The complete sequence of a human Y chromosome

First I would like to state that human genetics are very, very complex and we still do not have a complete understanding of them. For example, only relatively recently has the field of epigenetics made major advancementa, which (broadly speaking) studies how a cell's behavior can be changed WITHOUT it's DNA being changed.[1] This brings into question the age-old questions about environmental impact vs genetic impact in even greater detail. Anyways, sidebar over.

No, we are not completely sure how many chromosomes play a role in determining eye color. However, we do have a pretty good guess. Most recent estimates I found out the number at 16. OCA2 and HERC2 have the largest impact on eye color, but, there are many OTHER genes that also have smaller impacts on eye color. [2] That article I cited is actually amazing. But, it does touch on some more advanced subjects that are more introductory college-level biology or AP Biology than standard high school bio e.g. Gene Regulation, introns and extrons, etc.

To answer your more general question, in my (admittedly only mildly less basic, introductory college-level biology) opinion, it is unlikely that we will, anytime soon, reach a point where anything in genetics can be completly, 100% definitive. This is not to say that we haven't made amazing advancements in the field of genetics and biology more broadly. BUT, it would be a mistake to take for granted the complexity of the human genome. There is most definitely things we still do not understand about the genome, and will not for some time.

But, practically speaking, while other genes may have impact on some simple phenotypic traits, such as eye color, we can generally make an accurate guess based on only a few genes. In eye color, for example, one study was able to predict eye color with only 6 genes with about ~75% accuracy. [3]

The crazy part is, sometimes the genes that effect the phenotypic trait, don't actually store genetic material that determines the trait. In other words, they don't DIRECTLY determine the trait at all. Rather, the only effect ORHER genes which then effect the expression of the trait more directly. You can imagine that this could become very complex very very quickly when you have multiple genes effecting other genes which effect other genes, not to mention accoubting for environmental and demographic baises when doing these studies and you begin to see why this genetics is such a difficult field of study.

Apologies for the long post and rambling. Hopefully I was still able to provide you with some mediocre introductory-collage-level biology

[1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2791696/ [2] https://www.nature.com/articles/jhg2010126 [3] https://doi.org/10.1016/j.cub.2009.01.027

I'd rather these ideas spread to others, potentially younger readers, than never have to read a trope again. I'm not sure it will ever change if we just accept it and never discuss it again.

The public Human Genome Project used a group of people but most of the sequence library was derived from a single individual in Buffalo, NY. The celera project also used a group of people but it was mostly Venter's genome

https://www.nytimes.com/2002/04/27/us/scientist-reveals-secr...

I believe more recent sequencing projects have used a wider pool of individuals. I think some projects pool all the individuals and sequence them together, while others sequence each individual separately. This isn't really so much of a problem since the large-scale structure is highly similar across all humans and we have developed sophisticated approaches to model the variations in individuals, see https://www.biomedcentral.com/collections/graphgenomes for an explanation of the "graph structure" used to reprsent alternatives in the reference, which can include individual single nucleobase differences, as well as more complex ones such as large deletions in one individual, to rearrangements and even inversions.

If you think like an ML engineer, the genome is a feature vector 3B bases (or 6B binary bits) long that is highly redundant (many sections contain repeats and other regions that are correlated to other regions), and the mapping between that feature vector and an individual's specific properties (their "phenotype", which could be their height at full maturity, or their eye color, or hair properties, or propensity to diseases, etc) is highly nonlinear.

If you had a list of all the genomes of all the people in the world, and all their phenotypes (height, eye color, hair type, etc), you could take all their genomes as input variables and treat all their phenotypes as output variables, and make embeddings or other models that mapped from genomes to phenotypes. The result would be a predictive model that could take a human genome, and spit out a prediction of what that person looks like and other details around them (up to the limits of heritability).

A good example is height. If you take a very large diverse sample of people, and sequence them, you will find that about 50% of the variance in height can be traced to the genomic sequence of that individual (other things, such as socioeconomic status, access to health care, pollution, etc, which are non-genomic, contribute as well). originally many geneticists believed that a small number of genes- tiny parts of the feature vector- would be the important features in the genome that explained height.

But it didn't turn out that way. Instead, height is a nonlinear function of thousands of different locations (either individual bases, entire genes, or other structures that vary between individuals) in the genome. This was less surprising to folks who are molecular biologists (mainly based on the mental models geneticists and MBers use to think about the mapping of genotype to phenotype), and we still don't have great mechanistic explanations of how each individual difference works in concert with all the others to lead to specific heights.

When I started out studying this some 35 years ago the problem sounded fairly simple, I assumed it would be easy to find the place in my genome that led to my funny shaped (inherited) nose, but the more I learn about genomics and phenotypes, the more I appreciate that the problem is unbelievably complex, and really well suited to large datasets and machine learning. All the pharma have petabytes of genome sequences in the cloud that they try hard to analyze but the results are mixed.

I spent my entire thesis working on ATGCAAAT, by the way. https://en.wikipedia.org/wiki/Octamer_transcription_factor is a family of proteins that are incredibly important during growth and development. Your genome is sprinkled with locations that contain that sequence- or ones like it- that are used to regulate the expression of proteins to carry out the development plan.

> That is if we transfer the DNA to an advanced alien civilization - would they be able to make a human.

You'd need a cell to start the process, with the various nucleic acids distributed correctly and proteins/energy with which to create further proteins using the information encoded by the DNA. Thus the civilization would need information about cells and a set of building blocks before being able to use the DNA.