Genomic prediction based on selective linkage disequilibrium pruning of low-coverage whole-genome sequence variants in a pure Duroc population.

BACKGROUND: Although the accumulation of whole-genome sequencing (WGS) data has accelerated the identification of mutations underlying complex traits, its impact on the accuracy of genomic predictions is limited. Reliable genotyping data and pre-selected beneficial loci can be used to improve prediction accuracy. Previously, we reported a low-coverage sequencing genotyping method that yielded 11.3 million highly accurate single-nucleotide polymorphisms (SNPs) in pigs. Here, we introduce a method termed selective linkage disequilibrium pruning (SLDP), which refines the set of SNPs that show a large gain during prediction of complex traits using whole-genome SNP data. RESULTS: We used the SLDP method to identify and select markers among millions of SNPs based on genome-wide association study (GWAS) prior information. We evaluated the performance of SLDP with respect to three real traits and six simulated traits with varying genetic architectures using two representative models (genomic best linear unbiased prediction and BayesR) on samples from 3579 Duroc boars. SLDP was determined by testing 180 combinations of two core parameters (GWAS P-value thresholds and linkage disequilibrium r2). The parameters for each trait were optimized in the training population by five fold cross-validation and then tested in the validation population. Similar to previous GWAS prior-based methods, the performance of SLDP was mainly affected by the genetic architecture of the traits analyzed. Specifically, SLDP performed better for traits controlled by major quantitative trait loci (QTL) or a small number of quantitative trait nucleotides (QTN). Compared with two commercial SNP chips, genotyping-by-sequencing data, and an unselected whole-genome SNP panel, the SLDP strategy led to significant improvements in prediction accuracy, which ranged from 0.84 to 3.22% for real traits controlled by major or moderate QTL and from 1.23 to 11.47% for simulated traits controlled by a small number of QTN. CONCLUSIONS: The SLDP marker selection method can be incorporated into mainstream prediction models to yield accuracy improvements for traits with a relatively simple genetic architecture, however, it has no significant advantage for traits not controlled by major QTL. The main factors that affect its performance are the genetic architecture of traits and the reliability of GWAS prior information. Our findings can facilitate the application of WGS-based genomic selection.

Influence of Grout Properties on the Tensile Performance of Rockbolts Based on Modified Cable Elements.

The grout annulus (GA) has a significant effect on the tensile performance of rockbolts in mining engineering. However, little research has been conducted to use modified cable elements to study this effect quantitatively. This paper used the modified cable elements in FLAC3D to study the effect of the GA on the tensile performance of rockbolts. The two-stage coupling law was used to simulate the behaviour of the GA. The stress had a linear relation with the slippage before the shear strength (SS). After the SS, the stress decreased exponentially. Numerical in situ roadway reinforcement cases were used to study the influence of the grout annulus on the tensile performance of rockbolts. The results showed that, when the SS of the GA increased from 3.2 MPa to 6.4 Mpa, the peak force of rockbolts increased from 247 kN to 425 kN. Moreover, when the SS of the GA increased from 3.2 Mpa to 6.4 Mpa, the distance between the position of the maximum tensile capacity and the external end decreased from 1.17 m to 0.81 m. Last, for the circular roadway, the peak force in rockbolts installed in the lateral side was 171.7 kN, which was significantly larger than the top side of 72.3 kN.

Methods to detect and characterize introgression.

Introgression, also known as introgressive hybridization, refers to the process that genetic components from the gene pool of one population transfer to the other via constant backcrossing. Introgression is widespread in nature, which plays important roles in increasing genetic diversity and improving adaptability to the environment, and in turn, influences the evolutionary progress of animals, plants and humans. Being as an important evolutionary event, researchers pay great attention to the detection of introgression, the introgression direction, the introgression timing, the pattern of introgression and so on. With the rapid development of high-throughput sequencing technologies, methods to detect and characterize introgression based on genome-wide data are continuously developed. In this review, we summarize a series of methods for introgression detection, and introduce the design principles and applications of these methods. We also discuss the maintenance and selection of gene segments after introgression. This review provides a relatively comprehensive reference for the studies on introgression.

A novel base editor SpRY-ABE8eF148A mediates efficient A-to-G base editing with a reduced off-target effect.

