The design represents a genomics perspective on the biodiversity of the Earth.
The basis of the design are the shape of continents. These were taken from the award-winning Authagraph Map, which is a projection that strongly preserves shapes and areas. Wired calls it “not perfect, but close”.
I rearranged the authagraph map to fit the aspect ratio of the cover image (nearly 1:1) and allow for enough room for text on the cover. To make things interesting, I put Antarctica in the center — north is everywhere. Given how the image is constructed (read below), I had to remove some islands. Sorry, Madagascar — you're a star.
Australia has the job of representing all of Oceania, such as Inaccessible Island.
For each continent and ocean, a travelling salesman problem (TSP) was solved to find the shortest (or close to it) path that covers the area. The path joins points that were sampled at a level of detail that I thought would strike a good balance between detail and legibility.
Some continents do not have full coverage by the path &mdsah; some small islands and peninsulas were excluded (or extended). This needed to be done to give room for the ocean path between continents and to avoid situations where the ocean path crossed a landmass. The shortest solution isn't always the most appropriate.
The number of points visited for each landmass were
1,575 africa
848 antarctica
2,818 asia
475 australia
713 europe
1,674 namerica
17,354 ocean
872 samerica
26,329 ALL
I then smoothed the path using a J-spline curve.
The DNA double helix is a trope — let's embrace it.
And before you start pixel peeping: the helix doesn't have handedness. It's composed of three independent stacked layers: one layer per strand strands and one layer with bonds.
Once the helix was drawn, I added bases as circles and resized to increase visibility while avoiding overlap.
The number of base pairs per area is
nbp
australia 596
europe 872
antarctica 1,024
samerica 1,064
africa 1,911
namerica 2,033
asia 3,403
ocean 21,208
------
32,111
I mapped species sequenced as part of the Earth BioGenome Project to the path that corresponded to their habitat location. This was done using a combination of automated searches through the Global Biodiversity Information Facility (GBIF) and manual corrections.
For a given path, the length of the sequence of each species was fixed and depended on the length of the area's double helix and number of species assigned to it.
For example, in Africa we have 1,911 bases to distribute across 87 species, giving us `1911/87-1=20` bases per species. The value is rounded down to the nearest integer and the `-1` term allows for a gap between each sequence.
The ocean area is very large and has relatively few species, so we can have long sequences — 396 bases per species.
nbp species bp_per_species
australia 596 71 7
europe 872 113 6
antarctica 1,024 2 511
samerica 1,064 93 10
africa 1,911 87 20
namerica 2,033 182 10
asia 3,403 206 15
ocean 21,208 52 396
------ ---
32,111 806
Any bases left over on the helix were assigned to gaps. Initially, I thought of concatenating the sequences without any gaps. While this would allow me to represent (neglibibly) longer sequences, I was persuaded against this idea (thank you Emma!).
First, the Earth Biogenome sequencing isn't complete (nor will it ever be), so gaps in the sequence are a nice metaphor for this. Second, the gaps offer some hope of actually reading the sequences off for each species. Below is a view of one of the strands with the backbone and base pair locations within gaps shown in magenta.
In the final figure, the helix backbone in gaps is faded.
In the final figure, bases are colored by nucleotide (A, T, C, G) and region (land vs ocean).
You can download each species's sequence and its location.
Sequences were sampled from the Genbank records starting at the first non-repeated base. This was a quick way to avoid spamming the design with polytails.
For example, the sequence for the Hanuman langur
>PVII010000001.1:1-1000 Semnopithecus entellus isolate BS30 SemEnt_scaffold_0, WGS
AAAAA AAAAA AAAAA AAAAA AAAAA AAATT ATTTT GCTAA GGTCT GAGAA CTCCA GAAGG TGGTG TCGTG
----- ----- ----- ----- ----- ---++ +++++ +++++ +++++ +++++ +++++ +++++ +++++ +++++
** ***** ***** ***
was sampled by skipping the first 28 bases (A's) and uses the sequence indicated by * above.
The position and sequence for each species is shown below. The first base of the sequence is capitalized and remaining are lowercase. The numeric code below the species name is the taxon, a unique taxonomy ID used by Genbank.
A version of the above without the sequence is shown below.
It is not certain that everything is uncertain. —Blaise Pascal
We have already explored how we can mitigate bias caused by confounding variables in observational studies using propensity score (PS) matching (PSM) and propensity score weighting (PSW). However, any statistical model is only as good as its assumptions and, if it is specified incorrectly, it can itself produce biased estimates of the treatment effect.
This month, we explore double robustness, a powerful statistical concept that provides a valuable “safety net” against the risk of an incorrect model. It offers two opportunities, instead of just one, to obtain a valid estimate of the treatment effect — making it possible to draw credible causal inferences from observational data without having to depend on a single set of modeling assumptions.
Kurz, C.F., Krzywinski, M. & Altman, N. (2026) Points of significance: Double Robustness. Nat. Methods 23:868–869.
My cover design on the 7 April 2026 Nature Biotechnology issue shows the dendrogram that represents a cluster of uniquely expressed (or downregulated) genes in human naive stem cells induced from such cells. Within each dendrogram block, the genomic barcode sequence (sampled from Supplementary Table 1) is depicted with a Code 39 barcode. The highlighted barcode is one of those used for cell isolation.
Ishiguro S. et al. A multi-kingdom genetic barcoding system for precise clone isolation (2026) Nature Biotechnology 44:616–629.
Browse my gallery of cover designs.
Celebrate π Day (March 14th) and enjoy the art — but only if you're part of the 5%.
Go ahead, see what you can't see.
Authentic and accurate images of Ishihara's test plates photographed (and lovingly color-corrected) from the 38-plate Ishihara's Tests for Colour Deficiency.
I also provide the position, size, and color of each circle on each test plate.
What immortal hand or eye, could frame thy fearful symmetry? — William Blake, "The Tyger"
This month, we look at symmetric regression, which, unlike simple linear regression, it is reversible — remaining unaltered when the variables are swapped.
Simple linear regression can summarize the linear relationship between two variables `X` and `Y` — for example, when `Y` is considered the response (dependent) and `X` the predictor (independent) variable.
However, there are times when we are not interested (or able) to distinguish between dependent and independent variables — either because they have the same importance or the same role. This is where symmetric regression can help.
Luca Greco, George Luta, Martin Krzywinski & Naomi Altman (2025) Points of significance: Symmetric alternatives to the ordinary least squares regression. Nat. Methods 22:1610–1612.