This document summarizes a case study on the draft genome sequence of chickpea. Key points include:
- Researchers sequenced and assembled the ~738Mb genome of a kabuli chickpea variety, identifying an estimated 28,269 genes.
- The genome provides resources for molecular breeding through identification of candidate genes for traits like disease resistance.
- Resequencing of elite varieties provided insights into genome diversity and domestication.
- Analysis found the draft captured over 90% of the gene space through mapping of transcriptome data, and contained homologs for over 98% of core eukaryotic genes.
I would like to share this presentation file.
Some basics information regarding to molecular plant breeding, hope this help the beginner who start working in this field.
Thanks for many original source of information (mainly from slideshare.net, IRRI, CIMMYT and any paper received from professor and some over the internet)
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
Molecular Breeding in Plants is an introduction to the fundamental techniques...UNIVERSITI MALAYSIA SABAH
This slide describe the process of molecular breeding in plants which involves the application of molecular markers for Marker Assisted Selection and Marker Assisted Breeding.
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.
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.
I would like to share this presentation file.
Some basics information regarding to molecular plant breeding, hope this help the beginner who start working in this field.
Thanks for many original source of information (mainly from slideshare.net, IRRI, CIMMYT and any paper received from professor and some over the internet)
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
Molecular Breeding in Plants is an introduction to the fundamental techniques...UNIVERSITI MALAYSIA SABAH
This slide describe the process of molecular breeding in plants which involves the application of molecular markers for Marker Assisted Selection and Marker Assisted Breeding.
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.
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.
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.
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)
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.”
Biotechnology for Crop Improvement.
Molecular Plant Breeding-Marker Assisted Breeding/Selection.
Comparison between three main and commonly discussed marker systems- RFLP, RAPD and AFLP.
Basic Understanding for Simple Sequence Repeats, SCAR and CAPS.
Strategies to overcome food shortages using molecular plant breeding approaches, Application of various molecular marker systems and examples.
Reference List.
Presenter: Brenda Chong
Targeted Induced Local Lesions IN Genome. Mutations (Single base pair substitution) are created by traditionally used chemical mutagens. Identify SNPs and / or INDELS in a gene / genes of interest from a mutagenized population.
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.
CD Genomics is dedicated to providing a comprehensive list of genomics and microarray solutions for agriculture, including genome, exome, transcriptome, and metagenome sequencing, genome-wide association studies (GWAS), and targeted sequencing and genotyping that focus on a subset of regions or genes such as single nucleotide polymorphisms (SNPs). https://www.cd-genomics.com/Transcriptomics.html
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.
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)
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.”
Biotechnology for Crop Improvement.
Molecular Plant Breeding-Marker Assisted Breeding/Selection.
Comparison between three main and commonly discussed marker systems- RFLP, RAPD and AFLP.
Basic Understanding for Simple Sequence Repeats, SCAR and CAPS.
Strategies to overcome food shortages using molecular plant breeding approaches, Application of various molecular marker systems and examples.
Reference List.
Presenter: Brenda Chong
Targeted Induced Local Lesions IN Genome. Mutations (Single base pair substitution) are created by traditionally used chemical mutagens. Identify SNPs and / or INDELS in a gene / genes of interest from a mutagenized population.
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.
CD Genomics is dedicated to providing a comprehensive list of genomics and microarray solutions for agriculture, including genome, exome, transcriptome, and metagenome sequencing, genome-wide association studies (GWAS), and targeted sequencing and genotyping that focus on a subset of regions or genes such as single nucleotide polymorphisms (SNPs). https://www.cd-genomics.com/Transcriptomics.html
Genomics and its application in crop improvementKhemlata20
meaning ,definition of genome ,genomics ,tools of genomics ,what is genome sequencing ,methods of genome sequencingand genome mapping ,advantage of genomics over traditional breeding program, examples of some crops whose genome has been sequenced, important points about genomics, work in the field of genomics ,applications of genomics .classification of genomics .different Omics in genomics like Proteomics ,Transcriptomics ,Metabolomics ,Need of genome sequencing
Functional genomics is a general approach toward understanding how the genes of an organism work together by assigning new functions to unknown genes. Information about the hypothesized function of an unknown gene may be deduced from its sequence structure using already known functions of similar genes as the basis for comparison. Gene function analysis therefore necessitates the analysis of temporal and spatial gene expression patterns (Yunbi Xu et al , Plant Molecular Biology (2005) ).
