The need for agriculture phenotyping: "moving from genotype to phenotype"

Physiology of anammox adaptation to low temperatures and promising biomarkers: A review

The adaptation of bacteria involved in the anaerobic ammonium oxidation (anammox) to low temperatures in the mainstream of WWTP will unlock substantial treatment savings. However, their adaptation mechanisms have begun to be revealed only very recently. This study reviewed the state-of-the-art knowledge on these mechanisms from -omics studies, crucially including metaproteomics and metabolomics. Anammox bacteria adapt to low temperatures by synthesizing both chaperones of RNA and proteins and chemical chaperones. Furthermore, they preserve energy for the core metabolism by reducing biosynthesis in general. Thus, in this study, a number of biomarkers are proposed to help practitioners assess the extent of anammox bacteria adaptation and predict the decomposition of biofilms/granules or slower growth. The promising biomarkers also include unique ladderane lipids. Further proteomic and metabolomic studies are necessary for a more detailed understanding of anammox low-temperature adaptation, thus easing the transition to more cost-effective and sustainable wastewater treatment.

Estimating Conformational Traits in Dairy Cattle With DeepAPS: A Two-Step Deep Learning Automated Phenotyping and Segmentation Approach

Assessing conformation features in an accurate and rapid manner remains a challenge in the dairy industry. While recent developments in computer vision has greatly improved automated background removal, these methods have not been fully translated to biological studies. Here, we present a composite method (DeepAPS) that combines two readily available algorithms in order to create a precise mask for an animal image. This method performs accurately when compared with manual classification of proportion of coat color with an adjusted R² = 0.926. Using the output mask, we are able to automatically extract useful phenotypic information for 14 additional morphological features. Using pedigree and image information from a web catalog (www.semex.com), we estimated high heritabilities (ranging from h² = 0.18–0.82), indicating that meaningful biological information has been extracted automatically from imaging data. This method can be applied to other datasets and requires only a minimal number of image annotations (∼50) to train this partially supervised machine-learning approach. DeepAPS allows for the rapid and accurate quantification of multiple phenotypic measurements while minimizing study cost. The pipeline is available at https://github.com/lauzingaretti/deepaps.

Distributed phenomics with the unPAK project reveals the effects of mutations

Determining how genes are associated with traits in plants and other organisms is a major challenge in modern biology. The unPAK project - undergraduates phenotyping Arabidopsis knockouts - has generated phenotype data for thousands of non-lethal insertion mutation lines within a single Arabidopsis thaliana genomic background. The focal phenotypes examined by unPAK are complex macroscopic fitness-related traits, which have ecological, evolutionary and agricultural importance. These phenotypes are placed in the context of the wild-type and also natural accessions (phytometers), and standardized for environmental differences between assays. Data from the unPAK project are used to describe broad patterns in the phenotypic consequences of insertion mutation, and to identify individual mutant lines with distinct phenotypes as candidates for further study. Inclusion of undergraduate researchers is at the core of unPAK activities, and an important broader impact of the project is providing students an opportunity to obtain research experience.

Use of Natural Diversity and Biotechnology to Increase the Quality and Nutritional Content of Tomato and Grape

