Randomly generated genes will be spawned when your unit gains a mutation. Mutation buffs that your units gain are based on the gene that was generated. Through genetic engineering, it is possible to permanently implement certain mutations on your unit. Adding genes to your unit is how you increase their power and abilities. Genes themselves are made up of 4 major parts, type, receptors, effectors, and effects.
Gene Types[]
Each gene will have one type. Each type gives a general outline for what the gene will do, and they are often used by other genes for criteria, or targeting.
Idema: Idema genes will typically have effects that will work with other genes that are idema type.
Alter: Alter genes are the opposite of idema genes and will typically work better with genes that are not alter genes.
Mono: Mono type genes will often be very powerful for their rarity, but cannot be effected by other genes making them difficult to use at times.
Coetus: Coetus genes will generally apply effects to other genes in groups.
Medioc: Medioc genes are your basic average gene, they will be very common.
Dux: Dux genes will specialize in removing features from genes and adding in effects of their own.
Fex: Fex genes are very useful for helping add new genes into your DNA.
Accipe: Accipe genes will generally change its own effects based on nearby genes.
Mirus: Mirus genes will be very rare and will generally work with other mirus genes.
Omni: Omni genes will be very rare and powerful as they will generally modify very large groups of genes.
Exedo: Exedo genes will generally remove effects from nearby genes to empower its own effects.
Plex: Plex genes will be very complicated to use and add but will often have large payouts for the geneticist that can integrate one into their DNA.
Locum: Locum genes will usually gain effects based on their location in the DNA chain.
Phormid: Phormid genes work exclusively with bacteria, you can currently see them adding abilities to your units.
Gene Receptors and Effectors[]
Each gene will have a receptor and an effector. Each effector and receptor may contain up to two colors. At least one of the receptor colors must match one of the previous genes effector colors in order for it to be successfully added (combined) into that units DNA. There are two special colors: white and black. White effectors/receptors will combine with any other color, except for black; whereas Black effectors/receptors will not combine with any color (which results in black colors only being used at the front or back of your units DNA)
Gene Effects[]
Gene effects are what your gene actually does. A gene effect will generally be broken down into 2 pieces, a criteria and a payload. Criterias must be met in order for the gene to activate its payload. Example Criteria: “If the next gene to the right is a Fex gene then” this means this effect will only activate if the gene directly to the right of this gene is a Fex type gene. Example Payload: “The next 2 genes to the right each gain +1 to health” this means the next 2 genes to the right of this gene will each gain the effect +1 to health, meaning you could essentially gain +2 to health. A Gene effect, containing both the example criteria and payload might read: “If the next gene to the right is a Fex gene then, the next 2 genes to the right each gain +1 to health”
Effects vs Final Effects:[]
Each gene on your DNA strand will show two sets of effects one is labeled effects and one is labeled Final effects. Effects shows all of the requirements and effects that this gene can do. If an effect is red that means that its criteria is not met, and the payload will not be applied. If an effect is blue that means that its criteria is met, but that it has no target for its payload. If an effect is green than that means the criteria have been met and the payload has been applied. Final effects shows all of the payloads that are currently applied to this gene.
Gene Crafting[]
Genes can be crafted using nucleotides. Nucleotides are the currency used in genetic engineering.
Blueprinting genes:[]
Genes can be turned into ‘blueprints’. When they have been turned into a blueprint, a copy of that gene can be created at any time using nucleotides. You can make as many copies of the blueprinted gene as you can afford. Blueprinting genes does come with a risk. Each gene will have a blueprint chance(which you may have already noticed on your genes); the gene will be destroyed in a attempt to blueprint it, and if blueprinting fails, you lose the gene forever.
Assembling genes:[]
Each gene has a nucleotide cost to be constructed. Once a gene is blueprinted it will be able to be constructed for that nucleotide cost.
Disassembling genes:[]
Each gene has a nucleotide salvage amount. This is the amount of nucleotides you will get when you salvage that gene. When you salvage a gene, it is destroyed and you are given the nucleotides for that gene. This is usually the easiest way to obtain Nucleotides, since you can discard unwanted genes for useful nucleotides.
Gene Synthesis:[]
A player can spend a number of nucleotides to try and create a random gene. There is some risk with as this process can flat out fail, or give the player a very bad gene. The more nucleotides spent, the higher the chance of getting rare and powerful genes. However, there is a very steep falloff, so spending a massive number of nucleotides can be an incredible waste.
Gene Optimization:[]
A player can spend nucleotides and time in order to try and change a preexisting gene. Players can only optimize one gene at a time, and must wait until the attempt is finished before they can attempt to optimize another gene. This puts that gene at risk of being destroyed. The player can set up what they would like to try and change, or they can just try and reroll the item in general. Re-Rolling the whole gene is cheaper, and faster, but has a higher chance of complete failure, and the outcome can be uninteresting.
Randomize Entire Gene - 300n[]
Randomizes the entire gene. This option has a high chance of failure, or completely destroy the gene being modified.
Change Effector - 400n[]
Rerolls the effector of the gene being modified. This usually has a high success rate, but multiple rerolls can quickly destroy the gene if you're not careful.
Change Receptor - 400n[]
Rerolls the receptor of the gene being modified. This usually has a high success rate, but multiple rerolls can quickly destroy the gene if you're not careful.
Change Gene Type - 800n[]
Attempts to reroll the gene's type. This can be useful in certain situations, and has a decent success rate.
Change Values of Effects - 5000n[]
Attempt to reroll the values of a gene's effects. This can sometimes make your gene worse than it was before, or vastly improve it. More often it'll just make the gene worse, but other times it might make a gene really powerful.
Change Add to Organism Chance - 800n[]
Attempts to reroll the "add to organism chance" of the gene being modified. While its success rate is quite above-average, it can be really helpful in making a very hard-to-add gene almost guaranteed to compile.
Change Blueptint Chance - 8000n[]
Attempt to reroll the chance of blueprinting the gene. It's obviously very expensive, since if you successfully raise the blueprinting chance of a really powerful gene and then successfully blueprint it, you can create and add as many of that gene as you have nucleotides. Of course, the failure rate of this optimization is high, and you're much more likely to outright lose the gene.
Change Effect Targets - 3000n[]
Attempt to reroll the targets of a gene's effects. This can make a gene much more effective since it is applying its payload many more times. Of course, the effect target might be very tricky to take advantage of, especially if it is for example changing the target from "The next 3 [Non-Exedo] genes to the right" to "The next 6 genes to the left before the next [Non-Phormid] gene" or something like that.
Remove Criteria - 10000n[]
Attempts to remove gene criteria in order to access its effects much more readily. This has a very high gene destruction chance if it fails, since you'll lose the gene and you'll have wasted all of your nucleotides.
Remove Effects - 5000n[]
Attempts to remove one or more effects from the gene. It's pretty much useless to perform this optimization, because it's almost certain it'll remove more useful effects and leave your gene with the effects you intended on removing. Also, it can easily fail and destroy the gene.
Change Effect Target Values - 1500n[]
Attempts to change the number of genes targeted by the gene's effects.
Change Criteria Target Values - 1500n[]
Attempts to change the type of criteria for the gene's effects. This is usually easier than removing criteria altogether, since it's less likely to destroy your gene.