Role of Pangenomics for crop ImprovementPatelSupriya
It describes about the role of pangenomics in the crop improvement.It includes pangenome,superpangenome,databases,tools used in pangenomics,utilisation in crop improvement
OMICS is the comprehensive analysis of the biological system. The technologies which made a revolution such as Genomics, Transcriptomics, Proteomics, Metabolomics and Phenomics, in screening traits and develop novel improved organisms are mentioned here. The presentation gives a brief idea about various OMICS technology used in crop improvement, their steps, techniques used, applications, scope, advantages and disadvantages.
Molecular markers (DNA markers) have entered the scene of genetic improvement in a wide range of horticultural crops. Among the major traits targeted for improvement in horticultural breeding programmes are disease and pest resistance, fruit yield and quality, tree shape, floral morphology, drought tolerance and dormancy. The development of molecular techniques for genetic analysis has led to a great increase in the knowledge of horticultural genetics and understanding and behavior of their genomes. These molecular techniques in particular, molecular markers, have been used to monitor DNA sequence variation in and among the species and create new sources of genetic variation by introducing new and favorable traits from landraces, wild relatives and related species and to fasten the time taken in conventional breeding. Today, markers are also being used for, genetic mapping, gene tagging and gene introgression from exotic and wild species.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
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.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
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.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
3. Content
1) Introduction.
2) Background of Genomic Aided Selection for Crop Improvement.
3) Molecular and Genetic Markers in Plant Breeding.
4) Development of Genetic Markers.
5) Potential of cereal genomics
6) Progress in crop genome sequencing and analysis.
7) The impact of whole genome sequencing on breeding.
8) Genomic assisted features for future breeding.
9) Challenges in genomics-assisted crop improvement.
10)Case studies.
11)Conclusion.
12)References.
4. What is Genetics?
Study of Heredity and its Variation – heredity itself is meaningful
only ‘coz of variation.
Unit of study?
Species; Populations (natural/random mating/genetic cross
generated);Individuals
Components of variation?
Vp= Vg + Ve ; Interaction between genotype and environment also
matters.
How does variation arise?
Mutation; gene flow; recombination; ploidy level changes; gene
duplication; transposons
Who is interested?
Crop improvement biologists and evolutionary biologists
5. Genome is an organism’s complete set of DNA and is organized into
chromosomes containing genes that encode for hereditary traits. The
differences that distinguish one plant from another are encoded in the
plant’s genetic material, the DNA. DNA is packaged in chromosome
pairs (strands of genetic material), one coming from each parent. The
genes, which control a plant’s characteristics, are located on specific
segments of each chromosome. Together, all of a plant’s genes make
up its Genome.
6. Introduction
•In recent years advances in genetics and genomics have greatly enhanced our
understanding of the structural and functional aspects of plant genomes. Several
novel genetic and genomics approaches are expended.
•At only two Decades ago that plant scientists would have access to nearly the
complete genetic code of numerous plants species, including major crops species.
•Since the advent of modern crop improvement, breeders have dreamed of
applying marker-based selection in their populations.
•Morphological markers have long been known but are too few to be of any use.
• Protein markers, e.g. isozymes, are not of much use either also.
•Advances in genomics have given us microsatellite and SNP markers in such
high number that molecular marker technology for crop improvement and
eventually for human welfare has become a reality.
7. In past few years, Genomics research is generating new tools,
such as functional molecular markers and informatics, as well
as new knowledge about statistics and inheritance
phenomena that could increase the efficiency and precision of
crop improvement :
• A truly impressive number of advances in genetics and genomics
greatly enhanced our understanding of structural and functional
aspects of plant genomes but at the same time have challenged us
with many compelling avenues of investigation.
