Dumb question: is there a x_chromosome.txt with the sequence in order? Why do geneticists not talk about it this way?

The article doesn’t mention but now I’m curious what kind of read length and error rate they are achieving. This could have huge impacts across all sequencing.

In a simple English, could someone explain why is this good and what does it all mean?

I thought the human genome was mapped in 2003, when the Human Genome Project wrapped up: https://en.wikipedia.org/wiki/Human_Genome_Project

What's different about this?

There is a space missing in the title ("X chromosome").

So how do you actually isolate one chromosome to sequence it?

When I read the title my first thought was "Scientists found complete assembly language of human Xchromosome".

go banana slugs!

The press release is better than the link:

https://www.genome.gov/news/news-release/NHGRI-researchers-g...

It looks like they're using Oxford nanopore and PacBio sequencing technologies for the long reads. These are two up-and-coming sequencing technologies focused on extremely long reads. My understanding of both is that their error rates on individual base pairs are too high to reliably determine the actual sequence on their own (something like 15% error rates). Typically the long reads from these technologies are used as a "scaffold" to resolve the large-scale structure of a DNA sequence, while another sequencing technology, usually Illumina, is used to resolve the actual sequence. (Illumina produces short reads, but it produces a lot of them, and the error rate is much lower, about 1%-5%.) In addition, since PacBio and Oxford Nanopore are very different technologies, I'm guessing that they probably have different "error profiles", so they probably partially cover for each others' deficiencies when you use both of them at the same time.

Note: Don't take any of the specific numbers above as gospel. These technologies develop extremely quickly, so it's quite likely that my knowledge of typical error rates is out of date.

In any case, here's the relevant quote from the original link (to phys.org), before it was changed to the less technical press release, which doesn't mention any specific technologies used:

"The new project built on that effort, combining nanopore sequencing with other sequencing technologies from PacBio and Illumina, and optical maps from BioNano Genomics. Using these technologies, the team produced a whole-genome assembly that exceeds all prior human genome assemblies in terms of continuity, completeness, and accuracy, even surpassing the current human reference genome by some metrics."

The "ultra long" nanopore reads used in this study are often greater than 100kbp in length and occasionally up to 1Mbp

In the movie he mentions Oxford Nanopore tech and using reads of 100.000 to 1.000.000 base pairs

From the article: "Repetitive DNA sequences are common throughout the genome and have always posed a challenge for sequencing because most technologies produce relatively short "reads" of the sequence, which then have to be pieced together like a jigsaw puzzle to assemble the genome. Repetitive sequences yield lots of short reads that look almost identical, like a large expanse of blue sky in a puzzle, with no clues to how the pieces fit together or how many repeats there are. . . . Filling in the remaining gaps in the human genome sequence opens up new regions of the genome where researchers can search for associations between sequence variations and disease and for other clues to important questions about human biology and evolution."

Or, to make this more simple: Finding the complete DNA sequence of chromosomes is difficult. That's because some parts of the sequence are highly repetitive. Using a new type of lab machine, the scientists were able sequence the repetitive parts of the X chromosome. This gives a more complete picture of the X chromosome. And that can help scientists fight diseases and understand human biology better.

Imagine you have a bunch of aerial photographs that you're trying to assemble into one big mosaic of the entire region by matching up the overlaps on the edges. The problem is, this is a desert, and significant portions of the region are just flat expanses of empty sand, so all the aerial photographs from those regions look pretty much identical. Even worse, there's several of these flat sandy regions in the area, so you don't even know which region those photos came from.

So despite having taken multiple photos of every square inch of land in your target area, there's no way you can assemble them into one big image just by matching up the overlaps. Without a source of larger-scale information about the region, like a satellite photograph or GPS coordinates for the photos, you have no way of knowing how wide that desert is. All you know is that it's wider than one or two photographs.

