Comparative genomics of the closely related fungal genera Cryptococcus and Kwoniella reveals karyotype dynamics and suggests evolutionary mechanisms of pathogenesis.

In exploring the evolutionary trajectories of both pathogenesis and karyotype dynamics in fungi, we conducted a large-scale comparative genomic analysis spanning the Cryptococcus genus, encompassing both global human fungal pathogens and nonpathogenic species, and related species from the sister genus Kwoniella. Chromosome-level genome assemblies were generated for multiple species, covering virtually all known diversity within these genera. Although Cryptococcus and Kwoniella have comparable genome sizes (about 19.2 and 22.9 Mb) and similar gene content, hinting at preadaptive pathogenic potential, our analysis found evidence of gene gain (via horizontal gene transfer) and gene loss in pathogenic Cryptococcus species, which might represent evolutionary signatures of pathogenic development. Genome analysis also revealed a significant variation in chromosome number and structure between the 2 genera. By combining synteny analysis and experimental centromere validation, we found that most Cryptococcus species have 14 chromosomes, whereas most Kwoniella species have fewer (11, 8, 5, or even as few as 3). Reduced chromosome number in Kwoniella is associated with formation of giant chromosomes (up to 18 Mb) through repeated chromosome fusion events, each marked by a pericentric inversion and centromere loss. While similar chromosome inversion-fusion patterns were observed in all Kwoniella species with fewer than 14 chromosomes, no such pattern was detected in Cryptococcus. Instead, Cryptococcus species with less than 14 chromosomes showed reductions primarily through rearrangements associated with the loss of repeat-rich centromeres. Additionally, Cryptococcus genomes exhibited frequent interchromosomal translocations, including intercentromeric recombination facilitated by transposons shared between centromeres. Overall, our findings advance our understanding of genetic changes possibly associated with pathogenicity in Cryptococcus and provide a foundation to elucidate mechanisms of centromere loss and chromosome fusion driving distinct karyotypes in closely related fungal species, including prominent global human pathogens.

Distinct Escherichia coli transcriptional profiles in the guts of recurrent UTI sufferers revealed by pangenome hybrid selection.

Low-abundance members of microbial communities are difficult to study in their native habitats. This includes Escherichia coli, a minor, but common inhabitant of the gastrointestinal tract and opportunistic pathogen, including of the urinary tract, where it is the primary pathogen. While multi-omic analyses have detailed critical interactions between uropathogenic Escherichia coli (UPEC) and the bladder that mediate UTI outcome, comparatively little is known about UPEC in its pre-infection reservoir, partly due to its low abundance there (<1% relative abundance). To accurately and sensitively explore the genomes and transcriptomes of diverse E. coli in gastrointestinal communities, we developed E. coli PanSelect which uses a set of probes designed to specifically recognize and capture E. coli's broad pangenome from sequencing libraries. We demonstrated the ability of E. coli PanSelect to enrich, by orders of magnitude, sequencing data from diverse E. coli using a mock community and a set of human stool samples collected as part of a cohort study investigating drivers of recurrent urinary tract infections (rUTI). Comparisons of genomes and transcriptomes between E. coli residing in the gastrointestinal tracts of women with and without a history of rUTI suggest that rUTI gut E. coli are responding to increased levels of oxygen and nitrate, suggestive of mucosal inflammation, which may have implications for recurrent disease. E. coli PanSelect is well suited for investigations of native in vivo biology of E. coli in other environments where it is at low relative abundance, and the framework described here has broad applicability to other highly diverse, low abundance organisms.

Comparative genomics of Cryptococcus and Kwoniella reveals pathogenesis evolution and contrasting karyotype dynamics via intercentromeric recombination or chromosome fusion.

