Molecular Marker Techniques

MOLECULAR MARKER TECHNOLOGIES

http://en.wikipedia.org/wiki/Image:Chloroplastsfigure1.jpg

Outlines

Organization and flow of genetic information Molecular techniques to reveal genetic variation Type of molecular markers Which marker for what purpose Microsatellite marker Case study 1: using microsatellites to estimate gene

flow via pollen Case study 2: using microsatellites for individual-

specific DNA fingerprints

FLOW OF GENETIC INFORMATION

DNA molecule consists of two strands that wrap around each other to resemble a twisted ladder

A pairs with TC pairs with G

Deoxyribonucleic Acid (DNA): The molecule that encodes genetic information

Nuclear DNA: Diploid; biparental inherited; recombination occur; can be viewed as a huge ocean of largely nongenic DNA, with some tens of thousands of genes and gene clusters scattered around like small islands and archipelagos. A high proportion of this apparently nonfunctional DNA consists of repeated motifs and may be considered as junk DNA or selfish DNA

Choroplast DNA: Haploid; usually maternally inherited in angiosperms and paternally inherited in gymnosperms; typically ranging from 135 to 160 kb in size, is packed with genes and thus resembles the streamlined configuration of its cyanobacterial ancestral genome

Mitochondrial DNA: Haploid; typically maternally inherited; about 370 to 490 kb, about 10% of these sequences represent genes, another 10 to 26% were found to be made up of repetitive DNA, including retrotransposons. Thus, the majority of plant mtDNA sequences lack any obvious features of information

• Organism’s genomic DNAs are subjected to mutation as a result of normal cellular operations or interactions with environment

Biology of organism Genomes under consideration Types of mutations

• The rates of mutation are depending on:

• Mutations in genomic DNA can be classified into several categories:

GATCCGAGTGATCCGAGTAATCGCAATTAGCATCGCAATTAGCAGATCCGAGTGATCCGAGTGGTCGCAATTAGCATCGCAATTAGCA

Base substitutionBase substitution

GATCCGAGTAGATCCGAGTATCGCATCGCAATTAGCAATTAGCAGATCCGAGTAATTAGCAGATCCGAGTAATTAGCA

DeletionDeletion

GATCCGAGTATCGCAATTAGCAGATCCGAGTATCGCAATTAGCAGATCCGAGTATCGCAGATCCGAGTATCGCAGCGCATTAGCAATTAGCA

InsertionInsertion

GATCCGAGTATCGCAATTAGCAGATCCGAGTATCGCAATTAGCAGATCCGAGTATCGATCCGAGTATCTCTCGCGCAATTAGCAAATTAGCA

DuplicationDuplication

GATGATCCGCCGAGTATCGCAATTAGCAAGTATCGCAATTAGCAGATGATGCCGCCAGTATCGCAATTAGCAAGTATCGCAATTAGCA

InversionInversion

Through long evolutionary accumulation, many different instances of mutation as mentioned above should exist in any given species

The number and degree of the various types of mutations define the genetic diversity within a species

It has been widely recognized that loss of genetic diversity is a major threat for the maintenance and adaptive potential of species

• Example - if low genetic diversity, when a virulent form of a disease arises, many individuals may be susceptible and die

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• But as a result of natural genetic diversity within local plant populations, there may be some individuals that are at least partially resistant and there are able to survive and thus perpetuate the species

• For many plant species, ex situ and in situ conservation strategies have been developed to safeguard the extant of genetic diversity

• To manage this genetic diversity effectively the ability to identify genetic diversity is indispensable

• In addition, for this variation to be useful, it must be heritable and discernable; as recognizable phenotypic variation or as genetic mutation distinguishable through molecular marker technologies

Subsequently, mutation arises

genetic variation at DNA will cause variation at the

protein level

Protein markers

MutationMutation arises

genetic variation at the DNA level

DNA markers

A sequence of DNA or protein that can be screened to reveal key attributes of its state or composition

and thus used to reveal genetic variation

Definition of molecular markers

• Four major molecular techniques are commonly applied to reveal genetic variation. These are:

Polymerase chain reaction (PCR) Electrophoresis Hybridization DNA sequencing

POLYMERASE CHAIN REACTIONPCR is a procedure used to amplify (make multiple copies of) a specific sequence of DNA

The method was invented by Kary Banks Mullis in 1983, for which he received the Nobel Prize in Chemistry ten years later

three temperature-controlled steps

ELECTROPHORESISELECTROPHORESIS

Migration rate depend on electrical charge and size

The term The term 'electrophoresis' 'electrophoresis' literally means "to carry with literally means "to carry with electricity"electricity"

Technique for separating the components of a mixture of Technique for separating the components of a mixture of charged molecules (proteins, DNAs, or RNAs) in an electric charged molecules (proteins, DNAs, or RNAs) in an electric field within a gel or other support field within a gel or other support

HYBRIDIZATION

One of the most commonly used nucleic acid hybridization techniques is Southern blot hybridization

Southern blotting was named after Edward M. Southern who developed this procedure at Edinburgh University in the 1975

SEQUENCINGThe process of determining the order of the nucleotide bases along a DNA strand is called sequencing

In 1977, 24 years after the discovery of the structure of DNA, two separate methods for sequencing DNA were developed: chain termination method and chemical degradation method

Chain elongation proceeds until, by chance, DNA polymerase inserts a dideoxynucleotide, blocking further elongation

Principle: single-stranded DNA molecules that differ in length by just a single nucleotide can be separated from one another using PAGE

Recent detection techniquesTaqMan – a probe used to detect specific sequences in PCR products by employing 5’ to 3’ exonuclease activity of the Taq DNA polymerase

Microarray Technology – a high throughput screening technique based on the hybridization between oligonucleotide probes (genomic DNA or cDNA) and either DNA or mRNA

Pyrosequencing – refers to sequencing by synthesis, a simple to use technique for accurate analysis of DNA sequences

TYPES OF MOLECULAR MARKERS• Due to rapid developments in the field of molecular genetics, a

variety of molecular markers has emerged during the last few decades

Biochemical marker

Allozyme

Non-PCR based marker

RFLP, Minisatellite (VNTR)

PCR based marker

Microsatellite, RAPD, AFLP, CAPS (PCR-RFLP), ISSR, SSCP, SCAR,

SNP, etc.

