To date, research on poultry egg production performance has only been conducted within inter or intra-breed groups, while those combining both inter- and intra-breed groups are lacking. Egg production performance is known to differ markedly between Sichuan white goose (Anser cygnoides) and Landes goose (Anser anser). In order to understand the mechanism of egg production performance in geese, we undertook this study. Here, 18 ovarian stromal samples from both Sichuan white goose and Landes goose at the age of 145 days (3 individuals before egg production initiation for each breed) and 730 days (3 high- and low egg production individuals during non-laying periods for each breed) were collected to reveal the genome-wide expression profiles of ovarian mRNAs and lncRNAs between these two geese breeds at different physiological stages. Briefly, 58, 347, 797, 777, and 881 differentially expressed genes (DEGs) and 56, 24, 154, 105, and 224 differentially expressed long non-coding RNAs (DElncRNAs) were found in LLD vs. HLD (low egg production Landes goose vs. high egg production Landes goose), LSC vs. HSC (low egg production Sichuan White goose vs. high egg production Sichuan white goose), YLD vs. YSC (young Landes goose vs. young Sichuan white goose), HLD vs. HSC (high egg production Landes goose vs. high egg production Sichuan white goose), and LLD vs. LSC (low egg production Landes goose vs. low egg production Sichuan white goose) groups, respectively. Functional enrichment analysis of these DEGs and DElncRNAs suggest that the “neuroactive ligand–receptor interaction pathway” is crucial for egg production, and particularly, members of the 5-hydroxytryptamine receptor (HTR) family affect egg production by regulating ovarian metabolic function. Furthermore, the big differences in the secondary structures among HTR1F and HTR1B, HTR2B, and HTR7 may lead to their different expression patterns in goose ovaries of both inter- and intra-breed groups. These results provide novel insights into the mechanisms regulating poultry egg production performance.

Single-cell sequencing technologies have led to a revolution in our knowledge of the diversity of cell types, connections between biological levels of organization, and relationships between genotype and phenotype. These advances have mainly come from using model organisms; however, using single-cell sequencing in non-model organisms could enable investigations of questions inaccessible with typical model organisms. This primer describes a general workflow for single-cell sequencing studies and considerations for using non-model organisms (limited to multicellular animals). Importantly, single-cell sequencing, when further applied in non-model organisms, will allow for a deeper understanding of the mechanisms between genotype and phenotype and the basis for biological variation.

Dysregulation of adipogenesis causes metabolic diseases, like obesity and fatty liver. Migratory birds such as geese have a high tolerance of massive energy intake and exhibit little pathological development. Domesticated goose breeds, derivatives of the wild greyleg goose (Anser anser) or swan goose (Anser cygnoides), have high tolerance of energy intake resembling their ancestor species. Thus, goose is potentially a model species to study mechanisms associated with adipogenesis. Phenotypically, goose liver exhibited higher fat accumulation than adipose tissues during fattening (liver increased by 3.35 fold than 1.65 fold in adipose), showing a priority of fat accumulation in liver. We found the number of differentially expressed genes in liver (13.97%) was nearly twice the number of that in adipose (6.60%). These differentially expressed genes in liver function in several important lipid metabolism pathways, immune response, regulation of cancer, while in adipose, terms closely related to protein binding, gluconeogenesis were enriched. Typically, genes like MDH2 and SCD, which have key roles in glycolysis and fatty acids metabolism, had higher fold change in liver than in adipose tissues. Three hundred two differentially expressed long noncoding RNAs involved in regulation of metabolism in liver were also identified. For example, lncRNA XLOC_292762, which was 5.7 kb downstream of FERMT2, a gene involved phosphatidylinositol-3,4,5-trisphosphate binding, was significantly down-regulated after the high-intake feeding period. Further investigation of documented obesity-related orthologous genes in goose suggested that understanding the evolutionary split from mammals in adipogenesis will make goose fatty liver a better resource for future research. Our research reveals that goose uses liver as the major tissue to regulate a distinct lipid synthesis and degradation flux and the dynamic expression network analyses showed numerous layers of positive responses to both massive energy intake and possible pathological development. Our results offer insights into goose adipogenesis and provide a new perspective for research in human metabolic dysregulation.

Extrachromosomal DNAs (ecDNAs) are a pervasive feature found in cancer and contain oncogenes and their corresponding regulatory elements. Their unique structural properties allow a rapid amplification of oncogenes and alter chromatin accessibility, leading to tumorigenesis and malignant development. The uneven segregation of ecDNA during cell division enhances intercellular genetic heterogeneity, which contributes to tumor evolution that might trigger drug resistance and chemotherapy tolerance. In addition, ecDNA has the ability to integrate into or detach from chromosomal DNA, such progress results into structural alterations and genomic rearrangements within cancer cells. Recent advances in multi-omics analysis revealing the genomic and epigenetic characteristics of ecDNA are anticipated to make valuable contributions to the development of precision cancer therapy. Herein, we conclud the mechanisms of ecDNA generation and the homeostasis of its dynamic structure. In addition to the latest techniques in ecDNA research including multi-omics analysis and biochemical validation methods, we also discuss the role of ecDNA in tumor development and treatment, especially in drug resistance, and future challenges of ecDNA in cancer therapy.

Copy number variants are insertions and deletions of 1 kb or larger in a genome that play an important role in phenotypic changes and human disease. Many software applications have been developed to detect copy number variants using either whole-genome sequencing or whole-exome sequencing data. However, there is poor agreement in the results from these applications. Simulated datasets containing copy number variants allow comprehensive comparisons of the operating characteristics of existing and novel copy number variant detection methods. Several software applications have been developed to simulate copy number variants and other structural variants in whole-genome sequencing data. However, none of the applications reliably simulate copy number variants in whole-exome sequencing data. We have developed and tested SECNVs (Simulator of Exome Copy Number Variants), a fast, robust and customizable software application for simulating copy number variants and whole-exome sequences from a reference genome. SECNVs is easy to install, implements a wide range of commands to customize simulations, can output multiple samples at once, and incorporates a pipeline to output rearranged genomes, short reads and BAM files in a single command. Variants generated by SECNVs are detected with high sensitivity and precision by tools commonly used to detect copy number variants. SECNVs is publicly available at https://github.com/YJulyXing/SECNVs.