Mendelian Inheritance
Mendelian genetic analysis:
• The "classical" approach to understanding the
genetic basis of a trait.
• Based on analysis of inheritance patterns in the progeny
of a cross
R
R
0
R0
R0
0
R0
R0
Gregor Mendel
R
0
R
RR
R0
0
R0
00
en.wikipedia.org
Qualitative/discontinuous
variation vs. quantitative/
continuous variation
The number of genes
determining the trait
The effects of the
environment
RR beet
rr chard
Polymorphisms
A trait, a gene, a nucleotide
vs.
Trait (Phenotype)
A gene (genotype)
OPA_SNP_Name
Chr. Pos.
BSR-1H
Fr-H3
PPD-H2
PPD-H1
Eam6
VRS1
Denso
Int-C
VRN-H2
Bmy1
BSR-5H
FR-H2
FR-H1/VRN-H1
RPG4/RPG5
GBSSI waxy
VRN-H3
NUD
BOPA2_12_30817
BOPA1_5381-1950
BOPA1_8867-459
BOPA2_12_30872
BOPA1_4659-1261
BOPA2_12_30897
BOPA1_9618-372
BOPA1_6208-987
BOPA2_12_30886
BOPA2_12_30824
BOPA1_3928-513
BOPA2_12_30854
BK_17
SCRI_RS_6902
BOPA2_12_30902
BOPA2_12_30893
SCRI_RS_104566
ISU_MLA_949
1H
1H
1H
2H
2H
2H
3H
4H
4H
4H
5H
5H
5H
5H
7H
7H
7H
5381-1950
8867-459
OSU_HvPRR7_324
4659-1261
OSU_VRS1_HvHox1_260
9618-372
6208-987
OSU_VRN_H2_ZCCT_Ha_830
OSU_Bmy1_115_142
3928-513
OSU_HVCBF9_907
OSU_Waxy_HvGBSSI_promoter_230
OSU_VRN_H3_HvFT1_264
17.0 [A/G]
41.5 [A/G]
88.2 [A/G]
19.9 [A/G]
57.0 [A/G]
80.0 [A/G]
122.0 [A/C]
25.8 [A/C]
119.1 [T/A]
123.3 [A/G]
71.7 [A/G]
95.0 [A/G]
125.8 [C/G]
151.1 [A/C]
13.9 [C/G]
34.3 [A/G]
80.1 [A/G]
A
A
A
A
A
A
A
A
A
A
A
A
C
A
A
A
A
B allele
9K_NAME
SNP
QTL
A allele
A single nucleotide (genotype)
G
G
G
G
G
G
C
C
C
C
G
G
G
C
C
G
G
SourceSeq
GCTGAAGCGACAGAGCTAGTTGGCATATATGGAAAGAGGGATCAAG[A/G]CCTCATGAGGTTGCTTTCCATGGAGGGCGATGATGCCTCTAAT
TGTCRGCTTYATTAGGAGAAGACTCTCGGTGTC[A/G]TCTGTCGGTCCATGTCCATTTCATTTGTTGCTTGTGTAAAACCATATGGGGTTTGTTGTT
CCGAGCCCTAGAGGACTCGTTTCGCAGCATGAGCTCCTTCTCCAAGTCATCCATCATGGACC[A/G]GTCCACCGATTTCAGCAGCTCGCGTTATT
TGGTGGCCGTTCTCGACGGGGATAACTGCCGGGACAGACAGCCA[A/G]TATGCAGAGCTTTAGTACTACTATACTTTGTATGTATATGACTGACG
GTGGAGGTGAACTCCTGGCAAATCTTACAACAGGCAC[A/G]CCATGGGAGGCTGTTGCTAAGGAGGTAGGTACCACTTTTGGCACCGACTCTGG
TCAGATCCGAACCGAAAGCATGGACAAGCATCAGCTCTTTG[A/G]TTCATCCAACGTGGACACGACTTTCTTCGCGGCCAATGGTACACACGAC
CAACCCAGCTCAAGGAGCTGCGCCATTGTCATCC[A/C]CTAATCCAAGTACTAATATAACTGAGAGTTCGCTGTCTGAAACTTTTCACCTTGTTTC
GTACATTACATGTATAATCACTTGTGATCTGAAGAACAA [A/C]GCACATTCGGCGCTCAGCTGACGGGGTCGCGTTCCGGCCCGGGGTTGTAGAG
AATCACACTTCCTTAATTTCCATCTCAAAAAAAGCTACCGCCA [A/T]GTGACCAGCTCATATATATGCCACATAACTCCTTTAATTTATTCTGGTCG
TCAATGTTCCTAGTCCCGTGACCGTCGGTGTAGAAAATGTCGGGATCAC[A/G]CGTGCCGACGTCCCGCACCCACTGTGGGATTGGGATGTTGA
GCCACACGCTGCAAATACATCATGATAGATCACAAAC[A/G]CACACGTCGGCACAGATTAGCCAATAAGTACACAAGAAAGCGAAGGTACAG
AGCAGACCGGCGTCCAGACGCCGCTATGGAGCTGCTTGTTC[A/G]ACTAATTTAGCACTACTGTCAACATGTAGATAGTTGCGTTCTTCCAGATT
TTCAGTACGAGTAACAAGTTGCA[C/G]CGGCCAGCCTGGTGTATCATGCGGTTGCGAACATGCTAACCCCATGGAGGGGAGAGGAAAAGAAAT
ATGACGCCATGGATCCAGGACGGGCCCTGGCACCTGAAATGAC[A/C]GTGGSGTCTGCCGGTTCTGATGGATTCGGGGGTTGACCCCGGCGCCT
GAGTGAGTGTTGTTGTTGTTGAGTGGCAGAGGTTGTAGTGTGT[C/G]GTAGGGGGCGGGCGGGCGGAAGTGACGGGACTCCAAGGAAACGAAC
