A combination of transcriptional and microRNA regulation improves the stability of the relative concentrations of target genes

It is well known that, under suitable conditions, microRNAs are able to fine tune the relative concentration of their targets to any desired value. We show that this function is particularly effective when one of the targets is a Transcription Factor (TF) which regulates the other targets. This combination defines a new class of feed-forward loops (FFLs) in which the microRNA plays the role of master regulator. Using both deterministic and stochastic equations we show that these FFLs are indeed able not only to fine-tune the TF/target ratio to any desired value as a function of the miRNA concentration but also, thanks to the peculiar topology of the circuit, to ensures the stability of this ratio against stochastic fluctuations. These two effects are due to the interplay between the direct transcriptional regulation and the indirect TF/Target interaction due to competition of TF and target for miRNA binding (the so called "sponge effect"). We then perform a genome wide search of these FFLs in the human regulatory network and show that they are characterizedby a very peculiar enrichment pattern. In particular they are strongly enriched in all the situations in which the TF and its target have to be precisely kept at the same concentration notwithstanding the environmental noise. As an example we discuss the FFL involving E2F1 as Transcription Factor, RB1 as target and miR-17 family as master regulator. These FFLs ensure a tight control of the E2F/RB ratio which in turns ensures the stability of the transition from the G0/G1 to the S phase in quiescent cells.Comment: 23 pages, 10 figure

La medición, a través de los censos de población y vivienda, del acceso y uso personal y desde el hogar a las tecnologías de la información y las comunicaciones

Incluye BibliografíaEn este artículo se aborda la importancia de la medición de las tecnologías de la información y las comunicaciones (TIC) a través de los censos de población; se indican algunas consideraciones para medir el acceso personal y desde los hogares a las TIC, así como su uso, y se analizan las fuentes de datos para el cálculo de indicadores acerca de las TIC. Posteriormente, se indaga sobre la disponibilidad de datos relativos a las TIC en los censos de la década de 2000, teniendo en cuenta los bienes de consumo que permiten captar datos relacionados con las TIC y el tipo de preguntas que se plantearon con ese fin. Al mismo tiempo, se examina la penetración de los diferentes bienes relacionados con las TIC, de acuerdo con los datos censales de 2000. Finalmente, con miras a los relevamientos de los censos de la década de 2010, se presenta una propuesta de preguntas que se podrían incorporar o corregir en los censos de población a fin de contar con indicadores comparables entre los países de América Latina y el Caribe

La medición de las tecnologías de información y comunicación a través de los censos de población y vivienda: una propuesta con miras a la ronda de censos de la década de 2010

Incluye Bibliografí

ENCODE_micFFL

List of micFFL circuits obtained from ENCODE dat

Data from: A combination of transcriptional and microRNA regulation improves the stability of the relative concentrations of target genes

It is well known that, under suitable conditions, microRNAs are able to fine tune the relative concentration of their targets to any desired value. We show that this function is particularly effective when one of the targets is a Transcription Factor (TF) which regulates the other targets. This combination defines a new class of feed-forward loops (FFLs) in which the microRNA plays the role of master regulator. Using both deterministic and stochastic equations, we show that these FFLs are indeed able not only to fine-tune the TF/target ratio to any desired value as a function of the miRNA concentration but also, thanks to the peculiar topology of the circuit, to ensure the stability of this ratio against stochastic fluctuations. These two effects are due to the interplay between the direct transcriptional regulation and the indirect TF/Target interaction due to competition of TF and target for miRNA binding (the so called “sponge effect”). We then perform a genome wide search of these FFLs in the human regulatory network and show that they are characterized by a very peculiar enrichment pattern. In particular, they are strongly enriched in all the situations in which the TF and its target have to be precisely kept at the same concentration notwithstanding the environmental noise. As an example we discuss the FFL involving E2F1 as Transcription Factor, RB1 as target and miR-17 family as master regulator. These FFLs ensure a tight control of the E2F/RB ratio which in turns ensures the stability of the transition from the G0/G1 to the S phase in quiescent cells

Jaspar_micFFL

LIst of micFFL circuits obtained from Jaspar PW

The ratio of the target and TF concentrations as a function of for the micFFL and the NM2 and NM3 null models for three values and of the Hill exponent.

<p>The ratio of the target and TF concentrations as a function of for the micFFL and the NM2 and NM3 null models for three values and of the Hill exponent.</p

Comparison of switch-on (A) and switch-off (B) response times between micFFL and direct regulation (NM1).

<p>Comparison of switch-on (A) and switch-off (B) response times between micFFL and direct regulation (NM1).</p

A. Schematic description of the circuits discussed in the paper.

<p>NM1: direct regulation; NM2: open motif in which the microRNA regulates only the transcription factor; NM3: open motif in which the microRNA regulates only the target; NM4: Open motif in which the microRNA regulates both the TF and the target but the TF-target link is missing; NM5, open motif in which two different microRNAs regulate separately the TF and the target. In the box we show the activactory micFFL whose deterministic and stochastic behavior we studied in the paper. <b>B</b>. Schematic view of the general miRNA controlled Feed Forward Loops (combining both activactory and repressive TF-target interactions) mined in the bioinformatic analysis discussed in the paper. <b>C</b>. Schematic description of the chemical reactions which must be taken into account to describe the miRNA-mediated feedforward loop with a miRNA-target titrative interaction.</p

A. Randomization of miRNA-target links.

<p>Distribution of the number of FFLs for 1000 simulations obtained with JASPAR TFs list and confirmed by at least 4 miRNA databases (Z = 49,4). <b>B</b>. Randomization of miRNA-target links. Distribution of the number of FFLs for 1000 simulations obtained with ENCODE TFs list and confirmed by at least 4 miRNA databases (Z = 23,3). <b>C</b>. Randomization of TF-target links. Distribution of the number of FFLs for 1000 simulations obtained with JASPAR TFs list and confirmed by at least 4 miRNA databases (Z = −20,8). <b>D</b>. Randomization of TF-target links. Distribution of the number of FFLs for 1000 simulations obtained with ENCODE TFs list and confirmed by at least 4 miRNA databases (Z = −18,1).</p