Genome-wide association study and network analysis of in vitro transformation in Populus trichocarpa support key roles of diverse phytohormone pathways and cross talk.

Wide variation in amenability to transformation and regeneration (TR) among many plant species and genotypes presents a challenge to the use of genetic engineering in research and breeding. To help understand the causes of this variation, we performed association mapping and network analysis using a population of 1204 wild trees of Populus trichocarpa (black cottonwood). To enable precise and high-throughput phenotyping of callus and shoot TR, we developed a computer vision system that cross-referenced complementary red, green, and blue (RGB) and fluorescent-hyperspectral images. We performed association mapping using single-marker and combined variant methods, followed by statistical tests for epistasis and integration of published multi-omic datasets to identify likely regulatory hubs. We report 409 candidate genes implicated by associations within 5 kb of coding sequences, and epistasis tests implicated 81 of these candidate genes as regulators of one another. Gene ontology terms related to protein-protein interactions and transcriptional regulation are overrepresented, among others. In addition to auxin and cytokinin pathways long established as critical to TR, our results highlight the importance of stress and wounding pathways. Potential regulatory hubs of signaling within and across these pathways include GROWTH REGULATORY FACTOR 1 (GRF1), PHOSPHATIDYLINOSITOL 4-KINASE ß1 (PI-4Kß1), and OBF-BINDING PROTEIN 1 (OBP1).

CVID enteropathy is characterized by exceeding low mucosal IgA levels and interferon-driven inflammation possibly related to the presence of a pathobiont.

Common variable immunodeficiency (CVID), the most common symptomatic primary antibody deficiency, is accompanied in some patients by a duodenal inflammation and malabsorption syndrome known as CVID enteropathy (E-CVID).The goal of this study was to investigate the immunological abnormalities in CVID patients that lead to enteropathy as well as the contribution of intestinal microbiota to this process.We found that, in contrast to noE-CVID patients (without enteropathy), E-CVID patients have exceedingly low levels of IgA in duodenal tissues. In addition, using transkingdom network analysis of the duodenal microbiome, we identified Acinetobacter baumannii as a candidate pathobiont in E-CVID. Finally, we found that E-CVID patients exhibit a pronounced activation of immune genes and down-regulation of epithelial lipid metabolism genes. We conclude that in the virtual absence of mucosal IgA, pathobionts such as A. baumannii, may induce inflammation that re-directs intestinal molecular pathways from lipid metabolism to immune processes responsible for enteropathy.

GWAS supported by computer vision identifies large numbers of candidate regulators of in planta regeneration in Populus trichocarpa.

Plant regeneration is an important dimension of plant propagation and a key step in the production of transgenic plants. However, regeneration capacity varies widely among genotypes and species, the molecular basis of which is largely unknown. Association mapping methods such as genome-wide association studies (GWAS) have long demonstrated abilities to help uncover the genetic basis of trait variation in plants; however, the performance of these methods depends on the accuracy and scale of phenotyping. To enable a large-scale GWAS of in planta callus and shoot regeneration in the model tree Populus, we developed a phenomics workflow involving semantic segmentation to quantify regenerating plant tissues over time. We found that the resulting statistics were of highly non-normal distributions, and thus employed transformations or permutations to avoid violating assumptions of linear models used in GWAS. We report over 200 statistically supported quantitative trait loci (QTLs), with genes encompassing or near to top QTLs including regulators of cell adhesion, stress signaling, and hormone signaling pathways, as well as other diverse functions. Our results encourage models of hormonal signaling during plant regeneration to consider keystone roles of stress-related signaling (e.g. involving jasmonates and salicylic acid), in addition to the auxin and cytokinin pathways commonly considered. The putative regulatory genes and biological processes we identified provide new insights into the biological complexity of plant regeneration, and may serve as new reagents for improving regeneration and transformation of recalcitrant genotypes and species.

GWAS identifies candidate genes controlling adventitious rooting in Populus trichocarpa.

