Quantitative Inheritance – Complete Genetics Notes

Topic: Quantitative Inheritance

Points Covered in This Lecture:

Quantitative Inheritance
Polygenic Inheritance
Heritability
QTL Mapping
Marker-Assisted Selection

Quantitative genetics deals with traits that show continuous variation rather than simple discrete categories. Important examples include plant height, seed weight, milk production, body weight, blood pressure, crop yield, intelligence-related measurements, fruit size and many other biological characteristics. Such traits are usually influenced by multiple genes and environmental factors.

Understanding quantitative inheritance is particularly important in genetics, plant and animal breeding, evolutionary biology, agriculture, biotechnology, human genetics and population biology. The concepts of polygenic inheritance, heritability, quantitative trait loci (QTLs), linkage mapping and marker-assisted selection provide a framework for understanding and improving complex traits.

Index

1. Introduction to Quantitative Genetics
2. Quantitative Inheritance
3. Continuous Variation
4. Quantitative vs Mendelian Inheritance
5. Polygenic Inheritance
6. Additive Polygenic Model
7. Example of Polygenic Inheritance
8. Role of Environment
9. Normal Distribution of Quantitative Traits
10. Heritability
11. Broad-Sense Heritability
12. Narrow-Sense Heritability
13. Important Heritability Formulas
14. Interpretation of Heritability
15. Quantitative Trait Loci – QTL
16. QTL Mapping
17. Steps in QTL Mapping
18. Linkage and QTL Mapping
19. LOD Scores in QTL Mapping
20. QTL Interval Mapping
21. QTL Mapping vs Association Mapping
22. Marker-Assisted Selection
23. Steps in Marker-Assisted Selection
24. Types of Marker-Assisted Selection
25. Advantages of MAS
26. Limitations of MAS
27. MAS in Plant and Animal Breeding
28. Important Comparison Tables
29. High-Yield Exam Points
30. 10 MCQs with Answers
31. Quick Revision

1. Introduction to Quantitative Genetics

Quantitative genetics is the branch of genetics concerned with traits that are controlled by multiple genetic factors and are often strongly influenced by the environment. Instead of producing only a few clearly separated phenotypic classes, these traits commonly show a range of phenotypic values.

For example, in a population of plants, individuals may have heights of 50 cm, 51 cm, 52 cm, 53 cm, 54 cm and so on. Plant height therefore shows continuous variation. Similarly, human height does not normally fall into only two or three categories; instead, a broad range of heights occurs.

Quantitative traits are often controlled by many genes.
Each gene may contribute a relatively small effect.
Environmental factors can significantly influence the phenotype.
The phenotype is often described numerically.
Variation is commonly analyzed using statistical and population-genetic methods.
Many economically important agricultural traits are quantitative.

Core idea: Quantitative genetics connects Mendelian genetics with statistical analysis of variation in populations.

2. Quantitative Inheritance

Quantitative inheritance refers to the inheritance of traits whose phenotypic variation can be measured quantitatively and is generally influenced by multiple genes and environmental factors.

Examples of Quantitative Traits

Human height
Human body weight
Blood pressure
Milk production in cattle
Egg production in poultry
Growth rate
Seed weight
Grain yield
Fruit size
Plant height
Number of seeds per plant
Oil content of seeds
Protein content
Days to flowering

Characteristics of Quantitative Inheritance

Phenotypes usually show continuous variation.
Multiple genes may contribute to the phenotype.
Environmental conditions influence the phenotype.
Individual genes often have relatively small effects.
Phenotypic values can be measured numerically.
Statistical distributions are important for analysis.
Genotype and environment may interact.
Selection can change the population mean over generations.

3. Continuous Variation

Continuous variation occurs when phenotypes form a continuous range rather than a few distinct categories. For example, consider plant height. If one plant is 90 cm tall and another is 91 cm tall, there may be many intermediate phenotypes.

