Sample multiplexing is an emerging method in single-cell RNA sequencing (scRNA-seq) that addresses high costs and batch effects. Current multiplexing schemes use DNA labels to barcode cell samples but are limited in their stability and extent of labeling of heterogeneous cell populations. Here, we describe nanocoding, a technology that applies lipid nanoparticles (LNPs) for high barcode labeling density in multiplexed scRNA-seq. LNPs reduce dependencies on cell surface labeling mechanisms due to multiple controllable means of cell uptake, amplifying barcode loading 10-100-fold and allowing both protection and efficient release by upon cell lysis. In cultured cell lines and heterogeneous cells from tissue digests, nanocoding occurs in 40 min with stability after sample mixing and requires only commercially available reagents without complex chemical modifications. In spleen digests, 6-plex barcoded samples show minimal unlabeled cells, with all barcodes giving bimodal count distributions. Challenging samples from adipose tissue of obese rodents containing lipid-rich debris and heterogeneous cells show more than 95% labeling with all known subtypes identified. Using nanocoding, we investigate gene expression changes related to aging in adipose tissue, profiling cells that could not be readily identified with current direct conjugate methods using lipid or antibody conjugates. The ease of generating and tuning these constructs may afford efficient and robust sample multiplexing with minimal crosstalk.

Objective: Identify myeloid cell subsets from peripheral blood and monocyte-derived macrophages associated with MS in Black Americans. Background: Prior work in a cohort of patients composed primarily of underrepresented minority populations suggested an association between MS susceptibility and differential DNA methylation of genes that regulate cellular differentiation, proliferation, and invasion. Design/Methods: Peripheral blood mononuclear cells (PBMC) were obtained from Black American patients with MS and controls with non-inflammatory neurologic conditions under an IRB-approved protocol (UIC Neuroimmunology Biobank). Single cell libraries for RNAseq were constructed from PBMC (n=9) and monocyte-derived macrophages (MDM, n=6) using the Chromium Next GEM Single Cell 3′ Kit v3.1 and Chromium Next GEM Chip G (10x Genomics). Libraries were sequenced on an Illumina NovaSeq 6000. Expression data was analyzed in R software using the Seurat package (Butler et al., 2018). The SingleR and celldex packages (Aran et al., 2019) were used for identification of human peripheral immune cell types. Results: Peripheral blood monocytes from MS patients demonstrated an increase in relative numbers of transitional macrophages. These cells included those from classical CD163+ and non-classical CD16+ monocyte populations. Transcriptomic analysis showed an increase in the expression of a lncRNA (long non-coding RNA), KCNQ1OT1, in these cells. Analysis of MDM revealed expansion of a subset of C1Q1+ macrophages in MS. These cells express high levels of a pattern recognition receptor, FCN1 (ficolin 1). Global transcriptomic analysis revealed increased expression of SNHG5, a small nucleolar RNA host gene, in MS in all macrophage subtypes. Conclusions: These results suggest an association between expansion of specific monocyte-macrophage populations in our patient cohort. Increased expression of KCNQ1OT1 in transitional macrophages and SNHG5 in MDM is also consistent with our prior study of epigenetic biomarkers because these non-coding RNA's are associated with cellular differentiation and proliferation in neoplastic diseases. Disclosure: Mr. Bingen has nothing to disclose. The institution of Dr. Clark has received research support from National Science Foundation. Ms. Wright has nothing to disclose. Fangxiu Xu has nothing to disclose. The institution of Dr. Carrithers has received research support from Biogen.

A shale GeoBioCell microfluidic testbed has been used to evaluate the processes by which the growth of sulfate-reducing bacteria (SRB) biofilms and iron sulfide biominerals reduce porosity and increase hydraulic resistance in hydraulically fractured (fracked) shale reservoirs. These microbe-mineral-water interactions were tracked in real-time at 45°C (113°F) within proppant-filled microchannels constructed within Devonian New Albany Shale samples from the Illinois Basin. Metagenomic analyses of the SRB communities used in experimentation indicate they are composed of Desulfovibrio alaskensis, Aminivibrio species, and two Synergistaceae species. SRB growth and iron sulfide precipitation were tracked with high-resolution brightfield (BF) microscopy and hydraulic resistance (HR) measurements. After ~80-160 hours, exponential increases in HR reached complete clogging after ~150-230 hours (HR > 0.10 PSI/(μl min-1)). Porosity and permeability occlusion was caused by the growth of SRB biofilm streamers encrusted with iron sulfides. Environmental scanning electron microscopy (ESEM) revealed that these large 100’s μm-diameter SRB streamers were composed of microbial cells that adhere to each other, attach to proppant surfaces and extend downstream in and around proppant pore spaces. This indicates that in proppant-filled fracked shales, SRB streamers with iron sulfides readily attach, occlude pore space, and hinder flow. This establishes the shale GeoBioCell as a viable experimental testbed for future determination of the efficacy of microbial biocides and other oil field amendments that are routinely applied to maintain and enhance hydrocarbon production in fracked shale reservoirs.

