scholarly journals Immune gene diversity in archaic and present-day humans

2018 ◽  
Author(s):  
David Reher ◽  
Felix M. Key ◽  
Aida M. Andrés ◽  
Janet Kelso

Genome-wide analyses of two Neandertals and a Denisovan have shown that these archaic humans had lower genetic heterozygosity than present-day people. A similar reduction in genetic diversity of protein-coding genes (gene diversity) was found in exome sequences of three Neandertals. Reduced gene diversity, and particularly in genes involved in immunity, may have important functional consequences. In fact, it has been suggested that reduced diversity in immune genes may have contributed to Neandertal extinction. We therefore explored gene diversity in different human groups and at different time points on the Neandertal lineage with a particular focus on the diversity of genes involved in innate immunity and genes of the Major Histocompatibility Complex (MHC).We find that the two Neandertals and the Denisovan have similar gene diversity, both significantly lower than any present-day human. This is true across gene categories, with no gene set showing an excess decrease in diversity compared to the genome-wide average. Innate immune-related genes show a similar reduction in diversity to other genes, both in present-day and archaic humans. There is also no observable decrease in gene diversity over time in Neandertals, suggesting that there may have been no ongoing reduction in gene diversity in later Neandertals, although this needs confirmation with a larger sample size. In both archaic and present-day humans, genes with the highest levels of diversity are enriched for MHC-related functions. In fact, in archaic humans the MHC genes show evidence of having retained more diversity than genes involved only in the innate immune system.

2020 ◽  
Author(s):  
Zhiying Jia ◽  
Nan Wu ◽  
Xiaona Jiang ◽  
Heng Li ◽  
Jiaxin Sun ◽  
...  

ABSTRACTAnti-disease breeding is becoming the most promising solution to cyprinid herpesvirus-3 (CyHV-3) infection, the major threat to common carp aquaculture. Mortality studies suggested that a breeding strain of common carp is resistant to this disease. This study illustrates the immune mechanisms involved in anti-CyHV-3 ability. An integrative analysis of the protein-coding genes and long non-coding RNAs (lncRNAs) using transcriptomic data was also performed. Tissues from the head kidney of common carp were extracted at day 0 (the healthy control) and day 7 after CyHV-3 infection (the survivors), and used to analyze the transcriptome through both Illumina and Pac-bio sequencing. Following analysis of the Kyoto Encyclopedia of Genes and Genomes pathways and Gene Ontology terms involved, the immune-related genes were merged. These genes were filtered using the current common carp immune gene library, and information on the immune process was detailed. Immune gene categories and their corresponding genes in different comparison groups were revealed. Also, the immunological Gene Ontology terms for lncRNA modulation were retained. The weighted gene co-expression network analysis was used for the regulation of immune genes lncRNA. The results demonstrated that the breeding carp strain develops marked resistance to CyHV-3 through a specific innate immune mechanism. The featured biological processes were autophagy, phagocytosis, cytotoxicity, and virus blockage by lectins and mucin 3 (MUC3). Moreover, the immune suppressive signals, such as suppression of interleukin 21 receptor (IL21R) on STAT3, PI3K mediated the inhibition of inflammation by dopamine upon infection, as well as the inhibition of NLR family CARD domain containing 3 (NLRC3) on STING during a steady state. Possible susceptible factors for CyHV-3, such as integrin beta 1 (ITGB1), toll-like receptor 18 (TLR18), and C-C motif chemokine ligand 4 (CCL4), were also revealed from the common strain. The results of this study suggested that the regulation of galectin 3 (LGALS3) and T cell leukemia homeobox 3 (TLX3) by lncRNA may play a role in the resistance mechanism. Therefore, immune factors that are immunogenetically insensitive or susceptible to CyHV-3 infection have been revealed.


BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lin Chen ◽  
Yuxiang Dong ◽  
Yitong Pan ◽  
Yuhan Zhang ◽  
Ping Liu ◽  
...  

