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Introduction: Identifying genomic regions under selection is the most challenging issue for improving important traits in animals. Few studies have focused on identifying genomic regions under selection in sheep. The aim of this study was to identify selective sweeps and to explore the relationship between these and quantitative trait loci (QTL) in both domestic and wild sheep species using single nucleotide polymorphism markers (SNPs). Methods: Genomic data were obtained from the NextGen project, which included genotyping 20 domestic and 14 wild sheep using the Illumina Ovine SNP50K BeadChip. The XP-EHH, iHS, and RSB methods were employed to detect signatures of positive selection. Results: The results of the iHS method indicated 405 and 275 selective sweeps in domestic and wild sheep, respectively. Additionally, RSB and XP-EHH analyses revealed approximately 398 and 479 selective sweeps in domestic and wild sheep, respectively. Some of the genes associated with important QTL traits in domestic sheep include ADGRB3, CADM1, CAPN2, GALNT10, MTR, RELN , and USP25 , while in wild sheep, the relevant genes include ACAN, ACO1, GADL1, MGST3 , and PRDM16. Selective sweeps identified in domestic sheep were associated with body weight, muscle weight, milk protein percentage, and milk yield. In contrast, selective sweeps found in wild sheep were linked to average daily gain, bone weight, carcass fat percentage, and dressing percentage. Discussion: These results indicate that selection by humans and the environment have largely progressed in harmony, highlighting the importance of both economic and environmental traits for survival. Additionally, the identification of potential candidate genes associated with economic traits and genomic regions that have experienced selection can be utilized in sheep breeding programs. However, due to the incomplete information regarding the functional annotation of genes in sheep and the limited sample size, further research with a larger sample group is essential to gain a deeper understanding of the candidate genes linked to economic traits in both domestic and wild sheep. Advancing knowledge in this area can significantly enhance the effectiveness of breeding strategies. The quantitative trait loci identified in this study have the potential to be incorporated into breeding plans for both domestic and wild sheep. [ABSTRACT FROM AUTHOR]

Host–pathogen coevolution is defined as the reciprocal evolutionary changes in both species due to genotype × genotype (G×G) interactions at the genetic level determining the outcome and severity of infection. While co-analyses of hosts and pathogen genomes (co-genome-wide association studies) allow us to pinpoint the interacting genes, these do not reveal which host genotype(s) is/are resistant to which pathogen genotype(s). The knowledge of this so-called infection matrix is important for agriculture and medicine. Building on established theories of host–pathogen interactions, we here derive four novel indices capturing the characteristics of the infection matrix. These indices can be computed from full genome polymorphism data of randomly sampled uninfected hosts, as well as infected hosts and their pathogen strains. We use these indices in an approximate Bayesian computation method to pinpoint loci with relevant G×G interactions and to infer their underlying interaction matrix. In a combined single nucleotide polymorphism dataset of 451 European humans and their infecting hepatitis C virus (HCV) strains and 503 uninfected individuals, we reveal a new human candidate gene for resistance to HCV and new virus mutations matching human genes. For two groups of significant human–HCV (G×G) associations, we infer a gene-for-gene infection matrix, which is commonly assumed to be typical of plant–pathogen interactions. Our model-based inference framework bridges theoretical models of G×G interactions with host and pathogen genomic data. It, therefore, paves the way for understanding the evolution of key G×G interactions underpinning HCV adaptation to the European human population after a recent expansion. [ABSTRACT FROM AUTHOR]

Xiangdong black goats, indigenous to Hunan Province, China, exhibit remarkable adaptation to challenging environments and possess distinct black coat coloration alongside exceptional meat quality attributes. Despite their significance, comprehensive genomic investigations of this breed have been notably lacking. This study involved a comprehensive examination of population structure, genomic diversity, and regions of selection in Xiangdong black goats utilizing whole-genome sequencing data from 20 samples of this breed and 139 published samples from six other Chinese goat breeds. Our genomic analysis revealed a total of 19,133,125 biallelic single nucleotide polymorphisms (SNPs) within the Xiangdong black goat genome, primarily located in intergenic and intronic regions. Population structure analysis indicated that, compared with Jintang, Guizhou and Chengdu goats, Xiangdong black goats exhibit a reduced level of genetic differentiation but exhibit relatively greater divergence from Jining goats. An examination of genetic diversity within Xiangdong black goats revealed a moderate level of diversity, minimal inbreeding, and a substantial effective population size, which are more reflective of random mating patterns than other Chinese goat breeds. Additionally, we applied four distinct selective sweep methods, namely, the composite likelihood ratio (CLR), fixation index (FST), θπ ratio and cross-population extended haplotype homozygosity (XP-EHH), to identify genomic regions under positive selection and genes associated with fundamental biological processes. The most prominent candidate genes identified in this study are involved in crucial aspects of goat life, including reproduction (CCSER1, PDGFRB, IFT88, LRP1B, STAG1, and SDCCAG8), immunity (DOCK8, IL1R1, and IL7), lactation and milk production (SPP1, TLL1, and ERBB4), hair growth (CHRM2, SDC1, ITCH, and FGF12), and thermoregulation (PDE10A). In summary, our research contributes valuable insights into the genomic characteristics of the Xiangdong black goat, underscoring its importance and utility in future breeding programs and conservation initiatives within the field of animal breeding and genetics. [ABSTRACT FROM AUTHOR]

Introduction: Body measurement traits are integral in cattle production, serving as pivotal criteria for breeding selection. Wenshan cattle, a local breed in China’s Yunnan province, exhibit remarkable genetic diversity. However, the molecular mechanisms regulating body measurement traits in Wenshan cattle remain unexplored. Methods: In this study, we performed a genome-wide association method to identify genetic architecture for body height body length hip height back height (BAH), waist height and ischial tuberosity height using the Bovine 50 K single nucleotide polymorphism Array in 1060 Wenshan cattles. Results: This analysis reveals 8 significant SNPs identified through the mixed linear model (MLM), with 6 SNPs are associated with multiple traits and 4 SNPs are associated with all 6 traits. Furthermore, we pinpoint 21 candidate genes located in proximity to or within these significant SNPs. Among them, Scarb1, acetoacetyl-CoA synthetase and HIVEP3 were implicated in bone formation and rarely encountered in livestock body measurement traits, emerge as potential candidate genes regulating body measurement traits in Wenshan cattle. Discussion: This investigation provides valuable insights into the genetic mechanisms underpinning body measurement traits in this unique cattle breed, paving the way for further research in this domain. [ABSTRACT FROM AUTHOR]

Introduction: Several polymorphisms altering the NAT2 activity have already been identified. The geographical distribution of NAT2 variants has been extensively studied and has been demonstrated to vary significantly among different ethnic population. Here, we describe the genetic variability of human N-acetyltransferase 2 (NAT2) gene and the predominant genotype-deduced acetylation profiles of Brazilians. Methods: A total of 964 individuals, from five geographical different regions, were genotyped for NAT2 by sequencing the entire coding exon. Results: Twenty-three previously described NAT2 single nucleotide polymorphisms (SNPs) were identified, including the seven most common ones globally (c.191G>A, c.282C>T, c.341T>C, c.481C>T, c.590G>A, c.803A>G and c.857G>A). The main allelic groups were NAT2*5 (36%) and NAT2*6 (18.2%), followed to the reference allele NAT2*4 (20.4%). Combined into genotypes, the most prevalent allelic groups were NAT2*5/*5 (14.6%), NAT2*5/*6 (11.9%) and NAT2*6/*6 (6.2%). The genotype deduced NAT2 slow acetylation phenotype was predominant but showed significant variability between geographical regions. The prevalence of slow acetylation phenotype was higher in the Northeast, North and Midwest (51.3%, 45.5% and 41.5%, respectively) of the country. In the Southeast, the intermediate acetylation phenotype was the most prevalent (40.3%) and, in the South, the prevalence of rapid acetylation phenotype was significantly higher (36.7%), when compared to other Brazilian states (p < 0.0001). Comparison of the predicted acetylation profile among regions showed homogeneity among the North and Northeast but was significantly different when compared to the Southeast (p = 0.0396). The Southern region was significantly different from all other regions (p < 0.0001). Discussion: This study contributes not only to current knowledge of the NAT2 population genetic diversity in different geographical regions of Brazil, but also to the reconstruction of a more accurate phenotypic picture of NAT2 acetylator profiles in those regions. [ABSTRACT FROM AUTHOR]

In modern plant breeding, genomic selection is becoming the gold standard to select superior genotypes in large breeding populations that are only partially phenotyped. Many breeding programs commonly rely on single-nucleotide polymorphism (SNP) markers to capture genome-wide data for selection candidates. For this purpose, SNP arrays with moderate to high marker density represent a robust and cost-effective tool to generate reproducible, easy-to- handle, high-throughput genotype data from large-scale breeding populations. However, SNP arrays are prone to technical errors that lead to failed allele calls. To overcome this problem, failed calls are often imputed, based on the assumption that failed SNP calls are purely technical. However, this ignores the biological causes for failed calls—for example: deletions—and there is increasing evidence that gene presence–absence and other kinds of genome structural variants can play a role in phenotypic expression. Because deletions are frequently not in linkage disequilibrium with their flanking SNPs, permutation of missing SNP calls can potentially obscure valuable marker–trait associations. In this study, we analyze published datasets for canola and maize using four parametric and two machine learning models and demonstrate that failed allele calls in genomic prediction are highly predictive for important agronomic traits. We present two statistical pipelines, based on population structure and linkage disequilibrium, that enable the filtering of failed SNP calls that are likely caused by biological reasons. For the population and trait examined, prediction accuracy based on these filtered failed allele calls was competitive to standard SNP-based prediction, underlying the potential value of missing data in genomic prediction approaches. The combination of SNPs with all failed allele calls or the filtered allele calls did not outperform predictions with only SNP-based prediction due to redundancy in genomic relationship estimates. [ABSTRACT FROM AUTHOR]

