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Record W2471415527 · doi:10.1093/biolreprod/78.s1.165b

Genome-wide Mapping of DNA Fragmentation in Elongating Spermatids.

2008· article· en· W2471415527 on OpenAlexaff
Guylain Boissonneault, Frédéric Leduc, Geneviève Bikond Nkoma

Bibliographic record

VenueBiology of Reproduction · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsBiologyDNA fragmentationDNAFragmentation (computing)Molecular biologyDNA damageDNA polymerase IIChromatinGeneticsDNA clampTUNEL assayPlasmidPolymerase chain reactionGeneReverse transcriptase

Abstract

fetched live from OpenAlex

Spermatozoa of many infertile men present high DNA fragmentation levels and an altered or incomplete chromatin packaging of unknown origin. However, recent findings by our group and others demonstrated a programmed DNA fragmentation and DNA damage response in elongating spermatids of mice and rats. The persistence of this DNA fragmentation in later steps may alter the fertilizing potential of the male gamete. In this study, our aims was to design a new technique to map genome-wide DNA breaks with the goal of identifying sensitive loci harboring DNA fragmentation in elongating spermatids of mice. Here we describe a new strategy to map genome-wide DNA strand breaks termed "damaged DNA immunoprecipitation" or dDIP, that uses immunoprecipitation and the terminal deoxynucleotidyl transferase-mediated dUTP-biotin end labeling (TUNEL). The sensitivity and specificity of this approach was assessed by real-time polymerase chain reaction in vitro, with plasmid DNA and in vivo, in transformed E. coli bacteria using a plasmid as target. The mating-type locus of the yeast S. cerevisiae was also used as an endogenous double-strand break model. Application to DNA fragmentation in spermatids is therefore straightforward. Using these models, we demonstrate the specific capture of any sequence harboring a DNA strand break. The sensitivity and specificity of this technique was also established as we isolated DNA fragments in the vicinity of the DNA damage in very low concentration of starting material and within a large pool of captured DNA sequences. When used in combination with DNA microarray, quantitative PCR or sequencing technologies, dDIP will allow researchers to map genome-wide DNA strand breaks and other types of DNA damage that can be converted as strand breaks and to establish a comprehensive profile of genes and intergenic sequences harboring DNA damage. Using this approach, we will map DNA fragmentation found in elongating spermatids to understand their importance in the chromatin remodeling process and to identify hotspots as a potential source of genomic instability. Furthermore, mapping DNA fragmentation of spermatozoa of infertile men by this technique may be the first step toward the understanding of many cases of human infertility and the identification of sensitive hotspots of male infertility.

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.274
Teacher spread0.261 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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