Identify known and novel candidate genes associated with backfat thickness in Duroc pigs by large-scale genome-wide association analysis

Backfat thickness (BFT) is complex and economically important traits in the pig industry, since it reflects fat deposition and can be used to measure the carcass lean meat percentage in pigs. In this study, all 6,550 pigs were genotyped using the Geneseek Porcine 50K SNP Chip to identify SNPs related to BFT and to search for candidate genes through genome-wide association analysis in two Duroc populations. In total, 80 SNPs, including 39 significant and 41 suggestive SNPs, and 6 QTLs were identified significantly associated with the BFT. In addition, 9 candidate genes, including a proven major gene MC4R, 3 important candidate genes (RYR1, HMGA1 and NUDT3) which were previously described as related to BFT, and 5 novel candidate genes (SIRT2, NKAIN2, AMH, SORCS1 and SORCS3) were found based on their potential functional roles in BFT. The functions of candidate genes and gene set enrichment analysis indicate that most important pathways are related to energy homeostasis and adipogenesis. Finally, our data suggests that most of the candidate genes can be directly used for genetic improvement through molecular markers, except that the MC4R gene has an antagonistic effect on growth rate and carcass lean meat percentage in breeding. Our results will advance our understanding of the complex genetic architecture of BFT traits, and laid the foundation for additional genetic studies to increase carcass lean meat percentage of pig through marker-assisted selection and/or genomic selection.

7-Score Function for Assessing the Strength of Association Rules Applied for Construction Risk Quantifying

There are several factors influencing the time of construction project execution. The properties of the planned structure, the details of an order, and macroeconomic factors affect the project completion time. Every construction project is unique, but the data collected from previously completed projects help to plan the new one. The association analysis is a suitable tool for uncovering the rules—showing the influence of some factors appearing simultaneously. The input data to the association analysis must be preprocessed—every feature influencing the duration of the project must be divided into ranges. The number of features and the number of ranges (for each feature) create a very complicated combinatorial problem. The authors applied a metaheuristic tabu search algorithm to find the acceptable thresholds in the association analysis, increasing the strength of the rules found. The increase in the strength of the rules can help clients to avoid unfavorable sets of features, which in the past—with high confidence—significantly delayed projects. The new 7-score method can be used in various industries. This article shows its application to reduce the risk of a road construction contract delay. Importantly, the method is not based on expert opinions, but on historical data.

Association Study of the M132L Single Nucleotide Polymorphism With Susceptibility to Chronic Wasting Disease in Korean Elk: A Meta-Analysis

Chronic wasting disease (CWD) is a deleterious brain proteinopathy caused by a pathogenic form of prion protein (PrPSc), which is converted from a benign form of prion protein (PrPC) encoded by the prion protein gene (PRNP). In elk, the M132L single nucleotide polymorphism (SNP) of the PRNP gene likely plays a pivotal role in susceptibility to CWD. However, the association of the M132L SNP with susceptibility to CWD has not been evaluated in Korean elk to date. To estimate the association of the M132L SNP with susceptibility to CWD in Korean elk, we investigated the genotype and allele frequencies of the M132L SNP by amplicon sequencing and performed association analysis between CWD-positive and CWD-negative elk. In addition, we performed a meta-analysis to evaluate the association between the M132L SNP and susceptibility to CWD in quantitatively synthesized elk populations. Furthermore, we estimated the effect of the M132L SNP on elk PrP using in silico programs, including PolyPhen-2, PROVEAN, AMYCO and Swiss-PdbViewer. We did not identify a significant association between the M132L SNP of PRNP and susceptibility to CWD in Korean elk. The meta-analysis also did not identify a strong association between the M132L SNP of PRNP and susceptibility to CWD in quantitatively synthesized elk populations. Furthermore, we did not observe significant changes in structure, amyloid propensity or electrostatic potential based on the M132L SNP in elk PrP. To the best of our knowledge, this was the first report of an association analysis and meta-analysis in Korean elk and quantitatively synthesized elk populations, respectively.

Adaptive and powerful microbiome multivariate association analysis via feature selection

ABSTRACT The important role of human microbiome is being increasingly recognized in health and disease conditions. Since microbiome data is typically high dimensional, one popular mode of statistical association analysis for microbiome data is to pool individual microbial features into a group, and then conduct group-based multivariate association analysis. A corresponding challenge within this approach is to achieve adequate power to detect an association signal between a group of microbial features and the outcome of interest across a wide range of scenarios. Recognizing some existing methods’ susceptibility to the adverse effects of noise accumulation, we introduce the Adaptive Microbiome Association Test (AMAT), a novel and powerful tool for multivariate microbiome association analysis, which unifies both blessings of feature selection in high-dimensional inference and robustness of adaptive statistical association testing. AMAT first alleviates the burden of noise accumulation via distance correlation learning, and then conducts a data-adaptive association test under the flexible generalized linear model framework. Extensive simulation studies and real data applications demonstrate that AMAT is highly robust and often more powerful than several existing methods, while preserving the correct type I error rate. A free implementation of AMAT in R computing environment is available at https://github.com/kzb193/AMAT.

