Models of Somatic Hypermutation Targeting and Substitution Based on Synonymous Mutations from High-Throughput Immunoglobulin Sequencing Data

Analyses of somatic hypermutation (SHM) patterns in B cell immunoglobulin (Ig) sequences contribute to our basic understanding of adaptive immunity, and have broad applications not only for understanding the immune response to pathogens, but also to determining the role of SHM in autoimmunity and B cell cancers. Although stochastic, SHM displays intrinsic biases that can confound statistical analysis, especially when combined with the particular codon usage and base composition in Ig sequences. Analysis of B cell clonal expansion, diversification, and selection processes thus critically depends on an accurate background model for SHM micro-sequence targeting (i.e., hot/cold-spots) and nucleotide substitution. Existing models are based on small numbers of sequences/mutations, in part because they depend on data from non-coding regions or non-functional sequences to remove the confounding influences of selection. Here, we combine high-throughput Ig sequencing with new computational analysis methods to produce improved models of SHM targeting and substitution that are based only on synonymous mutations, and are thus independent of selection. The resulting “S5F” models are based on 806,860 Synonymous mutations in 5-mer motifs from 1,145,182 Functional sequences and account for dependencies on the adjacent four nucleotides (two bases upstream and downstream of the mutation). The estimated profiles can explain almost half of the variance in observed mutation patterns, and clearly show that both mutation targeting and substitution are significantly influenced by neighboring bases. While mutability and substitution profiles were highly conserved across individuals, the variability across motifs was found to be much larger than previously estimated. The model and method source code are made available at http://clip.med.yale.edu/SH

Developmental Bias in Cleavage-Stage Mouse Blastomeres

BACKGROUND: The cleavage-stage mouse embryo is composed of superficially equivalent blastomeres that will generate both the embryonic inner cell mass (ICM) and the supportive trophectoderm (TE). However, it remains unsettled whether the contribution of each blastomere to these two lineages can be accounted for by chance. Addressing the question of blastomere cell fate may be of practical importance, because preimplantation genetic diagnosis requires removal of blastomeres from the early human embryo. To determine whether blastomere allocation to the two earliest lineages is random, we developed and utilized a recombination-mediated, noninvasive combinatorial fluorescent labeling method for embryonic lineage tracing. RESULTS: When we induced recombination at cleavage stages, we observed a statistically significant bias in the contribution of the resulting labeled clones to the trophectoderm or the inner cell mass in a subset of embryos. Surprisingly, we did not find a correlation between localization of clones in the embryonic and abembryonic hemispheres of the late blastocyst and their allocation to the TE and ICM, suggesting that TE-ICM bias arises separately from embryonic-abembryonic bias. Rainbow lineage tracing also allowed us to demonstrate that the bias observed in the blastocyst persists into postimplantation stages and therefore has relevance for subsequent development. CONCLUSIONS: The Rainbow transgenic mice that we describe here have allowed us to detect lineage-dependent bias in early development. They should also enable assessment of the developmental equivalence of mammalian progenitor cells in a variety of tissues.Molecular and Cellular Biolog

The Massive Hosts of Radio Galaxies Across Cosmic Time

We present the results of a comprehensive Spitzer survey of 69 radio galaxies across 1<z<5.2. Using IRAC (3.6-8.0um), IRS (16um) and MIPS (24-160um) imaging, we decompose the rest-frame optical to infrared spectral energy distributions into stellar, AGN, and dust components and determine the contribution of host galaxy stellar emission at rest-frame H-band. Stellar masses derived from rest-frame near-IR data, where AGN and young star contributions are minimized, are significantly more reliable than those derived from rest-frame optical and UV data. We find that the fraction of emitted light at rest-frame H-band from stars is >60% for ~75% the high redshift radio galaxies. As expected from unified models of AGN, the stellar fraction of the rest-frame H-band luminosity has no correlation with redshift, radio luminosity, or rest-frame mid-IR (5um) luminosity. Additionally, while the stellar H-band luminosity does not vary with stellar fraction, the total H-band luminosity anti-correlates with the stellar fraction as would be expected if the underlying hosts of these radio galaxies comprise a homogeneous population. The resultant stellar luminosities imply stellar masses of 10^{11-11.5}Msun even at the highest redshifts. Powerful radio galaxies tend to lie in a similar region of mid-IR color-color space as unobscured AGN, despite the stellar contribution to their mid-IR SEDs at shorter-wavelengths. The mid-IR luminosities alone classify most HzRGs as LIRGs or ULIRGs with even higher total-IR luminosities. As expected, these exceptionally high mid-IR luminosities are consistent with an obscured, highly-accreting AGN. We find a weak correlation of stellar mass with radio luminosity.Comment: 63 pages, 14 figures, accepted for publication in ApJ

Genes as Tags: The Tax Implications of Widely Available Genetic Information

This paper examines how progress in genetics\u27 specifically, the proliferation of knowledge about the human genome\u27 may influence the feasibility and desirability of a tax that is based on individual human endowments or ability. The paper explores various forms that such a genetic endowment tax-and-transfer regime might take and identifies some of the benefits and costs of such a regime. The authors take no position on whether a genetic endowment tax would be desirable or not. However, one contribution of the paper is to observe that current law in the U.S., which restricts the use of genetic information by insurers and employers, is equivalent to a form of genetic endowment tax. The paper also notes that, in the absence of a government-mandated transfer policy with respect to genetic endowments, private insurance markets may arise to fill the gap, allowing individuals to purchase insurance against the possibility of a bad genetic draw

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Circulating microparticles: square the circle

Background: The present review summarizes current knowledge about microparticles (MPs) and provides a systematic overview of last 20 years of research on circulating MPs, with particular focus on their clinical relevance. Results: MPs are a heterogeneous population of cell-derived vesicles, with sizes ranging between 50 and 1000 nm. MPs are capable of transferring peptides, proteins, lipid components, microRNA, mRNA, and DNA from one cell to another without direct cell-to-cell contact. Growing evidence suggests that MPs present in peripheral blood and body fluids contribute to the development and progression of cancer, and are of pathophysiological relevance for autoimmune, inflammatory, infectious, cardiovascular, hematological, and other diseases. MPs have large diagnostic potential as biomarkers; however, due to current technological limitations in purification of MPs and an absence of standardized methods of MP detection, challenges remain in validating the potential of MPs as a non-invasive and early diagnostic platform. Conclusions: Improvements in the effective deciphering of MP molecular signatures will be critical not only for diagnostics, but also for the evaluation of treatment regimens and predicting disease outcomes