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Record W2551584398 · doi:10.5281/zenodo.7220285

PARENTAGE TESTING IN DIFFERENT BREEDS OF DOGS USING MICROSATELLITE MARKERS

2022· article· en· W2551584398 on OpenAlexaboutno aff
M. Parthiban, G. Nireesha, K.S. Aarthi, A. Palanisammi

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Genetics and Reproduction
Canadian institutionsnot available
FundersIndian Council of Agricultural Research
KeywordsMicrosatelliteBiologyEvolutionary biologyGeneticsAlleleGene

Abstract

fetched live from OpenAlex

ABSTRACT A total of 45 blood samples from progeny and the putative parents were tested for parentage analysis using a panel of microsatellite markers (short tandem repeats). Six breeds of dogs were represented viz. German shepherd, Dalmatian, Labrador, Great Dane, Boxer and Lhasa Apso in this study for genotype analysis. Ten different microsatellite marker loci were amplified by multiplex PCR. The multiplex PCR products were run in genetic analyzer. The data were analyzed using gene mapper software to measure the allele size. Such measured allele size was compared to determine whether there are matches between the progeny and the putative parents. In conclusion, short tandem repeats uniformly distributed in the genome was found to be highly polymorphic and can be used as molecular tool for parentage testing in dogs of different breeds. Key words: microsatellite markers, dog parentage, multiplex PCR.. REFERENCES Hearne, C.M., Ghosh, S., Todd J.A.1992. Microsatellites for linkage analysis of genetic traits. Trends genet. 8:288–294. Ichikawa, Y. Takagi, K. Tsumagari, S. Ishihama, K. Morita, M. Kanemaki, M. Takeishi, M. and Takahashi, H. (2001). Canine parentage testing based on microsatellite polymorphisms. J vet. Med. sci. 63:1209-1213. Jeffreys, A.J. Wilson, V. and Thein, S.L. (1985): Individual-specific fingerprints of human DNA. Nature, 316(6023):76–79. Muller, S. Flekna, G., Muller, M., Brem, G. 1999. Use of canine microsatellite polymorphisms in forensic examinations. J. Hered. 90:55-56. Nakamura, Y., Leppert, M., O'Connell, P., Wolff, R., Holm, T., Culver, M., Martin, C., Fujimoto, E., Hoff, M., Kumlin, E. 1987. Variable number of tandem repeat (VNTR) markers for human gene mapping. Science. 235.1616-22. Ostrander, E.A. and Robert K. W. 2005. The canine genome. Genome Res. 15: 1706-1716. Stallings, R.L., Ford, A.F., Nelson, D., Torney, D.C., Hildebrand, C.E., Moyzis, R.K. 1991. Evolution and distribution of (GT)n repetitive sequences in mammalian genomes. Genomics. 10(3):807-15. Walsh, P.S., Fildes, N.J., Reynolds, R. 1996. Sequence analysis and characterization of stutter products at the tetranucleotide repeat locus vWA. Nucleic Acids Res. 24: 2807–2812. Zaje, I. 1994. A new method of paternity testing for dogs, based on microsatellite sequences. Vet. Rec. 135: 545-547.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.040
GPT teacher head0.248
Teacher spread0.207 · 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 designBench or experimental
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
Published2022
Admission routes1
Has abstractyes

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