ArticleGenetics2018
Discovery of Lineage-Specific Genome Change in Rice Through Analysis of Resequencing Data.
Article in Genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Review
- Next-Generation Breeding Strategies for Climate-Ready Crops.Frontiers in plant science · 2021Review
- Super-Pangenome by Integrating the Wild Side of a Species for Accelerated Crop Improvement.Trends in plant science · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome comparisons provide information on the nature of genetic change, but such comparisons are challenged to differentiate the importance of the actual sequence change processes relative to the role of selection. This problem can be overcome by identifying changes that have not yet had the time to undergo millions of years of natural selection. We describe a strategy to discover accession-specific changes in the rice genome using an abundant resource routinely provided for many genome analyses, resequencing data. The sequence of the fully sequenced rice genome from variety Nipponbare was compared to the pooled (∼114×) resequencing data from 126
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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.