Adenine base editors (ABEs) can mediate two transition mutations, A-to-G and T-to-C, which are suitable for repairing G·C-to-T·A pathogenic variants, the most significant human pathogenic variant. By combining the protospacer adjacent motif (PAM)less SpRY nuclease with F148A-mutated TadA∗8e deaminase, we developed a new editor, SpRY-ABE8eF148A, in this study, which has narrowed the editing range and enhanced A-to-G editing efficiency in most sites with NR/YN PAMs. Furthermore, compared with SpRY-ABE8e, SpRY-ABE8eF148A significantly decreased the RNA off-target effect. Therefore, this engineered base editor, SpRY-ABE8eF148A, expanded the editing scope and improved the editing precision for G·C-to-T·A pathogenic variants. Besides, we established a bioinformatics tool, adenine base-repairing sgRNA database of pathogenic variant (ARDPM), to facilitate the development of precise editors.

The transmission of human mitochondrial DNA in four-generation pedigrees.

Most of the pathogenic variants in mitochondrial DNA (mtDNA) exist in a heteroplasmic state (coexistence of mutant and wild-type mtDNA). Understanding how mtDNA is transmitted is crucial for predicting mitochondrial disease risk. Previous studies were based mainly on two-generation pedigree data, which are limited by the randomness in a single transmission. In this study, we analyzed the transmission of heteroplasmies in 16 four-generation families. First, we found that 57.8% of the variants in the great grandmother were transmitted to the fourth generation. The direction and magnitude of the frequency change during transmission appeared to be random. Moreover, no consistent correlation was identified between the frequency changes among the continuous transmissions, suggesting that most variants were functionally neutral or mildly deleterious and thus not subject to strong natural selection. Additionally, we found that the frequency of one nonsynonymous variant (m.15773G>A) showed a consistent increase in one family, suggesting that this variant may confer a fitness advantage to the mitochondrion/cell. We also estimated the effective bottleneck size during transmission to be 21-71. In summary, our study demonstrates the advantages of multigeneration data for studying the transmission of mtDNA for shedding new light on the dynamics of the mutation frequency in successive generations.

Whole-genome analysis reveals the hybrid formation of Chinese indigenous DHB pig following human migration.

Hybridization is widespread in nature and is a valuable tool in domestic breeding. The DHB (DaHuaBai) pig in South China is the product of such a breeding strategy, resulting in increased body weight compared with other pigs in the surrounding area. We analyzed genomic data from 20 Chinese pig breeds and investigated the genomic architecture after breed formation of DHB. The breed showed inconsistency in genotype and body weight phenotype, in line with selection after hybridization. By quantifying introgression with a haplotype-based approach, we proposed a two-step introgression from large-sized pigs into small-sized pigs to produce DHB, consistent with the human migration events in Chinese history. Combining with gene prioritization and allele frequency analysis, we identify candidate genes that showed selection after introgression and that may affect body weight, such as IGF1R, SRC, and PCM1. Our research provides an example of a hybrid formation of domestic breeds along with human migration patterns.

Genome-wide analysis suggests multiple domestication events of Chinese local pigs.

Chinese local pigs have abundant phenotypes as a result of different cultures and habits of Chinese populations, geographic constraints and the long history of pig domestication. A comprehensive investigation of local Chinese pigs will benefit biodiversity research and future breeding practices. However, their classification and demographic history are not yet clear. We studied 91 Chinese local pigs from 14 breeds and 15 Chinese wild boars to reveal the dispersal of Chinese pigs, genetic groups and the demographic history. Based on spatial feature analyses, we believe that the geographic landscape played an important role in the dispersal of local pigs. According to genetic studies, Chinese pigs are divided into three groups where each group appears to have a distinct background. The nucleotide diversity, observed heterozygosity, runs of homozygosity and inbreeding coefficient varied among the groups and widespread migration also existed between the groups. Furthermore, demographic models have been constructed to explain the evolutionary relationship between the groups using the approximate Bayesian computation approach. These suggested that Chinese local pigs are inherited from an extinct Sus scrofa population from ~22 000 years ago. Then, the three groups diverged from ancestors ~16 000, ~11 000 and ~8700 years ago respectively. This study advances our understanding of the genetic variation and demographic history of Chinese local pigs.

Denoising method for a lidar bathymetry system based on a low-rank recovery of non-local data structures.

