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Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci ( P  < 5 × 10 −8 ), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis. A genome-wide association study and Metabochip meta-analysis of body mass index (BMI) detects 97 BMI-associated loci, of which 56 were novel, and many loci have effects on other metabolic phenotypes; pathway analyses implicate the central nervous system in obesity susceptibility and new pathways such as those related to synaptic function, energy metabolism, lipid biology and adipogenesis. Genetic correlates of obesity In the second of two Articles in this issue from the GIANT Consortium, Elizabeth Speliotes and collegues conducted a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), commonly used to define obesity and assess adiposity, to find 97 BMI-associated loci, of which 56 were novel. Many of these loci have significant effects on other metabolic phenotypes. The 97 loci account for about 2.7% of BMI variation, and genome-wide estimates suggest common variation accounts for more than 20% of BMI variation. Pathway analyses implicate the central nervous system in obesity susceptibility including synaptic function, glutamate signaling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

Background Lentinula edodes (Berk.) is the second most productive mushroom in the world. It contains compounds effective for antiviral, antitumor, antioxidant and immune regulation. Although genomes have previously been reported for this species, a high-quality chromosome-level reference for L. edodes is unavailable. This hinders detailed investigation of population genetics, breeding history of strains and genes related to environmental stress responses. Results A high-quality chromosome-level genome was constructed. We separated a monokaryon from protoplasts of the commercial L. edodes strain L808 and assembled the genome of L. edodes using PacBio long-read and Illumina short-read sequencing, along with the high-throughput chromatin conformation capture (Hi-C) technique. We assembled a 45.87 Mb genome, and 99% of the sequences were anchored onto 10 chromosomes. The contig and scaffold N50 length were 2.17 and 4.94 Mb, respectively. Over 96% of the complete Benchmarking Universal Single-Copy Orthologs (BUSCO) were identified, and 9853 protein-coding genes were predicted. We performed population genome resequencing using 34 wild strains and 65 commercial cultivars of L. edodes originating from China, Japan, the United States and Australia. Based on whole-genome variants, we showed substantial differences in the Chinese wild population, which divided into different branches according to the main areas of their geographical distribution. We also determined the breeding history of L. edodes at the molecular level, and demonstrated that the cultivated strains in China mainly originated from wild strains from China and Northeast Asia. Phenotypic analysis showed that 99 strains exhibited differences on the Cd accumulation. Three significant loci in the of L. edodes genome were identified using the genome-wide association study (GWAS) of Cd accumulation traits. Functional genes associated with Cd accumulation traits were related to DNA ligase and aminoacyl tRNA synthetase, indicating that DNA damage repair and in vivo protein translation may be responses to Cd stress. Conclusions A high-quality chromosome-level genome and population genetic data of L. edodes provide genetic resources for functional genomic, evolutionary and artificial breeding studies for L. edodes .

Mitochondrial DNA (mtDNA) exhibits distinct characteristics distinguishing it from the nuclear genome, necessitating specific analytical methods in genetic studies. This comprehensive review explores the complex role of mtDNA in a variety of genetic studies, including genome-wide, epigenome-wide, and phenome-wide association studies, with a focus on its implications for human traits and diseases. Here, we discuss the structure and gene-encoding properties of mtDNA, along with the influence of environmental factors and epigenetic modifications on its function and variability. Particularly significant are the challenges posed by mtDNA’s high mutation rate, heteroplasmy, and copy number variations, and their impact on disease susceptibility and population genetic analyses. The review also highlights recent advances in methodological approaches that enhance our understanding of mtDNA associations, advocating for refined genetic research techniques that accommodate its complexities. By providing a comprehensive overview of the intricacies of mtDNA, this paper underscores the need for an integrated approach to genetic studies that considers the unique properties of mitochondrial genetics. Our findings aim to inform future research and encourage the development of innovative methodologies to better interpret the broad implications of mtDNA in human health and disease.

