Technology development has always been one of the forces driving breakthroughs in biomedical research. Since the time of Thomas Morgan, Drosophilists have, step by step, developed powerful genetic tools for manipulati...Technology development has always been one of the forces driving breakthroughs in biomedical research. Since the time of Thomas Morgan, Drosophilists have, step by step, developed powerful genetic tools for manipulating and functionally dissecting the Drosophila genome, but room for improving these technologies and developing new techniques is still large, especially today as biologists start to study systematically the functional genomics of different model organisms, including humans, in a high-throughput manner. Here, we report, for the first time in Drosophila, a rapid, easy, and highly specific method for modifying the Drosophila genome at a very high efficiency by means of an improved transcription activator-like effector nuclease （TALEN） strategy. We took advantage of the very recently developed ＂unit assembly＂ strategy to assemble two pairs of specific TALENs designed to modify the yellow gene （on the sex chromosome） and a novel autosomal gene. The mRNAs of TALENs were subsequently injected into Drosophila embryos. From 31.2% of the injected Fo fertile flies, we detected inheritable modification involving the yellow gene. The entire process from construction of specific TALENs to detection of inheritable modifications can be accomplished within one month. The potential applications of this TALEN-mediated genome modification method in Drosophila are discussed.展开更多
Thinopyrum elongatum （2n = 2x = 14, EE）, a wild relative of wheat, has been suggested as a potentially novel source of resistance to several major wheat diseases including Fusarium Head Blight （FHB）. In this study...Thinopyrum elongatum （2n = 2x = 14, EE）, a wild relative of wheat, has been suggested as a potentially novel source of resistance to several major wheat diseases including Fusarium Head Blight （FHB）. In this study, a series of wheat （cv. Chinese Spring, CS） substitution and ditelosomic lines, including Th. elongatum additions, were assessed for Type II resistance to FHB. Results indicated that the lines containing chromosome 7E of Th. elongatum gave a high level of resistance to FHB, wherein the infection did not spread beyond the inoculated floret. Furthermore, it was determined that the novel resistance gene（s） of 7E was located on the short-ann （7ES） based on sharp difference in FHB resistance between the two 7E ditelosomic lines for each arm. On the other hand, Th. elongatum chromosomes 5E and 6E likely contain gene（s） for susceptibility to FHB because the disease spreads rapidly within the inoculated spikes of these lines. Genomic in situ hybridization （GISH） analysis revealed that the alien chromosomes in the addition and substitution lines were intact, and the lines did not contain discernible genomic aberrations. GISH and multicolor-GISH analyses were further performed on three trans- location lines that also showed high levels of resistance to FHB. Lines TA3499 and TA3695 were shown to contain one pair of wheat-Th. elongatum translocated chromosomes involving fragments of 7D plus a segment of the 7E, while line TA3493 was found to contain one pair of wheat-Th, elongatum translocated chromosomes involving the D- and A-genome chromosomes of wheat. Thus, this study has established that the short-arm of chromosome 7E of Th. elongatum harbors gene（s） highly resistant to the spreading of FHB, and chromatin of 7E introgressed into wheat chromosomes largely retained the resistance, implicating the feasibility of using these lines as novel material for breeding FHB-resistant wheat cultivars.展开更多
Haynaldia villosa possesses a lot of important agronomic traits and has been a powerful gene resource for wheat improvement. However, only several wheat-H, villosa translocation lines have been reported so far. In thi...Haynaldia villosa possesses a lot of important agronomic traits and has been a powerful gene resource for wheat improvement. However, only several wheat-H, villosa translocation lines have been reported so far. In this study, we attempted to develop an efficient method for inducing wheat-H, villosa chromosomal translocations. Triticum durum- Haynaldia villosa amphiploid pollen treated with 1 200 rad ^60Co-y-rays was pollinated to Triticum aestivum cv. ＇Chinese Spring＇. Ninety-eight intergeneric translocated chromosomes between T. durum and H. villosa were detected by genomic in situ hybridization in 44 of 61 M1 plants, indicating a translocation occurrence frequency of 72.1%; much higher than ever reported. There were 26, 62 and 10 translocated chromosomes involving whole arm translocations, terminal translocations, and intercarlary translocations, respectively. Of the total 108 breakage-fusion events, 79 involved interstitial regions and 29 involved centric regions. The ratio of small segment terminal translocations （W.W-V） was much higher than that of large segment terminal translocations （W-V.V）. All of the M1 plants were self-sterile, and their backcross progeny was all obtained with ＇Chinese Spring＇ as pollen donors. Transmission analysis showed that most of the translocations were transmittable. This study provides a new strategy for rapid mass production of wheat-alien chromosomal translocations, especially terminal translocations that will be more significant for wheat improvement.展开更多