Following the recent domestication process of the European rabbit (Oryctolagus cuniculus), many different breeds and lines, distinguished primarily by exterior traits such as coat colour, fur structure and body size and shape, have been constituted. In this study, we genotyped, with a high‐density single‐nucleotide polymorphism panel, a total of 645 rabbits from 10 fancy breeds (Belgian Hare, Champagne d'Argent, Checkered Giant, Coloured Dwarf, Dwarf Lop, Ermine, Giant Grey, Giant White, Rex and Rhinelander) and three meat breeds (Italian White, Italian Spotted and Italian Silver). ADMIXTURE analysis indicated that breeds with similar phenotypic traits (e.g. coat colour and body size) shared common ancestries. Signatures of selection using two haplotype‐based approaches (iHS and XP‐EHH), combined with the results obtained with other methods previously reported that we applied to the same breeds, we identified a total of 5079 independent genomic regions with some signatures of selection, covering about 1777 Mb of the rabbit genome. These regions consistently encompassed many genes involved in pigmentation processes (ASIP, EDNRA, EDNRB, KIT, KITLG, MITF, OCA2, TYR and TYRP1), coat structure (LIPH) and body size, including two major genes (LCORL and HMGA2) among many others. This study revealed novel genomic regions under signatures of selection and further demonstrated that population structures and signatures of selection, left into the genome of these rabbit breeds, may contribute to understanding the genetic events that led to their constitution and the complex genetic mechanisms determining the broad phenotypic variability present in these untapped rabbit genetic resources. [ABSTRACT FROM AUTHOR]

About three decades of breeding and selection in the Valle del Belìce sheep are expected to have left several genomic footprints related to milk production traits. In this study, we have assembled a dataset with 451 individuals of the Valle del Belìce sheep breed: 184 animals that underwent directional selection for milk production and 267 unselected animals, genotyped for 40,660 single‐nucleotide polymorphisms (SNPs). Three different statistical approaches, both within (iHS and ROH) and between (Rsb) groups, were used to identify genomic regions potentially under selection. Population structure analyses separated all individuals according to their belonging to the two groups. A total of four genomic regions on two chromosomes were jointly identified by at least two statistical approaches. Several candidate genes for milk production were identified, corroborating the polygenic nature of this trait and which may provide clues to potential new selection targets. We also found candidate genes for growth and reproductive traits. Overall, the identified genes may explain the effect of selection to improve the performances related to milk production traits in the breed. Further studies using high‐density array data, would be particularly relevant to refine and validate these results. [ABSTRACT FROM AUTHOR]

Background: The identification of genomic regions affected by selection is one of the most important goals in population genetics. If temporal data are available, allele frequency changes at SNP positions are often used for this purpose. Here we provide a new testing approach that uses haplotype frequencies instead of allele frequencies. Results: Using simulated data, we show that compared to SNP based test, our approach has higher power, especially when the number of candidate haplotypes is small or moderate. To improve power when the number of haplotypes is large, we investigate methods to combine them with a moderate number of haplotype subsets. Haplotype frequencies can often be recovered with less noise than SNP frequencies, especially under pool sequencing, giving our test an additional advantage. Furthermore, spurious outlier SNPs may lead to false positives, a problem usually not encountered when working with haplotypes. Post hoc tests for the number of selected haplotypes and for differences between their selection coefficients are also provided for a better understanding of the underlying selection dynamics. An application on a real data set further illustrates the performance benefits. Conclusions: Due to less multiple testing correction and noise reduction, haplotype based testing is able to outperform SNP based tests in terms of power in most scenarios. [ABSTRACT FROM AUTHOR]

Panels of informative biallelic single nucleotide polymorphisms (SNPs) have been proposed to be an economical method to fast-track the population genetic analysis of Plasmodium falciparum in malaria-endemic areas. Whilst used successfully in low-transmission areas where infections are monoclonal and highly related, we present the first study to evaluate the performance of these 24- and 96-SNP molecular barcodes in African countries, characterised by moderate-to-high transmission, where multiclonal infections are prevalent. For SNP barcodes it is generally recommended that the SNPs chosen i) are biallelic, ii) have a minor allele frequency greater than 0.10, and iii) are independently segregating, to minimise bias in the analysis of genetic diversity and population structure. Further, to be standardised and used in many population genetic studies, these barcodes should maintain characteristics i) to iii) across various iv) geographies and v) time points. Using haplotypes generated from the MalariaGEN P. falciparum Community Project version six database, we investigated the ability of these two barcodes to fulfil these criteria in moderate-to-high transmission African populations in 25 sites across 10 countries. Predominantly clinical infections were analysed, with 52.3% found to be multiclonal, generating high proportions of mixed-allele calls (MACs) per isolate thereby impeding haplotype construction. Of the 24- and 96-SNPs, loci were removed if they were not biallelic and had low minor allele frequencies in all study populations, resulting in 20- and 75-SNP barcodes respectively for downstream population genetics analysis. Both SNP barcodes had low expected heterozygosity estimates in these African settings and consequently biased analyses of similarity. Both minor and major allele frequencies were temporally unstable. These SNP barcodes were also shown to identify weak genetic differentiation across large geographic distances based on Mantel Test and DAPC. These results demonstrate that these SNP barcodes are vulnerable to ascertainment bias and as such cannot be used as a standardised approach for malaria surveillance in moderate-to-high transmission areas in Africa, where the greatest genomic diversity of P. falciparum exists at local, regional and country levels. [ABSTRACT FROM AUTHOR]

Giant kelp, Macrocystis pyrifera , exists as distinct morphological variants—or "ecomorphs"—in different populations, yet the mechanism for this variation is uncertain, and environmental drivers for either adaptive or plastic phenotypes have not been identified. The ecomorphs Macrocystis "pyrifera" and M. "integrifolia " are distributed throughout temperate waters of North and South America with almost no geographic overlap and exhibit an incongruous, non-mirrored, distribution across the equator. This study evaluates the degree of genetic divergence between M. "pyrifera" and M. "integrifolia" across 18 populations in Chile and California using whole-genome sequencing and single-nucleotide polymorphism markers. Our results based on a principal component analysis, admixture clustering by genetic similarity, and phylogenetic inference demonstrate that M. "pyrifera" and M. "integrifolia" are genetically distinguishable. Analyses reveal separation by Northern and Southern Hemispheres and between morphs within hemispheres, suggesting that the convergent "integrifolia" morphology arose separately in each hemisphere. This is the first study to use whole-genome sequencing to understand genetic divergence in giant kelp ecomorphs, identifying 83 potential genes under selection and providing novel insights about Macrocystis evolution that were not evident with previous genetic techniques. Future studies are needed to uncover the environmental forces driving local adaptation and presumed convergent evolution of these morphs. [ABSTRACT FROM AUTHOR]

North China and South Siberia, populated by Altaic‐ and Sino‐Tibetan‐speaking populations, possess extensive ethnolinguistic diversity and serve as the crossroads for the initial peopling of America and western–eastern transcontinental communication. However, the population genetic structure and admixture history of northern East Asians remain poorly understood due to a lack of genome‐wide data, especially for Mongolic‐speaking people in China. We genotyped genome‐wide single nucleotide polymorphisms for 510 individuals from 38 Mongolic, Tungusic, and Sinitic‐speaking populations. We first explored the shared alleles and haplotypes within the studied groups. We then merged with 3508 published modern and ancient Eurasian individuals to reconstruct the deep evolutionary and natural selection history of northern East Asians. We identified genetic substructures within Altaic‐speaking populations: Western Turkic people harbored more western Eurasian‐related ancestry; Northern Mongolic people in Siberia and eastern Tungusic people in Amur River Basin (ARB) possessed a majority of Neolithic ARB related ancestry; Southern Mongolic people in China possessed apparent genetic influence from Neolithic Yellow River Basin (YRB) farmers. Additionally, we found the differentiated admixture history between western and eastern Mongolians and geographically close Northeast Hans: the former received a genetic impact from western Eurasians, and the latter retained the primary Neolithic YRB and ARB ancestry. Moreover, we demonstrated that Kalmyk people from the northern Caucasus Mountains possessed a strong genetic affinity with Neolithic Mongolian Plateau (MP) people, supporting the hypothesis of their eastern Eurasian origin and long‐distance migration history. We also illuminated that historical pastoral empires in the MP contributed considerably to the gene pool of northern Mongolic people but rarely to the southern ones. We finally found natural selection signatures in Mongolians associated with alcohol metabolism. Our results demonstrated that the Neolithic ancestral sources from the MP or ARB played an important role in spreading Altaic populations and languages. The observed multisources of genetic diversity contributed significantly to the extensive ethnolinguistic diversity in northern East Asia. [ABSTRACT FROM AUTHOR]