Traditional marker systems

PCR generation: in vitro DNA amplification

Allozyme (biochemical marker)

Technique: Electrophoresis and enzyme staining

• The alternative forms of a particular protein visualized on a gel as bands of different mobility. Polymorphism due to mutation an amino acid has been replaced, the net electric charge of the protein may have been altered

RFLP (Non-PCR based marker)

Techniques: Electrophoresis and hybridization

• Targets variation in DNA restriction sites and in DNA restriction fragments. Sequence variation affecting the occurrence (absence or presence) of endonuclease recognition sites is considered to be main cause of length polymorphisms

RAPD (PCR-based marker)

Techniques: PCR and Electrophoresis

Uses primers of random sequence to amplify DNA fragments by PCR. Polymorphisms are considered to be primarily due to variation in the primer annealing sites, but they can also be generated by length differences in the amplified sequence between primer annealing sites

AFLP (PCR-based marker)


• A variant of RAPD. Following restriction enzyme digestion of DNA, a subset of DNA fragments is selected for PCR amplification and visualization

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Microsatellite (PCR based marker)


• Targets tandem repeats of a small (1-6 base pairs) nucleotide repeat motif. Polymorphism due to the number of tandem repeats

Other markers • Cleaved Amplified Polymorphic Sequence (CAPS/PCR-RFLP)• Inter Simple Sequence Repeat (ISSR)• Single-strand conformation Polymorphism (SSCP)• Sequence Characterized Amplified Region (SCAR)

More recent markers• Single-Nucleotide Polymorphism (SNP)• Retrotransposon-based markers

Sequence-Specific Amplified Polymorphism (S-SAP) Inter-retrotransposon Amplified Polymorphism (IRAP) Retrotransposon-Microsatellite Amplified Polymorphism (REMAP) Retrotransposon-Based Insertional Polymorphism (RBIP)

Weising, K., Nybom, H., Wolff, K. and Kahl, G. 2005. DNA Fingerprinting in Plants, Priciples, Methos, and Applications. 2nd Edition. CRC Press, Boca Raton, Florida, USA.

Spooner, D., van Treuren, R. and de Vicente, M.C. 2005. Molecular markers for genebank management. IPGRI Technical Bulletin No. 10. International Plant Genetic Resources Institute, Rome, Italy.

Henry, R.J. 2001. Plant Genotyping: The DNA Fingerprinting of Plants. CAB International Publishing, Wallingford, U.K.

Markers differ with respect to important features:

• Genomic abundance• Polymorphism level• Locus specificity

• Reproducibility

• Technical requirements

• Financial investment

• Codominance or dominace

Dominant marker: A marker shows dominant inheritance with

homozygous dominant individuals indistinguishable from heterozygous

individuals

Codominant marker:A marker in which both alleles are

expressed, thus heterozygous individuals can be distinguished from either

homozygous state

None of the available techniques is superior to all others for a wide range of applications, but the key-question rather is

which marker to use in which situation

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• Within and among population variation – Allozyme, SSR, AFLP and RAPD

• Genetic Linkage Mapping – AFLP, RAPD, Allozyme, RFLP, SSR, CAPS, SNP

• Mating system study – Allozyme or microsatellite

• Estimating gene flow via pollen and seed – Microsatellite (SSR)

• Phylogeography – cpSSR

• Clonal identification – AFLP or RAPD

• Polyploidy – multilocus dominant marker (AFLP)

• Phlogenetic study – conserve within species (DNA sequencing)

Intraspecific (among individuals) – markers target less conserve region

Interspecific (among species) – markers target more conserve region

• A framework for selecting appropriate techniques for plant genetic resources conservation can be referred to:

Karp, A., Kresovich, B., Bhat, K.V., Ayad, W.G. and Hodgkin, T. 1997. Molecular Tools in Plant Genetic Resources Conservation: A Guide to the Technologies. IPGRI Technical Bulletin No. 2. International Plant Genetic Resources Institute, Rome, Italy

Microsatellite marker

What are microsatellite? Where are microsatellites found? How do microsatellites mutate? Abundance in genome Why do microsatellite exist? Models of mutation Development of microsatellite primers Genotyping procedure Advantages Disadvantages Applications

What are microsatellite?• Tandem repeated sequences with a 1-6 repeat motif

Dinucleotide (CT)6 - CTCTCTCTCTCT Trinucleotide (CTG)4 - CTGCTGCTGCTG Tetranucleotide(ACTC)4 - ACTCACTCACTCACTC

• Synonymous to SSR and STR; Depending on nature of repeat tract, SSR can further divided into four categories:

Perfect repeat when repeat tract pure for one motif CTCTCTCTCTCT

Compound SSR when repeat tract pure for two motifs CTCTCTCACACA

Imperfect SSR if single base substitution CTCTCTACTCTCT

Region of cryptic simplicity if complex but repetitive structure GTGTCACAGAGT

Where are microsatellites found?

Majority are in non-coding region

How do microsatellites mutate?

