Genetic and epigenetic intra-tumoral heterogeneity cooperate to shape the evolutionary course of cancer 1 . Chronic lymphocytic leukemia (CLL) is a highly informative model for cancer evolution as it undergoes substantial genetic diversification and evolution with therapy 2 , 3 . The CLL epigenome is also an important disease-defining feature 4 , 5 , and growing CLL populations diversify through stochastic DNA methylation (DNAme) changes – epimutations 6 . However, previous studies based on bulk DNAme sequencing could not answer whether epimutations affect CLL populations homogenously. To measure epimutation rate at single-cell resolution, we applied multiplexed single-cell reduced representation bisulfite sequencing (MscRRBS) to healthy donors B cell and CLL patient samples. We observed that the common clonal CLL origin results in consistently elevated epimutation rate, with low cell-to-cell epimutation rate variability. In contrast, variable epimutation rates across normal B cells reflect diverse evolutionary ages across the B cell differentiation trajectory, consistent with epimutations serving as a molecular clock. Heritable epimutation information allowed high-resolution lineage reconstruction with single-cell data, applicable directly to patient samples. CLL lineage tree shape revealed earlier branching and longer branch lengths than normal B cells, reflecting rapid drift after the initial malignant transformation and a greater proliferative history. MscRRBS integrated with single-cell transcriptomes and genotyping confirmed that genetic subclones map to distinct clades inferred solely based on epimutation information. Lastly, to examine potential lineage biases during therapy, we profiled serial samples during ibrutinib-associated lymphocytosis, and identified clades of cells preferentially expelled from the lymph node with therapy, marked by distinct transcriptional profiles. The single-cell integration of genetic, epigenetic and transcriptional information thus charts CLL’s lineage history and its evolution with therapy.

The DNA base modification N6-methyladenine (m6A) is involved in many pathways related to the survival of bacteria and their interactions with hosts. Nanopore sequencing offers a new, portable method to detect base modifications. Here, we show that a neural network can improve m6A detection at trained sequence contexts compared to previously published methods using deviations between measured and expected current values as each adenine travels through a pore. The model, implemented as the mCaller software package, can be extended to detect known or confirm suspected methyltransferase target motifs based on predictions of methylation at untrained contexts. We use PacBio, Oxford Nanopore, methylated DNA immunoprecipitation sequencing (MeDIP-seq), and whole-genome bisulfite sequencing data to generate and orthogonally validate methylomes for eight microbial reference species. These well-characterized microbial references can serve as controls in the development and evaluation of future methods for the identification of base modifications from single-molecule sequencing data.

The mission of NASA’s GeneLab database (https://genelab.nasa.gov/) is to collect, curate, and provide access to the genomic, transcriptomic, proteomic and metabolomic (so-called ‘omics’) data from biospecimens flown in space or exposed to simulated space stressors, maximizing their utilization. This large collection of data enables the exploration of molecular network responses to space environments using a systems biology approach. We review here the various components of the GeneLab platform, including the new data repository web interface, and the GeneLab Online Data Entry (GEODE) web portal, which will support the expansion of the database in the future to include companion non-omics assay data. We discuss our design for GEODE, particularly how it promotes investigators providing more accurate metadata, reducing the curation effort required of GeneLab staff. We also introduce here a new GeneLab Application Programming Interface (API) specifically designed to support tools for the visualization of processed omics data. We review the outreach efforts by GeneLab to utilize the spaceflight data in the repository to generate novel discoveries and develop new hypotheses, including spearheading data analysis working groups, and a high school student training program. All these efforts are aimed ultimately at supporting precision risk management for human space exploration.

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Solenodons are insectivores found only in Hispaniola and Cuba, with a Mesozoic divergence date versus extant mainland mammals. Solenodons are the oldest lineage of living eutherian mammal for which a mitogenome sequence has not been reported. We determined complete mitogenome sequences for six Hispaniolan solenodons (Solenodon paradoxus) using next-generation sequencing. The solenodon mitogenomes were 16,454-16,457 bp long and carried the expected repertoire of genes. A mitogenomic phylogeny confirmed the basal position of solenodons relative to shrews and moles, with solenodon mitogenomes estimated to have diverged from those of other mammals ca. 78 Mya. Control region sequences of solenodons from the northern (n = 3) and southern (n = 5) Dominican Republic grouped separately in a network, with F = 0.72 (p = 0.036) between north and south. This regional genetic divergence supports previous morphological and genetic reports recognizing northern (S. p. paradoxus) and southern (S. p. woodi) subspecies in need of separate conservation plans.