TACGTACTAGCTAGAGAGAGCCCGATCGTGCATGTGCGTGTGGT[A/G]AGCACTTTCAGTTTCAGAGCTAAATTAAAATTTGCATTAGATAGTGG
AGCCCGCTTCCTGTGGGGGAGGTTCGGATGACAGGGCGGCG[A/G]CAGAGGGTAGCGGCGTTCTGAAAAATGGCGATGCCGTTGAAGGGGAT
Inheritance patterns for polymorphisms
Nuclear genome
•Autosomal = Biparental
V
v
V
VV
Vv
v
Vv
vv
•Sex-linked = XX vs. XY
Cytoplasmic genomes
•Chloroplasts and mitochondria = uniparental
•Details at end of this section
Delving into the nuclear genome:
Polymorphisms, loci, and alleles
Many alleles are possible, but there are only two alleles per
locus in a diploid individual
V
V
The “V” locus
Parent
v
v
v
v
v
v
Gametes
Homozygous
Dominant
v
or
Heterozygous
v
Homozygous
Recessive
v
v
v
or
or
v
Crosses between parents generate progeny populations
of different sorts: Filial (F) generations of selfing: e.g. F1,
F2, F3; backcross; doubled haploid; recombinant inbred,
etc.
Crosses between parents generate progeny populations
of different types. Filial (F) generations of selfing ( x )
Selfing
A
X
B
% Heterozygosity
F1
100
F2
50
F3
25
x
x
x
F ~∞
~0
Crosses between parents generate progeny populations of
different types.
Backcross
A
X
B
F1
X
A
BC1
BC1 X A
BC1
x
x
BC2
x
x
x
~∞
BC2 X A
BC3
~∞
Crosses between parents generate progeny populations
of different types:
Doubled Haploid
A
X
F1
B
Gametes
Double chromosome
number
Plants = F ∞
The genetic status (degree of homozygosity) of the
parents will determine which generation is appropriate for
genetic analysis and the interpretation of the data (e.g.
comparison of observed vs. expected phenotypes or
genotypes).
The degree of homozygosity of the parents will likely be a
function of their mating biology, e.g. cross vs. selfpollinated.
Mendelian analysis is straightforward when one or two
genes determine the trait.
Expected and observed ratios in cross progeny will be a
function of:
• the degree of homozygosity of the parents
• the generation studied
• the degree of dominance
• the degree of interaction between genes
• the number of genes determining the trait
Monohybrid Model: Segregation of alleles at a
locus
Example: Number of kernel rows in barley (Hordeum vulgare).
The VRS1 locus. Alleles are Vrs1 and vrs1. “V” and “v” for
short.
2 row
vs.
6 row
V
v
Phenotype
2-row
VV
6-row
vv
Genotype
Genotype
Vrs1 sequences
“Six-rowed barley originated from a mutation in a………
homeobox gene”
•Two-rowed is ancestral (wild type)
•Homeobox genes are transcription factors – they encode
proteins that bind to other genes and thus regulate the
expression of other genes
The model •In a two-row, the product of Vrs1 binds to another (unknown)
gene (or genes) that determine the fertility of lateral florets
•By preventing expression of this other gene, lateral florets are
sterile and thus the inflorescence has two rows of lateral florets
1.
2.
3.
4.
Vrs1
Lat
X
Transcription of Vrs1
Translation of Vrs1
Binding of Vrs1 to Lat
No expression of Lat
=2-row
1.
