Periodicities in coding and noncoding regions of the genes

Gene population statistical studies of protein coding genes and introns have identified two types of periodicities on the purine/pyrimidine alphabet: (i) the modulo 3 periodicity or coding periodicity (periodicity P3) in protein coding genes of eukaryotes, prokaryotes, viruses, chloroplasts, mitochondria, plasmids and in introns of viruses and mitochondria, and (ii) the modulo 2 periodicity (periodicity P2) in the eukaryotic introns. The periodicity study is herein extended to the 5' and 3' regions of eukaryotes, prokaryotes and viruses and shows: (i) the periodicity P3 in the 5' and 3' regions of eukaryotes. Therefore, these observations suggest a unitary and dynamic concept for the genes as for a given genome, the 5' and 3' regions have the genetic information for protein coding genes and for introns: (1) In the eukaryotic genome, the 5' (P2 and P3) and 3' (P2 and P3) regions have the information for protein coding genes (P3) and for introns (P2). The intensity of P3 is high in 5' regions and weak in 3' regions, while the intensity of P2 is weak in 5' regions and high in 3' regions. (2) In the prokaryotic genome, the 5' (P3) and 3' (P3) regions have the information for protein coding genes (P3). (3) In the viral genome, the 5' (P3) and 3' (P3) regions have the information for protein coding genes (P3) and for introns (P3). The absence of P2 in viral introns (in opposition to eukaryotic introns) may be related to the absence of P2 in 5' and 3' regions of viruses.     

Polymorphisms in the coding and noncoding regions of murinePgk-1 alleles

The mouse X-linkedPgk-1 gene encodes phosphoglycerate kinase. When transfected into human cells, thePgk-1^b allele causes the appearance of mouse PGK-1^b enzyme activity. We describe here cloning of mousePgk-1^a, an allele ofPgk-1 which encodes an enzyme, PGK-1^a, with distinct electrophoretic mobility. We constructed recombinants between the DNA encodingPgk-1^b andPgk-1^a and transfected these constructs into human to assess the electrophoretic characteristics of each recombinant. In this way the charge variation between the two proteins was localized to exons 4 or 5. Sequencing of these exons revealed a single base-pair difference between the two alleles at codon 155, which predicts the amino acids lysine and threonine in PGK-1^b and PGK-1^a, respectively. A number of other DNA sequence polymorphisms exist betweenPgk-1^b andPgk-1^a including part of an L1 repeated element unique toPgk-1^a. This work was supported by the Medical Research Council of Canada, the National Cancer Institute of Canada, and the Deutsche Forschungsgemeinschaft, SFB 304.     

Nucleotide sequence and evolution of coding and noncoding regions of a quail mitochondrial genome

Summary Segments of the Japanese quail mito-chondrial genome encompassing many tRNA and protein genes, the small and part of the large rRNA genes, and the control region have been cloned and sequenced. Analysis of the relative position of these genes confirmed that the tRNA^Glu and ND6 genes in galliform mitochondrial DNA are located immediately adjacent to the control region of the molecule instead of between the cytochrome b and ND5 genes as in other vertebrates. Japanese quail and chicken display another distinctive characteristic, that is, they both lack an equivalent to the light-strand replication origin found between the tRNA^Cys and tRNA^Asn genes in all vertebrate mitochondrial genomes sequenced thus far. Comparison of the protein-encoding genes revealed that a great proportion of the substitutions are silent and involve mainly transitions. This bias toward transitions also occurs in the tRNA and rRNA genes but is not observed in the control region where transversions account for many of the substitutions. Sequence alignment indicated that the two avian control regions evolve mainly through base substitutions but are also characterized by the occurrence of a 57-bp deletion/addition event at their 5′ end. The overall sequence divergence between the two gallinaceous birds suggests that avian mitochondrial genomes evolve at a similar rate to other vertebrate mitochondrial DNAs.     

