Genome-wide chromatin accessibility and nucleosome occupancy profiles have been widely investigated, while the longrange dynamics remain poorly studied at the single-cell level. Here, we present a new experimental approach, methyltransferase treatment followed by single-molecule long-read sequencing (MeSMLR-seq), for long-range mapping of nucleosomes and chromatin accessibility at single DNA molecules and thus achieve comprehensive-coverage characterization of the corresponding heterogeneity. MeSMLR-seq offers direct measurements of both nucleosome-occupied and nucleosome-evicted regions on a single DNA molecule, which is challenging for many existing methods. We applied MeSMLR-seq to haploid yeast, where single DNA molecules represent single cells, and thus we could investigate the combinatorics of many (up to 356) nucleosomes at long range in single cells. We illustrated the differential organization principles of nucleosomes surrounding the transcription start site for silent and actively transcribed genes, at the single-cell level and in the long-range scale. The heterogeneous patterns of chromatin status spanning multiple genes were phased. Together with single-cell RNAseq data, we quantitatively revealed how chromatin accessibility correlated with gene transcription positively in a highly heterogeneous scenario. Moreover, we quantified the openness of promoters and investigated the coupled chromatin changes of adjacent genes at single DNA molecules during transcription reprogramming. In addition, we revealed the coupled changes of chromatin accessibility for two neighboring glucose transporter genes in response to changes in glucose concentration.
To identify genetic contributions to type 2 diabetes (T2D) and related glycemic traits (fasting glucose, fasting insulin, and HbA1c), we conducted genome-wide association analyses (GWAS) in up to 7,178 Chinese subjects from nine provinces in the China Health and Nutrition Survey (CHNS). We examined patterns of population structure within CHNS and found that allele frequencies differed across provinces, consistent with genetic drift and population substructure. We further validated 32 previously described T2D- and glycemic trait-loci, including G6PC2 and SIX3-SIX2 associated with fasting glucose. At G6PC2, we replicated a known fasting glucose-associated variant (rs34177044) and identified a second signal (rs2232326), a low-frequency (4%), probably damaging missense variant (S324P). A variant within the lead fasting glucose-associated signal at SIX3-SIX2 co-localized with pancreatic islet expression quantitative trait loci (eQTL) for SIX3, SIX2, and three noncoding transcripts. To identify variants functionally responsible for the fasting glucose association at SIX3-SIX2, we tested five candidate variants for allelic differences in regulatory function. The rs12712928-C allele, associated with higher fasting glucose and lower transcript expression level, showed lower transcriptional activity in reporter assays and increased binding to GABP compared to the rs12712928-G, suggesting that rs12712928-C contributes to elevated fasting glucose levels by disrupting an islet enhancer, resulting in reduced gene expression. Taken together, these analyses identified multiple loci associated with glycemic traits across China, and suggest a regulatory mechanism at the SIX3-SIX2 fasting glucose GWAS locus.
SUMMARY Direct reprogramming of fibroblasts into cardiomyocyte-like cells (iCM) holds great potential for heart regeneration and disease modeling and may lead to future therapeutic applications. Currently, application of this technology is limited by our lack of understanding of the molecular mechanisms that drive direct iCM reprogramming. Using a quantitative mass spectrometry-based proteomic approach, we identified the temporal global changes in protein abundance that occur during initial phases of iCM reprogramming. Collectively, our results show systematic and temporally distinct alterations in levels of specific functional classes of proteins during the initiating steps of reprogramming including extracellular matrix proteins, translation factors, and chromatin-binding proteins. We have constructed protein relational networks associated with the initial transition of a fibroblast into an iCM. These findings demonstrate the presence of an orchestrated series of temporal steps associated with dynamic changes in protein abundance in a defined group of protein pathways during the initiating events of direct reprogramming.
dWe sequenced a novel conjugative multidrug resistance IncF plasmid, p42-2, isolated from Escherichia coli strain 42-2, previously identified in China. p42-2 is 106,886 bp long, composed of a typical IncFII-type backbone (ϳ54 kb) and one distinct acquired DNA region spanning ϳ53 kb, harboring 12 antibiotic resistance genes [bla CTX-M-55 , oqxA, oqxB, fosA3, floR, tetA(A), tetA(R), strA, strB, sul2, aph(3=)-II, and ⌬bla TEM-1 ]. The spread of these multidrug resistance determinants on the same plasmid is of great concern and, because of coresistance to antibiotics from different classes, is therapeutically challenging. Widespread antibiotic resistance poses an enormous threat for human and animal health worldwide (1). This problem has been exacerbated in recent years with the emergence of multidrug resistance (MDR) plasmids conferring resistance to most classes of antimicrobials (2). Plasmids of the incompatibility F (IncF) group, representing one of the most frequently encountered plasmid types (3), have frequently been associated with MDR phenotypes, including extended-spectrum -lactamases (ESBLs) and plasmid-mediated quinolone resistance (PMQR) genes (4, 5). In a previous study of ours, IncF plasmids recovered from Escherichia coli strains of food-producing and companion animals were investigated, and most of them carried numerous resistance determinants, such as bla CTX-M , rmtB, oqxAB, and floR (4, 6). The spread of these multiresistance plasmids has prompted worldwide concern because of coresistance to multiple antimicrobial agents that facilitates the survival of bacteria under the selective pressure of antibiotics. Herein, we analyzed a common subtype IncF plasmid, F33:AϪ:BϪ (FII, FIA, FIB [FAB] formula); this plasmid, designated p42-2, contains 12 different resistance genes and was fully sequenced, and the data were compared with those of other IncF plasmids.E. coli 42-2 was recovered from the feces of a healthy duck in Guangzhou, China. Conjugation was performed by mixing E. coli 42-2 and E. coli C600 in a liquid medium and isolating for E. coli C600 (p42-2) by selection on MacConkey agar containing streptomycin (1,000 mg/liter) and cefotaxime (2 mg/liter) as previously described (4, 6). p42-2 was extracted from the E. coli C600 transconjugant using a commercial kit (Qiagen midikit; Qiagen, Germany). Sequencing of p42-2 was performed on an Illumina IIx genome analyzer with a 500-bp paired-end library (approximately 100 million available reads, 935-fold genome coverage) and a 2,000-bp paired-end library (ϳ337 million available reads, 3,150-fold genome coverage). These raw data were assembled by SOAPdenovo (7). Gene prediction and annotation were performed using RAST tools (8). The sequence comparison and map generation were performed using BLAST (http://blast.ncbi.nlm.nih.gov) and Easyfig version 2.1 (9).Plasmid p42-2 confers resistance to ampicillin, chloramphenicol, kanamycin, streptomycin, sulfonamides/trimethoprim, tetracycline, olaquindox, fosfomycin, cephalosporin, and florfenicol. Because of its ...
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