Sarah L. Mehrem

This paper identifies the lettuce receptor LNR that recognizes the conserved heptapeptide motif in microbial NLPs, revealing convergent evolution of NLP recognition and potential for crop defense improvement.

DeepPheno links SNP genotypes to hyperspectral imaging in lettuce using deep learning, showing predictive performance for known and novel genotype-phenotype associations.

This study uses hyperspectral imaging to identify time-specific QTLs in field-grown lettuce by integrating phenotypic data with environmental factors and genome-wide association analysis.

GreenLeafVI is a FIJI plugin that enables high-throughput leaf chlorophyll content measurement using image-based colorimetric analysis, showing accuracy comparable to traditional methods.

This study uses drone-based phenotyping to conduct a GWAS on lettuce, confirming known QTLs and identifying new ones for plant height and color in field conditions.

The paper conducts GWAS on Lactuca species to identify genetic loci associated with phenotypic traits, finding novel QTLs in wild species not detected in domesticated lettuce.

This study constructs a lettuce super-pangenome to reduce bias in reference genes, identifying novel QTLs for disease resistance and origins of non-reference resistance loci from wild relatives.

sv-channels improves SV detection precision using deep learning, outperforming GRIDSS while maintaining Manta's recall.

This study analyzes seed coat color variation across lettuce and wild Lactuca species using GWAS to identify genetic loci associated with color differences.