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Alpha-1-Antitrypsin deficiency (AATD), caused by mutations, is one of the most prevalent Mendelian disorders among individuals of European descend. However, this condition, which is characterized by reduced serum levels of alpha-1-antitrypsin (AAT) and associated with increased risks of pulmonary emphysema and liver disease in both children and adults, remains frequently underdiagnosed. AATD clinical manifestations are often correlated with two pathogenic variants, the Z allele (p.Glu342Lys) and the S allele (p.Glu264Val), which can be combined in severe ZZ or moderate SZ risk genotypes. Yet, screenings of AATD cases and large sequencing efforts carried out in both control and disease populations are disclosing outstanding numbers of rare variants (>500), including many pathogenic and other likely deleterious mutations. Generally speaking, pathogenic variants can be subdivided into either loss- or gain-of-function according to their pathophysiological effects. In AATD, the loss-of-function is correlated with an uncontrolled activity of elastase by its natural inhibitor, the AAT. This phenomenon can result from the absence of circulating AAT (null alleles), poor AAT secretion from hepatocytes (deficiency alleles) or even from a modified inhibitory activity (dysfunctional alleles). On the other hand, the gain-of-function is connected with the formation of AAT polymers and their switching on of cellular stress and inflammatory responses (deficiency alleles). Less frequently, the gain-of-function is related to a modified protease affinity (dysfunctional alleles). Here, we revisit mutation spectrum, its origins and population history with a greater emphasis on variants fitting the aforementioned processes of AATD pathogenesis. Those were selected based on their clinical significance and wider geographic distribution. Moreover, we also provide some directions for future studies of AATD clinically heterogeneity and comprehensive diagnosis.

Schizophrenia has a heritability of 60–80% 1 , much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4 , and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies. A genome-wide association study including over 76,000 individuals with schizophrenia and over 243,000 control individuals identifies common variant associations at 287 genomic loci, and further fine-mapping analyses highlight the importance of genes involved in synaptic processes.

If there are no constraints on the process of speciation, then the number of species might be expected to match the number of available niches and this number might be indefinitely large. One possible constraint is the opportunity for allopatric divergence. In 1981, Felsenstein used a simple and elegant model to ask if there might also be genetic constraints. He showed that progress towards speciation could be described by the build-up of linkage disequilibrium among divergently selected loci and between these loci and those contributing to other forms of reproductive isolation. Therefore, speciation is opposed by recombination, because it tends to break down linkage disequilibria. Felsenstein then introduced a crucial distinction between “two-allele” models, which are subject to this effect, and “one-allele” models, which are free from the recombination constraint. These fundamentally important insights have been the foundation for both empirical and theoretical studies of speciation ever since.

Many population genetic activities, ranging from evolutionary studies to association mapping, to forensic identification, rely on appropriate estimates of population structure or relatedness. All applications require recognition that quantities with an underlying meaning of allelic dependence are not defined in an absolute sense, but instead are made “relative to” some set of alleles other than the target set. The 1984 Weir and Cockerham FST estimate made explicit that the reference set of alleles was across populations, whereas standard kinship estimates do not make the reference explicit. Weir and Cockerham stated that their FST estimates were for independent populations, and standard kinship estimates have an implicit assumption that pairs of individuals in a study sample, other than the target pair, are unrelated or are not inbred. However, populations lose independence when there is migration between them, and dependencies between pairs of individuals in a population exist for more than one target pair. We have therefore recast our treatments of population structure, relatedness, and inbreeding to make explicit that the parameters of interest involve the differences in degrees of allelic dependence between the target and the reference sets of alleles, and so can be negative. We take the reference set to be the population from which study individuals have been sampled. We provide simple moment estimates of these parameters, phrased in terms of allelic matching within and between individuals for relatedness and inbreeding, or within and between populations for population structure. A multi-level hierarchy of alleles within individuals, alleles between individuals within populations, and alleles between populations, allows a unified treatment of relatedness and population structure. We expect our new measures to have a wide range of applications, but we note that their estimates are sensitive to rare or private variants: some population-characterization applications suggest exploiting those sensitivities, whereas estimation of relatedness may best use all genetic markers without filtering on minor allele frequency.

