Evidence map›Paper›PMID 24532030›Full record

ArticleMolecular genetics and genomics : MGG2014

Lz-0 × Berkeley: a new Arabidopsis recombinant inbred line population for the mapping of complex traits.

Arnaud Capron, Xue Feng Chang, Chun Shi, Rodger Beatson, Thomas Berleth

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular genetics and genomics : MGG, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Arnaud CapronUniversity of Toronto-CSB, 25 Willcocks St., Toronto, ON, M5S 3B2, Canada.
Xue Feng Chang
Chun Shi
Rodger Beatson
Thomas Berleth

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study describes the generation and test of a genetic resource suited to identify determinants of cell biological traits in plants. The use of quantitative trait loci (QTL) mapping for a better genetic understanding of cell biological traits is still at an early stage, even for biotechnologically important cell properties, such as the dimensions of fiber cells. A common strategy, the mapping of QTLs in recombinant inbred line (RIL) populations, is limited by the fact that the existing RIL populations exploit only a small fraction of the existing natural variation. Here, we report the mapping of QTLs impacting on the length of fiber cells in Arabidopsis inflorescence stems in a newly generated RIL population derived from a cross between the accessions Berkeley and the little known Lz-0. Through inbreeding of individual F(2) plants, a total of 159 new F8 lines were produced and genotyped with a set of 49 single nucleotide polymorphism markers. The population was successfully used not only for the mapping of three QTLs controlling fiber length, but also to map five QTL controlling flowering time under short and long-day conditions. Our study demonstrates the usefulness of this new genetic resource by mapping in it QTLs underlying a poorly explored cellular trait as well as an already better explored regulatory pathway. The new RIL population and an online platform for the continuous supplementation of genetic markers will be generally available to substantially broaden the genetic diversity through which loci with impact on plant quantitative traits can be identified.

Indexed as

Chromosome MappingQuantitative Trait, HeritableQuantitative Trait LociArabidopsisFlowersGenotypeHybridization, GeneticInbreedingLod ScorePhenotype

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.