Application of information theory to DNA sequence analysis: A review

Román-Roldán, Ramón; Bernaola‐Galván, Pedro; Oliver, José Luis Tejera

doi:10.1016/0031-3203(95)00145-x

Cited by 73 publications

(59 citation statements)

References 18 publications

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“…This aspect of entropy has been exploited within molecular biology (Román-Roldán et al 1996) and, in particular, with regard to DNA regulatory binding sites and the question of how much ''information'' is required to identify such regions (Schneider et al 1986). These formal aspects of the entropy are of secondary importance for the present analysis.…”

Section: Measurement Of Diversitymentioning

confidence: 99%

The Distribution of Variation in Regulatory Gene Segments, as Present in MHC Class II Promoters

et al. 1998

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Diversity in the antigen-binding receptors of the immune system has long been a primary interest of biologists. Recently it has been suggested that polymorphism in regulatory (noncoding) gene segments is of substantial importance as well. Here, we survey the level of variation in MHC class II gene promoters in man and mouse using extensive collections of published sequences together with unpublished sequences recently deposited by us in the EMBL gene bank using the Shannon entropy to quantify diversity. For comparison, we also apply our analysis to distantly related MHC class II promoters, as well as to class I promoters and to class II coding regions. We observe a high level of intraspecies variability, which in mouse but not in man is localized to a significant extent near the binding sites of transcription factors-sites that are conserved over longer evolutionary distances. This localization may both indicate and enhance heterozygote advantage, as the presence of two functionally different promoters would be expected to confer flexibility in the immune response.A surge of interest in the variability of regulatory, noncoding gene segments is under way. Collections have been made of promoter sequences for MHC class I and class II genes in man (Louis et al. 1993;Yao et al. 1995) and class II in mouse (Janitz et al. 1997a), which add substantially to the information previously available for promoter sequences in the hemoglobin (Weatherall 1986;Labie and Elion 1996) and glucose-6-phosphate dehydrogenase (Vulliamy et al. 1992) genes. These are all genes that encode ''extrovert'' proteins that handle diverse foreign structures such as antigens and parasites, in contrast to the ''introvert'' proteins that handle conserved structures internal to the body (Mitchison 1997); hemoglobin and glucose-6-phosphate dehydrogenase have been included in this list as extrovert proteins, as the high level of polymorphism evident in their structural genes results largely from their interaction with malaria parasites. The genes that encode extrovert proteins often vary in their coding sequences, so as to provide a range of binding sites for these foreign structures, and vary also in their noncoding regions (for reference, see Mitchison 1997). Variation in noncoding gene segments is also evident to a lesser extent among genes encoding introvert proteins, particularly among cytokines (and their receptors and natural antagonists) (Daser et al. 1996). The functional consequences of this promoter sequence variation is not generally known, but its importance in determining expression level is becoming clearer for the class II MHC genes (Louis et al. 1994;Woolfrey and Nepom 1995), the ACE I gene (Villard et al. 1996), and cytokines genes (Messer et al. 1991;Pociot et al. 1992). For these MHC genes, valuable collections have been made of very distantly related sequences (Benoist and Mathis 1990), which enable comparisons to be made with the level of intraspecific variation. Thus, the basis for systematic study of this form of variation is no...

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Section: Measurement Of Diversitymentioning

confidence: 99%

The Distribution of Variation in Regulatory Gene Segments, as Present in MHC Class II Promoters

et al. 1998

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“…This analogy was established by several researchers in the past in works as early as Jukes and Gatlin (1971), Yockey (1978), Román-Roldán et al (1996), Battail (2004) and Konopka (2006). A key element of the analogy is the ability to quantify the information which is provided by the entropy as an information measure (Shannon, 1948).…”

Section: Introductionmentioning

confidence: 99%

The information capacity of the genetic code: Is the natural code optimal?