To the Editor: Rapid genetic diagnosis can guide clinical management, improve prognosis, and reduce costs in critically ill patients.1,2 Although most critical care decisions must be made in hours, traditional testing requires weeks and rapid testing requires days. We have found that nanopore genome sequencing can accurately and rapidly provide genetic diagnoses. Our workflow combines streamlined preparation of commercial nanopore sequencing, distributed Cloudbased bioinformatics, and a custom variant-prioritization approach (Fig. 1).3 Between December 2020 and May 2021, at two hospitals in Stanford, California, we enrolled 12 patients who were generally representative of persons living in the United States with respect to race, ethnic group, and sex (Tables S1 and S2 in the Supplementary Appendix, available with the full text of this letter at NEJM.org). We obtained an initial genetic diagnosis in 5 of the patients (Table S3). The shortest time from arrival of the blood sample in the laboratory to the initial diagnosis was 7 hours 18 minutes. After establishing a diagnosis in Patient 1, we updated our bioinformatics framework to permit the transfer of terabytes of raw signal data to Cloud storage in real time and distributed the data across multiple Cloud computing machines to achieve near real-time base calling and alignment, a step that reduced the postsequencing run time (base calling through alignment) by 93%, from 7 hours 21 minutes to 34 minutes (the average of postsequencing run times for Patients 2 to 12) (Table S5). Flow cells were washed and reused until exhaustion to reduce the sequencing cost per sample. Libraries were bar-coded in Patients 1 through 7 to prevent carryover from one sample to the next. After processing the sample obtained from Patient 7, we benchmarked and adopted a bar-code–free method to rapidly generate genome sequences.3 Removing the bar-coding process accelerated sample preparation by 37 minutes, to an average of 2.5 hours, and enabled us to load a greater amount of patients’ DNA into each flow cell (333 ng vs. 155 ng) and increase pore occupancy (to 82% from 64%) (Figs. S1 and S2 and Table S4). Our sequencing workflow generated 173 to 236 Gb of data per genome using 48 flow cells, with an alignment identity of 94% (Fig. S3) and 46 to 64× autosomal coverage (i.e., each base of each autosome was represented in 46 to 64 sequence reads) (Fig. S4). Half the sequencing throughput was in reads that were 25 kb or longer (Table S6). Small variants and structural variants were called after the reads were aligned to the GRCh37 human reference genome, which generated a median of 4,490,490 single-nucleotide variants and small insertions and deletions (indels).4,5 Custom filtration and prioritization of variants with an ultrarapid scoring system (Fig. S5) substantially decreased the number of candidate variants for manual review to a median of 29 (range, 16 to 53) for small variants and 22 (range, 11 to 37) for structural variants (Table S2). Each initial diagnosis was immediately reviewed by study and bedside physicians, and a consensus was reached as to whether the proposed variant represented the primary cause of the patient’s presentation. Diagnostic variants were identified in 5 of the 12 patients, who ranged in age from 3 months to 57 years. The findings were immediately confirmed by a laboratory certified by the Clinical Laboratory Improvement Amendments (CLIA) process and informed clinical management (including sympathectomy, heart transplantation, screening, and changes in medication) for each of the 5 patients or their family members. In one patient, a 3-month-old full-term infant who presented in status epilepticus, seizure semiology included right gaze deviation with bilateral upper-extremity clonic jerking and perioral myoclonic twitching. Interictal electroencephalography revealed abundant predominantly posterior

Dysregulation of cholesterol homeostasis is associated with many diseases such as cardiovascular disease and cancer. Liver X receptors (LXRs) are major upstream regulators of cholesterol homeostasis and are activated by endogenous cholesterol metabolites such as 27-hydroxycholesterol (27HC). LXRs and various LXR ligands such as 27HC have been described to influence several extra-hepatic biological systems. However, disparate reports of LXR function have emerged, especially with respect to immunology and cancer biology. This would suggest that, similar to steroid nuclear receptors, the LXRs can be selectively modulated by different ligands. Here, we use RNA-sequencing of macrophages and single-cell RNA-sequencing of immune cells from metastasis-bearing murine lungs to provide evidence that LXR satisfies the 2 principles of selective nuclear receptor modulation: (1) different LXR ligands result in overlapping but distinct gene expression profiles within the same cell type, and (2) the same LXR ligands differentially regulate gene expression in a highly context-specific manner, depending on the cell or tissue type. The concept that the LXRs can be selectively modulated provides the foundation for developing precision pharmacology LXR ligands that are tailored to promote those activities that are desirable (proimmune), but at the same time minimizing harmful side effects (such as elevated triglyceride levels).

