Carbon usage in yellow-fleshed Manihot esculenta storage roots shifts from starch biosynthesis to cell wall and raffinose biosynthesis via the myo-inositol pathway

Cassava is a crucial staple crop for smallholder farmers in tropical Asia and Sub-Saharan Africa. Although high yield remains the top priority for farmers, the significance of nutritional values has increased in cassava breeding programs. A notable negative correlation between provitamin A and starch accumulation poses a significant challenge for breeding efforts. The negative correlation between starch and carotenoid levels in conventional and genetically modified cassava plants implies the absence of a direct genomic connection between the two traits. The competition among various carbon pathways seems to account for this relationship. In this study, we conducted a thorough analysis of 49 African cassava genotypes with varying levels of starch and provitamin A. Our goal was to identify factors contributing to differential starch accumulation. Considering carotenoid levels as a confounding factor in starch production, we found that yellow- and white-fleshed storage roots did not differ significantly in most measured components of starch or de novo fatty acid biosynthesis. However, genes and metabolites associated with myo-inositol synthesis and cell wall polymer production were substantially enriched in high provitamin A genotypes. These results indicate that yellow-fleshed cultivars, in comparison to their white-fleshed counterparts, direct more carbon toward the synthesis of raffinose and cell wall components. This finding is underlined by a significant rise in cell wall components measured within the 20 most contrasting genotypes for carotenoid levels. Our findings enhance the comprehension of the biosynthesis of starch and carotenoids in the storage roots of cassava.

Efficient sugar utilization and transition from oxidative to substrate-level phosphorylation in high starch storage roots of African cassava genotypes

Cassava's storage roots represent one of the most important sources of nutritional carbohydrates worldwide. Particularly, smallholder farmers in sub-Saharan Africa depend on this crop plant, where resilient and yield-improved varieties are of vital importance to support steadily increasing populations. Aided by a growing understanding of the plant's metabolism and physiology, targeted improvement concepts already led to visible gains in recent years. To expand our knowledge and to contribute to these successes, we investigated storage roots of eight cassava genotypes with differential dry matter content from three successive field trials for their proteomic and metabolic profiles. At large, the metabolic focus in storage roots transitioned from cellular growth processes toward carbohydrate and nitrogen storage with increasing dry matter content. This is reflected in higher abundance of proteins related to nucleotide synthesis, protein turnover, and vacuolar energization in low starch genotypes, while proteins involved in sugar conversion and glycolysis were more prevalent in high dry matter genotypes. This shift in metabolic orientation was underlined by a clear transition from oxidative- to substrate-level phosphorylation in high dry matter genotypes. Our analyses highlight metabolic patterns that are consistently and quantitatively associated with high dry matter accumulation in cassava storage roots, providing fundamental understanding of cassava's metabolism as well as a data resource for targeted genetic improvement.

Detecting variation in starch granule size and morphology by high-throughput microscopy and flow cytometry

Starch forms semi-crystalline, water-insoluble granules, the size and morphology of which vary according to biological origin. These traits, together with polymer composition and structure, determine the physicochemical properties of starch. However, screening methods to identify differences in starch granule size and shape are lacking. Here, we present two approaches for high-throughput starch granule extraction and size determination using flow cytometry and automated, high-throughput light microscopy. We evaluated the practicality of both methods using starch from different species and tissues and demonstrated their effectiveness by screening for induced variation in starch extracted from over 10,000 barley lines, yielding four with heritable changes in the ratio of large A-granules to small B-granules. Analysis of Arabidopsis lines altered in starch biosynthesis further demonstrates the applicability of these approaches. Identifying variation in starch granule size and shape will enable identification of trait-controlling genes for developing crops with desired properties, and could help optimise starch processing.