The lidar bathymetry system (LBS) echo is often contaminated by mixed noise, which severely affects the accuracy of measuring sea depth. The denoising algorithm based on a single echo cannot deal with the decline of the signal-to-noise ratio and impulse noise caused by sea waves and abrupt terrain changes. Therefore, we propose a new denoising method for LBS based on non-local structure extraction and the low-rank recovery model. First, the high-frequency noise is eliminated based on the multiple echo in a small neighborhood, and then the matrix is constructed based on the processing results in a larger range. Then, we make full use of the structural similarity between LBS echoes by transforming the echo denoising issues into low-rank matrix restoration to further eliminate the noise. The experimental results show that this method can effectively preserve the seafloor signal and eliminate the mixed noise.

Photo-Fenton Degradation Process of Styrene in Nitrogen-Sealed Storage Tank.

Using styrene as a proxy for VOCs, a new method was developed to remove styrene gas in nitrogen atmospheres. The effect on the styrene removal efficiency was explored by varying parameters within the continuum dynamic experimental setup, such as ferrous ion concentration, hydrogen peroxide concentration, and pH values. The by-products are quantized by a TOC analyzer. The optimal process conditions were hydrogen peroxide at 20 mmol/L, ferrous ions at 0.3 mmol/L and pH 3, resulting in an average styrene removal efficiency of 96.23%. In addition, in this study, we construct a BAS-BP neural network model with experimental data as a sample training set, which boosts the goodness-of-fit of the BP neural network and is able to tentatively predict styrene gas residuals for different front-end conditions.

Distinct traces of mixed ancestry in western commercial pig genomes following gene flow from Chinese indigenous breeds.

Studying gene flow between different livestock breeds will benefit the discovery of genes related to production traits and provide insight into human historical breeding. Chinese pigs have played an indispensable role in the breeding of Western commercial pigs. However, the differences in the timing and volume of the contribution of pigs from different Chinese regions to Western pigs are not yet apparent. In this paper, we combine the whole-genome sequencing data of 592 pigs from different studies and illustrate patterns of gene flow from Chinese pigs into Western commercial pigs. We describe introgression patterns from four distinct Chinese indigenous groups into five Western commercial groups. There were considerable differences in the number and length of the putative introgressed segments from Chinese pig groups that contributed to Western commercial pig breeds. The contribution of pigs from different Chinese geographical locations to a given western commercial breed varied more than that from a specific Chinese pig group to different Western commercial breeds, implying admixture within Europe after introgression. Within different Western commercial lines from the same breed, the introgression patterns from a given Chinese pig group seemed highly conserved, suggesting that introgression of Chinese pigs into Western commercial pig breeds mainly occurred at an early stage of breed formation. Finally, based on analyses of introgression signals, allele frequencies, and selection footprints, we identified a ∼2.65 Mb Chinese-derived haplotype under selection in Duroc pigs (CHR14: 95.68-98.33 Mb). Functional and phenotypic studies demonstrate that this PRKG1 haplotype is related to backfat and loin depth in Duroc pigs. Overall, we demonstrate that the introgression history of domestic pigs is complex and that Western commercial pigs contain distinct traces of mixed ancestry, likely derived from various Chinese pig breeds.

Local Stability of McKean-Vlasov Equations Arising from Heterogeneous Gibbs Systems Using Limit of Relative Entropies.

A family of heterogeneous mean-field systems with jumps is analyzed. These systems are constructed as a Gibbs measure on block graphs. When the total number of particles goes to infinity, the law of large numbers is shown to hold in a multi-class context, resulting in the weak convergence of the empirical vector towards the solution of a McKean-Vlasov system of equations. We then investigate the local stability of the limiting McKean-Vlasov system through the construction of a local Lyapunov function. We first compute the limit of adequately scaled relative entropy functions associated with the explicit stationary distribution of the N-particles system. Using a Laplace principle for empirical vectors, we show that the limit takes an explicit form. Then we demonstrate that this limit satisfies a descent property, which, combined with some mild assumptions shows that it is indeed a local Lyapunov function.

Genome­wide association study and genomic prediction for growth traits in yellow-plumage chicken using genotyping-by-sequencing.