The Asteraceae family is a prominent group of flowering plants found across the globe, with the exception of Antarctica. The Asteraceae family is a largest flowering family pivotal group in plant evolution and diversification. Despite its importance, the genetic diversity within this family remains understudied. We focused on the rps -11 gene, a chloroplast marker previously utilized in phylogenetic studies, to investigate its potential in resolving Asteraceae relationships. The focus was on examining genetic diversity within sixteen specifically chosen species from the Asteraceae family. This assessment was based on an analysis of a chloroplast gene responsible for encoding the ribosomal protein of the smaller subunit 11 ( rps 11). Nearly 417 bp of rps 11 gene was amplified, sequenced, computationally translated into amino acid sequence and the data was used for phylogenetic analysis as well as for rps 11 protein structure predictions. Based on nucleotide and amino acid sequences phylograms were drawn with the help of Molecular Evolutionary Genetic Analysis (MEGA 6), which exhibited clear genetic relationship among species under investigation. The observed genetic distance was 0.02 for Maximum likelihood tree based on nucleotide sequences whereas it was 0.05 for phylogram based on amino acid sequences. These values revealed that amino acid-based tree has demonstrated greater diversity among selected species in comparison to nucleotides-based tree. On the basis of pair wise distance calculations, genetic divergence values were found within the range of 0.015–0.309. Moreover, 3D protein modeling for rps 11 protein of sixteen selected species was also carried out by iterative threading assembly refinement (I-Tasser) software. The models exhibiting the highest C-score were picked with satisfactory plot statistics (> 90%) and structurally validated by PROCHECK. Furthermore, Ramachandran plots displayed that the rps 11 protein structures of Tagetes minuta , Xanthium strumarium , Lactuca sativa and Chrysanthemum indicum have best feature models with > 90% of residues in the allowed region and ≤ 2% in the disallowed region. The research is not enough to stand alone to validate the viability of the rps 11 gene as a prospective contender for phylogenetic analysis. İn future we will focus on the maximum genetic diversity theory for phylogenetic analysis of this family.

Advancements in next-generation sequencing (NGS) technologies have led to a substantial increase in the availability of population genetic variant data, thus prompting the development of various population analysis tools to enhance our understanding of population structure and evolution. The tools that are currently used to analyze population genetic variant data generally require different environments, parameters, and formats of the input data, which can act as a barrier preventing the wide-spread usage of such tools by general researchers who may not be familiar with bioinformatics. To address this problem, we have developed an automated and comprehensive pipeline called PAPipe to perform nine widely used population genetic analyses using population NGS data. PAPipe seamlessly interconnects and serializes multiple steps, such as read trimming and mapping, genetic variant calling, data filtering, and format converting, along with nine population genetic analyses such as principal component analysis, phylogenetic analysis, population tree analysis, population structure analysis, linkage disequilibrium decay analysis, selective sweep analysis, population admixture analysis, sequentially Markovian coalescent analysis, and fixation index analysis. PAPipe also provides an easy-to-use web interface that allows for the parameters to be set and the analysis results to be browsed in intuitive manner. PAPipe can be used to generate extensive results that provide insights that can help enhance user convenience and data usability. PAPipe is freely available at https://github.com/jkimlab/PAPipe.

Genetic alterations in adult T‐cell leukemia/lymphoma (ATLL), a T‐cell malignancy associated with HTLV‐1, and their clinical impacts, especially from the perspective of viral strains, are not fully elucidated. We employed targeted next‐generation sequencing and single nucleotide polymorphism array for 89 patients with ATLL in Okinawa, the southernmost islands in Japan, where the frequency of HTLV‐1 tax subgroup‐A (HTLV‐1‐taxA) is notably higher than that in mainland Japan, where most ATLL cases have HTLV‐1‐taxB, and compared the results with previously reported genomic landscapes of ATLL in mainland Japan and the USA. Okinawan patients exhibited similar mutation profiles to mainland Japanese patients, with frequent alterations in TCR/NF‐ĸB (eg, PRKCB, PLCG1, and CARD11) and T‐cell trafficking pathways (CCR4 and CCR7), in contrast with North American patients who exhibited a predominance of epigenome‐associated gene mutations. Some mutations, especially GATA3 and RHOA, were detected more frequently in Okinawan patients than in mainland Japanese patients. Compared to HTLV‐1‐taxB, HTLV‐1‐taxA was significantly dominant in Okinawan patients with these mutations (GATA3, 34.1% vs 14.6%, P = .044; RHOA, 24.4% vs 6.3%, P = .032), suggesting the contribution of viral strains to these mutation frequencies. From a clinical viewpoint, we identified a significant negative impact of biallelic inactivation of PRDM1 (P = .027) in addition to the previously reported PRKCB mutations, indicating the importance of integrated genetic analysis. This study suggests that heterogeneous genetic abnormalities in ATLL depend on the viral strain as well as on the ethnic background. This warrants the need to develop therapeutic interventions considering regional characteristics. Targeted next‐generation sequencing and single nucleotide polymorphism array were applied to analyze aggressive adult T‐cell leukemia/lymphoma in Okinawa, which were not included in prior genomic studies. Our results showed that HTLV‐1 tax subgroup‐A was associated with high alteration frequencies in GATA3 and RHOA. Clinically, biallelic alterations, not heterozygous deletions or mutations, of PRDM1 were significantly associated with poor prognosis.