DNA polymerase slippage Unequal crossing over

• Microsatellites alleles change rather quickly over time E. coli – 10-2 events per locus per replication Drosophila – 6 X 10-6 events per locus per generation Human – 10-3 events per locus per generation

Abundance in genome

• Microsatellites have been found in every organism studied so far

• Most frequent in human > insect > plant > yeast > nematode

GA/CT DipterocarpGA/CT & CA/GT Conifer

• Most common dinucleotide:

CA/GT Human

Why do microsatellite exist?

• Majority are found in non-coding regions; thought no selective pressure; as "junk" DNA?

• In plant, high density of SSRs were found in close proximity to coding regions; regulatory properties

• Regulate gene expression and protein function, e.g., human diseases caused by expansions of polymorphic trinucleotide repeats in genes fragile X and myotonic dystrophy

• High level of polymorphism; a necessary source of genetic variation

Models of Mutation

• Size matters when doing statistical tests of population substructuring

• The mutation model still unclear but stepwise mutation appears to be the dominant force creating new alleles in the few model organisms studied to date

Stepwise Mutation Model (SMM) - when SSRs mutate, they gain or lose only one repeat

Two alleles differ by one repeat are more closely related than alleles differ by many repeats

CTCTCT

CTCTCTCT

CTCTCTCTCT

CTCTCT

CTCTCTCT

CTCTCTCTCT

• Several statistics based on estimates of allele frequencies (e.g., Fst & Rst) rely explicitly on a mutation model

Development of microsatellite primers

• Standard method to isolate microsatellites from clones

Creation of a small insert genomic library Library screening by hybridization DNA sequencing of positive clones Primer design and PCR analysis Identification of polymorphisms

• Can be time consuming and expensive. May be obtained by screening sequence in databases or screening libraries of clones

• This approach can be extremely tedious and inefficient for species with low microsatellite frequencies

• Alternative strategies to overcome Selective hybridization using nylon membrane Selective hybridization using steptavidin coated beads RAPD based Primer extension

Genotyping procedure

PCR

Electrophoresis

Agarose Denaturing PAGE CapillaryPAGE

Visualization

Silver staining

SybrGreen staining

Autoradio-graphy

Fluorescent dyes

• The use of fluorescently labeled primers, combine with automated electrophoresis system greatly simplified the analysis of microsatellite allele sizes

Primer1

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Advantages

Low quantities of template DNA required (10-100 ng) High genomic abundance Random distribution throughout the genome High level of polymorphism Band profiles can be interpreted in terms of loci and alleles Codominance of alleles Allele sizes can be determined with an accuracy of 1 bp,

allowing accurate comparison across different gels High reproducibility Different SSRs may be multiplexed in PCR or on gel Wide range of applications Amenable to automation

Disadvantages

High development costs in case primers are not yet available. Primers might be species specific

Heterozygotes may be misclassified as homozygotes when null-alleles occur due to mutation in the primer annealing sites

Stutter bands on gels may complicate accurate scoring of polymorphisms

Underlying mutation model (infinite alleles model or stepwise mutation model) largely unknown

Homoplasy due to different forward and backward mutations may underestimate genetic divergence

Applications

Population genetics: investigations within a genus of centers of origin, genetic diversity, population structures and relationships among species

Parentage analysis: seed orchard monitoring, mating systems and gene flow via pollen & seed

Fingerprinting: clone confirmation and individual-specific fingerprints

Genome mapping - Constructing full coverage or QTL maps Comparative mapping - Genome structure, framework maps,

or transferring trait and marker data among species

Generally, high mutation rate makes them informative and suitable for intraspecific studies but unsuitable for studies

involving higher taxonomic levels

Case study 1: Using microsatellites to estimate

gene flow via pollen

Effective breeding unit?

Pollen flow distance? Outcrossing rate?

Shorea leprosula Shorea parvifolia

Methodology

Sample collection

DNA extraction

SSRs analysis

1. Gene flow: exclusion and likelihood approaches2. Effective breeding unit: Nason et al. (1998)3. Model of pollen dispersal to get maximum pollen

flow distance

SSRs development

Data analysis

No. of clones

sequenced

No. of clones with

SSR (%)

No. of unique SSR clones (%)

Core sequence (no. of clones; % & repeat times)

624 592 (94.9)

315 (53.2)

CT/GA (266; 84.4 & 6-78)GT/CA (29; 9.2 & 8-46) Others (20; 6.4 & 6-40)

Microsatellite Loci

Locus Primer sequence (5’ – 3’)

Repeat motif Length N Size

range He PIC

lep074a F: ATC ACC AAG TAC CTA TCA TCAR: GCA ATG GCA CAC AGT CTA TC (CT)11 124 11 110-130 0.824 0.791

lep079 F: GTT GTC TGT TCT TAC CAG GAA GR: GCA TAA GTA TCG TCG CCA (CT)11 162 13 155-198 0.830 0.798

lep111a F: GGA AAC TAC TGG AGC AGA GACR: GGT GGG TTA TGG AGA ATG AG (GA)14 152 12 138-154 0.855 0.821

lep118 F: AAA GCG TAC AAA TTC ATC AR: CTA TTG GTT GGG TCA GAA GG (GA)16 170 15 145-176 0.892 0.861

lep280 F: GCA ACT AAA ATG GAC CAG AR: GAG TAA GGT GGC AGA TAT AGA G (CT)7 119 11 107-137 0.851 0.816

lep384 F: CCA AGA CAA CTC AAT CCT CAR: AGA TGA AGG TGT TGC TGT G (CT)13 206 14 191-219 0.657 0.632

lep562 F: TGA TTT GGG TGG TTG TAGR: TAT TAC ATT TTT CAA GTC AAG TC (GT)8 164 12 154-180 0.883 0.852

Lee, S.L. et al. 2004. Isolation and characterization of 21 microsatellite loci in an important tropical tree Shorea leprosula and their applicability to S. parvifolia. Molecular Ecology Notes 4: 222-225