HomeCirculation: Genomic and Precision MedicineVol. 15, No. 2Ultra-Rapid Nanopore Whole Genome Genetic Diagnosis of Dilated Cardiomyopathy in an Adolescent With Cardiogenic Shock Free AccessLetterPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessLetterPDF/EPUBUltra-Rapid Nanopore Whole Genome Genetic Diagnosis of Dilated Cardiomyopathy in an Adolescent With Cardiogenic Shock John E. Gorzynski, DVM, PhD, Sneha D. Goenka, MTech, Kishwar Shafin, BS, Tanner D. Jensen, BS, Dianna G. Fisk, PhD, Megan E. Grove, MS, Elizabeth Spiteri, PhD, Trevor Pesout, BS, Jean Monlong, PhD, Jonathan A. Bernstein, MD, PhD, Scott Ceresnak, MD, Pi-Chuan Chang, PhD, Jeffrey W. Christle, PhD, Henry Chubb, MBBS, PhD, Kyla Dunn, MS, Daniel R. Garalde, PhD, Joseph Guillory, MS, Maura R.Z. Ruzhnikov, MD, Chris Wright, DPhil, Courtney J. Wusthoff, MD, Katherine Xiong, MD, Seth A. Hollander, MD, Gerald J. Berry, MD, Miten Jain, PhD, Fritz J. Sedlazeck, PhD, Andrew Carroll, PhD, Benedict Paten, PhD and Euan A. Ashley, MB, ChB, DPhil John E. GorzynskiJohn E. Gorzynski https://orcid.org/0000-0002-9034-9016 Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.). , Sneha D. GoenkaSneha D. Goenka https://orcid.org/0000-0002-1716-7769 Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.). , Kishwar ShafinKishwar Shafin https://orcid.org/0000-0001-5252-3434 University of California at Santa Cruz Genomics Institute, Santa Cruz, CA (K.S., T.P., J.M., M.J., B.P.). , Tanner D. JensenTanner D. Jensen Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.). , Dianna G. FiskDianna G. Fisk Stanford Health Care, Palo Alto, CA (D.G.F., M.E.G.). , Megan E. GroveMegan E. Grove https://orcid.org/0000-0002-7972-0005 Stanford Health Care, Palo Alto, CA (D.G.F., M.E.G.). , Elizabeth SpiteriElizabeth Spiteri Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.). , Trevor PesoutTrevor Pesout University of California at Santa Cruz Genomics Institute, Santa Cruz, CA (K.S., T.P., J.M., M.J., B.P.). , Jean MonlongJean Monlong https://orcid.org/0000-0002-9737-5516 University of California at Santa Cruz Genomics Institute, Santa Cruz, CA (K.S., T.P., J.M., M.J., B.P.). , Jonathan A. BernsteinJonathan A. Bernstein https://orcid.org/0000-0001-5369-346X Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.). , Scott CeresnakScott Ceresnak https://orcid.org/0000-0002-9473-0105 Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.). , Pi-Chuan ChangPi-Chuan Chang https://orcid.org/0000-0003-3021-6446 Google Inc, Mountain View, CA (P.-C.C., A.C.). , Jeffrey W. ChristleJeffrey W. Christle Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.). , Henry ChubbHenry Chubb https://orcid.org/0000-0002-2859-3536 Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.). , Kyla DunnKyla Dunn Stanford Children’s Health, Palo Alto, CA (K.D.). , Daniel R. GaraldeDaniel R. Garalde Oxford Nanopore Technologies, United Kingdom (D.R.G., J.G., C.W.). , Joseph GuilloryJoseph Guillory Oxford Nanopore Technologies, United Kingdom (D.R.G., J.G., C.W.). , Maura R.Z. RuzhnikovMaura R.Z. Ruzhnikov https://orcid.org/0000-0001-9610-1612 Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.). , Chris WrightChris Wright Oxford Nanopore Technologies, United Kingdom (D.R.G., J.G., C.W.). , Courtney J. WusthoffCourtney J. Wusthoff https://orcid.org/0000-0002-1882-5567 Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.). , Katherine XiongKatherine Xiong Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.). , Seth A. HollanderSeth A. Hollander Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.). , Gerald J. BerryGerald J. Berry https://orcid.org/0000-0002-6176-2629 Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.). , Miten JainMiten Jain University of California at Santa Cruz Genomics Institute, Santa Cruz, CA (K.S., T.P., J.M., M.J., B.P.). , Fritz J. SedlazeckFritz J. Sedlazeck https://orcid.org/0000-0001-6040-2691 Baylor College of Medicine, Houston, TX (F.J.S.). , Andrew CarrollAndrew Carroll https://orcid.org/0000-0002-4824-6689 Google Inc, Mountain View, CA (P.-C.C., A.C.). , Benedict PatenBenedict Paten University of California at Santa Cruz Genomics Institute, Santa Cruz, CA (K.S., T.P., J.M., M.J., B.P.). and Euan A. AshleyEuan A. Ashley Correspondence to: Euan A. Ashley, MB, ChB, DPhil, Stanford University, 300 Pasteur Dr, Falk CVRC, CV-267, Stanford, CA 94305. Email E-mail Address: [email protected] https://orcid.org/0000-0001-9418-9577 Stanford University, CA (J.E.G., S.D.G., T.D.J., E.S., J.A.B., S.C., J.W.C., H.C., M.R.Z.R., C.J.W., K.X., S.A.H., G.J.B., E.A.A.). Originally published8 Feb 2022https://doi.org/10.1161/CIRCGEN.121.003591Circulation: Genomic and Precision Medicine. 2022;15Other version(s) of this articleYou are viewing the most recent version of this article. Previous versions: February 8, 2022: Ahead of Print Rapid genetic diagnosis has the potential to guide clinical treatment in critically ill patients leading to improved prognosis and decreased health care costs.1 Until recently, the turnaround time for whole genome diagnostic testing precluded its integration into critical care decision making (typical rapid whole genome sequencing clinical testing returns results in 5–7 days). Here, we describe a case of a teenager presenting with cardiogenic shock in whom a genetic diagnosis was made in under 12 hours using a new ultra-rapid long read whole genome sequencing assay and workflow.2,3A 13-year-old male previously in good health presented to his primary care provider with a nocturnal dry cough, decreased appetite, intermittent chest pain, and fatigue. Thoracic radiographs showed cardiomegaly leading to echocardiography, which revealed a dilated left ventricle with an ejection fraction of 29%. The patient was then transferred to Stanford Children’s Health, Lucile Packard Children’s Hospital and subsequent echocardiography revealed an ejection fraction of 20.9% and a left ventricular end-diastolic diameter of 6.6 cm (Figure [A]). Worsening end organ perfusion was observed and shortly thereafter the patient was cannulated for veno-arterial extracorporeal membrane oxygenation.Download figureDownload PowerPointFigure. Ultra-rapid genome sequencing of a patient with dilated cardiomyopathy identifies a variant in cardiac troponin. A, Baseline echocardiography (previous to extracorporeal membrane oxygenation [ECMO] cannulation). A short axis and 4 chamber view demonstrate dilated cardiomyopathy including biventricular remodeling with dilation and wall thinning, as well as mitral regurgitation. B, Right ventricular (RV) septal biopsy obtained via catheterization via the right femoral vein. Hematoxylin and eosin and trichrome stains show enlarged, irregularly shaped myocyte nuclei indicative of hypertrophy (H&E ×200; trichrome ×200). The trichrome stain highlights interstitial fibrosis indicated by the asterisk (*). C, The variant filtering and prioritization scheme allowed rapid review and interpretation of likely actionable variants by setting a threshold of 4 or higher for review and elevating the highest scoring variants for focused interpretation. This method identified a 3 base pair insertion in a short tandem repeat element of TNNT2 (ClinVar Accession: SCV002037155). D, Sanger Sequencing confirms presence of a heterozygous 3 base pair insertion in a short tandem repeat element of TNNT2. gnomAD indicates genome aggregation database; HGMD, human gene mutation