LINE-1 promotes tumorigenicity and exacerbates tumor progression via stimulating metabolism reprogramming in non-small cell lung cancer.

BACKGROUND: Long Interspersed Nuclear Element-1 (LINE-1, L1) is increasingly regarded as a genetic risk for lung cancer. Transcriptionally active LINE-1 forms a L1-gene chimeric transcript (LCTs), through somatic L1 retrotransposition (LRT) or L1 antisense promoter (L1-ASP) activation, to play an oncogenic role in cancer progression. METHODS: Here, we developed Retrotransposon-gene fusion estimation program (ReFuse), to identify and quantify LCTs in RNA sequencing data from TCGA lung cancer cohort (n = 1146) and a single cell RNA sequencing dataset then further validated those LCTs in an independent cohort (n = 134). We next examined the functional roles of a cancer specific LCT (L1-FGGY) in cell proliferation and tumor progression in LUSC cell lines and mice. RESULTS: The LCT events correspond with specific metabolic processes and mitochondrial functions and was associated with genomic instability, hypomethylation, tumor stage and tumor immune microenvironment (TIME). Functional analysis of a tumor specific and frequent LCT involving FGGY (L1-FGGY) reveal that the arachidonic acid (AA) metabolic pathway was activated by the loss of FGGY through the L1-FGGY chimeric transcript to promote tumor growth, which was effectively targeted by a combined use of an anti-HIV drug (NVR) and a metabolic inhibitor (ML355). Lastly, we identified a set of transcriptomic signatures to stratify the LUSC patients with a higher risk for poor outcomes who may benefit from treatments using NVR alone or combined with an anti-metabolism drug. CONCLUSIONS: This study is the first to characterize the role of L1 in metabolic reprogramming of lung cancer and provide rationale for L1-specifc prognosis and potential for a therapeutic strategy for treating lung cancer. TRIAL REGISTRATION: Study on the mechanisms of the mobile element L1-FGGY promoting the proliferation, invasion and immune escape of lung squamous cell carcinoma through the 12-LOX/Wnt pathway, Ek2020111. Registered 27 March 2020 - Retrospectively registered.

GWAS in Mice Maps Susceptibility to HIV-Associated Nephropathy to the Ssbp2 Locus.

BACKGROUND: To gain insight into the pathogenesis of collapsing glomerulopathy, a rare form of FSGS that often arises in the setting of viral infections, we performed a genome-wide association study (GWAS) among inbred mouse strains using a murine model of HIV-1 associated nephropathy (HIVAN). METHODS: We first generated F1 hybrids between HIV-1 transgenic mice on the FVB/NJ background and 20 inbred laboratory strains. Analysis of histology, BUN, and urinary NGAL demonstrated marked phenotypic variation among the transgenic F1 hybrids, providing strong evidence for host genetic factors in the predisposition to nephropathy. A GWAS in 365 transgenic F1 hybrids generated from these 20 inbred strains was performed. RESULTS: We identified a genome-wide significant locus on chromosome 13-C3 and multiple additional suggestive loci. Crossannotation of the Chr. 13 locus, including single-cell transcriptomic analysis of wildtype and HIV-1 transgenic mouse kidneys, nominated Ssbp2 as the most likely candidate gene. Ssbp2 is highly expressed in podocytes, encodes a transcriptional cofactor that interacts with LDB1 and LMX1B, which are both previously implicated in FSGS. Consistent with these data, older Ssbp2 null mice spontaneously develop glomerulosclerosis, tubular casts, interstitial fibrosis, and inflammation, similar to the HIVAN mouse model. CONCLUSIONS: These findings demonstrate the utility of GWAS in mice to uncover host genetic factors for rare kidney traits and suggest Ssbp2 as susceptibility gene for HIVAN, potentially acting via the LDB1-LMX1B transcriptional network.

Estimating greenhouse gas emissions from direct land use change due to crop production in multiple countries.