•Numerous transcription factors and even non coding sequences are
being implicated as the basis of considerable genetic variation found
to be very useful in revealing gene-trait associations.
Background of Genomic Aided Selection for
Crop Improvement
8. A variety of approaches
(cars)
MAS: MARKER-ASSISTED SELECTION
- Plants are selected for one or more (up to 8-10) alleles
MABC: MARKER-ASSISTED BACKCROSSING
One or more (up to 6-8) donor alleles are transferred
to an elite line
MARS: MARKER-ASSISTED RECURRENT SELECTION
Selection for several (up to 20-30) mapped QTLs relies
on index (genetic) values computed for each individual
based on its target QTLs
GWS: GENOME-WIDE SELECTION
Selection of genome-wide several loci that confer
tolerance/resistance/ superiority to traits of interest
using based on genome-wide marker profiling
9. The complete genome sequences of Arabidopsis, rice, sorghum
and popular as well as an enormous number of plant expressed
sequence tags (ESTs) have become available.
10. Molecular Markers in Plant Breeding
Molecular markers are now widely used to track loci and genome
regions in several crop-breeding programmes, as molecular markers
tightly linked with a large number of agronomic and disease
resistance traits are available in major crop species (Phillips and Vasil
2001, Jain et al. 2002, Gupta and Varshney 2004)
Markers can exhibit two modes of
inheritance i.e.
(a) Dominant/recessive
(b) Co-dominant.
If the genetic pattern of
homozygotes can be
distinguished from that of
heterozygotes, then a marker is
said to be co-dominant. Generally
co-dominant markers are more
informative than the dominant
markers.
11. In issue of the journal Nature , researchers who decoded the
human genome concluded that people have only 20,000 to
25,000 genes ,a drop from the 30,000 to 40,000 estimated
in 2001.
12. Genetic Markers in Plant Breeding
A large number of genes have been
identified through ‘wet lab’ as well as
in silico studies and a wealth of
sequence data have been accumulated
in public databases in the form of BAC
clones, ESTs, full length cDNA clones
and genes.
The availability of enormous amount
of sequence data from complete or
partial genes has made it possible to
develop the molecular markers directly
from the parts of genes. These markers
are referred as “genic” molecular
markers (GMM).
13. What is EST
Expressed sequence tag (EST) have generated from a vast
amount of publicly available sequence data from plant species;
these data can be mined for simple sequence repeats (SSRs).
• They have been developed and mapped in several crop species
and could prove useful for marker-assisted selection, especially
when the markers reside in the genes responsible for a phenotypic
trait.
GMMs developed from coding sequences like ESTs or fully
characterized genes frequently have been assigned known
functions. Based on the site of polymorphism and later’s effect on
phenotypic variation
14. These EST- SSRS are useful as molecular markers because
Their development is inexpensive,
They represent transcribed genes
A putative function can often be deduced by a homology
search.
Derived from transcripts,
Assaying the functional diversity in natural populations or
germplasm collections.
Valuable because of their higher level of transferability to
related species,
They can often be used as anchor markers for comparative
mapping and evolutionary studies.
15. Potential of cereal genomics
•Cereals, including rice, maize, wheat, barley, rye, sorghum,
oats and millets, have constituted the staple food of the world
since their domestication 10 000 years ago.
•In the past, cereals have been the subject of intensive
cytogenetic investigations, and these are now further
extended using the powerful tools of molecular biology in
the genomics era.
•The structural and functional genomics research on cereal
genomes , which during the past two decades has covered
both basic and applied aspects, deepens our understanding
about gene networks for cereal development and agronomy
•More interestingly genomics is revolutionizing breeding
methodology through marker-assisted selection (MAS) and
directed mutagenesis, which are significantly enhancing
the efficiency of breeding for the improvement of
agronomic traits.
16. The cloned genes, containing their own exons,
introns and regulatory elements, are good
candidates for transformation into other varieties of
the same crop, or into other cereals, without
additional modification.