Dof(DNA-binding with one finger)蛋白是植物特有的一类转录因子,在植物生长发育过程中起着重要的作用。在其N-末端有一个52氨基酸残基组成的高度保守的C2-C2单锌指结构,称为Dof保守域,能够特异性的识别植物启动子序列中的AAAG/CTTT作...Dof(DNA-binding with one finger)蛋白是植物特有的一类转录因子,在植物生长发育过程中起着重要的作用。在其N-末端有一个52氨基酸残基组成的高度保守的C2-C2单锌指结构,称为Dof保守域,能够特异性的识别植物启动子序列中的AAAG/CTTT作用元件,从而激活或抑制植物基因的表达;其C-末端的转录调控结构域,氨基酸序列较为多变,不具有保守性,是Dof蛋白在植物中功能多样性的基础;同时Dof蛋白也具有和蛋白相互作用的功能。在过去的十几年里,大量的Dof基因被克隆鉴定或从基因组数据库中预测出来,Dof蛋白在植物生长发育中的作用也受到更多关注。本文就Dof转录因子的特点,各物种中已经报道的Dof转录因子的数目、系统进化关系和分类及其生物学功能的进展进行了综述。展开更多
AIM To analyse cumulative loss of heterozygosity (LOH) of chromosomal regions and tumor suppressor genes in hepatocellular carcinomas (HCCs) from 20 southern African blacks. METHODS p53, RB1, BRCA1, BRCA2, WT1 and E c...AIM To analyse cumulative loss of heterozygosity (LOH) of chromosomal regions and tumor suppressor genes in hepatocellular carcinomas (HCCs) from 20 southern African blacks. METHODS p53, RB1, BRCA1, BRCA2, WT1 and E cadherin genes were analysed for LOH, and p53 gene was also analysed for the codon 249 mutation, in tumor and adjacent non tumorous liver tissues using molecular techniques and 10 polymorphic microsatellite markers. RESULTS p53 codon 249 mutation was found in 25% of the subjects, as was expected, because many patients were from Mozambique, a country with high aflatoxin B 1 exposure. LOH was found at the RB1, BRCA2 and WT1 loci in 20%(4/*!20) of the HCCs, supporting a possible role of these genes in HCC. No LOH was evident in any of the remaining genes. Reports of mutations of p53 and RB1 genes in combination, described in other populations, were not confirmed in this study. Change in microsatellite repeat number was noted at 9/*!10 microsatellite loci in different HCCs, and changes at two or more loci were detected in 15%(3/*!20) of subjects. CONCLUSION We propose that microsatellite/genomic instability may play a role in the pathogenesis of a subset of HCCs in black Africans.展开更多
[Objective] The study aimed to introduce a rapid and effective method that is suitable for extracting genomic DNA from animal and plant. [ Method ] The genomic DNAs were extracted from tender leaves of 24 peanut cuhiv...[Objective] The study aimed to introduce a rapid and effective method that is suitable for extracting genomic DNA from animal and plant. [ Method ] The genomic DNAs were extracted from tender leaves of 24 peanut cuhivars and from the liver, lung and kidney of white mouse through the specifically modified CTAB method. The DNAs were run on agarose gel, next detected by DNA/Protein analyzer. Finally PCR amplification was conducted to detect the quality of DNAs extracted using the modified CTAB method. [ Result] The clear and orderly bands were observed in gel detection, and the values of OD200/OD200 for DNAs extracted via modified CTAB method were between 1.77 - 1.83. The DNAs performed well in PCR amplification. [ Conclusion] The DNAs extracted by modified CTAB method could satisfy the requirement of PCR amplification.展开更多
Porcine deltacoronavirus(PDCoV) is a newly identified virus that causes watery diarrhea in newborn piglets and results in significant economic losses to the pig industry. Since first reported in Hong Kong in 2012, PDC...Porcine deltacoronavirus(PDCoV) is a newly identified virus that causes watery diarrhea in newborn piglets and results in significant economic losses to the pig industry. Since first reported in Hong Kong in 2012, PDCoV has been subsequently detected in USA, South Korea, Thailand, and China's Mainland. Here we isolated a strain of PDCoV, named CHN-GD-2016,from the intestinal content of a diseased newborn piglet with severe diarrhea in a pig farm in Guangdong, China. PDCoV CHN-GD-2016 could be identified by immunofluorescence with PDCoV specific rabbit antisera, and typical crown-shaped particles with spiky surface projections of this PDCoV were observed with electron microscopy. Genomic analysis showed that the PDCoV CHN-GD-2016 was closely related to other Chinese PDCoV strains, with the highest sequence similarity with the strain CHN/Tianjin/2016. Importantly, inoculation of newborn piglets with 1×10~5 TCID_(50) of CHN-GD-2016 by oral feeding successfully reproduced clear clinical symptoms, including vomiting, dehydration, and severe diarrhea in piglets. In addition, the virus RNA in rectal swabs from 1 to 7 days post inoculation was detected, macroscopic and microscopic lesions in small intestine were observed, and viral antigen was also detected in the small intestines with immunohistochemical staining. Collectively, the data show in this study confirms that PDCoV is present in Guangdong,China and is highly pathogenic in newborn piglets.展开更多
