Linkage and QTL mapping Populations and Association mapping population.
F2, Immortalized F2, Backcross (BC), Near isogenic lines (NIL), RIL, Double haploids(DH), Nested Association mapping (NAM), MAGIC and Interconnected populations.
Linkage and QTL mapping Populations and Association mapping population.
F2, Immortalized F2, Backcross (BC), Near isogenic lines (NIL), RIL, Double haploids(DH), Nested Association mapping (NAM), MAGIC and Interconnected populations.
A new era of genomics for plant science research has opened due the complete genome sequencing projects of Arabidopsis thaliana and rice. The sequence information available in public database has highlighted the need to develop genome scale reverse genetic strategies for functional analysis (Till et al., 2003). As most of the phenotypes are obscure, the forward genetics can hardly meet the demand of a high throughput and large-scale survey of gene functions. Targeting Induced Local Lesions in Genome TILLING is a general reverse genetic technique that combines chemical mutagenesis with PCR based screening to identity point mutations in regions of interest (McCallum et al., 2000). This strategy works with a mismatch-specific endonuclease to detect induced or natural DNA polymorphisms in genes of interest. A newly developed general reverse genetic strategy helps to locate an allelic series of induced point mutations in genes of interest. It allows the rapid and inexpensive detection of induced point mutations in populations of physically or chemically mutagenized individuals. To create an induced population with the use of physical/chemical mutagens is the first prerequisite for TILLING approach. Most of the plant species are compatible with this technique due to their self-fertilized nature and the seeds produced by these plants can be stored for long periods of time (Borevitz et al., 2003). The seeds are treated with mutagens and raised to harvest M1 plants, which are consequently, self-fertilized to raise the M2 population. DNA extracted from M2 plants is used in mutational screening (Colbert et al., 2001). To avoid mixing of the same mutation only one M2 plant from each M1 is used for DNA extraction (Till et al., 2007). The M3 seeds produce by selfing the M2 progeny can be well preserved for long term storage. Ethyl methane sulfonate (EMS) has been extensively used as a chemical mutagen in TILLING studies in plants to generate mutant populations, although other mutagens can be effective. EMS produces transitional mutations (G/C, A/T) by alkylating G residues which pairs with T instead of the conservative base pairing with C (Nagy et al., 2003). It is a constructive approach for users to attempt a range of chemical mutagens to assess the lethality and sterility on germinal tissue before creating large mutant populations.
Marker Assisted Selection in Crop BreedingPawan Chauhan
Marker Assisted Selection is a value addition to conventional methods of Crop Breeding. It has been gaining importance in plant breeding with new generation of plant breeders and to get accurate and fast desired result from plant breeding.
Advanced biometrical and quantitative genetics akshayAkshay Deshmukh
Additive and Multiplicative Model
Shifted Multiplicative Model
Analysis and Selection of Genotype
Methods and steps to select the best model
Bioplot and mapping genotype
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
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)
Gene mapping | Genetic map | Physical Map | DNA Data Analysis (upgraded)NARC, Islamabad
Genes are useful markers but not ideal.
Mapped feature that are not genes are called DNA markers.
DNA markers must have at least two alleles to be useful.
DNA sequence features that satisfy this requirement are-
– Restriction Fragment Length Polymorphism (RFLP)
Southern hybridization
PCR
– Simple Sequence Length Polymorphism (SSLP)
– Single Nucleotide Polymorphism (SNP)
Mapping- determining the location of elements with in a genome, with respect to identifiable land marks.
Gene mapping describes the methods used to identify the locus of a gene and the distances between genes.
In simple mapping of genes to specific locations on chromosomes.
Two types
Genetic map
Physical Map
They are useful in predicting results of dihybrid and trihybrid crosses.
It allows geneticists to understand the overall complexity and genetic organization of a particular species.
Identify genes responsible for diseases.
Identify genes responsible for traits.
genetic maps are useful from an evolutionary point of view.