BACKGROUND: Growth traits are of great importance for poultry breeding and production and have been the topic of extensive investigation, with many quantitative trait loci (QTL) detected. However, due to their complex genetic background, few causative genes have been confirmed and the underlying molecular mechanisms remain unclear, thus limiting our understanding of QTL and their potential use for the genetic improvement of poultry. Therefore, deciphering the genetic architecture is a promising avenue for optimising genomic prediction strategies and exploiting genomic information for commercial breeding. The objectives of this study were to: (1) conduct a genome-wide association study to identify key genetic factors and explore the polygenicity of chicken growth traits; (2) investigate the efficiency of genomic prediction in broilers; and (3) evaluate genomic predictions that harness genomic features. RESULTS: We identified five significant QTL, including one on chromosome 4 with major effects and four on chromosomes 1, 2, 17, and 27 with minor effects, accounting for 14.5 to 34.1% and 0.2 to 2.6% of the genomic additive genetic variance, respectively, and 23.3 to 46.7% and 0.6 to 4.5% of the observed predictive accuracy of breeding values, respectively. Further analysis showed that the QTL with minor effects collectively had a considerable influence, reflecting the polygenicity of the genetic background. The accuracy of genomic best linear unbiased predictions (BLUP) was improved by 22.0 to 70.3% compared to that of the conventional pedigree-based BLUP model. The genomic feature BLUP model further improved the observed prediction accuracy by 13.8 to 15.2% compared to the genomic BLUP model. CONCLUSIONS: A major QTL and four minor QTL were identified for growth traits; the remaining variance was due to QTL effects that were too small to be detected. The genomic BLUP and genomic feature BLUP models yielded considerably higher prediction accuracy compared to the pedigree-based BLUP model. This study revealed the polygenicity of growth traits in yellow-plumage chickens and demonstrated that the predictive ability can be greatly improved by using genomic information and related features.

Accelerated deciphering of the genetic architecture of agricultural economic traits in pigs using a low-coverage whole-genome sequencing strategy.

BACKGROUND: Uncovering the genetic architecture of economic traits in pigs is important for agricultural breeding. However, high-density haplotype reference panels are unavailable in most agricultural species, limiting accurate genotype imputation in large populations. Moreover, the infinitesimal model of quantitative traits implies that weak association signals tend to be spread across most of the genome, further complicating the genetic analysis. Hence, there is a need to develop new methods for sequencing large cohorts without large reference panels. RESULTS: We describe a Tn5-based highly accurate, cost- and time-efficient, low-coverage sequencing method to obtain 11.3 million whole-genome single-nucleotide polymorphisms in 2,869 Duroc boars at a mean depth of 0.73×. On the basis of these single-nucleotide polymorphisms, a genome-wide association study was performed, resulting in 14 quantitative trait loci (QTLs) for 7 of 21 important agricultural traits in pigs. These QTLs harbour genes, such as ABCD4 for total teat number and HMGA1 for back fat thickness, and provided a starting point for further investigation. The inheritance models of the different traits varied greatly. Most follow the minor-polygene model, but this can be attributed to different reasons, such as the shaping of genetic architecture by artificial selection for this population and sufficiently interconnected minor gene regulatory networks. CONCLUSIONS: Genome-wide association study results for 21 important agricultural traits identified 14 QTLs/genes and showed their genetic architectures, providing guidance for genetic improvement harnessing genomic features. The Tn5-based low-coverage sequencing method can be applied to large-scale genome studies for any species without a good reference panel and can be used for agricultural breeding.

Systematic Review on Local Ancestor Inference From a Mathematical and Algorithmic Perspective.

Genotypic data provide deep insights into the population history and medical genetics. The local ancestry inference (LAI) (also termed local ancestry deconvolution) method uses the hidden Markov model (HMM) to solve the mathematical problem of ancestry reconstruction based on genomic data. HMM is combined with other statistical models and machine learning techniques for particular genetic tasks in a series of computer tools. In this article, we surveyed the mathematical structure, application characteristics, historical development, and benchmark analysis of the LAI method in detail, which will help researchers better understand and further develop LAI methods. Firstly, we extensively explore the mathematical structure of each model and its characteristic applications. Next, we use bibliometrics to show detailed model application fields and list articles to elaborate on the historical development. LAI publications had experienced a peak period during 2006-2016 and had kept on moving in the following years. The efficiency, accuracy, and stability of the existing models were evaluated by the benchmark. We find that phased data had higher accuracy in comparison with unphased data. We summarize these models with their distinct advantages and disadvantages. The Loter model uses dynamic programming to obtain a globally optimal solution with its parameter-free advantage. Aligned bases can be used directly in the Seqmix model if the genotype is hard to call. This research may help model developers to realize current challenges, develop more advanced models, and enable scholars to select appropriate models according to given populations and datasets.

Exploring epigenetic biomarkers of universal specificities and commonalities among pan-cancer cohorts in The Cancer Genome Atlas.