Genome-wide association study(GWAS)and genomic prediction/selection(GP/GS)are the two essential enterprises in genomic research.Due to the great magnitude and complexity of genomic and phenotypic data,analytical metho...Genome-wide association study(GWAS)and genomic prediction/selection(GP/GS)are the two essential enterprises in genomic research.Due to the great magnitude and complexity of genomic and phenotypic data,analytical methods and their associated software packages are frequently advanced.GAPIT is a widely-used genomic association and prediction integrated tool as an R package.The first version was released to the public in 2012 with the implementation of the general linear model(GLM),mixed linear model(MLM),compressed MLM(CMLM),and genomic best linear unbiased prediction(g BLUP).The second version was released in 2016 with several new implementations,including enriched CMLM(ECMLM)and settlement of MLMs under progressively exclusive relationship(SUPER).All the GWAS methods are based on the single-locus test.For the first time,in the current release of GAPIT,version 3 implemented three multi-locus test methods,including multiple loci mixed model(MLMM),fixed and random model circulating probability unification(Farm CPU),and Bayesian-information and linkage-disequilibrium iteratively nested keyway(BLINK).Additionally,two GP/GS methods were implemented based on CMLM(named compressed BLUP;c BLUP)and SUPER(named SUPER BLUP;s BLUP).These new implementations not only boost statistical power for GWAS and prediction accuracy for GP/GS,but also improve computing speed and increase the capacity to analyze big genomic data.Here,we document the current upgrade of GAPIT by describing the selection of the recently developed methods,their implementations,and potential impact.All documents,including source code,user manual,demo data,and tutorials,are freely available at the GAPIT website(http://zzlab.net/GAPIT).展开更多
The first paradigm of plant breeding involves direct selection-based phenotypic observation,followed by predictive breeding using statistical models for quantitative traits constructed based on genetic experimental de...The first paradigm of plant breeding involves direct selection-based phenotypic observation,followed by predictive breeding using statistical models for quantitative traits constructed based on genetic experimental design and,more recently,by incorporation of molecular marker genotypes.However,plant performance or phenotype(P)is determined by the combined effects of genotype(G),envirotype(E),and genotype by environment interaction(GEI).Phenotypes can be predicted more precisely by training a model using data collected from multiple sources,including spatiotemporal omics(genomics,phenomics,and enviromics across time and space).Integration of 3D information profiles(G-P-E),each with multidimensionality,provides predictive breeding with both tremendous opportunities and great challenges.Here,we first review innovative technologies for predictive breeding.We then evaluate multidimensional information profiles that can be integrated with a predictive breeding strategy,particularly envirotypic data,which have largely been neglected in data collection and are nearly untouched in model construction.We propose a smart breeding scheme,integrated genomic-enviromic prediction(iGEP),as an extension of genomic prediction,using integrated multiomics information,big data technology,and artificial intelligence(mainly focused on machine and deep learning).We discuss how to implement iGEP,including spatiotemporal models,environmental indices,factorial and spatiotemporal structure of plant breeding data,and cross-species prediction.A strategy is then proposed for prediction-based crop redesign at both the macro(individual,population,and species)and micro(gene,metabolism,and network)scales.Finally,we provide perspectives on translating smart breeding into genetic gain through integrative breeding platforms and open-source breeding initiatives.We call for coordinated efforts in smart breeding through iGEP,institutional partnerships,and innovative technological support.展开更多
Worldwide, gastric cancer is one of the most common malignancies with high mortality. Various aspects of thedevelopment and progression of gastric cancer continue to be extensively investigated in order to further our...Worldwide, gastric cancer is one of the most common malignancies with high mortality. Various aspects of thedevelopment and progression of gastric cancer continue to be extensively investigated in order to further our understanding and provide more effective means for the prevention, diagnosis, and treatment of the disease. Estrogen receptors(ERs) are steroid hormone receptors that regulate cellular activities in many physiological and pathological processes in different tissues. There are two distinct forms of ERs, namely ERα and ERβ, with several alternative-splicing isoforms for each. They show distinct tissue distribution patterns and exert different biological functions. Dysregulation of ERs has been found to be associated closely with many diseases, including cancer. A number of studies have been conducted to investigate the role of ERs in gastric cancer, the possible mechanisms underlying these roles, and the clinical relevance of deregulated ERs in gastric cancer patients. To date, inconsistent associations of different ERs with gastric cancer have been