ArticleFrontiers in plant science2011
Next generation quantitative genetics in plants.
Article in Frontiers in plant science, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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.
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Who cites it
5 citing papers in PubMed.
- Core set construction and association analysis of Pinus massoniana from Guangdong province in southern China using SLAF-seq.Scientific reports · 2019Article
- Construction of a High-Density Genetic Map from RNA-Seq Data for an Arabidopsis Bay-0 × Shahdara RIL Population.Frontiers in genetics · 2017Article
- Using next-generation sequencing to isolate mutant genes from forward genetic screens.Nature reviews. Genetics · 2014Review
- Grand Challenges in Plant Systems Biology: Closing the Circle(s).Frontiers in plant science · 2012Article
- Editorial overview - computational approaches in aid of advancing understanding in plant physiology.Frontiers in plant science · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Most characteristics in living organisms show continuous variation, which suggests that they are controlled by multiple genes. Quantitative trait loci (QTL) analysis can identify the genes underlying continuous traits by establishing associations between genetic markers and observed phenotypic variation in a segregating population. The new high-throughput sequencing (HTS) technologies greatly facilitate QTL analysis by providing genetic markers at genome-wide resolution in any species without previous knowledge of its genome. In addition HTS serves to quantify molecular phenotypes, which aids to identify the loci responsible for QTLs and to understand the mechanisms underlying diversity. The constant improvements in price, experimental protocols, computational pipelines, and statistical frameworks are making feasible the use of HTS for any research group interested in quantitative genetics. In this review I discuss the application of HTS for molecular marker discovery, population genotyping, and expression profiling in QTL analysis.
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Registered trials
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.