Genetic Factors in Mammalian Prion Diseases.

Mammalian prion diseases are a group of neurodegenerative conditions caused by infection of the central nervous system with proteinaceous agents called prions, including sporadic, variant, and iatrogenic Creutzfeldt-Jakob disease; kuru; inherited prion disease; sheep scrapie; bovine spongiform encephalopathy; and chronic wasting disease. Prions are composed of misfolded and multimeric forms of the normal cellular prion protein (PrP). Prion diseases require host expression of the prion protein gene (PRNP) and a range of other cellular functions to support their propagation and toxicity. Inherited forms of prion disease are caused by mutation of PRNP, whereas acquired and sporadically occurring mammalian prion diseases are controlled by powerful genetic risk and modifying factors. Whereas some PrP amino acid variants cause the disease, others confer protection, dramatically altered incubation times, or changes in the clinical phenotype. Multiple mechanisms, including interference with homotypic protein interactions and the selection of the permissible prion strains in a host, play a role. Several non-PRNP factors have now been uncovered that provide insights into pathways of disease susceptibility or neurotoxicity.

Integrative splicing-quantitative-trait-locus analysis reveals risk loci for non-small-cell lung cancer.

Splicing quantitative trait loci (sQTLs) have been demonstrated to contribute to disease etiology by affecting alternative splicing. However, the role of sQTLs in the development of non-small-cell lung cancer (NSCLC) remains unknown. Thus, we performed a genome-wide sQTL study to identify genetic variants that affect alternative splicing in lung tissues from 116 individuals of Chinese ancestry, which resulted in the identification of 1,385 sQTL-harboring genes (sGenes) containing 378,210 significant variant-intron pairs. A comprehensive characterization of these sQTLs showed that they were enriched in actively transcribed regions, genetic regulatory elements, and splicing-factor-binding sites. Moreover, sQTLs were largely distinct from expression quantitative trait loci (eQTLs) and showed significant enrichment in potential risk loci of NSCLC. We also integrated sQTLs into NSCLC GWAS datasets (13,327 affected individuals and 13,328 control individuals) by using splice-transcriptome-wide association study (spTWAS) and identified alternative splicing events in 19 genes that were significantly associated with NSCLC risk. By using functional annotation and experiments, we confirmed an sQTL variant, rs35861926, that reduced the risk of lung adenocarcinoma (rs35861926-T, OR = 0.88, 95% confidence interval [CI]: 0.82-0.93, p = 1.87 × 10-5) by promoting FARP1 exon 20 skipping to downregulate the expression level of the long transcript FARP1-011. Transcript FARP1-011 promoted the migration and proliferation of lung adenocarcinoma cells. Overall, our study provided informative lung sQTL resources and insights into the molecular mechanisms linking sQTL variants to NSCLC risk.

Powerful and robust inference of complex phenotypes' causal genes with dependent expression quantitative loci by a median-based Mendelian randomization.

Isolating the causal genes from numerous genetic association signals in genome-wide association studies (GWASs) of complex phenotypes remains an open and challenging question. In the present study, we proposed a statistical approach, the effective-median-based Mendelian randomization (MR) framework, for inferring the causal genes of complex phenotypes with the GWAS summary statistics (named EMIC). The effective-median method solved the high false-positive issue in the existing MR methods due to either correlation among instrumental variables or noises in approximated linkage disequilibrium (LD). EMIC can further perform a pleiotropy fine-mapping analysis to remove possible false-positive estimates. With the usage of multiple cis-expression quantitative trait loci (eQTLs), EMIC was also more powerful than the alternative methods for the causal gene inference in the simulated datasets. Furthermore, EMIC rediscovered many known causal genes of complex phenotypes (schizophrenia, bipolar disorder, and total cholesterol) and reported many new and promising candidate causal genes. In sum, this study provided an efficient solution to discriminate the candidate causal genes from vast amounts of GWAS signals with eQTLs. EMIC has been implemented in our integrative software platform KGGSEE.

Subcutaneous adipose tissue splice quantitative trait loci reveal differences in isoform usage associated with cardiometabolic traits.