Combining SNP p-values from GWAS summary data is a promising strategy for detecting novel genetic factors. Existing statistical methods for the p-valuebased SNP-set testing confront two challenges. First, the statistical power of different methods depends on unknown patterns of genetic effects that could drastically vary over different SNP sets. Second, they do not identify which SNPs primarily contribute to the global association of the whole set. We propose a new signal-adaptive analysis pipeline to address these challenges using the omnibus thresholding Fisher's method (oTFisher). The oTFisher remains robustly powerful over various patterns of genetic effects. Its adaptive thresholding can be applied to estimate important SNPs contributing to the overall significance of the given SNP set. We develop efficient calculation algorithms to control the type I error rate, which accounts for the linkage disequilibrium among SNPs. Extensive simulations show that the oTFisher has robustly high power and provides a higher balanced accuracy in screening SNPs than the traditional Bonferroni and FDR procedures. We applied the oTFisher to study the genetic association of genes and haplotype blocks of the bone density-related traits using the summary data of the Genetic Factors for Osteoporosis Consortium. The oTFisher identified more novel and literaturereported genetic factors than existing p-value combination methods. Relevant computation has been implemented into the R package TFisher to support similar data analysis. [ABSTRACT FROM AUTHOR]

Bitter taste receptors (TAS2Rs) are noted for their role in perception, and mounting evidence suggests that they mediate responses to compounds entering airways, gut, and other tissues. The importance of these roles suggests that TAS2Rs have been under pressure from natural selection. To determine the extent of variation in TAS2Rs on a global scale and its implications for human evolution and behavior, we analyzed patterns of diversity in the complete 25 gene repertoire of human TAS2Rs in ~2,500 subjects representing worldwide populations. Across the TAS2R family as a whole, we observed 721 single nucleotide polymorphisms (SNPs) including 494 nonsynonymous SNPs along with 40 indels and gained and lost start and stop codons. In addition, computational predictions identified 169 variants particularly likely to affect receptor function, making them candidate sources of phenotypic variation. Diversity levels ranged widely among loci, with the number of segregating sites ranging from 17 to 41 with a mean of 32 among genes and per nucleotide heterozygosity (π) ranging from 0.02% to 0.36% with a mean of 0.12%. FST ranged from 0.01 to 0.26 with a mean of 0.13, pointing to modest differentiation among populations. Comparisons of observed π and FST values with their genome wide distributions revealed that most fell between the 5th and 95th percentiles and were thus consistent with expectations. Further, tests for natural selection using Tajima's D statistic revealed only two loci departing from expectations given D's genome wide distribution. These patterns are consistent with an overall relaxation of selective pressure on TAS2Rs in the course of recent human evolution.KEYWORDS taste, genetics, perception, selection, evolution. [ABSTRACT FROM AUTHOR]

Diagnostic approaches capable of ultrasensitive pathogen detection from low-volume clinical samples, running without any sophisticated instrument and laboratory setup, are easily field-deployable, inexpensive, and rapid, and are considered ideal for monitoring disease progression and surveillance. However, standard pathogen detection methods, including culture and microscopic observation, antibody-based serologic tests, and primarily polymerase chain reaction (PCR)-oriented nucleic acid screening techniques, have shortcomings that limit their widespread use in responding to outbreaks and regular diagnosis, especially in remote resource-limited settings (RLSs). Recently, clustered regularly interspaced short palindromic repeats (CRISPR)-based programmable technology has emerged to challenge the unmet criteria of conventional methods. It consists of CRISPR-associated proteins (Cas) capable of targeting virtually any specific RNA or DNA genome based on the guide RNA (gRNA) sequence. Furthermore, the discovery of programmable trans-cleavage Cas proteins like Cas12a and Cas13 that can collaterally damage reporter-containing single-stranded DNA or RNA upon formation of target Cas-gRNA complex has strengthened this technology with enhanced sensitivity. Current advances, including automated multiplexing, ultrasensitive single nucleotide polymorphism (SNP)-based screening, inexpensive paper-based lateral flow readouts, and ease of use in remote global settings, have attracted the scientific community to introduce this technology in nucleic acid-based precise detection of bacterial and viral pathogens at the point of care (POC). This review highlights CRISPR-Cas-based molecular technologies in diagnosing several tropical diseases, namely malaria, zika, chikungunya, human immunodeficiency virus and acquired immunodeficiency syndrome (HIV-AIDS), tuberculosis (TB), and rabies. [ABSTRACT FROM AUTHOR]

In the last 300 thousand years, the genus Chlorocebus expanded from equatorial Africa into the southernmost latitudes of the continent, where colder climate was a probable driver of natural selection. We investigated population-level genetic variation in the mitochondrial uncoupling protein 1 (UCP1) gene region—implicated in non-shivering thermogenesis (NST)—in 73 wild savannah monkeys from three taxa representing this southern expansion (Chlorocebus pygerythrus hilgerti, Chlorocebus cynosuros and Chlorocebus pygerythrus pygerythrus) ranging from Kenya to South Africa. We found 17 single nucleotide polymorphisms with extended haplotype homozygosity consistent with positive selective sweeps, 10 of which show no significant linkage disequilibrium with each other. Phylogenetic generalized least-squares modelling with ecological covariates suggest that most derived allele frequencies are significantly associated with solar irradiance and winter precipitation, rather than overall low temperatures. This selection and association with irradiance is demonstrated by a relatively isolated population in the southern coastal belt of South Africa. We suggest that sunbathing behaviours common to savannah monkeys, in combination with the strength of solar irradiance, may mediate adaptations to thermal stress via NST among savannah monkeys. The variants we discovered all lie in non-coding regions, some with previously documented regulatory functions, calling for further validation and research. [ABSTRACT FROM AUTHOR]

Type 2 diabetes mellitus (T2DM) is a complex disease that has risen in global prevalence over recent decades, resulting in concomitant and enormous socio-economic impacts. In addition to the well-documented risk factors of obesity, poor dietary habits and sedentary lifestyles, genetic background plays a key role in the aetiopathogenesis of diabetes and the development of associated micro- and macrovascular complications. Recent advances in genomic research, notably next-generation sequencing and genome- wide association studies, have greatly improved the efficiency with which genetic backgrounds to complex diseases are analysed. To date, several hundred single-nucleotide polymorphisms have been associated with T2DM or its complications. Given the polygenic background to T2DM (and numerous other complex diseases), the degree of genetic predisposition can be treated as a “continuous trait” quantified by a genetic risk score. Focusing mainly on the Central European population, this review summarizes recent state-of-the-art methods that have enabled us to better determine the genetic architecture of T2DM and the utility of genetic risk scores in disease prediction. [ABSTRACT FROM AUTHOR]

Frost is an abiotic stress factor that threatens plant development and crop productivity not only in cold regions but also in temperate zones. Roots play an important role in plant growth during frost stress. Therefore, variation in root characteristics could be studied to improve frost tolerance in winter faba bean. The present study aimed to identify the genomic regions that control frost tolerance in a winter faba bean population by focusing on root-related traits. A set of 185 genotypes were tested for frost tolerance under artificial frost growth conditions at -16°C, -18°C, and -19°C in a growth chamber. Frost stress reduced the root-related parameters in all genotypes, with a wide variation among genotypes. A genome-wide association study identified nine novel single-nucleotide polymorphisms that are associated with the root-related traits. The most frost-tolerant genotypes were identified; two genotypes, S&lowbar;028 and S&lowbar;220, exhibited remarkable performance under frost stress. Moreover, they harbored all four of the alleles favorable for frost tolerance. Remarkably, two markers showed genetic pleiotropic effects with positive allele effects on root fresh matter and root dry matter. Thus, both genotypes can be implemented in a breeding program to provide the alleles for healthier roots under frost conditions to develop more frost-tolerant varieties, and the two markers can be used to screen large collections to select for frost tolerance. These results may provide novel insights for improving frost tolerance in faba beans and in other legume crops. [ABSTRACT FROM AUTHOR]

Highly pathogenic coronaviruses, including SARS‐CoV‐2, SARS‐CoV and MERS‐CoV, are thought to be transmitted from bats to humans, but the viral genetic signatures that contribute to bat‐to‐human transmission remain largely obscure. In this study, we identified an identical ribosomal frameshift motif among the three bat–human pairs of viruses and strong purifying selection after jumping from bats to humans. This represents genetic signatures of coronaviruses that are related to bat‐to‐human transmission. To further trace the early human‐to‐human transmission of SARS‐CoV‐2 in North America, a geographically stratified genome‐wide association study (North American isolates and the remaining isolates) and a retrospective study were conducted. We determined that the single nucleotide polymorphisms (SNPs) 1,059.C > T and 25,563.G > T were significantly associated with approximately half of the North American SARS‐CoV‐2 isolates that accumulated largely during March 2020. Retrospectively tracing isolates with these two SNPs was used to reconstruct the early, reliable transmission history of North American SARS‐CoV‐2, and European isolates (February 26, 2020) showed transmission 3 days earlier than North American isolates and 17 days earlier than Asian isolates. Collectively, we identified the genetic signatures of the three pairs of coronaviruses and reconstructed an early transmission history of North American SARS‐CoV‐2. We envision that these genetic signatures are possibly diagnosable and predic markers for public health surveillance. [ABSTRACT FROM AUTHOR]

