7 ms·

I looked over the paper pretty quickly, but on a quick read it looks really nice. The data are really impressive, and they seemed to have pulled out really inte

by skosuri 13y ago

I looked over the paper pretty quickly, but on a quick read it looks really nice. The data are really impressive, and they seemed to have pulled out really interesting trends for how transcription factors are affecting coding sequence. Furthermore, they map how variants found across the various cell lines they used (81!) to show that these variants actually are causal for transcription factor binding changes. For those saying this is not a big deal, or is obvious; it is, and is not (respectively). It's been pretty clear for some time that codon choice is not random (hence codon optimization is useful when taking a gene from one organism to another), and over the last few years it's also been clear that codon bias can be evolutionarily constrained. For a while, it mostly thought to be based on tRNA levels (basically anticodons). However, it's been increasingly clear that there are other constraints to protein coding sequences than just the decoded protein sequence (aka the genetic code). For example, we published a paper a few weeks back [1] showing that in bacteria (and probably higher organisms), the N-terminus of genes has a lot of rare codons and this is due to other constraints such as relieving mRNA structure to allow better translation of proteins. I think in the coming years, we will find that other regulatory elements also shape this code, including sequences that control splicing, small RNAs, mRNA degradation and transport, et cetera Anyways, it's a pretty fun time in biology. The tools we have now make studies that were ridiculously impossible just a few years ago, a reality for an individual lab. I can't wait to see what the next few years bring. [1] http://arep.med.harvard.edu/pdf/Goodman_Sci_13.pdf\ http://arep.med.harvard.edu/pdf/Goodman_Sci_13.pdf\ EDIT: Since my comment has hijacked the most useful comment linking to the original study, I'll link to the comment here: https://news.ycombinator.com/item?id=6897122 https://news.ycombinator.com/item?id=6897122

daemonk 13y ago
Agreed. It's an interesting trend. I also just skimmed over it; however, I wonder how significant is their initial TF binding occupancy data. There are a bunch of papers recently that looked at binding sites and found that they don't really correlate well with transcription. The cell is just a stochastic bag of molecules. TFs bind whereever they can. I wonder if they are just seeing noise.
- skosuri 13y ago
  Fig 1E seems promising, as it shows that the bound bases tend to be more conserved. That said, you are right that as far I could tell there were no direct measurements of transcriptional effects. Either way, it was a good read, and brought up a bunch of interesting questions to figure out next.
- Estragon 13y ago
  Yes, so much bullshit has been published over the last decade as a result of artifacts in the measurement of TFBS that you have to be skeptical.
sounds 13y ago
So I admit I haven't skimmed the paper yet. Is it as comprehensive a map of DNA-encoded transcription factors as can be had? I ask because I can understand the way DNA codes for proteins–as a software-head–but the article definitely gets me with this "second language" and I want to think more about how the overlapping meanings might have developed (and how that might be apply to digital code). Other than "start," "stop," "intron," "exon," and "suppress" (aka disable), what do the transcription factors do in terms of actual cell proteins? I admit that a really detailed description of cell protein processes will be beyond my depth. :)
- waterlesscloud 13y ago
  I know next to nothing about this field, but I just sort of brute-forced my way through the OP paper with the help of wikipedia. It's a painful process. :-) But it has piqued my curiosity about the field. Are there any good introductory books/websites for the curious layman to get a grounding?
  - skosuri 13y ago
    Depends on what level. Wikipedia is actually quite good for this sort of thing. The classic book as a basic overview of molecular biology in general is the Molecular Biology of the Cell [1]. A really cool website to look at on cutting edge studies such as these is the ENCODE consortium's publications in Nature [2]. They simultaneously published 30 papers last year, and this is a really cool meta page that explains the ENCODE project and what they found. [1]. http://www.ncbi.nlm.nih.gov/books/NBK21054/ http://www.ncbi.nlm.nih.gov/books/NBK21054/ [2]. http://www.nature.com/encode/ http://www.nature.com/encode/
  - skosuri 13y ago
    Oh and for Codon usage in general, a really good review can be found here [1]. [1]. http://people.cs.vt.edu/~heath/VTMENA/CodonBias/PlotkinKudla_NatureReviewsGenetics_2011.pdf http://people.cs.vt.edu/~heath/VTMENA/CodonBias/PlotkinKudla...
  - mvleming 13y ago
    The Machinery of Life [1] is a fantastic book, I was one of those curious laymen and boy did it saturate my thirst for learning about microbiology. I think it's close to the time I read it again. [1] http://www.amazon.com/The-Machinery-Life-David-Goodsell/dp/0387849246 http://www.amazon.com/The-Machinery-Life-David-Goodsell/dp/0... Edit: Whoops, no Markdown support. Revised link to use footnote.
atmosx 13y ago
Do we have free access to this paper? I would like to read it, if possible.
timr 13y ago
"over the last few years it's also been clear that codon bias can be evolutionarily constrained. For a while, it mostly thought to be based on tRNA levels (basically anticodons). However, it's been increasingly clear that there are other constraints to protein coding sequences than just the decoded protein sequence (aka the genetic code)." This is a much older question than the last few years -- it's one of those "evergreen" questions that's been around for almost as long as we've been able to do statistics on codon prevalence. You'll see hand-wavy explanations for differences in codon usage in really old textbooks. The tRNA one is a particularly old chestnut -- I think I read about that one in my first undergrad course on molecular biology.

