ReviewVeterinary sciences2024
Applications of Next-Generation Sequencing Technologies and Statistical Tools in Identifying Pathways and Biomarkers for Heat Tolerance in Livestock.
Review in Veterinary sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Pangenomics for Agricultural Breeding: Construction Strategies, Evidence Integration, and Translational Constraints.Biology · 2026Review
- Potential Applications of Genome-Wide Association Studies in Establishing Climate Resilience in Livestock: A Comprehensive Review.International journal of molecular sciences · 2026Review
- Climate change and the emergence of Rift Valley fever virus: a pathological and environmental study of sheep jaundice in Egyptian slaughterhouses.BMC veterinary research · 2025Article
- Review
- Whole genome resequencing data of the Iranian cashmere goat breed.BMC research notes · 2025Article
- Candidate Genes, Markers, Signatures of Selection, and Quantitative Trait Loci (QTLs) and Their Association with Economic Traits in Livestock: Genomic Insights and Selection.International journal of molecular sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The climate change-associated abnormal weather patterns negatively influences the productivity and performance of farm animals. Heat stress is the major detrimental factor hampering production, causing substantial economic loss to the livestock industry. Therefore, it is important to identify heat-tolerant breeds that can survive and produce optimally in any given environment. To achieve this goal, a clearer understanding of the genetic differences and the underlying molecular mechanisms associated with climate change impacts and heat tolerance are a prerequisite. Adopting next-generation biotechnological and statistical tools like whole transcriptome analysis, whole metagenome sequencing, bisulphite sequencing, genome-wide association studies (GWAS), and selection signatures provides an opportunity to achieve this goal. Through these techniques, it is possible to identify permanent genetic markers for heat tolerance, and by incorporating those markers in marker-assisted breeding selection, it is possible to achieve the target of breeding for heat tolerance in livestock. This review gives an overview of the recent advancements in assessing heat tolerance in livestock using such 'omics' approaches and statistical models. The salient findings from this research highlighted several candidate biomarkers that have the potential to be incorporated into future heat-tolerance studies. Such approaches could revolutionise livestock production in the changing climate scenario and support the food demands of the growing human population.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.