This set of Bioinformatics Multiple Choice Questions & Answers (MCQs) focuses on “Comparative Approach”.
Explanation: Because of the much larger number of secondary structures to be computed, a more simplified energy rule has to be used to increase computational speed. Thus, the prediction results are not always guaranteed to be better than those predicted by Mfold.
2. The comparative approach uses basic RNA structure based predictions to infer a consensus structure.
Explanation: The comparative approach uses multiple evolutionarily related RNA sequences to infer a consensus structure. This approach is based on the assumption that RNA sequences that deem to be homologous fold into the same secondary structure.
3. To distinguish the conserved secondary structure among multiple related RNA sequences, a concept of “covariation” is used.
Explanation: It is known that RNA functional motifs are structurally conserved. To maintain the secondary structures while the homologous sequences evolve, a mutation occurring in one position that is responsible for base pairing should be compensated for by a mutation in the corresponding base-pairing position so to maintain base pairing and the stability of the secondary structure.
4. ______ of covariation can be ______ to the RNA structure and functions
a) Any lack, deleterious
b) Any lack, benign
c) Any abundance, deleterious
d) Any inadequacy, advantageous
Explanation: Based on this rule, algorithms can be written to search for the covariation patterns after a set of homologous RNA sequences are properly aligned. The detected correlated substitutions help to determine conserved base pairing in a secondary structure.
a) relatively distinct
d) least abundant
Explanation: predicting secondary structures for each individual sequence may produce errors, by comparing all predicted structures of a group of aligned RNA sequences and drawing a consensus. Hence, the commonly adopted structure can be selected; many other possible structures can be eliminated in the process.
6. The comparative-based algorithms can be further divided into two categories based on the type of input data.
Explanation: The comparative-based algorithms can be further divided as mentioned. One requires predefined alignment and the other does not.
7. The type of algorithm that requires predefined alignment, requires the user to provide _______ alignment as input.
a) not necessarily an alignment
b) multiple only
c) pairwise or multiple
d) pair wise only
Explanation: As the name suggests, it does require predefined alignment, the option ‘a’ becomes irrelevant. The sequence alignment can be obtained using standard alignment programs such as T-Coffee, PRRN, or Clustal. Based on the alignment input, the prediction programs compute structurally consistent mutational patterns such as covariation and derive a consensus structure common for all the sequences.
8. The type of algorithm that _____ predefined alignment is ______ for reasonably conserved sequences.
a) doesn’t require, more successful
b) requires, less successful
c) doesn’t require, relatively successful
d) requires, relatively successful
Explanation: The requirement for using this type of program is an appropriate set of homologous sequences that have to be similar enough to allow accurate alignment, but divergent enough to allow covariations to be detected. If this condition is not met, correct structures cannot be inferred.
a) are, will be
b) are, will not be
c) are not, will not be
d) are not, possibly will not be
Explanation: The selection of one single consensus structure is also a drawback because alternative and evolutionarily unconserved structures are not predicted. The RNAalifold is an example of this type of program based on predefined aligned sequences.
10. Which of the following is true about the RNAalifold?
a) Dynamic programming is not involved
b) Minimum free energy method is not used
c) Only minimum free energy is used
d) Covariation information is taken into consideration
Explanation: It is a program in the Vienna package. It uses a multiple sequence alignment as input to analyze covariation patterns on the sequences. A scoring matrix is created that combines minimum free energy and covariation information. Dynamic programming is used to select the structure that has the minimum energy for the whole set of aligned RNA sequences.
Sanfoundry Global Education & Learning Series – Bioinformatics.
To practice all areas of Bioinformatics, here is complete set of 1000+ Multiple Choice Questions and Answers.