Gene mapping / Genetic map vs Physical Map | determination of map distance a...NARC, Islamabad
Mapping- determining the location of elements with in a genome, with respect to identifiable land marks.
Gene mapping describes the methods used to identify the locus of a gene and the distances between genes.
In simple mapping of genes to specific locations on chromosomes.
Two types
Genetic map
Physical Map
Construction of a Linkage Map or Genetic Mapping
Construction of a Linkage Map or Genetic Mapping
1. DNA MARKERS FOR GENETIC MAPPING
– Restriction Fragment Length Polymorphism (RFLP)
– Simple Sequence Length Polymorphism (SSLP)
– Single Nucleotide Polymorphism (SNP)
2. Determination of Linkage Groups(No. of Chromosomes)
Dihybrid cross
Trihybrid cross
3. Determination of Map Distance
Recombination fraction
4. Determination of Gene Order
5. Combining Map Segments
A new era of genomics for plant science research has opened due the complete genome sequencing projects of Arabidopsis thaliana and rice. The sequence information available in public database has highlighted the need to develop genome scale reverse genetic strategies for functional analysis (Till et al., 2003). As most of the phenotypes are obscure, the forward genetics can hardly meet the demand of a high throughput and large-scale survey of gene functions. Targeting Induced Local Lesions in Genome TILLING is a general reverse genetic technique that combines chemical mutagenesis with PCR based screening to identity point mutations in regions of interest (McCallum et al., 2000). This strategy works with a mismatch-specific endonuclease to detect induced or natural DNA polymorphisms in genes of interest. A newly developed general reverse genetic strategy helps to locate an allelic series of induced point mutations in genes of interest. It allows the rapid and inexpensive detection of induced point mutations in populations of physically or chemically mutagenized individuals. To create an induced population with the use of physical/chemical mutagens is the first prerequisite for TILLING approach. Most of the plant species are compatible with this technique due to their self-fertilized nature and the seeds produced by these plants can be stored for long periods of time (Borevitz et al., 2003). The seeds are treated with mutagens and raised to harvest M1 plants, which are consequently, self-fertilized to raise the M2 population. DNA extracted from M2 plants is used in mutational screening (Colbert et al., 2001). To avoid mixing of the same mutation only one M2 plant from each M1 is used for DNA extraction (Till et al., 2007). The M3 seeds produce by selfing the M2 progeny can be well preserved for long term storage. Ethyl methane sulfonate (EMS) has been extensively used as a chemical mutagen in TILLING studies in plants to generate mutant populations, although other mutagens can be effective. EMS produces transitional mutations (G/C, A/T) by alkylating G residues which pairs with T instead of the conservative base pairing with C (Nagy et al., 2003). It is a constructive approach for users to attempt a range of chemical mutagens to assess the lethality and sterility on germinal tissue before creating large mutant populations.
Marker Assisted Selection in Crop BreedingPawan Chauhan
Marker Assisted Selection is a value addition to conventional methods of Crop Breeding. It has been gaining importance in plant breeding with new generation of plant breeders and to get accurate and fast desired result from plant breeding.
Advanced biometrical and quantitative genetics akshayAkshay Deshmukh
Additive and Multiplicative Model
Shifted Multiplicative Model
Analysis and Selection of Genotype
Methods and steps to select the best model
Bioplot and mapping genotype
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
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)
Gene mapping | Genetic map | Physical Map | DNA Data Analysis (upgraded)NARC, Islamabad
Genes are useful markers but not ideal.
Mapped feature that are not genes are called DNA markers.
DNA markers must have at least two alleles to be useful.
DNA sequence features that satisfy this requirement are-
– Restriction Fragment Length Polymorphism (RFLP)
Southern hybridization
PCR
– Simple Sequence Length Polymorphism (SSLP)
– Single Nucleotide Polymorphism (SNP)
Mapping- determining the location of elements with in a genome, with respect to identifiable land marks.
