We describe the draft genome of the microcrustacean Daphnia pulex, which is only 200 Mb and contains at least 30,907 genes. The high gene count is a consequence of an elevated rate of gene duplication resulting in tandem gene clusters. More than 1/3 of Daphnia’s genes have no detectable homologs in any other available proteome, and the most amplified gene families are specific to the Daphnia lineage. The co-expansion of gene families interacting within metabolic pathways suggests that the maintenance of duplicated genes is not random, and the analysis of gene expression under different environmental conditions reveals that numerous paralogs acquire divergent expression patterns soon after duplication. Daphnia-specific genes – including many additional loci within sequenced regions that are otherwise devoid of annotations – are the most responsive genes to ecological challenges.

T-cell acute lymphoblastic leukemia (T-ALL) is an immature hematopoietic malignancy driven mainly by oncogenic activation of NOTCH1 signaling1. In this study we report the presence of loss-of-function mutations and deletions of EZH2 and SUZ12 genes, encoding critical components of the Polycomb Repressive Complex 2 (PRC2) complex2,3, in 25% of T-ALLs. To further study the role of the PRC2 complex in T-ALL, we used NOTCH1-induced animal models of the disease, as well as human T-ALL samples, and combined locus-specific and global analysis of NOTCH1-driven epigenetic changes. These studies demonstrated that activation of NOTCH1 specifically induces loss of the repressive mark lysine-27 tri-methylation of histone 3 (H3K27me3)4 by antagonizing the activity of the Polycomb Repressive Complex 2 (PRC2) complex. These studies demonstrate a tumor suppressor role for the PRC2 complex in human leukemia and suggest a hitherto unrecognized dynamic interplay between oncogenic NOTCH1 and PRC2 function for the regulation of gene expression and cell transformation.

Relapsed childhood acute lymphoblastic leukemia (ALL) carries a poor prognosis despite intensive retreatment, due to intrinsic drug resistance1-2. The biological pathways that mediate resistance are unknown. Here we report the transcriptome profiles of matched diagnosis and relapse bone marrow specimens from ten pediatric B lymphoblastic leukemia patients using RNA-sequencing. Transcriptome sequencing identified 20 newly acquired novel non-synonymous mutations not present at initial diagnosis, of which two patients harbored relapse specific mutations in the same gene, NT5C2, a 5′-nucleotidase. Full exon sequencing of NT5C2 was completed in 61 additional relapse specimens, identifying five additional cases. Enzymatic analysis of mutant proteins revealed that base substitutions conferred increased enzymatic activity and resistance to treatment with nucleoside analogue therapies. Clinically, all patients who harbored NT5C2 mutations relapsed early, or within 36 months of initial diagnosis (p=0.03). These results suggest that mutations in NT5C2 are associated with the outgrowth of drug resistant clones in ALL.

We describe design, rapid assembly, and characterization of synthetic yeast Sc2.0 chromosome VI (synVI). A mitochondrial defect in the synVI strain mapped to synonymous coding changes within (), encoding an essential proteasome subunit; Sc2.0 coding changes reduced Pre4 protein accumulation by half. Completing Sc2.0 specifies consolidation of 16 synthetic chromosomes into a single strain. We investigated phenotypic, transcriptional, and proteomewide consequences of Sc2.0 chromosome consolidation in poly-synthetic strains. Another "bug" was discovered through proteomic analysis, associated with alteration of the transcription start due to transfer RNA deletion and loxPsym site insertion. Despite extensive genetic alterations across 6% of the genome, no major global changes were detected in the poly-synthetic strain "omics" analyses. This work sets the stage for completion of a designer, synthetic eukaryotic genome.

Improvements in mass spectrometry (MS)-based peptide sequencing provide a new opportunity to determine whether polymorphisms, mutations, and splice variants identified in cancer cells are translated. Herein, we apply a proteogenomic data integration tool (QUILTS) to illustrate protein variant discovery using whole genome, whole transcriptome, and global proteome datasets generated from a pair of luminal and basal-like breast-cancer-patient-derived xenografts (PDX). The sensitivity of proteogenomic analysis for singe nucleotide variant (SNV) expression and novel splice junction (NSJ) detection was probed using multiple MS/MS sample process replicates defined here as an independent tandem MS experiment using identical sample material. Despite analysis of over 30 sample process replicates, only about 10% of SNVs (somatic and germline) detected by both DNA and RNA sequencing were observed as peptides. An even smaller proportion of peptides corresponding to NSJ observed by RNA sequencing were detected (<0.1%). Peptides mapping to DNA-detected SNVs without a detectable mRNA transcript were also observed, suggesting that transcriptome coverage was incomplete (ϳ80%). In contrast to germline variants, somatic variants were less likely to be detected at the peptide level in the basal-like tumor than in the luminal tumor, raising the possibility of differential translation or protein degradation effects. In conclusion, this large-scale proteogenomic integration allowed us to determine the degree to which mutations are translated and identify gaps in sequence coverage, thereby benchmarking current technology and progress toward whole cancer proteome and transcriptome analysis. Massively parallel sequencing (MPS)1 of cancer genomes has demonstrated enormous complexity, and it is often unclear which somatic mutations drive tumor biology and which are nonfunctional passenger mutations that passively accumulate. RNA sequencing is frequently used to determine which nucleotide variants are transcribed and therefore have the potential for biological function. However, many mutations detected at the DNA level are not observed at the mRNA level, and their observation is dependent upon expression of the stability of the mRNA (1). Mutation detection at the peptide level clearly increases the confidence that any given variant is