La ionosfera: comunicare... naturalmente!

La ionosfera è la parte della media-alta atmosfera compresa tra i 60 e i 1000 km di quota. Essa è caratterizzata da una concentrazione di elettroni tale da modificare la propagazione delle onde radio che la attraversano

Transcriptome dynamics of CD4⁺ T cells during malaria maps gradual transit from effector to memory

The dynamics of CD4⁺ T cell memory development remain to be examined at genome scale. In malaria-endemic regions, antimalarial chemoprevention protects long after its cessation and associates with effects on CD4⁺ T cells. We applied single-cell RNA sequencing and computational modelling to track memory development during Plasmodium infection and treatment. In the absence of central memory precursors, two trajectories developed as T helper 1 (T_H1) and follicular helper T (T_(FH)) transcriptomes contracted and partially coalesced over three weeks. Progeny of single clones populated T_H1 and T_(FH) trajectories, and fate-mapping suggested that there was minimal lineage plasticity. Relationships between T_(FH) and central memory were revealed, with antimalarials modulating these responses and boosting T_H1 recall. Finally, single-cell epigenomics confirmed that heterogeneity among effectors was partially reset in memory. Thus, the effector-to-memory transition in CD4⁺ T cells is gradual during malaria and is modulated by antiparasitic drugs. Graphical user interfaces are presented for examining gene-expression dynamics and gene–gene correlations (http://haquelab.mdhs.unimelb.edu.au/cd4_memory/)

DNA methylation patterns identify subgroups of pancreatic neuroendocrine tumors with clinical association

Here we report the DNA methylation profile of 84 sporadic pancreatic neuroendocrine tumors (PanNETs) with associated clinical and genomic information. We identified three subgroups of PanNETs, termed T1, T2 and T3, with distinct patterns of methylation. The T1 subgroup was enriched for functional tumors and ATRX, DAXX and MEN1 wild-type genotypes. The T2 subgroup contained tumors with mutations in ATRX, DAXX and MEN1 and recurrent patterns of chromosomal losses in half of the genome with no association between regions with recurrent loss and methylation levels. T2 tumors were larger and had lower methylation in the MGMT gene body, which showed positive correlation with gene expression. The T3 subgroup harboured mutations in MEN1 with recurrent loss of chromosome 11, was enriched for grade G1 tumors and showed histological parameters associated with better prognosis. Our results suggest a role for methylation in both driving tumorigenesis and potentially stratifying prognosis in PanNETs

Transcriptome dynamics of CD4⁺ T cells during malaria maps gradual transit from effector to memory

The dynamics of CD4⁺ T cell memory development remain to be examined at genome scale. In malaria-endemic regions, antimalarial chemoprevention protects long after its cessation and associates with effects on CD4⁺ T cells. We applied single-cell RNA sequencing and computational modelling to track memory development during Plasmodium infection and treatment. In the absence of central memory precursors, two trajectories developed as T helper 1 (T_H1) and follicular helper T (T_(FH)) transcriptomes contracted and partially coalesced over three weeks. Progeny of single clones populated T_H1 and T_(FH) trajectories, and fate-mapping suggested that there was minimal lineage plasticity. Relationships between T_(FH) and central memory were revealed, with antimalarials modulating these responses and boosting T_H1 recall. Finally, single-cell epigenomics confirmed that heterogeneity among effectors was partially reset in memory. Thus, the effector-to-memory transition in CD4⁺ T cells is gradual during malaria and is modulated by antiparasitic drugs. Graphical user interfaces are presented for examining gene-expression dynamics and gene–gene correlations (http://haquelab.mdhs.unimelb.edu.au/cd4_memory/)

Non-coding RNAs underlie genetic predisposition to breast cancer

Funder: National Breast Cancer Foundation; doi: http://dx.doi.org/10.13039/501100001026Abstract: Background: Genetic variants identified through genome-wide association studies (GWAS) are predominantly non-coding and typically attributed to altered regulatory elements such as enhancers and promoters. However, the contribution of non-coding RNAs to complex traits is not clear. Results: Using targeted RNA sequencing, we systematically annotated multi-exonic non-coding RNA (mencRNA) genes transcribed from 1.5-Mb intervals surrounding 139 breast cancer GWAS signals and assessed their contribution to breast cancer risk. We identify more than 4000 mencRNA genes and show their expression distinguishes normal breast tissue from tumors and different breast cancer subtypes. Importantly, breast cancer risk variants, identified through genetic fine-mapping, are significantly enriched in mencRNA exons, but not the promoters or introns. eQTL analyses identify mencRNAs whose expression is associated with risk variants. Furthermore, chromatin interaction data identify hundreds of mencRNA promoters that loop to regions that contain breast cancer risk variants. Conclusions: We have compiled the largest catalog of breast cancer-associated mencRNAs to date and provide evidence that modulation of mencRNAs by GWAS variants may provide an alternative mechanism underlying complex traits

Whole-genome sequencing of acral melanoma reveals genomic complexity and diversity