A large-scale comparative genomic analysis was conducted for the global human fungal pathogens within the Cryptococcus genus, compared to non-pathogenic Cryptococcus species, and related species from the sister genus Kwoniella. Chromosome-level genome assemblies were generated for multiple species of both genera, resulting in a dataset encompassing virtually all of their known diversity. Although Cryptococcus and Kwoniella have comparable genome sizes (about 19.2 and 22.9 Mb) and similar gene content, hinting at pre-adaptive pathogenic potential, our analysis found evidence in pathogenic Cryptococcus species of specific examples of gene gain (via horizontal gene transfer) and gene loss, which might represent evolutionary signatures of pathogenic development. Genome analysis also revealed a significant variation in chromosome number and structure between the two genera. By combining synteny analysis and experimental centromere validation, we found that most Cryptococcus species have 14 chromosomes, whereas most Kwoniella species have fewer (11, 8, 5 or even as few as 3). Reduced chromosome number in Kwoniella is associated with formation of giant chromosomes (up to 18 Mb) through repeated chromosome fusion events, each marked by a pericentric inversion and centromere loss. While similar chromosome inversion-fusion patterns were observed in all Kwoniella species with fewer than 14 chromosomes, no such pattern was detected in Cryptococcus. Instead, Cryptococcus species with less than 14 chromosomes, underwent chromosome reductions primarily through rearrangements associated with the loss of repeat-rich centromeres. Additionally, Cryptococcus genomes exhibited frequent interchromosomal translocations, including intercentromeric recombination facilitated by transposons shared between centromeres. Taken together, our findings advance our understanding of genomic changes possibly associated with pathogenicity in Cryptococcus and provide a foundation to elucidate mechanisms of centromere loss and chromosome fusion driving distinct karyotypes in closely related fungal species, including prominent global human pathogens.

A rapid, low-cost, and highly sensitive SARS-CoV-2 diagnostic based on whole-genome sequencing.

Early detection of SARS-CoV-2 infection is key to managing the current global pandemic, as evidence shows the virus is most contagious on or before symptom onset. Here, we introduce a low-cost, high-throughput method for diagnosing and studying SARS-CoV-2 infection. Dubbed Pathogen-Oriented Low-Cost Assembly & Re-Sequencing (POLAR), this method amplifies the entirety of the SARS-CoV-2 genome. This contrasts with typical RT-PCR-based diagnostic tests, which amplify only a few loci. To achieve this goal, we combine a SARS-CoV-2 enrichment method developed by the ARTIC Network (https://artic.network/) with short-read DNA sequencing and de novo genome assembly. Using this method, we can reliably (>95% accuracy) detect SARS-CoV-2 at a concentration of 84 genome equivalents per milliliter (GE/mL). The vast majority of diagnostic methods meeting our analytical criteria that are currently authorized for use by the United States Food and Drug Administration with the Coronavirus Disease 2019 (COVID-19) Emergency Use Authorization require higher concentrations of the virus to achieve this degree of sensitivity and specificity. In addition, we can reliably assemble the SARS-CoV-2 genome in the sample, often with no gaps and perfect accuracy given sufficient viral load. The genotypic data in these genome assemblies enable the more effective analysis of disease spread than is possible with an ordinary binary diagnostic. These data can also help identify vaccine and drug targets. Finally, we show that the diagnoses obtained using POLAR of positive and negative clinical nasal mid-turbinate swab samples 100% match those obtained in a clinical diagnostic lab using the Center for Disease Control's 2019-Novel Coronavirus test. Using POLAR, a single person can manually process 192 samples over an 8-hour experiment at the cost of ~$36 per patient (as of December 7th, 2022), enabling a 24-hour turnaround with sequencing and data analysis time. We anticipate that further testing and refinement will allow greater sensitivity using this approach.

DNA hypomethylation silences anti-tumor immune genes in early prostate cancer and CTCs.

Cancer is characterized by hypomethylation-associated silencing of large chromatin domains, whose contribution to tumorigenesis is uncertain. Through high-resolution genome-wide single-cell DNA methylation sequencing, we identify 40 core domains that are uniformly hypomethylated from the earliest detectable stages of prostate malignancy through metastatic circulating tumor cells (CTCs). Nested among these repressive domains are smaller loci with preserved methylation that escape silencing and are enriched for cell proliferation genes. Transcriptionally silenced genes within the core hypomethylated domains are enriched for immune-related genes; prominent among these is a single gene cluster harboring all five CD1 genes that present lipid antigens to NKT cells and four IFI16-related interferon-inducible genes implicated in innate immunity. The re-expression of CD1 or IFI16 murine orthologs in immuno-competent mice abrogates tumorigenesis, accompanied by the activation of anti-tumor immunity. Thus, early epigenetic changes may shape tumorigenesis, targeting co-located genes within defined chromosomal loci. Hypomethylation domains are detectable in blood specimens enriched for CTCs.

Genome Sequence of Lichtheimia ornata, an Emerging Opportunistic Mucorales Pathogen.

