D9BrapaS1 resides in a segment of DNA on chromosome A09 that does not contain any annotated genes or other genomic features. Alignment of these alleles with the B. This indel has been deposited in to the dbSNP 9 database ss A search of the B. Alignment of the comparable portion of the Bra sequence indicates that the largest allele of D9BrapaS4 is nearly identical to the Bra sequence in the BRAD database except for a bp deletion in Bra in the repetitive DNA region of the marker.
Size variation between the alleles of D9BrapaS4 in RCBr is due to a multiple indels designated by ss , ss , and ss Due to the repetitive DNA sequence, multiple sequence alignments are possible and we cannot presently identify the exact position of the indels. Bra is a predicted gene based on similarity to Arabidopsis thaliana gene AT4G Both of these homologous genes are predicted to encode proteins with a protein phosphatase 2C PP2C domain near the C-terminus and a ribonuclease E rne domain in the second exon.
They are all in-frame deletions except for one case in allele 2 of D1BrapaS1 where two subsequent deletions preserve the reading frame.
In contrast, there is very little variation in the section of the gene predicted to encode a PP2C domain. Four different alleles of D1BrapaS1 show four different combinations of in-frame deletions in Bra The sequence shown is the portion of Bra that is predicted to encode an rne domain and lies within the marker D1BrapaS1.
The substitution is a synonymous polymorphism in the third position of a serine codon. Among the markers we have found to be most suitable for teaching laboratory use, two of the VNTR-type and one of the SNPs were expected to be on chromosome A09, the chromosome which we previously reported to hold the anthocyaninless locus Burdzinski and Wendell, Genetic map of the anthocyaninless locus relative to A09 marker reported in this paper.
Map distances are Kosambi centimorgans. For each strain, we determined the genotype of 20 randomly chosen plants grown from seeds obtained directly from Carolina Biological Supply.
It was also the only strain in which we detected all three alleles of D9BrapaS4. For each marker, the strains tested usually had the same major allele. The distribution of the genotypes in the plants tested did not deviate from Hardy-Weinberg expectations not shown. Estimated marker allele frequencies in fast plants strains from Carolina Biological Supply.
We have developed three strains of RCBr with genotypes optimized for use of these markers in an instructional lab. The strains vary in both the easy to score Mendelian loci anthocyaninless purple or non-purple stem color and yellow-green green or yellow-green leaf color , and the DNA markers we have developed. The DNA-based genetic markers that we have developed were intentionally designed for science education which is the main use of RCBr also known as Fast Plants.
They can be used as both markers for transmission genetics and provide the basis for extensions into molecular biology. The sequence data obtained can then be the basis of further exploration of the B.
The markers turn out to represent a wide variety of genomic features. Of the VNTR-type markers, one is in a non-genic region, one is within the intron of a gene, and one is within the open reading frame of a gene. Of the SNPs, one is in an intron and one is in the open reading from of a gene, although it is a synonymous substitution. Instructors can use the DNA sequence information we present here to develop lessons for students to study the possible impact on gene function of the sequence variation of the alleles.
Three of the markers form a linkage group with the anthocyaninless locus allowing them to be used in laboratory projects in genetic linkage and mapping. They are also excellent tools for projects such as paternity testing. We have previously described a laboratory project using RCBr to perform paternity testing, but the previous design used microsatellite markers Wendell and Pickard, which can pose difficulties for lab instructors due to the need for polyacrylamide gels to resolve them.
However, the markers we report here can be detected and alleles resolved in the most simple agarose slab gels. The data we provide on population allele frequencies in RCBr strains will be valuable to instructors using these markers for educational labs. Seeds for these strains are available by request to Douglas Wendell This could result if the repetitive DNA elements that we have selected are not prone to polymorphism, but could also result if or the RCBr populations have a low rate of polymorphism.
The latter explanation is consistent with previous work in which we tested microsatellite markers that had been developed for Brassica crop species for the usefulness in RCBr.
Out of 37 primer pairs that amplified a product in RCBr DNA we only found 22 to be polymorphic and only 11 that had more than two alleles in RCBr Burdzinski and Wendell, , despite the fact that microsatellites usually have multiple alleles. Because the intensity of staining of DNA in gels by dyes, whether fluorescent or visible, is proportional to the mass of DNA in a band, we encountered a problem of markers where the lower molecular weight bands of the cut allele were too faint for student to reliably detect.
Another complication was that in some cases the restriction enzyme that recognized the SNP also had multiple recognition sites close to the SNP. Teutonico J. Pires T. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access. Blakeslee AD Effect of induced polyploidy in plants. Comai L Genetic and epigenetic interactions in allopolyploid plants. Science — Google Scholar.