50 ha demographic plot in Pasoh Forest Reserve

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Pasoh Forest Reserve - 50-ha plot (190 individuals of S. leprosula and 102 of S. parvifolia 27 cm dbh within the 50-ha plot)

• Shorea leprosula – 9 loci (Pe = 0.999) lep074a, lep384, lep111a, lep118, lep280,

lep267, lep294, lep475 & lep562 PCR (500 x 9 = 4500 reactions)

• Shorea parvifoila – 6 loci (Pe = 0.999) lep074a, lep384, lep111a, lep118, lep280 &

lep294 PCR (360 x 6 = 2160 reactions)

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S. parvifolia (SP35)

Mother tree (no. of seed analyzed)

Mean distance between MT

% outcrossing (no. of seed)

% pollen outside plot

Mean pollen flow distance

Shorea leprosulaSL048 (45) 267.1 136.2 93.3 (42) 20.0 (9) 152.9 99.6SL062 (44) 363.2 151.6 88.6 (39) 20.5 (9) 302.6 188.9 SL074 (48) 259.2 151.2 85.4 (41) 18.8 (9) 148.6 187.2SL075 (43) 292.6 145.8 67.4 (29) 18.6 (8) 173.1 103.8SL084 (46) 512.6 228.3 82.6 (38) 23.9 (11) 448.2 245.3SL109 (45) 343.7 158.8 95.6 (43) 33.3 (15) 285.0 154.5SL160 (44) 567.1 243.1 81.8 (36) 31.8 (14) 580.3 288.4Mean 372.2 121.6 85.0 9.3 23.8 6.2 298.7 164.0Shorea parvifoliaSP009 (32) 309.0 166.5 59.4 (19) 9.4 (3) 61.9 100.5SP014 (48) 307.7 165.1 62.5 (30) 14.6 (7) 105.1 140.9SP020 (42) 348.7 172.2 85.6 (36) 33.3 (14) 194.0 146.7SP022 (47) 239.6 133.2 72.3 (34) 21.3 (10) 148.2 125.0SP025 (46) 376.2 192.4 56.5 (26) 19.6 (9) 317.1 277.0SP035 (44) 244.2 139.9 22.7 (10) 2.3 (1) 185.0 159.7Mean 304.2 54.7 59.8 21.1 16.8 10.7 168.6 88.1

Mother tree (no. of seed analyzed)

Breeding unit parameters

Size (individual) Area (ha) Radius (m)

Shorea leprosulaSL048 (45) 203.6 63.6 450.1SL062 (44) 208.0 65.0 454.9SL074 (48) 205.0 64.1 451.6SL075 (43) 221.0 69.0 468.8SL084 (46) 225.2 70.4 473.3SL109 (45) 245.7 76.8 494.4SL160 (44) 261.8 81.8 510.3Mean 224.3 22.1 70.1 6.9 471.9 23.0Shorea parvifoliaSP009 (32) 81.9 59.4 434.7SP014 (48) 90.0 65.2 455.6SP020 (42) 112.9 81.8 510.3SP022 (47) 97.8 70.8 474.8SP025 (46) 105.5 76.5 493.4SP035 (44) 76.7 55.6 420.5Mean 94.1 13.9 68.2 10.1 464.9 34.5

A:\data\pollen curve testing tembaga.xlsRank 2 Eqn 8157 Exponential(a,b)

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0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

Freq

uenc

y

Negative exponential curve y = ae(-x/c)

Moderate pollen flow (150 – 300 m) – Thrips as pollinators

Predominant outcrossing (85%) & mix-mating (60%)

Model for pollen dispersal – negative exponential model

Optimum population size for conservation - breeding unit area & breeding unit size obtained (about 70 ha)

Conclusion

Case study 2: Using microsatellites for individual-

specific DNA fingerprints

In forensic applications in forestry and chain of custody certification, two types of databases are required

To track the illegal log into its original population

Required fingerprinting databases for population

identification

To match the illegal log into its original stump

Required fingerprinting databases for individual

identification

DNA markers to match the illegal log into its original stump

Log being stolen / Illegal loggingCollect sample for DNA extraction

• Perform DNA analysis using DNA markers• Comparison of DNA profiles of log & stump• If the same, they are from the same tree

Stump being left behindCollect sample for DNA extraction

• However, In DNA testimony, it is necessary to provide an estimate of the weight of the evidence

• Three possible outcomes of a DNA test: no match, inconclusive, or MATCH between samples examined

• If MATCH, it would not be scientifically justifiable to speak of a match as poor proof of identity in the absence of underlying data that permit some reasonable estimate of how rare the matching characteristics actually are

• Therefore, in forensic casework, a population database must be established for statistical evaluation of the evidence to extrapolate the possibility of a random match

Random MATCH!!

