Fused graphical lasso recovers flowering time mutation genes in arabidopsis thaliana
Open accessAbstract
Conventional breeding approaches that focus on yield under highly favorable nutrient conditions have resulted in reduced genetic and trait diversity in crops. Under the growing threat from climate change, the mining of novel genes in more resilient varieties can help dramatically improve trait improvement efforts. In this work, we propose the use of the joint graphical lasso for discovering genes responsible for desired phenotypic traits. We prove its efficiency by using gene expression data for wild type and delayed flowering mutants for the model plant. Arabidopsis thaliana shows that it recovers the mutation causing genes LNK1 and LNK2. Some novel interactions of these genes were also predicted. Observing the network level changes between two phenotypes can also help develop meaningful biological hypotheses regarding the novel functions of these genes. Now that this data analysis strategy has been validated in a model plant, it can be extended to crop plants to help identify the key genes for beneficial traits for crop improvement.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Drought-related genes from crop wild relatives can be incorporated into modern cultivars to improve drought resistance.
“These genes can be incorporated into modern cultivars to improve their drought resistance (Kapoor et al., 2021).”
From Emerging applications of gene editing technologies for the development of climate-resilient crops (2025) · cites this paper as Kapoor et al., 2021
The Introduction says genes from crop wild relatives should be identified and incorporated into new germplasm to develop climate-resilient varieties. It also mentions improved abiotic-stress tolerance, but does not specifically say that incorporating drought-related genes into modern cultivars improves drought resistance. (LLM, conf=0.84)
Experimental — accuracy not yet measuredGenomics-assisted breeding has enabled researchers to identify drought-related genes in crop wild relatives.
“Furthermore, advancements in genomics-assisted breeding have enabled researchers to identify drought-related genes in crop wild relatives.”
From Emerging applications of gene editing technologies for the development of climate-resilient crops (2025) · cites this paper as Kapoor et al., 2021
The Introduction says that identifying stress-adaptation genes in crop wild relatives is important and that genomics-assisted breeding has strong potential to help. It does not say researchers have already identified drought-related genes in those relatives through genomics-assisted breeding. No page number is available in our copy. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 75 · Cited by 5
- Authors
- Kapoor, R., Datta, A., & Thomson, M.
- Affiliations
- Texas A&M University (US)
- Corresponding author
- Kapoor, Rajan
- Venue
- Inventions
- Publisher
- MDPI AG
- Published
- 2021-07-20
- Volume
- 6
- Issue
- 3
- Pages
- 52
- ISSN
- 2411-5134 (ISSN-L)
- OpenAlex
- W3184781166
- Cited by
- 5
- References
- 75
- Citations by year
- 2025: 1 · 2024: 3 · 2023: 1
- FWCI
- 0.31
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Inventions (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- TEES-AgriLife Center for Bioinformatics and 257 Genomics System Engineering (CBGSE) startup funds, , the Texas A&M X-Grant Program, and in part by the National Science Foundation (ECCS-1609236)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- flowering time, Arabidopsis thaliana, gene expression networks, gene-gene interaction, crop improvement, climate resilience
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