Set up from the beginning: The origin and early development of cassava storage roots

Despite the importance of storage root (SR) organs for cassava and the other root crops yield, their developmental origin is poorly understood. Here we use multiple approaches to shed light on the initial stages of root development demonstrating that SR and fibrous roots (FR) follow different rhizogenic processes. Transcriptome analysis carried out on roots collected before, during and after root bulking highlighted early and specific activation of a number of functions essential for root swelling and identified root-specific genes able to effectively discriminate emerging FR and SR. Starch and sugars start to accumulate at a higher rate in SR before they swell but only after parenchyma tissue has been produced. Finally, using non-destructive computed tomography measurements, we show that SR (but not FR) contain, since their emergence from the stem, an inner channel structure in continuity with the stem secondary xylem, indicating that SR derive from a distinct rhizogenic process compared with FR.

Datasets from harmonised metabolic phenotyping of root, tuber and banana crop

Biochemical characterisation of germplasm collections and crop wild relatives (CWRs) facilitates the assessment of biological potential and the selection of breeding lines for crop improvement. Data from the biochemical characterisation of staple root, tuber and banana (RTB) crops, i.e. banana (Musa spp.), cassava (Manihot esculenta), potato (Solanum tuberosum), sweet potato (Ipomoea batatas) and yam (Dioscorea spp.), using a metabolomics approach is presented. The data support the previously published research article “Metabolite database for root, tuber, and banana crops to facilitate modern breeding in understudied crops” (Price et al., 2020) [1].

Diversity panels for each crop, which included a variety of species, accessions, landraces and CWRs, were characterised. The biochemical profile for potato was based on five elite lines under abiotic stress. Metabolites were extracted from the tissue of foliage and storage organs (tuber, root and banana pulp) via solvent partition. Extracts were analysed via a combination of liquid chromatography – mass spectrometry (LC-MS), gas chromatography (GC)-MS, high pressure liquid chromatography with photodiode array detector (HPLC-PDA) and ultra performance liquid chromatography (UPLC)-PDA. Metabolites were identified by mass spectral matching to in-house libraries comprised from authentic standards and comparison to databases or previously published literature.

A population based expression atlas provides insights into disease resistance and other physiological traits in cassava (Manihot esculenta Crantz)

Cassava, a food security crop in Africa, is grown throughout the tropics and subtropics. Although cassava can provide high productivity in suboptimal conditions, the yield in Africa is substantially lower than in other geographies. The yield gap is attributable to many challenges faced by cassava in Africa, including susceptibility to diseases and poor soil conditions. In this study, we carried out 3’RNA sequencing on 150 accessions from the National Crops Resources Research Institute, Uganda for 5 tissue types, providing population-based transcriptomics resources to the research community in a web-based queryable cassava expression atlas. Differential expression and weighted gene co-expression network analysis were performed to detect 8820 significantly differentially expressed genes (DEGs), revealing similarity in expression patterns between tissue types and the clustering of detected DEGs into 18 gene modules. As a confirmation of data quality, differential expression and pathway analysis targeting cassava mosaic disease (CMD) identified 27 genes observed in the plant–pathogen interaction pathway, several previously identified CMD resistance genes, and two peroxidase family proteins different from the CMD2 gene. Present research work represents a novel resource towards understanding complex traits at expression and molecular levels for the development of resistant and high-yielding cassava varieties, as exemplified with CMD.

Assessing Protein Synthesis and Degradation Rates in Arabidopsis thaliana Using Amino Acid Analysis