database; LV, left ventricle; MAF, minor allele frequency; and RVIS, residual variation intolerance score.The differential diagnosis included lymphocytic or giant cell myocarditis, toxic cardiomyopathy, and genetic cardiomyopathy. While acute myocarditis patients often recover without the need for advanced therapies, genetic causes are typically associated with progressive disease requiring surgical mechanical support and transplantation.4,5 While toxic cardiomyopathy is a diagnosis of exclusion and myocarditis is either a diagnosis of exclusion or one secured by invasive cardiac biopsy, genetic cardiomyopathy can be conclusively demonstrated if a pathogenic variant is found in a known disease causing gene. Due to the acute onset and rapid progression of cardiogenic shock, there was a pressing need to differentiate the cause of disease. Advanced imaging (magnetic resonance imaging or F-fluorodeoxyglucose Computed Tomography-Positron Emission Tomography) can provide evidence for inflammatory cardiomyopathy, however, the patient’s condition limited the possibility of this testing. As such, the patient underwent right ventricular cardiac biopsy via catheterization of the right femoral vein (Figure [B]). In addition, the patient was enrolled in the ultra-rapid whole genome sequencing research program.Two milliliters of whole blood in ethylenediaminetetraacetic (EDTA) acid was collected and genomic DNA extracted using a modified Puregene (Qiagen) method, followed by sequencing library preparation using LSK-109 and native barcodes from Oxford Nanopore Technologies. Sample processing took a total of 4 hours and 12 minutes. The sequencing library was distributed over 48 PromethION flow cells which sequenced simultaneously for a total of 2 hours and 42 minutes resulting in 204 gigabases of sequencing reads with an N50 of 22 kilobases. In real time, the raw sequencing data was uploaded to a cloud server, where base calling and alignment occurred in parallel to sequencing. Small variants (single-nucleotide variants and small insertions/deletions) were called using PEPPER-Margin-DeepVariant resulting in identification of 4 371 501 genomic variants.6 Structural variants were called using Sniffles resulting in 20 prioritized structural variants.7 Sequencing data analysis and preparation took a total of 3 hours 36 minutes postsequencing. Variant call files were then transferred to the curation team where filtering, prioritization and manual curation identified a heterozygous duplication in a short tandem repeat element in TNNT2 (487_489dup GAG), an integral component of the cardiac sarcomere and a gene known to be associated with dilated cardiomyopathy (Figure [C]). Curation time took a total of 46 minutes, identifying a candidate variant in 11 hours and 16 minutes after the sample preparation began. Sanger sequencing confirmed the presence of this variant (Figure [D]) and parental testing later revealed it to be de novo, confirming this variant as likely pathogenic.The right ventricular biopsy produced 3 endomyocardial samples showing myocyte hypertrophy and patchy interstitial fibrosis compatible with dilated cardiomyopathy. No myocarditis, infiltrative disorders or metabolic alterations were present.Ultra-rapid whole genome sequencing identified a likely pathogenic variant in TNNT2 while pathology findings provided no evidence for an inflammatory cause, supporting the diagnosis of dilated cardiomyopathy with a genetic cause. These findings were available before the discussion of transplant listing. In contrast, a clinical panel sent to a commercial laboratory did not return results with the TNNT2 variant until the transplant listing decision was made, emphasizing the impact of rapid turnaround testing. The patient received a heart transplant 21 days after listing.Article InformationSources of FundingThis work was supported by in-kind contributions from Oxford Nanopore, Google, and Nvidia. University California Santa Cruz Genomics Institute and Stanford University unrestricted funds financially supported this study.Disclosures K. Shafin has performed paid internships at NVIDIA Corp and Google LLC, and presented a talk at an Oxford Nanopore Technologies (ONT) sponsored event. Drs Chang and Carroll are employees of Google LLC and own Alphabet stock as part of the standard compensation package. Dr Garalde, J. Guillory, and Dr Wusthoff are employees of ONT and share/share option holders. Dr Jain has received reimbursement for travel, accommodation and conference fees to speak at events organized by ONT. Dr Sedlazeck received travel compensation from Pacific Biotechnology and ONT. Dr Ashley is cofounder of Personalis, Deepcell, and Svexa, Advisor to Apple, and a Non-Executive Director of AstraZeneca. The other authors report no conflicts. Google employees did not have access to patient data.FootnotesFor Sources of Funding and Disclosures, see page 169.Correspondence to: Euan A. Ashley, MB, ChB, DPhil, Stanford University, 300 Pasteur Dr, Falk CVRC, CV-267, Stanford, CA 94305. Email [email protected]eduReferences1. Buchan JG, White S, Joshi R, Ashley EA. Rapid genome sequencing in the critically ill.Clin Chem. 2019; 65:723–726. doi: 10.1373/clinchem.2018.293506CrossrefMedlineGoogle Scholar2. Gorzynski JE, Goenka SD, Shafin K, Jensen TD, Fisk DG, Grove ME, Spiteri E, Pesout T, Monlong J, Baid G, et al.. Ultrarapid nanopore genome sequencing in a critical care setting. New Engl J Med. 2022. doi: 10.1056/NEJMc2112090CrossrefMedlineGoogle Scholar3. Goenka SD, Gorzynski JE, Shafin K, Fisk DG, Pesout T, Monlong J, Jensen TD, Chang P-C, Baid G, Bernstein JA, et al.. Accelerated whole genome nanopore sequencing pipeline enables ultra-rapid identification of disease-causing variants.Nat Biotechnol. 2022. doi: 10.1038/s41587-022-01221-5CrossrefMedlineGoogle Scholar4. Ammirati E, Cipriani M, Moro C, Raineri C, Pini D, Sormani P, Mantovani R, Varrenti M, Pedrotti P, Conca C, et al.; Registro Lombardo delle Miocarditi. Clinical presentation and outcome in a contemporary cohort of patients with acute myocarditis: multicenter lombardy registry.Circulation. 2018; 138:1088–1099. doi: 10.1161/CIRCULATIONAHA.118.035319LinkGoogle Scholar5. Schultheiss HP, Fairweather D, Caforio ALP, Escher F, Hershberger RE, Lipshultz SE, Liu PP, Matsumori A, Mazzanti A, McMurray J, et al.. Dilated cardiomyopathy.Nat Rev Dis Primers. 2019; 5:32. doi: 10.1038/s41572-019-0084-1CrossrefMedlineGoogle Scholar6. Shafin K, Pesout T, Chang PC, Nattestad M, Kolesnikov A, Goel S, Baid G, Kolmogorov M, Eizenga JM, Miga KH, et al.. Haplotype-aware variant calling with PEPPER-Margin-DeepVariant enables high accuracy in nanopore long-reads.Nat Methods. 2021; 18:1322–1332. doi: 10.1038/s41592-021-01299-wCrossrefMedlineGoogle Scholar7. Sedlazeck FJ, Rescheneder P, Smolka M, Fang H, Nattestad M, von Haeseler A, Schatz MC. Accurate detection of complex structural variations using single-molecule sequencing.Nat Methods. 2018; 15:461–468. doi: 10.1038/s41592-018-0001-7CrossrefMedlineGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetails April 2022Vol 15, Issue 2 Advertisement Article InformationMetrics © 2022 American Heart Association, Inc.https://doi.org/10.1161/CIRCGEN.121.003591PMID: 35133172 Originally publishedFebruary 8, 2022 Keywordsgenomedilatedcardiomyopathydiagnosisgenomicssequence analysis, DNAPDF download Advertisement SubjectsCardiomyopathyGeneticsPrecision Medicine