Gomez-Campo C Biology of crassica coenospecies, 4th edn. Elsevier, Amsterdam Google Scholar. Euphytica — CrossRef Google Scholar. J Econ Entomol — Google Scholar. Genetics — PubMed Google Scholar. The best way to combat this problem is to choose markers that have the lowest tendency to produce these extraneous bands. Figure 4. When microsatellite PCR products are resolved on nondenaturing polyacrylamide gels, in addition to the expected band from amplification of the genomic DNA, many extraneous bands are also observed.
Our evaluation plan was reviewed and approved by the Oakland University Institutional Review Board and ruled exempt. All student participation was by consent. We made observations on the project both for technical success Did the methods work in the hands of the students?
Evaluation of technical success came from in-class observation and examination of students' experimental results. The evaluation of the learning of concepts came from an examination of final lab reports compared with a pretest given at the beginning of the semester, from in-class observations, and from interviews with student volunteers.
Because we wanted the students to respond as freely and honestly as possible, the faculty member who evaluated the students' responses D. Although our objective was to evaluate the specific materials for the paternity exclusion project, our observations also provided insights on the students' general preparation for lab work. We observed inappropriate technique in the most basic of molecular biology methods such as measuring with micropipettors and mixing the microliter-scale volumes of liquids as must be done for DNA purification and analysis.
Without specific and direct discussion about how to use the micropipettes, some liquids end up at the top of vials, whereas other components get pipetted to the bottom or middle of the vials. Detection of this problem and coaching of proper technique reduced this problem. Generally, there are three points in this laboratory project at which students may experience technical failure: obtaining DNA, staining of gels, and setting up PCR reactions.
At each of these points, students were given the opportunity to repeat the step. It became evident to us how critical it is that time for students to redo things be built into the class schedule. As scientists, we all know that science is about experimentation, and we also know that experiments do not always work. Students should learn to improve their technique and to be accustomed to the idea of having to do something over if it does not work the first time.
Among failed preparations, low yield was the most common problem. Occasionally we have observed degraded DNA, as evidenced by no high-molecular-weight material but only a low-molecular-weight smear.
In the event of a failed purification, students were allowed a second attempt, and all second attempts were successful. Failure to obtain microsatellite genotype data can occur either because a PCR reaction did not produce a product or because the silver staining of the gel failed. Failure in staining appeared to be due to either excessive incubation with the developing solution or simply using the wrong reagent at a given step in the protocol.
Both types of failure were reduced with repeated experience Figure 5 B. In the case of a failed PCR reaction, it appeared that the most common reason was error in combining the components of the reaction mixture, because a second attempt performing PCR from the same original DNA sample was almost always successful.
Figure 5. Two gels demonstrating the value of giving the students a second attempt. The student was allowed to repeat the PCR and gel with much better results B. All students attempted to genotype their subjects for two different microsatellite markers, and most obtained enough data to work with. Almost two-thirds of students obtained microsatellite data on all four of their individuals for at least one marker. Among the rest, almost all still obtained enough data to perform interpretation.
Only one-eighth of students obtained genotype data on all four of their plants for both markers as in Figure 2 , and out of a class of 29 students, only one failed to obtain any microsatellite genotype data by the end of the semester.
An example of incomplete data that can still provide the student with experience in interpretation is given in Figure 6 , in which the student was unable to obtain marker data for the Mother.
In the analysis, the student first had to realize that because of missing data from the Mother, both of the Child's alleles must be viewed as potentially coming from its father. Compare this to the results of a different student shown in Figure 2 in which the Child is heterozygous, but it can be clearly determined which of its two alleles came from the Mother. In this run of the experiment, the correct conclusion is that the available data do not allow the exclusion of either Alleged Father.
Note that though the case shown in Figure 6 was unsuccessful for paternity exclusion, it was fully successful for requiring the student to practice analytical thinking skills. Figure 6.
Example of a gel in which a student did not obtain microsatellite data on all individuals in the experiment but was still able to perform some analysis. Data are missing for the Mother. The student can still perform analysis, though with the given data, neither Father can be excluded. The effect of the lab on conceptual learning was more difficult to evaluate because most students in the genetics lab course were taking the genetics lecture at the same time.
However, we were able to draw a few conclusions. We knew from the same baseline data set that roughly two-thirds of the students had difficulty answering simple inheritance questions about Mendelian genetics.
