advertisement

14 caratteri quantitativi

50 %
50 %
advertisement
Information about 14 caratteri quantitativi
Education

Published on February 11, 2008

Author: Paola

Source: authorstream.com

advertisement

Slide 1: Genetica quantitativa Obiettivi: Esaminare i primi studi che contribuirono allo sviluppo dei fondamenti di base della genetica quantitativa Descrivere i meccanismi attraverso i quali geni multipli contribuiscono insieme all’espressione fenotipica dei caratteri quantitativi Descrivere le componenti di base della variazione fenotipica e come queste sono usate per stimare l’ereditabilità di un carattere e la risposta alla selezione Quantitative Genetics: Quantitative Genetics But most traits are not discontinuous - rather they produce a continuous range of phenotypes e.g. from short to tall in humans. In Mendelian Genetics we typically study genes with discontinuous phenotypes. e.g purple or white flowers The differences between these phenotypes are thus quantitative, not qualitative. Typical Mendelian inheritance - discontinuous phenotypes: Typical Mendelian inheritance - discontinuous phenotypes Quantitative Genetics: Quantitative Genetics At first the lack of clear ratios for these traits seemed to contradict Mendelian laws. But now know that such traits are controlled by multiple genes each having a small effect on the phenotype and segregating in a normal Mendelian fashion - Quantitative trait loci (QTL) Slide 5: Homozygous parental pops. selected to have very different phenotypes - still show some environmental variation Plants selected from different parts of F2 produce F3 with corresponding phenotypes - proves F2 phenotype was partly genetically based. F2 - much greater variability - mean is intermediate in length variation here genetic + envir. F1 F1- intermediate - shows some variability (environmental) Typical inheritance where phenotypes show continuous range. F1- Intermediate- Shows some variability(environmental) Slide 6: NB - no nice 3:1, 9:3:3:1 ratios! This is the normal type of result for most traits. Due to:- 1. Multiple genes each having some cumulative effect on the phenotype - (QTL’S) plus 2. Environmentally caused variation Slide 7: How much of a variation in phenotype (VP) is due to genetic variation (VG) and how much to environmental variation (VE)? This can be expressed: VP = VG + VE. To work this equation, variation must be measured and then partitioned into genetic and environmental components. Statistical Tools The Mean: The Mean 1. Frequency distribution of a phenotypic trait can be summarized with two statistics, the mean and the variance. 2. The mean (average) represents the center of the phenotype distribution, and is calculated simply by adding all individual measurements and then dividing by the number of measurements added. Statistical tools The Variance and the Standard Deviation : The Variance and the Standard Deviation 1. Variance is the measure of how much the individual measurements spread out around the mean (how variable they are). a. Two sets of measurements may have the same mean, but different variances b. The variance (s2) is the average squared deviation from the mean. To calculate s2: i. Subtract the mean from each individual measurement. ii. Square the difference for each. iii. Add the squared values. iv. Divide by the number of original measurements minus 1 (n - 1). c. Standard deviation is used more often than variance, because it shares the same units as the original measurements (rather than units2 as in variance). Standard deviation is the square root of the variance. d. Table 23.2 shows sample calculations for variance and standard deviation. Graphs showing three distributions with the same mean but different variances: Peter J. Russell, iGenetics: Copyright © Pearson Education, Inc., publishing as Benjamin Cummings. Graphs showing three distributions with the same mean but different variances Slide 12: e. When mean and standard deviation are known, a theoretical normal distribution is specified. In a theoretical normal distribution: i. One standard deviation above or below the mean (± 1s) includes 66% of the individual observations. ii. Two standard deviations (± 2s) include 95% of the individual values. iii. Three standard deviations (± 3s) include > 99% of the individual values. 