Lichtheimia ornata is an emerging opportunistic Mucorales pathogen that is associated with fatal infections in immunocompromised individuals. While these environmentally acquired infections have rarely been reported to date, cases were noted in a recent analysis of coronavirus disease 2019 (COVID-19)-associated mucormycosis in India. Here, we report the annotated genome sequence of the environmental isolate CBS 291.66.

Activation of Notch and Myc Signaling via B-cell-Restricted Depletion of Dnmt3a Generates a Consistent Murine Model of Chronic Lymphocytic Leukemia.

Chronic lymphocytic leukemia (CLL) is characterized by disordered DNA methylation, suggesting these epigenetic changes might play a critical role in disease onset and progression. The methyltransferase DNMT3A is a key regulator of DNA methylation. Although DNMT3A somatic mutations in CLL are rare, we found that low DNMT3A expression is associated with more aggressive disease. A conditional knockout mouse model showed that homozygous depletion of Dnmt3a from B cells results in the development of CLL with 100% penetrance at a median age of onset of 5.3 months, and heterozygous Dnmt3a depletion yields a disease penetrance of 89% with a median onset at 18.5 months, confirming its role as a haploinsufficient tumor suppressor. B1a cells were confirmed as the cell of origin of disease in this model, and Dnmt3a depletion resulted in focal hypomethylation and activation of Notch and Myc signaling. Amplification of chromosome 15 containing the Myc gene was detected in all CLL mice tested, and infiltration of high-Myc-expressing CLL cells in the spleen was observed. Notably, hyperactivation of Notch and Myc signaling was exclusively observed in the Dnmt3a CLL mice, but not in three other CLL mouse models tested (Sf3b1-Atm, Ikzf3, and MDR), and Dnmt3a-depleted CLL were sensitive to pharmacologic inhibition of Notch signaling in vitro and in vivo. Consistent with these findings, human CLL samples with lower DNMT3A expression were more sensitive to Notch inhibition than those with higher DNMT3A expression. Altogether, these results suggest that Dnmt3a depletion induces CLL that is highly dependent on activation of Notch and Myc signaling. SIGNIFICANCE: Loss of DNMT3A expression is a driving event in CLL and is associated with aggressive disease, activation of Notch and Myc signaling, and enhanced sensitivity to Notch inhibition.

Smart-RRBS for single-cell methylome and transcriptome analysis.

The integration of DNA methylation and transcriptional state within single cells is of broad interest. Several single-cell dual- and multi-omics approaches have been reported that enable further investigation into cellular heterogeneity, including the discovery and in-depth study of rare cell populations. Such analyses will continue to provide important mechanistic insights into the regulatory consequences of epigenetic modifications. We recently reported a new method for profiling the DNA methylome and transcriptome from the same single cells in a cancer research study. Here, we present details of the protocol and provide guidance on its utility. Our Smart-RRBS (reduced representation bisulfite sequencing) protocol combines Smart-seq2 and RRBS and entails physically separating mRNA from the genomic DNA. It generates paired epigenetic promoter and RNA-expression measurements for ~24% of protein-coding genes in a typical single cell. It also works for micro-dissected tissue samples comprising hundreds of cells. The protocol, excluding flow sorting of cells and sequencing, takes ~3 d to process up to 192 samples manually. It requires basic molecular biology expertise and laboratory equipment, including a PCR workstation with UV sterilization, a DNA fluorometer and a microfluidic electrophoresis system.

Discovery of Candidate DNA Methylation Cancer Driver Genes.

Epigenetic alterations, such as promoter hypermethylation, may drive cancer through tumor suppressor gene inactivation. However, we have limited ability to differentiate driver DNA methylation (DNAme) changes from passenger events. We developed DNAme driver inference-MethSig-accounting for the varying stochastic hypermethylation rate across the genome and between samples. We applied MethSig to bisulfite sequencing data of chronic lymphocytic leukemia (CLL), multiple myeloma, ductal carcinoma in situ, glioblastoma, and to methylation array data across 18 tumor types in TCGA. MethSig resulted in well-calibrated quantile-quantile plots and reproducible inference of likely DNAme drivers with increased sensitivity/specificity compared with benchmarked methods. CRISPR/Cas9 knockout of selected candidate CLL DNAme drivers provided a fitness advantage with and without therapeutic intervention. Notably, DNAme driver risk score was closely associated with adverse outcome in independent CLL cohorts. Collectively, MethSig represents a novel inference framework for DNAme driver discovery to chart the role of aberrant DNAme in cancer. SIGNIFICANCE: MethSig provides a novel statistical framework for the analysis of DNA methylation changes in cancer, to specifically identify candidate DNA methylation driver genes of cancer progression and relapse, empowering the discovery of epigenetic mechanisms that enhance cancer cell fitness.This article is highlighted in the In This Issue feature, p. 2113.