Continuous variation is commonly associated with polygenic inheritance. However, continuous phenotypic distributions can also arise from environmental effects acting on genetic variation.

Continuous vs Discontinuous Variation

Feature	Continuous Variation	Discontinuous Variation
Phenotypes	Many intermediate values	Distinct categories
Genetic control	Often many genes	Often one or a few genes
Environmental effect	Often substantial	May be smaller in simple Mendelian examples
Example	Height, body weight	ABO blood groups
Analysis	Statistical/quantitative methods	Mendelian ratios often useful

4. Quantitative Inheritance vs Mendelian Inheritance

Feature	Mendelian Inheritance	Quantitative Inheritance
Number of genes	Often one or a few	Usually many
Phenotype	Discrete	Continuous
Environmental influence	Often limited in simple examples	Often important
Statistical approach	Ratios and probability	Variance, covariance, regression and other statistical methods
Example	Pea seed shape	Human height

5. Polygenic Inheritance

Polygenic inheritance occurs when a phenotype is influenced by multiple genes. Each contributing gene is sometimes called a polygene. When the effects of multiple loci are combined, a broad range of phenotypes may be produced.

In a simple additive polygenic model, each allele contributing to the trait adds a small amount to the phenotype. The combined effects of many loci can generate continuous variation.

Important Features

Many genes contribute to the phenotype.
Genes may be located at different loci.
Alleles can have additive effects.
Each locus may contribute a relatively small amount.
Environmental factors can modify the phenotype.
Phenotypes often show approximately continuous distributions.

Polygenic ≠ necessarily identical to quantitative: Polygenic traits are influenced by multiple genes, while quantitative traits are defined by their measurable continuous phenotypic variation. In many biological examples, the two concepts overlap strongly.

6. Additive Polygenic Model

Consider a simplified trait controlled by two loci, A/a and B/b. Suppose each contributing allele increases the phenotype by one unit.

The genotype with the fewest contributing alleles produces the lowest phenotypic value, while the genotype with the greatest number of contributing alleles produces the highest value.

For example, if A and B are contributing alleles:

aabb → 0 contributing alleles
Aabb → 1 contributing allele
aaBb → 1 contributing allele
AaBb → 2 contributing alleles
AABb → 3 contributing alleles
AABB → 4 contributing alleles

The actual phenotype also depends on environmental effects and on the assumptions of the particular genetic model.

Number of Phenotypic Classes

For a simplified additive model involving n gene pairs, the theoretical maximum number of phenotypic classes under idealized assumptions is:

Number of phenotypic classes = 2n + 1

Thus:

1 gene pair → 3 classes
2 gene pairs → 5 classes
3 gene pairs → 7 classes
4 gene pairs → 9 classes

This is a simplified classical model. Real quantitative traits may be affected by dominance, epistasis, environmental variation and genotype-environment interactions, so their distributions may not follow this simple expectation.

7. Example of Polygenic Inheritance

A classic conceptual example is skin pigmentation, where multiple genetic loci contribute to pigmentation and environmental factors such as UV exposure can also influence phenotype. Human height is another well-known example of a complex quantitative trait involving many genetic variants and environmental factors.

General Model

Locus 1 contributes a small amount.
Locus 2 contributes another small amount.
Locus 3 contributes another amount.
Additional loci further modify the phenotype.
Nutrition, climate, disease, lifestyle and other environmental factors can modify the observed phenotype.

Consequently, individuals carrying similar combinations of alleles may still show different phenotypic values if their environments differ.

8. Role of Environment in Quantitative Traits

The observed phenotype of an individual is not determined solely by its genotype. Environmental factors can substantially affect quantitative traits.

Phenotype = Genetic contribution + Environmental contribution

In a more complete quantitative-genetic framework, phenotype may also include genotype-environment interaction and other components.