2. Variance and standard deviation provide information about the phenotypes of a group. Normal distribution curve showing proportions of the data in the distribution that are included within certain multiples of standard deviation: Peter J. Russell, iGenetics: Copyright © Pearson Education, Inc., publishing as Benjamin Cummings. Normal distribution curve showing proportions of the data in the distribution that are included within certain multiples of standard deviation Slide 14: CONTINUOUS DISTRIBUTIONS RESULT FROM TWO CAUSES Influence of multiple environmental factors Segregation of multiple genetic factors Slide 15: Studi di Johannsen : fattori genetici e ambientali influenzano l’espressione fenotipica Studi di Nilsson-Ehle: geni multipli influenzano un singolo carattere Slide 16: Gli esperimenti di W. JOHANNSEN con linee pure di Phaseolus vulgaris permisero la distinzione tra genotipo e gli effetti di fattori ambientali sul genotipo che insieme producono uno specifico fenotipo. Slide 17: In questa varietà auto-impollinante obbligata ci sono numerose linee pure che differiscono per certe caratteristiche come il peso medio dei semi. Queste differenze sono determinate geneticamente , ma per per una serie di ragioni, come per esempio la posizione del baccello sulla pianta e le risultanti differenze nell’ acqusizione di nutrienti,ogni pianta produce semi di diverso peso. Slide 18: Pure line selection in beans.From a mixed lot of the “Princess” bean, a Pure Line (No.1) was isolated that produced beans averaging 0.64 g in weight. Another Pure Line (No.19) produced beans averaging 0,35 g in weight. The avarage seed weights of progenies of beans selected from pure Line No.1 were similar to those of the parent line. Likewise, progenies of seeds selected from Pure Line No.19 were similar to their parent line in average seed weight. Variations in seed weight of beans within a pure line are due to environmental variations on the development of individual seeds. This experiment demonstrated that a mixed population of a self-pollinated crop may be separated into pure lines inherently different, but that further selection within a pure line is ineffective in changing the genotype of the line. Slide 19: JOHANNSEN scelse per la coltivazione i semi più leggeri e più pesanti nell’ambito della variazione fenotipica di linee pure per alcune generazioni successive senza ottenere un cambiamento del peso medio dei semi. Una selezione entro linee pure è perciò senza effetto. Sulla base di queste osservazioni JOHANNSEN coniò i termini genotipo e fenotipo. Slide 20: Ipotesi di W. Johannsen Sapendo che ciascun seme è omozigote: la differenza di peso tra le linee pure è di natura genetica; la differenza di peso entro la singola linea pura dipende da fattori ambientali. Herman Nilsson-Ehle: Herman Nilsson-Ehle Seed color in wheat Three genes act additively to determine seed color. The dominant allele of each gene adds an equal amount of redness; the recessive allele adds no color to the seed. A adds 1 unit of redness, a does not. B adds 1 unit of redness, b does not. C adds 1 unit of redness, c does not. Nilsson-Ehle’s Model: Nilsson-Ehle’s Model Slide 23: P F1 F2 Nilsson-Ehle’s crosses demonstrated that the difference between the inheritance of genes influencing quantitative characteristics and the inheritance of genes influencing discontinuous characteristics is the number of loci that determine the characteristic. Both quantitative (continuous) and discontinuous traits are inherited according to Mendel’s laws. Slide 24: Quantitative traits are influenced by the combined effects of numerous genes. These are called polygenic or multifactorial traits. The genes follow Mendelian laws of inheritance; however, multifactorial traits have numerous possible phenotypic categories. Environmental influences blur the phenotypic differences between adjacent genotypes. Slide 25: Number of phenotypic categories = (# gene pairs × 2) +1 Connecting the points of a frequency distribution creates a bell-shaped curve called a normal distribution. As the number of loci affecting the trait increases, the # phenotypic categories increases. Slide 26: INFLUENCE OF THE NUMBER OF LOCI ON THE DISTRIBUTION OF PHENOTYPES Slide 27: H. Nilsson-Ehle (1908) pointed out the enormous genotypic variation possible under a multi-factorial hypothesis. Sexual reproduction can produce a huge diversity of genotypes. With 10 independent loci and only 2 alleles at each there are, 3 10 combinations  60,000 If there are + and – alleles with a frequency of 0.5, the probability that an individual would be all + or all – is (1/4) 10 = 10 –6 Slide 28: n = # di geni 1/4n = Rapporto (%) di individui F2 che esprimono l’uno o l’altro fenotipo estremo 2n + 1 = numero totale di categorie fenotipiche possibili Slide 29: E. M. East Experiments by East (1911, 1916) crossing strains of plants widely differing in quantitative trait values confirmed the ideas of Shull and Nilsson-Ehle. Parental Types AA aa Aa F1 x F1 AA Aa aa F2 OUTBREAK OF VARIATION Inheritance of Ear Length in Corn : Inheritance of Ear Length in Corn 1. Emerson and East (1913) experimented with two pure-breeding strains of corn. a. Each strain shows little