reported. These inconsistencies may be caused by variations in in vitro cell models and clinical samples, including assay conditions and protocols with regard to different forms of ERs. Given the potential of the deregulated ERs as diagnostic/prognostic markers or therapeutic targets for gastric cancer, it will be important to identify/confirm the association of each ER isoform with gastric cancer, to determine the specific roles and interactions that these individual ER isoforms play under specific conditions in the development and/or progression of gastric cancer, and to elucidate precisely these mechanisms. In this review, we summarize the achievements from early ER studies in gastric cancer to the most up-to-date discoveries, with an effort to provide a comprehensive understanding of the role of ERs roles in gastric cancer and its possible mechanisms. Furthermore, we propose directions for future investigations.展开更多
Genomic prediction is an effective way to accelerate the rate of agronomic trait improvement in plants.Traditional methods typically use linear regression models with clear assumptions;such methods are unable to captu...Genomic prediction is an effective way to accelerate the rate of agronomic trait improvement in plants.Traditional methods typically use linear regression models with clear assumptions;such methods are unable to capture the complex relationships between genotypes and phenotypes.Non-linear models(e.g.,deep neural networks)have been proposed as a superior alternative to linear models because they can capture complex non-additive effects.Here we introduce a deep learning(DL)method,deep neural network genomic prediction(DNNGP),for integration of multi-omics data in plants.We trained DNNGP on four datasets and compared its performance with methods built with five classic models:genomic best linear unbiased prediction(GBLUP);two methods based on a machine learning(ML)framework,light gradient boosting machine(LightGBM)and support vector regression(SVR);and two methods based on a DL framework,deep learning genomic selection(DeepGS)and deep learning genome-wide association study(DLGWAS).DNNGP is novel in five ways.First,it can be applied to a variety of omics data to predict phenotypes.Second,the multilayered hierarchical structure of DNNGP dynamically learns features from raw data,avoiding overfitting and improving the convergence rate using a batch normalization layer and early stopping and rectified linear activation(rectified linear unit)functions.Third,when small datasets were used,DNNGP produced results that are competitive with results from the other five methods,showing greater prediction accuracy than the other methods when large-scale breeding data were used.Fourth,the computation time required by DNNGP was comparable with that of commonly used methods,up to 10 times faster than DeepGS.Fifth,hyperparameters can easily be batch tuned on a local machine.Compared with GBLUP,LightGBM,SVR,DeepGS and DLGWAS,DNNGP is superior to these existing widely used genomic selection(GS)methods.Moreover,DNNGP can generate robust assessments from diverse datasets,including omics data,and quickly incorporate complex and large datas展开更多
Fish biology has been developed for more than 100 years,but some important breakthroughs have been made in the last decade.Early studies commonly concentrated on morphology,phylogenetics,development,growth,reproductio...Fish biology has been developed for more than 100 years,but some important breakthroughs have been made in the last decade.Early studies commonly concentrated on morphology,phylogenetics,development,growth,reproduction manipulation,and disease control.Recent studies have mostly focused on genetics,molecular biology,genomics,and genome biotechnologies,which have provided a solid foundation for enhancing aquaculture to ensure food security and improving aquatic environments to sustain ecosystem health.Here,we review research advances in five major areas:(1)biological innovations and genomic evolution of four significant fish lineages including non-teleost ray-finned fishes,northern hemisphere sticklebacks,East African cichlid fishes,and East Asian cyprinid fishes;(2)evolutionary fates and consequences of natural polyploid fishes;(3)biological consequences of fish domestication and selection;(4)development and innovation of fish breeding biotechnologies;and(5)applicable approaches and potential of fish genetic breeding biotechnologies.Moreover,five precision breeding biotechniques are examined and discussed in detail including gene editing for the introgression or removal of beneficial or detrimental alleles,use of sex-specific markers for the production of mono-sex populations,controllable primordial germ cell on-off strategy for producing sterile offspring,surrogate broodstock-based strategies to accelerate breeding,and genome incorporation and sexual reproduction regainbased approach to create synthetic polyploids.Based on these scientific and technological advances,we propose a blueprint for genetic improvement and new breed creation for aquaculture species and analyze the potential of these new breeding strategies for improving aquaculture seed industry and strengthening food security.展开更多