Examples of Environmental Effects

Nutrition can influence body growth.
Water availability can influence plant yield.
Temperature can affect plant development.
Soil nutrients can influence crop growth.
Management practices can influence agricultural productivity.
Physical activity can influence body composition.
Environmental stress can affect disease-related phenotypes.

A difference in phenotype between two individuals does not automatically mean that the difference is genetic.

9. Normal Distribution of Quantitative Traits

Many quantitative traits approximately follow a normal or bell-shaped distribution in sufficiently large populations when many small genetic and environmental effects combine.

Features of a Normal Distribution

Most individuals occur near the population mean.
Fewer individuals occur at the extreme ends.
The distribution is approximately symmetrical under ideal conditions.
Mean, variance and standard deviation are important descriptive measures.

The normal distribution is not an obligatory feature of every quantitative trait. Skewed distributions, mixtures of distributions and other patterns can occur depending on the biological and environmental processes involved.

10. Heritability

Heritability is a statistical measure describing the proportion of phenotypic variation in a particular population, under particular environmental conditions, that is attributable to genetic differences among individuals.

Heritability is therefore a property of a population and environment, not a fixed percentage of an individual's phenotype that is "genetic."

Very Important: A high heritability does NOT mean that a trait cannot be changed by the environment. Likewise, a low heritability does not mean that genes have no role in the trait.

Why is Heritability Important?

Helps estimate the genetic contribution to phenotypic variation.
Important in plant and animal breeding.
Helps predict response to selection.
Useful in evolutionary quantitative genetics.
Helps distinguish genetic and environmental sources of variation at the population level.

11. Broad-Sense Heritability

Broad-sense heritability is the proportion of total phenotypic variance that is attributable to total genetic variance.

H² = V_G / V_P

Where:

H² = broad-sense heritability
V_G = total genetic variance
V_P = total phenotypic variance

Total genetic variance can include:

Additive genetic variance
Dominance variance
Epistatic or interaction variance

Therefore:

V_G = V_A + V_D + V_I

where V_A is additive variance, V_D is dominance variance and V_I represents interaction or epistatic variance in a simplified decomposition.

12. Narrow-Sense Heritability

Narrow-sense heritability is the proportion of phenotypic variance attributable specifically to additive genetic variance.

h² = V_A / V_P

Where:

h² = narrow-sense heritability
V_A = additive genetic variance
V_P = phenotypic variance

Narrow-sense heritability is especially important in breeding because additive genetic effects are more directly related to the resemblance between parents and offspring and therefore to predictable response to selection.

13. Important Heritability Formulas

Broad-Sense Heritability

H² = V_G / V_P

Narrow-Sense Heritability

h² = V_A / V_P

Phenotypic Variance

In a simplified model:

V_P = V_G + V_E

where V_E is environmental variance. More detailed models may include genotype-environment interaction and other variance components.

Example

Suppose a population has:

Phenotypic variance = 100
Genetic variance = 60
Additive variance = 40

Then:

H² = 60 / 100 = 0.60 = 60%

and:

h² = 40 / 100 = 0.40 = 40%

Therefore, broad-sense heritability is 60% and narrow-sense heritability is 40% for this hypothetical population under the specified conditions.

14. Interpretation of Heritability

If a trait has a heritability of 0.70 in a particular population, this does not mean that 70% of an individual's phenotype is caused by genes. Instead, it means that, under the conditions of the study, approximately 70% of the variation among individuals is statistically attributable to genetic variation according to the definition and estimation method used.

Factors Affecting Heritability

Population genetic variation
Environmental variation
Measurement accuracy
Population structure
Age and developmental stage
Experimental design
Statistical method used to estimate variance components

If environmental variation becomes very large while genetic variation remains similar, heritability can decrease. Conversely, reducing environmental variation can increase the estimated heritability of a trait.

15. Heritability and Response to Selection

Narrow-sense heritability is closely related to the response of a population to selection.

