Methylation of histone H3 lysine 4 (H3K4me), a mark associated with gene activation, is mediated by SET1 and the related mixed lineage leukemia (MLL) histone methyltransferases (HMTs) across species. Mammals contain seven H3K4 HMTs, Set1A, Set1B, and MLL1-MLL5. The activity of SET1 and MLL proteins relies on protein-protein interactions within large multisubunit complexes that include three core components: RbBP5, Ash2L, and WDR5. It remains unclear how the composition and specificity of these complexes varies between cell types and during development. Caenorhabditis elegans contains one SET1 protein, SET-2, one MLL-like protein, SET-16, and single homologs of RbBP5, Ash2L, and WDR5. Here we show that SET-2 is responsible for the majority of bulk H3K4 methylation at all developmental stages. However, SET-2 and absent, small, or homeotic discs 2 (ASH-2) are differentially required for tri-and dimethylation of H3K4 (H3K4me3 and -me2) in embryos and adult germ cells. In embryos, whereas efficient H3K4me3 requires both SET-2 and ASH-2, H3K4me2 relies mostly on ASH-2. In adult germ cells by contrast, SET-2 serves a major role whereas ASH-2 is dispensable for H3K4me3 and most H3K4me2. Loss of SET-2 results in progressive sterility over several generations, suggesting an important function in the maintenance of a functional germ line. This study demonstrates that individual subunits of SET1-related complexes can show tissue specificity and developmental regulation and establishes C. elegans as a model to study SET1-related complexes in a multicellular organism.chromatin | epigenetics | mortal germ line H istone H3 lysine 4 (H3K4) methylation and the proteins involved in its implementation are evolutionarily conserved marks of active and potentially active genes in all eukaryotes examined (1, 2). In yeast, Set1 is found in a multiprotein complex known as COMPASS, which is solely responsible for all histone H3K4 methylation (3-5). In mammalian cells, seven family members have been characterized: SET1a and SET1b (orthologs of yeast Set1) (6) and five mixed lineage leukemia (MLL) family members, MLL1-5, that share only limited similarity with yeast Set1 beyond the SET domain (7-11). Human SET1a/SET1b mediate the bulk of H3K4 trimethylation (H3K4me3) in mammalian cell extracts (12). Members of the MLL family of proteins do not appear to contribute significantly to bulk changes in H3K4 methylation, but serve both unique and overlapping tissue-and developmental stage-specific functions. Loss of either MLL1 or MLL2 results in embryonic lethality in mice (13, 14), whereas MLL3, -4, and -5 gene knockout mice are viable but have distinct developmental defects (15-18). Caenorhabditis elegans contains one SET1 protein, SET-2, and one MLL-like protein, 20). Whereas both SET-2 and SET-16 are required for global H3K4 methylation, SET-2 plays a predominant role (19-21).The enzymatic activity of SET1/MLL family members is regulated by interactions with a number of other proteins, including Swd3/WDR5, Swd1/RbBP5, Bre2/Ash2, and Sdc1/hDPY...

Multiple signaling pathways ultimately modulate the epigenetic information embedded in the chromatin of gene promoters by recruiting epigenetic enzymes. We found that, in estrogen-regulated gene programming, the acetyltransferase CREB-binding protein (CBP) is specifically and exclusively methylated by the coactivatorassociated arginine methyltransferase (CARM1) in vivo. CARM1-dependent CBP methylation and p160 coactivators were required for estrogen-induced recruitment to chromatin targets. Notably, methylation increased the histone acetyltransferase (HAT) activity of CBP and stimulated its autoacetylation. Comparative genome-wide chromatin immunoprecipitation sequencing (ChIP-seq) studies revealed a variety of patterns by which p160, CBP, and methyl-CBP (meCBP) are recruited (or not) by estrogen to chromatin targets. Moreover, significant target gene-specific variation in the recruitment of (1) the p160 RAC3 protein, (2) the fraction of a given meCBP species within the total CBP, and (3) the relative recruitment of different meCBP species suggests the existence of a target gene-specific ''fingerprint'' for coregulator recruitment. Crossing ChIP-seq and transcriptomics profiles revealed the existence of meCBP ''hubs'' within the network of estrogen-regulated genes. Together, our data provide evidence for an unprecedented mechanism by which CARM1-dependent CBP methylation results in geneselective association of estrogen-recruited meCBP species with different HAT activities and specifies distinct target gene hubs, thus diversifying estrogen receptor programming.

Several studies have investigated RNA-DNA differences (RDD), presumably due to RNA editing, with conflicting results. We report a rigorous analysis of RDD in exonic regions in mice, taking into account critical biases in RNA-Seq analysis. Using deepsequenced F1 reciprocal inbred mice, we mapped 40 million RNA-Seq reads per liver sample and 180 million reads per adipose sample. We found 7300 apparent hepatic RDDs using a multiple-site mapping procedure, compared with 293 RDD found using a unique-site mapping procedure. After filtering for repeat sequence, splice junction proximity, undirectional strand, and extremity read bias, 63 RDD remained. In adipose tissue unique-site mapping identified 1667 RDD, and after applying the same four filters, 188 RDDs remained. In both tissues, the filtering procedure increased the proportion of canonical (A-to-I and C-to-U) editing events. The genomic DNA of 12 RDD sites among the potential 63 hepatic RDD was tested by Sanger sequencing, three of which proved to be due to unreferenced SNPs. We validated seven liver RDD with Sequenom technology, including two noncanonical, Gm5424 C-to-I(G) and Pisd I(G)-to-A RDD. Differences in diet, sex, or genetic background had very modest effects on RDD occurrence. Only a small number of apparent RDD sites overlapped between liver and adipose, indicating a high degree of tissue specificity. Our findings underscore the importance of properly filtering for bias in RNA-Seq investigations, including the necessity of confirming the DNA sequence to eliminate unreferenced SNPs. Based on our results, we conclude that RNA editing is likely limited to hundreds of events in exonic RNA in liver and adipose.S EVERAL recent studies have investigated genome-wide RNA editing using deep sequencing of transcriptomes by RNA-Seq on human transformed cells, cancer cell lines (Ju et al. 2011;Li et al. 2011;Bahn et al. 2012;Peng et al. 2012;Ramaswami et al. 2012), or tissues of inbred mouse strains (Danecek et al. 2012;Gu et al. 2012). Total reported RNA-DNA differences (RDD) sites have varied from hundreds to thousands. Over the same period, technical issues, such as mapping of reads in paralogous or repetitive sequence regions, mapping errors at splice sites, and systematic sequencing errors that could produce a large number of false-positive RDDs have been described (Kleinman and Majewski 2012;Pickrell et al. 2012). Another reported source of RDD error is undetected genomic DNA SNPs, arising from insufficient coverage of current DNA sequencing data (Schrider et al. 2011).We have examined genome-wide exonic RDD by using RNA-Seq data obtained from two tissues, liver and adipose, in F1 reciprocal crosses from two inbred strains of mice, DBA/2J (D2) and C57BL/6J (B6). These inbred mouse strains have been subjected to deep genomic sequencing and SNP analyses, with a higher coverage for B6 than for D2. A major aim was to estimate the impact of the major technical issues (paralog mapping, mismapping near splice sites and repeat sequences, and systematic seque...