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Advances and applications in bioinformatics and chemistry : AABC (1)
Jaimes-Díaz, Hueman (2)
Maldonado-Rodríguez, Rogelio (2)
Méndez-Tenorio, Alfonso (2)
Beattie, Kenneth L (1)
Carreño-Durán, Luis R (1)
Casique-Almazán, Janet (1)
Espinosa-Lara, Juana M (1)
García-Chéquer, Adda J (1)
Larios-Serrato, V (1)
Olguín-Ruiz, Gabriela Edith (1)
Palma-Orozco, Rosaura (1)
Pérez-Cervantes, Hilda (1)
Reyes-Prieto, Fabián (1)
Sánchez-Vallejo, Carlos Javier (1)
Zepeda-López, Héctor (1)
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Design of a set of probes with high potential for influenza virus epidemiological surveillance
Carreño-Durán, Luis R
Sánchez-Vallejo, Carlos Javier
Olguín-Ruiz, Gabriela Edith
An Influenza Probe Set (IPS) consisting in 1,249 9-mer probes for genomic fingerprinting of closely and distantly related Influenza Virus strains was designed and tested in silico. The IPS was derived from alignments of Influenza genomes. The RNA segments of 5,133 influenza strains having diverse degree of relatedness were concatenated and aligned. After alignment, 9-mer sites having high Shannon entropy were searched. Additional criteria such as: G+C content between 35 to 65%, absence of dimer or trimer consecutive repeats, a minimum of 2 differences between 9mers and selecting only sequences with Tm values between 34.5 and 36.5oC were applied for selecting probes with high sequential entropy. Virtual Hybridization was used to predict Genomic Fingerprints to assess the capability of the IPS to discriminate between influenza and related strains. Distance scores between pairs of Influenza Genomic Fingerprints were calculated, and used for estimating Taxonomic Trees. Visual examination of both Genomic Fingerprints and Taxonomic Trees suggest that the IPS is able to discriminate between distant and closely related Influenza strains. It is proposed that the IPS can be used to investigate, by virtual or experimental hybridization, any new, and potentially virulent, strain.
IPS; fingerprinting; Virtual Hybridization; Shannon Entropy; Microarray; Influenza virus
LifePrint: a novel k-tuple distance method for construction of phylogenetic trees
García-Chéquer, Adda J
Espinosa-Lara, Juana M
Beattie, Kenneth L
Advances and applications in bioinformatics and chemistry : AABC
Here we describe LifePrint, a sequence alignment-independent k-tuple distance method to estimate relatedness between complete genomes.
We designed a representative sample of all possible DNA tuples of length 9 (9-tuples). The final sample comprises 1878 tuples (called the LifePrint set of 9-tuples; LPS9) that are distinct from each other by at least two internal and noncontiguous nucleotide differences. For validation of our k-tuple distance method, we analyzed several real and simulated viroid genomes. Using different distance metrics, we scrutinized diverse viroid genomes to estimate the k-tuple distances between these genomic sequences. Then we used the estimated genomic k-tuple distances to construct phylogenetic trees using the neighbor-joining algorithm. A comparison of the accuracy of LPS9 and the previously reported 5-tuple method was made using symmetric differences between the trees estimated from each method and a simulated “true” phylogenetic tree.
The identified optimal search scheme for LPS9 allows only up to two nucleotide differences between each 9-tuple and the scrutinized genome. Similarity search results of simulated viroid genomes indicate that, in most cases, LPS9 is able to detect single-base substitutions between genomes efficiently. Analysis of simulated genomic variants with a high proportion of base substitutions indicates that LPS9 is able to discern relationships between genomic variants with up to 40% of nucleotide substitution.
Our LPS9 method generates more accurate phylogenetic reconstructions than the previously proposed 5-tuples strategy. LPS9-reconstructed trees show higher bootstrap proportion values than distance trees derived from the 5-tuple method.
phylogeny; sequence alignment; similarity search; tuple; viroid
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