The breeder's equation is commonly written as:

R = h²S

Where:

R = response to selection
h² = narrow-sense heritability
S = selection differential

The selection differential represents the difference between the mean phenotype of selected parents and the mean phenotype of the original population.

Example

If narrow-sense heritability is 0.40 and selection differential is 10 units:

R = 0.40 × 10 = 4 units

The expected response is therefore approximately 4 units under the assumptions of the simple breeder's equation.

16. Quantitative Trait Loci – QTL

A Quantitative Trait Locus, abbreviated QTL, is a genomic region associated with variation in a quantitative trait.

A QTL does not necessarily correspond to a single gene. It may represent a chromosomal region containing one or several causal genes, regulatory elements, or genetic variants associated with the trait.

Examples of Traits Studied Using QTL Analysis

Plant height
Grain yield
Flowering time
Drought tolerance
Salt tolerance
Seed weight
Fruit size
Milk production
Growth rate
Disease resistance

17. QTL Mapping

QTL mapping is a statistical-genetic approach used to identify genomic regions associated with variation in a quantitative phenotype.

The basic principle is to combine:

Phenotypic measurements
Genotypic marker information
Genetic linkage information
Statistical association between marker genotype and phenotype

If individuals carrying a particular marker allele tend to show different phenotypic values from individuals carrying another marker allele, the marker may be linked to a QTL affecting the trait.

18. Steps in QTL Mapping

Step 1 – Select Parents

Two parental lines showing contrasting phenotypes may be selected. For example, one plant line may show high disease resistance while another is susceptible.

Step 2 – Produce a Mapping Population

The parents are crossed and progeny are generated. Depending on the organism and research objective, mapping populations may include F₂, backcross, recombinant inbred or other populations.

Step 3 – Phenotyping

Each individual is measured for the quantitative trait.

Examples include:

Plant height in centimeters
Yield per plant
Seed weight
Disease severity score
Days to flowering

Step 4 – Genotyping

Individuals are genotyped using molecular markers such as SNPs, SSRs or other suitable marker systems.

Step 5 – Construct a Linkage Map

Markers are ordered according to their recombination relationships to produce a genetic linkage map.

Step 6 – Statistical Analysis

Marker genotypes are statistically related to phenotypic measurements. Regions showing strong evidence of association with the trait may be identified as QTL regions.

Step 7 – QTL Validation

Important QTLs should ideally be validated in independent populations or through additional experiments before being used extensively in breeding.

19. Linkage and QTL Mapping

Genetic linkage is the tendency of loci located near each other on the same chromosome to be inherited together because recombination between them is less frequent than expected for distant loci.

QTL mapping uses this principle. If a molecular marker is physically close to a QTL, recombination between the marker and QTL will be relatively uncommon. Therefore, marker genotype can provide information about the inheritance of the QTL.

Closer marker → generally lower recombination → stronger linkage information.

20. LOD Scores in QTL Mapping

LOD scores can also be used in QTL analysis to evaluate statistical evidence for the presence of a QTL at a particular genomic location.

The exact statistical model depends on the mapping population and analytical method, but the general idea is to compare a model containing a QTL with a model lacking a QTL.

A graph of LOD score against chromosomal position can show peaks. A strong peak indicates a genomic region with evidence for a QTL under the chosen model and threshold.

Interpretation of a QTL LOD Plot

X-axis → genomic or linkage-map position.
Y-axis → LOD score.
Peak → candidate QTL region.
Threshold line → statistical significance threshold determined by the analysis.

21. QTL Interval Mapping

Interval mapping evaluates the probability of a QTL being located within intervals between genetic markers rather than testing only individual markers.

This approach can provide better localization of QTLs compared with simple single-marker analysis.

Advantages

Uses information between marker positions.
Can detect QTLs that are not perfectly associated with a single marker.
Provides a profile of evidence across a chromosome.
Can estimate approximate QTL position.

