Abstract: The present invention is based on the use of the H3K9me2 methylation levels in plant genomes to predict transgene silencing, transgene stability, and/or transgene expression level. Provided are methods and/or systems for generating whole-genome H3K9me2 maps and its use with an assigned threshold value for predicting gene silencing. The methods and/or systems provided herein can be used in high-throughput setting for screening large number of transformed event in a relatively short period of time as compared to existing technologies.

Abstract: As disclosed herein, optimal native genomic loci have been identified in monocot plants, such as maize plants, that represent best sites for targeted insertion of exogenous sequences.

Abstract: As disclosed herein, optimal native genomic loci have been identified in dicot plants, such as soybean plants, that represent best sites for targeted insertion of exogenous sequences.

Abstract: As disclosed herein, optimal native genomic loci have been identified in monocot plants, such as maize plants, that represent best sites for targeted insertion of exogenous sequences.

Abstract: As disclosed herein, optimal native genomic loci have been identified in dicot plants, such as soybean plants, that represent best sites for targeted insertion of exogenous sequences.

Abstract: As disclosed herein, optimal native genomic loci from maize plants have been identified that represent best sites for targeted insertion of exogenous sequences.

Abstract: As disclosed herein, optimal native genomic loci of soybean plants have been identified that represent best sites for targeted insertion of exogenous sequences.

Abstract: As disclosed herein, optimal native genomic loci of soybean plants have been identified that represent best sites for targeted insertion of exogenous sequences.

Abstract: As disclosed herein, optimal native genomic loci from maize plants have been identified that represent best sites for targeted insertion of exogenous sequences.

Abstract: As disclosed herein, optimal native genomic loci of soybean plants have been identified that represent best sites for targeted insertion of exogenous sequences.

Abstract: This disclosure concerns the use of endogenous plant RNAi machinery to preferentially or specifically reduce transgene expression. In some embodiments, the disclosure concerns specific reduction of transgene expression in seed tissues of a dicot plant.

Abstract: As disclosed herein, optimal native genomic loci of soybean plants have been identified that represent best sites for targeted insertion of exogenous sequences.

Abstract: The present invention is based on the use of the H3K9me2 methylation levels in plant genomes to predict transgene silencing, transgene stability, and/or transgene expression level. Provided are methods and/or systems for generating whole-genome H3K9me2 maps and its use with an assigned threshold value for predicting gene silencing. The methods and/or systems provided herein can be used in high-throughput setting for screening large number of transformed event in a relatively short period of time as compared to existing technologies.

Abstract: As disclosed herein, optimal native genomic loci have been identified in monocot plants, such as maize plants, that represent best sites for targeted insertion of exogenous sequences.

Abstract: As disclosed herein, optimal native genomic loci of soybean plants have been identified that represent best sites for targeted insertion of exogenous sequences.

Abstract: As disclosed herein, optimal native genomic loci from maize plants have been identified that represent best sites for targeted insertion of exogenous sequences.

Abstract: As disclosed herein, optimal native genomic loci have been identified in dicot plants, such as soybean plants, that represent best sites for targeted insertion of exogenous sequences.

Abstract: Systems and methods for data analysis are provided. In one embodiment, a method may be provided for analysis comprising electronically receiving sequence data related to a plurality of sequences and a reference sequence, associating the sequence data with one of at least two groups, identifying a plurality of high quality read sequences from among the plurality of sequences, extracting a plurality of unique read sequences from the plurality of high quality read sequences, and aligning the plurality of unique read sequences against the reference sequence data corresponding to a reference sample. The method may further identify mutations in a targeted location, display the targeted mutations, and prioritize the technologies that caused the mutations according to their efficiency. In one example, the systems and methods are used to characterize the activity of several ZFN candidates.