What Happens During 1 Second of HFT?

What Happens During 1 Second of HFT?:
1/2 second of trading activity in Johnson & Johnson (symbol JNJ) on May 2, 2013


Published on May 3, 2013
Nanex explains:

“The bottom box (SIP) shows the National Best Bid and Offer. Watch how much it changes in the blink of an eye.
Watch High Frequency Traders (HFT) at the millisecond level jam thousands of quotes in the stock of Johnson and Johnson (JNJ) through our financial networks on May 2, 2013. Video shows 1/2 second of time. If any of the connections are not running perfectly, High Frequency Traders can profit from the price discrepancies that result. There is no economic justification for this abusive behavior.
Each box represents one exchange. The SIP (CQS in this case) is the box at 6 o’clock. It shows the National Best Bid/Offer. Watch how much it changes in a fraction of a second. The shapes represent quote changes which are the result of a change to the top of the book at each exchange. The time at the bottom of the screen is Eastern Time HH:MM:SS:mmm (mmm = millisecond). We slow time down so you can see what goes on at the millisecond level. A millisecond (ms) is 1/1000th of a second.
Note how every exchange must process every quote from the others — for proper trade through price protection. This complex web of technology must run flawlessly every millisecond of the trading day, or arbitrage (HFT profit) opportunities will appear. It is easy for HFTs to cause delays in one or more of the connections between each exchange.”

Source: Nanex

How Did Feathers Evolve?

How Did Feathers Evolve?:
To look at the evolution of modern bird feathers, we must start a long time ago, with the dinosaurs from whence they came. We see early incarnations of feathers on dinosaur fossils, and remnants of dinosaurs in a bird’s wish bone. Carl Zimmer explores the stages of evolution and how even the reasons for feathers have evolved over millions of years.


Lesson by Carl Zimmer, animation by Armella Leung.
For more, see Ed Ted

A Schnurri/Mad/Medea complex attenuates the dorsal-twist gradient readout at vnd

Justin Crocker, 

Albert Erives

http://www.sciencedirect.com/science/article/pii/S0012160613001310:

Morphogen gradients are used in developing embryos, where they subdivide a field of cells into territories characterized by distinct cell fate potentials. Such systems require both a spatially-graded distribution of the morphogen, and an ability to encode different responses at different target genes. However, the potential for different temporal responses is also present because morphogen gradients typically provide temporal cues, which may be a potential source of conflict. Thus, a low threshold response adapted for an early temporal onset may be inappropriate when the desired spatial response is a spatially-limited, high-threshold expression pattern. Here, we identify such a case with the Drosophila vnd locus, which is a target of the dorsal (dl) nuclear concentration gradient that patterns the dorsal/ventral (D/V) axis of the embryo. The vndgene plays a critical role in the “ventral dominance” hierarchy of vnd, ind, and msh, which individually specify distinct D/V neural columnar fates in increasingly dorsal ectodermal compartments. The role of vnd in this regulatory hierarchy requires early temporal expression, which is characteristic of low-threshold responses, but its specification of ventral neurogenic ectoderm demands a relatively high-threshold response to dl. We show that the Neurogenic Ectoderm Enhancer (NEE) at vnd takes additional input from the complementary Dpp gradient via a conserved Schnurri/Mad/Medea silencer element (SSE) unlike NEEs at brk, sog, rho, andvn. These results show how requirements for conflicting temporal and spatial responses to the same gradient can be solved by additional inputs from complementary gradients.

Differential binding of the related transcription factors Pho4 and Cbf1 can tune the sensitivity of promoters to different levels of an induction signal

Differential binding of the related transcription factors Pho4 and Cbf1 can tune the sensitivity of promoters to different levels of an induction signal:

Transcription factors that belong to the same family typically have similar, but not identical, binding specificities. As such, they can be expected to compete differentially for binding to different variants of their binding sites. Pho4 is a yeast factor whose nuclear concentration is up-regulated in low phosphate, while the related factor, Cbf1, is constitutively expressed. We constructed 16 GFP-reporter genes containing all palindromic variants of the motif NNCACGTGNN, and determined their activities at a range of phosphate concentrations. Pho4 affinity did not explain expression data well except under fully induced conditions. However, reporter activity was quantitatively well explained under all conditions by a model in which Cbf1 itself has modest activating activity, and Pho4 and Cbf1 compete with one another. Chromatin immunoprecipitation and computational analyses of natural Pho4 target genes, along with the activities of the reporter constructs, indicates that genes differ in their sensitivity to intermediate induction signals in part because of differences in their affinity for Cbf1. The induction sensitivity of both natural Pho4 target genes and reporter genes was well explained only by a model that assumes a role for Cbf1 in remodeling chromatin. Our analyses highlight the importance of taking into account the activities of related transcription factors in explaining system-wide gene expression data.