Neobalanocarpus heimii

Methodology

Sample collection

DNA extraction

SSRs analysis

Comprehensive DNA fingerprinting databases of N. heimii generated for individual identification

throughout P. Malaysia

SSRs screening

Data analysis

BEn Sun

Pia

Bub

Chi

Jel

GBa

LebHTBHTA

PRaRDa

Ter

RTuLak

BTiLen Ke

m

Ber

Les

Gom SLa

AmpPas

Pel

Lab LeBLeA

PaAPaB

KEDAHBkt. Enggang (BEn) Sungkop (Sun)

PERAKPiah (Pia) Bubu (Bub)Chikus (Chi)

SELANGORSg Lalang (SLa)Ampang (Amp)Gombak (Gom)

N. SEMBILANPasoh (Pas)Pelangai (Pel)

JOHORLabis (Lab) Panti C16 (PaA)Panti C68 (PaB)Lenggor C32 (LeA)Lenggor C76 (LeB)

KELANTANLebir (Leb) Jeli (Jel) G. Basor (GBa)

TERENGGANURambai Daun (RDa)H. Terengganu C31 (HTA)H. Terengganu C14A (HTB)Pasir Raja (PRa)

PAHANGLesong (Les)Bkt. Tinggi (BTi)Rotan Tunggal (RTu)Tersang (Ter)Lentang (Len)Lakum (Lak)Kemasul (Kem)Berkelah (Ber)

Sample collection

SSRs screening

51 SSR primer pairs developed for dipterocarps• Neobalanocarpus heimii (6) (Iwata et al. 2000)• Shorea lumutensis (2) (Lee et al. 2006) • Shorea leprosula (21) (Lee et al. 2004a)• Hopea bilitonensis (15) (Lee et al. 2004b)• Shorea curtisii (7) (Ujino et al. 1998)

Specific amplificationPeak: Scan 1583 Size 118.12 Height 111 Area 616

106 108 110 112 114 116 118 120 122 124 126 128 130 132 134 136 138 140 142 144 146 148 150 152 154

24b.fsa 24 Blue

100

200

25b.fsa 25 Blue

204060

26b.fsa 28 Blue

100

200

300

27b.fsa 31 Blue

20406080

28b.fsa 34 Blue

20406080

29b.fsa 25 Blue

50

100

30b.fsa 28 Blue

306090

31b.fsa 31 Blue

20406080

32b.fsa 34 Blue

100200300


92 94 96 98 100 102 104 106 108 110 112 114 116 118 120 122 124 126 128 130 132 134 136 138 140 017_01.fsa 1 Blue

1000

2000

3000

107.62 111.87

018_03.fsa 3 Blue

1000

2000

109.75 116.16

019_05.fsa 5 Blue

1000

2000

3000

107.69

020_07.fsa 7 Blue

2000

4000

109.78

021_09.fsa 9 Blue

1000

2000

109.78 111.88

022_11.fsa 11 Blue

500

10001500

109.69 118.45

023_13.fsa 13 Blue

1000

2000

103.36 107.59

P e a k : S c a n 1 7 8 7 S i z e 1 4 4 . 7 9 H e i g h t 4 2 1 A r e a 2 0 3 8

122 124 126 128 130 132 134 136 138 140 142 144 146 148 150 152 154 156 158 160 162 164 166 168 170 172 174 176 178 180 01a.f sa 1 Blue

200

400

146.83 150.89

02a.f sa 4 Blue

200040006000

146.71

03a.f sa 7 Blue

2000

40006000

146.83

04a.f sa 10 Blue

200040006000

150.77

05a.f sa 13 Blue

2000

4000

6000

146.81 150.88

06a.f sa 16 Blue

20004000

6000

150.77

07a.f sa 19 Blue

100020003000

146.81 150.88

Maternal genotype

Half-sib genotypes

Qualitative observations (each progeny possessed at least one maternal allele) to support the postulation of single-locus mode of inheritance

Mode of inheritance

Null allele

Homozygote excess (MICROCHECKER; Van Oosterhout et al. 2004)

Examine patterns of inheritance If any Individuals repeatedly fail to amplify any

alleles at just one locus while other loci amplify normally

H Shc09 (CT)n ? (A)nAllele 186a GGAAAAAAAAAAAAAAAAAA........TACGTACTTTTCGTTTTAGTTACGTTTTTCAATACCAAGAGA 70Allele 186b GGAAAAAAAAAAAAAAAAAA........TACGTACTTTTCGTTTTAGTTACGTTTTTCAATACCAAGAGAAllele 186c GGAAAAAAAAAAAAAAAAAA........TACGTACTTTTCGTTTTAGTTACGTTTTTCAATACCAAGAGAAllele 187 GGAAAAAAAAAAAAAAAAAAA.......TACGTACTTTTCGTTTTATTTACGTTTTTCAATACCAAGAGAAllele 194 GGAAAAAAAAAAAAAAAAAAAAAAAAAATACGTACTTTTCGTTTTAGTTACGTTTTTCAATACTAAGAGA

G Sle605 (GA)n ? (GA)n(CA)n(GA)nAllele 118a CCCGAGGAAGGGGGCAGAGAGACACAGAGAGAGAGAGAGA....GGCAGATGGAGGGAC.GGCGACAGCA 70Allele 118b CCCGAGGAAGGGGGCAGAGAGACACAGAGAGAGAGAGAGA....GGCAGATGGAGGGAC.GGCGACAGCAAllele 118c CCCGAGGAAGGGGGCAGAGAGACACAGAGAGAGAGAGAGA....GGCAGATGGAGGGAC.GGCGACAGCAAllele 119 CCCGAGGAAGGGGGCAGAGAGACACAGAGAGAGAGAGAGA....GGCAGATGGAGGGACCAGCGACAGCAAllele 121 CCCGAGGAAGGGGGCAGAGA..CACAGAGAGAGAGAGAGAGAGAGGCAGATGGAGGGACCAGCGACAGCA

