US 2025/0157576 A1Published application

System and method for gene-environment analysis

AssigneeAvalo, Inc.

InventorsEmily Bellis, Mariano Alvarez

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Abstract

The method for gene-environment analysis can include: determining an environment-variable association model, identifying causal variables associated with environmental parameters, determining a target set of causal variable values, and evaluating an organism based on the target set of causal variable values. In variants, the method can function to identify environmentally adaptive variable values (e.g., environmentally adaptive alleles), predict an optimal set of variable values (e.g., optimal genotype) for a target environment, and/or evaluate an individual organism relative to the optimal set of variable values (e.g., for breeding, for organism selection, etc.).

Claims20

Dependent claims

A method, comprising:

determining a first model defining a relationship between a set of genomic variables and a first set of environmental parameters;
using the first model, determining an association metric for each genomic variable in the set of genomic variables;
identifying causal genomic variables in the set of genomic variables based on the association metrics;
training a second model using training data, wherein the training data comprises:
for each of a set of training organisms, training values for the causal genomic variables and training values for a second set of environmental parameters;
using the second model, predicting target values for the causal genomic variables based on target values for the second set of environmental parameters;
and
selecting an organism for breeding based the target values for the causal genomic variables.

5 more elements

A system, comprising:

a processing system configured to:
select a set of causal variables associated with a first set of environmental parameters, wherein the set of causal variables is selected from a set of variables using an observed value and a test value for each variable in the set of variables, wherein a test value for a variable of interest in the set of variables is determined based on observed values for a subset of variables in the set of variables, wherein the subset of variables does not include the variable of interest;
train a model to predict values for the set of causal variables based on values for a second set of environmental variables;
using the model, predict target values for the set of causal variables based on target values for the second set of environmental variables;
and
select an organism from a set of candidate organisms for breeding based on:
the target values for the set of causal variables and, for each of the set of candidate organisms, observed values for the causal variables.

4 more elements

Dependencies are inferred from the claim text.

Facts

Application: 18/948,006Filed 14 Nov 2024
Priority: 14 Nov 2023
Published: 15 May 2025
Term ends: Not estimatedThe source records don’t support an estimate.

Classification4 codes

G16B 20/20
ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations: allele or variant detection, e.g. single…
G16B 20/00
Ict specially adapted for functional genomics or proteomics
G16B 40/20
ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge…:…
G16B
Bioinformatics, i.e. information and communication technology [ict] specially adapted for genetic or

Family

Application63/598,674Us provisional application · filed 14 Nov 2023
Application63/562,130Us provisional application · filed 6 Mar 2024
US 2025/0157576 A1This patent

From the US filing history. Foreign family members aren’t listed.

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