Successful Growth of RIL Arabidopsis thalianaOffspring Based on Traits Shared with Parent Plants

Loading...
Thumbnail Image

Date

2020-04

Journal Title

Journal ISSN

Volume Title

Publisher

Montana State University Billings

Abstract

This study was primarily focused on phenotypic observation of Arabidopsis thaliana offspring from the parent cross of varieties Columbia (CS933) and Landsberg (CS20). Arabidopsis was an ideal organism to use in this study due to its array of distinctive heritable traits and its relatively short life cycle. The offspring used in this study were recombinant inbred lines (RILs), which have been allowed to self-pollinate over a series of generations in order to fix their homozygosity. The RIL offspring of the two Arabidopsis thaliana parent varieties should exhibit a combination of observable traits from both parents. Given that Columbia grows in a warmer region, at a temperature closer to the conditions found in the growth room, it was hypothesized that these parent plants would grow more successfully than the Landsberg parent plants. By this same logic, it was hypothesized that offspring which share more traits with the Columbia parent would be more successful than those offspring which share many traits with Landsberg. The traits that were measured to determine growth success include silique number per plant and number of branch points off the main inflorescence (to determine fecundity), as well as the inflorescence height at the end of the growth period. Ultimately the CS20 parents were found to be less successful at surviving under the given conditions, as they showed the lowest averages in all the categories measured. The majority of the offspring shared two of the most distinctive phenotypic traits with CS933, floppy inflorescence and pointy siliques, while only one offspring line shared the blunt siliques and erect inflorescence found in CS20. Additionally, the most successful offspring lines tended to also be those plants with the largest rosette diameters, which was confirmed to be predictive of success by a linear regression analysis.

Description

Keywords

Citation

Copyright (c) 2002-2022, LYRASIS. All rights reserved.