The vast majority have no impact, but obviously some do. Are you suggesting that some of the biological differences between humans and chimpanzees have no genetic basis? I.e. they are miraculous…?
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What’s higher order physics?
Natural causation was there before we were. It has nothing to do with being perceived.
A mind thinking everything up for eternity is infinitely more complex than everything it’s thinking. The stuff being its own ground of being, infinitely parsimoniously less. Your erroneous mere assertions are driven by the irrelevant, grandiose desire to be significant.
We just can’t get over the fact that bags of enzymes are realising that they are bags of enzymes.
I can’t tell if you’re making a positive claim here or not. We have every reason to think that the physical differences between humans and chimps are caused by the small subset of genetic differences that are functional, and we have no reason to think otherwise. We only know what some of those functional genetic differences are, but that’s just because we only don’t understand what a lot of the differences do. It is again exactly analogous to the differences between any two individual humans.
Unsequenced and unaligned portions of the genome are generally highly repetitive sequence, the precise composition of which is unlikely to have any effect on function. In any case, so what? There is no single answer to how different the two genomes are. What biological question are you trying to answer? In terms of evolution, as we have sequenced and aligned more and more of the genomes, we continue to see differences that look exactly like accumulated mutation. Is there any reason at all to think that the situation will change going forward?
You haven’t given any basis for your doubtfulness.
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If information theory has something useful to say as a model of duplication followed by divergence we’ll be happy to use it. If it doesn’t, we won’t. Either way, the process happens and has functional effects.
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Just like “information” in computer science is a useful metaphor for electrical interactions that do things?
If you’re a solid-state physicist, yes, and you’ll ignore the metaphor any time it isn’t apt. If you’re a computer programmer, you’re interested only in the electrical interactions that do act like the metaphor and you’ll ignore (or get a technician to try to fix) any that don’t.
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I will try an respond to your various points:
1 I’m not sure where you get 3.2%, since the paper just says about 3%. Maybe in the supplemental info,
Yes, the exact number is given in supplemental info as 3.2%.
In any case, you should be taking half of that number, since that’s the amount of unique sequence in each genome.
The paper seems to be clear that this is the amount of “unique sequence” difference (maybe I missed something).
3 The 7% is not a thing – it represents the more or less arbitrary length given to the genome assembly, including large blocks whose size is poorly known. It is not in any way a measurement of the length of the two genomes. So remove that.
This is the current best estimate of genome size that we have.
4 I have no idea what this means, or what the reference is to. It really doesn’t make any sense, since genes are already included in the numbers already listed.
Sorry about the incomplete reference, here it is; Demuth et al 2006:
Where they write:
“Our results imply that humans and chimpanzees differ by at least 6% (1,418 of 22,000 genes) in their complement of genes, which stands in stark contrast to the oft-cited 1.5% difference (…)”
So I would suggest that we have some pretty significant differences which may not be additive. In fact given what we know about the genome, the whole might well be greater than the sum of the parts. At least one of these differences is probably not best expressed as a percentage. I am referring to the segmental duplications. The authors of the paper I cited write that:
“Almost all of the most extreme differences relate to changes in chromosome structure, including the emergence of African great ape subterminal heterochromatin. Nevertheless, base per base, large segmental duplication events have had a greater impact (2.7%) in altering the genomic landscape of these two species than single-base-pair substitution.”
(As a YEC, I do not accept that differences “emerged”. I would say that they are there as a result of created differences between apes and humans.)
Nevertheless, I think that the significance lies in the fact the genomic landscape is different. The landscape has an effect on gene expression and the effects on the phenotype could be quite significant.
Overall, I think the real challenge for an evolutionist is to explain how these difference arose and became fixed in the generally accepted evolutionary timescale.
Can gradual (“Darwinian”) accumulation of small changes acted on by natural selection account for all the above differences? Or were apes and humans created different?
Yes I understand the argument is a “heads I win, tails you lose” variety.
What argument?
