Long-read sequencing-based transcriptomic landscape in longissimus dorsi and transcriptome-wide association studies for growth traits of meat rabbits

Rabbits are an attractive meat livestock species that can efficiently convert human-indigestible plant biomass, and have been commonly used in biological and medical researches. Yet, transcriptomic landscape in muscle tissue and association between gene expression level and growth traits have not been specially studied in meat rabbits. In this study Oxford Nanopore Technologies (ONT) long-read sequencing technology was used for comprehensively exploring transcriptomic landscape in Longissimus dorsi for 115 rabbits at 84 days of age, and transcriptome-wide association studies (TWAS) were performed for growth traits, including body weight at 84 days of age and average daily gain during three growth periods. The statistical analysis of TWAS was performed using a mixed linear model, in which polygenic effect was fitted as a random effect according to gene expression level-based relationships. A total of 18,842 genes and 42,010 transcripts were detected, among which 35% of genes and 47% of transcripts were novel in comparison with the reference genome annotation. Furthermore, 45% of genes were widely expressed among more than 90% of individuals. The proportions (±SE) of phenotype variance explained by genome-wide gene expression level ranged from 0.501 ± 0.216 to 0.956 ± 0.209, and the similar results were obtained when explained by transcript expression level. In contrast, neither gene nor transcript was detected by TWAS to be statistically significantly associated with these growth traits. In conclusion, these novel genes and transcripts that have been extensively profiled in a single muscle tissue using long-read sequencing technology will greatly improve our understanding on transcriptional diversity in rabbits. Our results with a relatively small sample size further revealed the important contribution of global gene expression to phenotypic variation on growth performance, but it seemed that no single gene has an outstanding effect; this knowledge is helpful to include intermediate omics data for implementing genetic evaluation of growth traits in meat rabbits

A genome-wide association study of coat color in Chinese Rex rabbits

Coat color is an important phenotypic characteristic of the domestic rabbit (Oryctolagus cuniculus) and has specific economic importance in the Rex rabbit industry. Coat color varies considerably among different populations of rabbits, and several causal genes for this variation have been thoroughly studied. Nevertheless, the candidate genes affecting coat color variation in Chinese Rex rabbits remained to be investigated. In this study, we collected blood samples from 250 Chinese Rex rabbits with six different coat colors. We performed genome sequencing using a restriction site-associated DNA sequencing approach. A total of 91,546 single nucleotide polymorphisms (SNPs), evenly distributed among 21 autosomes, were identified. Genome-wide association studies (GWAS) were performed using a mixed linear model, in which the individual polygenic effect was fitted as a random effect. We detected a total of 24 significant SNPs that were located within a genomic region on chromosome 4 (OCU4). After re-fitting the most significant SNP (OCU4:13,434,448, p = 1.31e-12) as a covariate, another near-significant SNP (OCU4:11,344,946, p = 7.03e-07) was still present. Hence, we conclude that the 2.1-Mb genomic region located between these two significant SNPs is significantly associated with coat color in Chinese Rex rabbits. The well-studied coat-color-associated agouti signaling protein (ASIP) gene is located within this region. Furthermore, low genetic differentiation was also observed among the six coat color varieties. In conclusion, our results confirmed that ASIP is a putative causal gene affecting coat color variation in Chinese Rex rabbits

Microbiome of Total Versus Live Bacteria in the Gut of Rex Rabbits

Gastrointestinal bacteria are essential for host health, and only viable microorganisms contribute to gastrointestinal functions. When evaluating the gut microbiota by next generation sequencing method, dead bacteria, which compose a proportion of gut bacteria, may distort analysis of the live gut microbiota. We collected stomach, jejunum, ileum, cecum, and colon contents from Rex rabbits. A modified propidium monoazide (PMA) treatment protocol was used to exclude DNA from dead bacteria. Analysis of untreated samples yielded total bacteria, and analysis of PMA-treated samples yielded live bacteria. Quantitative polymerase chain reaction and 16S rRNA gene sequencing were performed to evaluate the live-to-total bacteria ratio and compare the difference between live and total microbiota in the entire digestive tract. A low proportion of live bacteria in the foregut (stomach 1.12%, jejunum 1.2%, ileum 2.84%) and a high proportion of live bacteria in the hindgut (cecum 24.66%, colon 19.08%) were observed. A significant difference existed between total and live microbiota. Clostridiales, Ruminococcaceae, and S24-7 dominated the hindgut of both groups, while Acinetobacter and Cupriavidus dominated only in live foregut microbiota. Clostridiales and Ruminococcaceae abundance decreased, while S24-7 increased in live hindgut microbiota. The alpha- and beta-diversities differed significantly between groups. Analysis of networks showed the mutual relationship between live bacteria differed vastly when compared with total bacteria. Our study revealed a large number of dead bacteria existed in the digestive tract of Rex rabbits and distorted the community profile of the live microbiota. Total bacteria is an improper representation of the live gut microbiota, particularly in the foregut

Calibration and Distortion Field Compensation of Gradiometer and the Improvement in Object Remote Sensing

Magnetometer, misalignment error and distortion field can reduce the accuracy of gradiometers. So, it is important to calibrate and compensate gradiometers error. Scale factor, bias, nonorthogonality, misalignment and distortion field should be considered. A gradiometer is connected by an aluminium frame, which contains two fluxgate magnetometers. A nonmagnetic rotation equipment is used to change gradiometer attitude, and the compensation parameters are estimated. Experiment results show that, after calibration and compensation, error of each axis is reduced from 888.4 nT, 1292.6 nT and 168.9 nT to 15.3 nT, 22.1 nT and 9.9 nT, respectively. It shows that the proposed method can calibrate gradiometer and compensate distortion field. After calibration and compensation, the object remote sensing performance is improved

Calibration and Distortion Field Compensation of Gradiometer and the Improvement in Object Remote Sensing

Magnetometer, misalignment error and distortion field can reduce the accuracy of gradiometers. So, it is important to calibrate and compensate gradiometers error. Scale factor, bias, nonorthogonality, misalignment and distortion field should be considered. A gradiometer is connected by an aluminium frame, which contains two fluxgate magnetometers. A nonmagnetic rotation equipment is used to change gradiometer attitude, and the compensation parameters are estimated. Experiment results show that, after calibration and compensation, error of each axis is reduced from 888.4 nT, 1292.6 nT and 168.9 nT to 15.3 nT, 22.1 nT and 9.9 nT, respectively. It shows that the proposed method can calibrate gradiometer and compensate distortion field. After calibration and compensation, the object remote sensing performance is improved

Calibration and Distortion Field Compensation of Gradiometer and the Improvement in Object Remote Sensing

Magnetometer, misalignment error and distortion field can reduce the accuracy of gradiometers. So, it is important to calibrate and compensate gradiometers error. Scale factor, bias, nonorthogonality, misalignment and distortion field should be considered. A gradiometer is connected by an aluminium frame, which contains two fluxgate magnetometers. A nonmagnetic rotation equipment is used to change gradiometer attitude, and the compensation parameters are estimated. Experiment results show that, after calibration and compensation, error of each axis is reduced from 888.4 nT, 1292.6 nT and 168.9 nT to 15.3 nT, 22.1 nT and 9.9 nT, respectively. It shows that the proposed method can calibrate gradiometer and compensate distortion field. After calibration and compensation, the object remote sensing performance is improved

MOESM1 of Illumina Miseq platform analysis caecum bacterial communities of rex rabbits fed with different antibiotics

Additional file 1. Additional tables