17. GMMs have been classified into two groups by:
(i) Gene-targeted markers (GTMs): are associated with
anonymous gene segments and derived from polymorphisms
within genes, however not necessarily involved in phenotypic trait
variation, e.g. untranslated regions (UTRs) of EST sequences.
(ii) Functional markers (FMs): associated with a gene of known
function and derived from polymorphic sequences or sites within genes
and, thus, more likely to be causally involved in phenotypic trait
variation (e.g. candidate gene-based molecular markers).
18. Development of Genetic Markers
•ESTs represent a basic commodity within the analysis of genomes and their
genes for a species.
•Developing molecular markers from ESTs, it is essential to define the
“unigenes” after cluster analysis of random ESTs using appropriate
computer programmes such as stackPack.
STS
19. Once the unigene sequence data from EST analysis or non-redundant set of
genes are available, molecular markers can be developed using two main
approaches:
(1) Direct mapping: ESTs of interest can be used as RFLP probe or
the PCR primers can be designed for the EST/gene. Direct mapping
approach should be undertaken with the unigene set of ESTs or
genes only.
20. 2) In silico mining: In this approach, the SSR or SNP
identification software tools are used to screen the
sequence data for ESTs/genes. For identification of
SNPs, the redundant set of EST data, generated from
more than one genotype of a given species, are used
21. Characteristics of Genetic Molecular Markers
The development of GMMs, now permits a targeted approach for detection of
nucleotide diversity in genes controlling agronomic traits in plant populations
1. Trait Mapping
•Their use as diagnostic markers for the trait in the selection
2. Functional Diversity
•GMMs, especially genic SSRs, have been found useful for estimating genetic
relationship on one hand while at the same time these have provided
opportunities to examine functional diversity in relation to adaptive variation
3. Interspecific or Intergeneric Transferability
•GMMs is that these markers provide high degree of transferability among
distantly related species
•Transferability of GMM markers to related species or genera has now been
demonstrated in several studies
22.
23. Progress in crop genome sequencing and analysis
•Advances in sequencing crop genomes have mirrored the development of
sequencing technologies.
•Until 2010, Sanger sequencing of bacterial artificial chromosome (BAC)-based
physical maps was the predominant approach used to access crop genomes such as
rice, poplar and maize.
•The sorghum genome was the first crop genome to be sequenced completely by
the exclusive use of WGS sequence assemblies, which were then assessed for
integrity using high-density genetic maps and physical maps.
•Since 2012, analyses of the sequences of 12 crop genomes have been
published, accounting for nearly half of the total published. This explosion of
data has been driven by cheaper and more effective sequencing technologies
(primarily the Illumina and Roche 454 methods) coupled with increasingly
sophisticated sequence and assembly strategies, which are generally
delivered by large genome centers.
24. •NGS speed and capacity enable over
100 published plant genomes.
•Underserved specialty and orphan crop
genomic resources grow due to low cost
NGS.
•Double haploid and diploid ancestors
key to sequence complex plant
genomes.
•Polyploidy, heterozygosity and repeats
complicate plant genome assembly but
also underlie key agronomic traits.
•More than 100 plant genomes have
been sequenced since 2000, 63% of
which are crop species.
28. Initial genetic maps consisted of few and sparse markers, many of which were
anonymous markers (simple sequence repeats (SSR)) or markers based on
restriction fragment length polymorphisms (RFLP).
if a phenotype of interest was affected by genetic variation within the SSR1-SSR2
interval
the complete region would be selected with little information about its gene
content or allelic variation
the Whole genome sequencing of a closely related species enabled projection of
gene content onto the target genetic map
This allowed breeders to postulate the presence of specific genes on the basis of
conserved gene order across species (synteny), although this varies between
species and regions
Complete genome sequence in the target species provides breeders with an
unprecedented wealth of information that allows them to access and identify
variation that is useful for crop improvement
29. You have just
cloned a gene
Evolutionary
relationship?
-Phylogenetic
tree
-Accession #?
-Annotation?
Is it already in
databases?
-Sub-localization
-Soluble?
-3D fold
Protein
characteristics?
-% identity?
-Family member?