Improving fruit quality has become a major goal in plant breeding. Direct approaches to tackling fruit quality traits specifically linked to consumer preferences and environmental friendliness, such as improved flavor, nutraceutical compounds, and sustainability, have slowly been added to a breeder priority list that already includes traits like productivity, efficiency, and, especially, pest and disease control. Breeders already use molecular genetic tools to improve fruit quality although most advances have been made in producer and industrial quality standards. Furthermore, progress has largely been limited to simple agronomic traits easy-to-observe, whereas the vast majority of quality attributes, specifically those relating to flavor and nutrition, are complex and have mostly been neglected. Fortunately, wild germplasm, which is used for resistance against/tolerance of environmental stresses (including pathogens), is still available and harbors significant genetic variation for taste and health-promoting traits. Similarly, heirloom/traditional varieties could be used to identify which genes contribute to flavor and health quality and, at the same time, serve as a good source of the best alleles for organoleptic quality improvement. Grape (Vitis vinifera L.) and tomato (Solanum lycopersicum L.) produce fleshy, berry-type fruits, among the most consumed in the world. Both have undergone important domestication and selection processes, that have dramatically reduced their genetic variability, and strongly standardized fruit traits. Moreover, more and more consumers are asking for sustainable production, incompatible with the wide range of chemical inputs. In the present paper, we review the genetic resources available to tomato/grape breeders, and the recent technological progresses that facilitate the identification of genes/alleles of interest within the natural or generated variability gene pool. These technologies include omics, high-throughput phenotyping/phenomics, and biotech approaches. Our review also covers a range of technologies used to transfer to tomato and grape those alleles considered of interest for fruit quality. These include traditional breeding, TILLING (Targeting Induced Local Lesions in Genomes), genetic engineering, or NPBT (New Plant Breeding Technologies). Altogether, the combined exploitation of genetic variability and innovative biotechnological tools may facilitate breeders to improve fruit quality tacking more into account the consumer standards and the needs to move forward into more sustainable farming practices.

Cereal Crop Proteomics: Systemic Analysis of Crop Drought Stress Responses Towards Marker-Assisted Selection Breeding

Sustainable crop production is the major challenge in the current global climate change scenario. Drought stress is one of the most critical abiotic factors which negatively impact crop productivity. In recent years, knowledge about molecular regulation has been generated to understand drought stress responses. For example, information obtained by transcriptome analysis has enhanced our knowledge and facilitated the identification of candidate genes which can be utilized for plant breeding. On the other hand, it becomes more and more evident that the translational and post-translational machinery plays a major role in stress adaptation, especially for immediate molecular processes during stress adaptation. Therefore, it is essential to measure protein levels and post-translational protein modifications to reveal information about stress inducible signal perception and transduction, translational activity and induced protein levels. This information cannot be revealed by genomic or transcriptomic analysis. Eventually, these processes will provide more direct insight into stress perception then genetic markers and might build a complementary basis for future marker-assisted selection of drought resistance. In this review, we survey the role of proteomic studies to illustrate their applications in crop stress adaptation analysis with respect to productivity. Cereal crops such as wheat, rice, maize, barley, sorghum and pearl millet are discussed in detail. We provide a comprehensive and comparative overview of all detected protein changes involved in drought stress in these crops and have summarized existing knowledge into a proposed scheme of drought response. Based on a recent proteome study of pearl millet under drought stress we compare our findings with wheat proteomes and another recent study which defined genetic marker in pearl millet.

Mechanisms of protein balance in skeletal muscle

Increased global demand for adequate protein nutrition against a backdrop of climate change and concern for animal agriculture sustainability necessitates new and more efficient approaches to livestock growth and production. Anabolic growth is achieved when rates of new synthesis exceed turnover, producing a positive net protein balance. Conversely, deterioration or atrophy of lean mass is a consequence of a net negative protein balance. During early life and periods of growth, muscle mass is driven by increases in protein synthesis at the level of mRNA translation. Throughout life, muscle mass is further influenced by degradative processes such as autophagy and the ubiquitin proteasome pathway. Multiple signal transduction networks guide and coordinate these processes alongside quality control mechanisms to maintain protein homeostasis (proteostasis). Genetics, hormones, and environmental stimuli each influence proteostasis control, altering capacity and/or efficiency of muscle growth. An overview of recent findings and current methods to assess muscle protein balance and proteostasis is presented. Current efforts to identify novel control points have the potential through selective breeding design or development of hormetic strategies to better promote growth and health span during environmental stress.