It is known that the allele ancestral to the variation at a polymorphic site cannot be assigned with certainty, and that the most frequently used method to assign the ancestral state—maximum parsimony—is prone to misinference. Estimates of counts of sites that have a certain number of copies of the derived allele in a sample (the unfolded site frequency spectrum, uSFS) made by parsimony are therefore also biased. We previously developed a maximum likelihood method to estimate the uSFS for a focal species using information from two outgroups while assuming simple models of nucleotide substitution. Here, we extend this approach to allow multiple outgroups (implemented for three outgroups), potentially any phylogenetic tree topology, and more complex models of nucleotide substitution. We find, however, that two outgroups and the Kimura two-parameter model are adequate for uSFS inference in most cases. We show that using parsimony to infer the ancestral state at a specific site seriously breaks down in two situations. The first is where the outgroups provide no information about the ancestral state of variation in the focal species. In this case, nucleotide variation will be underestimated if such sites are excluded. The second is where the minor allele in the focal species agrees with the allelic state of the outgroups. In this situation, parsimony tends to overestimate the probability of the major allele being derived, because it fails to account for the fact that sites with a high frequency of the derived allele tend to be rare. We present a method that corrects this deficiency and is capable of providing nearly unbiased estimates of ancestral state probabilities on a site-by-site basis and the uSFS.

Background The advancement of sequencing technologies today has made a plethora of whole-genome re-sequenced (WGRS) data publicly available. However, research utilizing the WGRS data without further configuration is nearly impossible. To solve this problem, our research group has developed an interactive Allele Catalog Tool to enable researchers to explore the coding region allelic variation present in over 1,000 re-sequenced accessions each for soybean, Arabidopsis , and maize. Results The Allele Catalog Tool was designed originally with soybean genomic data and resources. The Allele Catalog datasets were generated using our variant calling pipeline (SnakyVC) and the Allele Catalog pipeline (AlleleCatalog). The variant calling pipeline is developed to parallelly process raw sequencing reads to generate the Variant Call Format (VCF) files, and the Allele Catalog pipeline takes VCF files to perform imputations, functional effect predictions, and assemble alleles for each gene to generate curated Allele Catalog datasets. Both pipelines were utilized to generate the data panels (VCF files and Allele Catalog files) in which the accessions of the WGRS datasets were collected from various sources, currently representing over 1,000 diverse accessions for soybean, Arabidopsis , and maize individually. The main features of the Allele Catalog Tool include data query, visualization of results, categorical filtering, and download functions. Queries are performed from user input, and results are a tabular format of summary results by categorical description and genotype results of the alleles for each gene. The categorical information is specific to each species; additionally, available detailed meta-information is provided in modal popups. The genotypic information contains the variant positions, reference or alternate genotypes, the functional effect classes, and the amino-acid changes of each accession. Besides that, the results can also be downloaded for other research purposes. Conclusions The Allele Catalog Tool is a web-based tool that currently supports three species: soybean, Arabidopsis , and maize. The Soybean Allele Catalog Tool is hosted on the SoyKB website ( https://soykb.org/SoybeanAlleleCatalogTool/ ), while the Allele Catalog Tool for Arabidopsis and maize is hosted on the KBCommons website ( https://kbcommons.org/system/tools/AlleleCatalogTool/Zmays and https://kbcommons.org/system/tools/AlleleCatalogTool/Athaliana ). Researchers can use this tool to connect variant alleles of genes with meta-information of species.

