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Melatonin receptor 1A (MTNR1A) gene polymorphisms in the local goat population in South Sulawesi region of Indonesia

2019· article· en· W2946383447 on OpenAlexaboutno aff
Muhammad Ihsan Andi Dagong, Sri Rachma Aprilita Bugiwati, Nurul Purnomo

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationBiologyGenotypeAlleleGeneAllele frequencyGeneticsAndrologyMedicine

Abstract

fetched live from OpenAlex

Abstract Some important genes are involved in controlling the reproductive trait of goats, one of which is the Melatonin Receptor 1A (MTNR1A) gene. The MTNR1A gene is known with seasonal reproductive activity and related to lambing frequency in the goat. The purpose of this research was to determine the genetic polymorphisms of the MTNR1A gene in Kacang, and Peranakan Ottawa (PE) goat population reared traditionally in South Sulawesi region of Indonesia. In total 253 heads of goat consist of 137 heads of Kacang and 116 Peranakan Ottawa from South, Sulawesi region was used as research samples for blood collection. The blood samples were collected from the jugular vein, which was then continued for DNA extracted by using a DNA extraction kit. The MTNR1A genotype was identified by PCR-RFLP technique using restriction enzyme RsaI. The result showed that there was genetic diversity in the MTNR1A gene in Kacang and PE population with the obtained of two alleles R and r. The common allele was R with frequency 0.93 in Kacang population while in PE population was 0.89. The r allele was 0.06 and 0.10 in Kacang and PE population, respectively. The most common genotype found in the population was RR (0.95), while Rr was only 0.05 and rr genotype did not found in this population. Observed heterozygosity value was 0.05. According to the Hardy-Weinberg test, this population was in equilibrium for MTNR1A gene. In conclusion, this finding indicated that there was genetic diversity exists in local goat population, and future research needed to find any association with this genetic variation with reproductive performance, the data obtained from this study could be used for the strategic program in goat breeding to increase reproductive performance of local goat especially fertility traits.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.513
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.189
Teacher spread0.181 · 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 teacher head, 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

Citations3
Published2019
Admission routes1
Has abstractyes

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