Multiple presynaptic and postsynaptic targets have been identified for the reversible neurophysiological effects of general anesthetics on synaptic transmission and neuronal excitability. However, the synaptic mechanisms involved in persistent depression of synaptic transmission resulting in more prolonged neurological dysfunction following anesthesia are less clear. Here, we show that brain-derived neurotrophic factor (BDNF), a growth factor implicated in synaptic plasticity and dysfunction, enhances glutamate synaptic vesicle exocytosis, and that attenuation of vesicular BDNF release by isoflurane contributes to transient depression of excitatory synaptic transmission in mice. This reduction in synaptic vesicle exocytosis by isoflurane was acutely irreversible in neurons that release less endogenous BDNF due to a polymorphism (BDNF Val66Met; rs6265) compared to neurons from wild-type mice. These effects were prevented by exogenous application of BDNF. Our findings identify a role for a common human BDNF single nucleotide polymorphism in persistent changes of synaptic function following isoflurane exposure. These short-term persistent alterations in excitatory synaptic transmission indicate a role for human genetic variation in anesthetic effects on synaptic plasticity and neurocognitive function. [ABSTRACT FROM AUTHOR]

Climate change is a major influencing factor in beef production. The greenhouse gases produced from livestock production systems contribute to the overall greenhouse gas emissions. The aim of this study was to identify selection signatures within and between Nguni and Bonsmara cattle in relation to production and adaptation. For this purpose, genomic 150 K single nucleotide polymorphism data from Nguni (n = 231) and Bonsmara (n = 252) cattle in South Africa were used. Extended haplotype homozygosity (EHH) based analysis was executed within each population using integrated haplotype score (iHS). The R package rehh was used for detecting selection signatures across the two populations with cross population EHH (XP-EHH). Total of 121 regions of selection signatures were detected (p < 0.0001) in the Bonsmara and Nguni populations. Several genes relating to DNA methylation, heat stress, feed efficiency and nitrogen metabolism were detected within and between each population. These regions also included QTLs associated with residual feed intake, residual gain, carcass weight, stature and body weight in the Bonsmara, while QTLs associated with conception rate, shear force, tenderness score, juiciness, temperament, heat tolerance, feed efficiency and age at puberty were identified in Nguni. Based on the results of the study it is recommended that the Nguni and Bonsmara be utilized in crossbreeding programs as they have beneficial traits that may allow them to perform better in the presence of climate change. Results of this study coincide with Nguni and Bonsmara breed characteristics and performance, and furthermore support informative crossbreeding programs to enhance livestock productivity in South Africa. [ABSTRACT FROM AUTHOR]

Artificial and natural selection in livestock is expected to leave unique footprints on their genomes. Goat breeds in Kenya have evolved for survival, breeding, and production in various harsh ecological areas, and their genomes are likely to have acquired unique alleles for adaptation to such diverse production environments and other traits of economic importance. To investigate signals of selection for some selected goat breeds in Kenya, Alpine (n = 29), Galla (n = 12), Saanen (n = 24), and Toggenburg (n = 31) were considered. A total of 53,347 single-nucleotide polymorphisms (SNPs) generated using the Illumina GoatSNP50 BeadChip were analyzed. After quality control, 47,663 autosomal single-nucleotide polymorphisms remained for downstream analyses. Several complementary approaches were applied for the following analyses: integrated Haplotype Score (iHS), cross-population-extended haplotype homozygosity (XP-EHH), hapFLK, and FLK. A total of 404 top genomic regions were identified across all the four breeds, based on the four complementary analyses. Out of the 16 identified putative selection signature regions by the intersection of multiple-selective signal analyses, most of the putative regions were found to overlap significantly with the iHS and XP-EHH analyses on chromosomes 3, 4, 10, 15, 22, and 26. These regions were enriched with some genes involved in pathways associated directly or indirectly with environmental adaptation regulating immune responses (e.g., HYAL1 and HYAL3) , milk production (e.g., LEPR and PDE4B), and adaptability (e.g., MST1 and PCK). The results revealed few intersect between breeds in genomic selection signature regions. In general, this did not present the typical classic selection signatures as predicted due to the complex nature of the traits. The results support that some various selection pressures (e.g., environmental challenges, artificial selection, and genome admixture challenges) have molded the genome of goat breeds in Kenya. Therefore, the research provides new knowledge on the conservation and utilization of these goat genetic resources in Kenya. In-depth research is needed to detect precise genes connected with adaptation and production in goat breeds in Kenya. [ABSTRACT FROM AUTHOR]

Carbamazepine triggers dermatologic hypersensitivity reactions, associated with specific human leukocyte antigens (HLAs), especially HLA-B*15:02 and HLA-A*31:01. Previous efforts to identify single nucleotide variants (SNVs) with high predictive value as HLA proxies, revealed that rs1061235 and rs17179220 fulfill these requirements for HLA-A*31:01 in some but not all populations. Herein we explored the predictive performance of rs1061235 and rs17179220 as HLA-A*31:01 tags in populations of Native American ancestry, which are largely underrepresented in pharmacogenomic studies. The study cohorts comprised the overall Admixed American superpopulation of the 1000 Genomes Project (1 KG_AMR), a subcohort of individuals with predominant Native American ancestry (1 KG_NAT), the Native American population of the Human Genome Diversity Project (HGDP), plus Kaingang (KRC) and Guarani (GRC and GKW) adults from indigenous reservation areas in Brazil. The diversity of cohorts is reflected in the range of frequencies of HLA-A*31:01 (0.02–0.65), rs1061235 (0.03–0.13) and rs17179220 (0.12–0.66), as well as in the predictive performance of these SNVs as HLA-A*31:01 proxies. NPV (negative predictive value), the metric of primary interest for pharmacogenetic-informed carbamazepine prescription was maximal (NPV = 1.0) for both SNVs in 1 KG_AMR and 1 KG_NAT, for rs17179220, but not rs1061235 (NPV = 0.91) in HGDP, and for rs17179220 in GWK, but not GRC (NPV = 0.88) or KRC (NPV = 0.80). Collectively, the data support the notion that rs1061235 and rs17179220 are not optimal proxies for HLA-A*31:01 across populations of Native American ancestry. [ABSTRACT FROM AUTHOR]

The global movement of bees for agricultural pollination services can affect local pollinator populations via hybridization. When commercial bumblebees are of the same species but of different geographic origin, intraspecific hybridization may result in beneficial integration of new genetic variation, or alternatively may disrupt locally adapted gene complexes. However, neither the existence nor the extent of genomic introgression and evolutionary divergence between wild and commercial bumblebees is fully understood. We obtained whole‐genome sequencing data from wild and commercial Bombus terrestris collected from sites in Southern Sweden with and without long‐term use of commercially imported B. terrestris. We search for evidence of introgression, dispersal and genome‐wide differentiation in a comparative genomic analysis of wild and commercial bumblebees. Commercial B. terrestris were found in natural environments near sites where commercial bumblebees were used, as well as drifting wild B. terrestris in commercial bumblebee colonies. However, we found no evidence for widespread, recent genomic introgression of commercial B. terrestris into local wild conspecific populations. We found that wild B. terrestris had significantly higher nucleotide diversity (Nei's pi, π), while the number of segregating sites (Watterson's theta, θw) was higher in commercial B. terrestris. A highly divergent region on chromosome 11 was identified in commercial B. terrestris and found to be enriched with structural variants. The genes present in this region are involved in flight muscle contraction and structure and pathogen immune response, providing evidence for differing evolutionary processes operating in wild and commercial B. terrestris. We did not find evidence for recent introgression, suggesting that co‐occurring commercial B. terrestris have not disrupted evolutionary processes in wild B. terrestris populations. [ABSTRACT FROM AUTHOR]

Haplotyping or determination of genetic phase has always played a pivotal role in MHC (HLA studies) both in helping to understand inheritance patterns in diseases such as type 1 diabetes (T1D) and in ensuring better matching in transplantation scenarios such as haematopoietic stem cell transplantation (HSCT), using donors genetically related to the patient. In recent years the need to establish genetic phase in a number of clinical scenarios has become apparent. These include: Genetic phasing for hematopoietic stem cell transplants using unrelated donors, where the HLA haplotypes are not known but where haplotype‐matched recipients fare better clinically than allele matched, but haplotype mismatched patients.The use of checkpoint inhibitors is one of the most innovative and exciting developments in cancer treatment in years. An example is the use of the monoclonal ipilimumab to block the CTLA‐4 receptor which is known to contain polymorphic sites. Until the phase of these polymorphisms is known it will not be possible to determine how effectively this monoclonal will perform in individual patients.The role of miRNA single strand molecules and their effect on gene expression. Thousands of non‐coding genes have been identified and have been shown to be polymorphic, as have their target genes. Genetic phasing of polymorphism both in the miRNA source genes and their targets is clearly a fertile area of researchIn areas such a drug metabolism where the polymorphic family of CYP genes is responsible for the metabolism of the majority of prescription drugs, determining phase of SNPs is critical to understanding drug metabolism and efficacy.In multigenic disease studies combinations of single nucleotide polymorphisms (SNPs) in participating genes require accurate phasing in order to fully appreciate their role in the disease process. In addition, the level of expression of genes (point 3) is also important in understanding disease processes at the functional level.This review outlines the techniques that are currently available for approximating phase and discusses the clinical relevance of establishing genetic phase in areas of clinical medicine outlined in points 1–3. [ABSTRACT FROM AUTHOR]

