Alexander Edward Lipka

Single-cell RNA sequencing of developing maize ears facilitates functional analysis and trait candidate gene discovery

Developmental Cell · 2021 · 268 citations

Optical topometry and machine learning to rapidly phenotype stomatal patterning traits for maize QTL mapping

PLANT PHYSIOLOGY · 2021 · 75 citations

Stomata are adjustable pores on leaf surfaces that regulate the tradeoff of CO2 uptake with water vapor loss, thus having critical roles in controlling photosynthetic carbon gain and plant water use. The lack of easy, rapid methods for phenotyping epidermal cell traits have limited discoveries about the genetic basis of stomatal patterning. A high-throughput epidermal cell phenotyping pipeline is presented here and used for quantitative trait loci (QTL) mapping in field-grown maize (Zea mays). T…

The regulatory landscape of early maize inflorescence development

Genome biology · 2020 · 61 citations

BACKGROUND: The functional genome of agronomically important plant species remains largely unexplored, yet presents a virtually untapped resource for targeted crop improvement. Functional elements of regulatory DNA revealed through profiles of chromatin accessibility can be harnessed for fine-tuning gene expression to optimal phenotypes in specific environments. RESULT: Here, we investigate the non-coding regulatory space in the maize (Zea mays) genome during early reproductive development of po…

Genomic regions influencing aggressive behavior in honey bees are defined by colony allele frequencies

Proceedings of the National Academy of Sciences · 2020 · 60 citations

on linkage group (chromosome) 7, showed strong signals of both selection and admixture during the evolution of gentleness in a honey bee population. We thus found links between colony genetics and group behavior and also, molecular evidence for group-level selection, acting at the colony level. We conclude that group genetics dominates individual genetics in determining the fatal decision of honey bees to sting.

How Well Can Multivariate and Univariate GWAS Distinguish Between True and Spurious Pleiotropy?

Frontiers in Genetics · 2021 · 23 citations

Quantification of the simultaneous contributions of loci to multiple traits, a phenomenon called pleiotropy, is facilitated by the increased availability of high-throughput genotypic and phenotypic data. To understand the prevalence and nature of pleiotropy, the ability of multivariate and univariate genome-wide association study (GWAS) models to distinguish between pleiotropic and non-pleiotropic loci in linkage disequilibrium (LD) first needs to be evaluated. Therefore, we used publicly availa…