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High-Throughput Computer Vision Introduces the Time Axis to a Quantitative Trait Map of a Plant Growth Response
Automated image acquisition, a custom analysis algorithm, and a distributed computing resource were used to add time as a third dimension to a quantitative trait locus (QTL) map for plant root gravitropism, a model growth response to an environmental cue. Digital images of Arabidopsis thaliana seedl...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Genetics Society of America
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3813838/ https://www.ncbi.nlm.nih.gov/pubmed/23979570 http://dx.doi.org/10.1534/genetics.113.153346 |
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author | Moore, Candace R. Johnson, Logan S. Kwak, Il-Youp Livny, Miron Broman, Karl W. Spalding, Edgar P. |
author_facet | Moore, Candace R. Johnson, Logan S. Kwak, Il-Youp Livny, Miron Broman, Karl W. Spalding, Edgar P. |
author_sort | Moore, Candace R. |
collection | PubMed |
description | Automated image acquisition, a custom analysis algorithm, and a distributed computing resource were used to add time as a third dimension to a quantitative trait locus (QTL) map for plant root gravitropism, a model growth response to an environmental cue. Digital images of Arabidopsis thaliana seedling roots from two independently reared sets of 162 recombinant inbred lines (RILs) and one set of 92 near isogenic lines (NILs) derived from a Cape Verde Islands (Cvi) × Landsberg erecta (Ler) cross were collected automatically every 2 min for 8 hr following induction of gravitropism by 90° reorientation of the sample. High-throughput computing (HTC) was used to measure root tip angle in each of the 1.1 million images acquired and perform statistical regression of tip angle against the genotype at each of the 234 RIL or 102 NIL DNA markers independently at each time point using a standard stepwise procedure. Time-dependent QTL were detected on chromosomes 1, 3, and 4 by this mapping method and by an approach developed to treat the phenotype time course as a function-valued trait. The QTL on chromosome 4 was earliest, appearing at 0.5 hr and remaining significant for 5 hr, while the QTL on chromosome 1 appeared at 3 hr and thereafter remained significant. The Cvi allele generally had a negative effect of 2.6–4.0%. Heritability due to the QTL approached 25%. This study shows how computer vision and statistical genetic analysis by HTC can characterize the developmental timing of genetic architectures. |
format | Online Article Text |
id | pubmed-3813838 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Genetics Society of America |
record_format | MEDLINE/PubMed |
spelling | pubmed-38138382013-11-01 High-Throughput Computer Vision Introduces the Time Axis to a Quantitative Trait Map of a Plant Growth Response Moore, Candace R. Johnson, Logan S. Kwak, Il-Youp Livny, Miron Broman, Karl W. Spalding, Edgar P. Genetics Investigations Automated image acquisition, a custom analysis algorithm, and a distributed computing resource were used to add time as a third dimension to a quantitative trait locus (QTL) map for plant root gravitropism, a model growth response to an environmental cue. Digital images of Arabidopsis thaliana seedling roots from two independently reared sets of 162 recombinant inbred lines (RILs) and one set of 92 near isogenic lines (NILs) derived from a Cape Verde Islands (Cvi) × Landsberg erecta (Ler) cross were collected automatically every 2 min for 8 hr following induction of gravitropism by 90° reorientation of the sample. High-throughput computing (HTC) was used to measure root tip angle in each of the 1.1 million images acquired and perform statistical regression of tip angle against the genotype at each of the 234 RIL or 102 NIL DNA markers independently at each time point using a standard stepwise procedure. Time-dependent QTL were detected on chromosomes 1, 3, and 4 by this mapping method and by an approach developed to treat the phenotype time course as a function-valued trait. The QTL on chromosome 4 was earliest, appearing at 0.5 hr and remaining significant for 5 hr, while the QTL on chromosome 1 appeared at 3 hr and thereafter remained significant. The Cvi allele generally had a negative effect of 2.6–4.0%. Heritability due to the QTL approached 25%. This study shows how computer vision and statistical genetic analysis by HTC can characterize the developmental timing of genetic architectures. Genetics Society of America 2013-11 /pmc/articles/PMC3813838/ /pubmed/23979570 http://dx.doi.org/10.1534/genetics.113.153346 Text en Copyright © 2013 by the Genetics Society of America Available freely online through the author-supported open access option. |
spellingShingle | Investigations Moore, Candace R. Johnson, Logan S. Kwak, Il-Youp Livny, Miron Broman, Karl W. Spalding, Edgar P. High-Throughput Computer Vision Introduces the Time Axis to a Quantitative Trait Map of a Plant Growth Response |
title | High-Throughput Computer Vision Introduces the Time Axis to a Quantitative Trait Map of a Plant Growth Response |
title_full | High-Throughput Computer Vision Introduces the Time Axis to a Quantitative Trait Map of a Plant Growth Response |
title_fullStr | High-Throughput Computer Vision Introduces the Time Axis to a Quantitative Trait Map of a Plant Growth Response |
title_full_unstemmed | High-Throughput Computer Vision Introduces the Time Axis to a Quantitative Trait Map of a Plant Growth Response |
title_short | High-Throughput Computer Vision Introduces the Time Axis to a Quantitative Trait Map of a Plant Growth Response |
title_sort | high-throughput computer vision introduces the time axis to a quantitative trait map of a plant growth response |
topic | Investigations |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3813838/ https://www.ncbi.nlm.nih.gov/pubmed/23979570 http://dx.doi.org/10.1534/genetics.113.153346 |
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