Abstract Background Breast cancer is one of the main malignant tumors that threaten the lives of women, which has received more and more clinical attention worldwide. There are increasing evidences showing that the immune micro-environment of breast cancer (BC) seriously affects the clinical outcome. This study aims to explore the role of tumor immune genes in the prognosis of BC patients and construct an immune-related genes prognostic index. Methods The list of 2498 immune genes was obtained from ImmPort database. In addition, gene expression data and clinical characteristics data of BC patients were also obtained from the TCGA database. The prognostic correlation of the differential genes was analyzed through Survival package. Cox regression analysis was performed to analyze the prognostic effect of immune genes. According to the regression coefficients of prognostic immune genes in regression analysis, an immune risk scores model was established. Gene set enrichment analysis (GSEA) was performed to probe the biological correlation of immune gene scores. P < 0.05 was considered to be statistically significant. Results In total, 556 immune genes were differentially expressed between normal tissues and BC tissues (p < 0. 05). According to the univariate cox regression analysis, a total of 66 immune genes were statistically significant for survival risk, of which 30 were associated with overall survival (P < 0.05). Finally, a 15 immune genes risk scores model was established. All patients were divided into high- and low-groups. KM survival analysis revealed that high immune risk scores represented worse survival (p < 0.001). ROC curve indicated that the immune genes risk scores model had a good reliability in predicting prognosis (5-year OS, AUC = 0.752). The established risk model showed splendid AUC value in the validation dataset (3-year over survival (OS) AUC = 0.685, 5-year OS AUC = 0.717, P = 0.00048). Moreover, the immune risk signature was proved to be an independent prognostic factor for BC patients. Finally, it was found that 15 immune genes and risk scores had significant clinical correlations, and were involved in a variety of carcinogenic pathways. Conclusion In conclusion, our study provides a new perspective for the expression of immune genes in BC. The constructed model has potential value for the prognostic prediction of BC patients and may provide some references for the clinical precision immunotherapy of patients.


2021 ◽  
Vol 35 (2) ◽  
pp. 365-366
Author(s):  
Carlos E. Lara ◽  
Catherine E. Grueber ◽  
Benedikt Holtmann ◽  
Eduardo S. A. Santos ◽  
Sheri L. Johnson ◽  
...  

2020 ◽  
Author(s):  
tiefeng cao ◽  
huimin shen

Abstract Background:Chemotherapeutic resistance is responsible for treatment failure. Immunotherapy is important in ovarian cancer (OC). Systematic exploration of immunogenic landscape and reliable immune gene-based prognostic biomarkers or signature is necessary to be identified. This study aims to identify the immune gene-based prognostic biomarkers and regulatory factors, further to develop an individualized prediction signature.Methods: This study systematically explored the gene expression profiles from RNA-seq data set for The Cancer Genome Atlas (TCGA) ovarian cancer. Differentially expressed and survival-associated immune genes and transcription factors (TFs) were identified using immune genes from ImmPort dataset and TFs from Cistoma database. We developed the prognostic signature based on survival associated immune genes with LASSO (Least absolute shrinkage and selection operator) Cox regression analysis. Further, Network analysis was performed to uncover the potential molecular mechanisms of immune-related genes with the help of computational biology. Results: The prognostic signature, a weighted combination of the 21 immune-related genes, performed moderately in survival prediction with AUC was 0.746, 0.735, and 0.749 for 1, 3, and 5 year overall survival, respectively. Network analysis uncovered the regulatory role of TFs in immune genes. Intriguingly, the prognostic signature reflected infiltration of some immune cell subtypes.Conclusions: We first constructed a signature with 21 immune genes of clinical significance, which showed promising predictive value in the surveillance, prognosis, even immunotherapy response of OC patients.


2021 ◽  
Author(s):  
Alberto Gomez-Carballa ◽  
Irene Rivero-Calle ◽  
Jacobo Pardo-Seco ◽  
Jose Gomez-Rial ◽  
Carmen Rivero-Velasco ◽  
...  