Adventitious rooting (AR) is critical to the propagation, breeding, and genetic engineering of trees. The capacity for plants to undergo this process is highly heritable and of a polygenic nature; however, the basis of its genetic variation is largely uncharacterized. To identify genetic regulators of AR, we performed a genome-wide association study (GWAS) using 1148 genotypes of Populus trichocarpa. GWASs are often limited by the abilities of researchers to collect precise phenotype data on a high-throughput scale; to help overcome this limitation, we developed a computer vision system to measure an array of traits related to adventitious root development in poplar, including temporal measures of lateral and basal root length and area. GWAS was performed using multiple methods and significance thresholds to handle non-normal phenotype statistics and to gain statistical power. These analyses yielded a total of 277 unique associations, suggesting that genes that control rooting include regulators of hormone signaling, cell division and structure, reactive oxygen species signaling, and other processes with known roles in root development. Numerous genes with uncharacterized functions and/or cryptic roles were also identified. These candidates provide targets for functional analysis, including physiological and epistatic analyses, to better characterize the complex polygenic regulation of AR.

Robust High-Throughput Phenotyping with Deep Segmentation Enabled by a Web-Based Annotator.

The abilities of plant biologists and breeders to characterize the genetic basis of physiological traits are limited by their abilities to obtain quantitative data representing precise details of trait variation, and particularly to collect this data at a high-throughput scale with low cost. Although deep learning methods have demonstrated unprecedented potential to automate plant phenotyping, these methods commonly rely on large training sets that can be time-consuming to generate. Intelligent algorithms have therefore been proposed to enhance the productivity of these annotations and reduce human efforts. We propose a high-throughput phenotyping system which features a Graphical User Interface (GUI) and a novel interactive segmentation algorithm: Semantic-Guided Interactive Object Segmentation (SGIOS). By providing a user-friendly interface and intelligent assistance with annotation, this system offers potential to streamline and accelerate the generation of training sets, reducing the effort required by the user. Our evaluation shows that our proposed SGIOS model requires fewer user inputs compared to the state-of-art models for interactive segmentation. As a case study of the use of the GUI applied for genetic discovery in plants, we present an example of results from a preliminary genome-wide association study (GWAS) of in planta regeneration in Populus trichocarpa (poplar). We further demonstrate that the inclusion of a semantic prior map with SGIOS can accelerate the training process for future GWAS, using a sample of a dataset extracted from a poplar GWAS of in vitro regeneration. The capabilities of our phenotyping system surpass those of unassisted humans to rapidly and precisely phenotype our traits of interest. The scalability of this system enables large-scale phenomic screens that would otherwise be time-prohibitive, thereby providing increased power for GWAS, mutant screens, and other studies relying on large sample sizes to characterize the genetic basis of trait variation. Our user-friendly system can be used by researchers lacking a computational background, thus helping to democratize the use of deep segmentation as a tool for plant phenotyping.

Neither heat pulse, nor multigenerational exposure to a modest increase in water temperature, alters the susceptibility of Guadeloupean Biomphalaria glabrata to Schistosoma mansoni infection.

There are increasing concerns regarding the role global climate change will have on many vector-borne diseases. Both mathematical models and laboratory experiments suggest that schistosomiasis risk may change as a result of the effects of increasing temperatures on the planorbid snails that host schistosomes. Heat pulse/heat shock of the BS90 strain of Biomphalaria glabrata was shown to increase the rate of infection by Schistosoma mansoni, but the result was not replicable in a follow up experiment by a different lab. We characterised the susceptibility and cercarial shedding of Guadeloupean B. glabrata after infection with S. mansoni under two temperature regimes: multigenerational exposure to small increases in temperature, and extreme heat pulse events. Neither long-term, multigenerational rearing at elevated temperatures, nor transient heat pulse modified the susceptibility of Guadeloupean B. glabrata to infection (prevalence) or shedding of schistosome cercaria (intensity of infection). These findings suggest that heat pulse-induced susceptibility in snail hosts may be dependent on the strain of the snail and/or schistosome, or on some as-yet unidentified environmental co-factor.