β-KL离散量在识别DNA编码区域中的应用

根据DNA序列的‘终止密码子’及其‘逆补终止密码子’的分布情况,给出一种新的DNA序列向量的构建方法,运用Shannon熵相关理论,对Jensen-Shannon离散量和KL离散量进行了修正和比较。试验表明,该方法在预测DNA序列的基因编码与非编码区边界的效率上是86%显著高于Bernaola等人提出的70%。     

Kappa-chain constant-region gene sequences in genus Rattus: coding regions are diverging more rapidly than noncoding regions

We have determined the nucleotide sequence of a 1,200-base pair (bp) genomic fragment that includes the kappa-chain constant-region gene (C kappa) from two species of native Australian rodents, Rattus leucopus cooktownensis and Rattus colletti. Comparison of these sequences with each other and with other rodent C kappa genes shows three surprising features. First, the coding regions are diverging at a rate severalfold higher than that of the nearby noncoding regions. Second, replacement changes within the coding region are accumulating at a rate at least as great as that of silent changes. Third, most of the amino acid replacements are localized in one region of the C kappa domain--namely, the carboxy-terminal "bends" in the alpha-carbon backbone. These three features have previously been described from comparisons of the two allelic forms of C kappa genes in R. norvegicus. These data imply the existence of considerable evolutionary constraints on the noncoding regions (based on as yet undetermined functions) or powerful positive selection to diversify a portion of the constant-region domain (whose physiological significance is not known). These surprising features of C kappa evolution appear to be characteristic only of closely related C kappa genes, since comparison of rodent with human sequences shows the expected greater conservation of coding regions, as well as a predominance of silent nucleotide substitutions within the coding regions.      

GC-biased segregation of noncoding polymorphisms in Drosophila

The study of base composition evolution in Drosophila has been achieved mostly through the analysis of coding sequences. Third codon position GC content, however, is influenced by both neutral forces (e.g., mutation bias) and natural selection for codon usage optimization. In this article, large data sets of noncoding DNA sequence polymorphism in D. melanogaster and D. simulans were gathered from public databases to try to disentangle these two factors-noncoding sequences are not affected by selection for codon usage. Allele frequency analyses revealed an asymmetric pattern of AT vs. GC noncoding polymorphisms: AT --> GC mutations are less numerous, and tend to segregate at a higher frequency, than GC --> AT ones, especially at GC-rich loci. This is indicative of nonstationary evolution of base composition and/or of GC-biased allele transmission. Fitting population genetics models to the allele frequency spectra confirmed this result and favored the hypothesis of a biased transmission. These results, together with previous reports, suggest that GC-biased gene conversion has influenced base composition evolution in Drosophila and explain the correlation between intron and exon GC content.     

Roles of the coding and noncoding regions of rift valley Fever virus RNA genome segments in viral RNA packaging

We characterized the RNA elements involved in the packaging of Rift Valley fever virus RNA genome segments, L, M, and S. The 5'-terminal 25 nucleotides of each RNA segment were equally competent for RNA packaging and carried an RNA packaging signal, which overlapped with the RNA replication signal. Only the deletion mutants of L RNA, but not full-length L RNA, were efficiently packaged, implying the possible requirement of RNA compaction for L RNA packaging.     

Simple structural differences between coding and noncoding DNA

Background

The study of large-scale genome structure has revealed patterns suggesting the influence of evolutionary constraints on genome evolution. However, the results of these studies can be difficult to interpret due to the conceptual complexity of the analyses. This makes it difficult to understand how observed statistical patterns relate to the physical distribution of genomic elements. We use a simpler and more intuitive approach to evaluate patterns of genome structure.

Methodology/Principal Findings

We used randomization tests based on Morisita''s Index of aggregation to examine average differences in the distribution of purines and pyrimidines among coding and noncoding regions of 261 chromosomes from 223 microbial genomes representing 21 phylum level groups. Purines and pyrimidines were aggregated in the noncoding DNA of 86% of genomes, but were only aggregated in the coding regions of 52% of genomes. Coding and noncoding DNA differed in aggregation in 94% of genomes. Noncoding regions were more aggregated than coding regions in 91% of these genomes. Genome length appears to limit aggregation, but chromosome length does not. Chromosomes from the same species are similarly aggregated despite substantial differences in length. Aggregation differed among taxonomic groups, revealing support for a previously reported pattern relating genome structure to environmental conditions.

Conclusions/Significance

Our approach revealed several patterns of genome structure among different types of DNA, different chromosomes of the same genome, and among different taxonomic groups. Similarity in aggregation among chromosomes of varying length from the same genome suggests that individual chromosome structure has not evolved independently of the general constraints on genome structure as a whole. These patterns were detected using simple and readily interpretable methods commonly used in other areas of biology.     

