The Shisa3 knockout mouse exhibits normal bone phenotype

Genome-wide association study of growth curve parameters reveals novel genomic regions and candidate genes associated with metatarsal bone traits in chickens

The growth and development of chicken bones have an enormous impact on the health and production performance of chickens. However, the development pattern and genetic regulation of the chicken skeleton are poorly understood. This study aimed to evaluate metatarsal bone growth and development patterns in chickens via non-linear models, and to identify the genetic determinants of metatarsal bone traits using a genome-wide association study (GWAS) based on growth curve parameters. Data on metatarsal length (MeL) and metatarsal circumference (MeC) were obtained from 471 F2 chickens (generated by crossing broiler sires, derived from a line selected for high abdominal fat, with Baier layer dams) at 4, 6, 8, 10, and 12 weeks of age. Four non-linear models (Gompertz, Logistic, von Bertalanffy, and Brody) were used to fit the MeL and MeC growth curves. Subsequently, the estimated growth curve parameters of the mature MeL or MeC (A), time-scale parameter (b), and maturity rate (K) from the non-linear models were utilized as substitutes for the original bone data in GWAS. The Logistic and Brody models displayed the best goodness-of-fit for MeL and MeC, respectively. Single-trait and multi-trait GWASs based on the growth curve parameters of the Logistic and Brody models revealed 4 618 significant single nucleotide polymorphisms (SNPs), annotated to 332 genes, associated with metatarsal bone traits. The majority of these significant SNPs were located on Gallus gallus chromosome (GGA) 1 (167.433-176.318 Mb), GGA2 (96.791-103.543 Mb), GGA4 (65.003-83.104 Mb) and GGA6 (64.685-95.285 Mb). Notably, we identified 12 novel GWAS loci associated with chicken metatarsal bone traits, encompassing 35 candidate genes. In summary, the combination of single-trait and multi-trait GWASs based on growth curve parameters uncovered numerous genomic regions and candidate genes associated with chicken bone traits. The findings benefit an in-depth understanding of the genetic architecture underlying metatarsal growth and development in chickens.

Differential gene expression in the calvarial and cortical bone of juvenile female mice

Introduction

Both the calvarial and the cortical bones develop through intramembranous ossification, yet they have very different structures and functions. The calvaria enables the rapid while protected growth of the brain, whereas the cortical bone takes part in locomotion. Both types of bones undergo extensive modeling during embryonic and post-natal growth, while bone remodeling is the most dominant process in adults. Their shared formation mechanism and their highly distinct functions raise the fundamental question of how similar or diverse the molecular pathways that act in each bone type are.

Methods

To answer this question, we aimed to compare the transcriptomes of calvaria and cortices from 21-day old mice by bulk RNA-Seq analysis.

Results

The results revealed clear differences in expression levels of genes related to bone pathologies, craniosynostosis, mechanical loading and bone-relevant signaling pathways like WNT and IHH, emphasizing the functional differences between these bones. We further discussed the less expected candidate genes and gene sets in the context of bone. Finally, we compared differences between juvenile and mature bone, highlighting commonalities and dissimilarities of gene expression between calvaria and cortices during post-natal bone growth and adult bone remodeling.

Discussion

Altogether, this study revealed significant differences between the transcriptome of calvaria and cortical bones in juvenile female mice, highlighting the most important pathway mediators for the development and function of two different bone types that originate both through intramembranous ossification.