Greenhouse gas (GHG) emissions from direct land use change (LUC) in GHG footprint studies of crops are often estimated using national land use change statistics, as in many cases the exact location of crop cultivation and land use history is unknown. As such, these studies neglect spatial variability in land use change (amount and configuration) at the sub-national level as well as spatial variability in natural carbon stocks. For this reason, a spatial approach that enables consistent implementation of LUC emissions of crop production at different locations is developed and applied in this study. The dataset of crop production covers 69 crops cultivated on 1885 farms in 33 countries, spanning North and South America, Asia, Australia and Oceania, Europe and Africa, in the year 2014. Of the 1885 farms, 33% (619 farms) were identified to have LUC emissions when estimated at the local scale. LUC emissions of farms, derived using local scale location information, were found to have little correlation with those estimated at coarser spatial scales (such as the province or country level) using the spatial approach in this study or estimated using accounting approaches based on national statistics. Analysis at coarser spatial scales typically overestimated the LUC emissions of crops, as LUC in other regions can heavily influence these estimates. Therefore, it is concluded that local scale LUC emissions better represent local LUC dynamics, thereby improving the reliability of GHG footprint studies.

Greenhouse gas footprints of palm oil production in Indonesia over space and time.

Palm oil, the most widely used vegetable oil, is one of the largest drivers of greenhouse gas (GHG) emissions from global land use and land cover change. Here, we provide fine-resolution (100 m × 100 m) estimates of GHG footprints of current (2015) and potential future scenarios (2030) of crude palm oil (CPO) production in Indonesia. The current estimated average GHG footprint excluding production on Java is 5.7 t CO2 eq t-1 CPO; ranging from 0.7 t CO2 eq t-1 CPO in Hulu Sungai Tengah, Kalimantan to 26.0 t CO2 eq t-1 CPO in Pontianak, Kalimantan, and these vast differences are only discernible at fine spatial scales. The future GHG footprint of Indonesian CPO could be reduced by 42% without compromising increased output by limiting expansion to non-forest and non-peat land. Our fine-scale analysis provides a spatial screening approach to inform new oil palm concessions and sourcing decisions, before more cost-intensive patch analysis and carbon stock assessments are conducted.

Diagnostic Utility of Exome Sequencing for Kidney Disease.

BACKGROUND: Exome sequencing is emerging as a first-line diagnostic method in some clinical disciplines, but its usefulness has yet to be examined for most constitutional disorders in adults, including chronic kidney disease, which affects more than 1 in 10 persons globally. METHODS: We conducted exome sequencing and diagnostic analysis in two cohorts totaling 3315 patients with chronic kidney disease. We assessed the diagnostic yield and, among the patients for whom detailed clinical data were available, the clinical implications of diagnostic and other medically relevant findings. RESULTS: In all, 3037 patients (91.6%) were over 21 years of age, and 1179 (35.6%) were of self-identified non-European ancestry. We detected diagnostic variants in 307 of the 3315 patients (9.3%), encompassing 66 different monogenic disorders. Of the disorders detected, 39 (59%) were found in only a single patient. Diagnostic variants were detected across all clinically defined categories, including congenital or cystic renal disease (127 of 531 patients [23.9%]) and nephropathy of unknown origin (48 of 281 patients [17.1%]). Of the 2187 patients assessed, 34 (1.6%) had genetic findings for medically actionable disorders that, although unrelated to their nephropathy, would also lead to subspecialty referral and inform renal management. CONCLUSIONS: Exome sequencing in a combined cohort of more than 3000 patients with chronic kidney disease yielded a genetic diagnosis in just under 10% of cases. (Funded by the National Institutes of Health and others.).

Variability of Greenhouse Gas Footprints of Field Tomatoes Grown for Processing: Interyear and Intercountry Assessment.

Our study provides an integrated analysis of the variability of greenhouse gas (GHG) footprints of field-grown tomatoes for processing. The global farm-specific data set of 890 observations across 14 countries over a three-year period (2013-2015) was obtained from farms grown under Unilever's sustainable agricultural code. It represents on average 3% of the annual global production of processing tomatoes: insights can be used to help inform corporate sourcing strategies and certification schemes. The median GHG footprint ranged from 18 in Chile to 61 kg CO2-equiv per tonne of tomatoes in India, lower than results reported in other studies. We found that footprints are more consistent within countries than between them. Using linear mixed effect models, we quantified the relative influence of environmental conditions and farm management factors. Key variables were area of production and the method of fertilizer application. GHG footprints decreased with increasing area of production to a threshold of 17.4 ha. Farms using single fertilizer application methods in general had a larger GHG footprint than those using a combination of methods. We conclude that farm management factors should be prioritized for future data collection, and more stringent guidance on acceptable practices is required if greater comparability of outcomes is needed either within a scheme, such as the Unilever's sustainable agriculture code, or between schemes.