High-throughput mapping of regulatory DNA

Quantifying the effects of cis-regulatory DNA on gene expression is a major challenge. Here, we present the multiplexed editing regulatory assay (MERA), a high-throughput CRISPR-Cas9–based approach that analyzes the functional impact of the regulatory genome in its native context. MERA tiles thousands of mutations across ~40 kb of cis-regulatory genomic space and uses knock-in green fluorescent protein (GFP) reporters to read out gene activity. Using this approach, we obtain quantitative information on the contribution of cis-regulatory regions to gene expression. We identify proximal and distal regulatory elements necessary for expression of four embryonic stem cell–specific genes. We show a consistent contribution of neighboring gene promoters to gene expression and identify unmarked regulatory elements (UREs) that control gene expression but do not have typical enhancer epigenetic or chromatin features. We compare thousands of functional and nonfunctional genotypes at a genomic location and identify the base pair–resolution functional motifs of regulatory elements.National Institutes of Health (U.S.) (1U01HG007037

Navigating the Human Epigenome through Random Forests

With the recent identification of over 100 histone modifications in mammalian cell-types, there is an urgent need to discover the minimal set of modifications that can completely characterize a genomic element. Of particular interest are transcriptional enhancers that play critical roles in cell-type specific gene expression but are difficult to characterize because they often act in a distal manner to the gene they regulate. We developed a Random-Forest based algorithm, RFECS (Random Forest based Enhancer identification from Chromatin State) for genome- wide prediction of enhancers which allowed us to identify the most informative and robust set of three chromatin marks for enhancer prediction. In addition, RFECS was seen to have improved accuracy of prediction over previous methods. Applying this method to other genomic elements, we identified the minimal set of histone modifications required for prediction of promoters and gene bodies. Further, we elucidated the distinctive localization of histone lysine acetylations at enhancers, promoters and gene bodies, and obtained novel insights into the association of chromatin modification patterns with splicing. Using our algorithm, we predicted enhancers and promoters in 26 human primary tissues and 6 cell-lines, including 5 early developmental lineages. This lead us to the discovery of a novel class of cis-regulatory elements that can behave as enhancers in one cell-type and promoters in another. Further, we were able to associate the evolutionary conservation of regulatory sequences with properties such as tissue-specificity. RFECS is a powerful algorithm with two-fold advantage. First, we can identify the most informative set of modifications characterizing or distinguishing particular genomic elements, thus enabling an insight into the biological mechanism of function at these regions. Second, we can make accurate predictions of enhancers and promoters in a genome-wide fashion, enabling the comparison of regulatory mechanisms across various human tissues or cellular conditions. Variations of histone modification patterns at the predicted tissue-specific cis-regulatory elements may substantially influence gene expression, which could potentially explain the distinct phenotypes of genotypically identical tissue

Navigating the Human Epigenome through Random Forests

With the recent identification of over 100 histone modifications in mammalian cell-types, there is an urgent need to discover the minimal set of modifications that can completely characterize a genomic element. Of particular interest are transcriptional enhancers that play critical roles in cell-type specific gene expression but are difficult to characterize because they often act in a distal manner to the gene they regulate. We developed a Random-Forest based algorithm, RFECS (Random Forest based Enhancer identification from Chromatin State) for genome- wide prediction of enhancers which allowed us to identify the most informative and robust set of three chromatin marks for enhancer prediction. In addition, RFECS was seen to have improved accuracy of prediction over previous methods. Applying this method to other genomic elements, we identified the minimal set of histone modifications required for prediction of promoters and gene bodies. Further, we elucidated the distinctive localization of histone lysine acetylations at enhancers, promoters and gene bodies, and obtained novel insights into the association of chromatin modification patterns with splicing. Using our algorithm, we predicted enhancers and promoters in 26 human primary tissues and 6 cell-lines, including 5 early developmental lineages. This lead us to the discovery of a novel class of cis-regulatory elements that can behave as enhancers in one cell-type and promoters in another. Further, we were able to associate the evolutionary conservation of regulatory sequences with properties such as tissue-specificity. RFECS is a powerful algorithm with two-fold advantage. First, we can identify the most informative set of modifications characterizing or distinguishing particular genomic elements, thus enabling an insight into the biological mechanism of function at these regions. Second, we can make accurate predictions of enhancers and promoters in a genome-wide fashion, enabling the comparison of regulatory mechanisms across various human tissues or cellular conditions. Variations of histone modification patterns at the predicted tissue-specific cis-regulatory elements may substantially influence gene expression, which could potentially explain the distinct phenotypes of genotypically identical tissue

