Distinct frequency-distributions of homopolymeric DNA tracts in different genomes

Dechering, Koen J.; Cuelenaere, Koen; Konings, Ruud N. H.; Leunissen, Jack A. M.

doi:10.1093/nar/26.17.4056

Cited by 97 publications

(103 citation statements)

References 46 publications

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“…In budding yeast, homopolymeric dA:dT tracts (referred to here as polyA tracts) of ≥10 bp occur in the genome well above what is expected based on random chance ( Fig. 5C; Dechering et al 1998). Analyzing the association that polyA tracts of incremental length have with hybrid formation, we noted a sharp transition to near-perfect overlap for polyAs of ≥21 bp (Fig.…”

Section: Sequence Features Of Hybrid-prone Regionsmentioning

confidence: 71%

S1-DRIP-seq identifies high expression and polyA tracts as major contributors to R-loop formation

et al. 2016

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R loops form when transcripts hybridize to homologous DNA on chromosomes, yielding a DNA:RNA hybrid and a displaced DNA single strand. R loops impact the genome of many organisms, regulating chromosome stability, gene expression, and DNA repair. Understanding the parameters dictating R-loop formation in vivo has been hampered by the limited quantitative and spatial resolution of current genomic strategies for mapping R loops. We report a novel whole-genome method, S1-DRIP-seq (S1 nuclease DNA:RNA immunoprecipitation with deep sequencing), for mapping hybrid-prone regions in budding yeast Saccharomyces cerevisiae. Using this methodology, we identified ∼800 hybrid-prone regions covering 8% of the genome. Given the pervasive transcription of the yeast genome, this result suggests that R-loop formation is dictated by characteristics of the DNA, RNA, and/or chromatin. We successfully identified two features highly predictive of hybrid formation: high transcription and long homopolymeric dA:dT tracts. These accounted for >60% of the hybrid regions found in the genome. We demonstrated that these two factors play a causal role in hybrid formation by genetic manipulation. Thus, the hybrid map generated by S1-DRIP-seq led to the identification of the first global genomic features causal for R-loop formation in yeast.

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Section: Sequence Features Of Hybrid-prone Regionsmentioning

confidence: 71%

S1-DRIP-seq identifies high expression and polyA tracts as major contributors to R-loop formation

et al. 2016

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“…However, it has been suggested that cpSSRs of length 8 nt or more (regardless of repeat motif) are prone to slip-strand mispairing (SSM, thought to be the primary mutational mechanism to affect SSRs), whereas those of lesser length are not (Rose and Falush, 1998). Elsewhere, the critical threshold is estimated at 7-10 bp (Dechering et al, 1998).…”

Section: Frequency and Distribution Of Cpssrs In The Poaceae Species mentioning

confidence: 99%

Characterization of chloroplast DNA microsatellites from Saccharum spp and related species

Melotto-Passarin¹,

Tambarussi²,

Dressano³

et al. 2011

Genet. Mol. Res.

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ABSTRACT. Microsatellites, or simple sequence repeats (SSRs), and their flanking regions in chloroplast genomes (plastomes) of some species of the family Poaceae were analyzed in silico to look for DNA sequence variations. Comparison of the complete chloroplast DNA sequences (cpDNAs) of sugarcane (Saccharum hybrid cv. SP-80-3280 and S. officinarum cv. NCo310) and related species, Agrostis stolonifera, Brachypodium distachyon, Hordeum vulgare subsp vulgare, Lolium perenne, Oryza nivara, O. sativa subsp indica, O. sativa subsp japonica, Sorghum bicolor, Triticum aestivum, Zea mays, and Z. mays cv. B73, allowed us to examine the organization of chloroplast SSRs (cpSSRs) in genic and intergenic regions. We identified 204 cpSSRs in the sugarcane cpDNA; 22.5% were in genic regions. The ndh, rps, trn, and rpl gene clusters of the chloroplasts had the most repeats. Mononucleotide repeats were the most abundant cpSSRs in these species; however, di-, tri-, tetra-, penta-, and hexanucleotide repeats were also identified. Chloroplast SSRs in Poaceae variability possible; repeat motifs are not uniformly distributed across the Poaceae plastomes, but are mostly confined to intergenic regions. Phylogeny was determined by maximum parsimony and neighborjoining inference methods. The cpSSRs of these species were found to be polymorphic. It appears that individual cpSSRs in the Poaceae are stable, at least over short periods of evolutionary time. We conclude that the plastome database can be exploited for phylogenetic analysis and biotechnological development.

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“…These types of boundaries can be formed by nucleosome attracting signals, or nucleosome repelling signals such as poly(dA:dT) tracts (Bernstein et al 2004;Yuan et al 2005;Lee et al 2007;Field et al 2008;Kaplan et al 2009). Imperfect boundaries such as those that result over poly(dA:dT) tracts are common in eukaryotic genomes (Dechering et al 1998), indicating a possible functionality for these sequence-encoded signals. Indeed, when located within promoter regions, these sequences are hypothesized to have important effects on transcription (Struhl 1985;Iyer and Struhl 1995).…”

Section: Addition Of Boundary Elements For Nucleosome Formation Shiftmentioning

confidence: 99%

Incorporating Nucleosomes into Thermodynamic Models of Transcription Regulation

Raveh-Sadka

Levo

Segal

2009

Lecture Notes in Computer Science

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Transcriptional control is central to many cellular processes, and, consequently, much effort has been devoted to understanding its underlying mechanisms. The organization of nucleosomes along promoter regions is important for this process, since most transcription factors cannot bind nucleosomal sequences and thus compete with nucleosomes for DNA access. This competition is governed by the relative concentrations of nucleosomes and transcription factors and by their respective sequence binding preferences. However, despite its importance, a mechanistic understanding of the quantitative effects that the competition between nucleosomes and factors has on transcription is still missing. Here we use a thermodynamic framework based on fundamental principles of statistical mechanics to explore theoretically the effect that different nucleosome organizations along promoters have on the activation dynamics of promoters in response to varying concentrations of the regulating factors. We show that even simple landscapes of nucleosome organization reproduce experimental results regarding the effect of nucleosomes as general repressors and as generators of obligate binding cooperativity between factors. Our modeling framework also allows us to characterize the effects that various sequence elements of promoters have on the induction threshold and on the shape of the promoter activation curves. Finally, we show that using only sequence preferences for nucleosomes and transcription factors, our model can also predict expression behavior of real promoter sequences, thereby underscoring the importance of the interplay between nucleosomes and factors in determining expression kinetics.[Supplemental material is available online at www.genome.org. The computational model described in this paper is available at

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Distinct frequency-distributions of homopolymeric DNA tracts in different genomes

Cited by 97 publications

References 46 publications

S1-DRIP-seq identifies high expression and polyA tracts as major contributors to R-loop formation

S1-DRIP-seq identifies high expression and polyA tracts as major contributors to R-loop formation

Characterization of chloroplast DNA microsatellites from Saccharum spp and related species

Incorporating Nucleosomes into Thermodynamic Models of Transcription Regulation

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