Roles of alternative splicing in infectious diseases: from hosts, pathogens to their interactions

Genome-wide association analysis of the resistance to infectious hematopoietic necrosis virus in two rainbow trout aquaculture lines confirms oligogenic architecture with several moderate effect quantitative trait loci

Infectious hematopoietic necrosis (IHN) is a disease of salmonid fish that is caused by the IHN virus (IHNV), which can cause substantial mortality and economic losses in rainbow trout aquaculture and fisheries enhancement hatchery programs. In a previous study on a commercial rainbow trout breeding line that has undergone selection, we found that genetic resistance to IHNV is controlled by the oligogenic inheritance of several moderate and many small effect quantitative trait loci (QTL). Here we used genome wide association analyses in two different commercial aquaculture lines that were naïve to previous exposure to IHNV to determine whether QTL were shared across lines, and to investigate whether there were major effect loci that were still segregating in the naïve lines. A total of 1,859 and 1,768 offspring from two commercial aquaculture strains were phenotyped for resistance to IHNV and genotyped with the rainbow trout Axiom 57K SNP array. Moderate heritability values (0.15-0.25) were estimated. Two statistical methods were used for genome wide association analyses in the two populations. No major QTL were detected despite the naïve status of the two lines. Further, our analyses confirmed an oligogenic architecture for genetic resistance to IHNV in rainbow trout. Overall, 17 QTL with notable effect (≥1.9% of the additive genetic variance) were detected in at least one of the two rainbow trout lines with at least one of the two statistical methods. Five of those QTL were mapped to overlapping or adjacent chromosomal regions in both lines, suggesting that some loci may be shared across commercial lines. Although some of the loci detected in this GWAS merit further investigation to better understand the biological basis of IHNV disease resistance across populations, the overall genetic architecture of IHNV resistance in the two rainbow trout lines suggests that genomic selection may be a more effective strategy for genetic improvement in this trait.

Large-scale analysis reveals splicing biomarkers for tuberculosis progression and prognosis

BACKGROUND

Emerging evidence suggests that aberrant alternative splicing (AS) may play an important role in tuberculosis (TB). However, current knowledge regarding the value of AS in TB progression and prognosis remains unclear.

METHOD

Public RNA-seq datasets related to TB progression and prognosis were searched and AS analyses were conducted based on SUPPA2. Percent spliced in (PSI) was used for quantifying AS events and multiple machine learning (ML) methods were employed to construct predictive models. Area under curve (AUC), sensitivity and specificity were calculated to evaluate the model performance.

RESULTS

A total of 1587 samples from 7 datasets were included. Among 923 TB-progression related differential AS events (DASEs), 3 events (GET1-skipping exon (SE), TPD52-alternative first exons (AF) and TIMM10-alternative 5' splice site (A5)) were selected as candidate biomarkers; however, their predictive performance was limited. For TB prognosis, 5 events (PHF23-AF, KIF1B-SE, MACROD2-alternative 3' splice site (A3), CD55-retained intron (RI) and GALNT11-AF) were selected as candidates from the 1282 DASEs. Six ML methods were used to integrate these 5 events and XGBoost outperformed than others. AUC, sensitivity and specificity of XGBoost model were 0.875, 81.1% and 83.5% in training set, while they were 0.805, 68.4% and 73.2% in test set.

CONCLUSION

GET1-SE, TPD52-AF and TIMM10-A5 showed limited role in predicting TB progression, while PHF23-AF, KIF1B-SE, MACROD2-A3, CD55-RI and GALNT11-AF could well predict TB prognosis and work as candidate biomarkers. This work preliminarily explored the value of AS in predicting TB progression and prognosis and offered potential targets for further research.

Rs15285, a functional polymorphism located in lipoprotein lipase, predicts the risk and prognosis of gastric cancer

Lipoprotein lipase (LPL), a crucial gene in lipid metabolism, has a significant role in the progression of malignant tumors. The purpose of this research was to investigate the impact of rs15285 found in the LPL gene's 3'UTR region on the risk, biological behavior, and gastric cancer (GC) prognosis as well as to examine its potential function. Genotyping of rs15285 in 888 GC cases and 874 controls was conducted by SNaPshot technology. We used bioinformatics analysis and in vitro experiments to study the role of rs15285. First, this study revealed for the first time that polymorphism rs15285 increases the risk of GC (OR = 1.48, 95%CI = 1.16-1.89, P = 0.002). Although no relationship was found between rs12585 and the pathological features of GC, the prognosis of individuals with the rs12585 TT genotype was poorer than that of patients with the CC or CC+CT genotype (HR = 2.39 for TT vs. CC, P = 0.025; HR = 2.38 for TT vs. CC+CT, P = 0.025). In addition, bioinformatics analysis showed rs12585 may affect the binding of miRNAs to LPL, resulting in an increase of LPL expression to promote cancer progression. Ultimately, in vitro tests revealed that the rs15285 T allele increased LPL expression on the mRNA as well as the protein levels, promoting GC cell proliferation, invasion, and metastasis. The LPL rs12528 TT genotype increased the risk of GC and predicted a poor prognosis. Mechanistically, the rs15285 T allele could improve the expression of LPL, and thus promotes the malignant phenotype of GC. Therefore, our study may provide new biological predictors and a theoretical basis for the prognosis and customized therapy of stomach cancer patients. KEY POINTS: • Rs15285 polymorphism is a risk factor for GC. • Rs12585 TT genotype predicts a bad outcome in GC individuals. • Rs15285 T allele enhances GC cells malignant biological behavior.