Sequencing

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11th Annual <strong>Sequencing</strong>, Finishing, and Analysis in the Future Meeting A GENOME IN THE SUGAR BEET FIELD Friday, 3rd June 12:00 La Fonda Ballroom Talk (OS‐8.02) Mitch McGrath 1 , Belinda Townsend 2 , Karen Davenport 3 , Hajnalka Daligault 3 , Shannon Johnson 3 , Alex Hastie 4 , Sven Bockland 4 , Aude Darracq 5 , Glenda Willems 5 , Steve Barnes 5 , Paul Galewski 6 , Andy Funk 6 , Jane Pulman 6 , Tiffany Liu 6 , Kevin Childs 6 , Robert Bogden 7 , Jon Wittendorp 7 1 USDA‐ARS & Michigan State University, 2 Rothamsted Research, 3 Los Alamos National Laboratory, 4 BioNano Genomics, 5 SES Vanderhave, 6 Michigan State University, 7 Amplicon Express Beets (Beta vulgaris) have been, and are, widely consumed food and fodder crops over the past three millennia, most recently for their luxurious production of the sweetener sucrose, and perhaps transitioning to a burgeoning energy and industrial crop that would hearken to its days fueling draft animals during pre‐industrial times. As a member of the Carophyllales, a group of plant taxa known for their habitation in stressful and unusual environments, their unusual chemo‐systematics, and as a sister eudicot lineage to the asterid and rosid clades, beets occupy a niche in crop production in cooler, northern temperate climates with remarkable ability to produce biomass and accumulate solutes on an annual cycle. The capacity of beets to meet growing needs is prodigious. Promises of productivity depend on the ability to engineer products, for which a schematic would be useful. Such a resource is available through the genome, which in this case, was assembled during 2015 from raw reads to contigs (PacBio, Illumina) to scaffolds (BioNano, Dovetail), resulting in 86 superscaffolds in 566 Mb with 6% N’s and collapsing to 9 pseudo‐molecules plus 5 super‐scaffolds (4.5 Mb) unassigned. Plant breeding only has two goals: Improvement in quality traits and protection of existing traits. This schematic is being explored for features of trait construction (accumulation of small molecules such as betalain pigments and sucrose), development, and genetic indicators of crop diversity (leafy chards vs roots of vegetable and industrial beets) as well as disease resistance traits (rhizomania “crazy root” disease, resistance gene analogs). Such a resource, tied to a host of inbred genetic populations which themselves are a novel and unique resource for discovering genes through traditional and new comparative approaches, now gives the ability to dissect the genetic architecture of beets, and the phenology of agronomic trait development in general, in a species where traditional genetic analyses have not been possible due to the out‐crossing nature of its breeding system. Assembly of a high quality genome was relatively affordable from a deeply inbred individual. With a defined genetic architecture, variants detected at the population level, the level for which beet breeding has been most successful, are being identified with specific traits to gain insight into the biochemical and physiological processes contributing. Paired with gene expression changes across developmental transitions, specific genes responsible for bulk life‐stage properties may be uncovered. Such phyto‐centric information has never been available for beets, and plants in general, and strategies to exploit this information will likely still remain in the realm of particular crop idiosyncrasies. And beets do have many idiosyncrasies, which ideally, will be better interpreted and manipulated through close inspection of the beet genome. 139
11th Annual <strong>Sequencing</strong>, Finishing, and Analysis in the Future Meeting TRAIT MAPPING AND IMPROVEMENT OF THE MELON FLY (BACTROCERA CUCURBITAE) GENOME Friday, 3rd June 12:20 La Fonda Ballroom Talk (OS‐8.03) Sheina Sim 1 , Scott Geib 2 1 University of Hawaii, Manoa, 2 USDA‐ARS DKI US PBARC The melon fruit fly Bactrocera cucurbitae (Coquillett), is a destructive agricultural pest and is the subject of strict quarantines that are enforced to prevent its establishment outside of its current geographic range. In addition to quarantine efforts, additional control measures are necessary for its eradication in the case of invasion to agriculturally rich areas. The sterile insect technique (SIT) has been effective in the control of medfly (Ceratitis capitata), and is part of a management strategy that regulatory agencies intend to expand to B. cucurbitae and other important pests. A requirement of SIT is the availability of a genetic sexing strain (GSS) which enables the automation of sorting males from females so that only sterile males are released. In medfly, genetic sexing is based on pupal color (females have white pupae, males have wild‐type brown pupae) and temperature sensitivity (females die at elevated temperatures, males can survive at elevated temperatures). Similarly, there exists a GSS for B. cucurbitae in which pupal color is also sexually dimorphic where females have a white pupal case and males have a wild‐type brown pupal case, but its genetic basis is largely unknown. Genetic sexing by temperature sensitive lethal does not currently exist in Bactrocera. To facilitate the use of the B. cucurbitae GSS for SIT release, it is necessary to develop foundational tools for its biological, genetic, and genomic characterization to determine if the white pupae genes in B. cucurbitae and C. capitata are orthologs, and if it is possible to induce the tsl mutation in this species. The first step in this is to identify the genetic basis of wp in B. cucurbitae. In this study, the whole B. cucurbitae genome was sequenced and assembled. Five mapping populations for this species were then sequenced and genotyped using a double digest restriction associated digest sequencing library. From this, a consensus linkage map for B. cucurbitae was generated and used to super‐scaffold 69% of the draft assembly which includes 75% of annotated genes. White pupae was mapped to a few tightly linked loci found on one 8kb scaffold using QTL analysis. The locus with the highest LOD score was validated, showing consistency between genotype and phenotype. This data allows for the comparison of wp in melon fly with wp in medfly and the identification of the specific mutation causing wp. 140
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Sequencing

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