Analysis of LINE1 Retrotransposons in Huntington’s Disease

Transposable elements (TEs) are mobile genetic elements that made up about half the human genome. Among them, the autonomous non-LTR retrotransposon long interspersed nuclear element-1 (L1) is the only currently active TE in mammals and covers about 17% of the mammalian genome. L1s exert their function as structural elements in the genome, as transcribed RNAs to influence chromatin structure and as retrotransposed elements to shape genomic variation in somatic cells. L1s activity has been shown altered in several diseases of the nervous system. Huntington disease (HD) is a dominantly inherited neurodegenerative disorder caused by an expansion of a CAG repeat in the HTT gene which leads to a gradual loss of neurons most prominently in the striatum and, to a lesser extent, in cortical brain regions. The length of the expanded CAG tract is related to age at disease onset, with longer repeats leading to earlier onset. Here we carried out bioinformatic analysis of public RNA-seq data of a panel of HD mouse models showing that a decrease of L1 RNA expression recapitulates two hallmarks of the disease: it correlates to CAG repeat length and it occurs in the striatum, the site of neurodegeneration. Results were then experimentally validated in HttQ111 knock-in mice. The expression of L1-encoded proteins was independent from L1 RNA levels and differentially regulated in time and tissues. The pattern of expression L1 RNAs in human HD post-mortem brains showed similarity to mouse models of the disease. This work suggests the need for further study of L1s in HD and adds support to the current hypothesis that dysregulation of TEs may be involved in neurodegenerative diseases.

Physical geography, isolation by distance and environmental variables shape genomic variation of wild barley (Hordeum vulgare L. ssp. spontaneum) in the Southern Levant

Determining the extent of genetic variation that reflects local adaptation in crop-wild relatives is of interest for the purpose of identifying useful genetic diversity for plant breeding. We investigated the association of genomic variation with geographical and environmental factors in wild barley (Hordeum vulgare L. ssp. spontaneum) populations of the Southern Levant using genotyping by sequencing (GBS) of 244 accessions in the Barley 1K+ collection. The inference of population structure resulted in four genetic clusters that corresponded to eco-geographical habitats and a significant association between lower gene flow rates and geographical barriers, e.g. the Judaean Mountains and the Sea of Galilee. Redundancy analysis (RDA) revealed that spatial autocorrelation explained 45% and environmental variables explained 15% of total genomic variation. Only 4.5% of genomic variation was solely attributed to environmental variation if the component confounded with spatial autocorrelation was excluded. A synthetic environmental variable combining latitude, solar radiation, and accumulated precipitation explained the highest proportion of genomic variation (3.9%). When conditioned on population structure, soil water capacity was the most important environmental variable explaining 1.18% of genomic variation. Genome scans with outlier analysis and genome-environment association studies were conducted to identify adaptation signatures. RDA and outlier methods jointly detected selection signatures in the pericentromeric regions, which have reduced recombination, of the chromosomes 3H, 4H, and 5H. However, selection signatures mostly disappeared after correction for population structure. In conclusion, adaptation to the highly diverse environments of the Southern Levant over short geographical ranges had a limited effect on the genomic diversity of wild barley. This highlighted the importance of nonselective forces in genetic differentiation.

Deleterious Genetic Variation Across the NOD Signaling Pathway Is Associated With Reduced NFKB Signaling Transcription and Upregulation of Alternative Inflammatory Transcripts in Pediatric Inflammatory Bowel Disease

Background Inflammatory bowel disease may arise with inadequate immune response to intestinal bacteria. NOD2 is an established gene in Crohn’s disease pathogenesis, with deleterious variation associated with reduced NFKB signaling. We hypothesized that deleterious variation across the NOD2 signaling pathway impacts on transcription. Methods Treatment-naïve pediatric inflammatory bowel disease patients had ileal biopsies for targeted autoimmune RNA-sequencing and blood for whole exome sequencing collected at diagnostic endoscopy. Utilizing GenePy, a per-individual, per-gene score, genes within the NOD signaling pathway were assigned a quantitative score representing total variant burden. Where multiple genes formed complexes, GenePy scores were summed to create a “complex” score. Normalized transcript expression of 95 genes within this pathway was retrieved. Regression analysis was performed to determine the impact of genomic variation on gene transcription. Results Thirty-nine patients were included. Limited clustering of patients based on NOD signaling transcripts was related to underlying genomic variation. Patients harboring deleterious variation in NOD2 had reduced NOD2 (β = -0.702, P = 4.3 × 10-5) and increased NFKBIA (β = 0.486, P = .001), reflecting reduced NFKB signal activation. Deleterious variation in the NOD2-RIPK2 complex was associated with increased NLRP3 (β = 0.8, P = 3.1475 × 10-8) and TXN (β = -0.417, P = 8.4 × 10-5) transcription, components of the NLRP3 inflammasome. Deleterious variation in the TAK1-TAB complex resulted in reduced MAPK14 transcription (β = -0.677, P = 1.7 × 10-5), a key signal transduction protein in the NOD2 signaling cascade and increased IFNA1 (β = 0.479, P = .001), indicating reduced transcription of NFKB activators and alternative interferon transcription in these patients. Conclusions Data integration identified perturbation of NOD2 signaling transcription correlated with genomic variation. A hypoimmune NFKB signaling transcription response was observed. Alternative inflammatory pathways were activated and may represent therapeutic targets in specific patients.

