Article in Molecular biology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
0numbers the graph read from it
0cells of the map it votes in
5citing 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.
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
12 authors.
Ming HuKey Laboratory of Biology and Genetic Improvement of Horticultural Crops (South China), Ministry of Agriculture and Rural Affairs, College of Horticulture, South China Agricultural University, Guangdong 510642, China.ORCID 0009-0001-8791-3085
Penglong WanKey Laboratory of Biology and Genetic Improvement of Horticultural Crops (South China), Ministry of Agriculture and Rural Affairs, College of Horticulture, South China Agricultural University, Guangdong 510642, China.ORCID 0009-0003-6749-4367
Chengjie ChenTropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, State Key Laboratory of Tropical Crop Breeding, Laboratory of Crop Gene Resources and Germplasm Enhancement in South China, Ministry of Agriculture and Rural Affairs, Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation of Hainan Province, Hainan 571101, China.ORCID 0000-0001-5964-604X
Shuyuan TangKey Laboratory of Biology and Genetic Improvement of Horticultural Crops (South China), Ministry of Agriculture and Rural Affairs, College of Horticulture, South China Agricultural University, Guangdong 510642, China.ORCID 0009-0004-7383-2219
Jiahao ChenKey Laboratory of Biology and Genetic Improvement of Horticultural Crops (South China), Ministry of Agriculture and Rural Affairs, College of Horticulture, South China Agricultural University, Guangdong 510642, China.ORCID 0009-0007-5600-4886
Liang WangKey Laboratory of Biology and Genetic Improvement of Horticultural Crops (South China), Ministry of Agriculture and Rural Affairs, College of Horticulture, South China Agricultural University, Guangdong 510642, China.ORCID 0009-0007-2614-0457
Mahul ChakrabortyDepartment of Biology, Texas A&M University, College Station, TX 77843, USA.ORCID 0000-0003-2414-9187
Yongfeng ZhouTropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, State Key Laboratory of Tropical Crop Breeding, Laboratory of Crop Gene Resources and Germplasm Enhancement in South China, Ministry of Agriculture and Rural Affairs, Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation of Hainan Province, Hainan 571101, China.ORCID 0000-0003-0780-2973
Jinfeng ChenState Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China.ORCID 0000-0002-5628-6322
Brandon S GautDepartment of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697, USA.ORCID 0000-0002-1334-5556
J J EmersonDepartment of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697, USA.ORCID 0000-0001-9474-0891
Yi LiaoKey Laboratory of Biology and Genetic Improvement of Horticultural Crops (South China), Ministry of Agriculture and Rural Affairs, College of Horticulture, South China Agricultural University, Guangdong 510642, China.ORCID 0000-0002-7724-1799
Funding
Structural variation population size and the evolution of genome complexityR01GM123303 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI EMERSON, JAMES JORDAN · 2017 to 2021
$1.5M
The origin, maintenance, and adaptive consequences of variation in genome structureR35GM153327 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI James Jordan Emerson · 2024 to 2026
$1.1M
Evolutionary and functional consequences of structural genetic variation in DrosophilaR00GM129411 · NIGMS · TEXAS A&M UNIVERSITY · PI CHAKRABORTY, MAHUL · 2023 to 2025
$735k
Central Public-interest Scientific Institution Basal Research Fund for the Chinese Academy of Tropical Agricultural Sciences 1630032024026GuangDong Basic and Applied Basic Research Foundation 2024A1515010362Invigorate the Seed Industry of Guangdong Province 2023-NJS-00-012National Science Foundation IOS-2414478National Science Foundation of China 32102320National Science Foundation of China 32470607NIGMS NIH HHS R00 GM129411NIGMS NIH HHS R01 GM123303NIGMS NIH HHS R35 GM153327NIH HHS R00GM129411NIH HHS R01GM123303NIH HHS R35GM153327South China Agricultural UniversityTexas A&M University
6 · The paper itself
Abstract
Comparisons of complete genome assemblies offer a direct procedure for characterizing all genetic differences among them. However, existing tools are often limited to specific aligners or optimized for specific organisms, narrowing their applicability, particularly for large and repetitive plant genomes. Here, we introduce Structural Variants Genotyping of Assemblies on Population scales (SVGAP), a pipeline for structural variant (SV) discovery, genotyping, and annotation from high-quality genome assemblies at the population level. Through extensive benchmarks using simulated SV datasets at individual, population, and phylogenetic contexts, we demonstrate that SVGAP performs favorably relative to existing tools in SV discovery. Additionally, SVGAP is one of the few tools to address the challenge of genotyping SVs within large assembled genome samples, and it generates fully genotyped VCF files. Applying SVGAP to 26 maize genomes revealed hidden genomic diversity in centromeres, driven by abundant insertions of centromere-specific LTR-retrotransposons. The output of SVGAP is well-suited for pangenome construction and facilitates the interpretation of previously unexplored genomic regions.
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 Socratic graph.
Accurate, Scalable Structural Variant Genotyping in Complex Genomes at Population Scales. · full record | Socratic