Darwin's legacy II: why biology is not physics, or why it has taken a century to see the dependence of genes on the environment

Alternative splicing signature of alveolar type II epithelial cells of Tibetan pigs under hypoxia-induced

Alternative splicing (AS) allows the generation of multiple transcript variants from a single gene and affects biological processes by generating protein diversity in organisms. In total, 41,642 AS events corresponding to 9,924 genes were identified, and SE is the most abundant alternatively spliced type. The analysis of functional categories demonstrates that alternatively spliced differentially expressed genes (DEGs) were enriched in the MAPK signaling pathway and hypoxia-inducible factor 1 (HIF-1) signaling pathway. Proteoglycans in cancer between the normoxic (21% O2, TN and LN) and hypoxic (2% O2, TL and LL) groups, such as SLC2A1, HK1, HK2, ENO3, and PFKFB3, have the potential to rapidly proliferate alveolar type II epithelial (ATII) cells by increasing the intracellular levels of glucose and quickly divert to anabolic pathways by glycolysis intermediates under hypoxia. ACADL, EHHADH, and CPT1A undergo one or two AS types with different frequencies in ATII cells between TN and TL groups (excluding alternatively spliced DEGs shared between normoxic and hypoxic groups), and a constant supply of lipids might be obtained either from the circulation or de novo synthesis for better growth of ATII cells under hypoxia condition. MCM7 and MCM3 undergo different AS types between LN and LL groups (excluding alternatively spliced DEGs shared between normoxic and hypoxic groups), which may bind to the amino-terminal PER-SIM-ARNT domain and the carboxyl terminus of HIF-1α to maintain their stability. Overall, AS and expression levels of candidate mRNAs between Tibetan pigs and Landrace pigs revealed by RNA-seq suggest their potential involvement in the ATII cells grown under hypoxia conditions.

Post-transcriptional regulation through alternative splicing in the lungs of Tibetan pigs under hypoxia

In multicellular organisms, alternative splicing (AS) is central to the regulation of multiple biological processes. To further elucidate the adaptive strategy of AS in the lungs of Tibetan pigs in response to hypoxia, we identified and analyzed five basic AS types and 59,930 AS events in 18,179 genes. We found that approximately 65.10% of the total expressed genes underwent AS in the lungs of Tibetan pigs at a high altitude (TH). The frequencies of AS events were similar among the different groups (5.06-5.30 events in each gene on average). Skipped exons (SEs) were the predominant type of AS event, followed by mutually exclusive exons (MXEs), alternative 3' splice sites (A3SSs) and alternative 5' splice sites (A5SSs). Retained introns (RIs), the remaining type of AS event, showed lower frequencies. Further comparison analysis of differentially expressed genes (DEGs) and differentially spliced genes (DSGs) identified 2,209 differential splicing events in the above 18,000 expressed genes, including 918 increased and 1,291 decreased splicing events between the TH and Tibetan pigs at a low altitude (TL) groups. We identified 227 hypoxia-related genes involved in lung development that were differentially regulated through AS. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis clearly identified many DEGs and DSGs at high or low altitude. Seven pathways in the top 20 enriched KEGG terms overlapped for the DEGs and DSGs, including the chemokine signaling pathway, B cell receptor signaling pathway, and cytokine-cytokine receptor interaction, which exert many immunoregulatory and inflammatory actions critical to the lung under hypoxia. Twelve pathways overlapped in hypoxic DEGs and DSGs and included antigen processing, presentation and biosynthesis. ​GO analysis of the DEGs and DSGs among the four groups showed that numerous GO terms were enriched in the biological category, and the proportion of genes with downregulated expression was greater among 227 hypoxic genes than that of all genes. The results suggest that AS plays an essential role in the regulation of gene expression during hypoxia and that numerous genes involved in lung development are differentially regulated through AS.

Genes and genomes and unnecessary complexity in precision medicine

The sequencing of the human genome heralded the new age of 'genetic medicine' and raised the hope of precision medicine facilitating prolonged and healthy lives. Recent studies have dampened this expectation, as the relationships among mutations (termed 'risk factors'), biological processes, and diseases have emerged to be more complex than initially anticipated. In this review, we elaborate upon the nature of the relationship between genotype and phenotype, between chance-laden molecular complexity and the evolution of complex traits, and the relevance of this relationship to precision medicine. Molecular contingency, i.e., chance-driven molecular changes, in conjunction with the blind nature of evolutionary processes, creates genetic redundancy or multiple molecular pathways to the same phenotype; as time goes on, these pathways become more complex, interconnected, and hierarchically integrated. Based on the proposition that gene-gene interactions provide the major source of variation for evolutionary change, we present a theory of molecular complexity and posit that it consists of two parts, necessary and unnecessary complexity, both of which are inseparable and increase over time. We argue that, unlike necessary complexity, comprising all aspects of the organism's genetic program, unnecessary complexity is evolutionary baggage: the result of molecular constraints, historical circumstances, and the blind nature of evolutionary forces. In the short term, unnecessary complexity can give rise to similar risk factors with different genetic backgrounds; in the long term, genes become functionally interconnected and integrated, directly or indirectly, affecting multiple traits simultaneously. We reason that in addition to personal genomics and precision medicine, unnecessary complexity has consequences in evolutionary biology.

The Play of Genes and Non-genetic Factors on Type 2 Diabetes

Diabetes has been a disease of public health concern for a number of decades. It was in the 1930s when scientists made an interesting discovery that the disease is actually divided into two types as some patients were insensitive to insulin treatment then. Type 2 Diabetes which happens to be the non-insulin dependent one is the most common form of the disease and is caused by the interaction between genetic and non-genetic factors. Despite conflicting results, numerous studies have identified genetic and non-genetic factors associated with this common type of diabetes. This review has summarized literature on some genes and non-genetic factors which have been identified to be associated with Type 2 diabetes. It has sourced literature from PubMed, Web of Science and Medline without any limitation to regions, publication types, or languages. The paper has started with the introduction, the play of non-genetic factors, the impact of genes in general, and ended with the interaction between some genes and environmental factors.

Gene Co-Expression Network Analysis Unraveling Transcriptional Regulation of High-Altitude Adaptation of Tibetan Pig

Tibetan pigs have survived at high altitude for millennia and they have a suite of adaptive features to tolerate the hypoxic environment. However, the molecular mechanisms underlying the regulation of hypoxia-adaptive phenotypes have not been completely elucidated. In this study, we analyzed differentially expressed genes (DEGs), biological pathways and constructed co-expression regulation networks using whole-transcriptome microarrays from lung tissues of Tibetan and Duroc pigs both at high and low altitude. A total of 3,066 DEGs were identified and this list was over-represented for the ontology terms including metabolic process, catalytic activity, and KEGG pathway including metabolic pathway and PI3K-Akt signaling pathway. The regulatory (RIF) and phenotypic (PIF) impact factor analysis identified several known and several potentially novel regulators of hypoxia adaption, including: IKBKG, KLF6 and RBPJ (RIF1), SF3B1, EFEMP1, HOXB6 and ATF6 (RIF2). These findings provide new details of the regulatory architecture of hypoxia-adaptive genes and also insight into which genes may undergo epigenetic modification for further study in the high-altitude adaptation.