Years of selection for desirable fruit quality traits in dessert watermelon (Citrullus lanatus) has resulted in a narrow genetic base in modern cultivars. Development of novel genomic and genetic resources offers great potential to expand genetic diversity and improve important traits in watermelon. Here, we report a high-quality genome sequence of watermelon cultivar 'Charleston Gray', a principal American dessert watermelon, to complement the existing reference genome from '97103', an East Asian cultivar. Comparative analyses between genomes of 'Charleston Gray' and '97103' revealed genomic variants that may underlie phenotypic differences between the two cultivars. We then genotyped 1365 watermelon plant introduction (PI) lines maintained at the U.S. National Plant Germplasm System using genotyping-by-sequencing (GBS). These PI lines were collected throughout the world and belong to three Citrullus species, C. lanatus, C. mucosospermus and C. amarus. Approximately 25 000 high-quality single nucleotide polymorphisms (SNPs) were derived from the GBS data using the 'Charleston Gray' genome as the reference. Population genomic analyses using these SNPs discovered a close relationship between C. lanatus and C. mucosospermus and identified four major groups in these two species correlated to their geographic locations. Citrullus amarus was found to have a distinct genetic makeup compared to C. lanatus and C. mucosospermus. The SNPs also enabled identification of genomic regions associated with important fruit quality and disease resistance traits through genome-wide association studies. The high-quality 'Charleston Gray' genome and the genotyping data of this large collection of watermelon accessions provide valuable resources for facilitating watermelon research, breeding and improvement.