22. QTL Mapping vs Association Mapping

Feature	QTL Mapping	Association Mapping
Population	Often specially developed mapping populations	Natural/diverse populations or panels
Genetic structure	Known parental origins	Historical recombination
Resolution	Often moderate	Can be higher depending on population and LD
Time required	Mapping population may require development	Existing diversity panels may be used
Major concern	Population size and recombination	Population structure and linkage disequilibrium

23. Marker-Assisted Selection

Marker-Assisted Selection, commonly abbreviated MAS, is a breeding strategy in which molecular markers linked to genes or QTLs are used to help select individuals carrying desirable genetic characteristics.

Instead of relying exclusively on phenotype, breeders can use DNA marker information to identify individuals likely to carry desired alleles.

Basic Principle

DNA Marker → Detect desirable allele/linked region → Select individual → Breeding

MAS is particularly useful when the desired phenotype:

Is difficult to measure.
Appears late in development.
Requires destructive testing.
Has strong environmental influence.
Is expensive to phenotype.
Is controlled by a major gene or well-characterized QTL.

24. Steps in Marker-Assisted Selection

Identify the target trait: Determine the characteristic that needs improvement.
Identify associated genetic region: A gene, mutation or QTL associated with the desired trait is identified.
Develop or select a molecular marker: A marker closely linked to or directly identifying the desired allele is selected.
Genotype breeding material: DNA samples from candidate individuals are tested.
Select individuals: Individuals carrying the desired marker allele are selected.
Cross selected individuals: Selected individuals are used in breeding.
Repeat selection: Marker information can be used in subsequent generations.
Phenotypic validation: Selected individuals should eventually be evaluated for actual phenotype and agronomic performance.

25. Types of Marker-Assisted Selection

1. Marker-Assisted Backcrossing

Marker-assisted backcrossing is used to introduce a desired gene or QTL from a donor parent into an elite recurrent parent while recovering most of the recurrent parent's genome.

Three Major Selection Components

Foreground selection: Selects individuals carrying the target gene or QTL.
Recombinant selection: Uses markers around the target region to reduce unwanted donor DNA near the target locus.
Background selection: Selects individuals with the greatest proportion of the recurrent parent's genome.

2. Gene Pyramiding

Gene pyramiding involves combining multiple desirable genes or resistance genes into a single genetic background.

Useful for combining multiple disease-resistance genes.
Markers can help track each target gene.
Phenotypic screening alone may not distinguish individuals carrying different resistance genes.

3. Marker-Assisted Recurrent Selection

Markers can be repeatedly used during recurrent selection to accumulate favorable alleles over several generations.

26. Advantages of Marker-Assisted Selection

Selection can be performed at the DNA level.
Selection can occur before the trait is phenotypically expressed.
Useful for traits with strong environmental effects.
Can reduce the time required for breeding.
Useful for traits that are expensive to phenotype.
Can help select individuals carrying recessive alleles.
Useful for gene pyramiding.
Can improve the efficiency of backcrossing.
Can help track donor and recurrent parental genome segments.
Can support selection for multiple traits.

27. Limitations of Marker-Assisted Selection

Markers may not be perfectly linked to the causal gene.
Recombination between marker and target gene can reduce selection accuracy.
Marker development can be expensive.
Laboratory genotyping is required.
QTL effects may differ among genetic backgrounds.
Complex traits controlled by many small-effect loci may be difficult to improve using conventional MAS alone.
Environmental effects still need to be considered for phenotype validation.
Marker-trait associations may not transfer perfectly across populations.

Important: A linked marker is not necessarily the causal mutation. Recombination can separate a marker from the target locus.

28. MAS in Plant and Animal Breeding

Plant Breeding

MAS is widely useful in crop improvement. Breeders can use markers to select plants carrying favorable alleles for traits such as disease resistance, drought tolerance, salinity tolerance, quality traits and other characteristics.

