About biotranslator

I'm a graduate student interested in Biology, Bioinformatics, TFs, cis-elements, Promoters, Java, Linux, Gene Regulatory Networks, Plant genomics, NGS, Scientific visualizations between others

The B3 Superfamily of Plant Transcription Factors

The B3 superfamily of Transcription Factors has only been reported in the Viridiplantae kingdom from Chlorophyta to gymnosperms and angiosperms. Several phylogenetic analysis of the B3 superfamily distinguish between four to five structural families.
The ARF, REV, REM and LAV (which can be subdivided into VAL and ABI3/LEC2) or the ARF, REV, REM, VAL/HSI and ABI3/LEC2 (PMID:18986826 ; 22302388 ; 19503786 ; 23377560). The B3 superfamily appears to have evolved via gene duplication from a single lineage, as observed today in Chlorophyta, with the most “ancient” model exhibiting similarity to the VAL/HSI gene family in multicellular plants.

B3 families can be described with clear rules combining required and forbidden protein domains.
ARF family: Contains B3 and the Auxin Response Factor domains.
REV family: Contains B3 and AP2 domains.
REM family: Contains several copies of the B3 domain forbidden domains are Auxin Response Factor, AP2 and CW-type Zinc Finger
VAL/HSI family: Contains B3 domain and a CW-type Zinc Finger domain at the C-terminus.
ABI3/LEC2 family: Contains one B3 domain forbidden domains are Auxin Response Factor, AP2 and CW-type Zinc Finger

The B3 binding domain interacts with the major groove of DNA (PMID: 15548737). However, not much is known about the cis-element recognized in each of the families. Some particular preferences are know, for instance the maize VP1 is capable of recognizes the Sph box at the C1 promoter (PMID: 9165754). In rice a member of this family is related to the iron (Fe) deficiency response by binding the IDE1 cis-element (PMID: 19737364). The IRON DEFICIENCY RESPONSIVE CIS-ACTING ELEMENT BIDING FACTOR 1 (IDEF1) gene is expressed in constitutively expressed during both vegetative and reproductive stages (PMID: 20197292). Additionally IDEF1 is able to regulate by binding to the RY element when participating of seed development regulation.

I have estimated gene content in each of the currently available monocots genomes and basically I am looking for contrasting my results with the studies previously done in dictos where others have suggested a non uniform amplification of the B3 superfamily (i.e., not all the families have equally expanded).


South America : Google autocompleted


Inspired by a Bill the Lizard’s blog post Why is [programming language] so … ? which was itself inspired by an infographic called Why is [state] so … ?, I decided to try something similar with South America countries (no map, yes screenshots).

Back in school (pre-Wikipedia times), during Geography classes, I was taught that South America is one region of THE America continent and not a continent itself as nowadays Wikipedia says. Also, back in school, I was taught that South America includes twelve countries, in alphabetical order: Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Guyana, Paraguay, Peru, Suriname, Uruguay and Venezuela.

As Colombiana and currently studying abroad, I keep facing truths and myths perceived as realities by people from everywhere. Because nasty myths came often than truths, I keep wondering, How were spread so many wrong facts about us? it could be Google’s fault (why not?). Anyway judge by yourself

Remember, chance are that you get something different when you type things.

Why [Argentina] is -> The best, awesome, the best place to live, a developing country.
Why is [Argentina] so -> Expensive, european, racist, poor.

Why is [Bolivia] so -> Poor, Cold
Why [Bolivia] is -> Poor

Why [Brazil] is -> Emergent market, expensive, dangerous, important
Why is [Brazil] so -> Growing fast, Economy doing well, expensive, dangerous

Why [Chile] is -> Very diverse country, better than Argentina, so long, called chile
Why is [Chile] so -> Long, rich, dry

Why [Colombia] is -> Awesome, the best, dangerous
Why is [Colombia] so -> Violent, dangerous, poor, corrupt

Why [Ecuador] is -> The best place to live, important
Why is [Ecuador] so -> Poor, cheap, cold

Why [Guyana] is -> Part of the caribbean, a third world country
Why is [Guyana] so -> Poor, sparsely populated, expensive

Why [Paraguay] is -> Suspended from mercosur, poor, a developing country
Why is [Paraguay] so -> Poor, growing so fast

Why [Peru] is -> Poor, important, the best, bad
Why is [Peru] so -> Dry, poor, important

Why [Suriname] is -> Sparsely populated
Why is [Suriname] so -> Sparsely populated, poor

Why [Uruguay] is -> Rich country, awesome, good at soccer, a developing country
Why is [Uruguay] so -> Liberal, expensive, good at soccer

Why [Venezuela] is -> Poor, divided, not a democracy, famous
Why is [Venezuela] so -> Poor, corrupt, dangerous, violent

A Maize Pan-Transcriptome

Here I am adding to my neverending maize-related wish-list.