2.
3.
4.
vrs1
Lat
X
X
No transcription of vrs1 (or)
No translation of vrs1
No binding of vrs1 to Lat
Lat expresses and lateral florets are
fertile = 6-row
What happened to Vrs1 to make it vrs1 (loss of
function)?
•
Complete deletion of the gene ( - transcription, translation so no protein)
• Deletions of (or insertions into) key regions of the
gene leading to - transcription and/or + transcription
but – translation, or incorrect translation
• Nucleotide changes leading to + transcription, but
incorrect translation leading to non-functional protein
How many alleles are possible at a
locus?
• Only two per diploid individual, but many are possible in
a population of individuals
• New alleles arise through mutation
• Some mutations have no discernible effect on phenotype
• Different mutations in the same gene may lead to the
same or different phenotypes
All this happened to VRS1 in the
past 10,000 years!
2012
2-row, 6-row and
your local barley
Determining the inheritance of row type based on phenotype
Crosses between parents generate progeny
populations of different filial (F) generations: e.g. F1,
F2, F3; backcross; doubled haploid; recombinant
inbred, etc.
Doubled Haploid Production
using anther culture
Pollen (or eggs)
F1 (or other
generation)
Genotype Vv Ww
VW
Vw
vW
VW Vw vW vw
vw
Induction
Regeneration
Plantlets
Harvest Seed
Chromosome Doubling
VVWW
VVww
vvWW
vvww
VVWW
VVww
vvWW
vvww
Hypothesis Testing: Determining the
“Goodness of Fit”
Expected and observed ratios in cross progeny will be a
function of
•
•
•
•
•
the degree of homozygosity of the parents
the generation studied
the degree of dominance
the degree of interaction between genes
the number of genes determining the trait
Hypothesis Testing: Determining the
“Goodness of Fit”
• The Chi Square statistic tests "goodness of fit“; that
is, how closely observed and predicted results
agree
• The degrees of freedom that are used for the test
are a function of the number of classes
• This is a test of a null hypothesis: “the observed
ratio and expected ratios are not different”
The general formula
Chi square = (O1 - E1)2/E1 +........+ (On - En)2/En
where O1 = number of observed members of the first class
E1 = number of expected members of the first class
On = number of observed members of the nth class
En = number of expected members of the nth class
As deviations from hypothesized ratios get smaller, the chi
square value approaches 0; there is a good fit.
As deviations from hypothesized ratios get larger, the chi
square value gets larger; there is a poor fit.
What determines good vs. poor?
• The probability of observing a deviation as large, or
larger, due to chance alone.
• p values below 0.05 (i.e. 0.025, 0.01, .005) lie in the
area of rejection.
Interpreting the chi square statistic in terms of probability.
1. Determine degrees of freedom (df). df = number of
classes - 1.
2. Consult chi square table and/or calculator (on web)
Chi square computation for a monohybrid ratio
Example: Number of kernel rows (Vrs-1/vrs-1) in barley (Hordeum
vulgare). For simplicity, vrs-1 is abbreviated as "v" in the following
table. Hypothesis is 1:1 (expectation for 2 alleles at 1 locus in a doubled
haploid population). The data are for a SNP in HvHox1 (3_0897) from the Hb
population (n = 82). SNPs are assayed as nucleotides but converted to "A"
and "B" alleles for each locus. In this example, the OWB-D allele is A and the
OWB-R allele is B. Reviewing the sequence alignment, OWB-D = Guanine
(G) and OWB-R = Adenine (A)
Gametes
V
v
DH genotypes
VV
vv
DH phenotypes Two-row Six-row
Number
35
47
Genotype
Vrs1 sequences
Phenotype #Observed #Expected O - E
VV
35
41
-6
vv
47
41
6
(O - E)2/E
0.89
0.89
Totals
1.75 = chi square
82
82
0
p-value (1 df) = 0.18.
This chi square is well within the realm of acceptance, so
we conclude that there is indeed a 1:1 ratio of two-row: sixrow phenotypes (VV:vv genotypes) in the OWB population.
Be able to calculate chi-square tests for monohybrid F2,
monohybrid backcross (including testcross) and DH.
Chi square computation for dihybrid ratios
See online review if you are not familiar with dihybrids and chi
square calculation
Be able to calculate chi-square tests for dihybrid testcross and
DH. Know how many df you would use for F2 dihybrid.
Cytoplasmic inheritance:
• usually maternal inheritance but there are examples of
paternal inheritance in plants
Mitochondrial genomes
Chloroplast genomes
Mitochondrial genomes
Dombrowski et al. 1998
Chloroplast genomes
Biomedcentral.com