Disease resistance
Drought tolerance
Salt tolerance
Submergence tolerance
Grain quality
Plant architecture
Flowering time
Nutritional quality

Animal Breeding

Molecular markers can also be used in animal breeding to identify animals carrying desirable alleles associated with production, reproduction, disease resistance or quality traits.

Milk production
Milk composition
Growth rate
Meat quality
Disease resistance
Reproductive performance

29. Marker-Assisted Selection vs Genomic Selection

Marker-assisted selection generally focuses on a limited number of markers associated with specific genes or QTLs. Genomic selection, in contrast, typically uses genome-wide marker information to predict the breeding value of individuals for complex traits.

Feature	MAS	Genomic Selection
Markers	Usually selected markers	Genome-wide markers
Main target	Specific gene/QTL	Overall genetic breeding value
Best suited	Major genes and detectable QTLs	Complex traits controlled by many loci
Selection method	Presence/absence or genotype at target markers	Prediction of genomic breeding value

30. Genetic Variance Components

Quantitative genetics separates genetic variation into different components. The most important component for selection is additive genetic variance.

Additive variance (V_A): Variation due to the average effects of alleles.
Dominance variance (V_D): Variation caused by interactions between alleles at the same locus.
Epistatic variance (V_I): Variation caused by interactions between alleles at different loci.

V_G = V_A + V_D + V_I

The exact variance decomposition used in an analysis can be more detailed, but the basic distinction between additive and non-additive genetic variance is fundamental to quantitative genetics.

31. Genotype × Environment Interaction

Genotype-environment interaction occurs when different genotypes respond differently to environmental conditions.

For example, imagine two crop varieties. Variety A may perform better than variety B under high rainfall, while variety B may outperform variety A under drought conditions.

Genotype ranking may change across environments.
Breeding trials should therefore include appropriate environments.
QTL effects can also depend on environmental conditions.
Selection in one environment may not always produce the best genotype in another environment.

32. Relationship Between QTL Mapping and MAS

QTL mapping and marker-assisted selection are closely connected. QTL mapping helps identify genomic regions associated with quantitative traits, whereas MAS uses markers associated with those regions to assist selection in breeding programs.

QTL Mapping → Identify useful genomic region → Develop/choose marker → MAS

For example, if QTL mapping identifies a genomic region associated with disease resistance, a closely linked molecular marker can be used to screen breeding populations for the desired allele.

33. Important Comparison Table

Concept	Main Meaning	Major Application
Quantitative inheritance	Inheritance of measurable traits showing continuous variation	Complex trait analysis
Polygenic inheritance	Multiple genes contribute to a trait	Complex trait genetics
Broad-sense heritability	Total genetic variance / phenotypic variance	Estimate overall genetic contribution to variance
Narrow-sense heritability	Additive genetic variance / phenotypic variance	Predict response to selection
QTL	Genomic region associated with quantitative variation	Trait mapping
QTL mapping	Locates genomic regions influencing quantitative traits	Genetic mapping and breeding
MAS	Uses molecular markers to assist selection	Breeding

34. High-Yield Exam Points

Quantitative traits usually show continuous phenotypic variation.
Many quantitative traits are polygenic.
Environmental effects can strongly influence quantitative phenotypes.
Human height is a classic example of a quantitative trait.
Polygenic inheritance involves multiple genes contributing to a phenotype.
In a simple additive model, multiple alleles can make small contributions to phenotype.
For n gene pairs in a simplified additive model, the theoretical number of phenotypic classes is 2n + 1.
Broad-sense heritability is H² = V_G/V_P.
Narrow-sense heritability is h² = V_A/V_P.
Additive genetic variance is particularly important for response to selection.
The breeder's equation is R = h²S.
Heritability is population- and environment-specific.
Heritability does not indicate the percentage of an individual's phenotype caused by genes.
QTL stands for Quantitative Trait Locus.
A QTL is a genomic region associated with variation in a quantitative trait.
QTL mapping combines phenotypic measurements with genetic marker information.
Linkage information is important in many QTL mapping approaches.
LOD profiles can be used to identify regions with evidence for QTLs.
Marker-assisted selection uses molecular markers to assist breeding decisions.
Foreground selection targets the desired gene or QTL.
Background selection recovers the recurrent parent's genome.
Recombinant selection reduces unwanted donor DNA surrounding a target region.
Gene pyramiding combines multiple favorable genes.
MAS is especially useful for traits that are difficult, expensive or late to phenotype.
A molecular marker linked to a gene can be separated from that gene through recombination.
MAS is particularly effective for major genes and well-characterized QTLs.
Genomic selection generally uses genome-wide markers rather than a small number of target markers.

