Computational modelling of chromosomally clustering protein domains in bacteria

BACKGROUND

In bacteria, genes with related functions-such as those involved in the metabolism of the same compound or in infection processes-are often physically close on the genome and form groups called clusters. The enrichment of such clusters over various distantly related bacteria can be used to predict the roles of genes of unknown function that cluster with characterised genes. There is no obvious rule to define a cluster, given their variability in size and intergenic distances, and the definition of what comprises a "gene", since genes can gain and lose domains over time. Protein domains can cluster within a gene, or in adjacent genes of related function, and in both cases these are chromosomally clustered. Here, we model the distances between pairs of protein domain coding regions across a wide range of bacteria and archaea via a probabilistic two component mixture model, without imposing arbitrary thresholds in terms of gene numbers or distances.

RESULTS

We trained our model using matched gene ontology terms to label functionally related pairs and assess the stability of the parameters of the model across 14,178 archaeal and bacterial strains. We found that the parameters of our mixture model are remarkably stable across bacteria and archaea, except for endosymbionts and obligate intracellular pathogens. Obligate pathogens have smaller genomes, and although they vary, on average do not show noticeably different clustering distances; the main difference in the parameter estimates is that a far greater proportion of the genes sharing ontology terms are clustered. This may reflect that these genomes are enriched for complexes encoded by clustered core housekeeping genes, as a proportion of the total genes. Given the overall stability of the parameter estimates, we then used the mean parameter estimates across the entire dataset to investigate which gene ontology terms are most frequently associated with clustered genes.

CONCLUSIONS

Given the stability of the mixture model across species, it may be used to predict bacterial gene clusters that are shared across multiple species, in addition to giving insights into the evolutionary pressures on the chromosomal locations of genes in different species.

Lung expression of genes putatively involved in SARS-CoV-2 infection is modulated in cis by germline variants

Germline variants in genes involved in SARS-CoV-2 cell entry and in host innate immune responses to viruses may influence the susceptibility to infection. This study used whole-genome analyses of lung tissue to identify polymorphisms acting as expression quantitative trait loci (eQTLs) for 60 genes of relevance to SARS-CoV-2 infection susceptibility. The expression of genes with confirmed or possible roles in viral entry-replication and in host antiviral responses was studied in the non-diseased lung tissue of 408 lung adenocarcinoma patients. No gene was differently expressed by sex, but APOBEC3H levels were higher and PARP12 levels lower in older individuals. A total of 125 cis-eQTLs (false discovery rate < 0.05) was found to modulate mRNA expression of 15 genes (ABO, ANPEP, AP2A2, APOBEC3D, APOBEC3G, BSG, CLEC4G, DDX58, DPP4, FURIN, FYCO1, RAB14, SERINC3, TRIM5, ZCRB1). eQTLs regulating ABO and FYCO1 were found in COVID-19 susceptibility loci. No trans-eQTLs were identified. Genetic control of the expression of these 15 genes, which encode putative virus receptors, proteins required for vesicle trafficking, enzymes that interfere with viral replication, and other restriction factors, may underlie interindividual differences in risk or severity of infection with SARS-CoV-2 or other viruses.

Read-through transcripts in normal human lung parenchyma are down-regulated in lung adenocarcinoma

Read-through transcripts result from the continuous transcription of adjacent, similarly oriented genes, with the splicing out of the intergenic region. They have been found in several neoplastic and normal tissues, but their pathophysiological significance is unclear. We used high-throughput sequencing of cDNA fragments (RNA-Seq) to identify read-through transcripts in the non-involved lung tissue of 64 surgically treated lung adenocarcinoma patients. A total of 52 distinct read-through species was identified, with 24 patients having at least one read-through event, up to a maximum of 17 such transcripts in one patient. Sanger sequencing validated 28 of these transcripts and identified an additional 15, for a total of 43 distinct read-through events involving 35 gene pairs. Expression levels of 10 validated read-through transcripts were measured by quantitative PCR in pairs of matched non-involved lung tissue and lung adenocarcinoma tissue from 45 patients. Higher expression levels were observed in normal lung tissue than in the tumor counterpart, with median relative quantification ratios between normal and tumor varying from 1.90 to 7.78; the difference was statistically significant (P < 0.001, Wilcoxon's signed-rank test for paired samples) for eight transcripts: ELAVL1–TIMM44, FAM162B–ZUFSP, IFNAR2–IL10RB, INMT–FAM188B, KIAA1841–C2orf74, NFATC3–PLA2G15, SIRPB1–SIRPD, and SHANK3–ACR. This report documents the presence of read-through transcripts in apparently normal lung tissue, with inter-individual differences in patterns and abundance. It also shows their down-regulation in tumors, suggesting that these chimeric transcripts may function as tumor suppressors in lung tissue.