Gene mapping describes the methods used to identify the locus of a gene and the distances between genes.
In simple mapping of genes to specific locations on chromosomes.
Two types
Genetic map
Physical Map
They are useful in predicting results of dihybrid and trihybrid crosses.
It allows geneticists to understand the overall complexity and genetic organization of a particular species.
Identify genes responsible for diseases.
Identify genes responsible for traits.
genetic maps are useful from an evolutionary point of view.
Gene mapping / Genetic map vs Physical Map | determination of map distance a...NARC, Islamabad
Mapping- determining the location of elements with in a genome, with respect to identifiable land marks.
Gene mapping describes the methods used to identify the locus of a gene and the distances between genes.
In simple mapping of genes to specific locations on chromosomes.
Two types
Genetic map
Physical Map
Construction of a Linkage Map or Genetic Mapping
Construction of a Linkage Map or Genetic Mapping
1. DNA MARKERS FOR GENETIC MAPPING
– Restriction Fragment Length Polymorphism (RFLP)
– Simple Sequence Length Polymorphism (SSLP)
– Single Nucleotide Polymorphism (SNP)
2. Determination of Linkage Groups(No. of Chromosomes)
Dihybrid cross
Trihybrid cross
3. Determination of Map Distance
Recombination fraction
4. Determination of Gene Order
5. Combining Map Segments
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.
Gene mapping, describes the methods used to identify the locus of a gene and the distances between genes. The essence of all genome mapping is to place a collection of molecular markers onto their respective positions on the genome. Molecular markers come in all forms.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Nucleic Acid-its structural and functional complexity.
Location and mapping of chromosomes using conventional and cytological means.
1. LOCATION AND MAPPING
OF CHROMOSOMES USING
CONVENTIONAL AND
CYTOLOGICAL MEANS
NOOR E MUJJASSIM
PALB 8078
2. 2
Contents
Introduction to Genetic map
Steps in construction of linkage map
Application and limitation.
Cytological map construction
Deletion, interchange, monosomics and
trisomics, monotelodisomics.
Conclusion
3. A map - Graphical representation that provides information
about the location of sites and the spacing between them.
Genetic map is the schematic representation of the various
genetic markers in specific order in which they are located
in a chromosome as well as the relative distances between
these markers.
Map
4. Why to map the genes ?
Information gained regarding
chromosome organization
gene function and evolution
Mapping of a gene is often first step in
identifying gene responsible for
phenotype
identifying mutants
studying gene function
5. GENETIC/ LINKAGE MAP
• Linkage map is a schematic representation of relative location and
position of genetic markers on the chromosomes as determined by
frequency of recombination between all possible pairs of genetic markers.
• Depiction of the genes linked together on a straight line.
• measured in centi morgans (cM)
• map unit- 1 mu = 1% recombination between linked genes
• also known as a chromosome map. 5
6. • A linkage or genetic map of any plant or animal species denotes the
linear order of markers on a particular chromosome, which is determined
by the number of crossover events and recombination frequencies
between markers (Sturtevant, 1913).
• During segregation if a block of genes or chromosomal segments do not
assort independently, they are described as being linked. This is the basis
on which a genetic map is developed.
7. • Recombination among polymorphic loci and the likelihood that
recombination events occur between two points of a chromosome depends
in general on their physical distance.
• The closer they are located to each other, the more they tend to stay
together after meiosis.
• With the increase of the distance between these points on the chromosome,
the probability for recombination increases and genetic linkage tends to
disappear.
• This is why genetic linkage can be interpreted as a measure of physical
distance.
7
8. Steps in linkage map construction
1. Assigning markers onto chromosomes or linkage groups.
2. Finding the relative order of the markers.
3. Estimating the relative distances b/w the markers in map units
8
9. principle in assigning the markers on
chromosomes
• All those markers between whom the recombination frequency is less than
0.5 should be present on same chromosome or single chromosome.
• Punnett and bateson (1905), who examined two other traits (flower colour
and pollen shape) in pea plants.
