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Record W4220763077 · doi:10.1186/s12864-022-08430-x

Identification of novel alternative splicing associated with mastitis disease in Holstein dairy cows using large gap read mapping

2022· article· en· W4220763077 on OpenAlexafffund
Victoria Asselstine, Juan F. Medrano, Ángela Cánovas

Bibliographic record

VenueBMC Genomics · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversity of Guelph
FundersCanada First Research Excellence FundMinistry of Agriculture, Food and Rural AffairsNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsBiologyGene isoformAlternative splicingGeneMastitisRNA splicingMessenger RNAGeneticsDNA microarrayBovine genomeTranscriptomeGene expressionComputational biologyGenomeRNAMicrobiology

Abstract

fetched live from OpenAlex

BACKGROUND: Mastitis is a very common disease in the dairy industry that producers encounter daily. Transcriptomics, using RNA-Sequencing (RNA - Seq) technology, can be used to study the functional aspect of mastitis resistance to identify animals that have a better immune response to mastitis. When the cow has mastitis, not only genes but also specific mRNA isoforms generated via alternative splicing (AS) could be differentially expressed (DE), leading to the phenotypic variation observed. Therefore, the objective of this study was to use large gap read mapping to identify mRNA isoforms DE between healthy and mastitic milk somatic cell samples (N = 12). These mRNA isoforms were then categorized based on being 1) annotated mRNA isoforms for gene name and length, 2) annotated mRNA isoforms with different transcript length and 3) novel mRNA isoforms of non - annotated genes. RESULTS: Analysis identified 333 DE transcripts (with at least 2 mRNA isoforms annotated, with at least one being DE) between healthy and mastitic samples corresponding to 303 unique genes. Of these 333 DE transcripts between healthy and mastitic samples, 68 mRNA isoforms are annotated in the bovine genome reference (ARS.UCD.1.2), 249 mRNA isoforms had novel transcript lengths of known genes and 16 were novel transcript lengths of non - annotated genes in the bovine genome reference (ARS.UCD.1.2). Functional analysis including gene ontology, gene network and metabolic pathway analysis was performed on the list of 288 annotated and unique DE mRNA isoforms. In total, 67 significant metabolic pathways were identified including positive regulation of cytokine secretion and immune response. Additionally, numerous DE novel mRNA isoforms showed potential involvement with the immune system or mastitis. Lastly, QTL annotation analysis was performed on coding regions of the DE mRNA isoforms, identifying overlapping QTLs associated with clinical mastitis and somatic cell score. CONCLUSION: This study identified novel mRNA isoforms generated via AS that could lead to differences in the immune response of Holstein dairy cows and be potentially implemented in future breeding programs.

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)0.001
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 score0.781
Threshold uncertainty score0.242

Codex and Gemma teacher scores by category

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

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 head0.085
GPT teacher head0.265
Teacher spread0.180 · 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

Citations24
Published2022
Admission routes2
Has abstractyes

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