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Record W2970438969 · doi:10.1101/755272

Nucleosome positioning sequence patterns as packing or regulatory

2019· preprint· en· W2970438969 on OpenAlexafffund
Erinija Pranckevičienė, Sergey Hosid, Nathan Liang, Ilya Ioshikhes

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsNucleosomeChromatinSaccharomyces cerevisiaeBiologyDNAYeastGeneticsDNA sequencingGeneMolecular biologyCell biology

Abstract

fetched live from OpenAlex

Abstract Nucleosome positioning DNA sequence patterns (NPS) - usually distributions of particular dinucleotides or other sequence elements in nucleosomal DNA - at least partially determine chromatin structure and arrangements of nucleosomes that in turn affect gene expression. Statistically, NPS are defined as oscillations of the dinucleotide periodicity with about 10 base pairs (bp) which reflects the double helix period. We compared the nucleosomal DNA patterns in mouse, human and yeast organisms and observed few distinctive patterns that can be termed as packing and regulatory referring to distinctive modes of chromatin function. For the first time the NPS patterns in nucleus accumbens cells (NAC) in mouse brain were characterized and compared to the patterns in human CD4+ and apoptotic lymphocyte cells and well studied patterns in yeast. The NPS patterns in human CD4+ cells and mouse brain cells had very high positive correlation. However, there was no correlation between them and patterns in human apoptotic lymphocyte cells and yeast, but the latter two were highly correlated with each other. By their dinucleotide arrangements the analyzed NPS patterns classified into stable canonical WW/SS (W=A or T and S=C or G dinucleotide) and less stable RR/YY (R=A or G and Y =C or T dinucleotide) patterns and anti-patterns In the anti-patterns positioning of the dinucleotides is flipped compared to those in the regular patterns. Stable canonical WW/SS patterns and anti-patterns are ubiquitously observed in many organisms and they had high resemblance between yeast and human apoptotic cells. Less stable RR/YY patterns had higher positive correlation between mouse and normal human cells. Our analysis and evidence from scientific literature lead to idea that various distinct patterns in nucleosomal DNA can be related to the two roles of the chromatin: packing (WW/SS) and regulatory (RR/YY and “anti”). Author summary Precise positioning of nucleosomes on DNA sequence is essential for gene regulatory processes. Two main classes of nucleosome positioning sequence (NPS) patterns with a periodicity of 10bp for their sequence elements were previously described. In the 1st class AA,TT and other WW dinucleotides (W= A or T) tend to occur together in the major groove of DNA closest to the histone octamer, while SS dinucleotides (S= G or C) are primarily positioned in the major groove facing outward. In the 2nd class AA and TT are structurally separated (AA backbone near the histone octamer, and TT backbone further away), but grouped with other RR (R is purine A or G) and YY (Y is pyrimidine C or T) dinucleotides. In [8] we also described novel anti-NPS patterns, inverse to the conventional NPS patterns: WW runs inverse to SS, RR inverse to YY. We demonstrated that Yeast nucleosomes in promoters show higher correlation to the RR/YY pattern whereas novel anti-NPS patterns are viable for nucleosomes in the promoters of stress associated genes related to active chromatin remodeling. In the present study we attribute different functions to various NPS patterns: packing function to WW/SS and regulatory – to RR/YY and anti-NPS patterns.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.224
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2019
Admission routes2
Has abstractyes

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