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Ethyl methanesulfonate (EMS) mutagenesis offers important advantages for improving crops, such as cotton, with limited diversity in elite gene pools. EMS-induced point mutations are less frequently associated with deleterious traits than alleles from wild or exotic germplasm. From 157 mutant lines that have significantly improved fiber properties, we focused on nine mutant lines here. A total of eight populations were developed by crossing mutant lines in different combinations into GA230 (GA2004230) background. Multiple lines in each population were significantly improved for the fiber trait that distinguished the donor parent(s), demonstrating that an elite breeding line (GA230) could be improved for fiber qualities using the mutant lines. Genotypes improved for multiple fiber traits of interest suggesting that allele pyramiding is possible. Compared to midparent values, individual progeny in the population conferred fiber quality improvements of as much as 31.7% (in population O) for micronaire (MIC), 16.1% (in population P) for length, 22.4% (in population K) for strength, 4.1% (in population Q) for uniformity, 45.8% (in population N) for elongation, and 13.9% (in population O) for lint percentage (lint%). While further testing for stability of the phenotype and estimation of yield potential is necessary, mutation breeding shows promise as an approach to reduce the problem of the genetic bottleneck of upland cotton. The populations developed here may also contribute to identifying candidate genes and causal mutations for fiber quality improvement.
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This content will become publicly available on December 1, 2026
Large DNA and protein language models enhance discovery of deleterious mutations in maize
Background The maize inbred line Chang7-2 and derived lines are important male donors for hybrid production, contributing significantly to the development of high-yield and stress-tolerant hybrids. Additionally, Chang7-2 serves as a valuable model inbred line for genetic and genomic studies, facilitating the discovery of genes underlying hybrid vigor and other agronomic traits. Results Here, a reference genome assembly and a chemical-induced mutant population (N = 1,716) through ethyl methyl sulfonate (EMS) treatments are generated using Chang7-2. Each EMS line is whole genome sequenced and compared to the Chang7-2 genome, identifying 2,586,769 mutations with 4,939 mutations causing premature stop codons or altered splicing sites. The effect estimation of mutations using two large language artificial intelligence (AI) models, namely the protein language model ESM1b and the DNA language model PlantCaduceus, reveals 15,264 and 18,326 deleterious mutations, respectively. Mutation effects estimated with AI models accelerate revelation of four causal mutations underlying phenotypes of albino leaf, reduced cuticular wax, altered seed color, and male sterility. In addition, allelic expression quantification of genic mutations in 13 EMS M1 lines and their M2 heterozygous progeny, which contain both wildtype and mutant alleles, shows that mutant alleles are overall accumulated at a lower level compared to wildtype. Such allelic disparity is observed for some synonymous mutations, indicating they may not be biologically inconsequential. Conclusions AI-based estimation of mutation effects offers cross-species evidence for functional impacts of mutations. Our study demonstrates its application in revealing deleterious EMS mutations and identifying causal mutations responsible for mutant phenotypes.
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- PAR ID:
- 10691858
- Publisher / Repository:
- Springer Nature
- Date Published:
- Journal Name:
- Genome Biology
- Volume:
- 26
- Issue:
- 1
- ISSN:
- 1474-760X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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