Although imputation of missing SNP results has been widely used in genetic studies, claims about the quality and usefulness of imputation have outnumbered the few studies that have questioned its limitations. But it is becoming clear that these limitations are real—for example, disease association signals can be missed in regions of LD breakdown. Here, as a case study, using the chromosomal region of the well‐known lactase gene, LCT, we address the issue of imputation in the context of variants that have become frequent in a limited number of modern population groups only recently, due to selection. We study SNPs in a 500 bp region covering the enhancer of LCT, and compare imputed genotypes with directly genotyped data. We examine the haplotype pairs of all individuals with discrepant and missing genotypes. We highlight the nonrandom nature of the allelic errors and show that most incorrect imputations and missing data result from long haplotypes that are evolutionarily closely related to those carrying the derived alleles, while some relate to rare and recombinant haplotypes. We conclude that bias of incorrectly imputed and missing genotypes can decrease the accuracy of imputed results substantially. [ABSTRACT FROM AUTHOR]

Much of what we know about the genetic basis of herbicide resistance has come from detailed investigations of monogenic adaptation at known target‐sites, despite the increasingly recognized importance of polygenic resistance. Little work has been done to characterize the broader genomic basis of herbicide resistance, including the number and distribution of genes involved, their effect sizes, allele frequencies and signatures of selection. In this work, we implemented genome‐wide association (GWA) and population genomic approaches to examine the genetic architecture of glyphosate (Round‐up) resistance in the problematic agricultural weed Amaranthustuberculatus. A GWA was able to correctly identify the known target‐gene but statistically controlling for two causal target‐site mechanisms revealed an additional 250 genes across all 16 chromosomes associated with non‐target‐site resistance (NTSR). The encoded proteins had functions that have been linked to NTSR, the most significant of which is response to chemicals, but also showed pleiotropic roles in reproduction and growth. Compared to an empirical null that accounts for complex population structure, the architecture of NTSR was enriched for large effect sizes and low allele frequencies, suggesting the role of pleiotropic constraints on its evolution. The enrichment of rare alleles also suggested that the genetic architecture of NTSR may be population‐specific and heterogeneous across the range. Despite their rarity, we found signals of recent positive selection on NTSR‐alleles by both window‐ and haplotype‐based statistics, and an enrichment of amino acid changing variants. In our samples, genome‐wide single nucleotide polymorphisms explain a comparable amount of the total variation in glyphosate resistance to monogenic mechanisms, even in a collection of individuals where 80% of resistant individuals have large‐effect TSR mutations, indicating an underappreciated polygenic contribution to the evolution of herbicide resistance in weed populations. [ABSTRACT FROM AUTHOR]

Sequence analysis of the ORFK1 of human herpesvirus type 8 (HHV‐8) allows the identification of six major subtypes (A–F), which are related to human migrations and the clinical progression of Kaposi's sarcoma. Sequencing and subsequent phylogenetic analysis of ORFK1 is considered to be the most reliable method for HHV‐8 genotyping. However, it exhibits challenges and limitations. Herein, we designed and validated a single base extension (SBE) protocol for characterization of HHV‐8 ORFK1 subtypes. A nested polymerase chain reaction (PCR) protocol was carried out to amplify a small 294‐bp PCR product encompassing four single nucleotide polymorphisms at positions 360, 406, 465 and 527 of the HHV‐8 genome. Finally, a multiplex SBE technique was developed and validated in 20 samples previously genotyped by phylogenetic analysis. The patterns obtained in this reaction could successfully discriminate between ORFK1 subtypes. The typing results obtained completely matched with those of the 'gold standard' method in all analysed samples. This method can reliably identify HHV‐8 subtypes A, B and C, which are the most prevalent ones worldwide, and the remaining subtypes (D, E and F). SBE can be useful as an efficient, rapid and low‐cost screening method for viral genotyping in a single tube, particularly samples with low‐quality DNA, and with easy data interpretation. [ABSTRACT FROM AUTHOR]

Granule-bound starch synthase I (GBSSI) is responsible for Waxy gene encoding the, which is involved in the amylose synthesis step of starch biosynthesis. We investigated the genotypic and haplotypic variations of GBSSI (Os06g0133000) gene, including its evolutionary relatedness in the nucleotide sequence level using single-nucleotide polymorphisms (SNPs), indels, and structural variations (SVs) from 475 Korean World Rice Collection (KRICE_CORE), which comprised 54 wild rice and 421 cultivated represented by 6 ecotypes (temperate japonica, indica, tropical japonica, aus, aromatic, and admixture) or in another way by 3 varietal types (landrace, weedy, and bred). The results revealed that 27 of 59 haplotypes indicated a total of 12 functional SNPs (fSNPs), identifying 9 novel fSNPs. According to the identified novel fSNPs, we classified the entire rice collection into three groups: cultivated, wild, and mixed (cultivated and wild) rice. Five novel fSNPs were localized in wild rice: four G/A fSNPs in exons 2, 9, and 12 and one T/C fSNP in exon 13. We also identified the three previously reported fSNPs, namely, a G/A fSNP (exon 4), an A/C fSNP (exon 6), and a C/T fSNP (exon 10), which were observed only in cultivated rice, whereas an A/G fSNP (exon 4) was observed exclusively in wild rice. All-against-all comparison of four varietal types or six ecotypes of cultivated rice with wild rice showed that the GBSSI diversity was higher only in wild rice (π = 0.0056). The diversity reduction in cultivated rice can be useful to encompass the origin of this gene GBSSI during its evolution. Significant deviations of positive (wild and indica under balancing selection) and negative (temperate and tropical japonica under purifying selection) Tajima's D values from a neutral model can be informative about the selective sweeps of GBSSI genome insights. Despite the estimation of the differences in population structure and principal component analysis (PCA) between wild and subdivided cultivated subgroups, an inbreeding effect was quantified by F ST statistic, signifying the genetic relatedness of GBSSI. Our findings of a novel wild fSNPS can be applicable for future breeding of waxy rice varieties. Furthermore, the signatures of selective sweep can also be of informative into further deeper insights during domestication. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder characterized by paradoxical phenotypes of deficits as well as gain in brain function. To address this a genomic tradeoff hypothesis was tested and followed up with the biological interaction and evolutionary significance of positively selected ASD risk genes. SFARI database was used to retrieve the ASD risk genes while for population datasets 1000 genome data was used. Common risk SNPs were subjected to machine learning as well as independent tests for selection, followed by Bayesian analysis to identify the cumulative effect of selection on risk SNPs. Functional implication of these positively selected risk SNPs was assessed and subjected to ontology analysis, pertaining to their interaction and enrichment of biological and cellular functions. This was followed by comparative analysis with the ancient genomes to identify their evolutionary patterns. Our results identified significant positive selection signals in 18 ASD risk SNPs. Functional and ontology analysis indicate the role of biological and cellular processes associated with various brain functions. The core of the biological interaction network constitutes genes for cognition and learning while genes in the periphery of the network had direct or indirect impact on brain function. Ancient genome analysis identified de novo and conserved evolutionary selection clusters. The de-novo evolutionary cluster represented genes involved in cognitive function. Relative enrichment of the ASD risk SNPs from the respective evolutionary cluster or biological interaction networks may help in addressing the phenotypic diversity in ASD. This cognitive genomic tradeoff signatures impacting the biological networks can explain the paradoxical phenotypes in ASD. [ABSTRACT FROM AUTHOR]

Background/Aim: Heterogeneous nuclear ribonucleoproteins (hnRNPs) contribute to multiple cellular functions including RNA splicing, stabilization, transcriptional and translational regulation, and signal transduction. However, the prognostic importance of genetic variants of hnRNP genes in clinical outcomes of prostate cancer remains to be elucidated. Patients and Methods: We studied the association of 78 germline single-nucleotide polymorphisms (SNPs) in 23 hnRNP genes with the overall survival (OS), cancer-specific survival (CSS), and progression-free survival (PFS) in 630 patients with prostate cancer receiving androgen-deprivation therapy (ADT). Results: PTBP1 rs10420407 was the most significant SNP (false discovery rate q=0.003) and carriers of the A allele exhibited poor OS, CSS, and PFS. Multivariate Cox analysis confirmed PTBP1 rs10420407 A allele was an independent negative prognostic factor for OS and PFS. Expression quantitative trait loci analysis showed that the rs10420407 A allele had a trend towards increased PTBP1 mRNA expression, and higher expression was correlated with prostate cancer aggressiveness and poor patient prognosis. Meta-analysis of 16 independent studies further indicated a tumorigenic effect of PTBP1, with a higher expression in prostate cancers than in adjacent normal tissues (p<0.001). Conclusion: Our data suggest that PTBP1 rs10420407 may influence patient response to ADT, and PTBP1 may be involved in the pathogenesis of prostate cancer progression. [ABSTRACT FROM AUTHOR]