Is there similar
sequences?
-Alignments?
-Domains?
Is there conserved
regions?
Other
information?
-Expression profile?
-Mutants?
A critical failure of current bioinformatics is the lack of a single software
package that can perform all of these functions.
Applying algorithms to analyze genomics data
30. DNA (nucleotide sequences) databases
They are big databases and searching either one should produce
similar results because they exchange information routinely.
-GenBank (NCBI): http://www.ncbi.nlm.nih.gov
-DDBJ (DNA DataBase of Japan): http://www.ddbj.nig.ac.jp
-Yeast: http://yeastgenome.org
-Microbes: http://img.jgi.doe.gov/cgi-bin/pub/main.cgi
Specialized databases:Tissues, species…
-ESTs (Expressed Sequence Tags)
~at NCBI http://www.ncbi.nlm.nih.gov/dbEST
~at TIGR http://tigr.org/tdb/tgi
- ...many more!
31. They are big databases too:
-Swiss-Prot (very high level of annotation)
http://au.expasy.org/
-PIR (protein identification resource) the world's most
comprehensive catalog of information on proteins
http://www.pir.uniprot.org/
Translated databases:
-TREMBL (translated EMBL): includes entries that have
not been annotated yet into Swiss-Prot.
http://www.ebi.ac.uk/trembl/access.html
-GenPept (translation of coding regions in GenBank)
-pdb (sequences derived from the 3D structure
Brookhaven PDB) http://www.rcsb.org/pdb/
Protein (amino acid) databases
32. Cost - a major obstacle
Cost-efficiency has rarely been calculated
but GAS is more expensive for most traits
Exceptions include quality traits
Determined by:
Trait and method for phenotypic screening
Cost of glasshouse/field trials
Labour costs
Type of markers used
33. Genomic assisted features for future
breeding
Genomics has radically altered the scope of genetics by providing a
landscape of :-
their epigenetic states.
access to an enormous range of genetic variation.
the potential to measure gene expression directly.
with high precision and accuracy.
Superior breeding lines
Molecular markers associated with resistance to
biotic stresses and tolerance to abiotic stresses.
Alleles and haplotype information available on
germplasm set so that breeders can use informative
lines.
Set of well characterized disease resistance and
abiotic stress tolerance genes
Breeder-friendly genome database of Crops.
34. Challenges in genomics-
assisted crop improvement
Narrow genetic base in the primary gene
pool
Very few molecular (SSR) markers
Non-availability of appropriate germplasm
such as mapping populations
Intraspecific genetic map with low marker
density
Non-availability of trait-associated markers
in breeding
Issues of costs and expertise in molecular
breeding
Data Management
36. Draft genome sequence of chickpea (Cicer arietinum) provides
a resource for trait improvement (Varshney RK.,et al,2013)
Chickpea (Cicer arietinum) is the
second most widely grown legume
crop after soybean, accounting for a
substantial proportion of human
dietary nitrogen intake and playing
a crucial role in food security in
developing countries.
It is reported that the ~738Mb
draft whole genome shotgun
sequence, a kabuli chickpea variety,
which contains an estimated 28,269
genes.
37.
38. By taking Candidate genes for disease resistance and agronomic traits are
highlighted, including traits that distinguish the two main market classes of
cultivated chickpea—desi and kabuli. These data comprise a resource for chickpea
improvement through molecular breeding and provide insights into both genome
diversity and domestication.
To understand the genetic history among chickpea accessions, They resequenced
29 elite varieties from both desi and kabuli genotypes grown around the world,
and conducted genotyping by sequencing of 61 Cicer accessions from ten
countries.
To assess the proportion of the gene space captured in this draft genome
assembly , for this they mapped a 454/Roche transcriptome data set (>500 bp
read length), produced from the same CDC Frontier line and comprising 60,802
reads, to the genome assembly
On the basis of this analysis , they estimate gene coverage to be 90.8%.
Analysis of the draft genome assembly for core eukaryotic genes reveals
homologs for >98% of conserved genes in the assembly.