Allelic variation for alpha-Glucan Water Dikinase is associated with starch phosphate content in tetraploid potato

Key message Association analysis resulted in the identification of specific StGWD alleles causing either an increase or decrease in starch phosphate content which was verified in diploid and tetraploid potato mapping populations. Abstract Potatoes are grown for various purposes like French fries, table potatoes, crisps and for their starch. One of the most important aspects of potato starch is that it contains a high amount of phosphate ester groups which are considered to be important for providing improved functionalization after derivatization processes. Little is known about the variation in phosphate content as such in different potato varieties and thus we studied the genetic diversity for this trait. From other studies it was clear that the phosphate content is controlled by a quantitative trait locus (QTL) underlying the candidate gene α-Glucan Water Dikinase (StGWD) on chromosome 5. We performed direct amplicon sequencing of this gene by Sanger sequencing. Sequences of two StGWD amplicons from a global collection of 398 commercial cultivars and progenitor lines were used to identify 16 different haplotypes. By assigning tag SNPs to these haplotypes, each of the four alleles present in a cultivar could be deduced and linked to a phosphate content. A high value for intra-individual heterozygosity was observed (Ho = 0.765). The average number of different haplotypes per individual (Ai) was 3.1. Pedigree analysis confirmed that the haplotypes are identical-by-descent (IBD) and offered insight in the breeding history of elite potato germplasm. Haplotypes originating from introgression of wild potato accessions carrying resistance genes could be traced. Furthermore, association analysis resulted in the identification of specific StGWD alleles causing either an increase or decrease in starch phosphate content varying from 12 nmol PO4/mg starch to 38 nmol PO4/mg starch. These allele effects were verified in diploid and tetraploid mapping populations and offer possibilities to breed and select for this trait.

circTAF8 Regulates Myoblast Development and Associated Carcass Traits in Chicken

Recent studies have shown that circular RNAs (circRNAs) play important roles in skeletal muscle development. CircRNA biogenesis is dependent on the genetic context. Single-nucleotide polymorphisms in the introns flanking circRNAs may be intermediate-inducible factors between circRNA expression and phenotypic traits. Our previous study showed that circTAF8 is an abundantly and differentially expressed circRNA in leg muscle during chicken embryonic development. Here, we aimed to investigate circTAF8 function in muscle development and the association of the SNPs in the circTAF8 flanking introns with carcass traits. In this study, we observed that overexpression of circTAF8 could promote the proliferation of chicken primary myoblasts and inhibit their differentiation. In addition, the SNPs in the introns flanking the circTAF8 locus and those associated with chicken carcass traits were analyzed in 335 partridge chickens. A total of eight SNPs were found associated with carcass traits such as leg muscle weight, live weight, and half and full-bore weight. The association analysis results of haplotype combinations were consistent with the association analysis of a single SNP. These results suggest that circTAF8 plays a regulatory role in muscle development. These identified SNPs were found correlated with traits to muscle development and carcass muscle weight in chickens.

Association analysis and functional annotation of imputed sequence data within genomic regions influencing resistance to gastro-intestinal parasites detected by an LDLA approach in a nucleus flock of Sarda dairy sheep

Background Gastroinestinal nematodes (GIN) are one of the major health problem in grazing sheep. Although genetic variability of the resistance to GIN has been documented, traditional selection is hampered by the difficulty of recording phenotypes, usually fecal egg count (FEC). To identify causative mutations or markers in linkage disequilibrium (LD) to be used for selection, the detection of quantitative trait loci (QTL) for FEC based on linkage disequilibrium-linkage analysis (LDLA) was performed on 4097 ewes (from 181 sires) all genotyped with the OvineSNP50 Beadchip. Identified QTL regions (QTLR) were imputed from whole-genome sequences of 56 target animals of the population. An association analysis and a functional annotation of imputed polymorphisms in the identified QTLR were performed to pinpoint functional variants with potential impact on candidate genes identified from ontological classification or differentially expressed in previous studies. Results After clustering close significant locations, ten QTLR were defined on nine Ovis aries chromosomes (OAR) by LDLA. The ratio between the ANOVA estimators of the QTL variance and the total phenotypic variance ranged from 0.0087 to 0.0176. QTL on OAR4, 12, 19, and 20 were the most significant. The combination of association analysis and functional annotation of sequence data did not highlight any putative causative mutations. None of the most significant SNPs showed a functional effect on genes’ transcript. However, in the most significant QTLR, we identified genes that contained polymorphisms with a high or moderate impact, were differentially expressed in previous studies, contributed to enrich the most represented GO process (regulation of immune system process, defense response). Among these, the most likely candidate genes were: TNFRSF1B and SELE on OAR12, IL5RA on OAR19, IL17A, IL17F, TRIM26, TRIM38, TNFRSF21, LOC101118999, VEGFA, and TNF on OAR20. Conclusions This study performed on a large experimental population provides a list of candidate genes and polymorphisms which could be used in further validation studies. The expected advancements in the quality of the annotation of the ovine genome and the use of experimental designs based on sequence data and phenotypes from multiple breeds that show different LD extents and gametic phases may help to identify causative mutations.