Background Since the domestication of chicken, various breeds have been developed for food production, entertainment, and so on. Compared to indigenous chicken breeds which generally do not show elite production performance, commercial breeds or lines are selected intensely for meat or egg production. In the present study, in order to understand the molecular mechanisms underlying the dramatic differences of egg number between commercial egg-type chickens and indigenous chickens, we performed a genome-wide association study (GWAS) in a mixed linear model. Results We obtained 148 single nucleotide polymorphisms (SNPs) associated with egg number traits (57 significantly, 91 suggestively). Among them, 4 SNPs overlapped with previously reported quantitative trait loci (QTL), including 2 for egg production and 2 for reproductive traits. Furthermore, we identified 32 candidate genes based on the function of the screened genes. These genes were found to be mainly involved in regulating hormones, playing a role in the formation, growth, and development of follicles, and in the development of the reproductive system. Some genes such as NELL2 (neural EGFL like 2), KITLG (KIT ligand), GHRHR (Growth hormone releasing hormone receptor), NCOA1 (Nuclear receptor coactivator 1), ITPR1 (inositol 1, 4, 5-trisphosphate receptor type 1), GAMT (guanidinoacetate N-methyltransferase), and CAMK4 (calcium/calmodulin-dependent protein kinase IV) deserve our attention and further study since they have been reported to be closely related to egg production, egg number and reproductive traits. In addition, the most significant genomic region obtained in this study was located at 48.61–48.84 Mb on GGA5. In this region, we have repeatedly identified four genes, in which YY1 (YY1 transcription factor) and WDR25 (WD repeat domain 25) have been shown to be related to oocytes and reproductive tissues, respectively, which implies that this region may be a candidate region underlying egg number traits. Conclusion Our study utilized the genomic information from various chicken breeds or populations differed in the average annual egg number to understand the molecular genetic mechanisms involved in egg number traits. We identified a series of SNPs, candidate genes, or genomic regions that associated with egg number, which could help us in developing the egg production trait in chickens.

No abstract

No abstract

Corydalis yanhusuo is a medicinal plant frequently used in traditional Chinese medicine, which has effective medical effects in many aspects. Real-time polymerase chain reaction (RT-PCR) has been one of the most widely used methods in biosynthesis research due to its high sensitivity and quantitative properties in gene expression analysis. To obtain accurate normalization, reference genes are often selected in advance; however, no reference genes are available in C. yanhusuo. Herein, 12 reference gene candidates, named cyclophilin 2 (CYP2), elongation factor 1-α (EF1-α), protein phosphatase 2 (PP2A), SAND protein family (SAND), polypyrimidine tract-binding protein (PTBP), TIP41-like protein (TIP41), lyceraldehyde-3-phosphate hydrogenase (GAPDH), ubiquitin-conjugating enzyme 9 (UBC9), cyclophilin 1 (CYP1), tubulin beta (TUBA), thioredoxin (YLS8), and polyubiquitin 10 (UBQ10), were selected for stability analysis. After being treated with hormone, UV, salt, metal, oxidative, drought, cold (4 °C), and hot stresses (40 °C), the qRT-PCR data of the selected genes was analyzed with NormFinder, geNorm, and BestKeeper. The result indicated that GAPDH, SNAD, and PP2A were the top three most stable reference genes under most treatments. This study selected and validated reliable reference genes in C. yanhusuo under various environmental conditions, which can provide great help for future research on gene expression normalization in C. yanhusuo.

Structural variants (SVs) are one of the main sources of genetic variants and have a greater impact on phenotype evolution, disease susceptibility, and environmental adaptations than single nucleotide polymorphisms (SNPs). However, SVs remain challenging to accurately type, with several detection methods showing different limitations. Here, we explored SVs from 10 different chickens using PacBio technology and detected 49,501 high-confidence SVs. The results showed that the PacBio long-read detected more SVs than Illumina short-read technology genomes owing to some SV sites on chromosomes, which are related to chicken growth and development. During chicken domestication, some SVs beneficial to the breed or without any effect on the genomic function of the breed were retained, whereas deleterious SVs were generally eliminated. This study could facilitate the analysis of the genetic characteristics of different chickens and provide a better understanding of their phenotypic characteristics at the SV level, based on the long-read sequencing method. This study enriches our knowledge of SVs in chickens and improves our understanding of chicken genomic diversity.