Background: COVID-19 symptoms range from mild to severe illness; the cause for this differential response to infection remains unknown. Unravelling the immune mechanisms acting at different levels of the colonization process might be key to understand these differences. Methods and findings: We carried out a multi-tissue (nasal, buccal and blood; n = 156) gene expression analysis of immune-related genes from patients affected by different COVID-19 severities, and healthy controls through the nCounter technology. We then used a differential expression approach and pathways analysis to detect tissue specific immune severity signals in COVID-19 patients. Mild and asymptomatic cases showed a powerful innate antiviral response in nasal epithelium, characterized by activation of interferon (IFN) pathway and downstream cascades, successfully controlling the infection at local level. In contrast, weak macrophage/monocyte driven innate antiviral response and lack of IFN signalling activity were shown in severe cases. Consequently, oral mucosa from severe patients showed signals of viral activity, cell arresting and viral dissemination to the lower respiratory tract, which ultimately could explain the exacerbated innate immune response and impaired adaptative immune responses observed at systemic level. Results from saliva transcriptome suggest that the buccal cavity might play a key role in SARS-CoV-2 infection and dissemination in patients with worse prognosis. Conclusions: We found severity-related signatures in patient tissues mainly represented by genes involved in the innate immune system and cytokine/chemokine signalling. Local immune response could be key to determine the course of the systemic response and thus COVID-19 severity. Our findings provide a framework to investigate severity host gene biomarkers and pathways that might be relevant to diagnosis, prognosis, and therapy.


2015 ◽  
Vol 11 (9) ◽  
pp. 20150576 ◽  
Author(s):  
Sebastian Stockmaier ◽  
Dina K. N. Dechmann ◽  
Rachel A. Page ◽  
M. Teague O'Mara

Bat immune systems may allow them to respond to zoonotic agents more efficiently than other mammals. As the first line of defence, the taxonomically conserved acute phase immune reaction of leucocytosis and fever is crucial for coping with infections, but it is unknown if this response is a key constituent to bat immunological success. We investigated the acute phase reaction to a standard lipopolysaccharide (LPS) challenge in Pallas's mastiff bats ( Molossus molossus ). Challenged bats lost mass, but in contrast to other mammals showed no leucocytosis or fever. There also was no influence on body temperature reduction during torpor. When compared to recent genome-wide assays for constituent immune genes, this lack of a conserved fever response to LPS contributes to a clearer understanding of the innate immune system in bat species and of the coevolution of bats with a wide diversity of pathogens.


2020 ◽  
Vol 287 (1919) ◽  
pp. 20192675 ◽  
Author(s):  
Emily A. O'Connor ◽  
Dennis Hasselquist ◽  
Jan-Åke Nilsson ◽  
Helena Westerdahl ◽  
Charlie K. Cornwallis

Pathogen communities can vary substantially between geographical regions due to different environmental conditions. However, little is known about how host immune systems respond to environmental variation across macro-ecological and evolutionary scales. Here, we select 37 species of songbird that inhabit diverse environments, including African and Palaearctic residents and Afro-Palaearctic migrants, to address how climate and habitat have influenced the evolution of key immune genes, the major histocompatibility complex class I (MHC-I). Resident species living in wetter regions, especially in Africa, had higher MHC-I diversity than species living in drier regions, irrespective of the habitats they occupy. By contrast, no relationship was found between MHC-I diversity and precipitation in migrants. Our results suggest that the immune system of birds has evolved greater pathogen recognition in wetter tropical regions. Furthermore, evolving transcontinental migration appears to have enabled species to escape wet, pathogen-rich areas at key periods of the year, relaxing selection for diversity in immune genes and potentially reducing immune system costs.


2019 ◽  
Vol 5 ◽  
Author(s):  
Diana C. Outlaw ◽  
V. Woody Walstrom ◽  
Haley N. Bodden ◽  
Chuan-yu Hsu ◽  
Mark Arick ◽  
...  

