Biology subjects

Burger, P.

Publications and source records attributed to Burger, P..

6 recordsLinked to original sources

bioRxiv2024

Unraveling Genome- and Immunome-wide Genetic Diversity in Jaguars (Panthera onca): Implications for Targeted Conservation

Our study examines the declining Jaguar populations in Central and South America, assessing the impact of habitat loss and fragmentation on genetic diversity and local adaptation. We investigated population structure and immunome variability in 25 jaguars to identify unique genetic diversity for informed, targeted conservation. Our genome-wide analyses revealed three distinct geographic populations corresponding to Central America, South American lowland, and South American highland regions. While the highland population displayed lower overall immunome-wide variability, specific innate (Natural killer cell complex, Toll-like receptor) and adaptive (Major histocompatibility complex-class-II) immune genes crucial for adaptive responses showed promising diversity. Nonetheless, South American highland and Central American jaguars are severely threatened. Therefore, we propose re-evaluating evolutionary significant units to prioritize conservation efforts, preserving crucial genetic and adaptive diversity essential for the species resilience and long-term survival.

genomics↗

bioRxiv2021

NGS comparison of Downy and Powdery mildew resistance genomic regions between 'Regent' and 'Red Globe'

Powdery and downy mildew have a large negative impact on grape production worldwide. Quantitative trait loci (QTL) mapping projects have identified several loci for the genetic factors responsible for resistance to these pathogens. Several of these studies have focused on the cultivar Regent, which carries the resistance loci to downy mildew on chromosome 18 (Rpv3), as well powdery mildew on chromosome 15 (Ren3, Ren9). Several other minor resistance loci have also been identified on other chromosomes. Here we report on the re-sequencing of the Regent and Red Globe (susceptible) genomes using next generation sequencing. While the genome of Regent has more SNP variants than Red Globe, the distribution of these variants across the two genomes is not the same, nor is it uniform. The variation per gene shows that some genes have higher SNP density than others and that the number of SNPs for a given gene is not always the same for the two cultivars. In this study, we investigate the effectiveness of studying the variation of non-synonymous to synonymous SNP ratios between resistant and susceptible cultivars in the target QTL regions as a strategy to narrow down the number of likely candidate genes for Rpv3, Ren3 and Ren9.

genetics↗

bioRxiv2021

Plant detection and counting from high-resolution RGB images acquired from UAVs: comparison between deep-learning and handcrafted methods with application to maize, sugar beet, and sunflower crops

Progresses in agronomy rely on accurate measurement of the experimentations conducted to improve the yield component. Measurement of the plant density is required for a number of applications since it drives part of the crop fate. The standard manual measurements in the field could be efficiently replaced by high-throughput techniques based on high-spatial resolution images taken from UAVs. This study compares several automated detection of individual plants in the images from which the plant density can be estimated. It is based on a large dataset of high resolution Red/Green/Blue (RGB) images acquired from Unmanned Aerial Vehicules (UAVs) during several years and experiments over maize, sugar beet and sunflower crops at early stages. A total of 16247 plants have been labelled interactively on the images. Performances of handcrafted method (HC) were compared to those of deep learning (DL). The HC method consists in segmenting the image into green and background pixels, identifying rows, then objects corresponding to plants thanks to knowledge of the sowing pattern as prior information. The DL method is based on the Faster Region with Convolutional Neural Network (Faster RCNN) model trained over 2/3 of the images selected to represent a good balance between plant development stage and sessions. One model is trained for each crop. Results show that simple DL methods generally outperforms simple HC, particularly for maize and sunflower crops. A significant level of variability of plant detection performances is observed between the several experiments. This was explained by the variability of image acquisition conditions including illumination, plant development stage, background complexity and weed infestation. The image quality determines part of the performances for HC methods which makes the segmentation step more difficult. Performances of DL methods are limited mainly by the presence of weeds. A hybrid method (HY) was proposed to eliminate weeds between the rows using the rules developed for the HC method. HY improves slightly DL performances in the case of high weed infestation. When few images corresponding to the conditions of the testing dataset were complementing the training dataset for DL, a drastic increase of performances for all the crops is observed, with relative RMSE below 5% for the estimation of the plant density.

plant biology↗

bioRxiv2019

Large-scale in-vitro production of red blood cells from human peripheral blood mononuclear cells

