Systems and methods for use in identifying multiple genome edits and predicting the aggregate effects of the identified genome edits

Abstract

Methods are provided for genome editing. On example method includes editing a genome sequence of an organism with multiple edits simultaneously without precise knowledge of a phenotypic effect of each individual one of the multiple edits, wherein the multiple edits are selected based on a prediction of an aggregate phenotypic effect of the multiple edits on a phenotypic trait. The method also includes aggregating the multiple edits into multi-dimensional pools, whereby phenotypic effects of contrasting pools of edits are compared to ascertain which of the multiple edits are most likely to be causing large phenotypic effects while eliminating need to evaluate each edit separately. The organism may include one of: maize, soybean, wheat, sorghum, rice, cotton, rapeseed, sunflower, bean, tomato, squash, cucumber, melon, pepper, watermelon, eggplant, okra, pea, chickpea, lentil, peanut, onion, carrot, celery, beet, cauliflower, broccoli, cabbage, Brussels sprout, radish, black-eyed pea, potato, sweet-potato, sugar cane, cassava, and banana.

What is claimed is: 
     
         1 . A method of genome editing comprising:
 editing a genome sequence of an organism with multiple edits simultaneously without precise knowledge of a phenotypic effect of each individual one of the multiple edits, wherein the multiple edits are selected based on a prediction of an aggregate phenotypic effect of the multiple edits on a phenotypic trait; and   aggregating the multiple edits into multi-dimensional pools, whereby phenotypic effects of contrasting pools of edits are compared to ascertain which of the multiple edits are most likely to be causing large phenotypic effects while eliminating need to evaluate each edit separately; and   wherein the organism includes one of: maize, soybean, wheat, sorghum, rice, cotton, rapeseed, sunflower, bean, tomato, squash, cucumber, melon, pepper, watermelon, eggplant, okra, pea, chickpea, lentil, peanut, onion, carrot, celery, beet, cauliflower, broccoli, cabbage, Brussels sprout, radish, black-eyed pea, potato, sweet-potato, sugar cane, cassava, and banana.   
     
     
         2 . The method of  claim 1 , further comprising:
 identifying a population of candidate edits to the genomic sequence of said organism based on at least one of genome annotation, genome-wide association study (GWAS) analysis, gene expression data, and a biochemical pathway model;   ranking, by a computing device, each of the candidate edits based on a predicted ability of each candidate edit to affect one or more traits of interest in said organism, the predicted ability based on at least one of a probability of causing an effect, a magnitude of the effect, and a non-parametric classification parameter; and   selecting, by the computing device, said multiple edits from the candidate edits based on the rankings.   
     
     
         3 . The method of  claim 1 , further comprising determining, by a computing device, a sample size to be used in validating the multiple edits in the genome sequence; and
 subjecting a number of organism(s) consistent with the determined sample size to a cultivation space, whereby an aggregate effect of the multiple edits is permitted to be verified.   
     
     
         4 . The method of  claim 1 , further comprising determining a sample size to be edited for validating the multiple edits, prior to editing the genome sequence. 
     
     
         5 . The method of  claim 1 , further comprising subjecting a number of organism(s) having the genome sequence, which is edited, to a cultivation space, the cultivation space including one or more of pots, trays, grow rooms, greenhouses, plots, gardens, and fields. 
     
     
         6 . The method of  claim 5 , further comprising confirming an agronomic advancement of the edited genome in a plant without having to confirm the agronomic effect of each of the multiple edits individually. 
     
     
         7 . The method of  claim 1 , further comprising predicting the aggregate effect of the multiple edits to the genome sequence on at least one trait, prior to editing the genome sequence; and
 wherein editing the genome sequence includes editing the genomes sequence with the multiple edits only when the predicted aggregate effect satisfies a defined threshold.   
     
     
         8 . The method of  claim 7 , wherein predicting the aggregate effect of the multiple edits includes predicting the aggregate effect based on an additive model. 
     
     
         9 . The method of  claim 1 , wherein the phenotypic trait is a trait that confers one or more of herbicide tolerance, disease resistance, insect or pest resistance, altered fatty acid, protein or carbohydrate metabolism, grain yield, oil content, nutritional content, growth rate, and/or stress tolerance. 
     
     
         10 . The method of  claim 1 , wherein the phenotypic trait is a trait under monogenic or oligogenic control. 
     
     
         11 . The method of  claim 1 , wherein the phenotypic trait is a trait under polygenic control.