Background Significant differences in immune responses, prevalence or susceptibility of diseases and treatment responses have been described between males and females. Despite this, sex-differentiation analysis of the genetic architecture of inflammatory proteins is largely unexplored. We performed sex-stratified meta-analysis after protein quantitative trait loci (pQTL) mapping using inflammatory biomarkers profiled using targeted proteomics (Olink inflammatory panel) of two population-based cohorts of Europeans. Results Even though, around 67% of the pQTLs demonstrated shared effect between sexes, colocalization analysis identified two loci in the males ( LINC01135 and ITGAV ) and three loci ( CNOT10 , SRD5A2 , and LILRB5 ) in the females with evidence of sex-dependent modulation by pQTL variants. Furthermore, we identified pathways with relevant functions in the sex-biased pQTL variants. We also showed through cross-validation that the sex-specific pQTLs are linked with sex-specific phenotypic traits. Conclusion Our study demonstrates the relevance of genetic sex-stratified analysis in the context of genetic dissection of protein abundances among individuals and reveals that, sex-specific pQTLs might mediate sex-linked phenotypes. Identification of sex-specific pQTLs associated with sex-biased diseases can help realize the promise of individualized treatment.

Regulated transcription controls the diversity, developmental pathways and spatial organization of the hundreds of cell types that make up a mammal. Using single-molecule cDNA sequencing, we mapped transcription start sites (TSSs) and their usage in human and mouse primary cells, cell lines and tissues to produce a comprehensive overview of mammalian gene expression across the human body. We find that few genes are truly ‘housekeeping’, whereas many mammalian promoters are composite entities composed of several closely separated TSSs, with independent cell-type-specific expression profiles. TSSs specific to different cell types evolve at different rates, whereas promoters of broadly expressed genes are the most conserved. Promoter-based expression analysis reveals key transcription factors defining cell states and links them to binding-site motifs. The functions of identified novel transcripts can be predicted by coexpression and sample ontology enrichment analyses. The functional annotation of the mammalian genome 5 (FANTOM5) project provides comprehensive expression profiles and functional annotation of mammalian cell-type-specific transcriptomes with wide applications in biomedical research. A study from the FANTOM consortium using single-molecule cDNA sequencing of transcription start sites and their usage in human and mouse primary cells, cell lines and tissues reveals insights into the specificity and diversity of transcription patterns across different mammalian cell types. Mapping the human transcription FANTOM5 (standing for functional annotation of the mammalian genome 5) is the fifth major stage of a major international collaboration that aims to dissect the transcriptional regulatory networks that define every human cell type. Two Articles in this issue of Nature present some of the project's latest results. The first paper uses the FANTOM5 panel of tissue and primary cell samples to define an atlas of active, in vivo bidirectionally transcribed enhancers across the human body. These authors show that bidirectional capped RNAs are a signature feature of active enhancers and identify more than 40,000 enhancer candidates from over 800 human cell and tissue samples. The enhancer atlas is used to compare regulatory programs between different cell types and identify disease-associated regulatory SNPs, and will be a resource for studies on cell-type-specific enhancers. In the second paper, single-molecule sequencing is used to map human and mouse transcription start sites and their usage in a panel of distinct human and mouse primary cells, cell lines and tissues to produce the most comprehensive mammalian gene expression atlas to date. The data provide a plethora of insights into open reading frames and promoters across different cell types in addition to valuable annotation of mammalian cell-type-specific transcriptomes.

Indian Mahogany (Toona ciliata, Family: Meliaceae) is a fast-growing and multi-purpose timber species. The species is well adapted to sub-tropical climates and generally grows in moisture-prone areas. It is frequently naturalized throughout the western sub-Himalayan tract, valleys of the outer Himalayas, and Eastern and Western Ghats and also cultivated on a fairly large scale in the plains of India, but no information about SSR-based genetic diversity and population structuring of T. ciliata in the Indian context has been available till now. Notably, population genetic analysis of T. ciliata is important for its long-term conservation, management, and genetic improvement programs. Thus, the present study was conducted to characterize natural populations of T. ciliata using simple sequence repeat (SSR) markers. In total, 444 individuals collected from 15 distant geographical locations in the western Himalayas were analyzed with 10 SSR loci. A total of 71 alleles were generated, with a mean of seven alleles, which ranged from 4 to 12 alleles for individual marker loci. Overall, a low level of genetic diversity (mean He = 0.315, range = 0.251–0.366) and high genetic differentiation (FST = 0.338) were recorded for the analyzed populations. Genetic clustering and STRUCTURE analysis revealed a strong genetic structure where most analyzed populations were grouped into two major clusters, indicating the existence of two gene pools. Further, the partitioning of genetic variance was significant (p ≤ 0.001) which revealed 34% of genetic variance among the populations. The Mantel test was used to estimate the genetic distance in relation to horizontal and altitudinal geographical distance, but a non-significant correlation was obtained. The results indicated that genetic distance between populations is not influenced by horizontal and altitudinal geographical distance. Overall, the study on population genetic analysis of T. ciliata will be of paramount importance to the researchers, foresters, and policymakers for guiding future conservation decisions.