Molecular and systems approaches towards drought-tolerant canola crops

1169 I. 1170 II. 1170 III. 1172 IV. 1176 V. 1181 VI. 1182 1183 References 1183 SUMMARY: Modern agriculture is facing multiple challenges including the necessity for a substantial increase in production to meet the needs of a burgeoning human population. Water shortage is a deleterious consequence of both population growth and climate change and is one of the most severe factors limiting global crop productivity. Brassica species, particularly canola varieties, are cultivated worldwide for edible oil, animal feed, and biodiesel, and suffer dramatic yield loss upon drought stress. The recent release of the Brassica napus genome supplies essential genetic information to facilitate identification of drought-related genes and provides new information for agricultural improvement in this species. Here we summarize current knowledge regarding drought responses of canola, including physiological and -omics effects of drought. We further discuss knowledge gained through translational biology based on discoveries in the closely related reference species Arabidopsis thaliana and through genetic strategies such as genome-wide association studies and analysis of natural variation. Knowledge of drought tolerance/resistance responses in canola together with research outcomes arising from new technologies and methodologies will inform novel strategies for improvement of drought tolerance and yield in this and other important crop species.

Challenges and opportunities of bovine milk analysis by mass spectrometry

Bovine milk and its products (e.g. cheese, yoghurt) are an important part of human diet with beneficial effects for all ages. Although analyses of different milk components (e.g. proteins, lipids) pose huge challenges, the use of mass spectrometric (MS)-based techniques is steadily improving our understanding of the complexity of the biological traits that effect milk yield and its components to meet the global demand arising from population growth. In addition, different milk constituents have various applications in veterinary research and medicine, including early disease diagnosis. The aim of the review is to present an overview of the progress made in MS-based analysis of milk, and suggest a multi-pronged MS strategy to better explore different milk components for translational and clinical utilities.

Nutritional strategies to optimize dairy cattle immunity

Dairy cattle are susceptible to increased incidence and severity of both metabolic and infectious diseases during the periparturient period. A major contributing factor to increased health disorders is alterations in bovine immune mechanisms. Indeed, uncontrolled inflammation is a major contributing factor and a common link among several economically important infectious and metabolic diseases including mastitis, retained placenta, metritis, displaced abomasum, and ketosis. The nutritional status of dairy cows and the metabolism of specific nutrients are critical regulators of immune cell function. There is now a greater appreciation that certain mediators of the immune system can have a reciprocal effect on the metabolism of nutrients. Thus, any disturbances in nutritional or immunological homeostasis can provide deleterious feedback loops that can further enhance health disorders, increase production losses, and decrease the availability of safe and nutritious dairy foods for a growing global population. This review will discuss the complex interactions between nutrient metabolism and immune functions in periparturient dairy cattle. Details of how either deficiencies or overexposure to macro- and micronutrients can contribute to immune dysfunction and the subsequent development of health disorders will be presented. Specifically, the ways in which altered nutrient metabolism and oxidative stress can interact to compromise the immune system in transition cows will be discussed. A better understanding of the linkages between nutrition and immunity may facilitate the design of nutritional regimens that will reduce disease susceptibility in early lactation cows.

The "Dark Side" of Food Stuff Proteomics: The CPLL-Marshals Investigate

The present review deals with analysis of the proteome of animal and plant-derived food stuff, as well as of non-alcoholic and alcoholic beverages. The survey is limited to those systems investigated with the help of combinatorial peptide ligand libraries, a most powerful technique allowing access to low- to very-low-abundance proteins, i.e., to those proteins that might characterize univocally a given biological system and, in the case of commercial food preparations, attest their genuineness or adulteration. Among animal foods the analysis of cow's and donkey's milk is reported, together with the proteomic composition of egg white and yolk, as well as of honey, considered as a hybrid between floral and animal origin. In terms of plant and fruits, a survey is offered of spinach, artichoke, banana, avocado, mango and lemon proteomics, considered as recalcitrant tissues in that small amounts of proteins are dispersed into a large body of plant polymers and metabolites. As examples of non-alcoholic beverages, ginger ale, coconut milk, a cola drink, almond milk and orgeat syrup are analyzed. Finally, the trace proteome of white and red wines, beer and aperitifs is reported, with the aim of tracing the industrial manipulations and herbal usage prior to their commercialization.