Detecting selection in noncoding regions of nucleotide sequences

We present a maximum-likelihood method for examining the selection pressure and detecting positive selection in noncoding regions using multiple aligned DNA sequences. The rate of substitution in noncoding regions relative to the rate of synonymous substitution in coding regions is modeled by a parameter zeta. When a site in a noncoding region is evolving neutrally zeta = 1, while zeta > 1 indicates the action of positive selection, and zeta < 1 suggests negative selection. Using a combined model for the evolution of noncoding and coding regions, we develop two likelihood-ratio tests for the detection of selection in noncoding regions. Data analysis of both simulated and real viral data is presented. Using the new method we show that positive selection in viruses is acting primarily in protein-coding regions and is rare or absent in noncoding regions.     

Statistical analysis of nucleotide runs in coding and noncoding DNA sequences

A statistical analysis of the occurrence of particular nucleotide runs in DNA sequences of different species has been carried out. There are considerable differences of run distributions in DNA sequences of procaryotes, invertebrates and vertebrates. There is an abundance of short runs (1-2 nucleotides long) in the coding sequences and there is a deficiency of such runs in the noncoding regions. However, some interesting exceptions from this rule exist for the run distribution of adenine in procaryotes and for the arrangement of purine-pyrimidine runs in eucaryotes. The similarity in the distributions of such runs in the coding and noncoding regions may be due to some structural features of the DNA molecule as a whole. Runs of guanine (or cytosine) of three to six nucleotides occur predominantly in noncoding DNA regions in eucaryotes, especially in vertebrates.     

Clustering of identical oligomers in coding and noncoding DNA sequences.

We develop a quantitative method for analyzing repetitions of identical short oligomers in coding and noncoding DNA sequences. We analyze sequences presently available in the GenBank separately for primate, mammal, vertebrate, rodent, invertebrate and plant taxonomic partitions. We find that some oligomers "cluster" more than they would if randomly distributed, while other oligomers "repel" each other. To quantify this degree of clustering, we define clustering measures. We find that (i) clustering significantly differs in coding and noncoding DNA; (ii) in most cases, monomers, dimers and tetramers cluster in noncoding DNA but appear to repel each other in coding DNA. (iii) The degree of clustering for different sources (primates, invertebrates, and plants) is more conserved among these sources in the case of coding DNA than in the case of noncoding DNA. (iv) In contrast to other oligomers, we find that trimers always prefer to cluster. (v) Clustering of each particular oligomer is conserved within the same organism.     

Entropies of coding and noncoding sequences of DNA and proteins.

The entropies of protein coding genes from Escherichia coli were calculated according to Boltzmann's formula. Entropies of the coding regions were compared to the entropies of noncoding or miscoding ones. With nucleotides as code units, the entropies of the coding regions, when compared to the entropies of complete sequences (leader and coding region as well as trailer), were seen to be lower but with a marginal statistical significance. With triplets of nucleotides as code units, the entropies of correct reading frames were significantly lower than the entropies of frameshifts +1 and -1. With amino acids as code units, the results were opposite: Biologically functional proteins had significantly higher entropies than proteins translated from the frameshifted sequences. We attempt to explain this paradox with the hypothesis that the genetic code may have the ability of lowering information content (increasing entropy) of proteins while translating them from DNA. This ability might be beneficial to bacteria because it would make the functional proteins more probable (having a higher entropy) than nonfunctional proteins translated from frameshifted sequences.     

Pattern of nucleotide substitution and rate heterogeneity in the hypervariable regions I and II of human mtDNA.

This study provides a comprehensive survey of the complex pattern of nucleotide substitution in the control region of human mtDNA, which is of central importance to the studies of human evolution. A total of 1229 different hypervariable region I (HVRI) and 385 different hypervariable region II (HVRII) sequences were analyzed using a complex substitution model. Moreover, we suggest a new method to assign relative rates to each site in the sequence. Estimates are based on maximum-likelihood methods applied to randomly selected subsets of sequences. Our results indicate that the rate of substitution in HVRI is approximately twice as high as in HVRII and that this difference is mainly due to a higher frequency of pyrimidine transitions in HVRI. However, rate heterogeneity is more pronounced in HVRII.