Kuruoğlu

Arndt

2017

Journal of Theoretical Biology

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A B S T R A C TWe envision the molecular evolution process as an information transfer process and provide a quantitative measure for information preservation in terms of the channel capacity according to the channel coding theorem of Shannon. We calculate Information capacities of DNA on the nucleotide (for non-coding DNA) and the amino acid (for coding DNA) level using various substitution models. We extend our results on coding DNA to a discussion about the optimality of the natural codon-amino acid code. We provide the results of an adaptive search algorithm in the code domain and demonstrate the existence of a large number of genetic codes with higher information capacity. Our results support the hypothesis of an ancient extension from a 2-nucleotide codon to the current 3-nucleotide codon code to encode the various amino acids.

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“…The study of the information processing capabilities of living systems began in the 1970s (Roman-Roldan et al, 1996;Sarkar et al, 1978;Fowler, 1979) and was revived in the later part of the 1980s, due to the increase in genomic data which spurred a renewed interest in the use of information theory in the study of genomics. Information measures, such as entropy, have been used in recognition of DNA patterns, classification of genetic sequences, and other computational studies of genetic processes (Roman-Roldan et al, 1996;Palaniappan and Jernigan, 1984;Almagor, 1985;Schneider, 1991b,a;Altschul, 1991;Salamon and Konopka, 1992;Oliver et al, 1993;DeLaVega et al, 1996;Schneider and Mastronarde, 1996;Strait and Dewey, 1996;Pavesi et al, 1997;Loewenstern and Yianilos, 1997;Schneider, 1997Schneider, , 1999.…”

Section: Introductionmentioning

confidence: 99%

“…Information measures, such as entropy, have been used in recognition of DNA patterns, classification of genetic sequences, and other computational studies of genetic processes (Roman-Roldan et al, 1996;Palaniappan and Jernigan, 1984;Almagor, 1985;Schneider, 1991b,a;Altschul, 1991;Salamon and Konopka, 1992;Oliver et al, 1993;DeLaVega et al, 1996;Schneider and Mastronarde, 1996;Strait and Dewey, 1996;Pavesi et al, 1997;Loewenstern and Yianilos, 1997;Schneider, 1997Schneider, , 1999. Applying techniques from Coding Theory, a subfield of Information Theory, is a logical next step in the study of the information processing mechanisms of genetic systems.…”

Section: Introductionmentioning

confidence: 99%

Coding theory based models for protein translation initiation in prokaryotic organisms

et al. 2004

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Our research explores the feasibility of using communication theory, error control (EC) coding theory specifically, for quantitatively modeling the protein translation initiation mechanism. The messenger RNA (mRNA) of Escherichia coli K-12 is modeled as a noisy (errored), encoded signal and the ribosome as a minimum Hamming distance decoder, where the 16S ribosomal RNA (rRNA) serves as a template for generating a set of valid codewords (the codebook). We tested the E. coli based coding models on 5' untranslated leader sequences of prokaryotic organisms of varying taxonomical relation to E. coli including: Salmonella typhimurium LT2, Bacillus subtilis, and Staphylococcus aureus Mu50. The model identified regions on the 5' untranslated leader where the minimum Hamming distance values of translated mRNA sub-sequences and non-translated genomic sequences differ the most. These regions correspond to the Shine-Dalgarno domain and the non-random domain. Applying the EC coding-based models to B. subtilis, and S. aureus Mu50 yielded results similar to those for E. coli K-12. Contrary to our expectations, the behavior of S. typhimurium LT2, the more taxonomically related to E. coli, resembled that of the non-translated sequence group.

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Application of information theory to DNA sequence analysis: A review

Cited by 73 publications

References 18 publications

The Distribution of Variation in Regulatory Gene Segments, as Present in MHC Class II Promoters

The Distribution of Variation in Regulatory Gene Segments, as Present in MHC Class II Promoters

The information capacity of the genetic code: Is the natural code optimal?

Coding theory based models for protein translation initiation in prokaryotic organisms

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