Gastrointestinal nematode (GIN) infections have negative impacts on animal health, welfare and production. Information from molecular studies can highlight the underlying genetic mechanisms that enhance host resistance to GIN. However, such information often lacks for traditionally managed indigenous livestock. Here, we analysed 600 K single nucleotide polymorphism genotypes of GIN infected and non-infected traditionally managed autochthonous Tunisian sheep grazing communal natural pastures. Population structure analysis did not find genetic differentiation that is consistent with infection status. However, by contrasting the infected versus non-infected cohorts using ROH, LR-GWAS, FST and XP-EHH, we identified 35 candidate regions that overlapped between at least two methods. Nineteen regions harboured QTLs for parasite resistance, immune capacity and disease susceptibility and, ten regions harboured QTLs for production (growth) and meat and carcass (fatness and anatomy) traits. The analysis also revealed candidate regions spanning genes enhancing innate immune defence (SLC22A4, SLC22A5, IL-4, IL-13), intestinal wound healing/repair (IL-4, VIL1, CXCR1, CXCR2) and GIN expulsion (IL-4, IL-13). Our results suggest that traditionally managed indigenous sheep have evolved multiple strategies that evoke and enhance GIN resistance and developmental stability. They confirm the importance of obtaining information from indigenous sheep to investigate genomic regions of functional significance in understanding the architecture of GIN resistance. [ABSTRACT FROM AUTHOR]

Anterior cruciate ligament (ACL) rupture is a common condition that disproportionately affects young people, 50% of whom will develop knee osteoarthritis (OA) within 10 years of rupture. ACL rupture exhibits both hereditary and environmental risk factors, but the genetic basis of the disease remains unexplained. Spontaneous ACL rupture in the dog has a similar disease presentation and progression, making it a valuable genomic model for ACL rupture. We leveraged the dog model with Bayesian mixture model (BMM) analysis (BayesRC) to identify novel and relevant genetic variants associated with ACL rupture. We performed RNA sequencing of ACL and synovial tissue and assigned single nucleotide polymorphisms (SNPs) within differentially expressed genes to biological prior classes. SNPs with the largest effects were on chromosomes 3, 5, 7, 9, and 24. Selection signature analysis identified several regions under selection in ACL rupture cases compared to controls. These selection signatures overlapped with genome-wide associations with ACL rupture as well as morphological traits. Notable findings include differentially expressed ACSF3 with MC1R (coat color) and an association on chromosome 7 that overlaps the boundaries of SMAD2 (weight and body size). Smaller effect associations were within or near genes associated with regulation of the actin cytoskeleton and the extracellular matrix, including several collagen genes. The results of the current analysis are consistent with previous work published by our laboratory and others, and also highlight new genes in biological pathways that have not previously been associated with ACL rupture. The genetic associations identified in this study mirror those found in human beings, which lays the groundwork for development of disease-modifying therapies for both species. [ABSTRACT FROM AUTHOR]

The genomic region (~4 Mb) of the human major histocompatibility complex (MHC) on chromosome 6p21 is a prime model for the study and understanding of conserved polymorphic sequences (CPSs) and structural diversity of ancestral haplotypes (AHs)/conserved extended haplotypes (CEHs). The aim of this study was to use a set of 95 MHC genomic sequences downloaded from a publicly available BioProject database at NCBI to identify and characterise polymorphic human leukocyte antigen (HLA) class I genes and pseudogenes, MICA and MICB , and retroelement indels as haplotypic lineage markers, and single-nucleotide polymorphism (SNP) crossover loci in DNA sequence alignments of different haplotypes across the Olfactory Receptor (OR) gene region (~1.2 Mb) and the MHC class I region (~1.8 Mb) from the GPX5 to the MICB gene. Our comparative sequence analyses confirmed the identity of 12 haplotypic retroelement markers and revealed that they partitioned the HLA-A/B/C haplotypes into distinct evolutionary lineages. Crossovers between SNP-poor and SNP-rich regions defined the sequence range of haplotype blocks, and many of these crossover junctions occurred within particular transposable elements, lncRNA, OR12D2, MUC21, MUC22, PSORS1A3, HLA-C, HLA-B , and MICA. In a comparison of more than 250 paired sequence alignments, at least 38 SNP-density crossover sites were mapped across various regions from GPX5 to MICB. In a homology comparison of 16 different haplotypes, seven CEH/AH (7.1, 8.1, 18.2, 51.x, 57.1, 62.x , and 62.1) had no detectable SNP-density crossover junctions and were SNP poor across the entire ~2.8 Mb of sequence alignments. Of the analyses between different recombinant haplotypes, more than half of them had SNP crossovers within 10 kb of LTR16B/ERV3-16A3_I, MLT1, Charlie , and/or THE1 sequences and were in close vicinity to structurally polymorphic Alu and SVA insertion sites. These studies demonstrate that (1) SNP-density crossovers are associated with putative ancestral recombination sites that are widely spread across the MHC class I genomic region from at least the telomeric OR12D2 gene to the centromeric MICB gene and (2) the genomic sequences of MHC homozygous cell lines are useful for analysing haplotype blocks, ancestral haplotypic landscapes and markers, CPSs, and SNP-density crossover junctions. [ABSTRACT FROM AUTHOR]

Back and thigh skin of chickens showed significant differences in the thickness and the feather follicle density and size, which are important traits for slaughtered chickens' appearance. In the present study, global gene expression profiling was conducted in the back and thigh skin of chickens using Microarray technology. The results showed that 676 genes were differentially expressed between back and thigh skin. The expression of the differentially expressed genes (DEGs), including PPP1R3C, IGF1, PTCHD1, HOXB6, FGF9, CAMK4, SHH, BMP8B, FOXN1 and PTGER2, was validated by real‐time quantitative polymerase chain reaction (RT‐qPCR), and the results were consistent with microarray results. Functional analysis revealed that the DEGs were significantly involved in cell proliferation, differentiation, apoptosis, adhesion and transport process, and the pathways were significantly mapped into the ECM‐receptor interaction, peroxisome, focal adhesion, Hedgehog and PPAR signalling pathways. Protein–protein interaction network analysis suggested that signalling pathways related to feathers morphogenesis and development, such as Wnt, FGF, MAPK, SHH and BMP signalling pathways, occupied important positions in the network. Genes involved in these signalling pathways and adhesion molecules might play a vital role in skin and feather follicle development. Further single nucleotide polymorphism (SNP) association analysis of Wnt3A showed that the AC genotype of SNP g.255361 C>A significantly increased the feather follicle density of thigh skin. Our findings may provide new insights on candidate genes and pathways related to skin and feather follicle formation of chickens. [ABSTRACT FROM AUTHOR]

Despite the global importance of tropical ecosystems, few studies have identified how natural selection has shaped their megadiversity. Here, we test for the role of adaptation in the evolutionary success of the widespread, highly abundant Neotropical palm Mauritia flexuosa. We used a genome scan framework, sampling 16,262 single-nucleotide polymorphisms (SNPs) with target sequence capture in 264 individuals from 22 populations in rainforest and savanna ecosystems. We identified outlier loci as well as signal of adaptation using Bayesian correlations of allele frequency with environmental variables and detected both selective sweeps and genetic hitchhiking events. Functional annotation of SNPs with selection footprints identified loci affecting genes related to adaptation to environmental stress, plant development, and primary metabolic processes. The strong differences in climatic and soil variables between ecosystems matched the high differentiation and low admixture in population Bayesian clustering. Further, we found only small differences in allele frequency distribution in loci putatively under selection among widespread populations from different ecosystems, with fixation of a single allele in most populations. Taken together, our results indicate that adaptive selective sweeps related to environmental stress shaped the spatial pattern of genetic diversity in M. flexuosa , leading to high similarity in allele frequency among populations from different ecosystems. [ABSTRACT FROM AUTHOR]

Summary: Domestication and population differentiation in crops involve considerable phenotypic changes. The logs of these evolutionary paths, including natural/artificial selection, can be found in the genomes of the current populations. However, these profiles have been little studied in tree crops, which have specific characters, such as long generation time and clonal propagation, maintaining high levels of heterozygosity. We conducted exon‐targeted resequencing of 129 genomes in the genus Prunus, mainly Japanese apricot (Prunus mume), and apricot (Prunus armeniaca), plum (Prunus salicina), and peach (Prunus persica). Based on their genome‐wide single‐nucleotide polymorphisms merged with published resequencing data of 79 Chinese P. mume cultivars, we inferred complete and ongoing population differentiation in P. mume. Sliding window characterization of the indexes for genetic differentiation identified interspecific fragment introgressions between P. mume and related species (plum and apricot). These regions often exhibited strong selective sweeps formed in the paths of establishment or formation of substructures of P. mume, suggesting that P. mume has frequently imported advantageous genes from other species in the subgenus Prunus as adaptive evolution. These findings shed light on the complicated nature of adaptive evolution in a tree crop that has undergone interspecific exchange of genome fragments with natural/artificial selections. Significance Statement: The study conducted genome‐wide characterization of indices for genetic differentiation and identified fragmental interspecific introgressions in woody crops, focusing on Japanese apricot (Prunus mume) and related species in the subgenus Prunus (e.g., apricot [Prunus armeniaca] and plum [Prunus salicina]). Importantly, introgressed regions often underwent strong positive selection in the paths of domestication or variety differentiation, indicating that the Japanese apricot has frequently imported advantageous genes from other species. [ABSTRACT FROM AUTHOR]