Preneoplastic Alterations Define CLL DNA Methylome and Persist through Disease Progression and Therapy.

Most human cancers converge to a deregulated methylome with reduced global levels and elevated methylation at select CpG islands. To investigate the emergence and dynamics of the cancer methylome, we characterized genome-wide DNA methylation in pre-neoplastic monoclonal B cell lymphocytosis (MBL) and chronic lymphocytic leukemia (CLL), including serial samples collected across disease course. We detected the aberrant tumor-associated methylation landscape at CLL diagnosis and found no significantly differentially methylated regions in the high-count MBL-to-CLL transition. Patient methylomes showed remarkable stability with natural disease and post-therapy progression. Single CLL cells were consistently aberrantly methylated, indicating a homogeneous transition to the altered epigenetic state, and a distinct expression profile together with MBL cells compared to normal B cells. Our longitudinal analysis reveals the cancer methylome to emerge early, which may provide a platform for subsequent genetically-driven growth dynamics and together with its persistent presence suggests a central role in the normal-to-cancer transition.

Phylogenetic analysis of SARS-CoV-2 in Boston highlights the impact of superspreading events.

Analysis of 772 complete severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from early in the Boston-area epidemic revealed numerous introductions of the virus, a small number of which led to most cases. The data revealed two superspreading events. One, in a skilled nursing facility, led to rapid transmission and significant mortality in this vulnerable population but little broader spread, whereas other introductions into the facility had little effect. The second, at an international business conference, produced sustained community transmission and was exported, resulting in extensive regional, national, and international spread. The two events also differed substantially in the genetic variation they generated, suggesting varying transmission dynamics in superspreading events. Our results show how genomic epidemiology can help to understand the link between individual clusters and wider community spread.

Phylogenetic analysis of SARS-CoV-2 in the Boston area highlights the role of recurrent importation and superspreading events.

SARS-CoV-2 has caused a severe, ongoing outbreak of COVID-19 in Massachusetts with 111,070 confirmed cases and 8,433 deaths as of August 1, 2020. To investigate the introduction, spread, and epidemiology of COVID-19 in the Boston area, we sequenced and analyzed 772 complete SARS-CoV-2 genomes from the region, including nearly all confirmed cases within the first week of the epidemic and hundreds of cases from major outbreaks at a conference, a nursing facility, and among homeless shelter guests and staff. The data reveal over 80 introductions into the Boston area, predominantly from elsewhere in the United States and Europe. We studied two superspreading events covered by the data, events that led to very different outcomes because of the timing and populations involved. One produced rapid spread in a vulnerable population but little onward transmission, while the other was a major contributor to sustained community transmission, including outbreaks in homeless populations, and was exported to several other domestic and international sites. The same two events differed significantly in the number of new mutations seen, raising the possibility that SARS-CoV-2 superspreading might encompass disparate transmission dynamics. Our results highlight the failure of measures to prevent importation into MA early in the outbreak, underscore the role of superspreading in amplifying an outbreak in a major urban area, and lay a foundation for contact tracing informed by genetic data.

Distinct evolutionary paths in chronic lymphocytic leukemia during resistance to the graft-versus-leukemia effect.

Leukemic relapse remains a major barrier to successful allogeneic hematopoietic stem cell transplantation (allo-HSCT) for aggressive hematologic malignancies. The basis for relapse of advanced lymphoid malignancies remains incompletely understood and may involve escape from the graft-versus-leukemia (GvL) effect. We hypothesized that for patients with chronic lymphocytic leukemia (CLL) treated with allo-HSCT, leukemic cell-intrinsic features influence transplant outcomes by directing the evolutionary trajectories of CLL cells. Integrated genetic, transcriptomic, and epigenetic analyses of CLL cells from 10 patients revealed that the clinical kinetics of post-HSCT relapse are shaped by distinct molecular dynamics. Early relapses after allo-HSCT exhibited notable genetic stability; single CLL cell transcriptional analysis demonstrated a cellular heterogeneity that was static over time. In contrast, CLL cells relapsing late after allo-HSCT displayed notable genetic evolution and evidence of neoantigen depletion, consistent with marked single-cell transcriptional shifts that were unique to each patient. We observed a greater rate of epigenetic change for late relapses not seen in early relapses or relapses after chemotherapy alone, suggesting that the selection pressures of the GvL bottleneck are unlike those imposed by chemotherapy. No selective advantage for human leukocyte antigen (HLA) loss was observed, even when present in pretransplant subpopulations. Gain of stem cell modules was a common signature associated with leukemia relapse regardless of posttransplant relapse kinetics. These data elucidate the biological pathways that underlie GvL resistance and posttransplant relapse.