F Sle392 (GA)n ? (TA)n(GA)n Allele 182a CTGAGCTATGAATGAAATAATTCAATATATATATA....GAGAGAGAGAGA....GGAGGTGAGGCCCAC 70Allele 182b CTGAGCTATGAATGAAATAATTCAATATATATATA....GAGAGAGAGAGA....GGAGGTGAGGCCCACAllele 182c CTGAGCTATGAATGAAATAATTCAATATATATATA....GAGAGAGAGAGA....GGAGGTGAGGCCCACAllele 188 CTGAGCTATGAATGAAATAATTCAATATATATATATATAGAGAGAGAGAGAGA..GGAGGTGAGGCCCACAllele 190 CTGAGCTATGAATGAAATAATTCAATATATATATATATAGAGAGAGAGAGAGAGAGGAGGTGAGGCCCAC

E Hbi161 (GGA)n ? (GGGAGA)n (GGA)n HOMOPLASYAllele 96a GACGCCG.CCGAAGGGGGAAAGGGAGAGGGAGA......GGAGGAGGAGGAGGAGAGTGA 60Allele 96b GACGCCG.CCGAAGGGGGAGAGGGAGAGGGAGA......GGAGGAGGAGGAGGAGAGTGAAllele 96C GACGCCG.CCGAAGGGGGAGAGGGAGAGGGAGA......GGAGGAGGAGGAGGAGAGTGAAllele 99 GACGCCG.CCGAAGGGGGAGAGGGAGAGGGAGAGGGAGAGGAGGAGGAGGA...GAGTGAAllele 100 GACGCCGCCCGAAGGGGGAGAGGGAGAGGGAGAGGGAGAGGAGGAGGAGGA...GAGTGA

H Shc09 (CT)n ? (A)nAllele 186a GGAAAAAAAAAAAAAAAAAA........TACGTACTTTTCGTTTTAGTTACGTTTTTCAATACCAAGAGA 70Allele 186b GGAAAAAAAAAAAAAAAAAA........TACGTACTTTTCGTTTTAGTTACGTTTTTCAATACCAAGAGAAllele 186c GGAAAAAAAAAAAAAAAAAA........TACGTACTTTTCGTTTTAGTTACGTTTTTCAATACCAAGAGAAllele 187 GGAAAAAAAAAAAAAAAAAAA.......TACGTACTTTTCGTTTTATTTACGTTTTTCAATACCAAGAGAAllele 194 GGAAAAAAAAAAAAAAAAAAAAAAAAAATACGTACTTTTCGTTTTAGTTACGTTTTTCAATACTAAGAGA

G Sle605 (GA)n ? (GA)n(CA)n(GA)nAllele 118a CCCGAGGAAGGGGGCAGAGAGACACAGAGAGAGAGAGAGA....GGCAGATGGAGGGAC.GGCGACAGCA 70Allele 118b CCCGAGGAAGGGGGCAGAGAGACACAGAGAGAGAGAGAGA....GGCAGATGGAGGGAC.GGCGACAGCAAllele 118c CCCGAGGAAGGGGGCAGAGAGACACAGAGAGAGAGAGAGA....GGCAGATGGAGGGAC.GGCGACAGCAAllele 119 CCCGAGGAAGGGGGCAGAGAGACACAGAGAGAGAGAGAGA....GGCAGATGGAGGGACCAGCGACAGCAAllele 121 CCCGAGGAAGGGGGCAGAGA..CACAGAGAGAGAGAGAGAGAGAGGCAGATGGAGGGACCAGCGACAGCA

F Sle392 (GA)n ? (TA)n(GA)n Allele 182a CTGAGCTATGAATGAAATAATTCAATATATATATA....GAGAGAGAGAGA....GGAGGTGAGGCCCAC 70Allele 182b CTGAGCTATGAATGAAATAATTCAATATATATATA....GAGAGAGAGAGA....GGAGGTGAGGCCCACAllele 182c CTGAGCTATGAATGAAATAATTCAATATATATATA....GAGAGAGAGAGA....GGAGGTGAGGCCCACAllele 188 CTGAGCTATGAATGAAATAATTCAATATATATATATATAGAGAGAGAGAGAGA..GGAGGTGAGGCCCACAllele 190 CTGAGCTATGAATGAAATAATTCAATATATATATATATAGAGAGAGAGAGAGAGAGGAGGTGAGGCCCAC

E Hbi161 (GGA)n ? (GGGAGA)n (GGA)n HOMOPLASYAllele 96a GACGCCG.CCGAAGGGGGAAAGGGAGAGGGAGA......GGAGGAGGAGGAGGAGAGTGA 60Allele 96b GACGCCG.CCGAAGGGGGAGAGGGAGAGGGAGA......GGAGGAGGAGGAGGAGAGTGAAllele 96C GACGCCG.CCGAAGGGGGAGAGGGAGAGGGAGA......GGAGGAGGAGGAGGAGAGTGAAllele 99 GACGCCG.CCGAAGGGGGAGAGGGAGAGGGAGAGGGAGAGGAGGAGGAGGA...GAGTGAAllele 100 GACGCCGCCCGAAGGGGGAGAGGGAGAGGGAGAGGGAGAGGAGGAGGAGGA...GAGTGA

Repeat motif

Dinucleotide repeats (CT)n to mononucleotide repeats (A)n

D Nhe018 (CT)n → (CT)n(CTAT)n

Allele137a CGCTCTCTCTCTCTCTCTCTCTCT..CTATCTATCTATCTAT................CTGTGTCTCTCC 70Allele137b CGCTCTCTCTCTCTCTCTCTCTCT..CTATCTATCTATCTAT................CTGTGTCTCTCCAllele137c CGCTCTCTCTCTCTCTCTCTCTCT..CTATCTATCTATCTAT................CTGTGTCTCTCCAllele139 CGCTCTCTCTCTCTCTCTCTCTCTCTCTATCTATCTATCTAT................CTGTGTCTCTCCAllele149 CGCTCTCTCTCTCTCTCTCT......CTATCTATCTATCTATCTATCTATCTATCTATCTGTGTCTCTCC