Previous genetic studies on hair morphology focused on the overall morphology of the hair using data collected by self-report or researcher observation. Here, we present the first genome-wide association study (GWAS) of a micro-level quantitative measure of hair curvature. We compare these results to GWAS results obtained using a macro-level classification of observable hair curvature performed in the same sample of twins and siblings of European descent. Observational data were collected by trained observers, while quantitative data were acquired using an Optical Fibre Diameter Analyser (OFDA). The GWAS for both the observational and quantitative measures of hair curvature resulted in genome-wide significant signals at chromosome 1q21.3 close to the trichohyalin (TCHH) gene, previously shown to harbor variants associated with straight hair morphology in Europeans. All genetic variants reaching genome-wide significance for both GWAS (quantitative measure lead single-nucleotide polymorphism [SNP] rs12130862, p = 9.5 × 10-09; observational measure lead SNP rs11803731, p = 2.1 × 10-17) were in moderate to very high linkage disequilibrium (LD) with each other (minimum r2 = .45), indicating they represent the same genetic locus. Conditional analyses confirmed the presence of only one signal associated with each measure at this locus. Results from the quantitative measures reconfirmed the accuracy of observational measures. [ABSTRACT FROM AUTHOR]

Piscine novirhabdovirus = Viral Hemorrhagic Septicemia Virus (VHSV) first appeared in the Laurentian Great Lakes with large outbreaks from 2005 to 2006, as a new and novel RNA rhabdovirus subgenogroup (IVb) that killed >30 fish species. Interlude periods punctuated smaller more localized outbreaks in 2007, 2010, and 2017, although some fishes tested positive in the intervals. There have not been reports of outbreaks or positives from 2018, 2019, or 2020. Here, we employ a combined population genetics and phylogenetic approach to evaluate spatial and temporal evolutionary trajectory on its G‐gene sequence variation, in comparison with whole‐genome sequences (11,083 bp) from a subset of 44 individual isolates (including 40 newly sequenced ones). Our results show that IVb (N = 184 individual fish isolates) diversified into 36 G‐gene haplotypes from 2003 to 2017, stemming from two originals ("a" and "b"). G‐gene haplotypes "a" and "b" differed by just one synonymous single‐nucleotide polymorphism (SNP) substitution, remained the most abundant until 2011, then disappeared. Group "a" descendants (14 haplotypes) remained most prevalent in the Upper and Central Great Lakes, with eight (51%) having nonsynonymous substitutions. Group "b" descendants primarily have occurred in the Lower Great Lakes, including 22 haplotypes, of which 15 (68%) contained nonsynonymous changes. Evolutionary patterns of the whole‐genome sequences (which had 34 haplotypes among 44 isolates) appear congruent with those from the G‐gene. Virus populations significantly diverged among the Upper, Central, and Lower Great Lakes, diversifying over time. Spatial divergence was apparent in the overall patterns of nucleotide substitutions, while amino acid changes increased temporally. VHSV‐IVb thus significantly differentiated across its less than two decades in the Great Lakes, accompanied by declining outbreaks and virulence. Continuing diversification likely allowed the virus to persist at low levels in resident fish populations, and may facilitate its potential for further and future spread to new habitats and nonacclimated hosts. [ABSTRACT FROM AUTHOR]

Objectives: Long‐tailed macaques (Macaca fascicularis) are widely distributed throughout the mainland and islands of Southeast Asia, making them a useful model for understanding the complex biogeographical history resulting from drastic changes in sea levels throughout the Pleistocene. Past studies based on mitochondrial genomes (mitogenomes) of long‐tailed macaque museum specimens have traced their colonization patterns throughout the archipelago, but mitogenomes trace only the maternal history. Here, our objectives were to trace phylogeographic patterns of long‐tailed macaques using low‐coverage nuclear DNA (nDNA) data from museum specimens. Methods: We performed population genetic analyses and phylogenetic reconstruction on nuclear single nucleotide polymorphisms (SNPs) from shotgun sequencing of 75 long‐tailed macaque museum specimens from localities throughout Southeast Asia. Results: We show that shotgun sequencing of museum specimens yields sufficient genome coverage (average ~1.7%) for reconstructing population relationships using SNP data. Contrary to expectations of divergent results between nuclear and mitochondrial genomes for a female philopatric species, phylogeographical patterns based on nuclear SNPs proved to be closely similar to those found using mitogenomes. In particular, population genetic analyses and phylogenetic reconstruction from the nDNA identify two major clades within M. fascicularis: Clade A includes all individuals from the mainland along with individuals from northern Sumatra, while Clade B consists of the remaining island‐living individuals, including those from southern Sumatra. Conclusions: Overall, we demonstrate that low‐coverage sequencing of nDNA from museum specimens provides enough data for examining broad phylogeographic patterns, although greater genome coverage and sequencing depth would be needed to distinguish between very closely related populations, such as those throughout the Philippines. [ABSTRACT FROM AUTHOR]

Wild grapevine, Vitis vinifera L. subsp. sylvestris (Gmelin, Hegi) is spontaneous to Europe and common in Tuscany. In this study, wild grapevines were identified in 22 populations from eight locations in Tuscan Maremma (Grosseto and Siena province). The plants were propagated by cuttings, collected in a vineyard, genotyped by nuclear simple sequence repeats (SSRs), chloroplast SSRs and single nucleotide polymorphisms (SNPs), and compared to locally cultivated varieties (Vitis vinifera L. subsp. sativa) and to non- vinifera and non- vitis genotypes. The identity analysis revealed that some individuals were redundant genotypes, suggesting natural vegetative propagation. In addition, four of the supposed V.v. sylvestris were in fact naturalized V.v. sativa. The majority of putative sylvestris genotypes had chlorotype A, while the remainder had chlorotype D, as the majority of Vitis vinifera subsp. sativa cultivated in Italy. Some of the recovered sylvestris genotypes appeared to be natural crosses with cultivated grapevine varieties in Tuscany, and their chlorotype suggests a higher pollen flow from sativa to the sylvestris genotypes than in the opposite direction. In addition, other genotypes appeared to be crosses within sylvestris , sylvestris - sativa or sylvestris - sylvestris siblings, or equivalent relationships. These relationships suggest a noticeably level of sexual reproductive activities among sylvestris and sylvestris - sativa genotypes. A cluster and structure analysis clearly differentiated the true sylvestris from the sativa , and the non- vinifera or non- vitis genotypes, and also highlighted a possible introgression of sylvestris into some Italian and French cultivated varieties. The results therefore suggest that, in addition to the primary ancient center of domestication from the Near East to Central Asia, the introgression among cultivated and wild grapevine occurred in other centers of diversification along the migration routes, contributing to the domestication processes, and suggesting that these processes are still ongoing despite the reduction in populations of sylvestris. The results also highlight that the GrapeReSeq 18K Vitis genotyping chip are suitable for non- vitis genotyping and that the range of SNPs heterozygosity in sylvestris appears to be up to 6% less and does not overlap the heterozygosity range of sativa genotypes. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the impact of selection on the genome structure of beef cattle through identification of selection signatures reflecting the breeding standard of each breed and to discover potential functional genetic variants to improve performance traits. Genotyping data of six beef breeds (Aberdeen Angus, Hereford, Limousin, Charolais, Piedmontese and Romagnola) were used to perform genome-wide scans for selection signatures. The approaches applied were based on an assumption that selection leads to linkage disequilibrium or to a decrease of genetic variability in genomic regions containing genotypes connected with favourable phenotypes. Thus, the selection signatures were analysed based on Wright's FST index, distribution of runs of homozygosity segments in the beef genome and determination of linkage disequilibrium variability between breeds. The number and length of detected selection signals were different depending on the breeds and methodological approaches. As expected due to the breeding goals of analysed breeds, common signals were located on autosomes 2, 6, 7, 13 and 20 close to the genes associated with coat colour (KIT, KDR), muscle development (GDF9, GHRH, GHR), double muscling (MSTN), meat tenderness (CAST) and intramuscular fat content (SCD). But, across the genomes of analysed breeds, unique selection signals were found as well. The subsequent analysis of those single nucleotide polymorphism markers can be beneficial for the genetic progress of studied breeds in future. [ABSTRACT FROM AUTHOR]

Nile tilapia (Oreochromis niloticus) is one of the most produced farmed fish in the world and represents an important source of protein for human consumption. Farmed Nile tilapia populations are increasingly based on genetically improved stocks, which have been established from admixed populations. To date, there is scarce information about the population genomics of farmed Nile tilapia, assessed by dense single nucleotide polymorphism (SNP) panels. The patterns of linkage disequilibrium (LD) may affect the success of genome-wide association studies (GWAS) and genomic selection (GS), and also provide key information about demographic history of farmed Nile tilapia populations. The objectives of this study were to provide further knowledge about the population structure and LD patterns, as well as, estimate the effective population size (N e) for three farmed Nile tilapia populations, one from Brazil (POP A) and two from Costa Rica (POP B and POP C). A total of 55 individuals from each population, were genotyped using a 50K SNP panel selected from a whole-genome sequencing (WGS) experiment. The first two principal components explained about 20% of the total variation and clearly differentiated between the three populations. Population genetic structure analysis showed evidence of admixture, especially for POP C. The contemporary N e estimated, based on LD values, ranged from 78 to 159. No differences were observed in the LD decay among populations, with a rapid decrease of r 2 with increasing inter-marker distance. Average r 2 between adjacent SNP pairs ranged from 0.19 to 0.03 for both POP A and C, and 0.20 to 0.03 f or POP B. Based on the number of independent chromosome segments in the Nile tilapia genome, at least 9.4, 7.6, and 4.6K SNPs for POP A, POP B, and POP C respectively, are required for the implementation of GS in the present farmed Nile tilapia populations. [ABSTRACT FROM AUTHOR]