The evolutionarily ancient Aquificales bacterium Sulfurihydrogenibium spp. dominates filamentous microbial mat communities in shallow, fast-flowing, and dysoxic hot-spring drainage systems around the world. In the present study, field observations of these fettuccini-like microbial mats at Mammoth Hot Springs in Yellowstone National Park are integrated with geology, geochemistry, hydrology, microscopy, and multi-omic molecular biology analyses. Strategic sampling of living filamentous mats along with the hot-spring CaCO3 (travertine) in which they are actively being entombed and fossilized has permitted the first direct linkage of Sulfurihydrogenibium spp. physiology and metabolism with the formation of distinct travertine streamer microbial biomarkers. Results indicate that, during chemoautotrophy and CO2 carbon fixation, the 87-98% Sulfurihydrogenibium-dominated mats utilize chaperons to facilitate enzyme stability and function. High-abundance transcripts and proteins for type IV pili and extracellular polymeric substances (EPSs) are consistent with their strong mucus-rich filaments tens of centimeters long that withstand hydrodynamic shear as they become encrusted by more than 5 mm of travertine per day. Their primary energy source is the oxidation of reduced sulfur (e.g., sulfide, sulfur, or thiosulfate) and the simultaneous uptake of extremely low concentrations of dissolved O-2 facilitated by bd-type cytochromes. The formation of elevated travertine ridges permits the Sulfurihydrogenibium-dominated mats to create a shallow platform from which to access low levels of dissolved oxygen at the virtual exclusion of other microorganisms. These ridged travertine streamer microbial biomarkers are well preserved and create a robust fossil record of microbial physiological and metabolic activities in modern and ancient hot-spring ecosystems.

