The human placenta methylome.

Tissue-specific DNA methylation is found at promoters, enhancers, and CpG islands but also over larger genomic regions. In most human tissues, the vast majority of the genome is highly methylated (>70%). Recently, sequencing of bisulfite-treated DNA (MethylC-seq) has revealed large partially methylated domains (PMDs) in some human cell lines. PMDs cover up to 40% of the genome and are associated with gene repression and inactive chromatin marks. However, to date, only cultured cells and cancers have shown evidence for PMDs. Here, we performed MethylC-seq in full-term human placenta and demonstrate it is the first known normal tissue showing clear evidence of PMDs. We found that PMDs cover 37% of the placental genome, are stable throughout gestation and between individuals, and can be observed with lower sensitivity in Illumina 450K Infinium data. RNA-seq analysis confirmed that genes in PMDs are repressed in placenta. Using a hidden Markov model to map placental PMDs genome-wide and compare them to PMDs in other cell lines, we found that genes within placental PMDs have tissue-specific functions. For regulatory regions, methylation levels in promoter CpG islands are actually higher for genes within placental PMDs, despite the lower overall methylation of surrounding regions. Similar to PMDs, polycomb-regulated regions are hypomethylated but smaller and distinct from PMDs, with some being hypermethylated in placenta compared with other tissues. These results suggest that PMDs are a developmentally dynamic feature of the methylome that are relevant for understanding both normal development and cancer and may be of use as epigenetic biomarkers.

Assemblathon 1: a competitive assessment of de novo short read assembly methods.

Low-cost short read sequencing technology has revolutionized genomics, though it is only just becoming practical for the high-quality de novo assembly of a novel large genome. We describe the Assemblathon 1 competition, which aimed to comprehensively assess the state of the art in de novo assembly methods when applied to current sequencing technologies. In a collaborative effort, teams were asked to assemble a simulated Illumina HiSeq data set of an unknown, simulated diploid genome. A total of 41 assemblies from 17 different groups were received. Novel haplotype aware assessments of coverage, contiguity, structure, base calling, and copy number were made. We establish that within this benchmark: (1) It is possible to assemble the genome to a high level of coverage and accuracy, and that (2) large differences exist between the assemblies, suggesting room for further improvements in current methods. The simulated benchmark, including the correct answer, the assemblies, and the code that was used to evaluate the assemblies is now public and freely available from http://www.assemblathon.org/.