* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Analysis of Monohybrid and Dyhybrid Crosses Lab
Gene nomenclature wikipedia , lookup
Behavioural genetics wikipedia , lookup
Site-specific recombinase technology wikipedia , lookup
History of genetic engineering wikipedia , lookup
Genetic engineering wikipedia , lookup
Public health genomics wikipedia , lookup
Gene expression profiling wikipedia , lookup
Gene expression programming wikipedia , lookup
Artificial gene synthesis wikipedia , lookup
Pharmacogenomics wikipedia , lookup
Human genetic variation wikipedia , lookup
Genomic imprinting wikipedia , lookup
Genome (book) wikipedia , lookup
Hardy–Weinberg principle wikipedia , lookup
Population genetics wikipedia , lookup
Designer baby wikipedia , lookup
Quantitative trait locus wikipedia , lookup
Genetic drift wikipedia , lookup
Analysis of Monohybrid and Dihybrid Crosses Lab Introduction to Genetic Models Using Corn, Zea mays When Mendel crossed peas, he found phenotypic ratios remarkably close to those predicted by his model of inheritance. However, remember that the laws of heredity (a genetic model) predict the probabilities of certain combinations of genetic traits occurring in offspring. In real unions of egg and sperm, we don’t expect to see ratios that correspond exactly to the probabilities predicted by a model. In this lab we will work with probabilities of phenotypic classes in corn. The phenotypic classes we will examine are traits related to kernel shape and color. The color phenotype of maize (corn) kernels usually depends on the pigmentation of the aleurone (a layer of cells between the endosperm [central tissue] and the pericarp covering). If the aluerone is colorless, then the kernel appears to be the color of the underlying endosperm. The shape phenotype is related to the conversion of photosynthetic sugars products to starch and is therefore referred to often as the starchy/sweet gene. The alleles of this gene are the T allele that controls the conversion of sugar to starch in the maturing kernel, and the sugary (t) allele that elevates the level of the water-soluble polysaccharide phytoglycogen and decreases starch. Kernels are wrinkled in appearance when dried for kernels that only have t alleles. The wild-type T allele encodes starch debranching enzyme I. Monohybrid cross The ears you have contain the F2 seed (kernels) of an original cross between parents that were homozygous dominant (RR) and homozygous recessive (rr) for the aleurone color gene. Color gene: Purple allele = R Yellow allele = r 1. What are the expected phenotypic and genotypic ratios? Please show/explain how you derived your answers. 2. Count and record the number of kernels in the different phenotypes: Phenotypes Number of Kernels ____________________ ________________ ____________________ ________________ 3. Using Chi-square analysis, determine whether or not your data fit the expected phenotypic ratio. You should include: 1) null hypothesis, 2) all work in chi-square calculations and 3) do you reject or fail to reject your null hypothesis. Dihybrid cross Your ear of corn for this exercise again differs in color. The second trait controls whether the texture of the kernels is smooth or rough. Color gene: Purple allele = R yellow allele = r Shape gene: Round (starchy) allele = T Wrinkled (sweet) allele = t The second set of ears you have contain the F2 seed (kernels) of an original cross between parents that were homozygous dominant for the aleurone color and sugary genes (RRTT) and homozygous recessive for the aleurone color and sugary genes (rrtt). 1. What are the expected phenotypic and genotypic ratios? Please show/explain how you derived your answers. 2. Count and record the number of kernels in the different phenotypes: Phenotypes Number of Kernels ____________________ ________________ ____________________ ________________ ____________________ ________________ ____________________ ________________ 3. Using Chi-square analysis, determine whether or not your data fit the expected phenotypic ratio. You should include: 1) null hypothesis, 2) all work in chi-square calculations and 3) do you reject or fail to reject your null hypothesis.