The Rhizosphere Bacterial Communities Differ Among Domesticated Maize Landraces – An Experimental Confirmation

The plant-associated microbiome has been shown to vary considerably between species and across environmental gradients. The effects of genomic variation on the microbiome within single species are less clearly understood, with results often confounded by the larger effects of climatic and edaphic variation. In this study, the effect of genomic variation on the rhizosphere bacterial communities of maize was investigated by comparing different genotypes grown within controlled environments. Rhizosphere bacterial communities were profiled by metabarcoding the universal bacterial 16S rRNA v3-v4 region. Initially, plants from the inbred B73 line and the Ancho - More 10 landrace were grown for 12-weeks and compared. The experiment was then repeated with an additional four Mexican landraces (Apachito - Chih 172, Tehua - Chis 204, Serrano - Pueb 180 and Hairnoso de Ocho) that were grown alongside additional B73 and Ancho - More 10 genotypes. In both experiments there were significant genotypic differences in the rhizosphere bacteria. Additionally, the bacterial communities were significantly correlated with genomic distance between genotypes, with the more closely related landraces being more similar in rhizosphere bacterial communities. Despite limited sampling numbers, here we confirm that genomic variation in maize landraces is associated with differences in the rhizosphere bacterial communities. Further studies that go beyond correlations to identify the mechanisms that determine the genotypic variation of the rhizosphere microbiome are required.

Investigating Variations/SNPs in AUH Gene Causing 3-Methylglutaconic Aciduria, Type I

A Single nucleotide polymorphisms (SNPs) is a source variation in a genome. The AUH gene gives guidance about how to generate an enzyme named 3-methylglutaconyl-CoA hydratase. Mutations in AUH gene leads to 3-Methylglutaconic aciduria type I disease. The authors used multiple bioinformatics tools SIFT, Provean, PolyPhen, PHD-SNP, I-Mutant, ConSurf server and Project HOPE to isolate missense SNPs that should be deleterious to the structure and function of the AUH protein. This research aims to analyze the impact of missense SNPs on the structure and function of AUH protein. There have been a total of 259 Missense SNPs obtained, of which 13 mutations were identified as deleterious to the structure and function of the AUH protein. This is the first study in relation to AUH gene missense SNPs where most damaging SNPs associated with the AUH gene were examined using computational analysis. This research could be useful in designing specific medicines for treatment of genomic variation diseases.

Mapping of novel loci involved in lung and colon tumor susceptibility by the use of genetically selected mouse strains

Two non-inbred mouse lines, phenotypically selected for maximal (AIRmin) and minimal (AIRmax) acute inflammatory response, show differential susceptibility/resistance to the development of several chemically-induced tumor types. An intercross pedigree of these mice was generated and treated with the chemical carcinogen dimethylhydrazine, which induces lung and intestinal tumors. Genome wide high-density genotyping with the Restriction Site-Associated DNA genotyping (2B-RAD) technique was used to map genetic loci modulating individual genetic susceptibility to both lung and intestinal cancer. Our results evidence new common quantitative trait loci (QTL) for those phenotypes and provide an improved understanding of the relationship between genomic variation and individual genetic predisposition to tumorigenesis in different organs.

Analysis of Clinical Characteristics and Virus Strains Variation of Patients Infected With SARS-CoV-2 in Jiangsu Province—A Retrospective Study

Background: At present, the global sever acute respiratory syndrome coronavirus 2 (SARS-CoV-2) situation is still grim, and the risk of local outbreaks caused by imported viruses is high. Therefore, it is necessary to monitor the genomic variation and genetic evolution characteristics of SARS-CoV-2. The main purpose of this study was to detect the entry of different SARS-CoV-2 variants into Jiangsu Province, China.Methods: First, oropharyngeal swabs were collected from 165 patients (55 locally confirmed cases and 110 imported cases with confirmed and asymptomatic infection) diagnosed with SARS-CoV-2 infection in Jiangsu Province, China between January 2020 and June 2021. Then, whole genome sequencing was used to explore the phylogeny and find potential mutations in genes of the SARS-CoV-2. Last, association analysis among clinical characteristics and SARS-CoV-2 Variant of Concern, pedigree surveillance analysis of SARS-COV-2, and single nucleotide polymorphisms (SNPs) detection in SARS-COV-2 samples was performed.Results: More men were infected with the SARS-CoV-2 when compared with women. The onset of the SARS-CoV-2 showed a trend of younger age. Moreover, the number of asymptomatic infected patients was large, similar to the number of common patients. Patients infected with Alpha (50%) and Beta (90%) variants were predominantly asymptomatic, while patients infected with Delta (17%) variant presented severe clinical features. A total of 935 SNPs were detected in 165 SARS-COV-2 samples. Among which, missense mutation (58%) was the dominant mutation type. About 56% of SNPs changes occurred in the open reading frame 1ab (ORF1ab) gene. Approximately, 20% of SNP changes occurred in spike glycoprotein (S) gene, such as p.Asp501Tyr, p.Pro681His, and p.Pro681Arg. In total, nine SNPs loci in S gene were significantly correlated with the severity of patients. It is worth mentioning that amino acid substitution of p.Asp614Gly was significantly positively correlated with the clinical severity of patients. The amino acid replacements of p.Ser316Thr and p.Lu484Lys were significantly negatively correlated with the course of disease.Conclusion: Sever acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may further undergo a variety of mutations in different hosts, countries, and weather conditions. Detecting the entry of different virus variants of SARS-CoV-2 into Jiangsu Province, China may help to monitor the spread of infection and the diversity of eventual recombination or genomic mutations.