C. scindens is one of a few identified gut bacterial species capable of converting host cholic acid into disease-associated secondary bile acids such as deoxycholic acid. The current work represents an important advance in understanding the nutritional requirements and response to bile acids of the medically important human gut bacterium, C. scindens ATCC 35704. A defined medium has been developed which will further the understanding of bile acid metabolism in the context of growth substrates, cofactors, and other metabolites in the vertebrate gut. Analysis of the complete genome supports the nutritional requirements reported here. Genome-wide transcriptomic analysis of gene expression in the presence of cholic acid and deoxycholic acid provides a unique insight into the complex response of C. scindens ATCC 35704 to primary and secondary bile acids. Also revealed are genes with the potential to function in bile acid transport and metabolism.

Strains of Eggerthella lenta are capable of oxidation-reduction reactions capable of oxidizing and epimerizing bile acid hydroxyl groups. Several genes encoding these enzymes, known as hydroxysteroid dehydrogenases (HSDH) have yet to be identified. It is also uncertain whether the products of E. lenta bile acid metabolism are further metabolized by other members of the gut microbiota. We characterized a novel human fecal isolate identified as E. lenta strain C592. The complete genome of E. lenta strain C592 was sequenced and comparative genomics with the type strain (DSM 2243) revealed high conservation, but some notable differences. E. lenta strain C592 falls into group III, possessing 3α, 3β, 7α, and 12α-hydroxysteroid dehydrogenase (HSDH) activity, as determined by mass spectrometry of thin layer chromatography (TLC) separated metabolites of primary and secondary bile acids. Incubation of E. lenta oxo-bile acid and iso-bile acid metabolites with whole-cells of the high-activity bile acid 7α-dehydroxylating bacterium, Clostridium scindens VPI 12708, resulted in minimal conversion of oxo-derivatives to lithocholic acid (LCA). Further, Iso-chenodeoxycholic acid (iso-CDCA; 3β,7α-dihydroxy-5β-cholan-24-oic acid) was not metabolized by C. scindens. We then located a gene encoding a novel 12α-HSDH in E. lenta DSM 2243, also encoded by strain C592, and the recombinant purified enzyme was characterized and substrate-specificity determined. Genomic analysis revealed genes encoding an Rnf complex (rnfABCDEG), an energy conserving hydrogenase (echABCDEF) complex, as well as what appears to be a complete Wood-Ljungdahl pathway. Our prediction that by changing the gas atmosphere from nitrogen to hydrogen, bile acid oxidation would be inhibited, was confirmed. These results suggest that E. lenta is an important bile acid metabolizing gut microbe and that the gas atmosphere may be an important and overlooked regulator of bile acid metabolism in the gut.

Sequencing the RNA in a biological sample can unlock a wealth of information, including the identity of bacteria and viruses, the nuances of alternative splicing or the transcriptional state of organisms. However, current methods have limitations due to short read lengths and reverse transcription or amplification biases. Here we demonstrate nanopore direct RNA-seq, a highly parallel, real-time, single-molecule method that circumvents reverse transcription or amplification steps. This method yields full-length, strand-specific RNA sequences and enables the direct detection of nucleotide analogs in RNA.

Intense artificial selection over the last 100 years has produced elite maize (Zea mays) inbred lines that combine to produce high-yielding hybrids. To further our understanding of how genome and transcriptome variation contribute to the production of high-yielding hybrids, we generated a draft genome assembly of the inbred line PH207 to complement and compare with the existing B73 reference sequence. B73 is a founder of the Stiff Stalk germplasm pool, while PH207 is a founder of Iodent germplasm, both of which have contributed substantially to the production of temperate commercial maize and are combined to make heterotic hybrids. Comparison of these two assemblies revealed over 2500 genes present in only one of the two genotypes and 136 gene families that have undergone extensive expansion or contraction. Transcriptome profiling revealed extensive expression variation, with as many as 10,564 differentially expressed transcripts and 7128 transcripts expressed in only one of the two genotypes in a single tissue. Genotype-specific genes were more likely to have tissue/condition-specific expression and lower transcript abundance. The availability of a high-quality genome assembly for the elite maize inbred PH207 expands our knowledge of the breadth of natural genome and transcriptome variation in elite maize inbred lines across heterotic pools.

Yiran Dong*, Vaibhav Srivastava, Vincent Bulone, Kathleen M. Keating, Radhika S. 6! Khetani, Christopher J. Fields, William P. Inskeep, Robert A. Sanford, Peter M. Yau, Brian 7! S. Imai,!Alvaro G. Hernandez, Chris Wright, Mark Band, Joseph Weber, Isaac K. Cann, 8! Shuomeng Guang, Dag Ahrén, Bruce W. Fouke* 9! 10! 11! 12! 13! 14! Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, 15! USA 16! Department of Geology, University of Illinois Urbana-Champaign, USA 17! Energy Biosciences Institute, University of Illinois Urbana-Champaign, USA 18! Division of Glycoscience, School of Biotechnology, Royal Institute of Technology (KTH), 19! Stockholm, Sweden 20! Roy J. Carver Biotechnology Center, University of Illinois Urbana-Champaign, USA 21! Harvard T. H. Chan School of Public Health Bioinformatics Core, Harvard University, 22! USA 23! Department of Land Resources and Environmental Sciences, Montana State University, USA 24! Thermal Biology Institute, Montana State University, USA 25! Department of Animal Sciences, University of Illinois Urbana-Champaign, USA 26! Department of Microbiology, University of Illinois Urbana-Champaign, USA 27! Department of Bioengineering, University of Illinois Urbana-Champaign, USA 28! Microbial Ecology Group, Bioinformatics Infrastructure for Life Sciences, Department of 29! Biology, Lund University, Lund, Sweden 30! 31!

