Efficient SNP Discovery by Combining Microarray and Lab-on-a-Chip Data for Animal Breeding and Selection

Multiplex Detection of SNPs for Genetic Monitoring in Laboratory Mice by Luminex xTAG Assay

Background: The genetic quality of laboratory mice may have a direct impact on the results of research. Therefore, it is essential to improve genetic monitoring methods to guarantee research quality. However, few current methods boast high efficiency, high throughput, low cost, and general applicability at the same time. Methods: First, we got 34 SNP loci from previous studies for inbred strains and screened out 15 loci with good polymorphism for outbred groups from these 34 loci. Then, by using the Luminex xTAG assay, we tested inbred strains and outbred groups. Results: We tested commonly used inbred strains and five DNA samples from the International Council for Laboratory Animal Science, obtaining correct genotyping results. Additionally, some loci were potentially confirmed to be useful for distinguishing C57BL/6 and BALB/c mouse substrains. Furthermore, we tested three outbred groups and analyzed the genetic structure, and we compared the results of the SNP markers by xTAG assay to the STR markers by PCR, the trends of the three groups are the same. Conclusions: In our studies, the panels could meet the requirements for method promotion and provide a good choice for the genetic monitoring of inbred and outbred mice.

Genetic Markers Related to Meat Quality Properties in Fattened HF and HF x Charolaise Steers

This study involved 45 Holstein and 60 Holstein-Charolaise steers, tailored with specific diets according to breed and rearing systems. DNA genotyping was conducted for DGAT1, LEP, SCD1, SREBF1, and TG genes to investigate their impact on carcass conformation traits, beef quality traits, and sensory quality traits. The results showed associations between the genetic variants and the analyzed traits. Specifically, DGAT1 was found to affect drip loss, meat brightness, and color saturation. The TG gene was associated with marbling and meat color. LEP influenced trim fat and pH levels, while SCD1 was linked to metabolic energy live weight gains, and pH levels. SREBF1 was related to fatness.

Rethinking underutilized cereal crops: pan-omics integration and green system biology

MAIN CONCLUSION

Due to harsh lifestyle changes, in the present era, nutritional security is needed along with food security so it is necessary to include underutilized cereal crops (UCCs) in our daily diet to counteract the rising danger of human metabolic illness. We can attain both the goal of zero hunger and nutritional security by developing improved UCCs using advanced pan-omics (genomics, transcriptomics, proteomics, metabolomics, nutrigenomics, phenomics and ionomics) practices. Plant sciences research progressed profoundly since the last few decades with the introduction of advanced technologies and approaches, addressing issues of food demand of the growing population, nutritional security challenges and climate change. However, throughout the expansion and popularization of commonly consumed major cereal crops such as wheat and rice, other cereal crops such as millet, rye, sorghum, and others were impeded, despite their potential medicinal and nutraceutical qualities. Undoubtedly neglected underutilized cereal crops (UCCs) also have the capability to withstand diverse climate change. To relieve the burden of major crops, it is necessary to introduce the new crops in our diet in the way of UCCs. Introgression of agronomically and nutritionally important traits by pan-omics approaches in UCCs could be a defining moment for the population's well-being on the globe. This review discusses the importance of underutilized cereal crops, as well as the application of contemporary omics techniques and advanced bioinformatics tools that could open up new avenues for future study and be valuable assets in the development and usage of UCCs in the perspective of green system biology. The increased and improved use of UCCs is dependent on number of factors that necessitate a concerted research effort in agricultural sciences. The emergence of functional genomics with molecular genetics might gear toward the reawakening of interest in underutilized cereals crops. The need of this era is to focus on potential UCCs in advanced agriculture and breeding programmes. Hence, targeting the UCCs, might provide a bright future for better health and scientific rationale for its use.

Application potential of chicken DNA chip in domestic pigeon species - Preliminary results

Introducing the SNP technology to pigeon breeding will enhance the competitiveness of a sector that produces one of the healthiest and best quality meats. The present study aimed to test the applicability of the Illumina Chicken_50K_CobbCons array on 24 domestic pigeon individuals from the Mirthys hybrids and Racing pigeon breeds. A total of 53,313 SNPs were genotyped. Principal component analysis shows a significant overlap between the two groups. The chip performed poorly in this data set, with a call rate per sample of 0.474 (49%). The low call rate was likely due to an increase in the evolutionary distance. A total of 356 SNPs were retained after a relatively strict quality control. We have demonstrated that it is technically feasible to use a chicken microarray chip on pigeon samples. Presumably, with a larger sample size and by assigning phenotypic data, efficiency would be improved, allowing more thorough analyses, such as genome-wide association studies.

Two Different Copy Number Variations of the SOX5 and SOX8 Genes in Yak and Their Association with Growth Traits

Copy number variation (CNV) is a structural variant with significant impact on genetic diversity. CNV has been widely used in breeding for growth traits, meat production or quality, and coat color. SRY-like box genes (SOXs) are a class of transcription factors that play a regulatory role in cell fate specification and differentiation. SOX5 and SOX8 belong to subgroups D and E of the SOXs, respectively. Previous studies have shown that SOX5 and SOX8 are essential in the development of bones. In this study, we explored the association between the growth traits and CNVs of SOX5 and SOX8 in 326 Ashidan yaks and detected mRNA expression levels in different tissues. Our results illustrated that CNVs of SOX5 and SOX8 were significantly associated with withers height at 18 months of age and chest girth at 30 months of age (p < 0.05). The CNV combination of SOX5 and SOX8 was significantly associated with withers height at 18 months of age (p < 0.01). SOX5 expression in the lung was significantly higher than in the heart, spleen, kidney, and muscle (p < 0.05). SOX8 expression in the lung was significantly higher than in the liver and muscle (p < 0.05). Our results provide evidence that the CNVs of SOX5 and SOX8 genes could be used as new markers for the selection of yak growth traits.

