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Transcriptomic analysis comparing mouse strains with extreme total lung capacities identifies novel candidate genes for pulmonary function.

ABSTRACT: Failure to attain peak lung function by early adulthood is a risk factor for chronic lung diseases. Previously, we reported that C3H/HeJ mice have about twice total lung capacity (TLC) compared to JF1/MsJ mice. We identified seven lung function quantitative trait loci (QTL: Lfnq1-Lfnq7) in backcross/intercross mice derived from these inbred strains. We further demonstrated, superoxide dismutase 3, extracellular (Sod3), Kit oncogene (Kit) and secreted phosphoprotein 1 (Spp1) located on these Lfnqs as lung function determinants. Emanating from the concept of early origin of lung disease, we sought to identify novel candidate genes for pulmonary function by investigating lung transcriptome in C3H/HeJ and JF1/MsJ mice at the completion of embryonic development, bulk alveolar formation and maturity.Design-based stereological analysis was performed to study lung structure in C3H/HeJ and JF1/MsJ mice. Microarray was used for lung transcriptomic analysis [embryonic day 18, postnatal days 28, 70]. Quantitative real time polymerase chain reaction (qRT-PCR), western blot and immunohistochemical analysis were used to confirm selected differences.Stereological analysis revealed decreased alveolar number density, elastin to collagen ratio and increased mean alveolar volume in C3H/HeJ mice compared to JF1/MsJ. Gene ontology term "extracellular region" was enriched among the decreased JF1/MsJ transcripts. Candidate genes identified using the expression-QTL strategy include: ATP-binding cassette, sub-family G (WHITE), member 1 (Abcg1), formyl peptide receptor 1 (Fpr1), gamma-aminobutyric acid (GABA) B receptor, 1 (Gabbr1); histocompatibility 2 genes: class II antigen E beta (H2-Eb1), D region locus 1 (H2-D1), and Q region locus 4 (H2-Q4); leucine rich repeat containing 6 (testis) (Lrrc6), radial spoke head 1 homolog (Rsph1), and surfactant associated 2 (Sfta2). Noteworthy genes selected as candidates for their consistent expression include: Wnt inhibitor factor 1 (Wif1), follistatin (Fst), chitinase-like 1 (Chil1), and Chil3.Comparison of late embryonic, adolescent and adult lung transcript profiles between mouse strains with extreme TLCs lead to the identification of candidate genes for pulmonary function that has not been reported earlier. Further mechanistic investigations are warranted to elucidate their mode of action in determining lung function.

SUBMITTER: George L

PROVIDER: S-EPMC5551015 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Transcriptomic analysis comparing mouse strains with extreme total lung capacities identifies novel candidate genes for pulmonary function.

George Leema L Mitra Ankita A Thimraj Tania A TA Irmler Martin M Vishweswaraiah Sangeetha S Lunding Lars L Hühn Dorothea D Madurga Alicia A Beckers Johannes J Fehrenbach Heinz H Upadhyay Swapna S Schulz Holger H Leikauf George D GD Ganguly Koustav K

Respiratory research 20170809 1

<h4>Background</h4>Failure to attain peak lung function by early adulthood is a risk factor for chronic lung diseases. Previously, we reported that C3H/HeJ mice have about twice total lung capacity (TLC) compared to JF1/MsJ mice. We identified seven lung function quantitative trait loci (QTL: Lfnq1-Lfnq7) in backcross/intercross mice derived from these inbred strains. We further demonstrated, superoxide dismutase 3, extracellular (Sod3), Kit oncogene (Kit) and secreted phosphoprotein 1 (Spp1) lo ...[more]

PMID: 28793908

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Project description:BACKGROUND: In pigs, the perinatal period is the most critical time for survival. Piglet maturation, which occurs at the end of gestation, leads to a state of full development after birth. Therefore, maturity is an important determinant of early survival. Skeletal muscle plays a key role in adaptation to extra-uterine life, e.g. glycogen storage and thermoregulation. In this study, we performed microarray analysis to identify the genes and biological processes involved in piglet muscle maturity. Progeny from two breeds with extreme muscle maturity phenotypes were analyzed at two time points during gestation (gestational days 90 and 110). The Large White (LW) breed is a selected breed with an increased rate of mortality at birth, whereas the Meishan (MS) breed produces piglets with extremely low mortality at birth. The impact of the parental genome was analyzed with reciprocal crossed fetuses. RESULTS: Microarray analysis identified 12,326 differentially expressed probes for gestational age and genotype. Such a high number reflects an important transcriptomic change that occurs between 90 and 110 days of gestation. 2,000 probes, corresponding to 1,120 unique annotated genes, involved more particularly in the maturation process were further studied. Functional enrichment and graph inference studies underlined genes involved in muscular development around 90 days of gestation, and genes involved in metabolic functions, such as gluconeogenesis, around 110 days of gestation. Moreover, a difference in the expression of key genes, e.g. PCK2, LDHA or PGK1, was detected between MS and LW just before birth. Reciprocal crossing analysis resulted in the identification of 472 genes with an expression preferentially regulated by one parental genome. Most of these genes (366) were regulated by the paternal genome. Among these paternally regulated genes, some known imprinted genes, such as MAGEL2 or IGF2, were identified and could have a key role in the maturation process. CONCLUSION: These results reveal the biological mechanisms that regulate muscle maturity in piglets. Maturity is also under the conflicting regulation of the parental genomes. Crucial genes, which could explain the biological differences in maturity observed between LW and MS breeds, were identified. These genes could be excellent candidates for a key role in the maturity.

Project description:Biomedical research studies have generated large multi-omic datasets to study complex diseases like Alzheimer's disease (AD). An important aim of these studies is the identification of candidate genes that demonstrate congruent disease-related alterations across the different data types measured by the study. We developed a new method to detect such candidate genes in large multi-omic case-control studies that measure multiple data types in the same set of samples. The method is based on a gene-centric integrative coefficient quantifying to what degree consistent differences are observed in the different data types. For statistical inference, a Bayesian hierarchical model is used to study the distribution of the integrative coefficient. The model employs a conditional autoregressive prior to integrate a functional gene network and to share information between genes known to be functionally related. We applied the method to an AD dataset consisting of histone acetylation, DNA methylation, and RNA transcription data from human cortical tissue samples of 233 subjects, and we detected 816 genes with consistent differences between persons with AD and controls. The findings were validated in protein data and in RNA transcription data from two independent AD studies. Finally, we found three subnetworks of jointly dysregulated genes within the functional gene network which capture three distinct biological processes: myeloid cell differentiation, protein phosphorylation and synaptic signaling. Further investigation of the myeloid network indicated an upregulation of this network in early stages of AD prior to accumulation of hyperphosphorylated tau and suggested that increased CSF1 transcription in astrocytes may contribute to microglial activation in AD. Thus, we developed a method that integrates multiple data types and external knowledge of gene function to detect candidate genes, applied the method to an AD dataset, and identified several disease-related genes and processes demonstrating the usefulness of the integrative approach.

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Transcriptomic analysis comparing mouse strains with extreme total lung capacities identifies novel candidate genes for pulmonary function.

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Transcriptomic analysis comparing mouse strains with extreme total lung capacities identifies novel candidate genes for pulmonary function.

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