variation in ear length. i. The Black Mexican sweet corn variety has short ears (mean length 6.63 cm) with a standard deviation (s) of 0.816. ii. Tom Thumb popcorn has long ears (mean length 16.80 cm), and s = 1.887. b. The two strains were crossed, and the F1 plants interbred (Figure 23.9). i. The mean ear length in the F1 is 12.12 cm, approximately intermediate, and s = 1.519. ii. Since both parents were true-breeding, all F1 plants should have the same heterozygous genotype, and any variation in length would be due to environmental factors. iii. The mean ear length of the F2 is 12.89 cm, very similar to the F1, but in the F2, s = 2.252, reflecting its greater variability. iv. It is expected that the environment would have the same effect on the F2 that it had on the P and F1 plants, but it would not be expected to have more effect. v. The increased variability in the F2 most likely results from its greater genetic variation. Inheritance of ear length in corn: Peter J. Russell, iGenetics: Copyright © Pearson Education, Inc., publishing as Benjamin Cummings. Inheritance of ear length in corn Slide 32: An other example is East’s study of Nicotiana longiflora flower length in genetic crosses. a. He crossed a short-flowered strain (mean length of 40.4 mm) with a long-flowered strain (mean length of 93.1 mm). b. The F1 progeny (173 plants) had a mean flower length of 63.5 mm, intermediate to the parents. c. The F2 had a mean of 68.8 mm, very similar to the F1. But the F2 had a variance of 42.2 mm2, while F1 variance was only 8.6 mm2, indicating that more phenotypes occur among the F2 than among the F1. Slide 33: Nicotiana longiflora Slide 34: . Aside from the environmental influence, four observations emerge that apply generally to similar quantitative-inheritance studies: a. The F1 will have a mean value for the trait intermediate between the means of the two true-breeding parental lines. b. The mean value in the F2 is about the same as that for the F1. c. F2 shows more variability around the mean than the F1 does. d. Extreme values for the trait in the F2 extend farther into the parental range than the extreme values for the F1. . The data are not consistent with a single Mendelian locus, because the discrete classes expected do not occur. Slide 35: Heritability Heritability is the proportion of a population’s phenotypic variation attributable to genetic factors. To assess heritability: a. Measure the variation in the trait. b. Partition the variance into components attributable to different causes. ¨ Phenotype = genotype + environment + genotype * environment interaction VP = VG + VE + VGE VP = (VA + VD + VI) + VE + VGE Slide 36: VGE – genotype by environment interaction the proportion of phenotypic variance that is due to the inconsistency of genotypic expression in different environments. VA – additive genetic variance the proportion of genetic variance that is due to additive effects of alleles at loci controlling the quantitative trait VD – dominance genetic variance the proportion of genetic variance due to transient interactions between alleles at loci controlling the quantitative trait VI – epistatic genetic variance the proportion of genetic variance due to interactions among alleles at difference loci controlling the quantitative trait Slide 37: Heritability can be divided into two types, broad-sense and narrow-sense. The amount of variation among individuals resulting from genetic variance (VG) is the broad-sense heritability of a phenotype (VG / VP). Heritability ranges from 0–1, with 0 meaning no variation from genetic differences, and 1 meaning that all variation is genetically based. Broad-based heritability: i. Includes all types of genes and gene actions. ii. Does not distinguish between additive, dominance and interactive genetic variance. iii. Assumes that interaction between genotype and environment (VG x E) is not important. iv. Is therefore of questionable usefulness. Slide 38: Additive genetic effects are more often used, because this component allows prediction of the average phenotype of the offspring when phenotypes of the parents are known. a. For example, in a cross for a trait involving a single locus: i. One parent might be 10 cm tall, with the genotype A1A1, and the other parent 20 cm tall, with the genotype A2A2. ii. If the alleles are additive, the F1 (A1A2) will be 15 cm tall, while if one allele is dominant, the F1 will resemble one of the parents. Narrow-sense heritability is the proportion of the variance resulting from additive genetic variance. VA determines resemblance across generations, and responds to selection in a predictable way. Understanding Heritability : Understanding Heritability 1. Heritability estimates have limitations that are often ignored, leading