What's in Your Genome?: Chapter 4: Pervasive Transcription (revised)

I'm working (slowly) on a book called What's in Your Genome?: 90% of your genome is junk! The first chapter is an introduction to genomes and DNA [What's in Your Genome? Chapter 1: Introducing Genomes ]. Chapter 2 is an overview of the human genome. It's a summary of known functional sequences and known junk DNA [What's in Your Genome? Chapter 2: The Big Picture]. Chapter 3 defines "genes" and describes protein-coding genes and alternative splicing [What's in Your Genome? Chapter 3: What Is a Gene?].

Chapter 4 is all about pervasive transcription and genes for functional noncoding RNAs. I've finally got a respectable draft of this chapter. This is an updated summary—the first version is at: What's in Your Genome? Chapter 4: Pervasive Transcription.

Chapter 4: Pervasive Transcription
How much of the genome is transcribed?

The latest data indicates that about 90% of the human genome is transcribed if you combine all the data from all the cell types that have been analyzed. This is about the same percentage that was reported by ENCODE in their preliminary study back in 2007 and about the same percentage they reported in the 2012 papers. Most of the transcripts are present in less than one copy per cell. Most of them are only found in one or two cell types. Most of them are not conserved in other species.

How do we know about pervasive transcription?

There are several technologies that are capable of detecting all the transcripts in a cell. The most powerful is RNA-Seq, a technique that copies RNAs into cDNA then performs massive parallel sequencing ("next gen" sequencing) on all the cDNAs. The sequences are then matched back to the reference genome to see which parts of the genome were transcribed. The technique is capable of detecting concentrations of less than one transcript per cell.

Different kinds of noncoding RNAs

There are ribosomal RNAs, tRNAs, and a variety of unique RNAs like those that are part of RNAse P, signal recognition particle etc. In addition there are six main classes of other noncoding RNAS in humans: small nuclear RNAs (snRNAs); small nucleolar RNAs (snoRNAs); microRNAs (miRNAs); short interfering RNAs (siRNAs); PIWI-interacting RNAs (piRNAs); and long noncoding RNAs (lncRNAs). There are many proven examples of functional RNAs in each of the main classes but there are also large numbers of putative members that may or may not be true functional noncoding RNAs.

        Box 4-1: Long noncoding RNAs (lncRNAs)

There are more than 100,000 transcripts identified as lncRNAS. Nobody knows how many of these are actually real functional lncRNAs and how many are just spurious transcripts. The best analyses suggest that less than 20,000 meet the minimum criteria for function and probably only a fraction of these are actually functional.

Understanding transcription

It's important to understand that transcription is an inherently messy process. Regulatory proteins and RNA polymerase initiation complexes will bind to thousands of sites in the human genome that have nothing to do with transcription of nearby genes.

        Box 4-2: Revisiting the Central Dogma

Many scientists and journalist believe that the discovery of massive numbers of noncoding RNAs overthrows the Central Dogma of Molecular Biology. They are wrong.

        Box 4-3: John Mattick proves his hypothesis?

John Mattick claims that the human genome produces tens of thousands of regulatory RNAs that are responsible for fine-tuning the expression of the protein-coding genes. He was given the 2012 Chen Award by the Human Genome Organization for "proving his hypothesis over the course of 18 years." He has not proven his hypothesis.

Antisense transcription

Some transcripts are complimentary to the coding strand in protein-coding genes. This is consistent with spurious transcription to yield junk RNA but many workers have suggested functional roles for most of these antisense RNAs.

What the scientific papers don't tell you

There are hundreds of scientific papers devoted to proving that most newly-discovered noncoding RNAs have a biological function. What they don't tell you is that most of these transcripts are present in concentrations that are inconsistent with function (<1 molecule per cell). They also don't tell you that conservation is the best measure of function and these transcripts are (mostly) not conserved. More importantly, the majority of these papers don't even mention the possibility that these transcripts could be junk RNA produced by spurious transcription. That's a serious omission—it means that science writers who report on this work are unaware of the controversy.

On the origin of new genes

Some scientists are willing to concede that most transcripts are just noise but they claim this is an adaptation for future evolution. The idea here is that the presence of these transcripts makes it easier to evolve new protein-coding genes. While it's true that such genes could evolve more readily in a genome full of noise and junk, this cannot be a reason for such a sloppy genome.

How do you determine function?

The best way to determine function is to take a single transcript and show that it has a demonstrable function. If you take a genomics approach, then the best way to narrow down the list is to concentrate on those transcripts that are present in sufficient concentrations and are conserved in related species. In the absence of evidence, the null hypothesis is junk.

Biochemistry is messy

We're used to the idea that errors in DNA replication give rise to mutations and mutations drive evolution. We're less used to the idea that all other biochemical processes have much higher error rates. This is true of highly specific enzymes and it's even more true of complex processes like transcription, RNA processing (splicing), and translation. The idea that transcription errors could give rise to spurious transcripts in large genomes is perfectly consistent with everything we know about such processes. In fact, it's inevitable that spurious transcripts will be common in such genomes.

        Box 4-4: The random genome project

Sean Eddy has proposed an experiment to establish a baseline level of spurious transcripts and to demonstrate that the null hypothesis is the best explanation for the majority of transcripts. He suggests that scientists construct a synthetic chromosome of random DNA sequences and insert it into a human cell line. The next step is to perform an ENCODE project on this DNA. He predicts that the methods will detect hundreds of transcription factor binding sites and transcripts.

Change your worldview

There are two ways of looking at biochemical processes within cells. The first imagines that everything has a function and cells are as fine-tuned and functional as a Swiss watch. The second imagines that biochemical processes are just good enough to do the job and there's lots of mistakes and sloppiness. The first worldview is inconsistent with the evidence. The second worldview is consistent with the evidence. If you are one of those people who think that cells and genomes are the products of adaptive excellence then it's time to change your worldview.

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