Abstract All organisms encounter pathogens, and birds are especially susceptible to infection by malaria parasites and other haemosporidians. It is important to understand how immune genes, primarily innate immune genes which are the first line of host defense, have evolved across birds, a highly diverse group of tetrapods. Here, we find that innate immune genes are highly conserved across the avian tree of life and that although most show evidence of positive or diversifying selection within specific lineages or clades, the number of sites is often proportionally low in this broader context of putative constraint. Rather, evidence shows a much higher level of negative or purifying selection in these innate immune genes – rather than adaptive immune genes – which is consistent with birds' long coevolutionary history with pathogens and the need to maintain a rapid response to infection. We further explored avian responses to haemosporidians by comparing differential gene expression in wild birds (1) uninfected with haemosporidians, (2) infected with Plasmodium and (3) infected with Haemoproteus (Parahaemoproteus). We found patterns of significant differential expression with some genes unique to infection with each genus and a few shared between ‘treatment’ groups, but none that overlapped with the genes included in the phylogenetic study.


2021 ◽  
Author(s):  
tiefeng cao ◽  
huimin shen

Abstract Background: Various components of the immune system play a critical role in the prognosis and treatment response in ovarian cancer (OC). Immunotherapy has been recognized as a hallmark of cancer but the effect is contradictional. Reliable immune gene-based prognostic biomarkers or regulatory factors are necessary to be systematically explored to develop an individualized prediction signature.Methods: This study systematically explored the gene expression profiles in patients with ovarian cancer from RNA-seq data set for The Cancer Genome Atlas (TCGA). Differentially expressed immune genes and transcription factors (TFs) were identified using the collected immune genes from ImmPort dataset and TFs from Cistoma database. Survival associated immune genes and TFs were identified in terms of overall survival. The prognostic signature was developed based on survival associated immune genes with LASSO (Least absolute shrinkage and selection operator) Cox regression analysis. Further, we performed network analysis to uncover the potential regulators of immune-related genes with the help of computational biology. Results: The prognostic signature, a weighted combination of the 21 immune-related genes, performed moderately in survival prediction with AUC was 0.746, 0.735, and 0.749 for 1, 3, and 5 year overall survival, respectively. Network analysis uncovered the regulatory role of TFs in immune genes. Intriguingly, the prognostic signature reflected the immune cells landscape and infiltration of some immune cell subtypes.Conclusions: We first constructed a signature with 21 immune genes of clinical significance, which showed promising predictive value in the surveillance, and prognosis of OC patients.


2021 ◽  
Vol 12 ◽  
Author(s):  
Shaojun Hu ◽  
Xiusheng Qu ◽  
Yu Jiao ◽  
Jiahui Hu ◽  
Bo Wang

Background: To classify triple-negative breast cancer (TNBC) immunotyping using the public database, analyze the differences between subtypes in terms of clinical characteristics and explore the role and clinical significance of immune subtypes in TNBC immunotherapy.Methods: We downloaded TNBC data from the cBioPortal and GEO databases. The immune genes were grouped to obtain immune gene modules and annotate their biological functions. Log-rank tests and Cox regression were used to evaluate the prognosis of immune subtypes (IS). Drug sensitivity analysis was also performed for the differences among immune subtypes in immunotherapy and chemotherapy. In addition, dimension reduction analysis based on graph learning was utilized to reveal the internal structure of the immune system and visualize the distribution of patients.Results: Significant differences in prognosis were observed between subtypes (IS1, IS2, and IS3), with the best in IS3 and the worst in IS1. The sensitivity of IS3 to immunotherapy and chemotherapy was better than the other two subtypes. In addition, Immune landscape analysis found the intra-class heterogeneity of immune subtypes and further classified IS3 subtypes (IS3A and IS3B). Immune-related genes were divided into seven functional modules (The turquoise module has the worst prognosis). Five hub genes (RASSF5, CD8A, ICOS, IRF8, and CD247) were screened out as the final characteristic genes related to poor prognosis by low expression.Conclusions: The immune subtypes of TNBC were significantly different in prognosis, gene mutation, immune infiltration, drug sensitivity, and heterogeneity. We validated the independent role of immune subtypes in tumor progression and immunotherapy for TNBC. This study provides a new perspective for personalized immunotherapy and the prognosis evaluation of TNBC patients in the future.


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