to misunderstanding and abuse. Important qualifications and limitations of heritability: a. Broad-sense heritability does not indicate the extent to which a trait is genetic. Rather, it measures the proportion of the phenotypic variance in a population resulting from genetic factors. ii. If all individuals have the same genes at loci controlling a trait (e.g., eye or ear number), VG = 0, even though genes are clearly involved in producing the trait. ii.High heritability also does not mean that environment is unimportant. It may mean instead that environmental factors influencing the trait are relatively uniform across the population. Slide 40: c. Heritability is not fixed for a trait. It depends on the genetic makeup and the specific environment of the population d. Even if heritability is high in each of two populations and the populations differ markedly in a particular trait, one cannot assume that the populations are genetically different e. Traits shared by family members are familial traits and do not necessarily have high heritability. b. Heritability does not indicate what proportion of an individual’s phenotype is genetic. Heritability is a characteristic of a population, not an individual. How Heritability Is Calculated : How Heritability Is Calculated 1. Many of the methods used compare related and unrelated individuals, or compare individuals with different degrees of relatedness. When environmental conditions are identical: a. Closely related individuals have similar phenotypes when the trait is genetically determined. b. Related individuals are no more similar in phenotype than unrelated ones when the trait is environmentally determined. 2. Methods of calculating heritability include: a. Comparison of parents and offspring. b. Comparison of identical and nonidentical twins. c. Response-to-selection data. Heritability estimates: Heritability estimates Calculation of Broad-Sense Heritability Cross two pure lines and generate F1 and F2 progeny Calculate variance for a quantitative trait for each generation of this population (P1, P2, F1, F2) grown together S2F2 is equivalent to VP Assume no GxE Mean of S2 P1, S2 P2, and S2 F1 estimates S2E S2F2 = S2G + ((S2 P1 + S2 P2 + S2 F1 )/3) S2G = S2F2 - S2E H2 = S2G / S2F2 Regression: Regression 1. Regression analysis is used to determine the precise relationship between variables. a. A graph is plotted for the individual data points, one on the x axis and the other on the y. The regression is the line that best fits the points (the squared vertical distance from the points to the regression line is minimized). b. The regression line can be represented with the equation y = a + bx, where: i. x and y are values of the two variables. ii. b is the slope (regression coefficient). iii. a is the y intercept (the expected value of y when x is 0). c. The slope shows how much of an increase in the y variable is associated with a unit increase in the x variable. Fig. 23.7 Regression of sons’ height on fathers’ height: Peter J. Russell, iGenetics: Copyright © Pearson Education, Inc., publishing as Benjamin Cummings. Fig. 23.7 Regression of sons’ height on fathers’ height Fig. 23.8 Regression lines with different slopes: Peter J. Russell, iGenetics: Copyright © Pearson Education, Inc., publishing as Benjamin Cummings. Fig. 23.8 Regression lines with different slopes Slide 46: Heritability from parent-offspring regression is calculated by regression of data measuring the phenotypes of parents and offspring in a series of families. i. Random scatter across the plot indicates no relationship between the traits of parents and offspring, and thus low heritability. ii. Linear relationships between phenotypes of parents and offspring indicate that heritabifity is high (unless environmental effects have influenced the trait). iii. Slope of the parent-offspring regression line reflects the magnitude of heritability. a. The mean phenotype of the parents (mid-parent value) and mean phenotype of offspring are plotted with each point on the graph representing one family (Figure 23.13). Regression analysis is a common method for measuring the extent to which variation in a trait is genetically determined. When the mean phenotype of the offspring is regressed against the mean phenotype of the parents b = h2 narrow-sense heritability. Slide 47: (1) If the slope is 0, narrow-sense heritability (h2) is also 0. (2) If the slope is 1, offspring have a phenotype exactly intermediate between the two parents, and additive gene effects account for the entire phenotype. (3) If the slope is between 0 and 1, both additive genes and nonadditive factors (dominant and epistatic genes, environment) affect the phenotype Slide 48: When the mean phenotype of the offspring is regressed