Based on the amount of RNA-Seq/Microarray data generated, The maize community should have significant amount of information to start compiling a Pan-transcriptome for some tissues/developmental stages of interest.

I know that some researchers at Michigan State University (Hansey/Hirsch CN) at have already started, but wondering if someone out there (Gramene? MaizeGDB?) is gathering a good portion of the information generated by the community and building a Pan-transcriptome of Maize. So far, Hansey and collaborators have generated and analyzed RNA-Seq from seedlings of 21 maize lines including the reference maize inbred line B73. So, here I will point out at references/resources that could be used to build a Zea mays Pan-transcriptome while I wish for the 10,001 maize genomes project to happen.

1. Wang X, Elling AA, Li X, Li N, Peng Z, He G, Sun H, Qi Y, Liu XS, Deng XW. Genome-wide and organ-specific landscapes of epigenetic modifications and their relationships to mRNA and small RNA transcriptomes in maize. Plant Cell 21(4):1053-69 (2009). #B73
2. Eveland AL, Satoh-Nagasawa N, Goldshmidt A, Meyer S, Beatty M, Sakai H, Ware D, Jackson D. Digital gene expression signatures for maize development. Plant Physiol. 154(3):1024-39 (2010). #B73
3. Li P, Ponnala L, Gandotra N, Wang L, Si Y, Tausta SL, Kebrom TH, Provart N, Patel R, Myers CR, Reidel EJ, Turgeon R, Liu P, Sun Q, Nelson T, Brutnell TP. The developmental dynamics of the maize leaf transcriptome. Nat Genet 42(12):1060-7 (2010). #B73
4. Sekhon RS, Lin H, Childs KL, Hansey CN, Buell CR, de Leon N, Kaeppler SM. Genome-wide atlas of transcription during maize development. Plant J 66(4):553-63 (2011).
5. Davidson, R. M. et al. Utility of RNA sequencing for analysis of maize reproductive transcriptomes. Plant Genome 4, 191–203 (2011). #B73
6. Waters AJ, Makarevitch I, Eichten SR, Swanson-Wagner RA, Yeh CT, Xu W, Schnable PS, Vaughn MW, Gehring M, Springer NM. Parent-of-origin effects on gene expression and DNA methylation in the maize endosperm. Plant Cell 23(12):4221-33 (2011) #B73xMo17
7. Zhang M, Zhao H, Xie S, Chen J, Xu Y, Wang K, Zhao H, Guan H, Hu X, Jiao Y, Song W, Lai J. Extensive, clustered parental imprinting of protein-coding and noncoding RNAs in developing maize endosperm. Proc Natl Acad Sci U S A. 108(50):20042-7 (2011) #B73xMo17
8. Hansey CN, Vaillancourt B, Sekhon RS, de Leon N, Kaeppler SM, Buell CR. Maize (Zea mays L.) genome diversity as revealed by RNA-sequencing. PLoS One 7(3):e33071 (2012).
9. Chang YM, Liu WY, Shih AC, Shen MN, Lu CH, Lu MY, Yang HW, Wang TY, Chen SC, Chen SM, Li WH, Ku MS. Characterizing regulatory and functional differentiation between maize mesophyll and bundle sheath cells by transcriptomic analysis. Plant Physiol 160(1):165-77 (2012). #B73
10. Sekhon RS, Briskine R, Hirsch CN, Myers CL, Springer NM, Buell CR, de Leon N, Kaeppler SM. Maize gene atlas developed by RNA sequencing and comparative evaluation of transcriptomes based on RNA sequencing and microarrays. PLoS One 8(4):e61005 (2013). #B73
11. Fu J, Cheng Y, Linghu J, Yang X, Kang L, Zhang Z, Zhang J, He C, Du X, Peng Z, Wang B, Zhai L, Dai C, Xu J, Wang W, Li X, Zheng J, Chen L, Luo L, Liu J, Qian X, Yan J, Wang J, Wang G. RNA sequencing reveals the complex regulatory network in the maize kernel. Nat Commun 4:2832 (2013).
12. Li L, Petsch K, Shimizu R, Liu S, Xu WW, Ying K, Yu J, Scanlon MJ, Schnable PS, Timmermans MC, Springer NM, Muehlbauer GJ. Mendelian and non-Mendelian regulation of gene expression in maize. PLoS Genet 9(1):e1003202 (2013). #B73xMo17
13. Fordyce SL, Ávila-Arcos MC, Rasmussen M, Cappellini E, Romero-Navarro JA, Wales N, Alquezar-Planas DE, Penfield S, Brown TA, Vielle-Calzada JP, Montiel R, Jørgensen T, Odegaard N, Jacobs M, Arriaza B, Higham TF, Ramsey CB, Willerslev E, Gilbert MT. Deep sequencing of RNA from ancient maize kernels. PLoS One 8(1):e50961 (2013).
14. He G, Chen B, Wang X, Li X, Li J, He H, Yang M, Lu L, Qi Y, Wang X, Wang Deng X. Conservation and divergence of transcriptomic and epigenomic variation in maize hybrids. Genome Biol 14(6):R57 (2013) #B73xMo17
15. Xin M, Yang R, Li G, Chen H, Laurie J, Ma C, Wang D, Yao Y, Larkins BA, Sun Q, Yadegari R, Wang X, Ni Z. Dynamic expression of imprinted genes associates with maternally controlled nutrient allocation during maize endosperm development. Plant Cell 25(9):3212-27 (2013). #B73xMo17