These students, for example, could not articulate inheritance patterns given a specific example. By the end of the paternity exclusion laboratory experience, all students asked during exit interviews could explain and respond to questions about linkage relationships and inheritance patterns, using data sets or information different from their own data set. More importantly, however, all laboratory write-ups from all students enrolled in the genetics class clearly indicated that they had an understanding of the paternity exclusion concepts and could interpret their own data sets appropriately.
Student responses in independently conducted focused interviews before, during, and after the completion of the course indicated that students were able to articulate a growing depth of understanding both of laboratory techniques in DNA extraction processes and interpreting data collected from PCR and silver staining. Laboratory write-ups also indicated understanding of specific processes and data interpretation. A critical component to student understanding of this paternity exclusion laboratory exercise was instructor observation and questions posed to students as they conducted their laboratory work.
For example, the believability factor discussed previously was an issue e. In summary, in this article we have described the development, use, and evaluation of a series of what we believe to be cost-effective, paternity exclusion laboratory exercises suitable for a to wk undergraduate genetics laboratory course. The protocols used have been successfully implemented for 2 yr and have provided students with opportunities to develop technical laboratory skills and gain confidence in using common laboratory apparatus.
Additionally, students were able to successfully collect and interpret unique data sets from DNA extraction, purification, PCR, and gel electrophoresis, having enough time to repeat procedures where necessary. The ability to repeat procedures allowed students to critically reanalyze their procedures and refine their techniques, giving them confidence in their abilities to conduct viable investigations and draw conclusions from their unique data sets.
We are especially interested in determining whether our findings are replicated and in ways to further improve the protocols. When the results are returned, click on a region of sequence similarity to connect it with its partner region. To modify the extent of genomic region analyzed, drag the slider bars located at the end of the genomic regions to zoom in on a region, and either specify an exact amount of sequence up and downstream of the anchor gene, or modify all up and down regions by the same amount.
Use the slider bars to adjust the regions so that only syntenic regions are compared and rerun the analysis. To change the display order of the sequences, drag the sequence submission boxes around relative to one another. After identifying orthologs to TOC1 in B. Prior experimental work identified a DNA binding sequence, dubbed EE, in over 30 circadian rhythm cycling genes whose peak expression was at the end of the day Harmer et al. While, as expected, there is extensive sequence conservation across protein coding regions, there are additional regions of sequence similarity in the CNSs.
Such conservation is assumed to be due to purifying selection providing that enough evolutionary time has passed to randomize non-functional sequences Freeling and Subramaniam, Figure 6. A Gene models are composite arrows where green or yellow regions represent protein coding sequence, blue is mRNA, and gray is the full extent of the gene.
Regions of sequence similar are as in Figure 5 and were identified using BLASTN; such regions are in the opposite orientation if drawn below the dashed line. In any case, analysis of CNSs among homologous syntenic gene sets identifies putative regulatory sequences for further experimental functional characterization.
Highlight all of the connections between regions of sequence similarity by holding the Shift key and clicking on a colored box.
To get information about a particular region of sequence similarity, click on that colored box without holding the Shift key. While every genome is sacred, it is essential to have the appropriate computational tools to analyze a genome at various scales.
Likewise, comparative analyses of a genome to itself and to related species are required in order to understand how a genome and its genetic components have evolved. The B. Besides being from an agronomically important and morphological diverse clade of plants, its close phylogenetic relationship to the model plant system A.
Due to the timing and phylogenetic placement of the Brassica hexaploidy event, and the wealth of information and genetic tools available for A. It is sufficiently diverged from Arabidopsis to permit the in-depth characterization of its genome structure, gene retention patterns, and conserved CNSs. The example analyses provided above show how to extract a variety of curious patterns and scientific insights from the Brassica genome through comparison to Arabidopsis.
The next set of genomic resources of benefit to the Brassica , Arabidopsis , genome evolution, and gene regulation research communities will be extensive functional genomics data for B.
However, to make the most use of such data, they will need to be integrated into comparative genomics platforms such as CoGe. The vision would be to continue these analyses by overlaying and integrating functional data to investigate the regulation, usage, and timing of TOC1 in Arabidopsis and its syntenic orthologs in B. This would permit further characterization of the CNSs found between these sequences and ask questions such as: why has B. What is the functional consequence of retaining or losing particular CNSs?
Is there something special about the truncation of intron 1 in Bra? Sequencing genomes and obtaining their functional data is relatively inexpensive, analyzing these data to transform genomic information into knowledge needs to be too.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. We would like to thank the reviews for the their insightful and helpful comments in improving this paper.
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