Plants continually synthesize and degrade proteins, for example, to adjust protein content during development or during adaptation to new environments. In order to estimate global protein synthesis and degradation rates in plants, we developed a relatively simple and inexpensive method using a combination of ¹³ CO₂ labeling and mass spectrometry-based analyses. Arabidopsis thaliana plants are subjected to a 24-hr ¹³ CO₂ pulse followed by a 4-day ¹² CO₂ chase. Soluble alanine and serine from total protein and glucose from cell wall material are analyzed by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) and their ¹³ C enrichment (%) is estimated. The rate of protein synthesis during the ¹³ CO₂ pulse experiment is defined as the rate of incorporation of labeled amino acids into proteins normalized by a correction factor for incomplete enrichment in free amino acid pools. The rate of protein degradation is estimated as the difference between the rate of protein synthesis and the relative growth rate calculated using the ¹³ C enrichment of glucose from cell wall material. Degradation rates are also estimated from the ¹² CO₂ pulse experiment. The following method description includes setting up and performing labeling experiments, preparation and measurement of samples, and calculation steps. In addition, an R script is provided for the calculations. 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Setting up the ¹³ CO₂ labeling system and stable isotope labeling of Arabidopsis thaliana rosette leaves Basic Protocol 2: Extraction of soluble amino acids for GC-TOF-MS analysis Basic Protocol 3: Preparation of amino acids from total protein for GC-TOF-MS analysis Basic Protocol 4: Preparation of sugars from cell wall material for GC-TOF-MS analysis Basis Protocol 5: GC-TOF-MS analysis of ¹³ C-labeled samples and estimation of ¹³ C enrichment (%) Basis Protocol 6: Estimation of protein synthesis and degradation rates.

Highly dynamic, coordinated, and stage-specific profiles are revealed by a multi-omics integrative analysis during tuberous root development in cassava

Cassava (Manihot esculenta) is an important starchy root crop that provides food for millions of people worldwide, but little is known about the regulation of the development of its tuberous root at the multi-omics level. In this study, the transcriptome, proteome, and metabolome were examined in parallel at seven time-points during the development of the tuberous root from the early to late stages of its growth. Overall, highly dynamic and stage-specific changes in the expression of genes/proteins were observed during development. Cell wall and auxin genes, which were regulated exclusively at the transcriptomic level, mainly functioned during the early stages. Starch biosynthesis, which was controlled at both the transcriptomic and proteomic levels, was mainly activated in the early stages and was greatly restricted during the late stages. Two main branches of lignin biosynthesis, coniferyl alcohol and sinapyl alcohol, also functioned during the early stages of development at both the transcriptomic and proteomic levels. Metabolomic analysis further supported the stage-specific roles of particular genes/proteins. Metabolites related to lignin and flavonoid biosynthesis showed high abundance during the early stages, those related to lipids exhibited high abundance at both the early and middle stages, while those related to amino acids were highly accumulated during the late stages. Our findings provide a comprehensive resource for broadening our understanding of tuberous root development and will facilitate future genetic improvement of cassava.

The Cassava Source-Sink project: opportunities and challenges for crop improvement by metabolic engineering

Cassava (Manihot esculenta Crantz) is one of the important staple foods in Sub-Saharan Africa. It produces starchy storage roots that provide food and income for several hundred million people, mainly in tropical agriculture zones. Increasing cassava storage root and starch yield is one of the major breeding targets with respect to securing the future food supply for the growing population of Sub-Saharan Africa. The Cassava Source-Sink (CASS) project aims to increase cassava storage root and starch yield by strategically integrating approaches from different disciplines. We present our perspective and progress on cassava as an applied research organism and provide insight into the CASS strategy, which can serve as a blueprint for the improvement of other root and tuber crops. Extensive profiling of different field-grown cassava genotypes generates information for leaf, phloem, and root metabolic and physiological processes that are relevant for biotechnological improvements. A multi-national pipeline for genetic engineering of cassava plants covers all steps from gene discovery, cloning, transformation, molecular and biochemical characterization, confined field trials, and phenotyping of the seasonal dynamics of shoot traits under field conditions. Together, the CASS project generates comprehensive data to facilitate conventional breeding strategies for high-yielding cassava genotypes. It also builds the foundation for genome-scale metabolic modelling aiming to predict targets and bottlenecks in metabolic pathways. This information is used to engineer cassava genotypes with improved source-sink relations and increased yield potential.