Clusters of polymorphic transmembrane genes control resistance to schistosomes in snail vectors.

Schistosomiasis is a debilitating parasitic disease infecting hundreds of millions of people. Schistosomes use aquatic snails as intermediate hosts. A promising avenue for disease control involves leveraging innate host mechanisms to reduce snail vectorial capacity. In a genome-wide association study of Biomphalaria glabrata snails, we identify genomic region PTC2 which exhibits the largest known correlation with susceptibility to parasite infection (>15 fold effect). Using new genome assemblies with substantially higher contiguity than the Biomphalaria reference genome, we show that PTC2 haplotypes are exceptionally divergent in structure and sequence. This variation includes multi-kilobase indels containing entire genes, and orthologs for which most amino acid residues are polymorphic. RNA-Seq annotation reveals that most of these genes encode single-pass transmembrane proteins, as seen in another resistance region in the same species. Such groups of hyperdiverse snail proteins may mediate host-parasite interaction at the cell surface, offering promising targets for blocking the transmission of schistosomiasis.

Schistosomiasis is a widespread parasitic disease, affecting over 200 million people in tropical countries. It is caused by schistosome worms, which are carried by freshwater snails. These snails release worm larvae into the water, where they can infect humans ­ for example, after bathing or swimming. Treatment options for schistosomiasis are limited. Eliminating the freshwater snails is one way to control the disease, but this is not always effective in the long term and the chemicals used can also harm other animals in the water. Another way to manage schistosomiasis could be to stop the worms from infecting their snail host by breaking the parasites' life cycle without killing the snails. It is already known that some snails are naturally resistant to infection by some strains of schistosomes. Since this immunity is also inherited by the offspring of resistant snails, there is likely a genetic mechanism behind it. However, very little else is known about any genes that might be involved. Tennessen et al. therefore set out to identify what genes were responsible for schistosome resistance and how they worked. The experiments used a large laboratory colony of snails, whose susceptibility to schistosome infection varied among individual animals. To determine the genes behind this variation, Tennessen et al. first searched for areas of DNA that also differed between the immune and infected snails. Comparing genetic sequences across over 1,000 snails revealed a distinct region of DNA that had a large effect on how likely they were to be infected. This section of DNA turned out to be highly diverse, with different snails carrying varying numbers and different forms of the genes within this region. Many of these genes appear to encode proteins found on the surface of snail cells, which could affect whether snails and worms can recognize each other when they come into contact. This in turn could determine whether or not the worms can infect their hosts. These results shed new light on how the snails that carry schistosomes may be able to resist infections. In the future, this knowledge could be key to controlling schistosomiasis, either by releasing genetically engineered, immune snails into the wild (thus making it harder for the parasites to reproduce) or by using the snails' mechanism of resistance to design better drug therapies.

Akkermansia muciniphila mediates negative effects of IFNγ on glucose metabolism.

Cross-talk between the gut microbiota and the host immune system regulates host metabolism, and its dysregulation can cause metabolic disease. Here, we show that the gut microbe Akkermansia muciniphila can mediate negative effects of IFNγ on glucose tolerance. In IFNγ-deficient mice, A. muciniphila is significantly increased and restoration of IFNγ levels reduces A. muciniphila abundance. We further show that IFNγ-knockout mice whose microbiota does not contain A. muciniphila do not show improvement in glucose tolerance and adding back A. muciniphila promoted enhanced glucose tolerance. We go on to identify Irgm1 as an IFNγ-regulated gene in the mouse ileum that controls gut A. muciniphila levels. A. muciniphila is also linked to IFNγ-regulated gene expression in the intestine and glucose parameters in humans, suggesting that this trialogue between IFNγ, A. muciniphila and glucose tolerance might be an evolutionally conserved mechanism regulating metabolic health in mice and humans.