Polymorphisms in SHISA3 and RFC3 genes and their association with feed conversion ratio in Hu sheep

In animal husbandry, feed efficiency is a crucial economic trait. In this study, the general linear model was used to perform association analysis for various genotypes and feed conversion ratio (FCR)-related traits. Reverse transcription-quantitative PCR (RT-qPCR) was used to detect the expression of SHISA3 and RFC3 mRNA levels in 10 tissues from 6 sheep. The results showed that SNPs in the NC_040257.1:c.625 T > C and NC_040261.1:g.9905 T > C were analyzed whether they were associated to feed efficiency parameters in Hu sheep (body weight, feed intake, average daily growth, and feed conversion ratio). NC_040257.1:c.625 T > C was shown to be significantly associated with body weight at 80, 100, and 120 days as well as feed conversion ratio (P < 0.05), whereas NC_040261.1:g.9905 T > C was found to be significantly associated with average daily weight gain from 80-140 days (ADG80-140) and FCR (P < 0.05). In Hu sheep, the CC genotypes of SHISA3 and RFC3 were the most common genotypes related to feed efficiency traits. Furthermore, the feed conversion ratio of the combined genotypes TT ^SHISA3-CC ^RFC3, TT ^SHISA3-CT ^RFC3, TT ^SHISA3-TT ^RFC3, CT ^SHISA3-CC ^RFC3 and CT ^SHISA3-CT ^RFC3 was significantly better than the FCR of CC ^SHISA3-TT ^RFC3. RT-qPCR results showed that the expression levels of SHISA3 were lower in the lung than in spleen, kidney, muscle and lymph (P < 0.05), and RFC3 was the lung had a highly significant higher expression level than the heart, liver, spleen, and muscle (P < 0.01). In conclusion, SHISA3 and RFC3 polymorphisms can be used as genetic markers for improving feed conversion efficiency in Hu sheep.

Genome-Wide Association Studies for Growth Curves in Meat Rabbits Through the Single-Step Nonlinear Mixed Model

Growth is a complex trait with moderate to high heritability in livestock and must be described by the longitudinal data measured over multiple time points. Therefore, the used phenotype in genome-wide association studies (GWAS) of growth traits could be either the measures at the preselected time point or the fitted parameters of whole growth trajectory. A promising alternative approach was recently proposed that combined the fitting of growth curves and estimation of single-nucleotide polymorphism (SNP) effects into single-step nonlinear mixed model (NMM). In this study, we collected the body weights at 35, 42, 49, 56, 63, 70, and 84 days of age for 401 animals in a crossbred population of meat rabbits and compared five fitting models of growth curves (Logistic, Gompertz, Brody, Von Bertalanffy, and Richards). The logistic model was preferably selected and subjected to GWAS using the approach of single-step NMM, which was based on 87,704 genome-wide SNPs. A total of 45 significant SNPs distributed on five chromosomes were found to simultaneously affect the two growth parameters of mature weight (A) and maturity rate (K). However, no SNP was found to be independently associated with either A or K. Seven positional genes, including KCNIP4, GBA3, PPARGC1A, LDB2, SHISA3, GNA13, and FGF10, were suggested to be candidates affecting growth performances in meat rabbits. To the best of our knowledge, this is the first report of GWAS based on single-step NMM for longitudinal traits in rabbits, which also revealed the genetic architecture of growth traits that are helpful in implementing genome selection.

Exome Sequencing Reveals De Novo Variants in Congenital Scoliosis

Congenital scoliosis (CS) is a lateral curvature of the spine characterized by the presence of vertebral anomalies. Pathogenic genetic variants in the TBX6 gene are one of the causes of CS. However, since many clinically diagnosed cases of CS are without known TBX6 gene variations, this study aims to uncover new genes related to disease susceptibility of CS by exome sequencing (ES). This study employed ES in a cohort of 5 Japanese patients with CS and their healthy parents or a sister for a total of 16 samples among 5 families. Variant interpretation was performed using SIFT, PolyPhen-2, Mutation Taster, and CADD. Four de novo variants were identified by ES and confirmed by Sanger sequencing: 1 frameshift variant (SHISA3) and 3 missense variants (AGBL5, HDAC4, and PDE2A). ES also uncovered 1 homozygous variant in the MOCOS gene. All of these variants were predicted to be deleterious by SIFT, PolyPhen-2, Mutation Taster, and/or CADD. The number of de novo variants identified in this study was exactly what would be expected by chance. Additional functional studies or gathering matched patients using Gene Matcher are needed.