinozaki, 2013) .ROS play a dual role in the response of plants to abiotic stresses functioning as toxic by-products of stress metabolism, as well as important signal transduction molecules and the ROS signaling networks can control growth, development, and stress response ( Mahajan,s and Tuteja, 2005) .
Genotyping by Sequencing is a robust,fast and cheap approach for high throughput marker discovery.It has applications in crop improvement programs by enhancing identification of superior genotypes.
MAGIC :Multiparent advanced generation intercross and QTL discovery
1. MAGIC, Multiparent advanced generation intercross a
new genetic resource for multiple trait improvement and
QTL discovery in crops
G.Kalidasan
2. Quantitative traits
Phenotype expression
Natural variation
Experimental System
Selection or Natural Population
Experimental Population
Multiparent Advanced Generation Intercross Population
Case Studies
3. Selection and Natural populations
Selection experiments
Marker allele frequency –
Unrelated individuals
Many generations
Difference in phenotype
LD between QTL and marker
LD around a QTL
5. Exploits LD in diverse population
Human
Crops
Maize
Advantage
Cheaper and high density markers
Disadvantage
Spurious associations
Greater precision but low power
6. Mutant population
Spontaneous mutation
Induced mutation
Mutagenesis
Large resources
Poly ploidy
TILLING
Phenotyping screen
Knowledge on genes controlling trait
7. F2 and backcross (BC) populations
Additive effects
Few meioses
Recombinant inbred lines
RILs are advanced homozygous
lines
Increased recombination events
and improved map resolution
Epistatic interactions
8. Near isogenic lines(NIL)
Target trait is required for the
generation of NILs.
High-resolution mapping
Double haploids
100% purity and genetic
uniformity.
Genetic studies
9. Randomly and sequentially
intercrossed population.
Phenotypic selection to further
reduce the frequency of deleterious
alleles from the donor.
Detect QTLs with epistatic effects
Useful meiotic recombination
10. Linkage map
DNA Markers
Position and relative genetic distance
For identifying chromosomal regions that contain genes
controlling simple or complex traits using QTL analysis
QTL mapping
Advantage
High detection power
Few markers are required
Disadvantage
Large confidence interval of upto 5 to 30cM
Limited resolution
Only two alleles tested
11. Multiparent advanced generation intercross
Animals. (Mott et al., 2000) and (Yalchin et al., 2005)
Fine-mapping of multiple QTLs for multiple traits in the same
population.
Advanced intercrossed lines (AILs)
Each generation reduces the extent of linkage disequilibrium
(LD), thus allowing QTL to be mapped more accurately.
Lines derived from early generations can be used for QTL
detection and coarse mapping
While those derived from later generations will only detect
marker-trait associations if markers are located very close to
the QTL.
12. Extended to plants
(Cavanagh et al., 2008)
Diverse founder lines
n/2 generations
RILs
Increased intercrossing
cycles
14. Statistics tools
Linear mixed effect model and Hierarchical Bayes QTL
mapping - study the interrelationship between individuals MLs
and founder lines and increases the precision to detect QTL
HAPPY- a software package for Multipoint QTL Mapping in
Genetically Heterogeneous Animals
R/mp Map- A computational platform for the genetic analysis of
multi-parent recombinant inbred lines
15. Advantages
Shuffling the genes across different parents enable accurately
ordering the genes
Increased recombination - novel rearrangements of alleles and
greater genetic diversity.
Best combinations of genes for important traits development
1000 Magic individuals
Seeds retained - fine mapping
Epistatic and G X E interactions
Facilitate the discovery, identification and manipulation of new
forms of allelic variability
16. Disadvantages
Extensive segregation
More time
Large scale phenotyping
18. In Arabidopsis fine mapping of QTL for germination and bolting
time (Kover et al. 2009)
Studies in flowering time candidate genes
(Ehrenreich et al. 2009)
Developed computational platform R/mp Map for Genetic
analysis (Huang and George,
2011)
19.
20. 19 ‘‘founder’’ accessions
Wide geographical distribution
Staggered planting scheme
Replanted families – randomly
assigned crosses
342 F4 outcrossed families
Each F4 family derived up to 3 MLs
followed by selfing 6 generations
527 lines taken out of 1026
21.
