Name: モジュール9: 量的形質病変（QTL）のマッピング - CTGN (Module 9: Mapping Quantitative Trait Loci (QTL) - CTGN)
Uploaded: 2021-01-14T05:35:27.000Z
Duration: 56 min 18 s
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modules, most traits of interest in forest trees are quantitatively

inherited. That is, they are controlled by many genes,

each of which controls a modest amount of the variance

in that trait. A gene that controls some portion of the genetic

variance of a phenotypic trait is called a quantitative trait locus,

identify QTL and their relative location in the genome by

placing them on genetic maps. This is done by demonstrating

a statistically significant association between the

quantitative trait phenotype and one or more genetic

markers already located on a map. QTL mapping

is a powerful tool for elucidating the genetic architecture of

complex traits and provides a clearly defined approach for marker-assisted

selection in applied breeding or natural environment settings.

QTL mapping and give some examples of how it has been done

in forest trees. Additionally, we will reflect on

some of the limitations of the QTL approach using pedigree crosses.

to identify and map QTL are those previously noted for

construction of genetic maps themselves. The factors that distinguish

the need for high quality phenotypes for all the progeny being genotyped

and 2) a different set of analytical tools.

Let’s quickly review the points noted here.

Experimental Populations: For the most part,

pedigreed crosses such as those needed for genetic mapping are needed.

means a three generation intercross, though virtually any

cross can be used, including open-pollinated crosses and

You may improve your chances of detecting QTL by making the crosses

to ensure segregation of the traits of interest in the F2 progeny.

important. Studies have shown that 500 or more progeny

are required to avoid bias in the number of QTL identified

and the proportion of variation those QTL explain.

markers are multi-allelic, co-dominant markers that

could potentially tag as many as four alleles

the same set of markers used in making your genetic map.

to completely cover the genome is desirable.

Phenotypes: High quality measurement of the

traits of interest are essential. One way to dramatically

improve phenotypic trait estimates is to clonally replicate the progeny

in the study trials. In effect, this results

in an increase in trait heritability. We will leave

comments on the last two points, analytical tools and verification,

for later. Suffice it to say that what we seek are

associations between differences in phenotypic means

of genotypic classes, evaluated one locus at a time.

The subsequent effort to accurately locate significant

the concept of what constitutes a QTL, as might be

found in a three-generation intercross. Note

that the “deck is stacked”, so to speak, in the grandparent

generation. That is, crosses are made between parents that are

contrasting phenotypically. For this example we see that

grandparents that are homozygous for upper case alleles at

markers across a given linkage group appear to be associated with small

stature and trees homozygous for lower case alleles

seem to be of large stature. The F1 offspring of this

cross are intermediate in size, suggesting that the locus that

appears to be affecting tree size must be exhibiting additive gene

action (i.e. heterozygotes are intermediate

to either homozygote). In the segregating F2

generation, one can test mean tree size of all three marker genotypic

classes to determine if they vary from one another.

In this case, only locus B appears to show a relationship

between tree size and genotypic class. The logical

interpretation is that the locus affecting tree size must

reside near the B marker. How close are they to one another?

They may be only a few thousand base pairs apart,

pairs from one another. We can’t tell the difference at this point.

Remember from the genetic mapping module that mapping precision

is largely a function of how many meiotic events you have to look at.

As you will see, the confidence interval around

the location of a QTL is generally quite large.

Now image testing the genotypic classes of 75

markers spread across the genome for this same trait.

or many. Whatever your result, if you have done the

experiment correctly, you can have some confidence that the result is a

reflection of the real situation for that one specific pedigreed cross.

illustrative of realistic data that come from QTL studies.

Again, the basic concepts of QTL mapping are shown here.

For simplicity, this is illustrated using F2 offspring

derived from the intermating of two inbred lines.

In terms of markers, only three genotypes are possible,

and BB. Markers can be widely interspersed,

since recombination will be rare in a single generation.

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モジュール9: 量的形質病変（QTL）のマッピング - CTGN (Module 9: Mapping Quantitative Trait Loci (QTL) - CTGN)

trait

effect

single

population