by skosuri 13y ago

daemonk 13y ago

Agreed. It's an interesting trend. I also just skimmed over it; however, I wonder how significant is their initial TF binding occupancy data. There are a bunch of papers recently that looked at binding sites and found that they don't really correlate well with transcription. The cell is just a stochastic bag of molecules. TFs bind whereever they can. I wonder if they are just seeing noise.

skosuri 13y ago
Fig 1E seems promising, as it shows that the bound bases tend to be more conserved. That said, you are right that as far I could tell there were no direct measurements of transcriptional effects. Either way, it was a good read, and brought up a bunch of interesting questions to figure out next.
Estragon 13y ago
Yes, so much bullshit has been published over the last decade as a result of artifacts in the measurement of TFBS that you have to be skeptical.

sounds 13y ago

So I admit I haven't skimmed the paper yet. Is it as comprehensive a map of DNA-encoded transcription factors as can be had? I ask because I can understand the way DNA codes for proteins–as a software-head–but the article definitely gets me with this "second language" and I want to think more about how the overlapping meanings might have developed (and how that might be apply to digital code). Other than "start," "stop," "intron," "exon," and "suppress" (aka disable), what do the transcription factors do in terms of actual cell proteins? I admit that a really detailed description of cell protein processes will be beyond my depth. :)

waterlesscloud 13y ago
I know next to nothing about this field, but I just sort of brute-forced my way through the OP paper with the help of wikipedia. It's a painful process. :-) But it has piqued my curiosity about the field. Are there any good introductory books/websites for the curious layman to get a grounding?
- skosuri 13y ago
  Depends on what level. Wikipedia is actually quite good for this sort of thing. The classic book as a basic overview of molecular biology in general is the Molecular Biology of the Cell [1]. A really cool website to look at on cutting edge studies such as these is the ENCODE consortium's publications in Nature [2]. They simultaneously published 30 papers last year, and this is a really cool meta page that explains the ENCODE project and what they found. [1]. http://www.ncbi.nlm.nih.gov/books/NBK21054/ http://www.ncbi.nlm.nih.gov/books/NBK21054/ [2]. http://www.nature.com/encode/ http://www.nature.com/encode/
- skosuri 13y ago
  Oh and for Codon usage in general, a really good review can be found here [1]. [1]. http://people.cs.vt.edu/~heath/VTMENA/CodonBias/PlotkinKudla_NatureReviewsGenetics_2011.pdf http://people.cs.vt.edu/~heath/VTMENA/CodonBias/PlotkinKudla...
- mvleming 13y ago
  The Machinery of Life [1] is a fantastic book, I was one of those curious laymen and boy did it saturate my thirst for learning about microbiology. I think it's close to the time I read it again. [1] http://www.amazon.com/The-Machinery-Life-David-Goodsell/dp/0387849246 http://www.amazon.com/The-Machinery-Life-David-Goodsell/dp/0... Edit: Whoops, no Markdown support. Revised link to use footnote.

atmosx 13y ago

Do we have free access to this paper? I would like to read it, if possible.

timr 13y ago

"over the last few years it's also been clear that codon bias can be evolutionarily constrained. For a while, it mostly thought to be based on tRNA levels (basically anticodons). However, it's been increasingly clear that there are other constraints to protein coding sequences than just the decoded protein sequence (aka the genetic code)." This is a much older question than the last few years -- it's one of those "evergreen" questions that's been around for almost as long as we've been able to do statistics on codon prevalence. You'll see hand-wavy explanations for differences in codon usage in really old textbooks. The tRNA one is a particularly old chestnut -- I think I read about that one in my first undergrad course on molecular biology.