Microevolutionary Dynamics of Chicken Genomes under Divergent Selection for Adiposity

HBP1 promotes chicken preadipocyte proliferation via directly repressing SOCS3 transcription

Preadipocyte proliferation is an essential process in adipose development. During proliferation of preadipocytes, transcription factors play crucial roles. HMG-box protein 1 (HBP1) is an important transcription factor of cellular proliferation. However, the function and underlying mechanisms of HBP1 in the proliferation of preadipocytes remain unclear. Here, we found that the expression level of HBP1 decreased first and then increased during the proliferation of chicken preadipocytes. Knockout of HBP1 could inhibit the proliferation of preadipocytes, while overexpression of HBP1 could promote the proliferation of preadipocytes. ChIP-seq data showed that HBP1 had the unique DNA binding motif in chicken preadipocytes. By integrating ChIP-Seq and RNA-Seq, we revealed a total of 3 candidate target genes of HBP1. Furthermore, the results of ChIP-qPCR, RT-qPCR, luciferase reporter assay and EMSA showed that HBP1 could inhibit the transcription of suppressor of cytokine signaling 3 (SOCS3) by binding to its promoter. Moreover, we confirmed that SOCS3 can mediate the regulation of HBP1 on the proliferation of preadipocytes through RNAi and rescue experiments. Altogether, these data demonstrated that HBP1 directly targets SOCS3 to regulate chicken preadipocyte proliferation. Our findings expand the transcriptional regulatory network of preadipocyte proliferation, and they will be helpful in formulating a molecular breeding scheme to control excessive abdominal fat deposition and to improve meat quality in chickens.

Resequencing of a Pekin duck breeding population provides insights into the genomic response to short-term artificial selection

BACKGROUND

Short-term, intense artificial selection drives fast phenotypic changes in domestic animals and leaves imprints on their genomes. However, the genetic basis of this selection response is poorly understood. To better address this, we employed the Pekin duck Z2 pure line, in which the breast muscle weight was increased nearly 3-fold after 10 generations of breeding. We denovo assembled a high-quality reference genome of a female Pekin duck of this line (GCA_003850225.1) and identified 8.60 million genetic variants in 119 individuals among 10 generations of the breeding population.

RESULTS

We identified 53 selected regions between the first and tenth generations, and 93.8% of the identified variations were enriched in regulatory and noncoding regions. Integrating the selection signatures and genome-wide association approach, we found that 2 regions covering 0.36 Mb containing UTP25 and FBRSL1 were most likely to contribute to breast muscle weight improvement. The major allele frequencies of these 2 loci increased gradually with each generation following the same trend. Additionally, we found that a copy number variation region containing the entire EXOC4 gene could explain 1.9% of the variance in breast muscle weight, indicating that the nervous system may play a role in economic trait improvement.

CONCLUSIONS

Our study not only provides insights into genomic dynamics under intense artificial selection but also provides resources for genomics-enabled improvements in duck breeding.

Genome-wide signatures of the geographic expansion and breeding of soybean

Soybean is a leguminous crop that provides oil and protein. Exploring the genomic signatures of soybean evolution is crucial for breeding varieties with improved adaptability to environmental extremes. We analyzed the genome sequences of 2,214 soybeans and proposed a soybean evolutionary route, i.e., the expansion of annual wild soybean (Glycine soja Sieb. & Zucc.) from southern China and its domestication in central China, followed by the expansion and local breeding selection of its landraces (G. max (L.) Merr.). We observed that the genetic introgression in soybean landraces was mostly derived from sympatric rather than allopatric wild populations during the geographic expansion. Soybean expansion and breeding were accompanied by the positive selection of flowering time genes, including GmSPA3c. Our study sheds light on the evolutionary history of soybean and provides valuable genetic resources for its future breeding.

Folate inhibits lipid deposition via the autophagy pathway in chicken hepatocytes

Excessive fat deposition affects the efficiency and quality of broiler meat production. To understand the molecular mechanism underlying abdominal fat content of broiler lines under divergent selection, we have attempted multiple genetics and genomics methods previously. However, the molecular mechanism of hepatic fat deposition remains largely unknown. On broiler lines divergently selected for abdominal fat content, we performed integrated mRNA and lncRNA sequencing on liver tissues. Key genes and signaling pathways related to the biosynthesis, elongation and metabolism of fatty acids, metabolic pathways, and folate biosynthesis were revealed. Then, primary hepatocytes (sex determined) were isolated and cultured, and treatment concentrations of folate and palmitic acid were optimized. Expression profiling on primary hepatocytes treated by folate and/or palmitic acid revealed that folic acid inhibited lipid deposition in a sex-dependent way, through regulating transcriptional and protein levels of genes related to DNA methylation, lipid metabolism (mTOR/SREBP-1c/PI3K), and autophagy (LAMP2/ATG5) pathways. Taken together, folate could interfere with hepatic lipid deposition possibly through the involvement of the autophagy pathway in broilers.