39. To evaluate the conservation of chickpea gene models in other plant species, used
BLAST to query the chickpea proteome against the proteomes of A. thaliana, M.
truncatula, G. max, Cajanus cajan and L. japonicus.
Using this analysis, proteins predicted for chickpea were most similar to those from
M. truncatula (89.7% of predicted chickpea proteins were similar to M. truncatula
proteins) and
A.thaliana (79.2% had similarity with A. thaliana proteins).
They also observed five instances in which organelle genome segments of >10 kb
had been integrated into chickpea pseudomolecules, consistent with findings in
both plant and animal genomes.
Genome organization and evolution
Approximately half (49.41%) of the chickpea genome is composed of transposable
elements and unclassified repeats, which is comparable to other sequenced
legumes:
M. truncatula (30.5%),
Pigeonpea (C. cajan, 51.6%)
Soybean (G. max,59%).
40. Fig. Shared and unique gene families in legume species chickpea, M. truncatula,
L. japonicus, soybean, pigeonpea; in millettioid and galegoids, and in legumes, A. thaliana
and grape.
Long-terminal repeat (LTR) retrotransposons are the most abundant
transposable element class, and cover >45% of the total nuclear genome
41. Genetic diversity among cultivated varieties and germplasm
With the objective of understanding genetic diversity in chickpea , they used
whole genome resequencing (WGRS) of 29 (17 desi and 12 kabuli) chickpea
breeding lines and released varieties collected from the leading chickpea-growing
countries. WGRS yielded 204.52 Gb of high-quality sequence data with an
average coverage of 9.5×, from which calculated the average pair wise nucleotide
diversity within population
This draft whole genome sequence of chickpea (CDC Frontier, a kabuli chickpea
variety) adds to the genomic resources available for legume research.
The Papilionaceae subfamily now has the draft or complete genome sequences of
two model species (M. truncatula and L. japonicus) and
three crop legume species (chickpea, soybean and pigeonpea).
The availability of these genome sequences should facilitate de novo assembly of
the genomes of other important but less-studied galegoid legume crops such as pea
(Pisum sativum), lentil (Lens culinaris) and faba bean (Vicia faba).
42. Furthermore, analyses by this objective such as
population structure,
Diversity, and
phylogenetic analyses
not only document the mixed use of desi and kabuli genotypes in
breeding, but also serve to identify regions (and candidate genes) across
the genome that might have been greatly affected by selection during
domesticationor breeding.
Fig. Phylogenetic
tree of seven
species.
44. Achievements and prospects of genomics-assisted breeding in three
legume crops of the semi-arid tropics(Mohan SM.,Gaur PM.,
Varshney RK., et al, 2013)
Legumes form an important constituent of food crops consumed globally and
complement cereal crops as a source of dietary protein. In addition to
providing important micronutrients to human beings, they also fix
atmospheric nitrogen, which consequently increase soil fertility and
production of other cereal crops.
Among several food crops, chickpea (Cicer
arietinum), pigeonpea (Cajanus cajan) and
groundnut or peanut (Arachis hypogaea)
are the leading legume crops to feed
underprivileged living in the semi-arid
tropics (SAT), which is also called “habitat
of the hungry”.Chickpea (Cicer arietinum
L.)
45. Genomic resources
Molecular markers and genotyping
platforms
Genomics-assisted breeding (GAB)
Marker-assisted recurrent
selection (MARS)
Genomic selection (GS)
Draft genome sequences,large-scale molecular markers,
construction of comprehensive genetic maps,
establishment of various marker-trait associations and
initiation of molecular breeding in these three crops.
Range of marker systems
hybridization-based Diversity Array Technology
(DArT)
sequence based markers (SNPs)
Integration and use of genomic tools in breeding
practices for developing superior lines with enhanced
biotic or abiotic stress tolerance and improved yield.
Involves estimation of marker effects from
genotyping F2 or F3 population and
phenotyping F2 derived F4 or F5 progenies,
followed by two or three recombination cycles
based on presence of marker alleles for small
effect QTLs .
Targets identification of superior lines with
higher breeding value in a breeding program
based on genome-wide marker profile data.