• If traits are co-inherited more often than expected by chance, they are
linked.
9
10. Genetic maps of chromosomes are based on the average number of
crossovers that occur during meiosis.
Recombination frequencies less than 15 % estimate map distance
directly; however greater than 15% underestimate map distance because
multiple cross over events do not always produce recombinant
chromosomes.
an average of one chiasma during meiosis is equivalent to 50 centi
morgan of genetic map distance.
10
12. DNA
isolation
Keep the tubes in
PCR
Complimentary strand
synthesis
Amplified product separated
by gel electrophoresis
Screen in mapping
population
Identify polymorphic markers
Score the data
Feed into software
Linkage map
13. Once the markers are assigned to linkage group,
then what next?
Identifying the best possible order of markers:
1.Minimum sum of adjuscent RF (SURF)
2.Minimum product of adjuscent RF (PUF)
3.Maximum sum of adjuscent LOD Score(SALOD)
4.Least square method
5.Maximum likelihood method
13
14. Finding the relative distance between ordered
markers;
• By using mapping functions;
1.Morgan’s mapping function
2.Haldane mapping function
3.Kosambi mapping function
14
15. Factors on which linkage map depends;
Size of the mapping population.
Number of markers.
Recombination fraction threshold.
LOD score
Criteria used to arrive at best possible order
Mapping function used
15
16. BASIC AND APPLIED USES OF GENETIC MAPS
(a) Study genomes of related species with common markers,
(b) Tag important traits of interest with associated markers and follow the
transmission and selection of the former in breeding cycles, and
(c) With the advent of recombinant DNA technologies, genetic mapping can
be carried to its logical conclusion, positional cloning (isolation) of a gene
solely on the basis of its chromosomal location without regard to its
biological function.
16
17. LIMITATIONS OF GENETIC MAP
The resolution of genetic map depends on the
number of cross overs that have been scored
Genetic maps have limited accuracy.
Certain genomic regions more sensitive to
recombination
Markers must be polymorphic for genetic
mapping 17
18. Contents
• Introduction
• Techniquesfor Gene Location
1. Useof Structural ChromosomalAberrations
2. Useof Numerical ChromosomalAberrations
3. Useof ChromosomalBanding
4. Useof In situ hybridizationtechniques
• Techniquesfor GeneTransfer
1. Transfer of whole genome
2. Transfer of whole chromosome
3. Substitution of alien chromosomearm
4. Interchanges
19. Introduction
• Locating the gene means assigning the genes
to specific chromosome or chromosomearm
• Transfer of gene means transfer of particular
segment or whole chromosome or whole
genome across the species for improving its
economic use
20. Use of structuralaberrations
1. Deficiencies
2. Inversions
3. Translocations
a) Uselinkage between
marker and semisterility
b) Overlapping
translocations
c) Useof B-Atranslocations
Use ofaneuploids
1. Trisomicanalysis
2. Monosomic and
nullisomic
analysis
Use of chromosome bandingtechniques
1. Qbanding
2. Gbanding
3. Cbanding
4. Nbanding
In situ hybridizationtechniques
1. FISH
2. GISH
22. Use of deficienciesin chromosome mapping in plants
• Female with recessive marker stocks crossed with
irradiated pollen from male carrying dominant
allele
• F1heterozygote seed grown
• If……. Egg fertilized by normal pollen it will show
dominant phenotype
• If……. egg fertilized by pollen containing deficiency
at that concerned locus it will show recessive
phenotype instead of dominant
Here, the transmission of deficiency does not
impaired
23. • They used pollen of tomato variety red cherry’s pollen to irradiate with X rays to pollinate
homozygous recessive female
• Plants in M1 generation showing pseudo dominance used for cytologicalstudy
• Young flower buds from pseudo dominant plants collected and pachytene chromosomes
examined for deficiencies
• Cytological studies of 74 deficiencies of tomato chromosomes induced by radiation and
identified by the pseudo-dominant technique reveal the loci of 35 genes on 18 of the 24
arms of thecomplement.