With marker and phenotype information from observed populations, genomic selection （GS） can be used to establish associations between markers and phenotypes. It aims to use genome-wide markers to estimate the effect...With marker and phenotype information from observed populations, genomic selection （GS） can be used to establish associations between markers and phenotypes. It aims to use genome-wide markers to estimate the effects of all loci and thereby predict the genetic values of untested populations, so as to achieve more comprehensive and reliable selection and to accelerate genetic progress in crop breeding. GS models usually face the problem that the number of markers is much higher than the number of phenotypic observations. To overcome this issue and improve prediction accuracy, many models and algorithms, including GBLUP, Bayes, and machine learning have been employed for GS. As hot issues in GS research, the estimation of non-additive genetic effects and the combined analysis of multiple traits or multiple environments are also important for improving the accuracy of prediction. In recent years, crop breeding has taken advantage of the development of GS. The principles and characteristics of current popular GS methods and research progress in hese methods for crop improvement are reviewed in this paper.展开更多
基金supported by the grants from the 973 Program(Nos.2009CB918702 and 2012CB945101)the NSFC(Nos.31071087 and 31100889)+1 种基金W.-M.D.is supported by NIH grant R01GM072562National Science Foundation of USA(IOS-1052333)
文摘Technology development has always been one of the forces driving breakthroughs in biomedical research. Since the time of Thomas Morgan, Drosophilists have, step by step, developed powerful genetic tools for manipulating and functionally dissecting the Drosophila genome, but room for improving these technologies and developing new techniques is still large, especially today as biologists start to study systematically the functional genomics of different model organisms, including humans, in a high-throughput manner. Here, we report, for the first time in Drosophila, a rapid, easy, and highly specific method for modifying the Drosophila genome at a very high efficiency by means of an improved transcription activator-like effector nuclease （TALEN） strategy. We took advantage of the very recently developed ＂unit assembly＂ strategy to assemble two pairs of specific TALENs designed to modify the yellow gene （on the sex chromosome） and a novel autosomal gene. The mRNAs of TALENs were subsequently injected into Drosophila embryos. From 31.2% of the injected Fo fertile flies, we detected inheritable modification involving the yellow gene. The entire process from construction of specific TALENs to detection of inheritable modifications can be accomplished within one month. The potential applications of this TALEN-mediated genome modification method in Drosophila are discussed.
基金supported by the grant of the National High Technology Research and Development Program("863"Program)of China(No.2011AA100101)
文摘Thinopyrum elongatum （2n = 2x = 14, EE）, a wild relative of wheat, has been suggested as a potentially novel source of resistance to several major wheat diseases including Fusarium Head Blight （FHB）. In this study, a series of wheat （cv. Chinese Spring, CS） substitution and ditelosomic lines, including Th. elongatum additions, were assessed for Type II resistance to FHB. Results indicated that the lines containing chromosome 7E of Th. elongatum gave a high level of resistance to FHB, wherein the infection did not spread beyond the inoculated floret. Furthermore, it was determined that the novel resistance gene（s） of 7E was located on the short-ann （7ES） based on sharp difference in FHB resistance between the two 7E ditelosomic lines for each arm. On the other hand, Th. elongatum chromosomes 5E and 6E likely contain gene（s） for susceptibility to FHB because the disease spreads rapidly within the inoculated spikes of these lines. Genomic in situ hybridization （GISH） analysis revealed that the alien chromosomes in the addition and substitution lines were intact, and the lines did not contain discernible genomic aberrations. GISH and multicolor-GISH analyses were further performed on three trans- location lines that also showed high levels of resistance to FHB. Lines TA3499 and TA3695 were shown to contain one pair of wheat-Th. elongatum translocated chromosomes involving fragments of 7D plus a segment of the 7E, while line TA3493 was found to contain one pair of wheat-Th, elongatum translocated chromosomes involving the D- and A-genome chromosomes of wheat. Thus, this study has established that the short-arm of chromosome 7E of Th. elongatum harbors gene（s） highly resistant to the spreading of FHB, and chromatin of 7E introgressed into wheat chromosomes largely retained the resistance, implicating the feasibility of using these lines as novel material for breeding FHB-resistant wheat cultivars.
基金Supported by the National Natural Science Foundation of China(30270827)the Program for Changjiang Scholars and Innovative Research in Universities(10418).
文摘Haynaldia villosa possesses a lot of important agronomic traits and has been a powerful gene resource for wheat improvement. However, only several wheat-H, villosa translocation lines have been reported so far. In this study, we attempted to develop an efficient method for inducing wheat-H, villosa chromosomal translocations. Triticum durum- Haynaldia villosa amphiploid pollen treated with 1 200 rad ^60Co-y-rays was pollinated to Triticum aestivum cv. ＇Chinese Spring＇. Ninety-eight intergeneric translocated chromosomes between T. durum and H. villosa were detected by genomic in situ hybridization in 44 of 61 M1 plants, indicating a translocation occurrence frequency of 72.1%; much higher than ever reported. There were 26, 62 and 10 translocated chromosomes involving whole arm translocations, terminal translocations, and intercarlary translocations, respectively. Of the total 108 breakage-fusion events, 79 involved interstitial regions and 29 involved centric regions. The ratio of small segment terminal translocations （W.W-V） was much higher than that of large segment terminal translocations （W-V.V）. All of the M1 plants were self-sterile, and their backcross progeny was all obtained with ＇Chinese Spring＇ as pollen donors. Transmission analysis showed that most of the translocations were transmittable. This study provides a new strategy for rapid mass production of wheat-alien chromosomal translocations, especially terminal translocations that will be more significant for wheat improvement.
文摘Dof(DNA-binding with one finger)蛋白是植物特有的一类转录因子,在植物生长发育过程中起着重要的作用。在其N-末端有一个52氨基酸残基组成的高度保守的C2-C2单锌指结构,称为Dof保守域,能够特异性的识别植物启动子序列中的AAAG/CTTT作用元件,从而激活或抑制植物基因的表达;其C-末端的转录调控结构域,氨基酸序列较为多变,不具有保守性,是Dof蛋白在植物中功能多样性的基础;同时Dof蛋白也具有和蛋白相互作用的功能。在过去的十几年里,大量的Dof基因被克隆鉴定或从基因组数据库中预测出来,Dof蛋白在植物生长发育中的作用也受到更多关注。本文就Dof转录因子的特点,各物种中已经报道的Dof转录因子的数目、系统进化关系和分类及其生物学功能的进展进行了综述。
文摘AIM To analyse cumulative loss of heterozygosity (LOH) of chromosomal regions and tumor suppressor genes in hepatocellular carcinomas (HCCs) from 20 southern African blacks. METHODS p53, RB1, BRCA1, BRCA2, WT1 and E cadherin genes were analysed for LOH, and p53 gene was also analysed for the codon 249 mutation, in tumor and adjacent non tumorous liver tissues using molecular techniques and 10 polymorphic microsatellite markers. RESULTS p53 codon 249 mutation was found in 25% of the subjects, as was expected, because many patients were from Mozambique, a country with high aflatoxin B 1 exposure. LOH was found at the RB1, BRCA2 and WT1 loci in 20%(4/*!20) of the HCCs, supporting a possible role of these genes in HCC. No LOH was evident in any of the remaining genes. Reports of mutations of p53 and RB1 genes in combination, described in other populations, were not confirmed in this study. Change in microsatellite repeat number was noted at 9/*!10 microsatellite loci in different HCCs, and changes at two or more loci were detected in 15%(3/*!20) of subjects. CONCLUSION We propose that microsatellite/genomic instability may play a role in the pathogenesis of a subset of HCCs in black Africans.
文摘[Objective] The study aimed to introduce a rapid and effective method that is suitable for extracting genomic DNA from animal and plant. [ Method ] The genomic DNAs were extracted from tender leaves of 24 peanut cuhivars and from the liver, lung and kidney of white mouse through the specifically modified CTAB method. The DNAs were run on agarose gel, next detected by DNA/Protein analyzer. Finally PCR amplification was conducted to detect the quality of DNAs extracted using the modified CTAB method. [ Result] The clear and orderly bands were observed in gel detection, and the values of OD200/OD200 for DNAs extracted via modified CTAB method were between 1.77 - 1.83. The DNAs performed well in PCR amplification. [ Conclusion] The DNAs extracted by modified CTAB method could satisfy the requirement of PCR amplification.
基金supported by the National Key Research and Development Program (2016YFD0500101)
文摘Porcine deltacoronavirus(PDCoV) is a newly identified virus that causes watery diarrhea in newborn piglets and results in significant economic losses to the pig industry. Since first reported in Hong Kong in 2012, PDCoV has been subsequently detected in USA, South Korea, Thailand, and China's Mainland. Here we isolated a strain of PDCoV, named CHN-GD-2016,from the intestinal content of a diseased newborn piglet with severe diarrhea in a pig farm in Guangdong, China. PDCoV CHN-GD-2016 could be identified by immunofluorescence with PDCoV specific rabbit antisera, and typical crown-shaped particles with spiky surface projections of this PDCoV were observed with electron microscopy. Genomic analysis showed that the PDCoV CHN-GD-2016 was closely related to other Chinese PDCoV strains, with the highest sequence similarity with the strain CHN/Tianjin/2016. Importantly, inoculation of newborn piglets with 1×10~5 TCID_(50) of CHN-GD-2016 by oral feeding successfully reproduced clear clinical symptoms, including vomiting, dehydration, and severe diarrhea in piglets. In addition, the virus RNA in rectal swabs from 1 to 7 days post inoculation was detected, macroscopic and microscopic lesions in small intestine were observed, and viral antigen was also detected in the small intestines with immunohistochemical staining. Collectively, the data show in this study confirms that PDCoV is present in Guangdong,China and is highly pathogenic in newborn piglets.