Alternate splicing events can create isoforms that alter gene function, and genetic variants associated with alternate gene isoforms may reveal molecular mechanisms of disease. We used subcutaneous adipose tissue of 426 Finnish men from the METSIM study and identified splice junction quantitative trait loci (sQTLs) for 6,077 splice junctions (FDR < 1%). In the same individuals, we detected expression QTLs (eQTLs) for 59,443 exons and 15,397 genes (FDR < 1%). We identified 595 genes with an sQTL and exon eQTL but no gene eQTL, which could indicate potential isoform differences. Of the significant sQTL signals, 2,114 (39.8%) included at least one proxy variant (linkage disequilibrium r2 > 0.8) located within an intron spanned by the splice junction. We identified 203 sQTLs that colocalized with 141 genome-wide association study (GWAS) signals for cardiometabolic traits, including 25 signals for lipid traits, 24 signals for body mass index (BMI), and 12 signals for waist-hip ratio adjusted for BMI. Among all 141 GWAS signals colocalized with an sQTL, we detected 26 that also colocalized with an exon eQTL for an exon skipped by the sQTL splice junction. At a GWAS signal for high-density lipoprotein cholesterol colocalized with an NR1H3 sQTL splice junction, we show that the alternative splice product encodes an NR1H3 transcription factor that lacks a DNA binding domain and fails to activate transcription. Together, these results detect splicing events and candidate mechanisms that may contribute to gene function at GWAS loci.

A natural non-synonymous single nucleotide polymorphism in GmbHLH113 negates its inhibitory effect on root hair elongation in soybean.

Root hair length (RHL) is an important character that affects nutrient acquisition in plants. The regulatory network in soybean controlling RHL is yet to be fully understood. In this study, we identified a quantitative trait locus (QTL) regulating RHL. One candidate causal gene in this QTL (GmbHLH113), preferentially expressed in root hairs, was annotated as encoding a basic helix-loop-helix transcription factor. In wild soybeans, the allelic type of GmbHLH113 with a glycine in the 13th residue, which was associated with a reduction in RHL, was shown to localize in the nucleus and activate gene transcription. Another allelic type with a single nucleotide polymorphism that resulted in a glutamate in the 13th residue is fixed in cultivated soybeans, and it lost the ability to localize to the nucleus or negatively regulate RHL. The ectopic expression of GmbHLH113 from W05 in Arabidopsis root hairs resulted in shorter RHL and reduced phosphorus (P) accumulation in shoots. Hence, a loss-of-function allele in cultivated soybeans might have been selected during domestication due to its association with a longer RHL and improved nutrient acquisition.

African ancestry-derived APOL1 risk genotypes show proximal epigenetic associations.

Apolipoprotein L1 (APOL1) coding variants, termed G1 and G2, are established genetic risk factors for a growing spectrum of diseases, including kidney disease, in individuals of African ancestry. Evidence suggests that the risk variants, which show a recessive mode of inheritance, lead to toxic gain-of-function changes of the APOL1 protein. Disease occurrence and presentation vary, likely due to modifiers or second hits. To understand the role of the epigenetic landscape in relation to APOL1 risk variants, we performed methylation quantitative trait locus (meQTL) analysis to identify differentially methylated CpGs influenced by APOL1 risk variants in 611 African American individuals. We identified five CpGs that were significantly associated with APOL1 risk alleles in discovery and replication studies, and one CpG-APOL1 association was independent of other genomic variants. Our study highlights proximal DNA methylation alterations that may help explain the variable disease risk and clinical manifestation of APOL1 variants.

Identification of two major QTLs for pod shell thickness in peanut (Arachis hypogaea L.) using BSA-seq analysis.

BACKGROUND: Pod shell thickness (PST) is an important agronomic trait of peanut because it affects the ability of shells to resist pest infestations and pathogen attacks, while also influencing the peanut shelling process. However, very few studies have explored the genetic basis of PST. RESULTS: An F2 segregating population derived from a cross between the thick-shelled cultivar Yueyou 18 (YY18) and the thin-shelled cultivar Weihua 8 (WH8) was used to identify the quantitative trait loci (QTLs) for PST. On the basis of a bulked segregant analysis sequencing (BSA-seq), four QTLs were preliminarily mapped to chromosomes 3, 8, 13, and 18. Using the genome resequencing data of YY18 and WH8, 22 kompetitive allele-specific PCR (KASP) markers were designed for the genotyping of the F2 population. Two major QTLs (qPSTA08 and qPSTA18) were identified and finely mapped, with qPSTA08 detected on chromosome 8 (0.69-Mb physical genomic region) and qPSTA18 detected on chromosome 18 (0.15-Mb physical genomic region). Moreover, qPSTA08 and qPSTA18 explained 31.1-32.3% and 16.7-16.8% of the phenotypic variation, respectively. Fifteen genes were detected in the two candidate regions, including three genes with nonsynonymous mutations in the exon region. Two molecular markers (Tif2_A08_31713024 and Tif2_A18_7198124) that were developed for the two major QTL regions effectively distinguished between thick-shelled and thin-shelled materials. Subsequently, the two markers were validated in four F2:3 lines selected. CONCLUSIONS: The QTLs identified and molecular markers developed in this study may lay the foundation for breeding cultivars with a shell thickness suitable for mechanized peanut shelling.