C Nhe015 (TC)n(AC)n HOMOPLASY

Allele147a AAGACCAGGTCTCTCTCTCTCTCTCTCTCTCTGTCTCTC....ACACACACACACACAC......ATTCA 70Allele147b AAGACCAGGTCTCTCTCTCTCTCTCTCTCTCTGTCTCTC....ACACACACACACACAC......ATTCA Allele147c AAGACCAGGTCTCTCTCTCTCTCTCTCTCTCTCTCTCTCTCTCACACACACACAC..........ATTCAAllele149 AAGACCAGGTCTCTCTCTCTCTCTCTCTCTCTCTCTCTCTCTCACACACACACACAC........ATTCAAllele153 AAGACCAGGTCTCTCTCTCTCTCTCTCTCTCTCTCTCTC....ACACACACACACACACACACACATTCA

B Nhe011 (GA)n HOMOPLASY

Allele164a AAAAGAGAAACAACCATCTTTAAAGAG.AAAAAGGAGGGATAGAGAGAGAGAGAGAGA..........AG 70Allele164b AAAAGAGAAACAACCATCTTTAAAGAG.AAAAAGGAGGGAGAGAGAGAGAGAGAGAGA..........AGAllele164c AAAAGAGAAACAACCATCTTTAAAGAG.AAAAAGGAGGGAGAGAGAGAGAGAGAGAGA..........AGAllele165 AAAAGAGAAACAAGCATCTTTAAAGAGGAAAAAGAAAAGAGAGAGAGAGAGAGAGAGA..........AGAllele174 AGAAGAGAAACAAGCATCTTTAAAGAG.AAAAAGAAAAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAAG

A Nhe005 (CT)nAllele115a TGAATTGTTAGCAGCCTGAGCTTGAGCCTGATTTGAGCTCTCTCTCTCTCTCTCTCTCTCT........A 70Allele115b TGAATTGTTAGCAGCCTGAGCTTGAGCCTGATTTGAGCTCTCTCTCTCTCTCTCTCTCTCT........AAllele115c TGAATTGTTAGCAGCCTGAGCTTGAGCCTGATTTGAGCTCTCTCTCTCTCTCTCTCTCTCT........AAllele117 TGAATTGTTAGCAGCTTGAGCTTGAGCCTGATTTGAGCTCTCTCTCTCTCTCTCTCTCTCTCT......AAllele123 TGAATTGTTAGCAGCCTGAGCTTGAGCCTGATTTGAGCTCTCTCTCTCTCTCTCTCTCTCTCTCTCTCTA

D Nhe018 (CT)n → (CT)n(CTAT)n

Allele137a CGCTCTCTCTCTCTCTCTCTCTCT..CTATCTATCTATCTAT................CTGTGTCTCTCC 70Allele137b CGCTCTCTCTCTCTCTCTCTCTCT..CTATCTATCTATCTAT................CTGTGTCTCTCCAllele137c CGCTCTCTCTCTCTCTCTCTCTCT..CTATCTATCTATCTAT................CTGTGTCTCTCCAllele139 CGCTCTCTCTCTCTCTCTCTCTCTCTCTATCTATCTATCTAT................CTGTGTCTCTCCAllele149 CGCTCTCTCTCTCTCTCTCT......CTATCTATCTATCTATCTATCTATCTATCTATCTGTGTCTCTCC

C Nhe015 (TC)n(AC)n HOMOPLASY

Allele147a AAGACCAGGTCTCTCTCTCTCTCTCTCTCTCTGTCTCTC....ACACACACACACACAC......ATTCA 70Allele147b AAGACCAGGTCTCTCTCTCTCTCTCTCTCTCTGTCTCTC....ACACACACACACACAC......ATTCA Allele147c AAGACCAGGTCTCTCTCTCTCTCTCTCTCTCTCTCTCTCTCTCACACACACACAC..........ATTCAAllele149 AAGACCAGGTCTCTCTCTCTCTCTCTCTCTCTCTCTCTCTCTCACACACACACACAC........ATTCAAllele153 AAGACCAGGTCTCTCTCTCTCTCTCTCTCTCTCTCTCTC....ACACACACACACACACACACACATTCA

B Nhe011 (GA)n HOMOPLASY

Allele164a AAAAGAGAAACAACCATCTTTAAAGAG.AAAAAGGAGGGATAGAGAGAGAGAGAGAGA..........AG 70Allele164b AAAAGAGAAACAACCATCTTTAAAGAG.AAAAAGGAGGGAGAGAGAGAGAGAGAGAGA..........AGAllele164c AAAAGAGAAACAACCATCTTTAAAGAG.AAAAAGGAGGGAGAGAGAGAGAGAGAGAGA..........AGAllele165 AAAAGAGAAACAAGCATCTTTAAAGAGGAAAAAGAAAAGAGAGAGAGAGAGAGAGAGA..........AGAllele174 AGAAGAGAAACAAGCATCTTTAAAGAG.AAAAAGAAAAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAAG

A Nhe005 (CT)nAllele115a TGAATTGTTAGCAGCCTGAGCTTGAGCCTGATTTGAGCTCTCTCTCTCTCTCTCTCTCTCT........A 70Allele115b TGAATTGTTAGCAGCCTGAGCTTGAGCCTGATTTGAGCTCTCTCTCTCTCTCTCTCTCTCT........AAllele115c TGAATTGTTAGCAGCCTGAGCTTGAGCCTGATTTGAGCTCTCTCTCTCTCTCTCTCTCTCT........AAllele117 TGAATTGTTAGCAGCTTGAGCTTGAGCCTGATTTGAGCTCTCTCTCTCTCTCTCTCTCTCTCT......AAllele123 TGAATTGTTAGCAGCCTGAGCTTGAGCCTGATTTGAGCTCTCTCTCTCTCTCTCTCTCTCTCTCTCTCTA