基金partially funded by National Science Foundation,the United States(Grant Nos.DBI 1661348 and ISO 2029933)the United States Department of Agriculture–National Institute of Food and Agriculture,the United States(Hatch Project No.1014919,Grant Nos.2018-70005-28792,2019-67013-29171,and 2020-67021-32460)+3 种基金the Washington Grain Commission,the United States(Endowment and Grant Nos.126593 and 134574)Sichuan Science and Technology Program,China(Grant Nos.2021YJ0269 and 2021YJ0266)the Program of Chinese National Beef Cattle and Yak Industrial Technology System,China(Grant No.CARS-37)Fundamental Research Funds for the Central Universities,China(Southwest Minzu University,Grant No.2020NQN26)。
文摘Genome-wide association study(GWAS)and genomic prediction/selection(GP/GS)are the two essential enterprises in genomic research.Due to the great magnitude and complexity of genomic and phenotypic data,analytical methods and their associated software packages are frequently advanced.GAPIT is a widely-used genomic association and prediction integrated tool as an R package.The first version was released to the public in 2012 with the implementation of the general linear model(GLM),mixed linear model(MLM),compressed MLM(CMLM),and genomic best linear unbiased prediction(g BLUP).The second version was released in 2016 with several new implementations,including enriched CMLM(ECMLM)and settlement of MLMs under progressively exclusive relationship(SUPER).All the GWAS methods are based on the single-locus test.For the first time,in the current release of GAPIT,version 3 implemented three multi-locus test methods,including multiple loci mixed model(MLMM),fixed and random model circulating probability unification(Farm CPU),and Bayesian-information and linkage-disequilibrium iteratively nested keyway(BLINK).Additionally,two GP/GS methods were implemented based on CMLM(named compressed BLUP;c BLUP)and SUPER(named SUPER BLUP;s BLUP).These new implementations not only boost statistical power for GWAS and prediction accuracy for GP/GS,but also improve computing speed and increase the capacity to analyze big genomic data.Here,we document the current upgrade of GAPIT by describing the selection of the recently developed methods,their implementations,and potential impact.All documents,including source code,user manual,demo data,and tutorials,are freely available at the GAPIT website(http://zzlab.net/GAPIT).
基金National Key Research and Development Program of China(2016YFD0101803)Central Public-interest Scientific Institution Basal Research Fund(Y2020PT20)+5 种基金Agricultural Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences(CAAS-XTCX2016009)Shijiazhuang Science and Technology Incubation Program(191540089A)Hebei Innovation Capability Enhancement Project(19962911D)Project of Hainan Yazhou Bay Seed Laboratory(B21HJ0223)Department of Science and Technology of Ninxia Project(NXNYYZ202001)Research activities at CIMMYT were supported by the Bill and Melinda Gates Foundation and the CGIAR Research Program MAIZE.
文摘The first paradigm of plant breeding involves direct selection-based phenotypic observation,followed by predictive breeding using statistical models for quantitative traits constructed based on genetic experimental design and,more recently,by incorporation of molecular marker genotypes.However,plant performance or phenotype(P)is determined by the combined effects of genotype(G),envirotype(E),and genotype by environment interaction(GEI).Phenotypes can be predicted more precisely by training a model using data collected from multiple sources,including spatiotemporal omics(genomics,phenomics,and enviromics across time and space).Integration of 3D information profiles(G-P-E),each with multidimensionality,provides predictive breeding with both tremendous opportunities and great challenges.Here,we first review innovative technologies for predictive breeding.We then evaluate multidimensional information profiles that can be integrated with a predictive breeding strategy,particularly envirotypic data,which have largely been neglected in data collection and are nearly untouched in model construction.We propose a smart breeding scheme,integrated genomic-enviromic prediction(iGEP),as an extension of genomic prediction,using integrated multiomics information,big data technology,and artificial intelligence(mainly focused on machine and deep learning).We discuss how to implement iGEP,including spatiotemporal models,environmental indices,factorial and spatiotemporal structure of plant breeding data,and cross-species prediction.A strategy is then proposed for prediction-based crop redesign at both the macro(individual,population,and species)and micro(gene,metabolism,and network)scales.Finally,we provide perspectives on translating smart breeding into genetic gain through integrative breeding platforms and open-source breeding initiatives.We call for coordinated efforts in smart breeding through iGEP,institutional partnerships,and innovative technological support.
