In eukaryotic cells, transcription of every protein-coding gene begins with the assembly of an RNA Polymerase II preinitiation complex (PIC) on the promoter 1 . The promoters, in conjunction with enhancers, silencers and insulators, define the combinatorial codes that specify gene expression patterns 2 . Our ability to analyze the control logic encoded in the human genome is currently limited by a lack of accurate information of the promoters for most genes 3 . Here, we describe a genomewide map of active promoters in human fibroblast cells, determined by experimentally locating the sites of PIC binding throughout the human genome. This map defines 10,571 active promoters corresponding to 6,763 known genes and at least 1,199 un-annotated transcriptional units. Features of the map suggest extensive usage of multiple promoters by the human genes and widespread clustering of active promoters in the genome. In addition, examination of the genome-wide expression profile reveals four general classes of promoters that define the transcriptome of the cell. These results provide a global view of the functional relationship among the transcriptional machinery, chromatin structure and gene expression in human cells.The PIC consists of the RNA Polymerase II (RNAP), the transcription factor IID (TFIID) and other general transcription factors 4 . Our strategy to map the PIC binding sites involves a chromatin immunoprecipitation coupled DNA microarray analysis (ChIP-on-chip), which combines the immunoprecipitation of PIC-bound chromatin from formaldehyde crosslinked cells with parallel identification of the resulting bound DNA sequences using DNA microarrays 5,6 . Previously, we have demonstrated the feasibility of this strategy by successfully mapping active promoters in 1% of the human genome that correspond to the 44 genomic loci known as the ENCODE regions 6,7 . To apply this strategy to the entire human genome, we fabricated a series of DNA microarrays 8 containing roughly 14.5 million 50-mer oligonucleotides, designed to represent all the non-repeat DNA throughout the human genome at 100 basepairs (bp) resolution. We immunoprecipitated TFIID-bound DNA from the primary fibroblast IMR90 cells with a monoclonal antibody that specifically recognizes the TAF1 subunit of this complex (TBP associated factor 1, formerly TAF II 250 9, Fig 1a). We then amplified and fluorescently labeled the resulting DNA, and hybridized it to the above microarrays along with a differentially labeled control DNA (Fig. 1a). We determined 9,966 potential TFIID-binding regions using a simple algorithm requiring a stretch of four neighboring probes to have a hybridization signal significantly above the background. To 6 To whom correspondence should be addressed. Email: biren@ucsd.edu. Phone: 858 822 5766; Fax: 858 534 7750. 5 These two authors contributed equally to this work. Author to which correspondence and material request should be addressed: Bing Ren, biren@ucsddu. The microarray datasets are available from GEO (accession numbers to be ...

Customized TALENs and Cas9/gRNAs have been used for targeted mutagenesis in zebrafish to induce indels into protein-coding genes. However, indels are usually not sufficient to disrupt the function of non-coding genes, gene clusters or regulatory sequences, whereas large genomic deletions or inversions are more desirable for this purpose. By injecting two pairs of TALEN mRNAs or two gRNAs together with Cas9 mRNA targeting distal DNA sites of the same chromosome, we obtained predictable genomic deletions or inversions with sizes ranging from several hundred bases to nearly 1 Mb. We have successfully achieved this type of modifications for 11 chromosomal loci by TALENs and 2 by Cas9/gRNAs with different combinations of gRNA pairs, including clusters of miRNA and protein-coding genes. Seven of eight TALEN-targeted lines transmitted the deletions and one transmitted the inversion through germ line. Our findings indicate that both TALENs and Cas9/gRNAs can be used as an efficient tool to engineer genomes to achieve large deletions or inversions, including fragments covering multiple genes and non-coding sequences. To facilitate the analyses and application of existing ZFN, TALEN and CRISPR/Cas data, we have updated our EENdb database to provide a chromosomal view of all reported engineered endonucleases targeting human and zebrafish genomes.

Background: The known risk factors of childhood OSAS include tonsillar and adenoidhypertrophy, obesity, craniofacial anomalies, neuromuscular disorders and African-American (AA) ancestry. Whether other factors such as allergic rhinitis (AR), premature, environmental tobacco smoking (ETS) are associated with OSAS are inconsistent in different studies. Our study enrolled children of a broad age range and included potential risk factors of OSAS derived from previous studies and our own experience. Our objective is to identify risk factors of OSAS in children in a clinical setting. Methods: Children between 2 and 15 years of age exhibiting snoring symptoms who visited the sleep center for polysomnography (PSG) were enrolled. All children completed a questionnaire, physical examination and PSG. The questionnaire included demographic data and information related to potential risk factors for sleep disorders. A physical examination included measurements of height, weight, neck circumference, waist and hip ratio, visual evaluation of the tonsils and the degree of adenoid obstruction. Children with obstructive apnea-hypopnea index (OAHI) ≥ 1 were defined as OSAS.Results: A total of 1578 children were enrolled and1009 children exhibited OSAS. Univariate analyses showed that snoring occurring for ≥ 3 months, male gender, preterm birth, breastfeeding, obesity, neck circumference ≥ 30 cm, waist/hip ratio ≥ 0.95, tonsillar hypertrophy, and adenoid hypertrophy were associated with OSAS. The proportion of low educational level was higher in parents who breastfed their babies than those who didn't. Multivariate analysis showed that snoring for ≥ 3 months, male gender, obesity, breastfeeding, tonsillar hypertrophy, and adenoid hypertrophy were associated with OSAS. Confounders such as socioeconomic status, parental occupation, and healthrelated behaviors should be explored further to investigate the relationship between breastfeeding and OSAS. Conclusion: The independent risk factors for OSAS in children included snoring ≥ 3 months, male gender, obesity, breastfeeding, tonsillar and adenoid hypertrophy. The study was registered on Clinical Trials government (NCT02447614). The name of the trial is "Follow-up Studies of Primary Snoring (PS) and Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) in Chinese Children" and the URL is https://clinicaltrials.gov/.

A major limitation for RNA-seq analysis of alternative splicing is its reliance on high sequencing coverage. We report DARTS ( https://github.com/Xinglab/DARTS ), a computational framework that integrates deep learning-based predictions with empirical RNA-seq evidence to infer differential alternative splicing between biological samples. DARTS leverages public RNA-seq big data to provide a knowledge base of splicing regulation via deep learning, helping researchers better characterize alternative splicing using RNA-seq datasets even with modest coverage.

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