Thanks to the Maize eFP Browser we can access the Sekhon et al., 2011 microarray-data and the Li et al., 2010 RNA-Seq data as informative and beautiful pictograms. So, just imagine having the same information discriminated per allele/inbred line.

Finally, did you notice that, reference 10 here, was a popular one in the twitterverse back in May/2013.

My notes about Brassinosteroid Signaling Network

Crystal structure of BAK1 phosphorylated cytoplasmic domain (CD) in complex with AMP-PNP as found in Arabidopsis thaliana
Yan L, Ma Y, Liu D, Wei X, Sun Y, Chen X, Zhao H, Zhou J, Wang Z, Shui W, Lou Z. 2012. Structural basis for the impact of phosphorylation on the activation of plant receptor-like kinase BAK1. Cell Res. 22(8):1304-8. doi: 10.1038/cr.2012.74

Brassinosteroid (BR) Gene Regulatory Network :

1. Sun, Y. et al. Integration of brassinosteroid signal transduction with the transcription network for plant growth regulation in Arabidopsis. Developmental Cell 19, 765–777 (2010).
2. Cheminant, S. et al. DELLAs regulate chlorophyll and carotenoid biosynthesis to prevent photooxidative damage during seedling deetiolation in Arabidopsis. Plant Cell 23, 1849–1860 (2011).
3. Ye, H., Li, L., Guo, H. & Yin, Y. MYBL2 is a substrate of GSK3-like kinase BIN2 and acts as a corepressor of BES1 in brassinosteroid signaling pathway in Arabidopsis. Proc. Natl. Acad. Sci. U.S.A. 109, 20142–20147 (2012).
4. Wang, Z.-Y., Bai, M.-Y., Oh, E. & Zhu, J.-Y. Brassinosteroid signaling network and regulation of photomorphogenesis. Annu. Rev. Genet. 46, 701–724 (2012).
5. Oh, M.-H., Wang, X., Clouse, S. D. & Huber, S. C. Deactivation of the Arabidopsis BRASSINOSTEROID INSENSITIVE 1 (BRI1) receptor kinase by autophosphorylation within the glycine-rich loop. Proc. Natl. Acad. Sci. U.S.A. 109, 327–332 (2012).
6. Oh, E., Zhu, J.-Y. & Wang, Z.-Y. Interaction between BZR1 and PIF4 integrates brassinosteroid and environmental responses. Nat. Cell Biol. 14, 802–809 (2012).
7. Kumar, S. V. et al. Transcription factor PIF4 controls the thermosensory activation of flowering. Nature 484, 242–245 (2012).
8. Bai, M.-Y. et al. Brassinosteroid, gibberellin and phytochrome impinge on a common transcription module in Arabidopsis. Nat. Cell Biol. 14, 810–817 (2012).
9. Daviere, J. M. & Achard, P. Gibberellin signaling in plants. Development 140, 1147–1151 (2013).
10. Sakamoto, T., Morinaka, Y., Inukai, Y., Kitano, H. & Fujioka, S. Auxin signal transcription factor regulates expression of the brassinosteroid receptor gene in rice. Plant J. 73, 676–688 (2013).

Plus two bonus from December, 2013

11.  Zhang, D et al., Transcription factor HAT1 is phosphorylated by BIN2 kinase and mediates brassinosteroid repressed gene expression in Arabidopsis. Plant J. (2013).
12. Cheon J, Fujioka S, Dilkes BP, Choe S. Brassinosteroids Regulate Plant Growth through Distinct Signaling Pathways in Selaginella and Arabidopsis. PLoS One. 8(12):e81938 (2013).

BTW, the last paper [reference 12] is quite popular in the twitterverse those days