Size homoplasy

51 SSR primer pairsSpecific

amplification

Mode of inheritance

Null allele Repeat

motif

Size homoplasy

16 SSR primer pairs selected

Nhe004, Nhe005, Nhe011, Nhe015, Nhe018, Nhe019, Hbi016, Hbi161, Sle111a, Sle392, Sle605,

Slu044a, Shc03, Shc04, Shc07, Shc09

• What model to use: product rule or subpopulation models?

Pasoh Forest Reserve (231 individuals)

PA101PA292

PA013

PA230

Clustering analysis on genetic distance via NJ method

• Unrelated individual (86.4%)

• Half-siblings (12.4%)

• Full-siblings (0.9%)

• Parent-offspring (0.3%)

Relatedness among individuals using ML-Relate software

• Results clearly showed that population is deviated from HWE

Perform statistical tests to check:• Hardy-Weinberg equilibrium for allele independence• Linkage equilibrium for locus independence

InbreedingPopulation

substructuring

• Random match probability need to be calculated using subpopulation model and corrected for coancestry (FST) and inbreeding (FIS) coefficients

Ayres and Overall (1999). Forensic Science International 103: 207-216

[Fst + (1 – Fst)pi] [2Fst + (1 – Fst)pi] Homozygote:

P(A i A i/A i A i) = Fis + (1-Fis)[Fst + (1 – Fst) pi] Fis2 + 2Fis(1-Fis) (1 + Fst)

[2Fst + (1 – Fst)pi][3Fst + (1 – Fst)pi] ]

+ (1-Fis)2

(1 + Fst)(1 + 2Fst)

[Fst + (1 – Fst)pi][Fst + (1 – Fst) pj] Heterozygote: P(A i Aj/A i Aj ) = 2(1-Fis) (1 + Fst)(1 + 2Fst)

BEnSun

Pia

Bub

Chi

Jel

GBa

LebHTBHTA

PRaRDa

Ter

RTuLak

BTiLen Kem

Ber

Les

GomSLa

AmpPasPel

Lab LeBLeA

PaAPaB

Region A

Region B

Region CBEn

Sun

Pia

Bub

Chi

Jel

GBa

LebHTBHTA

PRaRDa

Ter

RTuLak

BTiLen Kem

Ber

Les

GomSLa

AmpPasPel

Lab LeBLeA

PaAPaB

Region A

Region B

Region C

PaB

PaA

LeB

LeA

Les

Lab

Pel

Pas

RDa

Ber

Kem

BTi

Lak

Len

Ter

RTu

HTB

HTA

Jel

GBa

Leb

Pia

PRa

SLa

Amp

Gom

Chi

Bub

Sun

BEn

Region A

Region C

Region B

PaB

PaA

LeB

LeA

Les

Lab

Pel

Pas

RDa

Ber

Kem

BTi

Lak

Len

Ter

RTu

HTB

HTA

Jel

GBa

Leb

Pia

PRa

SLa

Amp

Gom

Chi

Bub

Sun

BEn

PaB

PaA

LeB

LeA

Les

Lab

Pel

Pas

RDa

Ber

Kem

BTi

Lak

Len

Ter

RTu

HTB

HTA

Jel

GBa

Leb

Pia

PRa

SLa

Amp

Gom

Chi

Bub

Sun

BEn

PaB

PaA

LeB

LeA

Les

Lab

Pel

Pas

RDa

Ber

Kem

BTi

Lak

Len

Ter

RTu

HTB

HTA

Jel

GBa

Leb

Pia

PRa

SLa

Amp

Gom

Chi

Bub

Sun

BEn

Region A

Region C

Region B

Population structure of N. heimii throughout P. Malaysia

Allele frequenciesFst = 0.0470Fis = 0.1758Match probability



DNA fingerprinting databases of N. heimiii throughout P. Malaysia

REGION BPas, Pel, Lab, PaA, PaB, LeA, LeB, Les, BTi, RTu, Ter, Len,

Lak, Kem, Ber, RDa

REGION CHTA, HTB, PRa, Leb,

Jel, GBa, Pia

REGION A BEn, Sun, Bub, Chi,

SLa, Amp, Gom

Hardy-Weinberg equilibrium for allele independenceLinkage equilibrium for locus independence

Applications of the databases

Genotypes GenotypesNhe004 262/262 262/262

Nhe005 129/129 129/129

Nhe011 176/186 176/186

Nhe015 143/181 143/181

Nhe018 141/169 141/169

Nhe019 214/220 214/220

Hbi016 140/141 140/141

Hbi161 102/105 102/105

Sle111a 137/140 137/140

Sle392 187/189 187/189

Sle605 120/120 120/120

Slu044a 148/148 148/148

Shc03 131/139 131/139

Shc04 85/117 85/117

Shc07 169/169 169/169

Shc09 190/201 190/201

Locus

DNA fingerprinting database Region A (Allele frequencies)

Sub-population model (Fst = 0.0470; Fis = 0.1758)

Using database to extrapolate the possibility of a random match

Provides legal

evidence to convict the

illegal loggers

99.9999999…% sure that the log is originated from this stump

To ensure conservation & sustainable utilization of

FGRs

Molecular Marker Techniques

Science

Transcript of Molecular Marker Techniques