Biology subjects

Mehrem, S. L.

Publications and source records attributed to Mehrem, S. L..

5 recordsLinked to original sources

bioRxiv2025

GreenLeafVI: A FIJI plugin for high-throughput analysis of leaf chlorophyll content

Chlorophyll breakdown is a central process during plant senescence or stress responses and leaf chlorophyll content is therefore a strong predictor of plant health. Chlorophyll quantification can be done in several ways, most of which are time-consuming or require specialized equipment. A simple alternative to these methods is the use of image-based chlorophyll estimation, which uses the color values in RGB images to calculate colorimetric visual indexes as a measure for the leaf chlorophyll content. Image-based chlorophyll measurement is non-destructive and, apart from a digital camera, requires no specialized equipment. Here, we developed the ImageJ plugin GreenLeafVI that facilitates high-throughput image analysis for measuring leaf chlorophyll content. Our plugin offers the option to white-balance images to decrease variation between images and has an optional background removal step. We show that this method can reliably quantify leaf chlorophyll content in a variety of plant species. In addition, we show that image-based chlorophyll quantification can replicate GWAS results based on traditional chlorophyll extraction methods, showing that this method is highly accurate.

plant biology↗

bioRxiv2025

Exploring phenotypic and genetic variation in Lactuca with GWAS in L. sativa and L. serriola

Crop wild relatives provide valuable insights into trait diversity and the genetic basis of agronomic traits. In the genus Lactuca, domesticated lettuce (Lactuca sativa) and its wild progenitor, Lactuca serriola, have been extensively studied, yet broader wild species remain underrepresented. Here, we present a phenotypic dataset of 550 Lactuca accessions, including 20 wild relatives, capturing plant morphology, pigmentation, and pathogen resistance traits derived from images and genetic resource collections. To investigate the genetic basis of these traits, we used a jointly processed SNP set for L. sativa and L. serriola, applying an iterative two-step GWAS approach, enabling the dissection of multiple loci per trait. We identified both known and novel QTLs associated with anthocyanin accumulation, leaf morphology, and pathogen resistance in L. sativa and L. serriola. Importantly, we identified L. serriola-specific QTLs undetected in L. sativa, revealing unique genetic architectures underlying anthocyanin biosynthesis and leaf morphology in the wild progenitor. These findings expand the knowledge of Lactuca beyond cultivated varieties, highlighting the potential of wild species for breeding applications. Our dataset and results provide a foundation for further investigations into the evolutionary and agronomic significance of Lactuca diversity.

plant biology↗

bioRxiv2024

From aerial drone to QTL: Leveraging next-generation phenotyping to reveal the genetics of color and height in field-grown Lactuca sativa

In recent years, the automation of genotyping has significantly enhanced the efficiency of genome-wide association studies. As a result, phenotyping rather than genotyping is now the rate-limiting step, especially in field experiments. For this reason, there is a strong need to further automate in-field phenotyping. Here we present a GWAS study on 194 field-grown accessions of lettuce (Lactuca sativa). These accessions were non-destructively phenotyped at two time points 15 days apart using an unmanned aerial vehicle. Our high throughput phenotyping approach integrates an RGB camera, a multispectral camera to measure the reflectance at 5 wavelengths (blue, green, red, red edge, near-infrared), and precise height estimation. We used the mean and other descriptives such as median, quantiles, minimum and maximum to quantify different aspects of color and height variation in lettuce from the drone images. Using this approach, we confirm several previously described QTLs, now in populations grown under field conditions, and identify several new QTLs for plant-height and color.

plant biology↗

bioRxiv2024

Natural variation in seed coat color in lettuce and wild Lactuca species

Seed coat color is a well described trait in lettuce (Lactuca sativa), varying from black to pale white pigmentation. In this study, we delve into seed coat color variation of several species within the Lactuca genus, encompassing L. sativa and 15 wild varieties, offering broader insights into the diversity of this trait. To capture seed coat color quantitatively, we use grey pixel values from publicly available images, enabling us to measure seed coat color as a continuous trait across the genus. Darker seed coats predominate within the Lactuca genus, with L. sativa displaying a distinctive bimodal distribution of black and white seed coats. Lactuca virosa exhibits the darkest seed coat coloration and less variation, while Lactuca saligna and Lactuca serriola display lighter shades and greater variability. To identify the polymorphic loci underlying the observed variation we performed GWAS on seed coat color in both L. sativa and L. serriola. For L. sativa, we confirmed the one known major QTL linked to black and white seed coat color, which we reproduce in two independent, published genotype collections (n=129, n=138). Within the same locus, we identify additional candidate genes associated with seed coat color. For L. serriola, GWAS yielded several minor QTLs linked to seed coat color, harboring candidate genes predicted to be part of the anthocyanin pathway. These findings highlight the phenotypic diversity present within the broader Lactuca genus and provide insights into the genetic mechanisms governing seed coat coloration in both cultivated lettuce and its wild relatives.

plant biology↗

bioRxiv2024

Lactuca super-pangenome reduces bias towards reference genes in lettuce research

Breeding of lettuce (Lactuca sativa L.), the most important leafy vegetable worldwide, for enhanced disease resistance and resilience relies on multiple wild relatives to provide the necessary genetic diversity. In this study, we constructed a super-pangenome based on four Lactuca species (representing the primary, secondary and tertiary gene pools) and comprising 474 accessions. We include 68 newly sequenced accessions to improve cultivar coverage and add important foundational breeding lines. With the super-pangenome we find substantial presence/absence variation (PAV) and copy-number variation (CNV). Functional enrichment analyses of core and variable genes show that transcriptional regulators are conserved whereas disease resistance genes are variable. PAV-genome-wide association studies (GWAS) and CNV-GWAS are largely congruent with single-nucleotide polymorphism (SNP)-GWAS. Importantly, they also identify several major novel quantitative trait loci (QTL) for resistance against Bremia lactucae in variable regions not present in the reference lettuce genome. The usability of the super-pangenome is demonstrated by identifying the likely origin of non-reference resistance loci from the wild relatives Lactuca serriola, Lactuca saligna and Lactuca virosa. The provided methodology and data provide a strong basis for research into PAVs, CNVs and other variation underlying important biological traits of lettuce and other crops.

plant biology↗