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Kulesza E, Thomas P, Prewitt SF, Shalit-Kaneh A, Wafula E, Knollenberg B, Winters N, Esteban E, Pasha A, Provart N, Praul C, Landherr L, dePamphilis C, Maximova SN, Guiltinan MJ. The cacao gene atlas: a transcriptome developmental atlas reveals highly tissue-specific and dynamically-regulated gene networks in Theobroma cacao L. BMC PLANT BIOLOGY 2024; 24:601. [PMID: 38926852 PMCID: PMC11201900 DOI: 10.1186/s12870-024-05171-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 05/19/2024] [Indexed: 06/28/2024]
Abstract
BACKGROUND Theobroma cacao, the cocoa tree, is a tropical crop grown for its highly valuable cocoa solids and fat which are the basis of a 200-billion-dollar annual chocolate industry. However, the long generation time and difficulties associated with breeding a tropical tree crop have limited the progress of breeders to develop high-yielding disease-resistant varieties. Development of marker-assisted breeding methods for cacao requires discovery of genomic regions and specific alleles of genes encoding important traits of interest. To accelerate gene discovery, we developed a gene atlas composed of a large dataset of replicated transcriptomes with the long-term goal of progressing breeding towards developing high-yielding elite varieties of cacao. RESULTS We describe the creation of the Cacao Transcriptome Atlas, its global characterization and define sets of genes co-regulated in highly organ- and temporally-specific manners. RNAs were extracted and transcriptomes sequenced from 123 different tissues and stages of development representing major organs and developmental stages of the cacao lifecycle. In addition, several experimental treatments and time courses were performed to measure gene expression in tissues responding to biotic and abiotic stressors. Samples were collected in replicates (3-5) to enable statistical analysis of gene expression levels for a total of 390 transcriptomes. To promote wide use of these data, all raw sequencing data, expression read mapping matrices, scripts, and other information used to create the resource are freely available online. We verified our atlas by analyzing the expression of genes with known functions and expression patterns in Arabidopsis (ACT7, LEA19, AGL16, TIP13, LHY, MYB2) and found their expression profiles to be generally similar between both species. We also successfully identified tissue-specific genes at two thresholds in many tissue types represented and a set of genes highly conserved across all tissues. CONCLUSION The Cacao Gene Atlas consists of a gene expression browser with graphical user interface and open access to raw sequencing data files as well as the unnormalized and CPM normalized read count data mapped to several cacao genomes. The gene atlas is a publicly available resource to allow rapid mining of cacao gene expression profiles. We hope this resource will be used to help accelerate the discovery of important genes for key cacao traits such as disease resistance and contribute to the breeding of elite varieties to help farmers increase yields.
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Affiliation(s)
- Evelyn Kulesza
- Department of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA
- Huck Institute of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Patrick Thomas
- Department of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Sarah F Prewitt
- Department of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA
- USDA Animal and Plant Health Inspection Service (APHIS), Riverdale, MD, 20737, USA
| | - Akiva Shalit-Kaneh
- Department of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA
- Plant Sciences, Volcani-ARO (Agricultural and Rural Organization), Gilat, Israel
| | - Eric Wafula
- Department of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA
- Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Benjamin Knollenberg
- Department of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA
- Mars Inc, Davis, CA, 95616, USA
| | - Noah Winters
- Department of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA
- Battelle Memorial Institute, Columbus, OH, 43201, USA
| | - Eddi Esteban
- Department of Cell & Systems Biology, Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, ON, Canada
| | - Asher Pasha
- Department of Cell & Systems Biology, Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, ON, Canada
| | - Nicholas Provart
- Department of Cell & Systems Biology, Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, ON, Canada
| | - Craig Praul
- Huck Institute of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Lena Landherr
- Department of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Claude dePamphilis
- Department of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA
- Huck Institute of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Siela N Maximova
- Department of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA
- Huck Institute of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Mark J Guiltinan
- Department of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA.
- Huck Institute of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA.
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Creating Shared Value and Strategic Corporate Social Responsibility through Outsourcing within Supply Chain Management. SUSTAINABILITY 2022. [DOI: 10.3390/su14041940] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
One way to develop local clusters is to strengthen those clusters by using outsourcing to conduct strategic social responsibility, or in other words, to create shared value, which is a win-win strategy for the buyer, supplier, and society and the best and most viable alternative to traditional corporate social responsibilities. In the leading research, a model for decision-making within the supply chain has been developed for purchasing based on shared value creation, long-term relationship management, and purchasing strategies. The research consists of two strategic mathematical models, using goal programming, and then is solved by a meta-heuristic algorithm. Potential outsourcing companies are assessed and then clustered according to their geographic locations in the decision-making process. One (or several) cluster(s) was selected among clusters based on knowledge and relationship criteria. Besides, in the primary mathematical model, the orders in different periods and the selection of suppliers are determined. In this model, in addition to optimizing the cost, the dispersion of purchases from suppliers is maximized to increase relationships and strengthen all members of the cluster. Maximizing the distribution by converting a secondary objective function to goal-programming variables transforms the multi-objective model into a single-objective model. In addition to economic benefits for buyers and suppliers, this purchasing plan concentrates on strengthening the local industrial cluster, fostering employment and ease of recruitment for human resources, accessing more infrastructures and technical support facilities, developing an education system in the region, and assisting knowledge-based enterprises with development.
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