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Long, Evan Robbins, Kelly Buckler, Edward Messer, Philipp 2023-03-31T16:38:02Z 2023-03-31T16:38:02Z 2022-12 ProQuest Submission ID: 13435 ProQuest Publication ID: 29999402 https://hdl.handle.net/1813/112949 https://doi.org/10.7298/t4e4-3f54 15644115 145 pages Cassava (Manihot esculenta) is a root crop that serves as an important caloric source for many tropical regions of the world. Cassava was domesticated 5k-10k years ago where it transitioned from being a perennial, outcrossing species to a crop grown as an annual or biannual and is propagated clonally through stem cuttings. Breeding efforts in cassava are hindered by high levels of inbreeding depression and limited sexual reproductive ability. Genetic load due to the accumulation of underlying deleterious mutations has been hypothesized as an underlying cause for these difficulties. In recent years genomic selection has been adopted as a strategy to accelerate genetic gain and quickly purge genetic load. Obtaining accurate and consistent genotype data across thousands of cassava clones is necessary to more effectively implement genomic selection strategies. Genomic selection uses genome-wide markers to predict plant performance to accelerate genetic gain, by reducing time and money to evaluate every cross. Genotype imputation, a method of obtaining genome-wide variants from limited sequence, has been hindered in cassava due to its high levels of heterozygosity. The first section of this project concerns the creation of a Practical Haplotype Graph (PHG) in cassava to improve genotype imputation in cassava, which in turn can enable more effective genomic selection strategies. Centuries of limited sexual recombination, selection cannot effectively purge recessive deleterious mutations, which may be responsible for observed genetic load in cassava. This work aims to understand these deleterious mutations and evaluate the prospect of incorporating them into improvement of cassava. With accurate genotypes and knowledge of deleterious impact of specific mutations, breeders and researchers will be able to more effectively improve genetic gain in cassava. Millions of years of selection and evolution can reveal what regions of a genome are functionally important and what mutations may be deleterious. I sequenced and assembled 27 plant species that, like cassava, belong to the Euphorbiaceae family. Using comparative genomics with these and other publicly available genome data, I analyzed evolutionary conservation across 53 species. By looking at selection signatures in cassava through evolutionary conservation, I discovered genes responsible for effective sexual reproduction to have an abundance of functional mutation in cassava suggesting a relaxation of selection compared to the rest of the Euphorbiaceae family. Derived alleles at conserved regions of the genome were then used to identify putative deleterious mutation contributing to genetic load. These mutations were found to be negatively correlated with fitness related traits in cassava and were additionally validated through incorporation in genomic prediction scenarios. This dissertation summarizes the efforts made to uncover the source and effects of genetic load in cassava by leveraging millions of years of evolutionary signal. en Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/ Cassava Deleterious Mutations Euphorbiaceae Evolutionary Conservation Genomic Selection Imputation LEVERAGING EVOLUTION TO UNDERSTAND GENETIC LOAD IN CASSAVA (MANIHOT ESCULENTA) dissertation or thesis https://newcatalog.library.cornell.edu/catalog/15644115 application/pdf Plant Breeding Cornell University Doctor of Philosophy Ph. D., Plant Breeding https://hdl.handle.net/1813/59810.2 Publication Cornell Theses and Dissertations Long, Evan 5893a6ea-7af3-41d7-abc6-04bcd26ab5df open.access open.access <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="0d5b648e-2c48-401d-a6d1-a2bec8b00320"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>en</Language> <Title>LEVERAGING EVOLUTION TO UNDERSTAND GENETIC LOAD IN CASSAVA (MANIHOT ESCULENTA)</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2022-12</PublicationDate> <DOI>https://doi.org/10.7298/t4e4-3f54</DOI> <Authors> <Author> <DisplayName>Long, Evan</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <OrgUnit /> </Publisher> </Publishers> <License>https://creativecommons.org/licenses/by/4.0/</License> <Keyword>Cassava</Keyword> <Keyword>Deleterious Mutations</Keyword> <Keyword>Euphorbiaceae</Keyword> <Keyword>Evolutionary Conservation</Keyword> <Keyword>Genomic Selection</Keyword> <Keyword>Imputation</Keyword> <Abstract>Cassava (Manihot esculenta) is a root crop that serves as an important caloric source for many tropical regions of the world. Cassava was domesticated 5k-10k years ago where it transitioned from being a perennial, outcrossing species to a crop grown as an annual or biannual and is propagated clonally through stem cuttings. Breeding efforts in cassava are hindered by high levels of inbreeding depression and limited sexual reproductive ability. Genetic load due to the accumulation of underlying deleterious mutations has been hypothesized as an underlying cause for these difficulties. In recent years genomic selection has been adopted as a strategy to accelerate genetic gain and quickly purge genetic load. Obtaining accurate and consistent genotype data across thousands of cassava clones is necessary to more effectively implement genomic selection strategies. Genomic selection uses genome-wide markers to predict plant performance to accelerate genetic gain, by reducing time and money to evaluate every cross. Genotype imputation, a method of obtaining genome-wide variants from limited sequence, has been hindered in cassava due to its high levels of heterozygosity. The first section of this project concerns the creation of a Practical Haplotype Graph (PHG) in cassava to improve genotype imputation in cassava, which in turn can enable more effective genomic selection strategies. Centuries of limited sexual recombination, selection cannot effectively purge recessive deleterious mutations, which may be responsible for observed genetic load in cassava. This work aims to understand these deleterious mutations and evaluate the prospect of incorporating them into improvement of cassava. With accurate genotypes and knowledge of deleterious impact of specific mutations, breeders and researchers will be able to more effectively improve genetic gain in cassava. Millions of years of selection and evolution can reveal what regions of a genome are functionally important and what mutations may be deleterious. I sequenced and assembled 27 plant species that, like cassava, belong to the Euphorbiaceae family. Using comparative genomics with these and other publicly available genome data, I analyzed evolutionary conservation across 53 species. By looking at selection signatures in cassava through evolutionary conservation, I discovered genes responsible for effective sexual reproduction to have an abundance of functional mutation in cassava suggesting a relaxation of selection compared to the rest of the Euphorbiaceae family. Derived alleles at conserved regions of the genome were then used to identify putative deleterious mutation contributing to genetic load. These mutations were found to be negatively correlated with fitness related traits in cassava and were additionally validated through incorporation in genomic prediction scenarios. This dissertation summarizes the efforts made to uncover the source and effects of genetic load in cassava by leveraging millions of years of evolutionary signal.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>