Molecular Alterations of the Endocannabinoid System in Psychiatric Disorders

The therapeutic benefits of the current medications for patients with psychiatric disorders contrast with a great variety of adverse effects. The endocannabinoid system (ECS) components have gained high interest as potential new targets for treating psychiatry diseases because of their neuromodulator role, which is essential to understanding the regulation of many brain functions. This article reviewed the molecular alterations in ECS occurring in different psychiatric conditions. The methods used to identify alterations in the ECS were also described. We used a translational approach. The animal models reproducing some behavioral and/or neurochemical aspects of psychiatric disorders and the molecular alterations in clinical studies in post-mortem brain tissue or peripheral tissues were analyzed. This article reviewed the most relevant ECS changes in prevalent psychiatric diseases such as mood disorders, schizophrenia, autism, attentional deficit, eating disorders (ED), and addiction. The review concludes that clinical research studies are urgently needed for two different purposes: (1) To identify alterations of the ECS components potentially useful as new biomarkers relating to a specific disease or condition, and (2) to design new therapeutic targets based on the specific alterations found to improve the pharmacological treatment in psychiatry.

Impact of genotypic errors with equal and unequal family contribution on accuracy of genomic prediction in aquaculture using simulation

Genotypic errors, conflict between recorded genotype and the true genotype, can lead to false or biased population genetic parameters. Here, the effect of genotypic errors on accuracy of genomic predictions and genomic relationship matrix are investigated using a simulation study based on population and genomic structure comparable to black tiger prawn, Penaeus monodon. Fifty full-sib families across five generations with phenotypic and genotypic information on 53 K SNPs were simulated. Ten replicates of different scenarios with three heritability estimates, equal and unequal family contributions were generated. Within each scenario, four SNP densities and three genotypic error rates in each SNP density were implemented. Results showed that family contribution did not have a substantial impact on accuracy of predictions across different datasets. In the absence of genotypic errors, 3 K SNP density was found to be efficient in estimating the accuracy, whilst increasing the SNP density from 3 to 20 K resulted in a marginal increase in accuracy of genomic predictions using the current population and genomic parameters. In addition, results showed that the presence of even 10% errors in a 10 and 20 K SNP panel might not have a severe impact on accuracy of predictions. However, below 10 K marker density, even a 5% error can result in lower accuracy of predictions.

Genetic loci associated with coronary artery disease harbor evidence of selection and antagonistic pleiotropy

Traditional genome-wide scans for positive selection have mainly uncovered selective sweeps associated with monogenic traits. While selection on quantitative traits is much more common, very few signals have been detected because of their polygenic nature. We searched for positive selection signals underlying coronary artery disease (CAD) in worldwide populations, using novel approaches to quantify relationships between polygenic selection signals and CAD genetic risk. We identified new candidate adaptive loci that appear to have been directly modified by disease pressures given their significant associations with CAD genetic risk. These candidates were all uniquely and consistently associated with many different male and female reproductive traits suggesting selection may have also targeted these because of their direct effects on fitness. We found that CAD loci are significantly enriched for lifetime reproductive success relative to the rest of the human genome, with evidence that the relationship between CAD and lifetime reproductive success is antagonistic. This supports the presence of antagonistic-pleiotropic tradeoffs on CAD loci and provides a novel explanation for the maintenance and high prevalence of CAD in modern humans. Lastly, we found that positive selection more often targeted CAD gene regulatory variants using HapMap3 lymphoblastoid cell lines, which further highlights the unique biological significance of candidate adaptive loci underlying CAD. Our study provides a novel approach for detecting selection on polygenic traits and evidence that modern human genomes have evolved in response to CAD-induced selection pressures and other early-life traits sharing pleiotropic links with CAD.

Automated melting curve analysis in droplet microfluidics for single nucleotide polymorphisms (SNP) genotyping

An integrated microchip platform with automated analysis capability for DNA melting curves is developed for Single Nucleotide Polymorphism (SNP) genotyping applications.

SNP Arrays

The papers published in this Special Issue “SNP arrays” (Single Nucleotide Polymorphism Arrays) focus on several perspectives associated with arrays of this type. The range of papers vary from a case report to reviews, thereby targeting wider audiences working in this field. The research focus of SNP arrays is often human cancers but this Issue expands that focus to include areas such as rare conditions, animal breeding and bioinformatics tools. Given the limited scope, the spectrum of papers is nothing short of remarkable and even from a technical point of view these papers will contribute to the field at a general level. Three of the papers published in this Special Issue focus on the use of various SNP array approaches in the analysis of three different cancer types. Two of the papers concentrate on two very different rare conditions, applying the SNP arrays slightly differently. Finally, two other papers evaluate the use of the SNP arrays in the context of genetic analysis of livestock. The findings reported in these papers help to close gaps in the current literature and also to give guidelines for future applications of SNP arrays.