35. 10 Multiple Choice Questions (MCQs)

Q1. Which of the following is a typical quantitative trait?

ABO blood group
Plant height
Presence of a specific Mendelian mutation only
Sex chromosome constitution

Correct Answer: B — Plant height
Plant height generally shows continuous variation and is influenced by multiple genetic and environmental factors.

Q2. Polygenic inheritance refers to inheritance in which:

Only one gene controls the phenotype
Only environmental factors control the phenotype
Multiple genes contribute to the phenotype
Only mitochondrial genes are involved

Correct Answer: C — Multiple genes contribute to the phenotype
Polygenic traits are influenced by multiple genetic loci, often with small effects contributed by individual loci.

Q3. Which formula represents broad-sense heritability?

H² = V_A/V_P
H² = V_G/V_P
H² = V_E/V_P
H² = V_P/V_G

Correct Answer: B — H² = V_G/V_P
Broad-sense heritability represents the proportion of phenotypic variance attributable to total genetic variance.

Q4. Narrow-sense heritability specifically measures the proportion of phenotypic variance due to:

Environmental variance
Dominance variance only
Additive genetic variance
Total environmental effects

Correct Answer: C — Additive genetic variance
Narrow-sense heritability is h² = V_A/V_P. It is particularly important for predicting response to selection.

Q5. The breeder's equation is commonly represented as:

R = h²S
R = H²/V_P
R = V_G + V_E
R = S/h²

Correct Answer: A — R = h²S
R represents response to selection, h² represents narrow-sense heritability, and S represents the selection differential.

Q6. QTL stands for:

Qualitative Trait Linkage
Quantitative Trait Locus
Quantitative Transfer Linker
Quick Trait Location

Correct Answer: B — Quantitative Trait Locus
A QTL is a genomic region associated with variation in a quantitative trait.

Q7. Which of the following is an important step in QTL mapping?

Only protein purification
Only microscopy
Genotyping and phenotyping a mapping population
Only RNA translation

Correct Answer: C — Genotyping and phenotyping a mapping population
QTL mapping requires both genetic marker information and measurements of the quantitative phenotype.

Q8. Marker-Assisted Selection primarily uses:

Protein concentration only
Molecular markers
Microscopy only
Random environmental variation

Correct Answer: B — Molecular markers
MAS uses DNA markers associated with desirable genes or QTLs to assist selection during breeding.

Q9. Which type of selection aims to recover the largest possible proportion of the recurrent parent's genome during marker-assisted backcrossing?

Foreground selection
Background selection
Negative selection
Phenotypic selection only

Correct Answer: B — Background selection
Background selection uses molecular markers distributed throughout the genome to identify individuals carrying a high proportion of the recurrent parent's genome.

Q10. Which statement about heritability is correct?

High heritability means the environment has no effect.
Heritability is always the same in every population.
Heritability is a population- and environment-dependent statistical measure.
Heritability measures only environmental variation.

Correct Answer: C — Heritability is a population- and environment-dependent statistical measure.
Heritability describes the proportion of phenotypic variation attributable to genetic variation within a specified population and environment. It does not mean that a fixed percentage of an individual's phenotype is genetic.

36. Quick Revision – One-Minute Notes