Prediction of evolutionary constraint by genomic annotations improves functional prioritization of genomic variants in maize.

ABSTRACT:

Background

Crop improvement through cross-population genomic prediction and genome editing requires identification of causal variants at high resolution, within fewer than hundreds of base pairs. Most genetic mapping studies have generally lacked such resolution. In contrast, evolutionary approaches can detect genetic effects at high resolution, but they are limited by shifting selection, missing data, and low depth of multiple-sequence alignments. Here we use genomic annotations to accurately predict nucleotide conservation across angiosperms, as a proxy for fitness effect of mutations.

Results

Using only sequence analysis, we annotate nonsynonymous mutations in 25,824 maize gene models, with information from bioinformatics and deep learning. Our predictions are validated b

SUBMITTER: Ramstein GP 

PROVIDER: S-EPMC9438327 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature