Symbiotic nitrogen fixation in members of the Fabaceae family is highly efficient and beneficial for global agriculture,but not all species in this family form root nodules with rhizobial bacteria.Nodulation mainly oc...Symbiotic nitrogen fixation in members of the Fabaceae family is highly efficient and beneficial for global agriculture,but not all species in this family form root nodules with rhizobial bacteria.Nodulation mainly occurs in plants belonging to the Papilionoideae and Caesalpinioideae subfamilies(Tederso0 et al.,2018;van Velzen et al.,2019).Nodulation mechanisms in Fabaceae are well studied(Yang et al.,2022),and genomic comparisons of nodulating and non-nodulating host species can provide valuable insights into the evolutionary and genetic basis of this key process.展开更多
BACKGROUND The evolutionary mutational changes of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)since its emergence in Chhattisgarh,India in 2020 have warranted the need for the characterization of every ...BACKGROUND The evolutionary mutational changes of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)since its emergence in Chhattisgarh,India in 2020 have warranted the need for the characterization of every lineage/sublineage that has evolved until February 2024.AIM To unravel the evolutionary pathway of SARS-CoV-2 in Chhattisgarh from 2020 to February 2024.METHODS A total of 635 coronavirus disease 2019 cases obtained between 2020 and February 2024 were investigated by whole genome sequencing.RESULTS Whole genome sequencing analysis identified the evolution of SARS-CoV-2 into seventeen lineages from 2020 to 2024.SARS-CoV-2 initially emerged in Chhattisgarh in its Alpha(B.1.1.7)variant in 2020.Thereafter,it continuously underwent periodical mutational changes in the spike gene to further differentiate into various lineages/sublineages,viz.,Kappa,Delta,BA.1,and BA.2 in 2021;the Omicron lineage(BA.5,BA.2.12.1,BA.2.75,BQ.1,and XBB)in 2022;the new Omicron lineage(XBB.1.5,XBB.1.16,XBB.1.9.1,and XBB.2.3)in 2023;and finally to JN.1 in January and February 2024.The predominant lineages over these 4 years were BA.1.1.7(Alpha)in 2020,B.1.617.2(Delta)in the period between 2021 and mid-2022,B.1.1.529(Omicron)in late 2022 to 2023,and Omicron-JN.1 in early 2024.The presently circulating JN.1 lineage was observed harboring exclusive predominant mutations of E4554K,A570V,P621A,and P1143 L with 99%CONCLUSION SARS-CoV-2 from 2020 to 2024 has evolved into 17 lineages/sublineages in Chhattisgarh.The presently circulating JN.1 harbored 40 mutations,especially E554K,A570V,P621S,and P1143 L,capacitating the virus with features of host cell entry,stability,replication,rapid transmissibility,and crucial immune evasion.Therefore,earlier immunity from either vaccination or prior infection may not protect against the current lineage and increases the possibility of future outbreaks.Thus,the periodical genomic surveillance of SARS-CoV-2 is essential for the genomic blueprint of the circulating virus,which may help in updating the vaccine strain and various basic research for developing appropriate therapeutics and diagnostics.展开更多
Genetic genealogy provides crucial insights into the complex biological relationships within contemporary and ancient human populations by analyzing shared alleles and chromosomal segments that are identical by descen...Genetic genealogy provides crucial insights into the complex biological relationships within contemporary and ancient human populations by analyzing shared alleles and chromosomal segments that are identical by descent to understand kinship,migration patterns,and population dynamics.Within forensic science,forensic investigative genetic genealogy(FIGG)has gained prominence by leveraging next-generation sequencing technologies and population-specific genomic resources,opening useful investigative avenues.In this review,we synthesize current knowledge,underscore recent advancements,and discuss the growing role of FIGG in forensic genomics.FIGG has been pivotal in revitalizing dormant inquiries and offering genetic leads in numerous cold cases.Its effectiveness relies on the extensive single-nucleotide polymorphism profiles contributed by individuals from diverse populations to specialized genomic databases.Advances in computational genomics and the growth of human genomic databases have spurred a profound shift in the application of genetic genealogy across forensics,anthropology,and ancient DNA studies.As the field progresses,FIGG is evolving from a nascent practice into a more sophisticated and specialized discipline,shaping the future of forensic investigations.展开更多
The yellow boxfish(Ostracion cubicus)exhibits a combination of derived morphological traits specialized for coral reef environments and ancestral characteristics,including a fused dermal plate.Contradictory evolutiona...The yellow boxfish(Ostracion cubicus)exhibits a combination of derived morphological traits specialized for coral reef environments and ancestral characteristics,including a fused dermal plate.Contradictory evolutionary evidence hinders true classification of O.cubicus.To clarify its evolutionary position within Tetraodontiformes,a chromosome-level genome assembly was generated,representing the most contiguous and complete genome to date for this lineage.Notably,O.cubicus possessed the largest genome within the order Tetraodontiformes,primarily due to extensive transposable element expansion.Phylogenetic analysis based on 19 whole genomes and 131 mitochondrial genomes resolved Tetraodontiformes into three major sister groups(Ostraciidae-Molidae,Tetraodontidae,and Balistidae-Monacanthidae).Comparative genomic evidence indicated that O.cubicus diverged early from the common ancestor of modern Tetraodontiformes and retained the highest number of HOX genes among surveyed taxa.Although overall genomic architecture was largely conserved,certain genetic and environmental changes may have contributed to its phenotypic adaptations,including climate cooling during the Miocene-Pliocene Transition,recent DNA and long interspersed nuclear element(LINE)transposon bursts,lineage-specific chromosomal rearrangements,and gene family expansion.Many positively selected genes and rapidly evolving genes were associated with skeletal development,including bmp7,egf7,and bmpr2.Transcriptomic comparisons between carapace and tail skin revealed various candidate genes and pathways related to carapace formation,such as postn,scpp1,and components of the TGF-βsignaling pathway.A derived amino acid substitution in eda,coupled with protein structural modeling,suggested potential molecular convergence in dermal plate formation among teleosts.These findings provide novel insights into the genomic and developmental basis of carapace evolution and coral reef-adaptation in O.cubicus,offering a strong case for evolutionary balance between genomic conservation with regulatory innovation to achieve coral reef specialization.展开更多
The plastid genome(plastome)represents an indispensable molecular resource for studying plant phylogeny and evolution.Although plastome size is much smaller than that of nuclear genomes,accurately and efficientlyannot...The plastid genome(plastome)represents an indispensable molecular resource for studying plant phylogeny and evolution.Although plastome size is much smaller than that of nuclear genomes,accurately and efficientlyannotating and utilizing plastome sequences remain challenging.Therefore,a streamlined phylogenomic pipeline spanning plastome annotation,phylogenetic reconstruction and comparative genomics would greatly facilitate research utilizing this important organellar genome.Here,we develop PlastidHub,a novel web application employing innovative tools to analyze plastome sequences.In comparison with existing tools,key novel functionalities in PlastidHub include:(1)standardization of quadripartite structure;(2)improvement of annotation flexibility and consistency;(3)quantitative assessment of annotation completeness;(4)diverse extraction modes for canonical and specialized sequences;(5)intelligent screening of molecular markers for biodiversity studies;(6)genelevel visual comparison of structural variations and annotation completeness.PlastidHub features cloud-based web applications that do not require users to install,update,or maintain tools;detailed help documents including user guides,test examples,a static pop-up prompt box,and dynamic pop-up warning prompts when entering unreasonable parameter values;batch processing capabilities for all tools;intermediate results for secondary use;and easy-to-operate task flows between fileupload and download.A key feature of PlastidHub is its interrelated task-based user interface design.Give that PlastidHub is easy to use without specialized computational skills or resources,this new platform should be widely used among botanists and evolutionary biologists,improving and expediting research employing the plastome.PlastidHub is available at https://www.plastidhub.cn.展开更多
The principle of genomic selection(GS) entails estimating breeding values(BVs) by summing all the SNP polygenic effects. The visible/near-infrared spectroscopy(VIS/NIRS) wavelength and abundance values can directly re...The principle of genomic selection(GS) entails estimating breeding values(BVs) by summing all the SNP polygenic effects. The visible/near-infrared spectroscopy(VIS/NIRS) wavelength and abundance values can directly reflect the concentrations of chemical substances, and the measurement of meat traits by VIS/NIRS is similar to the processing of genomic selection data by summing all ‘polygenic effects' associated with spectral feature peaks. Therefore, it is meaningful to investigate the incorporation of VIS/NIRS information into GS models to establish an efficient and low-cost breeding model. In this study, we measured 6 meat quality traits in 359Duroc×Landrace×Yorkshire pigs from Guangxi Zhuang Autonomous Region, China, and genotyped them with high-density SNP chips. According to the completeness of the information for the target population, we proposed 4breeding strategies applied to different scenarios: Ⅰ, only spectral and genotypic data exist for the target population;Ⅱ, only spectral data exist for the target population;Ⅲ, only spectral and genotypic data but with different prediction processes exist for the target population;and Ⅳ, only spectral and phenotypic data exist for the target population.The 4 scenarios were used to evaluate the genomic estimated breeding value(GEBV) accuracy by increasing the VIS/NIR spectral information. In the results of the 5-fold cross-validation, the genetic algorithm showed remarkable potential for preselection of feature wavelengths. The breeding efficiency of Strategies Ⅱ, Ⅲ, and Ⅳ was superior to that of traditional GS for most traits, and the GEBV prediction accuracy was improved by 32.2, 40.8 and 15.5%, respectively on average. Among them, the prediction accuracy of Strategy Ⅱ for fat(%) even improved by 50.7% compared to traditional GS. The GEBV prediction accuracy of Strategy Ⅰ was nearly identical to that of traditional GS, and the fluctuation range was less than 7%. Moreover, the breeding cost of the 4 strategies was lower than that of traditional GS methods, with Strategy Ⅳ being the lowest as it did not require genotyping.Our findings demonstrate that GS methods based on VIS/NIRS data have significant predictive potential and are worthy of further research to provide a valuable reference for the development of effective and affordable breeding strategies.展开更多
Artificial intelligence(AI)is significantly advancing precision medicine,particularly in the fields of immunogenomics,radiomics,and pathomics.In immunogenomics,AI can process vast amounts of genomic and multi-omic dat...Artificial intelligence(AI)is significantly advancing precision medicine,particularly in the fields of immunogenomics,radiomics,and pathomics.In immunogenomics,AI can process vast amounts of genomic and multi-omic data to identify biomarkers associated with immunotherapy responses and disease prognosis,thus providing strong support for personalized treatments.In radiomics,AI can analyze high-dimensional features from computed tomography(CT),magnetic resonance imaging(MRI),and positron emission tomography/computed tomography(PET/CT)images to discover imaging biomarkers associated with tumor heterogeneity,treatment response,and disease progression,thereby enabling non-invasive,real-time assessments for personalized therapy.Pathomics leverages AI for deep analysis of digital pathology images,and can uncover subtle changes in tissue microenvironments,cellular characteristics,and morphological features,and offer unique insights into immunotherapy response prediction and biomarker discovery.These AI-driven technologies not only enhance the speed,accuracy,and robustness of biomarker discovery but also significantly improve the precision,personalization,and effectiveness of clinical treatments,and are driving a shift from empirical to precision medicine.Despite challenges such as data quality,model interpretability,integration of multi-modal data,and privacy protection,the ongoing advancements in AI,coupled with interdisciplinary collaboration,are poised to further enhance AI’s roles in biomarker discovery and immunotherapy response prediction.These improvements are expected to lead to more accurate,personalized treatment strategies and ultimately better patient outcomes,marking a significant step forward in the evolution of precision medicine.展开更多
Preserving genetic diversity is crucial for the long-term survival of wild plant species,yet many remain at risk of genetic erosion due to small population sizes and habitat fragmentation.Here,we present a comparative...Preserving genetic diversity is crucial for the long-term survival of wild plant species,yet many remain at risk of genetic erosion due to small population sizes and habitat fragmentation.Here,we present a comparative genomic study of the critically endangered Oreocharis esquirolii(Gesneriaceae)and its widespread congener O.maximowiczii.We assembled and annotated chromosome-level reference genomes for both species and generated whole-genome resequencing data from 28 O.esquirolii and 79 O.maximowiczii individuals.Our analyses reveal substantially lower genetic diversity and higher inbreeding in O.esquirolii,despite its overall reduced mutational burden.Notably,O.esquirolii exhibits an elevated proportion of strongly deleterious mutations relative to O.maximowiczii,suggesting that limited opportunities for purging have allowed these variants to accumulate.These contrasting genomic profileslikely reflectdivergent demographic histories,with O.esquirolii having experienced severe bottlenecks and protracted population decline.Collectively,our findingshighlight the critically endangered status of O.esquirolii,characterized by diminished genetic diversity,pronounced inbreeding,and reduced ability to eliminate deleterious alleles.This study provides valuable genomic resources for the Gesneriaceae family and underscores the urgent need for targeted conservation measures,including habitat protection and ex situ preservation efforts,to mitigate the extinction risk facing O.esquirolii and potentially other threatened congeners.展开更多
Common bean(Phaseolus vulgaris L.)is a vital source of protein and essential nutrients for human consumption and plays a key role in sustainable agriculture due to its nitrogen-fixing ability(Nadeem et al.,2021).Kidne...Common bean(Phaseolus vulgaris L.)is a vital source of protein and essential nutrients for human consumption and plays a key role in sustainable agriculture due to its nitrogen-fixing ability(Nadeem et al.,2021).Kidney beans,a subcategory of dry common beans,are highly valued for their rich protein,dietary fiber,low fat content,and various trace elements(Garcia-Cordero et al.,2021).Despite the release of several de novo genome assemblies(Goodstein et al.,2012;Schmutz et al.,2014;Vlasova et al.,2016;Cortinovis et al.,2024),existing common bean genomes remain incomplete,particularly in complex regions such as centromeres and telomeres,limiting a comprehensive understanding of the genomic landscape.展开更多
Sorghum,renowned for its substantial biomass production and remarkable tolerance to various stresses,possesses extensive gene resources and phenotypic variations.A comprehensive understanding of the genetic basis unde...Sorghum,renowned for its substantial biomass production and remarkable tolerance to various stresses,possesses extensive gene resources and phenotypic variations.A comprehensive understanding of the genetic basis underlying complex agronomic traits is essential for unlocking the potential of sorghum in addressing food and feed security and utilizing marginal lands.In this context,we provide an overview of the major trends in genomic resource studies focusing on key agronomic traits over the past decade,accompanied by a summary of functional genomic platforms.We also delve into the molecular functions and regulatory networks of impactful genes for important agricultural traits.Lastly,we discuss and synthesize the current challenges and prospects for advancing molecular design breeding by gene-editing and polymerization of the excellent alleles,with the aim of accelerating the development of desired sorghum varieties.展开更多
Cotton is an essential agricultural commodity,but its global yield is greatly affected by climate change,which poses a serious threat to the agriculture sector.This review aims to provide an overview of the impact of ...Cotton is an essential agricultural commodity,but its global yield is greatly affected by climate change,which poses a serious threat to the agriculture sector.This review aims to provide an overview of the impact of climate change on cotton production and the use of genomic approaches to increase stress tolerance in cotton.This paper discusses the effects of rising temperatures,changing precipitation patterns,and extreme weather events on cotton yield.It then explores various genomic strategies,such as genomic selection and marker-assisted selection,which can be used to develop stress-tolerant cotton varieties.The review emphasizes the need for interdisciplinary research efforts and policy interventions to mitigate the adverse effects of climate change on cotton production.Furthermore,this paper presents advanced prospects,including genomic selection,gene editing,multi-omics integration,highthroughput phenotyping,genomic data sharing,climate-informed breeding,and phenomics-assisted genomic selection,for enhancing stress resilience in cotton.Those innovative approaches can assist cotton researchers and breeders in developing highly resilient cotton varieties capable of withstanding the challenges posed by climate change,ensuring the sustainable and prosperous future of cotton production.展开更多
Acral melanoma,the most common melanoma subtype in East Asia,is associated with a poor prognosis.This study aims to comprehensively analyze the genomic characteristics of acral melanoma in East Asians.We conduct whole...Acral melanoma,the most common melanoma subtype in East Asia,is associated with a poor prognosis.This study aims to comprehensively analyze the genomic characteristics of acral melanoma in East Asians.We conduct whole-genome sequencing of 55 acral melanoma tumors and perform data mining with relevant clinical data.Our findings reveal a unique mutational profile in East Asian acral melanoma,characterized by fewer point mutations and structural variations,a higher prevalence of NRAS mutations,and a lower frequency of BRAF mutations compared to patients of European descent.Notably,we identify previously underestimated ultraviolet radiation signatures and their significant association with BRAF and NRAS mutations.Structural rearrangement signatures indicate distinct mutational processes in BRAF-driven versus NRAS-driven tumors.We also find that homologous recombination deficiency with MAPK pathway mutations correlated with poor prognosis.The structural variations and amplifications in EP300,TERT,RAC1,and LZTR1 point to potential therapeutic targets tailored to East Asian populations.The high prevalence of whole-genome duplication events in BRAF/NRAS-mutated tumors suggests a synergistic carcinogenic effect that warrants further investigation.In summary,our study provides important insights into the genetic underpinnings of acral melanoma in East Asians,creating opportunities for targeted therapies.展开更多
Genomic medicine has evolved significantly,merging centuries of scientific progress with modern molecular biology and clinical care.It utilizes knowledge of the human genome to enhance disease prevention,diagnosis,tre...Genomic medicine has evolved significantly,merging centuries of scientific progress with modern molecular biology and clinical care.It utilizes knowledge of the human genome to enhance disease prevention,diagnosis,treatment,and potential reversal.Genomic medicine in hepatology is particularly promising due to the crucial role of the liver in several metabolic processes and its association with diseases such as metabolic dysfunction-associated steatotic liver disease,type 2 diabetes mellitus,liver cirrhosis,and cardiovascular conditions.The mid-20th century witnessed a paradigm shift in medicine,marked by the emergence of molecular biology,which enabled a deeper understanding of gene expression and regulation.This connection between basic science and clinical practice has enhanced our knowledge of the role of gene-environment interactions in the onset and progression of liver diseases.In Latin America,including Mexico,with its genetically diverse and admixed populations,genomic medicine provides a foundation for personalized and culturally relevant health strategies.This review highlights the need for genomic medicine,examining its historical evolution,integration into hepatology in Mexico,and its potential applications in the prevention of chronic diseases.It emphasizes the importance of training in genomic literacy and interdisciplinary education in medical training,particularly in the field of hepatology,with a focus on genomic medicine expertise.展开更多
As a high-value eudicot family,many famous horticultural crop genomes have been deciphered in Oleaceae.However,there are currently no bioinformatics platforms focused on empowering genome research in Oleaceae.Herein,w...As a high-value eudicot family,many famous horticultural crop genomes have been deciphered in Oleaceae.However,there are currently no bioinformatics platforms focused on empowering genome research in Oleaceae.Herein,we developed the first comprehensive Oleaceae Genome Research Platform(OGRP,https://oleaceae.cgrpoee.top/).In OGRP,70 genomes of 10 Oleaceae species and 46 eudicots and 366 transcriptomes involving 18 Oleaceae plant tissues can be obtained.We built 34 window-operated bioinformatics tools,collected 38 professional practical software programs,and proposed 3 new pipelines,namely ancient polyploidization identification,ancestral karyotype reconstruction,and gene family evolution.Employing these pipelines to reanalyze the Oleaceae genomes,we clarified the polyploidization,reconstructed the ancestral karyotypes,and explored the effects of paleogenome evolution on genes with specific biological regulatory roles.Significantly,we generated a series of comparative genomic resources focusing on the Oleaceae,comprising 108 genomic synteny dot plots,1952225 collinear gene pairs,multiple genome alignments,and imprints of paleochromosome rearrangements.Moreover,in Oleaceae genomes,researchers can efficiently search for 1785987 functional annotations,22584 orthogroups,29582 important trait genes from 74 gene families,12664 transcription factor-related genes,9178872 transposable elements,and all involved regulatory pathways.In addition,we provided downloads and usage instructions for the tools,a species encyclopedia,ecological resources,relevant literatures,and external database links.In short,ORGP integrates rich data resources and powerful analytical tools with the characteristic of continuous updating,which can efficiently empower genome research and agricultural breeding in Oleaceae and other plants.展开更多
Dear Editor,Viruses transmitted by arthropods(arboviruses)are highly diverse,both genetically and in terms of host insect species.They are widely distributed across the virosphere,with significant representation in th...Dear Editor,Viruses transmitted by arthropods(arboviruses)are highly diverse,both genetically and in terms of host insect species.They are widely distributed across the virosphere,with significant representation in the family Rhabdoviridae,which encompasses a total of 580 different species divided into 4 sub-families and 62 genera(ICTV:https://talk.ictvonline.org/)(Kuhn et al.,2023;Walker et al.,2022).展开更多
Objective:Lymphovascular invasion(LVI)is a crucial step in metastasis and is closely associated with poor prognosis in patients with breast cancer.However,its clinical and molecular characteristics remain insufficient...Objective:Lymphovascular invasion(LVI)is a crucial step in metastasis and is closely associated with poor prognosis in patients with breast cancer.However,its clinical and molecular characteristics remain insufficiently defined.We aimed to identify molecular targets for LVI-positive(LVI+)breast cancer and predict patient prognosis via the analysis of genomic variations using targeted sequencing.Methods:We established a large-scale targeted sequencing cohort of 4,079 breast cancer samples,which included 3,159 early-stage and locally advanced patients with available LVI statuses.Comparisons of somatic mutation frequencies and germline pathogenic/likely pathogenic(P/LP)mutation frequencies,mutational signature analyses,and mutual exclusivity and co-occurrence analyses were performed to identify key genomic features involved in LVI+patients.Additionally,Kaplan-Meier survival analysis was conducted to further explore the prognostic value of co-mutations in LVI+cases.Results:We observed that LVI+patients with the hormone receptor-positive/human epidermal growth factor receptor 2-negative(HR+/HER2-)and triple-negative breast cancer(TNBC)subtypes exhibited worse disease-free survival.Notably,HR+/HER2-and HER2+breast cancer patients with LVI displayed distinct genomic features compared with LVI-tumors.Specifically,LVI+HR+/HER2-tumors exhibited greater frequencies of somatic mutations in TP53 and ESR1,germline BRCA2 P/LP variations,and an enrichment of clock-like single-base substitution(SBS)1 mutational signatures.In contrast,LVI+HER2+tumors demonstrated a higher incidence of somatic PIK3CA mutations and increased activity of the apolipoprotein B m RNA editing enzyme catalytic polypeptide(APOBEC)-associated SBS2 signature.Furthermore,we revealed that the co-mutation of TP53 and NF1 could serve as a potential prognostic marker for LVI+HR+/HER2-patients.Conclusions:Our findings provide a comprehensive overview of the genomic characteristics of LVI in breast cancer,thereby offering insights that may help in refining precision treatment strategies for LVI+breast cancer patients.展开更多
Tetracentron sinense is a‘living fossil’tree in East Asia.Understanding how this‘living fossil’responds to climate change and adapts to local environments is critical for its conservation.Here,we used resequenced ...Tetracentron sinense is a‘living fossil’tree in East Asia.Understanding how this‘living fossil’responds to climate change and adapts to local environments is critical for its conservation.Here,we used resequenced genomes to clarify the evolutionary history and adaptive potential of T.sinense.We identifiedsix divergent lineages in T.sinense:three lineages from southwestern China(Yunnan Province)and three lineages from the central subtropical region of China.Additionally,we detected hybridization events between some adjacent lineages.Demographic analysis revealed that over the past 10,000 years the effective population size(Ne)of three T.sinense lineages(i.e.,NORTH,SWEST,and YNWEST)increased after their last bottleneck and then remained stable,whereas that of the remaining three lineages(i.e.,YSEAST,YC,and EAST)declined steadily.The decline in effective population size in the Yunnan lineages aligned well with the decrease in genome-wide diversity and a significantincrease in the frequency of runs of homozygosity.Deleterious variants and positively selected sites were involved in the evolution of different lineages.Further,genotype–environment association(GEA)analyses indicated adaptation to temperature-and precipitation-related factors.Genomic offset analyses found the most vulnerable populations,while SC and SC-yad were predicted to better handle extreme changes.Our findingsprovide insights into the evolutionary history and conservation of T.sinense and enhance our understanding of the evolution of living fossil species.展开更多
Background Genomic prediction has revolutionized animal breeding,with GBLUP being the most widely used prediction model.In theory,the accuracy of genomic prediction could be improved by incorporating information from ...Background Genomic prediction has revolutionized animal breeding,with GBLUP being the most widely used prediction model.In theory,the accuracy of genomic prediction could be improved by incorporating information from QTL.This strategy could be especially beneficial for machine learning models that are able to distinguish informative from uninformative features.The objective of this study was to assess the benefit of incorporating QTL genotypes in GBLUP and machine learning models.This study simulated a selected livestock population where QTL and their effects were known.We used four genomic prediction models,GBLUP,(weighted)2GBLUP,random forest(RF),and support vector regression(SVR)to predict breeding values of young animals,and considered different scenarios that varied in the proportion of genetic variance explained by the included QTL.Results 2GBLUP resulted in the highest accuracy.Its accuracy increased when the included QTL explained up to 80%of the genetic variance,after which the accuracy dropped.With a weighted 2GBLUP model,the accuracy always increased when more QTL were included.Prediction accuracy of GBLUP was consistently higher than SVR,and the accuracy for both models slightly increased with more QTL information included.The RF model resulted in the lowest prediction accuracy,and did not improve by including QTL information.Conclusions Our results show that incorporating QTL information in GBLUP and SVR can improve prediction accuracy,but the extent of improvement varies across models.RF had a much lower prediction accuracy than the other models and did not show improvements when QTL information was added.Two possible reasons for this result are that the data structure in our data does not allow RF to fully realize its potential and that RF is not designed well for this particular prediction problem.Our study highlighted the importance of selecting appropriate models for genomic prediction and underscored the potential limitations of machine learning models when applied to genomic prediction in livestock.展开更多
基金supported by the National Natural Science Foundation of China(No.32160142)Guangxi Natural Science Foundation(No.2023GXNSFDA026034)+3 种基金State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources(SKLCUSAb202302)to H.W.,the National Natural Science Foundation of China(No.32460062)to Y.L.,and 1+9 Leading the Charge with Open Competition'project of Sichuan Academy of Agricultural Sciences(1+9KJGG010)Fruit tree breeding project in Sichuan Province(2021YFYZ0023)to H.X.
文摘Symbiotic nitrogen fixation in members of the Fabaceae family is highly efficient and beneficial for global agriculture,but not all species in this family form root nodules with rhizobial bacteria.Nodulation mainly occurs in plants belonging to the Papilionoideae and Caesalpinioideae subfamilies(Tederso0 et al.,2018;van Velzen et al.,2019).Nodulation mechanisms in Fabaceae are well studied(Yang et al.,2022),and genomic comparisons of nodulating and non-nodulating host species can provide valuable insights into the evolutionary and genetic basis of this key process.
文摘BACKGROUND The evolutionary mutational changes of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)since its emergence in Chhattisgarh,India in 2020 have warranted the need for the characterization of every lineage/sublineage that has evolved until February 2024.AIM To unravel the evolutionary pathway of SARS-CoV-2 in Chhattisgarh from 2020 to February 2024.METHODS A total of 635 coronavirus disease 2019 cases obtained between 2020 and February 2024 were investigated by whole genome sequencing.RESULTS Whole genome sequencing analysis identified the evolution of SARS-CoV-2 into seventeen lineages from 2020 to 2024.SARS-CoV-2 initially emerged in Chhattisgarh in its Alpha(B.1.1.7)variant in 2020.Thereafter,it continuously underwent periodical mutational changes in the spike gene to further differentiate into various lineages/sublineages,viz.,Kappa,Delta,BA.1,and BA.2 in 2021;the Omicron lineage(BA.5,BA.2.12.1,BA.2.75,BQ.1,and XBB)in 2022;the new Omicron lineage(XBB.1.5,XBB.1.16,XBB.1.9.1,and XBB.2.3)in 2023;and finally to JN.1 in January and February 2024.The predominant lineages over these 4 years were BA.1.1.7(Alpha)in 2020,B.1.617.2(Delta)in the period between 2021 and mid-2022,B.1.1.529(Omicron)in late 2022 to 2023,and Omicron-JN.1 in early 2024.The presently circulating JN.1 lineage was observed harboring exclusive predominant mutations of E4554K,A570V,P621A,and P1143 L with 99%CONCLUSION SARS-CoV-2 from 2020 to 2024 has evolved into 17 lineages/sublineages in Chhattisgarh.The presently circulating JN.1 harbored 40 mutations,especially E554K,A570V,P621S,and P1143 L,capacitating the virus with features of host cell entry,stability,replication,rapid transmissibility,and crucial immune evasion.Therefore,earlier immunity from either vaccination or prior infection may not protect against the current lineage and increases the possibility of future outbreaks.Thus,the periodical genomic surveillance of SARS-CoV-2 is essential for the genomic blueprint of the circulating virus,which may help in updating the vaccine strain and various basic research for developing appropriate therapeutics and diagnostics.
基金supported by the National Natural Science Foundation of China(82202078)the Major Project of the National Social Science Foundation of China(23&ZD203)+3 种基金the Open Project of the Key Laboratory of Forensic Genetics of the Ministry of Public Security(2022FGKFKT05)the Center for Archaeological Science of Sichuan University(23SASA01)the 1‧3‧5 Project for Disciplines of Excellence,West China Hospital,Sichuan University(ZYJC20002)the Sichuan Science and Technology Program(2024NSFSC1518).
文摘Genetic genealogy provides crucial insights into the complex biological relationships within contemporary and ancient human populations by analyzing shared alleles and chromosomal segments that are identical by descent to understand kinship,migration patterns,and population dynamics.Within forensic science,forensic investigative genetic genealogy(FIGG)has gained prominence by leveraging next-generation sequencing technologies and population-specific genomic resources,opening useful investigative avenues.In this review,we synthesize current knowledge,underscore recent advancements,and discuss the growing role of FIGG in forensic genomics.FIGG has been pivotal in revitalizing dormant inquiries and offering genetic leads in numerous cold cases.Its effectiveness relies on the extensive single-nucleotide polymorphism profiles contributed by individuals from diverse populations to specialized genomic databases.Advances in computational genomics and the growth of human genomic databases have spurred a profound shift in the application of genetic genealogy across forensics,anthropology,and ancient DNA studies.As the field progresses,FIGG is evolving from a nascent practice into a more sophisticated and specialized discipline,shaping the future of forensic investigations.
基金supported by the Basic and Applied Basic Research Foundation of Guangdong Province(2020A1515110882)National Science Fund for Distinguished Young Scholars(32225049)。
文摘The yellow boxfish(Ostracion cubicus)exhibits a combination of derived morphological traits specialized for coral reef environments and ancestral characteristics,including a fused dermal plate.Contradictory evolutionary evidence hinders true classification of O.cubicus.To clarify its evolutionary position within Tetraodontiformes,a chromosome-level genome assembly was generated,representing the most contiguous and complete genome to date for this lineage.Notably,O.cubicus possessed the largest genome within the order Tetraodontiformes,primarily due to extensive transposable element expansion.Phylogenetic analysis based on 19 whole genomes and 131 mitochondrial genomes resolved Tetraodontiformes into three major sister groups(Ostraciidae-Molidae,Tetraodontidae,and Balistidae-Monacanthidae).Comparative genomic evidence indicated that O.cubicus diverged early from the common ancestor of modern Tetraodontiformes and retained the highest number of HOX genes among surveyed taxa.Although overall genomic architecture was largely conserved,certain genetic and environmental changes may have contributed to its phenotypic adaptations,including climate cooling during the Miocene-Pliocene Transition,recent DNA and long interspersed nuclear element(LINE)transposon bursts,lineage-specific chromosomal rearrangements,and gene family expansion.Many positively selected genes and rapidly evolving genes were associated with skeletal development,including bmp7,egf7,and bmpr2.Transcriptomic comparisons between carapace and tail skin revealed various candidate genes and pathways related to carapace formation,such as postn,scpp1,and components of the TGF-βsignaling pathway.A derived amino acid substitution in eda,coupled with protein structural modeling,suggested potential molecular convergence in dermal plate formation among teleosts.These findings provide novel insights into the genomic and developmental basis of carapace evolution and coral reef-adaptation in O.cubicus,offering a strong case for evolutionary balance between genomic conservation with regulatory innovation to achieve coral reef specialization.
基金the Natural Science Foundation of Shandong Province(ZR2020QC022)the Science and Technology Basic Resources Investigation Program of China(No.2019FY100900)+2 种基金the Major Program for Basic Research Project of Yunnan Province(202401BC070001)Yunnan Revitalization Talent Support Program:Yunling Scholar Project to Tingshuang Yithe open research project of“Cross Cooperative Team”of the Germplasm Bank of Wild Species,Kunming Institute of Botany,Chinese Academy of Sciences.
文摘The plastid genome(plastome)represents an indispensable molecular resource for studying plant phylogeny and evolution.Although plastome size is much smaller than that of nuclear genomes,accurately and efficientlyannotating and utilizing plastome sequences remain challenging.Therefore,a streamlined phylogenomic pipeline spanning plastome annotation,phylogenetic reconstruction and comparative genomics would greatly facilitate research utilizing this important organellar genome.Here,we develop PlastidHub,a novel web application employing innovative tools to analyze plastome sequences.In comparison with existing tools,key novel functionalities in PlastidHub include:(1)standardization of quadripartite structure;(2)improvement of annotation flexibility and consistency;(3)quantitative assessment of annotation completeness;(4)diverse extraction modes for canonical and specialized sequences;(5)intelligent screening of molecular markers for biodiversity studies;(6)genelevel visual comparison of structural variations and annotation completeness.PlastidHub features cloud-based web applications that do not require users to install,update,or maintain tools;detailed help documents including user guides,test examples,a static pop-up prompt box,and dynamic pop-up warning prompts when entering unreasonable parameter values;batch processing capabilities for all tools;intermediate results for secondary use;and easy-to-operate task flows between fileupload and download.A key feature of PlastidHub is its interrelated task-based user interface design.Give that PlastidHub is easy to use without specialized computational skills or resources,this new platform should be widely used among botanists and evolutionary biologists,improving and expediting research employing the plastome.PlastidHub is available at https://www.plastidhub.cn.
基金supported by the National Natural Science Foundation of China(32160782 and 32060737).
文摘The principle of genomic selection(GS) entails estimating breeding values(BVs) by summing all the SNP polygenic effects. The visible/near-infrared spectroscopy(VIS/NIRS) wavelength and abundance values can directly reflect the concentrations of chemical substances, and the measurement of meat traits by VIS/NIRS is similar to the processing of genomic selection data by summing all ‘polygenic effects' associated with spectral feature peaks. Therefore, it is meaningful to investigate the incorporation of VIS/NIRS information into GS models to establish an efficient and low-cost breeding model. In this study, we measured 6 meat quality traits in 359Duroc×Landrace×Yorkshire pigs from Guangxi Zhuang Autonomous Region, China, and genotyped them with high-density SNP chips. According to the completeness of the information for the target population, we proposed 4breeding strategies applied to different scenarios: Ⅰ, only spectral and genotypic data exist for the target population;Ⅱ, only spectral data exist for the target population;Ⅲ, only spectral and genotypic data but with different prediction processes exist for the target population;and Ⅳ, only spectral and phenotypic data exist for the target population.The 4 scenarios were used to evaluate the genomic estimated breeding value(GEBV) accuracy by increasing the VIS/NIR spectral information. In the results of the 5-fold cross-validation, the genetic algorithm showed remarkable potential for preselection of feature wavelengths. The breeding efficiency of Strategies Ⅱ, Ⅲ, and Ⅳ was superior to that of traditional GS for most traits, and the GEBV prediction accuracy was improved by 32.2, 40.8 and 15.5%, respectively on average. Among them, the prediction accuracy of Strategy Ⅱ for fat(%) even improved by 50.7% compared to traditional GS. The GEBV prediction accuracy of Strategy Ⅰ was nearly identical to that of traditional GS, and the fluctuation range was less than 7%. Moreover, the breeding cost of the 4 strategies was lower than that of traditional GS methods, with Strategy Ⅳ being the lowest as it did not require genotyping.Our findings demonstrate that GS methods based on VIS/NIRS data have significant predictive potential and are worthy of further research to provide a valuable reference for the development of effective and affordable breeding strategies.
基金supported by grants from the National Natural Science Foundation of China(Grant No.82272008)The Science&Technology Development Fund of Tianjin Education Commission for Higher Education(Grant No.2021KJ194)Tianjin Key Medical Discipline(Specialty)Construction Project(Grant No.TJYXZDXK-009A).
文摘Artificial intelligence(AI)is significantly advancing precision medicine,particularly in the fields of immunogenomics,radiomics,and pathomics.In immunogenomics,AI can process vast amounts of genomic and multi-omic data to identify biomarkers associated with immunotherapy responses and disease prognosis,thus providing strong support for personalized treatments.In radiomics,AI can analyze high-dimensional features from computed tomography(CT),magnetic resonance imaging(MRI),and positron emission tomography/computed tomography(PET/CT)images to discover imaging biomarkers associated with tumor heterogeneity,treatment response,and disease progression,thereby enabling non-invasive,real-time assessments for personalized therapy.Pathomics leverages AI for deep analysis of digital pathology images,and can uncover subtle changes in tissue microenvironments,cellular characteristics,and morphological features,and offer unique insights into immunotherapy response prediction and biomarker discovery.These AI-driven technologies not only enhance the speed,accuracy,and robustness of biomarker discovery but also significantly improve the precision,personalization,and effectiveness of clinical treatments,and are driving a shift from empirical to precision medicine.Despite challenges such as data quality,model interpretability,integration of multi-modal data,and privacy protection,the ongoing advancements in AI,coupled with interdisciplinary collaboration,are poised to further enhance AI’s roles in biomarker discovery and immunotherapy response prediction.These improvements are expected to lead to more accurate,personalized treatment strategies and ultimately better patient outcomes,marking a significant step forward in the evolution of precision medicine.
基金supported by National Key R&D Program of China(2024YFF1307400)Guangdong S&T Program(2022B1111230001).
文摘Preserving genetic diversity is crucial for the long-term survival of wild plant species,yet many remain at risk of genetic erosion due to small population sizes and habitat fragmentation.Here,we present a comparative genomic study of the critically endangered Oreocharis esquirolii(Gesneriaceae)and its widespread congener O.maximowiczii.We assembled and annotated chromosome-level reference genomes for both species and generated whole-genome resequencing data from 28 O.esquirolii and 79 O.maximowiczii individuals.Our analyses reveal substantially lower genetic diversity and higher inbreeding in O.esquirolii,despite its overall reduced mutational burden.Notably,O.esquirolii exhibits an elevated proportion of strongly deleterious mutations relative to O.maximowiczii,suggesting that limited opportunities for purging have allowed these variants to accumulate.These contrasting genomic profileslikely reflectdivergent demographic histories,with O.esquirolii having experienced severe bottlenecks and protracted population decline.Collectively,our findingshighlight the critically endangered status of O.esquirolii,characterized by diminished genetic diversity,pronounced inbreeding,and reduced ability to eliminate deleterious alleles.This study provides valuable genomic resources for the Gesneriaceae family and underscores the urgent need for targeted conservation measures,including habitat protection and ex situ preservation efforts,to mitigate the extinction risk facing O.esquirolii and potentially other threatened congeners.
基金supported by the National Natural Science Foundation of China(32241045,32241046,32241038)the Major Special Science and Technology Projects in Shanxi Province(202101140601027)+3 种基金Shanxi Provincial Agricultural Key Technologies Breakthrough Project(NYGG01)Doctoral Research Starting Project at Shanxi Agricultural University(2024BQ77)the National Key Research and Development Program of China(2023YFD1202705/2023YFD120270503,2023YFD1202703/2023YFD1202703-4)Shanxi HouJi Laboratory Self-proposed Research Project(202304010930003/202304010930003-03).
文摘Common bean(Phaseolus vulgaris L.)is a vital source of protein and essential nutrients for human consumption and plays a key role in sustainable agriculture due to its nitrogen-fixing ability(Nadeem et al.,2021).Kidney beans,a subcategory of dry common beans,are highly valued for their rich protein,dietary fiber,low fat content,and various trace elements(Garcia-Cordero et al.,2021).Despite the release of several de novo genome assemblies(Goodstein et al.,2012;Schmutz et al.,2014;Vlasova et al.,2016;Cortinovis et al.,2024),existing common bean genomes remain incomplete,particularly in complex regions such as centromeres and telomeres,limiting a comprehensive understanding of the genomic landscape.
基金the National Science Foundation for Young Scientists of China(32201780)the Fundamental Research Fund for the Central Universities(77000–12240011)+2 种基金Shenzhen Postdoctoral Funding Project(szbo202410)the National Natural Science Foundation of China(32241045 and 32241038)the National Key Research and Development Program of China(2022YFD1500503,2023YFD1200700,and 2023YFD1200704).
文摘Sorghum,renowned for its substantial biomass production and remarkable tolerance to various stresses,possesses extensive gene resources and phenotypic variations.A comprehensive understanding of the genetic basis underlying complex agronomic traits is essential for unlocking the potential of sorghum in addressing food and feed security and utilizing marginal lands.In this context,we provide an overview of the major trends in genomic resource studies focusing on key agronomic traits over the past decade,accompanied by a summary of functional genomic platforms.We also delve into the molecular functions and regulatory networks of impactful genes for important agricultural traits.Lastly,we discuss and synthesize the current challenges and prospects for advancing molecular design breeding by gene-editing and polymerization of the excellent alleles,with the aim of accelerating the development of desired sorghum varieties.
基金supported by major national R&D projects(No.2023ZD04040-01)National Natural Science Foundation of China(No.5201101621)National Key R&D Plan(No.2022YFD1200304).
文摘Cotton is an essential agricultural commodity,but its global yield is greatly affected by climate change,which poses a serious threat to the agriculture sector.This review aims to provide an overview of the impact of climate change on cotton production and the use of genomic approaches to increase stress tolerance in cotton.This paper discusses the effects of rising temperatures,changing precipitation patterns,and extreme weather events on cotton yield.It then explores various genomic strategies,such as genomic selection and marker-assisted selection,which can be used to develop stress-tolerant cotton varieties.The review emphasizes the need for interdisciplinary research efforts and policy interventions to mitigate the adverse effects of climate change on cotton production.Furthermore,this paper presents advanced prospects,including genomic selection,gene editing,multi-omics integration,highthroughput phenotyping,genomic data sharing,climate-informed breeding,and phenomics-assisted genomic selection,for enhancing stress resilience in cotton.Those innovative approaches can assist cotton researchers and breeders in developing highly resilient cotton varieties capable of withstanding the challenges posed by climate change,ensuring the sustainable and prosperous future of cotton production.
基金supported by the National Key Research and Development Program(2023YFC2506404)the Natural Science Foundation of China(82272848,82425047,82272676)+2 种基金Beijing Municipal Administration of Hospitals'Ascent Plan(DFL20220901)Beijing Natural Science Foundation(7242021,L248021)Sichuan Provincial Science and Technology Department Key Research and Development Program(2024YFHZ0004)。
文摘Acral melanoma,the most common melanoma subtype in East Asia,is associated with a poor prognosis.This study aims to comprehensively analyze the genomic characteristics of acral melanoma in East Asians.We conduct whole-genome sequencing of 55 acral melanoma tumors and perform data mining with relevant clinical data.Our findings reveal a unique mutational profile in East Asian acral melanoma,characterized by fewer point mutations and structural variations,a higher prevalence of NRAS mutations,and a lower frequency of BRAF mutations compared to patients of European descent.Notably,we identify previously underestimated ultraviolet radiation signatures and their significant association with BRAF and NRAS mutations.Structural rearrangement signatures indicate distinct mutational processes in BRAF-driven versus NRAS-driven tumors.We also find that homologous recombination deficiency with MAPK pathway mutations correlated with poor prognosis.The structural variations and amplifications in EP300,TERT,RAC1,and LZTR1 point to potential therapeutic targets tailored to East Asian populations.The high prevalence of whole-genome duplication events in BRAF/NRAS-mutated tumors suggests a synergistic carcinogenic effect that warrants further investigation.In summary,our study provides important insights into the genetic underpinnings of acral melanoma in East Asians,creating opportunities for targeted therapies.
文摘Genomic medicine has evolved significantly,merging centuries of scientific progress with modern molecular biology and clinical care.It utilizes knowledge of the human genome to enhance disease prevention,diagnosis,treatment,and potential reversal.Genomic medicine in hepatology is particularly promising due to the crucial role of the liver in several metabolic processes and its association with diseases such as metabolic dysfunction-associated steatotic liver disease,type 2 diabetes mellitus,liver cirrhosis,and cardiovascular conditions.The mid-20th century witnessed a paradigm shift in medicine,marked by the emergence of molecular biology,which enabled a deeper understanding of gene expression and regulation.This connection between basic science and clinical practice has enhanced our knowledge of the role of gene-environment interactions in the onset and progression of liver diseases.In Latin America,including Mexico,with its genetically diverse and admixed populations,genomic medicine provides a foundation for personalized and culturally relevant health strategies.This review highlights the need for genomic medicine,examining its historical evolution,integration into hepatology in Mexico,and its potential applications in the prevention of chronic diseases.It emphasizes the importance of training in genomic literacy and interdisciplinary education in medical training,particularly in the field of hepatology,with a focus on genomic medicine expertise.
基金supported by the National Natural Science Foundation of China(32470676 and 32170236)Central Guidance on Local Science and Technology Development Fund of Hebei Province(246Z2508G)+2 种基金Hebei Natural Science Foundation(C2020209064)Tangshan Science and Technology Program Project(21130217C)Key research project of North China University of Science and Technology(ZD-YG-202313-23).
文摘As a high-value eudicot family,many famous horticultural crop genomes have been deciphered in Oleaceae.However,there are currently no bioinformatics platforms focused on empowering genome research in Oleaceae.Herein,we developed the first comprehensive Oleaceae Genome Research Platform(OGRP,https://oleaceae.cgrpoee.top/).In OGRP,70 genomes of 10 Oleaceae species and 46 eudicots and 366 transcriptomes involving 18 Oleaceae plant tissues can be obtained.We built 34 window-operated bioinformatics tools,collected 38 professional practical software programs,and proposed 3 new pipelines,namely ancient polyploidization identification,ancestral karyotype reconstruction,and gene family evolution.Employing these pipelines to reanalyze the Oleaceae genomes,we clarified the polyploidization,reconstructed the ancestral karyotypes,and explored the effects of paleogenome evolution on genes with specific biological regulatory roles.Significantly,we generated a series of comparative genomic resources focusing on the Oleaceae,comprising 108 genomic synteny dot plots,1952225 collinear gene pairs,multiple genome alignments,and imprints of paleochromosome rearrangements.Moreover,in Oleaceae genomes,researchers can efficiently search for 1785987 functional annotations,22584 orthogroups,29582 important trait genes from 74 gene families,12664 transcription factor-related genes,9178872 transposable elements,and all involved regulatory pathways.In addition,we provided downloads and usage instructions for the tools,a species encyclopedia,ecological resources,relevant literatures,and external database links.In short,ORGP integrates rich data resources and powerful analytical tools with the characteristic of continuous updating,which can efficiently empower genome research and agricultural breeding in Oleaceae and other plants.
基金jointly funded by Campus France and China Scholarship Council through the PHC Cai Yuanpei 2016 program under grant number 36724VF(Laurent Dacheux)funding from Institut Pasteur,Parissupported by the MRC New Investigator Grant MR/Z506242/1.
文摘Dear Editor,Viruses transmitted by arthropods(arboviruses)are highly diverse,both genetically and in terms of host insect species.They are widely distributed across the virosphere,with significant representation in the family Rhabdoviridae,which encompasses a total of 580 different species divided into 4 sub-families and 62 genera(ICTV:https://talk.ictvonline.org/)(Kuhn et al.,2023;Walker et al.,2022).
基金supported by grants from the National Natural Science Foundation of China(No.82373303,No.82072922,No.82403750)a grant from the Natural Science Foundation of Shanghai(No.24ZR1412600)。
文摘Objective:Lymphovascular invasion(LVI)is a crucial step in metastasis and is closely associated with poor prognosis in patients with breast cancer.However,its clinical and molecular characteristics remain insufficiently defined.We aimed to identify molecular targets for LVI-positive(LVI+)breast cancer and predict patient prognosis via the analysis of genomic variations using targeted sequencing.Methods:We established a large-scale targeted sequencing cohort of 4,079 breast cancer samples,which included 3,159 early-stage and locally advanced patients with available LVI statuses.Comparisons of somatic mutation frequencies and germline pathogenic/likely pathogenic(P/LP)mutation frequencies,mutational signature analyses,and mutual exclusivity and co-occurrence analyses were performed to identify key genomic features involved in LVI+patients.Additionally,Kaplan-Meier survival analysis was conducted to further explore the prognostic value of co-mutations in LVI+cases.Results:We observed that LVI+patients with the hormone receptor-positive/human epidermal growth factor receptor 2-negative(HR+/HER2-)and triple-negative breast cancer(TNBC)subtypes exhibited worse disease-free survival.Notably,HR+/HER2-and HER2+breast cancer patients with LVI displayed distinct genomic features compared with LVI-tumors.Specifically,LVI+HR+/HER2-tumors exhibited greater frequencies of somatic mutations in TP53 and ESR1,germline BRCA2 P/LP variations,and an enrichment of clock-like single-base substitution(SBS)1 mutational signatures.In contrast,LVI+HER2+tumors demonstrated a higher incidence of somatic PIK3CA mutations and increased activity of the apolipoprotein B m RNA editing enzyme catalytic polypeptide(APOBEC)-associated SBS2 signature.Furthermore,we revealed that the co-mutation of TP53 and NF1 could serve as a potential prognostic marker for LVI+HR+/HER2-patients.Conclusions:Our findings provide a comprehensive overview of the genomic characteristics of LVI in breast cancer,thereby offering insights that may help in refining precision treatment strategies for LVI+breast cancer patients.
基金supported by the National Natural Science Foundation of China(no.32570426)the Key Basic Research Program of Yunnan Province,China(202101BC070003)+1 种基金the Fundamental Research Funds for the Central Universities(QNTD202502)the STI 2030—Major Program(2022ZD0401605-2).
文摘Tetracentron sinense is a‘living fossil’tree in East Asia.Understanding how this‘living fossil’responds to climate change and adapts to local environments is critical for its conservation.Here,we used resequenced genomes to clarify the evolutionary history and adaptive potential of T.sinense.We identifiedsix divergent lineages in T.sinense:three lineages from southwestern China(Yunnan Province)and three lineages from the central subtropical region of China.Additionally,we detected hybridization events between some adjacent lineages.Demographic analysis revealed that over the past 10,000 years the effective population size(Ne)of three T.sinense lineages(i.e.,NORTH,SWEST,and YNWEST)increased after their last bottleneck and then remained stable,whereas that of the remaining three lineages(i.e.,YSEAST,YC,and EAST)declined steadily.The decline in effective population size in the Yunnan lineages aligned well with the decrease in genome-wide diversity and a significantincrease in the frequency of runs of homozygosity.Deleterious variants and positively selected sites were involved in the evolution of different lineages.Further,genotype–environment association(GEA)analyses indicated adaptation to temperature-and precipitation-related factors.Genomic offset analyses found the most vulnerable populations,while SC and SC-yad were predicted to better handle extreme changes.Our findingsprovide insights into the evolutionary history and conservation of T.sinense and enhance our understanding of the evolution of living fossil species.
基金the financial support from China Scholarship Council(CSC,File No.202007720040)which has sponsored Jifan Yang's PhD study at Wageningen University&Research.
文摘Background Genomic prediction has revolutionized animal breeding,with GBLUP being the most widely used prediction model.In theory,the accuracy of genomic prediction could be improved by incorporating information from QTL.This strategy could be especially beneficial for machine learning models that are able to distinguish informative from uninformative features.The objective of this study was to assess the benefit of incorporating QTL genotypes in GBLUP and machine learning models.This study simulated a selected livestock population where QTL and their effects were known.We used four genomic prediction models,GBLUP,(weighted)2GBLUP,random forest(RF),and support vector regression(SVR)to predict breeding values of young animals,and considered different scenarios that varied in the proportion of genetic variance explained by the included QTL.Results 2GBLUP resulted in the highest accuracy.Its accuracy increased when the included QTL explained up to 80%of the genetic variance,after which the accuracy dropped.With a weighted 2GBLUP model,the accuracy always increased when more QTL were included.Prediction accuracy of GBLUP was consistently higher than SVR,and the accuracy for both models slightly increased with more QTL information included.The RF model resulted in the lowest prediction accuracy,and did not improve by including QTL information.Conclusions Our results show that incorporating QTL information in GBLUP and SVR can improve prediction accuracy,but the extent of improvement varies across models.RF had a much lower prediction accuracy than the other models and did not show improvements when QTL information was added.Two possible reasons for this result are that the data structure in our data does not allow RF to fully realize its potential and that RF is not designed well for this particular prediction problem.Our study highlighted the importance of selecting appropriate models for genomic prediction and underscored the potential limitations of machine learning models when applied to genomic prediction in livestock.