Pineapple (Ananas comosus (L.) Merr.) is the most economically valuable crop possessing crassulacean acid metabolism (CAM), a photosynthetic carbon assimilation pathway with high water-use efficiency, and the second most important tropical fruit. We sequenced the genomes of pineapple varieties F153 and MD2 and a wild pineapple relative, Ananas bracteatus accession CB5. The pineapple genome has one fewer ancient whole-genome duplication event than sequenced grass genomes and a conserved karyotype with seven chromosomes from before the ρ duplication event. The pineapple lineage has transitioned from C3 photosynthesis to CAM, with CAM-related genes exhibiting a diel expression pattern in photosynthetic tissues. CAM pathway genes were enriched with cis-regulatory elements associated with the regulation of circadian clock genes, providing the first cis-regulatory link between CAM and circadian clock regulation. Pineapple CAM photosynthesis evolved by the reconfiguration of pathways in C3 plants, through the regulatory neofunctionalization of preexisting genes and not through the acquisition of neofunctionalized genes via whole-genome or tandem gene duplication.

High-throughput RNA sequencing (RNA-seq) greatly expands the potential for genomics discoveries, but the wide variety of platforms, protocols and performance capabilitites has created the need for comprehensive reference data. Here we describe the Association of Biomolecular Resource Facilities next-generation sequencing (ABRF-NGS) study on RNA-seq. We carried out replicate experiments across 15 laboratory sites using reference RNA standards to test four protocols (poly-A-selected, ribo-depleted, size-selected and degraded) on five sequencing platforms (Illumina HiSeq, Life Technologies PGM and Proton, Pacific Biosciences RS and Roche 454). The results show high intraplatform (Spearman rank R > 0.86) and inter-platform (R > 0.83) concordance for expression measures across the deep-count platforms, but highly variable efficiency and cost for splice junction and variant detection between all platforms. For intact RNA, gene expression profiles from rRNA-depletion and poly-A enrichment are similar. In addition, rRNA depletion enables effective analysis of degraded RNA samples. This study provides a broad foundation for cross-platform standardization, evaluation and improvement of RNA-seq.

As part of the DNA Sequencing Research Group of the Association of Biomolecular Resource Facilities, we have tested the reproducibility of the Roche/454 GS-FLX Titanium System at five core facilities. Experience with the Roche/454 system ranged from <10 to >340 sequencing runs performed. All participating sites were supplied with an aliquot of a common DNA preparation and were requested to conduct sequencing at a common loading condition. The evaluation of sequencing yield and accuracy metrics was assessed at a single site. The study was conducted using a laboratory strain of the Dutch elm disease fungus Ophiostoma novo-ulmi strain H327, an ascomycete, vegetatively haploid fungus with an estimated genome size of 30-50 Mb. We show that the Titanium System is reproducible, with some variation detected in loading conditions, sequencing yield, and homopolymer length accuracy. We demonstrate that reads shorter than the theoretical minimum length are of lower overall quality and not simply truncated reads. The O. novo-ulmi H327 genome assembly is 31.8 Mb and is comprised of eight chromosome-length linear scaffolds, a circular mitochondrial conti of 66.4 kb, and a putative 4.2-kb linear plasmid. We estimate that the nuclear genome encodes 8613 protein coding genes, and the mitochondrion encodes 15 genes and 26 tRNAs.

Multiple recent publications on RNA-Seq have demonstrated the power of next generation sequencing technologies in whole transcriptome analysis. The vendor specific protocols used for RNA library construction typically require at least 100ng of total RNA. However, under certain conditions such as single cells, stem cells, difficult to isolate cell types, or fractionated cancer cells, only a small amount of material is available. In these cases, effective transcriptome profiling requires amplification of subnanogram amounts of RNA. Several RNA amplification kits are available for amplification prior to library construction and next generation sequencing but these kits have not been comprehensively field evaluated for accuracy and performance of RNA-Seq for picogram amounts of RNA. This study conducted by the DNA Sequencing Research Group (DSRG) focuses on the evaluation of amplification kits for RNA-Seq. Four commercial amplification kits were chosen: Ovation v2 (NuGEN Technologies), SMARTer (Clontech), Seqplex (Sigma Aldrich), and Super-AMP (Miltenyi Biotech). Starting material was 5ng, 500pg and 50pg of human total reference RNA (Clontech) spiked with Ambion ERCC control mix (Life Technologies) following the manufacturer's protocol. Each kit was tested at 3 different sites to assess reproducibility. Total RNA and ERCC RNA spike-in control mixes from the same lots were sent to 12 ABRF lab sites for amplification and cDNA generation. Ideally, this would have resulted in 36 different amplified samples, 3 from each input RNA. Libraries were constructed at one site from the amplified cDNAs using the TruSeq RNA library preparation kit on the Tecan Freedom EVO Liquid Handling Robot. As an unamplified control, ribosomal depletion and PolyA selection were performed separately using 5ng, 100ng and 1ug of total RNA prior to library construction. All libraries were pooled and sequenced using the Illumina HiSeq platform. An overview of the study and the results will be presented.