26. Inversions for locatinggene
• Inversions can be readily detected by a comparison of recombination frequency
betweentheplantwithnormalandinvertedchromosome.
• Existence-firstdetectedbySturtevantandPlunkettin1926
• They prepared genetic maps for the genes se st p DL H ca located in the third
chromosomeof Drosophila melanogaster (gene sequence: se st pDLHca) using
lessrecombinationwithininverted segments.
27. Interchanges in chromosomemapping
1.Using linkage between marker and semisterility
• Translocations have been utilized in maize, barley and pea for determining linkage
groups/genes with specificchromosomes
• It is based on observed linkage between interchange breakpoint or semi-sterility &
marker gene located on one of thechromosomes
• involves crossing of translocation heterozygote and recessive markerstock
• F1are selfed or backcrosswith recessive markerstock
• In F2study of recombination between breakpoint or semi sterility & marker gene using
two point or three point test crossmethod.
28. Chromosome mapping using translocation in maize
Chomosome Marker genes mapped References
1 br ( brachytic dwarf)
f ( fine striped leaf)
an ( anther ear dwarf)
bm2 ( brown midrib leaf)
Burnham ( 1948)
7 V5 (virescent)
Ra ( ramose tassel ear )
gl ( glossy leaf -1 )
Ij ( iojap variegation )
Burnham ( 1948)
8 j (japonica) Burnham ( 1934)
9 C ( coloured aleurone)
sh (shrunken)
wx (waxy)
Burnham ( 1934)
30. 2. Overlapping translocationsprocedure
• Method first proposed by Gopinath and Burnham in1956
• Femaleproduces four type of gametes
1. balanced translocation for onechromosome
2. balanced translocation for anotherchromosome
3. gamete with duplications
4. gamete with deficiencies(they areabortive)
• So,if gene located in interstitial region then progenies will have genotypes AaandAAa
• From this when segmental trisomic (AAa) selfed, itwill give trisomic ratio 17:1
• Thistechnique extensively used in Drosophila to locate structuralgenes
32. 3. Use of B-Atranslocations
• Most efficient method for locating recessive mutants to the proper chromosome arm
• Romanand Ullstrup demonstrated the usefulness of the B-Atranslocation method
when they located agene (hm) for reaction to Helminthosporium carbonurn in maize
• In 1947, Romanproduced the first B-Atranslocations by X-raying mature pollen from
plants carrying B-typechromosomes
Production of aB-Atranslocation
Translocation heterozygote
Translocation homozygote
33. Cont…..
• Romanshowed that nondisjunction of the Bchromosome occurs at the
second division of the microspore
• It produces one hyperploid sperm with two B chromosomes and one
hypoploid sperm with none
Beckett,1978
34. Use for locatinggene
1. Cross of normal plant with recessive marker (susu) with
B-A translocation homozygote with dominant marker
(SuSu)
2. When hypoploid male nuclei fertilize the secondary
nuclei…….it will give sugary endosperm (susu) and
hyperploid with egg…….it will give F1 sugary seed
(SuSusu)
3. But in next generation only 6.4 % sugary seeds obtained
which is trisomic ratio as expected for the critical line
35. Use of Aneuploid forlocatinggenes
Aneuploidy
loss or gain of one or few
chromosomes ascompared
to normal somatic
chromosome complement
Generally asaview of
locating the geneswe
usenullisomic,
monosomic or trisomics
asper convenience
36.
37. TrisomicAnalysis
• Use of trisomics for locating the genes and preparing chromosome mapping called
trisomicanalysis
• BRIDGES (1921)was first to usetrisomics to locate the gene ey (eyeless) hasits locus
in the fourth chromosomeof Drosophilamelanogaster.