against the phenotype of only one parent, the narrow-sense heritability is twice the slope(b = 1/2 h2 ), because the offspring shares only 1/2 its genes with the parent. The factor by which the slope is multiplied to obtain heritability increases as the distance between relatives increases. Heritability estimates are not precise and may vary widely for the same trait in the same organism. Fig. 23.13 Three hypothetical regressions of mean parental wing length on mean offspring wing length in Drosophila: Peter J. Russell, iGenetics: Copyright © Pearson Education, Inc., publishing as Benjamin Cummings. Fig. 23.13 Three hypothetical regressions of mean parental wing length on mean offspring wing length in Drosophila Response to Selection : Response to Selection 1. Both plant and animal breeding and evolutionary biology are concerned with genetic change in groups of organisms, and use the methods of quantitative genetics to predict rate and magnitude of genetic change. 2. Natural selection is based on the idea that certain genotypes leave more offspring than others, leading to adaptive change in the population. 3. Artificial selection (selective breeding) by humans mimics this process, and can be a powerful tool for rapid change in a species (e.g., domestic dogs). 4. In both artificial and natural selection, genetic variation is a key factor in determining the rate and type of evolution, and so quantifying it is important. Estimating the Response to Selection : Estimating the Response to Selection 1. Phenotypes will change from one generation to the next in response to selection if the appropriate genes are present in the population. The amount of phenotypic change in one generation is the selection response, R. a. An example is body size in Drosophila melanogaster. i. A geneticist begins by weighing flies to determine the average weight in the population (e.g., 1.3 mg). ii. The largest flies (e.g., 3 mg) are selected for breeding. iii. Weights of the F1 are compared with those of the original unselected population. iv. If they are significantly larger, response to selection has occurred. b. The selection response is dependent upon: i. Narrow-sense heritability. ii. Selection differential (s), the difference between the mean phenotype of the selected parents and that of the unselected population. (In the Drosophila example,s = 3.0 mg - 1.3 mg = 1.7 mg). Slide 52: c. Selection response relates to selection differential and heritability by the “breeder’s equation,” R = h2S. i. In the example, R (response to selection) is the difference in mean body weight between F1 flies and the original population (R = 2.0 mg - 1.3 mg = 0.7 mg). ii. R and S are known, so the equation can be solved for h (narrow-sense heritability): h2 = R/S = 0.7 mg/1.7 mg = 0.41. iii. This is a common method for determining heritability of many traits. d. As long as genetic variation is present, traits will respond to selection in each generation. ii. Eventually the response to selection decreased. Possible explanations include: (1) No further genetic variation for the trait exists within the population. (2) Some variation still exists, but genes for the selected trait have detrimental effects on other traits due to genetic correlations. Slide 54: Knowledge that there is a genetic component to a trait does not allow accurate predictions about offspring. Another analysis method for phenotypic variance, genotype-by-environment (G X E) interaction, is needed. a. G X E variance exists when the relative effects of the genotypes differ among environments b. An example is temperature affecting plant height: i. In a cold environment, height of genotype AA plants averages 40 cm, while those with genotype Aa are 35 cm. ii. In a warm climate, genotype AA is 50 cm tall, while genotype Aa is now 60 cm. iii. Both genotypes grow taller in warm temperatures (an environmental effect). There is also a genetic effect, but it depends on the environment. Genetic-environmental interaction is represented by VGx E. Slide 55: Norm of reaction More often, several genotypes produce the same phenotype for a polygenic trait. Reasons for this include: (1) Dominance, producing the same phenotype in both heterozygous and homozygous dominant individuals. (2) Epistasis, resulting from control of the expression of other loci. Instead, a range of phenotypes is produced when environmental factors affect the trait. Each genotype will have a range of possible phenotypes, the norm of reaction. Fig. 23.12 Hypothetical example of the effects of genes and environments on plant height: Peter J. Russell, iGenetics: Copyright © Pearson Education, Inc., publishing as Benjamin Cummings. Fig. 23.12 Hypothetical example of the effects of genes and environments on plant height