This is essentially same problem that current genome assemblies have: there are regions of repetitive sequence in the genome, so all the sequencing reads from those regions look identical to each other, just like the photographs of flat sandy desert, and there's no way to tell how they're supposed to overlap to form the full sequence. The only way to resolve these regions is with a technology that can read all the way through from one end to the other without stopping, producing a single contiguous sequence.

The link here describes the fruits of an effort using exactly those sorts of long-read technologies to fill in all the gaps in the X chromosome sequence, thus generating a single contiguous sequence from end to end, something that hasn't previously been possible for DNA sequences of this size.

As to why this is important, these repetitive sequences, despite being apparently featureless, still sometimes have important effects (not unlike the apparently dead and featureless desert in the analogy). In addition, sometimes there are "oases" of functionally important non-repetitive DNA sequence within the "desert" of repetition, and previous genome assembly methods would not be able to tell where these oases belonged. All of this is important because many functional DNA elements are cis-acting. That is, they exert effects on genes that are nearby on the genome. So if you don't know where they belong, then you don't know what they're doing.

If you can assemble one big chromosome sequence from end to end, all of the above problems go away, and you can finally get on with the analysis you wanted to do anyway and stop worrying about not being able to calculate meaningful distances between DNA elements.

Having a complete and accurate map is important for researchers who study the X-chromosome.

Long sequences reads allowed them to map the highly repetitive chromosome. Most sequencing is done by high-throughput short reads.

The technology can theoretically be used to map other regions of the genome which are highly repetitive.

Their github has lots of information about what they do:

https://github.com/nanopore-wgs-consortium/chm13

Step 1: the researchers use a diploid cell line where the entire diploid X chromosome is homozygous: both copies of the X chromosome in this cell line are identical. This is part of why the researchers chose to look at the X chromosome.

> To circumvent the complexity of assembling both haplotypes of a diploid genome, we selected the effectively haploid CHM13hTERT cell line for sequencing (abbr. CHM13)

Incidentally, they do capture the other chromosomes in this process:

> Several chromosomes were captured in two contigs, broken only at the centromere (Fig 1a).

> https://www.biorxiv.org/content/10.1101/735928v3.full.pdf

Step 2: Follow a procedure for DNA prep that results in long stretches of DNA (though not an entire chromosome-length) and amplify (make multiple copies of) the mixture, per this reference:

> https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5889714/

Step 3: Run the mixture through a nanopore sequencer (essentially a hole a few nanometres across), reading the change in current in response to the different bases, including methylated bases.

Step 4: Repeat this many many times to get multiple reads of each region of the data:

> In total, we sequenced 98 MinION flow cells for a total of 155 Gb (50× coverage, 1.6 Gb/flow cell, SNote 2). Half of all sequenced bases were contained in reads of 70 kb or longer (78 Gb, 25× genome coverage) and the longest validated read was 1.04 Mb.

Step 5: Overlay the data from the long measurements

> Once we had collected sufficient sequencing coverage for de novo assembly, we combined 39× of the ultra-long reads with 70× coverage of previously generated PacBio data 18 and assembled the CHM13 genome using Canu 19. This initial assembly totaled 2.90 Gbp with half of the genome contained in contiguous sequences (contigs) of length 75 Mbp or greater (NG50), which exceeds the continuity of the reference genome GRCh38 (75 vs. 56 Mbp NG50).

> The read was placed in the location of the assembly having the most unique markers in common with the read. Alignments were further filtered to exclude short and low identity alignments. This process was repeated after each polishing round, with new unique markers and alignments recomputed after each round.

Step 6: Check up the data against the reference genome:

> The corrected contigs were then ordered and oriented relative to one another using the optical map and assigned to chromosomes using the human reference genome.

> The final assembly consists of 2.94 Gbp in 590 contigs with a contig NG50 of 72 Mbp. We estimate the median consensus accuracy of this assembly to be >99.99%.

Essentially, this work closes up difficult-to-read gaps in the reference genome ( https://en.wikipedia.org/wiki/Reference_genome#Human_referen... )

I don’t believe you do.