Complex genetic control of lung tumorigenesis in resistant mice strains

The SM/J mouse strain is resistant to chemically‐induced lung tumorigenesis despite having a haplotype, in the pulmonary adenoma susceptibility locus (Pas1) locus, that confers tumor susceptibility in other strains. To clarify this inconsistent genotype‐phenotype correlation, we crossed SM/J mice with another resistant strain and conducted genome‐wide linkage analysis in the (C57BL/6J × SM/J)F2 progeny exposed to urethane to induce lung tumors. Overall, >80% of F2 mice of both sexes developed from 1 to 20 lung tumors. Genotyping of 372 F2 mice for 744 informative non‐redundant SNPs dispersed over all autosomal chromosomes revealed four quantitative trait loci (QTLs) affecting lung tumor multiplicity, on chromosomes 3 (near rs13477379), 15 (rs6285067), 17 (rs33373629) and 18 (rs3706601), all with logarithm of the odds (LOD) scores >5. Four QTLs modulated total lung tumor volume, on chromosome 3 (rs13477379), 10 (rs13480702), 15 (rs6285067) and 17 (rs3682923), all with LOD scores >4. No QTL modulating lung tumor multiplicity or total volume was detected in Pas1 on chromosome 6. The present study demonstrates that the SM/J strain carries, at the Pas1 locus, the resistance allele: a finding that will facilitate identification of the Pas1 causal element. More generally, it demonstrates that lung tumorigenesis is under complex polygenic control even in a pedigree with low susceptibility to this neoplasia, suggesting that the genetics of lung tumorigenesis is much more complex than evidenced by the pulmonary adenoma susceptibility and resistance loci that have, so far, been mapped in a small number of crosses between a few inbred strains.

Human Lung Tissue Transcriptome: Influence of Sex and Age

Background

Sex and age strongly influence the pathophysiology of human lungs, but scarce information is available about their effects on pulmonary gene expression.

Methods

We followed a discovery-validation strategy to identify sex- and age-related transcriptional differences in lung.

Results

We identified transcriptional profiles significantly associated with sex (215 genes; FDR < 0.05) and age at surgery (217 genes) in non-involved lung tissue resected from 284 lung adenocarcinoma patients. When these profiles were tested in three independent series of non-tumor lung tissue from an additional 1,111 patients, we validated the association with sex and age for 25 and 22 genes, respectively. Among the 17 sex-biased genes mapping on chromosome X, 16 have been reported to escape X-chromosome inactivation in other tissues or cells, suggesting that this mechanism influences lung transcription too. Our 22 age-related genes partially overlap with genes modulated by age in other tissues, suggesting that the aging process has similar consequences on gene expression in different organs. Finally, seven genes whose expression was modulated by sex in non-tumor lung tissue, but no age-related gene, were also validated using publicly available data from 990 lung adenocarcinoma samples, suggesting that the physiological regulatory mechanisms are only partially active in neoplastic tissue.

Conclusions

Gene expression in non-tumor lung tissue is modulated by both sex and age. These findings represent a validated starting point for research on the molecular mechanisms underlying the observed differences in the course of lung diseases among men and women of different ages.

Expression quantitative trait analysis reveals fine germline transcript regulation in mouse lung tumors

Gene expression modulates cellular functions in both physiologic and pathologic conditions. Herein, we carried out a genetic linkage study on the transcriptome of lung tumors induced by urethane in an (A/J x C57BL/6)F4 intercross population, whose individual lung tumor multiplicity (Nlung) is linked to the genotype at the Pulmonary adenoma susceptibility 1 (Pas1) locus. We found that expression levels of 1179 and 1579 genes are modulated by an expression quantitative trait locus (eQTL) in cis and in trans, respectively (LOD score > 5). Of note, the genomic area surrounding and including the Pas1 locus regulated 14 genes in cis and 857 genes in trans. In lung tumors of the same (A/J x C57BL/6)F4 mice, we found 1124 genes whose transcript levels associated with Nlung (FDR < 0.001). The expression levels of about a third of these genes (n = 401) were regulated by the genotype at the Pas1 locus. Pathway analysis of the sets of genes associated with Nlung and regulated by Pas1 revealed a set of 14 recurrently represented genes that are components or targets of the Ras-Erk and Pi3k-Akt signaling pathways. Altogether our results illustrate the architecture of germline control of gene expression in mouse lung cancer: they highlight the importance of Pas1 as a tumor-modifier locus, attribute to it a novel role as a major regulator of transcription in lung tumor nodules and strengthen the candidacy of the Kras gene as the effector of this locus.