46. Fig. A coordinated and collaborative efforts on development and application of
genomic resources for crop improvement of SAT legumes.
47. This figure shows coordinated and collaborative efforts of ICRISAT and its partners, using
high-throughput sequencing and genotyping and modern breeding approaches, to develop
and apply genomic resources in crop improvement programs of three legume crops.
genomic and transcriptomic resources such as molecular markers, ESTs, genes,
transcriptome assemblies and genome sequences have been developed using Sanger and
next generation sequencing technology platforms
cost-effective,
low- capillary electrophoresis (SSR genotyping), ,
medium- iScan or BeadXpress systems and KASPar assays (SNP genotyping)
and high-throughput DArT genotyping platforms (panel on top).
A range of genetic resources (panel on right) are used using different genotyping
platforms to develop genetic map (center top left) as well as
for multi-location phenotyping for traits of interest to breeders (center top right).
Genotyping data and phenotyping data are used to identify the QTLs/markers associated
with target traits using QTL mapping or association mapping approaches (center down
left).
Genetic and QTL information subsequently are used in breeding program using modern
breeding programs such as marker-assisted back crossing (MABC) (center down right).
By using these modern breeding approaches, superior lines for target traits with enhanced
crop productivity are generated (panel on bottom).
‘orphan
legumes’
‘genomic resource
rich’
49. The peanut or groundnut (Arachis
hypogaea) is a species in
the family Fabaceae (Leguminosae) is the
third largest angiosperm family, containing
ca. 18,000 species attributed to 650 genera
(Zhu et al. 2005). Legumes are important to
world agriculture, as they provide biological
fixed nitrogen, break the cereal disease
cycles, and contribute to locally grown food
and feed, including forage (Stoddard et al.
2009).
Development and deployment of genomic resources for
groundnut improvement.(Varshney RK., etal., 2012)
51. With an objective to increase breeding efficiency for accelerated development of
superior genotypes, by ICRISAT and its partners have developed and deployed
thousands of genetic markers such as
SSRs (>6000),
DArTs (>15,000 features)
SNPs (90 KASP assays) in several genetic applications.
The above efforts resulted in development of many
genetic maps (82-198 loci),
consensus maps (>3600 loci) and
identification of QTLs for drought tolerance related traits (153
QTLs) and
foliar disease resistance (143 QTLs).
Efforts are underway to conduct genetic and QTL mapping for oil content,
oil/nutritional quality, seed dormancy, nodulation, disease resistance, drought
tolerance and pod yield.
52. Association mapping conducted using large scale genotyping
(4597 DArT features and 154 SSRs) and
multiple season phenotyping data (51 traits) identified
a total of 524 highly significant marker-trait associations (MTAs).
Further efforts are in progress to identify MTAs at high genetic resolution
through comprehensive genome-wide association studies (GWAS) in diverse
groundnut global germplasm sets (ICRISAT reference set, minicore collections
of USA and China).
Three elite cultivars (TAG 24, JL 24 and ICGV 91114) were improved through
MABC approach by introgressing a major QTL for rust resistance.
MABC efforts to develop lines with high oleate trait individually as well as
pyramiding with genes/QTLs for two foliar diseases (LLS and rust) are
underway. In addition, efforts have been initiated to deploy genomic selection
for improvement of complex traits such as yield under drought stress.
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55. Conclusion
Now a days, genomics-assisted breeding has shown its tremendous
successful for crop improvement in several crops, however these successes
have been largely restricted to temperate cereal and legume crops, and
others such as Eucalyptus, sugarcane, tomato and other vegetables crops.
Although it is clear that present stage of plant genomics research has great
potential to revolutionize the discipline of plant breeding, high costs invested
in associated with genomics research currently limit the implementation of
genomics-assisted crop improvement, especially for inbreeding or minor
crops. Marker-assisted breeding and selection will gradually domesticated
into ‘genomics-assisted breeding’ for crop improvement. Being a agriculture
rich country one should utilize this research technique keeping in mind about
how it will help full to a our farmers or Breeders.