Comparison of F-tests for Univariate and Multivariate Mixed-Effect Models in Genome-Wide Association Mapping

The use of various statistical methods for authenticity and detection of adulteration in fish and seafood

Various methodologies including genetic analyses, morphometrics, proteomics, lipidomics, metabolomics, etc. are now used or being developed to authenticate fish and seafood. Such techniques usually lead to the generation of enormous amounts of data. The analysis and interpretation of this information can be particularly challenging. Statistical techniques are therefore commonly used to assist in analyzing these data, visualizing trends and differences and extracting conclusions. This review article aims at presenting and discussing statistical methods used in studies on fish and seafood authenticity and adulteration, allowing researchers to consider their options based on previous successes/failures but also offering some recommendations about the future of such techniques. Techniques such as PCA, AMOVA and FST statistics, that allow the differentiation of genetic groups, or techniques such as MANOVA that allow large data sets of morphometric characteristics or elemental differences to be analyzed are discussed. Furthermore, methods such as cluster analysis, DFA, CVA, CDA and heatmaps/Circos plots that allow samples to be differentiated based on their geographical origin are also reviewed and their advantages and disadvantages as found in past studies are given. Finally, mathematical simulations and modeling are presented in a detailed review of studies using them, together with their advantages and limitations.

Multivariate linear mixed model enhanced the power of identifying genome-wide association to poplar tree heights in a randomized complete block design

With the advances in high-throughput sequencing technologies, it is not difficult to extract tens of thousands of single-nucleotide polymorphisms (SNPs) across many individuals in a fast and cheap way, making it possible to perform genome-wide association studies (GWAS) of quantitative traits in outbred forest trees. It is very valuable to apply traditional breeding experiments in GWAS for identifying genome variants associated with ecologically and economically important traits in Populus. Here, we reported a GWAS of tree height measured at multiple time points from a randomized complete block design (RCBD), which was established with clones from an F₁ hybrid population of Populus deltoides and Populus simonii. A total of 22,670 SNPs across 172 clones in the RCBD were obtained with restriction site-associated DNA sequencing (RADseq) technology. The multivariate mixed linear model was applied by incorporating the pedigree relationship matrix of individuals to test the association of each SNP to the tree heights over 8 time points. Consequently, 41 SNPs were identified significantly associated with the tree height under the P-value threshold determined by Bonferroni correction at the significant level of 0.01. These SNPs were distributed on all but two chromosomes (Chr02 and Chr18) and explained the phenotypic variance ranged from 0.26% to 2.64%, amounting to 63.68% in total. Comparison with previous mapping studies for poplar height as well as the candidate genes of these detected SNPs were also investigated. We therefore showed that the application of multivariate linear mixed model to the longitudinal phenotypic data from the traditional breeding experimental design facilitated to identify far more genome-wide variants for tree height in poplar. The significant SNPs identified in this study would enhance understanding of molecular mechanism for growth traits and would accelerate marker-assisted breeding programs in Populus.

Proteome-wide Systems Genetics to Identify Functional Regulators of Complex Traits

Proteomic technologies now enable the rapid quantification of thousands of proteins across genetically diverse samples. Integration of these data with systems-genetics analyses is a powerful approach to identify new regulators of economically important or disease-relevant phenotypes in various populations. In this review, we summarize the latest proteomic technologies and discuss technical challenges for their use in population studies. We demonstrate how the analysis of correlation structure and loci mapping can be used to identify genetic factors regulating functional protein networks and complex traits. Finally, we provide an extensive summary of the use of proteome-wide systems genetics throughout fungi, plant, and animal kingdoms and discuss the power of this approach to identify candidate regulators and drug targets in large human consortium studies.

Molecular detection and genotype distribution of Enterocytozoon bieneusi in farmed silver foxes (Vulpes vulpes) and arctic foxes (Vulpes lagopus) in Shandong Province, eastern China

Enterocytozoon bieneusi is an opportunistic enteric pathogen which can infect a wide range of animal species and humans. It is the most diagnosed species of Microsporidia in humans and has an impact on public health. Many infected animals including foxes may be a potential source for transmitting E. bieneusi to humans. However, limited information is available on the E. bieneusi prevalence and genotypes in farmed foxes in China. Therefore, in the present study, 344 fresh fecal samples were collected from farmed foxes (Vulpes vulpes and Vulpes lagopus) in Shandong Province, and the prevalence and genotypes of E. bieneusi were examined based on sequence analysis of the ribosomal internal transcribed spacer (ITS) region. The overall E. bieneusi prevalence was 9% (31/344); of them, 6.5% (9/138) in farmed silver foxes (V. vulpes) and 10.7% (22/206) in farmed arctic foxes (V. lagopus). Moreover, four known (Hum-q1, NCF2, HND-1, and Type IV) and two novel E. bieneusi genotypes (SDF1 and SDF2) were identified in farmed foxes in the present study. All of the E. bieneusi genotypes belonged to the zoonotic group based on phylogenetic analysis. In addition, 2, 4, 0, and 11 samples were successfully amplified at MS1, MS3, MS4, and MS7 loci, respectively. The present study reveals E. bieneusi prevalence and genotype distribution in farmed foxes in Shandong Province and enlarged the host and geographic information of E. bieneusi in China.