Purpose Genotyping CYP2D6 is important for precision drug therapy because the enzyme it encodes metabolizes approximately 25% of drugs, and its activity varies considerably among individuals. Genotype analysis of CYP2D6 is challenging due to its highly polymorphic nature. Over 100 haplotypes (star alleles) have been defined for CYP2D6 , some involving a gene conversion with its nearby nonfunctional but highly homologous paralog CYP2D7 . We present Stargazer, a new bioinformatics tool that uses next-generation sequencing (NGS) data to call star alleles for CYP2D6 ( https://stargazer.gs.washington.edu/stargazerweb/ ). Stargazer is currently being extended for other pharmacogenes. Methods Stargazer identifies star alleles from NGS data by detecting single nucleotide variants, insertion-deletion variants, and structural variants. Stargazer detects structural variation, including gene deletions, duplications, and conversions, by calculating paralog-specific copy numbers from read depths. Results We applied Stargazer to the NGS data of 32 ethnically diverse HapMap trios that were genotyped by TaqMan assays, long-range polymerase chain reaction, quantitative multiplex polymerase chain reaction, high-resolution melting analysis, and/or Sanger sequencing. CYP2D6 genotyping by Stargazer was 99.0% concordant with the data obtained by these methods, and showed that 28.1% of the samples had structural variation including CYP2D6/CYP2D7 hybrids. Conclusion Accurate genotyping of pharmacogenes with NGS and subsequent allele calling with Stargazer will aid the implementation of precision drug therapy.

Allopolyploidy is a prevalent process in plants, having important physiological, ecological and evolutionary consequences. Transcriptomic responses to genomic merger and doubling have been demonstrated in many allopolyploid systems, encompassing a diversity of phenomena including homoeolog expression bias, genome dominance, expression-level dominance and revamping of co-expression networks. Notwithstanding the foregoing, there remains a need to develop a conceptual framework that will stimulate a deeper understanding of these diverse phenomena and their mechanistic interrelationships. Here we introduce considerations relevant to this framework with a focus on cis–trans interactions among duplicated genes and alleles in hybrids and allopolyploids. By extending classic allele-specific expression analysis to the allopolyploid level, we distinguish the distinct effects of progenitor regulatory interactions from the novel intergenomic interactions that arise from genome merger and allopolyploidization. This perspective informs experiments designed to reveal the molecular genetic basis of gene regulatory control, and will facilitate the disentangling of genetic from epigenetic and higher-order effects that impact gene expression. Finally, we suggest that the extended cis–trans model may help conceptually unify several presently disparate hallmarks of allopolyploid evolution, including genome-wide expression dominance and biased fractionation, and lead to a new level of understanding of phenotypic novelty accompanying polyploidy.

Summary Allele‐specific expression (ASE) can lead to phenotypic diversity and evolution. However, the mechanisms regulating ASE are not well understood, particularly in woody perennial plants. In this study, we investigated ASE genes in the apple cultivar ‘Royal Gala’ (RG). A high quality chromosome‐level genome was assembled using a homozygous tetra‐haploid RG plant, derived from anther cultures. Using RNA‐sequencing (RNA‐seq) data from RG flower and fruit tissues, we identified 2091 ASE genes. Compared with the haploid genome of ‘Golden Delicious’ (GD), a parent of RG, we distinguished the genomic sequences between the two alleles of 817 ASE genes, and further identified allele‐specific presence of a transposable element (TE) in the upstream region of 354 ASE genes. These included MYB110a that encodes a transcription factor regulating anthocyanin biosynthesis. Interestingly, another ASE gene, MYB10 also showed an allele‐specific TE insertion and was identified using genome data of other apple cultivars. The presence of the TE insertion in both MYB genes was positively associated with ASE and anthocyanin accumulation in apple petals through analysis of 231 apple accessions, and thus underpins apple flower colour evolution. Our study demonstrated the importance of TEs in regulating ASE on a genome‐wide scale and presents a novel method for rapid identification of ASE genes and their regulatory elements in plants.