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The information argument being made regarding duplication. It is convenient to switch information definitions, i.e. from Shannon to Kolmogorov, so in one case duplication doubles info content to debunk ID, and in the second case information content remains the same so as to support common descent.
In all this debunking and confirmation it would be nice for arguers to use formal definition of what information metric is used, so it is clear when we are swapping and there is less confusion.
AA != A unless A={0,1} in multiplication. not a series.
The paper (of which I was an author, by the way) is quite clear that ~1.5% is the amount of unique sequence in each genome. You don’t get a meaningful number by adding them. Take these two sequences:
ACGTACGTGGGGGGGG
and
ACGTACGTTTTTTTTT
Each has 50% unique sequence. If you add those together, you get 100% – what’s 100% different about them?
I have seen no recent studies of the relative size of the genomes, and you provided no references. The genome assemblies are not meant to represent precise measures of actual genome size, and physical measurements of genome size haven’t allowed any such conclusion, at least not that I’m aware of. The situation for physical measurements (as of 2015) was nicely summarized here.
Thanks. There’s good reason to doubt such early attempts to identify differences in gene complement between species, given the incompleteness of genomes and the imperfection of gene annotation: see here for details. In any case, we’re not talking about 6% of the genome here – we’re talking about 6% of genes, which make up less than 2% of the genome.
The differences continue to be what I previously stated.
Sure – segmental duplications involve more sequence than single-base substitutions. That’s also true of differences between individual humans.
What problem do you see with the timescale? Why do the differences look so much like a bunch of mutations if they’re not?
No, it can’t. Most of the differences are neutral and not acted on by natural selection, and some of the changes (in terms of amount of sequence) are not small. In that respect they are (again) exactly like differences between individual humans. I haven’t seen anything here that doesn’t look like the product of evolution.
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Sorry, I was talking about biologists doing biology. How ‘information’ is deployed in responding to attacks on evolution varies with the content of the attack and with the knowledge of the participants.
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What information metric do biologists doing biology use?
Hmm! Your example above is clear but I am still confused. In Supplementary Notes: Genome Evolution (2005-03-03208), I read under the heading,
Estimate of indel basepairs:
“The total number of insertion/deletion bases between chimpanzee and human was estimated as follows. The number of unaligned bases (“insertions” < 15 kb) within sequence scaffolds was 31.78 Mb (2347812 events) and 35.18 Mb (2741577 events) for human and chimpanzee respectively. The number of chimpanzee deletions >15 kb was estimated by paired-end sequence to be 8.2 Mb (163 events). 5.9 Mb of chimpanzee sequence could not be mapped back to human using low sequence threshold cutoffs. We estimate a similar amount of such sequence for human. In total, we estimate 95.2 Mb (31.78+35.18+5.9 2 + 8.22) or 3.2% difference between chimp and human.”
Are you saying that the 3.2% number is not meaningful?
I should have been more careful! My calculations were based on the relative number of bases which are published here:
https://www.ncbi.nlm.nih.gov/genome/browse/#!/overview/
So we could argue about whether of not this is the “size of the genome” or the number of “bits of information” (putting on my tin hat) in each genome.
Mostly none. When they do use one, they use whatever provides a suitable framework for answering whatever question it is they’re asking. For example, AIC (and less commonly BIC) are often used for model comparison. Information for the kind of application you seem to be interested in – calculating the information present in a piece of sequence – is rarely used.
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Or we could ask NCBI what they’re supposed to mean – which I did in 2009. The response from NCBI: ‘The ~8% relates to the length of the reference assembly and not the actual genome length. There are gaps and unplaced contigs that “extend” the assembly but are not meant to represent the actual length of the genome.’
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What is a fallen creation? A vase knocked off a shelf?
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Here is one “problem”. How does a new protein coding gene arise in humans and become fixed in a population if there is no selective advantage, given the time available and the random nature of mutation?
There may be ~1000 such genes (allowing for the possibility that the number published by Demuth et al, may be an overestimate) which are now fixed in the human genome.