ArticleBMC genomics2026
Genome-wide association analysis to identify candidate genes for growth rate traits in Chinese endemic geese.
Article in BMC genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChina has abundant resources of local goose breeds with significant differences in growth rates among breeds. These differences provide natural genetic materials for exploring key functional genes and molecular markers of growth traits. The genetic loci related to growth rate are important economic traits that affect slaughter weight and feeding costs. In view of this, we used genome-wide association analysis (GWAS) method to determine the genes related to growth rate.
resultsFrom hatching to 10 weeks of age, the weight data of 255 China local geese were measured every 2 weeks. Based on the growth curve, we evaluated the relative and absolute growth rates (RGR and AGR) during the early rapid growth stages of 0–2, 2–4, 4–6, 6–8, and 8–10 weeks of age. GWAS analysis of AGR identified 32 SNPs and annotated 17 associated genes, including STX11, PNDC1, MRPL18, and others. There are 38 SNPs related to RGR, and 19 important candidate genes have been annotated, including SLC24A4, CPSF2, MAP2, and other genes. Five genes are shared in AGR and RGR, namely FAM210B, GULP1, MAS1, MRPL18, and PNLDC1. In addition, through further enrichment analysis, pathways related to growth and development were identified, and candidate genes such as GULP1, STX11, METAP2 were further screened.
conclusionThis study identified 70 SNPs associated with growth rate and annotated 36 genes. Further analysis suggests that GULP1, STX11, METAP2, PTH1R, SMAD7, GK, CTBP2, and DEF6 are important candidate genes. These findings offer valuable data resources for the molecular breeding of indigenous Chinese geese and provide a robust theoretical framework to inform future breeding programs aimed at developing fast-growing Chinese goose breeds.
Indexed as
Identifiers
What Socratic 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 Socratic graph.