• Similar identifications followed shortly in Datura: the gene “ White ” wasidentified
with the trisomic type “Poinsettia ” (BLAKESLEEandFARNHAM1923)
42. Monosomic & NullisomicAnalysis
Monosomic analysis
• Usedfor locating genesin Polyploid speciesand in maize (can tolerate
monosomic)
For dominant gene For recessive genes
43. Locating Dominant gene by absenceof
expression in nullisomics
• When dominant genelocated on chromosome
• Nullisomic for that chromosome will not show that character
• E.g.,
genesfor red seedcolour--- on chromosome3D
genefor awn suppression -- on chromosome 4Band6B
Wheat
44. Locating dominantgeneby analysis ofF1
• Crosswhole set of monosomics using asfemale containing dominant marker with
normal male containing recessive for thattrait
• Analyse ratio observed in F1
45. Locating recessivegene by analysis in F2
• Crossbetween whole set of monosomoics containing recessive trait with normal male
carrying homozygous dominant for thatgene
• In F1 all plants show dominant phenotype for both critical and non critical lines
• In F2ratiosanalysed
46. Locating genes usingintervarietal chromosomal
substitutions
• Useof whole chromosomesubstitutions
donor1. Monosomic series crossed with
variety
2. F1monosomics selected cytologically
3. Selfed to get disomic for the univalent
chromosome of donor
4. Then disomics are back-crossed to
recipient to recoverrecipient
5. If this substitution leads
morphological changes then
conclude that gene located
to major
we can
on that
chromosome
47. Locating genes on chromosomearms
• Locating gene on one of two arms of chromosomes by using telocentricchromosomes in
form of
Monotelosomics - 20II +1tI
Monoisosomics - 20II +1iI
Ditelosomics- 20II +1tII
Monotelodisomics- 20II +1heteroII
• Example :
In Chinesespring wheat monotelosomics for chromosome arm 6BSare awned (Chinese
spring is awnless), soit concluded that awn inhibitor gene B2is present on 6BL(Sears,1962)
48.
49. The long arm of chromosome 5A of common wheat carries the gene Q which is
responsible for the suppression of speltoid effect and for squarehead spike
characteristic of the variety Chinese Spring (SEARS 1954).
50. Materials and Methods
Chinese Spring wheat ditelosomic for chromosome arm 5AL was crossed to the
substitution line 'spelta-5A'.
Spikes of the F1 plants (2n=41+t) were speltoid and nonsquare head.
The F1 plants were selfed as well as test-crossed as male parents to Chinese Spring.
Results and Discussion
The test-cross progeny consisted of 44 plants of which 26 were of vulgare-type and 18
of spelta-type. This phenotypic segregation conforms to a 1:1 ratio, indicating independence
of the Q locus and the chromosome 5A centromere.
The chromosome constitution and phenotype of the test cross plants are summarized in
Table 1.
51.
52. The F2 progeny of the selfed monotelodisomic F1 consisted of 227 plants of which
166 were of spelta-type (nonsquarehead) and 61 were of vublgare-type
(squaerhead). This segregation was a very good fit for a 3:1 ratio (X2=0.424;
p=0.50-0.70).
A random sample of 80 F2 plants were used for meiotic studies to determine their
chromosome constitution.
CONCLUSION
The data of both test cross and F2progenies indicated that the Q locus is
genetically independent of the chromosome 5A centromere.
Hence it can be concluded that the gene Q is located 50 or more crossover units
from the centromere, i.e. it has a distal location on the long arm of chromosome
5A.
53. Conclusion
• Both the classical and molecular cytogenetic techniques are important for thegene location
• Among the several cytogenetic techniques that can be employed in centromere mapping and in
determining the orientation of linkage maps, translocations and deficiencies have been used
profitably
• Deficiency and translocation are most commonly used for the location of genesinseveral crops like
tomato (deficiency), maize and barley (translocation)
• Monosomic and nullisomic analysis are widely used for locating the genesin polyploids suchas
wheat
• Trisomics are usedfor gene detection in diploids