Transfusion of donor-derived red blood cells is the most common form of cellular therapy. Donor availability and the potential risk of alloimmunization and other transfusion-related complications may, however, limit the availability of transfusion units especially for chronically transfused patients. In-vitro cultured, customizable red blood cells would negate these concerns and introduce precision medicine. Large-scale, cost effective production depends on optimization of culture conditions. We developed a defined medium and adapted our protocols to GMP culture requirements, which reproducibly provided pure erythroid cultures from peripheral blood mononuclear cells without prior CD34+ isolation, and a 3x107-fold increase in erythroblasts in 25 days. Expanded erythroblast cultures could be differentiated to CD71dimCD235a+CD44+CD117-DRAQ5- red blood cells in 12 days. More than 90% of the cells enucleated and expressed adult hemoglobin as well as the correct blood group antigens. Deformability and oxygen binding capacity of cultured red blood cells was comparable to in-vivo reticulocytes. Daily RNA sampling during differentiation followed by RNA-seq provided a high-resolution map/resource of changes occurring during terminal erythropoiesis. The culture process was compatible with upscaling using a G-Rex bioreactor with a capacity of 1L per reactor, allowing transition towards clinical studies and small-scale applications.

cell biology↗

bioRxiv2018

Polyfunctional tumor-reactive T cells are effectively expanded from non-small cell lung cancers, and correlate with an immune-engaged T cell profile in situ

Non-small cell lung cancer (NSCLC) is the second most prevalent type of cancer. With the current treatment regimens, the mortality rate remains high. Therefore, better therapeutic approaches are necessary. NSCLCs generally possess many genetic mutations and are well infiltrated by T cells (TIL), making TIL therapy an attractive option. Here we show that T cells from treatment naive, stage I-IVa NSCLC tumors can effectively be isolated and expanded, with similar efficiency as from normal lung tissue. Importantly, 76% (13/17) of tested TIL products isolates from NSCLC lesions exhibited clear reactivity against primary tumor digests, with 0.5%-30% of T cells producing the inflammatory cytokine Interferon (IFN)-{gamma}. Both CD4+ and CD8+ T cells displayed tumor reactivity. The cytokine production correlated well with CD137 and CD40L expression. Furthermore, almost half (7/17) of the TIL products contained polyfunctional T cells that produced Tumor Necrosis Factor (TNF)- and/or IL-2 in addition to IFN-{gamma}, a hallmark of effective immune responses. Tumor-reactivity in the TIL products correlated with high percentages of CD103+CD69+CD8+ T cell infiltrates in the tumor lesions, with PD-1hiCD4+ T cells, and with FoxP3+CD25+CD4+ regulatory T cell infiltrates, suggesting that the composition of T cell infiltrates may predict the level of tumor reactivity. In conclusion, the effective generation of tumor-reactive and polyfunctional TIL products implies that TIL therapy will be a successful treatment regimen for NSCLC patients.

immunology↗

bioRxiv2018

Heliaphen, an outdoor high-throughput phenotyping platform designed to integrate genetics and crop modeling

Heliaphen is an outdoor pot platform designed for high-throughput phenotyping. It allows automated management of drought scenarios and plant monitoring during the whole plant cycle. A robot moving between plants growing in 15L pots monitors plant water status and phenotypes plant or leaf morphology, from which we can compute more complex traits such as the response of leaf expansion (LE) or plant transpiration (TR) to water deficit. Here, we illustrate the platform capabilities for sunflower on two practical cases: a genetic and genomics study for the response to drought of yield-related traits and a simulation study, where we use measured parameters as inputs for a crop simulation model. For the genetic study, classical measurements of thousand-kernel weight (TKW) were done on a sunflower bi-parental population under water stress and control conditions managed automatically. The association study using the TKW drought-response highlighted five genetic markers. A complementary transcriptomic experiment identified closeby candidate genes differentially expressed in the parental backgrounds in drought conditions. For the simulation study, we used the SUNFLO crop simulation model to assess the impact of two traits measured on the platform (LE and TR) on crop yield in a large population of environments. We conducted simulations in 42 contrasted locations across Europe and 21 years of climate data. We defined the pattern of abiotic stresses occurring at this continental scale and identified ideotypes (i.e. genotypes with specific traits values) that are more adapted to specific environment types. This study exemplifies how phenotyping platforms can help with the identification of the genetic architecture of complex response traits and the estimation of eco-physiological model parameters in order to define ideotypes adapted to different environmental conditions.

plant biology↗