Pathogen stimulations and immune cells synergistically affect the gene expression profile characteristics of porcine peripheral blood mononuclear cells.

BACKGROUND: Pigs serve as a crucial source of protein in the human diet and play a fundamental role in ensuring food security. However, infectious diseases caused by bacteria or viruses are a major threat to effective global pig farming, jeopardizing human health. Peripheral blood mononuclear cells (PBMCs) are a mixture of immune cells that play crucial roles in immunity and disease resistance in pigs. Previous studies on the gene expression regulation patterns of PBMCs have concentrated on a single immune stimulus or immune cell subpopulation, which has limited our comprehensive understanding of the mechanisms of the pig immune response. RESULTS: Here, we integrated and re-analyzed RNA-seq data published online for porcine PBMC stimulated by lipopolysaccharide (LPS), polyinosinic acid (PolyI:C), and various unknown microorganisms (EM). The results revealed that gene expression and its functional characterization are highly specific to the pathogen, identifying 603, 254, and 882 pathogen-specific genes and 38 shared genes, respectively. Notably, LPS and PolyI:C stimulation directly triggered inflammatory and immune-response pathways, while exposure to mixed microbes (EM) enhanced metabolic processes. These pathogen-specific genes were enriched in immune trait-associated quantitative trait loci (QTL) and eGenes in porcine immune tissues and were implicated in specific cell types. Furthermore, we discussed the roles of eQTLs rs3473322705 and rs1109431654 in regulating pathogen- and cell-specific genes CD300A and CD93, using cellular experiments. Additionally, by integrating genome-wide association studies datasets from 33 complex traits and diseases in humans, we found that pathogen-specific genes were significantly enriched for immune traits and metabolic diseases. CONCLUSIONS: We systematically analyzed the gene expression profiles of the three stimulations and demonstrated pathogen-specific and cell-specific gene regulation across different stimulations in porcine PBMCs. These findings enhance our understanding of shared and distinct regulatory mechanisms of genetic variants in pig immune traits.

Identification of candidate genes for Fusarium head blight resistance from QTLs using RIL population in wheat.

Fusarium head blight (FHB) stands out as one of the most devastating wheat diseases and leads to significantly grain yield losses and quality reductions in epidemic years. Exploring quantitative trait loci (QTL) for FHB resistance is a critical step for developing new FHB-resistant varieties. We previously constructed a genetic map of unigenes (UG-Map) according to the physical positions using a set of recombinant-inbred lines (RILs) derived from the cross of 'TN18 × LM6' (TL-RILs). Here, the number of diseased spikelets (NDS) and relative disease index (RDI) for FHB resistance were investigated under four environments using TL-RILs, which were distributed across 13 chromosomes. A number of 36 candidate genes for NDS and RDI from of 19 stable QTLs were identified. The average number of candidate genes per QTL was 1.89, with 14 (73.7%), two (10.5%), and three (15.8%) QTLs including one, two, and 3-10 candidate genes, respectively. Among the 24 candidate genes annotated in the reference genome RefSeq v1.1, the homologous genes of seven candidate genes, including TraesCS4B02G227300 for QNds/Rdi-4BL-4553, TraesCS5B02G303200, TraesCS5B02G303300, TraesCS5B02G303700, TraesCS5B02G303800 and TraesCS5B02G304000 for QNds/Rdi-5BL-9509, and TraesCS7A02G568400 for QNds/Rdi-7AL-14499, were previously reported to be related to FHB resistance in wheat, barely or Brachypodium distachyon. These genes should be closely associated with FHB resistance in wheat. In addition, the homologous genes of five genes, including TraesCS1A02G037600LC for QNds-1AS-2225, TraesCS1D02G017800 and TraesCS1D02G017900 for QNds-1DS-527, TraesCS1D02G018000 for QRdi-1DS-575, and TraesCS4B02G227400 for QNds/Rdi-4BL-4553, were involved in plant defense responses against pathogens. These genes should be likely associated with FHB resistance in wheat.

Mouse Genetic Reference Populations: Cellular Platforms for Integrative Systems Genetics.

Interrogation of disease-relevant cellular and molecular traits exhibited by genetically diverse cell populations enables in vitro systems genetics approaches for uncovering the basic properties of cellular function and identity. Primary cells, stem cells, and organoids derived from genetically diverse mouse strains, such as Collaborative Cross and Diversity Outbred populations, offer the opportunity for parallel in vitro/in vivo screening. These panels provide genetic resolution for variant discovery and functional characterization, as well as disease modeling and in vivo validation capabilities. Here we review mouse cellular systems genetics approaches for characterizing the influence of genetic variation on signaling networks and phenotypic diversity, and we discuss approaches for data integration and cross-species validation.