Charolais cattle are one of the most important breeds for meat production worldwide; in México, its selection is mainly made by live weight traits. One strategy for mapping important genomic regions that might influence productive traits is the identification of signatures of selection. This type of genomic features contains loci with extended linkage disequilibrium (LD) and homozygosity patterns that are commonly associated with sites of quantitative trait locus (QTL). Therefore, the objective of this study was to identify the signatures of selection in Charolais cattle genotyped with the GeneSeek Genomic Profiler Bovine HD panel consisting of 77 K single nucleotide polymorphisms (SNPs). A total 61,311 SNPs and 819 samples were used for the analysis. Identification of signatures of selection was carried out using the integrated haplotype score (iHS) methodology implemented in the rehh R package. The top ten SNPs with the highest piHS values were located on BTA 4, 5, 6 and 14. By identifying markers in LD with top ten SNPs, the candidate regions defined were mapped to 52.8–59.3 Mb on BTA 4; 67.5–69.3 on BTA 5; 39.5–41.0 Mb on BTA 6; and 26.4–29.6 Mb on BTA 14. The comparison of these candidate regions with the bovine QTLdb effectively confirmed the association (p < 0.05) with QTL related to growth traits and other important productive traits. The genomic regions identified in this study indicated selection for growth traits on the Charolais population via the conservation of haplotypes on various chromosomes. These genomic regions and their associated genes could serve as the basis for haplotype association studies and for the identification of causal genes related to growth traits. [ABSTRACT FROM AUTHOR]

Understanding the genomic basis of adaptation in maize is important for gene discovery and the improvement of breeding germplasm, but much remains a mystery in spite of significant population genetics and archaeological research. Identifying the signals underpinning adaptation are challenging as adaptation often coincided with genetic drift, and the base genomic diversity of the species in massive. In this study, tGBS technology was used to genotype 1,143 diverse maize accessions including landraces collected from 20 countries and elite breeding lines of tropical lowland, highland, subtropical/midaltitude and temperate ecological zones. Based on 355,442 high‐quality single nucleotide polymorphisms, 13 genomic regions were detected as being under selection using the bottom‐up searching strategy, EigenGWAS. Of the 13 selection regions, 10 were first reported, two were associated with environmental parameters via EnvGWAS, and 146 genes were enriched. Combining large‐scale genomic and ecological data in this diverse maize panel, our study supports a polygenic adaptation model of maize and offers a framework to enhance our understanding of both the mechanistic basis and the evolutionary consequences of maize domestication and adaptation. The regions identified here are promising candidates for further, targeted exploration to identify beneficial alleles and haplotypes for deployment in maize breeding. [ABSTRACT FROM AUTHOR]

We propose a Bayesian nonparametric model to infer population admixture, extending the hierarchical Dirichlet process to allow for correlation between loci due to linkage disequilibrium. Given multilocus genotype data from a sample of individuals, the proposed model allows inferring and classifying individuals as unadmixed or admixed, inferring the number of subpopulations ancestral to an admixed population and the population of origin of chromosomal regions. Our model does not assume any specific mutation process, and can be applied to most of the commonly used genetic markers. We present a Markov chain Monte Carlo (MCMC) algorithm to perform posterior inference from the model and we discuss some methods to summarize the MCMC output for the analysis of population admixture. Finally, we demonstrate the performance of the proposed model in a real application, using genetic data from the ectodysplasin-A receptor (EDAR) gene, which is considered to be ancestry-informative due to well-known variations in allele frequency as well as phenotypic effects across ancestry. The structure analysis of this dataset leads to the identification of a rare haplotype in Europeans. We also conduct a simulated experiment and show that our algorithm outperforms parametric methods. [ABSTRACT FROM AUTHOR]

Infectious diseases are significant demographic and evolutionary drivers of populations, but studies about the genetic basis of disease resistance and susceptibility are scarce in wildlife populations. Cetacean morbillivirus (CeMV) is a highly contagious disease that is increasing in both geographic distribution and incidence, causing unusual mortality events (UME) and killing tens of thousands of individuals across multiple cetacean species worldwide since the late 1980s. The largest CeMV outbreak in the Southern Hemisphere reported to date occurred in Australia in 2013, where it was a major factor in a UME, killing mainly young Indo‐Pacific bottlenose dolphins (Tursiops aduncus). Using cases (nonsurvivors) and controls (putative survivors) from the most affected population, we carried out a genome‐wide association study to identify candidate genes for resistance and susceptibility to CeMV. The genomic data set consisted of 278,147,988 sequence reads and 35,493 high‐quality SNPs genotyped across 38 individuals. Association analyses found highly significant differences in allele and genotype frequencies among cases and controls at 65 SNPs, and Random Forests conservatively identified eight as candidates. Annotation of these SNPs identified five candidate genes (MAPK8, FBXW11, INADL, ANK3 and ACOX3) with functions associated with stress, pain and immune responses. Our findings provide the first insights into the genetic basis of host defence to this highly contagious disease, enabling the development of an applied evolutionary framework to monitor CeMV resistance across cetacean species. Biomarkers could now be established to assess potential risk factors associated with these genes in other CeMV‐affected cetacean populations and species. These results could also possibly aid in the advancement of vaccines against morbilliviruses. [ABSTRACT FROM AUTHOR]

This paper shows a straightforward, but surprisingly effective approach to detect genomic regions of importance, illustrated on two Simmental cattle populations. Medium density genomic data of 42 German/Austrian (denoted as "Western") and 38 Russian Simmental cattle were used to identify the most frequent haplotypes within the two populations. The haplotypes were defined as non-overlapping segments of ten single nucleotide ploymorphisms (SNP). The phasing was done with the SHAPEIT software, with a follow up analysis of haplotypes using the GHap package. Despite the low sample size a number of high frequency haplotypes could be identified accross the whole genome. The identified genes residing direcly in these high frequency haplotypes were extremely relevant for the dual purpose Simmental cattle. A large part of these genes influenced growth rate and carcass traits, others were relevant for the milk production. A smaller proportion was connected to the reproduction, immune system and cellular processes, with indirect influence on production traits. [ABSTRACT FROM AUTHOR]

In this article we examine the history of the production of microarray technologies and their role in constructing and operationalizing views of human genetic difference in contemporary genomics. Rather than the “turn to difference” emerging as a post-Human Genome Project (HGP) phenomenon, interest in individual and group differences was a central, motivating concept in human genetics throughout the twentieth century. This interest was entwined with efforts to develop polymorphic “genetic markers” for studying human traits and diseases. We trace the technological, methodological and conceptual strategies in the late twentieth century that established single nucleotide polymorphisms (SNPs) as key focal points for locating difference in the genome. By embedding SNPs in microarrays, researchers created a technology that they used to catalog and assess human genetic variation. In the process of making genetic markers and array-based technologies to track variation, scientists also made commitments to ways of describing, cataloging and “knowing” human genetic differences that refracted difference through a continental geographic lens. We show how difference came to matter in both senses of the term: difference was made salient to, and inscribed on, genetic matter(s), as a result of the decisions, assessments and choices of collaborative and hybrid research collectives in medical genomics research. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is one of the leading cancers throughout the world. It represents the third most common cancer and the fourth in mortality. Most of CRC are sporadic, arise with no known high-penetrant genetic variation and with no previous family history. The etiology of sporadic CRC is considered to be multifactorial and arises from the interaction of genetic variants of low-penetrant genes and environmental risk factors. The most common well-studied genetic variation is single nucleotide polymorphisms (SNPs). SNP arises as a point mutation. If the frequency of the sequence variation reaches 1% or more in the population, it is referred to as polymorphism, but if it is lower than 1%, the allele is typically considered as a mutation. Lots of SNPs have been associated with CRC development and progression, for example, genes of TGF-β1 and CHI3L1 pathways. TGF-β1 is a pleiotropic cytokine with a dual role in cancer development and progression. TGF-β1 mediates its actions through canonical and noncanonical pathways. The most important negative regulatory protein for TGF-β1 activity is termed SMAD7. The production of TGF-β can be controlled by another protein called YKL-40. YKL-40 is a glycoprotein with an important role in cancer initiation and metastasis. YKL-40 is encoded by the CHI3L1 gene. The aim of the present review is to give a brief introduction of CRC, SNP, and examples of some SNPs that have been documented to be associated with CRC. We also discuss two important signaling pathways TGF-β1 and CHI3L1 that influence the incidence and progression of CRC. [ABSTRACT FROM AUTHOR]