Biology subjects

Marrano, A.

Publications and source records attributed to Marrano, A..

4 recordsLinked to original sources

bioRxiv2025

PlantCV v4: Image analysis software for high-throughput plant phenotyping

PlantCV is an open-source Python project aimed at developing tools to address a range of image-based, plant phenotyping questions. PlantCV has been used for more than 10 years to automate trait collection from image data and the newest release, PlantCV version 4, continues to lower the barrier to entry for users without substantial coding experience through extensive example use-case tutorials and simplified installation. In addition to usability, we document added functionality since the release of PlantCV v2, including support for more image types such as fluorescence, thermal, and hyperspectral data. Finally, we describe the development of a new subpackage focused on morphological trait measurements like leaf angle, and demonstrate its utility as compared to more manual methods of data collection. CORE IDEASO_LIPlantCV is an open-source, open-development, Python-based software package that has a new release for improved functionality and usability to make image analysis flexible and easier for researchers without a coding background. C_LIO_LIPlantCV is now capable of handling new data types that are relevant to researchers, such as thermal and hyperspectral, and has built in functionality for extracting information from these image types. C_LIO_LIThe software project aims to lower the barrier to entry into image analysis for researchers by providing numerous, versioned, interactive tutorials that cover most common use cases, particularly in plant science. C_LI

plant biology↗

bioRxiv2022

Strong genotype by environment interactions in the rice Global MAGIC population across seedling stage drought

Crop adaptation is required to sustainably increase the rate of yield gains to meet projected future needs under the challenging conditions of climate change and competition for resources. Future adaptation will likely need to harness both highly polygenic traits and genotype-by-environment interactions (GxE), the study of which is aided by complex recombinant populations. We used the diverse Oryza sativa Global Multiparent Advanced Generation InterCross (MAGIC) population to study the genetic architecture and contributions of seedling emergence, establishment, and development to yield components under dry-direct seeding and seedling stage drought across three growing seasons. Dry-direct seeding is an establishment practice that has the potential to reduce methane emissions, water use, and labor demands for rice farmers, but increases the possibility of early-season drought conditions. We found substantial evidence for large roles of environmental variation and GxE in controlling trait variation. Maintenance of shoot growth during seedling stage drought was positively correlated with crown root number and both directly and indirectly influenced agronomic traits. Other than the major green revolution locus sd1, most allelic effects were conditionally neutral (affecting trait values in some environments but not others) and most alleles had their strongest effect in an environmental extreme. This discovery is both a challenge and a potential opportunity: with variable genetic architecture, selection in any one environment may not result in stable trait gains across environments. However, conditionally neutral GxE is a potential route to sustainable yield stability through allele pyramiding.

genetics↗

bioRxiv2020

Scanning the rice Global MAGIC population for dynamic genetic control of seed traits under vegetative drought.

Grain size and weight are important yield components in rice (Oryza sativa L.). There is still uncertainty about the genetic control of these traits under drought stress, the most pressing emerging issue in many rice cultivation areas. To address this lack of knowledge, we investigated the genetic architecture of seed size, shape, and weight using the rice Global Multi-parent Advanced Generation Intercross (MAGIC) population, grown under well-watered and vegetative drought conditions. We measured variation in seed size and shape with a new high-throughput phenotyping method based on a desktop scanner and the open-source package Plant Computer Vision (PlantCV). Besides being affordable, rapid, and accurate, our method captured the phenotypic divergence between drought and well-watered samples, expressed as 12 different traits that include traditional size metrics and new grain shape measures. Overall, under water deficit, the MAGIC lines produced smaller and shorter seeds. We identified ten MAGIC lines with traits that make them good candidates for the release of rice cultivars with high yield potential under vegetative drought stress. We ran a marker-trait association analysis for the measured seed-related traits. Most of the identified marker-trait associations showed strong genotype-by-environment interactions (GxE), with most allele effects being conditionally neutral. These results suggest dynamic genetic control of seed size, shape, and weight under vegetative drought stress in rice, highlighting the importance of understanding the contribution of GxE interactions on trait variation to develop resilient and high-yielding rice varieties. Our study confirms that combining low-cost and high-throughput phenotyping strategies with a diverse genetic material suited for multi-environmental trial provides solutions for adapting rice cultivation to current and future environmental adversities.

plant biology↗

bioRxiv2019

High-quality chromosome-scale assembly of the walnut (Juglans regia L) reference genome

The release of the first reference genome of walnut (Juglans regia L.) enabled many achievements in the characterization of walnut genetic and functional variation. However, it is highly fragmented, preventing the integration of genetic, transcriptomic, and proteomic information to fully elucidate walnut biological processes. Here we report the new chromosome-scale assembly of the walnut reference genome (Chandler v2.0) obtained by combining Oxford Nanopore long-read sequencing with chromosome conformation capture (Hi-C) technology. Relative to the previous reference genome, the new assembly features an 84.4-fold increase in N50 size, and the full sequence of all 16 chromosomal pseudomolecules, nine of which present telomere sequences at both ends. Using full-length transcripts from single-molecule real-time sequencing, we predicted 40,491 gene models, with a mean gene length higher than the previous gene annotations. Most of the new protein-coding genes (90%) are full-length, which represents a significant improvement compared to Chandler v1.0 (only 48%). We then tested the potential impact of the new chromosome-level genome on different areas of walnut research. By studying the proteome changes occurring during catkin development, we observed that the virtual proteome obtained from Chandler v2.0 presents fewer artifacts than the previous reference genome, enabling the identification of a new potential pollen allergen in walnut. Also, the new chromosome-scale genome facilitates in-depth studies of intraspecies genetic diversity by revealing previously undetected autozygous regions in Chandler, likely resulting from inbreeding, and 195 genomic regions highly differentiated between Western and Eastern walnut cultivars. Overall, Chandler v2.0 is a valuable resource to understand and explore walnut biology better.

genomics↗