Advances in and prospects for Actinidia viruses

Kiwifruit (Actinidia spp.) is an economically important fruit crop worldwide. Before 2010, kiwifruit viruses had not received much attention; since then, more than 20 viruses infecting kiwifruit have been discovered. Some of these viruses cause severe yellowing, mosaic, necrosis, ringspots and other symptoms on leaves, seriously impacting yield and quality. Many of these viruses are widely distributed. This review summarizes recent research advances in the identification, genomic variation, distribution, transmission, detection, incidence, prevention and control of kiwifruit viruses and proposes directions for future research. Using virus-tested propagation material is the most economical and effective method for controlling kiwifruit viruses.

Identification of a Cancer Stemness Driven Prognostic Model and Therapeutic Drug Targets by Machine Learning in Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is one of the most common malignancies. Cancer stem cells (CSCs), characterized by self-renewal and drug-resistance, play an important role in the development and progression of diverse cancers, but the underlying association of HCC and CSCs is not fully researched.Methods: Transcriptome and clinical data of 903 patients in four independent HCC cohorts were obtained from TCGA, ICGC, and GEO databases. We evaluated the stemlike index for each patient to reflect the cancer stemness by using one-class logistic regression (OCLR) algorithm. GISTIC 2.0, Maftools and GSVA were used to reveal the association between the stemness index and genomic variation and biological processes in HCC. The differential expression analysis, univariate Cox analysis and LASSO analysis were used to identify the prognostic stemness signatures. The HCC stemness-related risk score (HCSRS) was constructed to quantify stemness levels of individual tumors. Based on HCSRS, the nomogram was established for HCC prognosis in a quantitative approach. Additionally, single sample Gene Set Enrichment Analysis (ssGSEA) algorithm was used to evaluate the immune infiltration levels in HCC, and drug response analysis was adopted to identify potential agents with drug sensitivity in high-HCSRS score patients.Results: The stemness index in HCC tissues was significantly higher than that in normal tissues, and there was a significant positive correlation with pathological grade. Patients with high stemness index showed higher somatic mutation frequency, tumor mutation load, and copy number variation frequency, and were significantly enriched in tumor-related signaling pathways. Meanwhile, the 7-gene based HCSRS model that was trained and validated in 4 independent cohorts exhibited high predictive significance for overall survival (OS). Further analysis revealed that patients with high HCSRS possessed higher immunosuppression status, characterized by significantly decreased infiltration of anti-tumor immune cells (CD8 T cells, cytotoxic T cells, DC cells, NK cells, etc.) and exhausted CYT responses. At last, a total of twelve agents were identified to have potential therapeutic effects in high-HCSRS patients.Conclusion: In current study, we systematically analyzed the potential relationship of HCC stemness with genomic variation, tumor microenvironment and biological processes, provided a theoretical basis for individualized treatment of HCC patients.

CottonGVD: A Comprehensive Genomic Variation Database for Cultivated Cottons

Cultivated cottons are the most important economic crop, which produce natural fiber for the textile industry. In recent years, the genetic basis of several essential traits for cultivated cottons has been gradually elucidated by decoding their genomic variations. Although an abundance of resequencing data is available in public, there is still a lack of a comprehensive tool to exhibit the results of genomic variations and genome-wide association study (GWAS). To assist cotton researchers in utilizing these data efficiently and conveniently, we constructed the cotton genomic variation database (CottonGVD; http://120.78.174.209/ or http://db.cngb.org/cottonGVD). This database contains the published genomic information of three cultivated cotton species, the corresponding population variations (SNP and InDel markers), and the visualized results of GWAS for major traits. Various built-in genomic tools help users retrieve, browse, and query the variations conveniently. The database also provides interactive maps (e.g., Manhattan map, scatter plot, heatmap, and linkage disequilibrium block) to exhibit GWAS and expression GWAS results. Cotton researchers could easily focus on phenotype-associated loci visualization, and they are interested in and screen for candidate genes. Moreover, CottonGVD will continue to update by adding more data and functions.