ArticleFrontiers in veterinary science2024
Screening of functional genes for hypoxia adaptation in Tibetan pigs by combined genome resequencing and transcriptome analysis.
Article in Frontiers in veterinary science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Integrated SNP and SV Analyses Reveal Genetic Mechanisms Underlying High-Altitude Adaptation in Goats.Animals : an open access journal from MDPI · 2026Article
- Genomics Insights into the Demographic History and Introgression of Tibetan Pigs.Animals : an open access journal from MDPI · 2026Article
- Genomic Signatures Underlying Environmental Adaptation and Reproductive Traits in the Tibetan Pig.Animals : an open access journal from MDPI · 2026Article
- Adaptation of Diqing Tibetan pigs to hypoxic and cold environments through extramedullary hematopoiesis and uncoupled thermogenesis in the liver.BMC biology · 2025Article
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11 authors.
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Abstract
The high-altitude, low-oxygen environment of the Qinghai-Tibet Plateau poses significant challenges for the introduction of superior livestock breeds. However, local plateau species have adapted to thrive and reproduce under these harsh conditions. Understanding the molecular mechanisms behind plateau animals' adaptation to low-oxygen environments is essential for breeding livestock suited to high-altitude regions. Tibetan pigs, which have undergone long-term natural selection and artificial breeding, have developed the ability to survive and reproduce in hypoxic environments. In this study, we conducted whole-genome resequencing of 30 Tibetan pigs from high-altitude regions and 30 Diannan small-ear pigs from low-altitude areas, to identify candidate genes that support Tibetan pigs' adaptation to hypoxic conditions through selection signal analysis. Additionally, we performed transcriptome sequencing on five tissues (heart, liver, spleen, lung, and bone marrow) from both Tibetan pigs and Diannan small-ear pigs to identify genes with significant differential expression between the two breeds. We then integrated the genomic and transcriptomic data by examining the expression of candidate genes identified in selection signal analysis across different tissues. The selection signal analysis identified 10 genes-
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