22. Developmental quantitative traits
Measured the heritability (h2)
h2 L is the proportion of variation that is due to genetic
differences between lines, using the phenotypic average of the
replicates within each line
h2 P is an estimate of the genetic variance if only one replicate
per line were phenotyped
h2L ≥ h2P
h2L increases with the number of replicates
Mean of each line is used for QTL mapping
23. Phenotypic variance
Diallelic population - 0.5
Magic – 0.052
Average minor allele frequency in
founder lines is 0.22
70% of SNP shared between any pair
of founders
Increasing replication within line
reduces non- genetic variance
Improves power of QTL
24. A hidden Markov model (HMM) is used to make a multipoint
probabilistic reconstruction of the genome of each ML as a mosaic of
the founder haplotypes.
Diallelic SNPs cannot distinguish between all founders so information
from neighboring SNPs is used to compute the posterior probability
Pis(L) is that at a given locus L, the ML i is descended from founder s.
Locus is defined to be the interval between two adjacent genotyped
SNPs, labeled by the name of the left-hand SNP.
25. Used fixed-effects QTL models but to accommodate population
structure, in different ways used multiple-QTL modeling or random
effects to explain the correlations introduced in population structure
Checked with hierarchical Bayesian random effects model
All approaches model the mosaic structure of the MAGIC genomes
as described in and implemented in the R package HAPPY
Detected two QTLs on chromosomes 3 and 4 for the number of days
to germination and bolting time.
26.
27. Constructed a linkage map from a four parent MAGIC population and
validate it against a comprehensive DArT consensus map drawing
together maps from over 100 biparental populations
Incorporated the alien introgressions in to the linkage map
Level of LD across the genome and compare it with previous
estimates for LD from previous studies
The power and precision of MAGIC for QTL mapping for plant height ,
an important trait for yield potential
28. Selected four elite wheat
cultivar , A- Yitpi , B- Baxter,
C- Chara, D- Westonia
Genetic diversity based on
genetic survey of international
wheat samples
Diverse geographical distribution
Phenotypic diversity for a range
of traits
29. Genotyping
Used 1285 DArT markers, 57 SSR markers and 1536 SNPs
384 SNPs observed to be polymorphic among the parental lines
were selected for genome wide coverage
Phenotyping
1100 RILs – Plant height was recorded
30. R package mpMap
Filtered with monomorphic markers
Estimated the recombination fraction all pairs of loci with function
‘mpestrf’
Grouped the markers based on estimated recombination fractions
and LOD scores with the function ‘mpgroup’
For map resolution computed recombination events for all lines
using the function ‘mpprob’
Which calculates the multipoint probablity at each locus that the
observed genotype is inherited from each of the four founder
31. Both internal and external comparisons was done
Examined a series of diagnostic plots to propose changes to
ordering which were then tested through ‘ compare orders’ function
in R/mpMap
Used heatmaps based on both recombination fractions and LD
using R/Ldheatmap
The tool provided visualization of the relationships between all pairs
of markers
32. External comparison
Diagnostic checks are compared it to an external DArT consensus
wheat map
Each individual consensus map was based on genotyping involving
the analyis of between 206 and 1525markers, with an average
density of 582 markers
33. Test the introgression in magic population
Sr36 is an introgression from Triticum timopheevii for stem rust
resistance – carried in variety Baxter on chromosome 2B cause
segregation distortion
Aimed to identify markers associated with it and identify lines
containing it
Computed the degree of segregation distortion for which i) the
Baxter allele differed from all other founder alleles
ii) mutual recombination of < 0.05 was observed were tagged as
potential markers in the introgression
Estimated the probablity of a line having inherited an allele from the
founder Baxter for the identified markers(‘mpprob’)
34. Linkage disequilbrium
Multipoint probablities were computed using the function ‘mpprob’ in
R/mpMap and LD was computed using the function ‘mpcalcld’
QTL Mapping
For all analyses used the ‘mplMmm’ function in the R package
mpMap, which performs the interval mapping in the context of a
linear mixed model
Three QTL for plant height were detected near known genes on
chromosomes 2D, 4B, 4D.
35. (MAGIC) populations combine the advantages of linkage analysis and
association studies.
The increased recombination in MAGIC populations leads to novel
rearrangements of alleles and greater genetic diversity
Can facilitate the discovery, identification and manipulation of new
forms of allelic variability
They require longer time and more resource to be generated and they
are likely to show extensive segregation for developmental traits.
MAGIC populations are likely to bring paradigm shift towards QTL
analysis in plant species
36. The experimental method was underway since it has to be studied
in many crops
The tools used for QTL mapping are very complex, so simplified
models has to be developed in near future for understanding.
In near future the method will bring success in finding our economic
interest of traits in plants.
Editor's Notes
By waiting until an advanced generation, one could allow for phenotypic selection to further reduce the frequency of deleterious or undesirable alleles from the donor.