TETs compete with DNMT3 activity in pluripotent cells at thousands of methylated somatic enhancers.

Mammalian cells stably maintain high levels of DNA methylation despite expressing both positive (DNMT3A/B) and negative (TET1-3) regulators. Here, we analyzed the independent and combined effects of these regulators on the DNA methylation landscape using a panel of knockout human embryonic stem cell (ESC) lines. The greatest impact on global methylation levels was observed in DNMT3-deficient cells, including reproducible focal demethylation at thousands of normally methylated loci. Demethylation depends on TET expression and occurs only when both DNMT3s are absent. Dynamic loci are enriched for hydroxymethylcytosine and overlap with subsets of putative somatic enhancers that are methylated in ESCs and can be activated upon differentiation. We observe similar dynamics in mouse ESCs that were less frequent in epiblast stem cells (EpiSCs) and scarce in somatic tissues, suggesting a conserved pluripotency-linked mechanism. Taken together, our data reveal tightly regulated competition between DNMT3s and TETs at thousands of somatic regulatory sequences within pluripotent cells.

Small Molecule Targets TMED9 and Promotes Lysosomal Degradation to Reverse Proteinopathy.

Intracellular accumulation of misfolded proteins causes toxic proteinopathies, diseases without targeted therapies. Mucin 1 kidney disease (MKD) results from a frameshift mutation in the MUC1 gene (MUC1-fs). Here, we show that MKD is a toxic proteinopathy. Intracellular MUC1-fs accumulation activated the ATF6 unfolded protein response (UPR) branch. We identified BRD4780, a small molecule that clears MUC1-fs from patient cells, from kidneys of knockin mice and from patient kidney organoids. MUC1-fs is trapped in TMED9 cargo receptor-containing vesicles of the early secretory pathway. BRD4780 binds TMED9, releases MUC1-fs, and re-routes it for lysosomal degradation, an effect phenocopied by TMED9 deletion. Our findings reveal BRD4780 as a promising lead for the treatment of MKD and other toxic proteinopathies. Generally, we elucidate a novel mechanism for the entrapment of misfolded proteins by cargo receptors and a strategy for their release and anterograde trafficking to the lysosome.

Epigenetic evolution and lineage histories of chronic lymphocytic leukaemia.

Genetic and epigenetic intra-tumoral heterogeneity cooperate to shape the evolutionary course of cancer1. Chronic lymphocytic leukaemia (CLL) is a highly informative model for cancer evolution as it undergoes substantial genetic diversification and evolution after therapy2,3. The CLL epigenome is also an important disease-defining feature4,5, and growing populations of cells in CLL diversify by stochastic changes in DNA methylation known as epimutations6. However, previous studies using bulk sequencing methods to analyse the patterns of DNA methylation were unable to determine whether epimutations affect CLL populations homogeneously. Here, to measure the epimutation rate at single-cell resolution, we applied multiplexed single-cell reduced-representation bisulfite sequencing to B cells from healthy donors and patients with CLL. We observed that the common clonal origin of CLL results in a consistently increased epimutation rate, with low variability in the cell-to-cell epimutation rate. By contrast, variable epimutation rates across healthy B cells reflect diverse evolutionary ages across the trajectory of B cell differentiation, consistent with epimutations serving as a molecular clock. Heritable epimutation information allowed us to reconstruct lineages at high-resolution with single-cell data, and to apply this directly to patient samples. The CLL lineage tree shape revealed earlier branching and longer branch lengths than in normal B cells, reflecting rapid drift after the initial malignant transformation and a greater proliferative history. Integration of single-cell bisulfite sequencing analysis with single-cell transcriptomes and genotyping confirmed that genetic subclones mapped to distinct clades, as inferred solely on the basis of epimutation information. Finally, to examine potential lineage biases during therapy, we profiled serial samples during ibrutinib-associated lymphocytosis, and identified clades of cells that were preferentially expelled from the lymph node after treatment, marked by distinct transcriptional profiles. The single-cell integration of genetic, epigenetic and transcriptional information thus charts the lineage history of CLL and its evolution with therapy.

