Marcelo Mollinari
Publications
- A public mid-density genotyping platform for alfalfa (Medicago sativa L.) , Genetic Resources (2023)
- Advances in genomic characterization of Urochloa humidicola: exploring polyploid inheritance and apomixis , Theoretical and Applied Genetics (2023)
- Advances in genomic characterization ofUrochloa humidicola: exploring polyploid inheritance and apomixis , (2023)
- Advances in the Development of Chromosome-Scale Haplotype-Resolved Genome Assemblies of Hexaploid Sweetpotatoes , International Plant & Animal Genome 30 Conference (2023)
- Developing best practices for genotyping-by-sequencing analysis in the construction of linkage maps , GigaScience (2023)
- Genetic Mapping in Interconnected Hexaploid Sweetpotato Populations , International Plant & Animal Genome 30 Conference (2023)
- Selecting the Best Bioinformatic Pipeline for Evaluating Diploid and Auto-Tetraploid Garden Rose Genotype-by-Sequencing Data , International Plant & Animal Genome 30 Conference (2023)
- Developing best practices for genotyping-by-sequencing analysis using linkage maps as benchmarks , bioRxiv (2022)
- Polyploid Goes to Genomics , 21st Century Pathology (2022)
- VIEWpoly: a visualization tool to integrate and explore results of polyploid genetic analysis , Journal of Open Source Software (2022)
Grants
Banana, cassava, potato, sweetpotato and yam (collectively referred to as roots, tubers, and bananas or RTB crops hereafter) are major contributors to poverty alleviation and food and nutrition security in sub-Saharan Africa (SSA). RTB crops provide nearly 50% of total caloric intake in D.R. Congo, Ghana, Tanzania and Rwanda, 30% in Uganda, and 25% in Africa's most populated country, Nigeria. Moreover, given their role to buffer local food systems against external shocks such as conflicts disrupting global commodity supply chains, climate change, and the forecasted population growth, unprecedent domestic production and value of production growth is forecasted for these crops. To deliver nutritious, affordable RTB foods, and supplies for processors in SSA, this two-year project initiation proposal represents the first phase towards establishing a longer-term plan for an 11-year-long, multi-donor driven portfolio of investments in the genetic improvement of RTB crops. Our overarching purpose is to contribute, through the development of market-preferred, gender-sensitive and climate-resilient varieties, to poverty alleviation, food and nutrition security and overall quality of life of smallholder farmers, processors, and consumers in rural and urban areas. This project will contribute to all the One CGIAR???s Genetic Innovation impact areas, namely: nutrition, health, and food security; poverty reduction, livelihoods, and jobs; gender equality, youth, and social inclusion; climate adaptation and mitigation; and environmental health and biodiversity. We aim to achieve this by implementing state-of-the-art, streamlined breeding approaches, and the market-preferred varieties to be developed are expected to command increased adoption rates and to quickly replace the older varieties and landraces that are currently in use. NC State partner with the One CGIAR to build upon capacities in African countries as well as those within One CGIAR that were developed through extensive prior BMGF breeding investments such as Breeding Better Bananas, GT4SP (NCSU led), NextGen Cassava, RTBFoods, SASHA (NCSU partner), SweetGAINS (NCSU partner), Africa Yam and Excellence in Breeding. Moreover, we will build upon assets, infrastructure and human talent posted at several One CGIAR centers and national and international programs in SSA countries, research, development and extension programs, and advanced research institutions.
In the last few years, we have developed a series of pipeline computational tools for analyzing genomic data in complex autopolyploid species: tools like VCF2SM and SuperMASSA for processing raw DNA sequences to call genetic dosage markers (marker identification); MAPpoly for constructing a genetic linkage map from the dosage markers (linkage map construction and haplotype inference); QTLpoly for locating genes that are important to trait phenotypes by using the linkage map (QTL mapping) and also for performance prediction. MAPpoly and QTLpoly are currently implemented for full-sib families and are being extended to multiple families. In this project we propose to further extend MAPpoly and QTLpoly for general multiple-generation pedigree breeding populations that are typical in practical polyploid breeding programs. Moreover, we propose to develop a new downstream computational tool, called DecisionPoly, that is user-friendly and offers clearly illustrated actionable information to assist breeders to make the short and long-term breeding decisions based on the collected and learned information about their breeding populations for different breeding objectives.
The implementation of genomics-assisted breeding techniques in polyploid specialty crops is significantly delayed compared to diploid species. The development of new tools, user friendly interfaces and training materials are needed by polyploid crop breeders to accelerate genetic gain for key traits of importance and meet the needs of growers and consumers. Polyploid specialty crops contribute significantly to food production in the US and throughout the world. The list of polyploid specialty crops used for food includes roots and tubers (potato, sweet potato), fruit (strawberry, blackberry, blueberry, European plum, tart cherry, kiwi, persimmon, banana), vegetables (leek, watermelon), and other uses (coffee, basil, hops). The annual value of these crops in the US is about $9.5 billion and many times greater on a global scale. The production and use of polyploid food crops contributes substantially to the nutritional welfare and employment of millions of people. In addition to food crops, polyploid species are used as ornamentals (rose, chrysanthemum, lily, orchids, lantana) and for turfgrass (ryegrass, bentgrass, Kentucky bluegrass, tall fescue, bermudagrass, zoysia). The turfgrass and ornamental production sectors produce about 1/3 the value of all specialty crop production and 15% of agricultural production in the USA. This $16.7 billion industry employs about two million people and delivers an economic impact of at least $136 billion. The turfgrass and ornamentals used in home, private and public landscapes significantly impact human health and urban ecology. These plants enhance air and water quality, sequester carbon, reduce runoff and erosion, provide energy savings in heating and cooling, facilitate rain capture and storm water management, reduce noise and dust pollution, and promote wildlife habitat. In addition, they increase property values and psychological wellbeing. The production of food crops and the production and maintenance of turfgrass and ornamentals requires substantial resources (agricultural chemicals, fertilizers, and water). Given the increased scarcity of water and concern over the environmental contamination of agrochemicals, it is essential to move towards more sustainable production and landscape systems. A major component of these future more sustainable systems will be new cultivars with improved yield, quality and environmental resilience. Objective 1. The software developed will meet the five needs identified during the planning grant: (a) multi-SNP haplotype discovery and population genotyping using next-generation sequencing; (b) linkage mapping with multi-allelic markers and genotype quality scores; (c) GWAS and genomic selection in mixed ploidy populations and with multi-allelic markers; (d) QTL mapping in interconnected F1 populations; (e) fine mapping, haplotype visualization, and efficient assembly of QTL alleles across multiple loci. Objective 2. Software will be developed so the user can explore different designs for genetic mapping projects or breeding programs. Simulation options will include the mating design, genome size, meiotic properties, population size, and costs for genotyping and phenotyping. Objective 3. Complete documentation of the syntax and options for each software will be created, as well as example datasets and corresponding workflows. These training materials will be publicly available through a Polyploid Community Resource web page that will be developed and hosted by Washington State University. Graphical user interfaces will be developed for the command-line software developed in Objectives 1 and 2 and made available through the website. Hands-on workshops will be created to showcase the new software and train the polyploid breeding community about polyploid genetics and the use of the analytical toolset. Objective 4. Research projects involving the new computational tools are planned for six polyploid crops representing a range of ploidy levels, preferential pairing propensity, interspecific diversity among breeding germplasm, and genomic data/r