A deep lobe parotid tumor tending the facial nerve and its branches

Benign tumors of major salivary glands commonly affect the parotid gland and it is rare when the tumor exclusively involves the deep lobe of the gland. The mainstay of treatment is surgical excision. Parotid surgeries carry a formidable risk of injury to the facial nerve. Hence, identification of extracranial part of facial nerve using many of its anatomical landmarks helps in preventing this daunting complication. There are instances where the facial nerve's morphometry is altered due to the location and extent of the tumor. A better knowledge of the anatomy and anticipation for these variations can result in a better outcome limiting the complications of the surgery

Distinct and predictive histone lysine acetylation patterns at promoters, enhancers, and gene bodies.

In eukaryotic cells, histone lysines are frequently acetylated. However, unlike modifications such as methylations, histone acetylation modifications are often considered redundant. As such, the functional roles of distinct histone acetylations are largely unexplored. We previously developed an algorithm RFECS to discover the most informative modifications associated with the classification or prediction of mammalian enhancers. Here, we used this tool to identify the modifications most predictive of promoters, enhancers, and gene bodies. Unexpectedly, we found that histone acetylation alone performs well in distinguishing these unique genomic regions. Further, we found the association of characteristic acetylation patterns with genic regions and association of chromatin state with splicing. Taken together, our work underscores the diverse functional roles of histone acetylation in gene regulation and provides several testable hypotheses to dissect these roles

Degradation studies of organic acids in commercially packed fruit juices: A reverse phase high performance liquid chromatographic approach

Organic acids are important constituents of fruit juices. They render tartness, flavour and specific taste to fruit juices. Shelf life and stability of fruit juices are important factors, which determine their nutritional quality and freshness. In this view, the effect of storage on the concentration of organic acids in commercially packed fruit juices is studied by reverse phase high performance liquid chromatography (RP-HPLC). Ten packed fruit juices from two different brands are stored at 30 C for 24, 48 and 72 hours. A reverse phase high performance liquid chromatographic method is used to determine the concentration of oxalic, tartaric, malic, ascorbic and citric acid in the fruit juices during storage. The chromatographic analysis of organic acids is carried out using mobile phase 0.5% (w/v) ammonium dihydrogen orthophosphate buffer (pH 2.8) on C18 column with UV-Vis detector. The results show that the concentration of organic acids generally decreases in juices under study with the increase in storage time. All the fruit juices belonging to tropicana brand underwent less organic acid degradation in comparison to juices of real brand. Orange fruit juice is found to be least stable among the juices under study, after the span of 72 hours. Amongst all the organic acids under investigation minimum stability is shown by ascorbic acid followed by malic and citric acid

RFECS: A Random-Forest Based Algorithm for Enhancer Identification from Chromatin State

Transcriptional enhancers play critical roles in regulation of gene expression, but their identification in the eukaryotic genome has been challenging. Recently, it was shown that enhancers in the mammalian genome are associated with characteristic histone modification patterns, which have been increasingly exploited for enhancer identification. However, only a limited number of cell types or chromatin marks have previously been investigated for this purpose, leaving the question unanswered whether there exists an optimal set of histone modifications for enhancer prediction in different cell types. Here, we address this issue by exploring genome-wide profiles of 24 histone modifications in two distinct human cell types, embryonic stem cells and lung fibroblasts. We developed a Random-Forest based algorithm, RFECS (Random Forest based Enhancer identification from Chromatin States) to integrate histone modification profiles for identification of enhancers, and used it to identify enhancers in a number of cell-types. We show that RFECS not only leads to more accurate and precise prediction of enhancers than previous methods, but also helps identify the most informative and robust set o