Omics technologies in poultry health and productivity - part 1: current use in poultry research

In biology, molecular terms with the suffix "-omics" refer to disciplines aiming at the collective characterization of pools of molecules derived from different layers (DNA, RNA, proteins, metabolites) of living organisms using high-throughput technologies. Such omics analyses have been widely implemented in poultry research in recent years. This first part of a bipartite review on omics technologies in poultry health and productivity examines the use of multiple omics and multi-omics techniques in poultry research. More specific present and future applications of omics technologies, not only for the identification of specific diagnostic biomarkers, but also for potential future integration in the daily monitoring of poultry production, are discussed in part 2. Approaches based on omics technologies are particularly used in poultry research in the hunt for genetic markers of economically important phenotypical traits in the host, and in the identification of key bacterial species or functions in the intestinal microbiome. Integrative multi-omics analyses, however, are still scarce. Host physiology is investigated via genomics together with transcriptomics, proteomics and metabolomics techniques, to understand more accurately complex production traits such as disease resistance and fertility. The gut microbiota, as a key player in chicken productivity and health, is also a main subject of such studies, investigating the association between its composition (16S rRNA gene sequencing) or function (metagenomics, metatranscriptomics, metaproteomics, metabolomics) and host phenotypes. Applications of these technologies in the study of other host-associated microbiota and other host characteristics are still in their infancy.

Identification of a Long Noncoding RNA (lncPRDM16) Inhibiting Preadipocyte Proliferation in the Chicken

Long noncoding RNAs are vital to a variety of biological and physiological processes through multiple modes of functional interaction with DNA, RNA, and proteins. In chickens, numerous lncRNAs were discovered to be important to growth or disease progression. However, the detailed molecular function and role of lncRNAs remain less explored. Here, we performed lncRNA sequencing on abdominal adipose tissues from broiler lines divergently selected for abdominal fat content, and significantly differentially expressed lncRNAs were found, including lncPRDM16, a divergently transcribed and conserved lncRNA near PRDM16. Full lengths of two transcripts of lncPRDM16 were obtained, and their genomic structures were compared. Expression dynamics of lncPRDM16 in different tissues and during preadipocyte proliferation and differentiation were profiled. Moreover, a 250-nucleotide sequence at 5'-end was found to be inevitable to the function of lncPRDM16 in inhibiting preadipocyte proliferation and regulating the promoter activities of both lncPRDM16 and PRDM16. Taken together, we identified the 5'-end functional elements of lncPRDM16 and their potential importance in inhibiting preadipocyte proliferation. Our findings provide the foundation for further exploration of lncPRDM16 function and potential improvement of chicken muscle quality.

Polymorphisms of KLF3 gene coding region and identification of their functionality for abdominal fat in chickens

KLF3 is a member of the Kruppel‐like factor (KLF) family of transcription factors, and plays an important role in several biological processes, including adipogenesis, erythropoiesis and B‐cell development. The purposes of this study are to search for polymorphisms of KLF3 coding region and to provide functional evidence for abdominal fat in chickens. A total of 168 SNPs in KLF3 coding region were detected in a unique chicken population, the Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF). Of which three single nucleotide polymorphisms (g.3452T > C, g.8663A > G and g.10751G > A) were significantly correlated with abdominal fat weight (AFW) and abdominal fat percentage (AFP) of 329 birds from the 19th generation of NEAUHLF (FDR < 0.05). The reporter gene assay was performed to verify functionality of these three SNPs in both ICP‐1 and DF1 cells. Results showed that the luciferase activity of G allele was significantly higher than that of A allele in g.10751G > A (p < 0.05). However, there were no significant differences between different alleles of others two SNPs in luciferase activity. Overall, KLF3 is an important candidate gene that affects chicken abdominal fat content, and the g.10751G > A is a functional variant that potential would be applied to marker‐assisted selection (MAS) for selective breeding programme.