High-throughput identification of long-range regulatory elements and their target promoters in the human genome

High-throughput identification of long-range regulatory elements and their target promoters in the human genome:
Enhancer elements are essential for tissue-specific gene regulation during mammalian development. Although these regulatory elements are often distant from their target genes, they affect gene expression by recruiting transcription factors to specific promoter regions. Because of this long-range action, the annotation of enhancer element–target promoter pairs remains elusive. Here, we developed a novel analysis methodology that takes advantage of Hi-C data to comprehensively identify these interactions throughout the human genome. To do this, we used a geometric distribution-based model to identify DNA–DNA interaction hotspots that contact gene promoters with high confidence. We observed that these promoter-interacting hotspots significantly overlap with known enhancer-associated histone modifications and DNase I hypersensitive sites. Thus, we defined thousands of candidate enhancer elements by incorporating these features, and found that they have a significant propensity to be bound by p300, an enhancer binding transcription factor. Furthermore, we revealed that their target genes are significantly bound by RNA Polymerase II and demonstrate tissue-specific expression. Finally, we uncovered that these elements are generally found within 1 Mb of their targets, and often regulate multiple genes. In total, our study presents a novel high-throughput workflow for confident, genome-wide discovery of enhancer–target promoter pairs, which will significantly improve our understanding of these regulatory interactions.

Systematic dissection of regulatory motifs in 2000 predicted human enhancers using a massively parallel reporter assay [RESEARCH]

Systematic dissection of regulatory motifs in 2000 predicted human enhancers using a massively parallel reporter assay [RESEARCH]:
Genome-wide chromatin annotations have permitted the mapping of putative regulatory elements across multiple human cell types. However, their experimental dissection by directed regulatory motif disruption has remained unfeasible at the genome scale. Here, we use a massively parallel reporter assay (MPRA) to measure the transcriptional levels induced by 145-bp DNA segments centered on evolutionarily conserved regulatory motif instances within enhancer chromatin states. We select five predicted activators (HNF1, HNF4, FOXA, GATA, NFE2L2) and two predicted repressors (GFI1, ZFP161) and measure reporter expression in erythroleukemia (K562) and liver carcinoma (HepG2) cell lines. We test 2104 wild-type sequences and 3314 engineered enhancer variants containing targeted motif disruptions, each using 10 barcode tags and two replicates. The resulting data strongly confirm the enhancer activity and cell-type specificity of enhancer chromatin states, the ability of 145-bp segments to recapitulate both, the necessary role of regulatory motifs in enhancer function, and the complementary roles of activator and repressor motifs. We find statistically robust evidence that (1) disrupting the predicted activator motifs abolishes enhancer function, while silent or motif-improving changes maintain enhancer activity; (2) evolutionary conservation, nucleosome exclusion, binding of other factors, and strength of the motif match are predictive of enhancer activity; (3) scrambling repressor motifs leads to aberrant reporter expression in cell lines where the enhancers are usually inactive. Our results suggest a general strategy for deciphering cis-regulatory elements by systematic large-scale manipulation and provide quantitative enhancer activity measurements across thousands of constructs that can be mined to develop predictive models of gene expression.

Patterns of regulatory activity across diverse human cell types predict tissue identity, transcription factor binding, and long-range interactions [RESEARCH]

Patterns of regulatory activity across diverse human cell types predict tissue identity, transcription factor binding, and long-range interactions [RESEARCH]:
Regulatory elements recruit transcription factors that modulate gene expression distinctly across cell types, but the relationships among these remains elusive. To address this, we analyzed matched DNase-seq and gene expression data for 112 human samples representing 72 cell types. We first defined more than 1800 clusters of DNase I hypersensitive sites (DHSs) with similar tissue specificity of DNase-seq signal patterns. We then used these to uncover distinct associations between DHSs and promoters, CpG islands, conserved elements, and transcription factor motif enrichment. Motif analysis within clusters identified known and novel motifs in cell-type-specific and ubiquitous regulatory elements and supports a role for AP-1 regulating open chromatin. We developed a classifier that accurately predicts cell-type lineage based on only 43 DHSs and evaluated the tissue of origin for cancer cell types. A similar classifier identified three sex-specific loci on the X chromosome, including the XIST lincRNA locus. By correlating DNase I signal and gene expression, we predicted regulated genes for more than 500K DHSs. Finally, we introduce a web resource to enable researchers to use these results to explore these regulatory patterns and better understand how expression is modulated within and across human cell types.