Add a comment

Related presentations

Related pages

2.caratteri e scale di misura flashcards | Quizlet

Vocabulary words for 2.caratteri e scale di misura. Includes studying games and tools such as flashcards.
Read more

Südtirols Wald: Holzmesskundliche Daten | Abteilung ...

Quelle: INFC, 2007 – I caratteri quantitativi - CFS – Ispettorato Generale, CRA - ISAFA, Trento ... 14,5. VORRAT STEHENDES TOTHOLZ. m ...
Read more

PROF.SSA SILVIA PACEI CORSO DI LAUREA IN ECONOMIA ...

14 CARATTERI QUANTITATIVI DISCRETI X = carattere quantitativo discreto xi = i.esimo livello del carattere (i = 1, 2, … , m) La struttura di base della ...
Read more

Introduzione alla statistica e ai dati - YouTube

Introduzione alla statistica e ai dati ... Published on May 14, ... Impara a riconoscere i caratteri qualitativi e quantitativi, ...
Read more

Nessun titolo diapositiva - bagliacca.altervista.org

caratteri quantitativi; ma anche gli effetti dei caratteri ... 14. 15 Equazione descrittiva Modelli matematici: •Modello a compartimenti = compartimental ...
Read more

STATISTICA - quizmedicinaveterinaria.altervista.org

Caratteri: Qualitativi Quantitativi o Discreti o Continui Esistono caratteri che possono variare da quantitativi a qualitativi con ... 11/14/2013 3:18:15 ...
Read more

Variabilità di caratteri quantitativi in ceppi di ...

Variabilità di caratteri quantitativi in ceppi di Drosophila subobscura. PDF. Full access. DOI: 10.1080/11250005409438186 ... Published online: 14 Sep 2009
Read more

PPT - Corso di statistica PowerPoint Presentation - ID:6606471

Caratteri quantitativi (VARIABILI): assumono intensità rappresentate da numeri reali . ... 0,14 . 0,74 . 100 . 0,0010 . 400 -- | 500 . 0,10 . 0,84 . 100 ...
Read more

Seminari di Statistica PoliMI-Bocconi-CNR

... 20133 Milano PROGRAMMA 14:30 Chiara Sabatti Department of Human ... Pearson and Fisher fu quello dell'ereditarieta` dei caratteri quantitativi.
Read more