Corrupted coordination of epigenetic modifications leads to diverging chromatin states and transcriptional heterogeneity in CLL.

Cancer evolution is fueled by epigenetic as well as genetic diversity. In chronic lymphocytic leukemia (CLL), intra-tumoral DNA methylation (DNAme) heterogeneity empowers evolution. Here, to comprehensively study the epigenetic dimension of cancer evolution, we integrate DNAme analysis with histone modification mapping and single cell analyses of RNA expression and DNAme in 22 primary CLL and 13 healthy donor B lymphocyte samples. Our data reveal corrupted coherence across different layers of the CLL epigenome. This manifests in decreased mutual information across epigenetic modifications and gene expression attributed to cell-to-cell heterogeneity. Disrupted epigenetic-transcriptional coordination in CLL is also reflected in the dysregulation of the transcriptional output as a function of the combinatorial chromatin states, including incomplete Polycomb-mediated gene silencing. Notably, we observe unexpected co-mapping of typically mutually exclusive activating and repressing histone modifications, suggestive of intra-tumoral epigenetic diversity. Thus, CLL epigenetic diversification leads to decreased coordination across layers of epigenetic information, likely reflecting an admixture of cells with diverging cellular identities.

Capturing sequence diversity in metagenomes with comprehensive and scalable probe design.

Metagenomic sequencing has the potential to transform microbial detection and characterization, but new tools are needed to improve its sensitivity. Here we present CATCH, a computational method to enhance nucleic acid capture for enrichment of diverse microbial taxa. CATCH designs optimal probe sets, with a specified number of oligonucleotides, that achieve full coverage of, and scale well with, known sequence diversity. We focus on applying CATCH to capture viral genomes in complex metagenomic samples. We design, synthesize, and validate multiple probe sets, including one that targets the whole genomes of the 356 viral species known to infect humans. Capture with these probe sets enriches unique viral content on average 18-fold, allowing us to assemble genomes that could not be recovered without enrichment, and accurately preserves within-sample diversity. We also use these probe sets to recover genomes from the 2018 Lassa fever outbreak in Nigeria and to improve detection of uncharacterized viral infections in human and mosquito samples. The results demonstrate that CATCH enables more sensitive and cost-effective metagenomic sequencing.

Targets and genomic constraints of ectopic Dnmt3b expression.

DNA methylation plays an essential role in mammalian genomes and expression of the responsible enzymes is tightly controlled. Deregulation of the de novo DNA methyltransferase DNMT3B is frequently observed across cancer types, yet little is known about its ectopic genomic targets. Here, we used an inducible transgenic mouse model to delineate rules for abnormal DNMT3B targeting, as well as the constraints of its activity across different cell types. Our results explain the preferential susceptibility of certain CpG islands to aberrant methylation and point to transcriptional state and the associated chromatin landscape as the strongest predictors. Although DNA methylation and H3K27me3 are usually non-overlapping at CpG islands, H3K27me3 can transiently co-occur with DNMT3B-induced DNA methylation. Our genome-wide data combined with ultra-deep locus-specific bisulfite sequencing suggest a distributive activity of ectopically expressed Dnmt3b that leads to discordant CpG island hypermethylation and provides new insights for interpreting the cancer methylome.

Comparative genomic analysis of embryonic, lineage-converted and stem cell-derived motor neurons.

Advances in stem cell science allow the production of different cell types in vitro either through the recapitulation of developmental processes, often termed 'directed differentiation', or the forced expression of lineage-specific transcription factors. Although cells produced by both approaches are increasingly used in translational applications, their quantitative similarity to their primary counterparts remains largely unresolved. To investigate the similarity between in vitro-derived and primary cell types, we harvested and purified mouse spinal motor neurons and compared them with motor neurons produced by transcription factor-mediated lineage conversion of fibroblasts or directed differentiation of pluripotent stem cells. To enable unbiased analysis of these motor neuron types and their cells of origin, we then subjected them to whole transcriptome and DNA methylome analysis by RNA sequencing (RNA-seq) and reduced representation bisulfite sequencing (RRBS). Despite major differences in methodology, lineage conversion and directed differentiation both produce cells that closely approximate the primary motor neuron state. However, we identify differences in Fas signaling, the Hox code and synaptic gene expression between lineage-converted and directed differentiation motor neurons that affect their utility in translational studies.