Aim: To explore the mechanism of cancer by employing a comprehensive analysis of DNA methylation patterns and variations among pan-cancer cohorts. Materials & methods: This research focused on the discovery of universally specific or common biomarkers by mathematical statistics and machine learning methods in The Cancer Genome Atlas. Results: We found 138 differently methylated CpGs (DMCs) with a common methylation trend and eight common differently methylated regions in different cancer cohorts. Additionally, we found 99 DMCs to distinguish 32 different cancer cohorts in random forest analysis because of the specificity mechanism, but each DMC still had high instability. Conclusion: Our results could facilitate the development of biomarkers that are universally specific and common features across pan-cancer cohorts.

Weyl Prior and Bayesian Statistics.

When using Bayesian inference, one needs to choose a prior distribution for parameters. The well-known Jeffreys prior is based on the Riemann metric tensor on a statistical manifold. Takeuchi and Amari defined the α -parallel prior, which generalized the Jeffreys prior by exploiting a higher-order geometric object, known as a Chentsov-Amari tensor. In this paper, we propose a new prior based on the Weyl structure on a statistical manifold. It turns out that our prior is a special case of the α -parallel prior with the parameter α equaling - n , where n is the dimension of the underlying statistical manifold and the minus sign is a result of conventions used in the definition of α -connections. This makes the choice for the parameter α more canonical. We calculated the Weyl prior for univariate Gaussian and multivariate Gaussian distribution. The Weyl prior of the univariate Gaussian turns out to be the uniform prior.

Genetic Dissection of Growth Traits in a Unique Chicken Advanced Intercross Line.

The advanced intercross line (AIL) that is created by successive generations of pseudo-random mating after the F2 generation is a valuable resource, especially in agricultural livestock and poultry species, because it improves the precision of quantitative trait loci (QTL) mapping compared with traditional association populations by introducing more recombination events. The growth traits of broilers have significant economic value in the chicken industry, and many QTLs affecting growth traits have been identified, especially on chromosomes 1, 4, and 27, albeit with large confidence intervals that potentially contain dozens of genes. To promote a better understanding of the underlying genetic architecture of growth trait differences, specifically body weight and bone development, in this study, we report a nine-generation AIL derived from two divergent outbred lines: High Quality chicken Line A (HQLA) and Huiyang Bearded (HB) chicken. We evaluate the genetic architecture of the F0, F2, F8, and F9 generations of AIL and demonstrate that the population of the F9 generation sufficiently randomized the founder genomes and has the characteristics of rapid linkage disequilibrium decay, limited allele frequency decline, and abundant nucleotide diversity. This AIL yielded a much narrower QTL than the F2 generations, especially the QTL on chromosome 27, which was reduced to 120 Kb. An ancestral haplotype association analysis showed that most of the dominant haplotypes are inherited from HQLA but with fluctuation of the effects between them. We highlight the important role of four candidate genes (PHOSPHO1, IGF2BP1, ZNF652, and GIP) in bone growth. We also retrieved a missing QTL from AIL on chromosome 4 by identifying the founder selection signatures, which are explained by the loss of association power that results from rare alleles. Our study provides a reasonable resource for detecting quantitative trait genes and tracking ancestor history and will facilitate our understanding of the genetic mechanisms underlying chicken bone growth.

The Core and Distinction of the Gut Microbiota in Chinese Populations across Geography and Ethnicity.

The diversity of the human gut microbiota constitutes a fundamental health indicator of different populations. The relative importance of geographical location and ethnicity on the gut microbiota, however, has not been previously addressed. Due to unique ethnic distributions across China, we recruited distinct minority ethnic groups, including Han populations, in each of the seven cities that were explored in this study. We investigated the gut microbiota of 394 healthy subjects (14 groups) from these seven different cities using 16S rRNA sequencing. Our results indicated that both geographical location and ethnicity were major factors. However, geographical location exhibited greater influence than ethnicity on both the composition and diversity of the gut microbiota. In addition, a total of 15 shared biomarkers at the genus level were identified in three distinct locations, including seven in Inner Mongolia, seven in Xinjiang and one in Gansu. Furthermore, 65 unique biomarkers were found in 14 population groups, which indicated specific communities in different populations. Based on the gut microbiota species, two main enterotypes-namely Prevotella (ETP) and Bacteroides (ETB), which consist of Prevotella and Bacteroides as the core bacterial genus, were observed in Chinese populations. Our unique experimental design using the same ethnic group-Han, as a control in different locations, enables delineating the importance of geographical location and ethnicity on the gut microbiota, and provides the fundamental characteristics of gut microbiota diversity in Chinese populations.