ArticleBMC genomics2014
Identification and characterization of transcript polymorphisms in soybean lines varying in oil composition and content.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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.
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
38 citing papers in PubMed.
- Genetic dissection of oil content in maize kernel using combined genome-wide association analysis and linkage mapping.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Single-Cell Omics in Legumes: Research Trends and Applications.Plants (Basel, Switzerland) · 2025Review
- Identification of candidate genes and genomic prediction of soybean fatty acid components in two soybean populations.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Development of a CRISPR/Cas9-mediated gene-editing method to isolate a mutant of the unicellular green alga Parachlorella kessleri strain NIES-2152 with improved lipid productivity.Biotechnology for biofuels and bioproducts · 2024Article
- Oil candidate genes in seeds of cotton (Gossypium hirsutum L.) and functional validation of GhPXN1.Biotechnology for biofuels and bioproducts · 2023Article
- Identification of an important QTL for seed oil content in soybean.Molecular breeding : new strategies in plant improvement · 2023Article
- Genetic architecture of protein and oil content in soybean seed and meal.The plant genome · 2023Article
- Reference Genes and Expression Analysis of Seed Desaturases Genes in Soybean Mutant Accessions.Biochemical genetics · 2022Article
- POWR1 is a domestication gene pleiotropically regulating seed quality and yield in soybean.Nature communications · 2022Article
- Development of a versatile resource for post-genomic research through consolidating and characterizing 1500 diverse wild and cultivated soybean genomes.BMC genomics · 2022Article
- Population structure and genetic diversity characterization of soybean for seed longevity.PloS one · 2022Article
- Article
- Transcriptomic Analysis Reveals Key Genes Involved in Oil and Linoleic Acid Biosynthesis duringInternational journal of molecular sciences · 2021Article
- Genetic loci and causal genes for seed fatty acids accumulation across multiple environments and genetic backgrounds in soybean.Molecular breeding : new strategies in plant improvement · 2021Article
- Quantitative proteomic analyses of two soybean low phytic acid mutants to identify the genes associated with seed field emergence.BMC plant biology · 2019Article
- Compositional Analysis of Non-Polar and Polar Metabolites in 14 Soybeans Using Spectroscopy and Chromatography Tools.Foods (Basel, Switzerland) · 2019Article
- Genomic changes and biochemical alterations of seed protein and oil content in a subset of fast neutron induced soybean mutants.BMC plant biology · 2019Article
- Comparative transcriptome analysis of cultivated and wild seeds of Salvia hispanica (chia).Scientific reports · 2019Article
- Comparative transcriptomic analysis of high- and low-oil3 Biotech · 2019Article
- Dynamic Transcriptome Changes Related to Oil Accumulation in Developing Soybean Seeds.International journal of molecular sciences · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVariation in seed oil composition and content among soybean varieties is largely attributed to differences in transcript sequences and/or transcript accumulation of oil production related genes in seeds. Discovery and analysis of sequence and expression variations in these genes will accelerate soybean oil quality improvement.
resultsIn an effort to identify these variations, we sequenced the transcriptomes of soybean seeds from nine lines varying in oil composition and/or total oil content. Our results showed that 69,338 distinct transcripts from 32,885 annotated genes were expressed in seeds. A total of 8,037 transcript expression polymorphisms and 50,485 transcript sequence polymorphisms (48,792 SNPs and 1,693 small Indels) were identified among the lines. Effects of the transcript polymorphisms on their encoded protein sequences and functions were predicted. The studies also provided independent evidence that the lack of FAD2-1A gene activity and a non-synonymous SNP in the coding sequence of FAB2C caused elevated oleic acid and stearic acid levels in soybean lines M23 and FAM94-41, respectively.
conclusionsAs a proof-of-concept, we developed an integrated RNA-seq and bioinformatics approach to identify and functionally annotate transcript polymorphisms, and demonstrated its high effectiveness for discovery of genetic and transcript variations that result in altered oil quality traits. The collection of transcript polymorphisms coupled with their predicted functional effects will be a valuable asset for further discovery of genes, gene variants, and functional markers to improve soybean oil quality.
Indexed as
Identifiers
What OpenQuestion holds
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.