To increase understanding of the genomic landscape of acral melanoma, a rare form of melanoma occurring on palms, soles or nail beds, whole genome sequencing of 87 tumors with matching transcriptome sequencing for 63 tumors was performed. Here we report that mutational signature analysis reveals a subset of tumors, mostly subungual, with an ultraviolet radiation signature. Significantly mutated genes are BRAF, NRAS, NF1, NOTCH2, PTEN and TYRP1. Mutations and amplification of KIT are also common. Structural rearrangement and copy number signatures show that whole genome duplication, aneuploidy and complex rearrangements are common. Complex rearrangements occur recurrently and are associated with amplification of TERT, CDK4, MDM2, CCND1, PAK1 and GAB2, indicating potential therapeutic options.This work was supported by a National Health and Medical Research Council of Australia (NHMRC) Program Grant (1093017, G.J.M., R.A.S., N.H., G.V.L., J.F.T.), an NHMRC project grant (APP1123217) and NHMRC Fellowship grants (R.A.S., N.K.H. - APP1139071, G.VL.). G.V.L is supported by an NHMRC Practitioner Fellowship and the University of Sydney Medical Foundation. R.A.S is supported by an NHMRC Practitioner Fellowship. J.S.W. is supported by a NHMRC early career fellowship (1111678). N.W. is supported by an NHMRC Senior Research Fellowship (1139071). N.K.H. is supported by an NHMRC Senior Principal Research Fellowship (1117663). P.M.F. was supported by the Deborah and John McMurtrie MIA Pathology Fellowship. T.J.D. was supported by the Jani Haenke Melanoma Pathology Fellowship. Support from Melanoma Institute Australia, the Royal Prince Alfred Hospital and New South Wales Health Pathology is also gratefully acknowledged

Whole genome landscapes of uveal melanoma show an ultraviolet radiation signature in iris tumours

Uveal melanoma (UM) is the most common intraocular tumour in adults and despite surgical or radiation treatment of primary tumours, ~50% of patients progress to metastatic disease. Therapeutic options for metastatic UM are limited, with clinical trials having little impact. Here we perform whole-genome sequencing (WGS) of 103 UM from all sites of the uveal tract (choroid, ciliary body, iris). While most UM have low tumour mutation burden (TMB), two subsets with high TMB are seen; one driven by germline MBD4 mutation, and another by ultraviolet radiation (UVR) exposure, which is restricted to iris UM. All but one tumour have a known UM driver gene mutation (GNAQ, GNA11, BAP1, PLCB4, CYSLTR2, SF3B1, EIF1AX). We identify three other significantly mutated genes (TP53, RPL5 and CENPE).This project was funded by the National Health and Medical Research Council (NHMRC; 1093017), the Walking On Sunshine Foundation, Anne Stanton, Nicola Laws and Lloyd Owen in Memorial and Civic Solutions. This study was also funded by Fight for Sight, Denmark. A.L.P. is supported by Highland Island Enterprise (HMS9353763). This work was supported by an NHMRC Program Grant (G.V.L., G.J.M., R.A.S. and N.K.H.). G.V.L. is supported by an NHMRC Practitioner Fellowship and The University of Sydney, Medical Foundation. R.A.S. is supported by an NHMRC Practitioner Fellowship. Support from Melanoma Institute Australia and The Ainsworth Foundation is also gratefully acknowledged. J.S.W. is supported by a NHMRC early career fellowship (1111678). N.W. is supported by an NHMRC Senior Research Fellowship (1139071). N.K.H. is supported by an NHMRC Senior Principal Research Fellowship (1117663)

DNA methylation patterns identify subgroups of pancreatic neuroendocrine tumors with clinical association

Here we report the DNA methylation profile of 84 sporadic pancreatic neuroendocrine tumors (PanNETs) with associated clinical and genomic information. We identified three subgroups of PanNETs, termed T1, T2 and T3, with distinct patterns of methylation. The T1 subgroup was enriched for functional tumors and ATRX, DAXX and MEN1 wild-type genotypes. The T2 subgroup contained tumors with mutations in ATRX, DAXX and MEN1 and recurrent patterns of chromosomal losses in half of the genome with no association between regions with recurrent loss and methylation levels. T2 tumors were larger and had lower methylation in the MGMT gene body, which showed positive correlation with gene expression. The T3 subgroup harboured mutations in MEN1 with recurrent loss of chromosome 11, was enriched for grade G1 tumors and showed histological parameters associated with better prognosis. Our results suggest a role for methylation in both driving tumorigenesis and potentially stratifying prognosis in PanNETs

Variance explained by whole genome sequence variants in coding and regulatory genome annotations for six dairy traits

There are an exceedingly large number of sequence variants discovered through whole genome sequencing in most populations, including cattle. Deciphering which of these affect complex traits is a major challenge. In this study we hypothesize that variants in some functional classes, such as splice site regions, coding regions, DNA methylated regions and long noncoding RNA will explain more variance in complex traits than others. Two variance component approaches were used to test this hypothesis - the first determines if variants in a functional class capture a greater proportion of the variance, than expected by chance, the second uses the proportion of variance explained when variants in all annotations are fitted simultaneously.Our data set consisted of 28.3 million imputed whole genome sequence variants in 16,581 dairy cattle with records for 6 complex trait phenotypes, including production and fertility. We found that sequence variants in splice site regions and synonymous classes captured the greatest proportion of the variance, explaining up to 50% of the variance across all traits. We also found sequence variants in target sites for DNA methylation (genomic regions that are found be highly methylated in bovine placentas), captured a significant proportion of the variance. Per sequence variant, splice site variants explain the highest proportion of variance in this study. The proportion of variance captured by the missense predicted deleterious (from SIFT) and missense tolerated classes was relatively small.The results demonstrate using functional annotations to filter whole genome sequence variants into more informative subsets could be useful for prioritization of the variants that are more likely to be associated with complex traits. In addition to variants found in splice sites and protein coding genes regulatory variants and those found in DNA methylated regions, explained considerable variation in milk production and fertility traits. In our analysis synonymous variants captured a significant proportion of the variance, which raises the possible explanation that synonymous mutations might have some effects, or more likely that these variants are miss-annotated, or alternatively the results reflect imperfect imputation of the actual causative variants

Validated lncRNA from blood stranded RNA-Seq that overlap with class 3 un-stranded lncRNA.

<p>Validated lncRNA from blood stranded RNA-Seq that overlap with class 3 un-stranded lncRNA.</p