基金Supported by The National Natural Science Foundation of ChinaNo.30271450+1 种基金No.30471955No.30672365 and No.81172516
文摘Worldwide, gastric cancer is one of the most common malignancies with high mortality. Various aspects of thedevelopment and progression of gastric cancer continue to be extensively investigated in order to further our understanding and provide more effective means for the prevention, diagnosis, and treatment of the disease. Estrogen receptors(ERs) are steroid hormone receptors that regulate cellular activities in many physiological and pathological processes in different tissues. There are two distinct forms of ERs, namely ERα and ERβ, with several alternative-splicing isoforms for each. They show distinct tissue distribution patterns and exert different biological functions. Dysregulation of ERs has been found to be associated closely with many diseases, including cancer. A number of studies have been conducted to investigate the role of ERs in gastric cancer, the possible mechanisms underlying these roles, and the clinical relevance of deregulated ERs in gastric cancer patients. To date, inconsistent associations of different ERs with gastric cancer have been reported. These inconsistencies may be caused by variations in in vitro cell models and clinical samples, including assay conditions and protocols with regard to different forms of ERs. Given the potential of the deregulated ERs as diagnostic/prognostic markers or therapeutic targets for gastric cancer, it will be important to identify/confirm the association of each ER isoform with gastric cancer, to determine the specific roles and interactions that these individual ER isoforms play under specific conditions in the development and/or progression of gastric cancer, and to elucidate precisely these mechanisms. In this review, we summarize the achievements from early ER studies in gastric cancer to the most up-to-date discoveries, with an effort to provide a comprehensive understanding of the role of ERs roles in gastric cancer and its possible mechanisms. Furthermore, we propose directions for future investigations.
基金National Key R&D Program of China(2021YFD1201200)National Science Foundation of China(32022064)+1 种基金Project of Hainan Yazhou Bay Seed Lab(B21HJ0223)Innovation Program of the Chinese Academy of Agricultural Sciences.
文摘Genomic prediction is an effective way to accelerate the rate of agronomic trait improvement in plants.Traditional methods typically use linear regression models with clear assumptions;such methods are unable to capture the complex relationships between genotypes and phenotypes.Non-linear models(e.g.,deep neural networks)have been proposed as a superior alternative to linear models because they can capture complex non-additive effects.Here we introduce a deep learning(DL)method,deep neural network genomic prediction(DNNGP),for integration of multi-omics data in plants.We trained DNNGP on four datasets and compared its performance with methods built with five classic models:genomic best linear unbiased prediction(GBLUP);two methods based on a machine learning(ML)framework,light gradient boosting machine(LightGBM)and support vector regression(SVR);and two methods based on a DL framework,deep learning genomic selection(DeepGS)and deep learning genome-wide association study(DLGWAS).DNNGP is novel in five ways.First,it can be applied to a variety of omics data to predict phenotypes.Second,the multilayered hierarchical structure of DNNGP dynamically learns features from raw data,avoiding overfitting and improving the convergence rate using a batch normalization layer and early stopping and rectified linear activation(rectified linear unit)functions.Third,when small datasets were used,DNNGP produced results that are competitive with results from the other five methods,showing greater prediction accuracy than the other methods when large-scale breeding data were used.Fourth,the computation time required by DNNGP was comparable with that of commonly used methods,up to 10 times faster than DeepGS.Fifth,hyperparameters can easily be batch tuned on a local machine.Compared with GBLUP,LightGBM,SVR,DeepGS and DLGWAS,DNNGP is superior to these existing widely used genomic selection(GS)methods.Moreover,DNNGP can generate robust assessments from diverse datasets,including omics data,and quickly incorporate complex and large datas
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences(XDB31000000)the Consulting Research Projects of Hubei Institute of Chinese Engineering Development Strategies and Academic Divisions of the Chinese Academy of Sciences(2021-SM02-B-010)+2 种基金the Key Program of Frontier Sciences of the Chinese Academy of Sciences(Grant No.QYZDY-SSW-SMC025)the China Agriculture Research System(CARS-45-07)the Autonomous Project of the State Key Laboratory of Freshwater Ecology and Biotechnology(2019FBZ04).
文摘Fish biology has been developed for more than 100 years,but some important breakthroughs have been made in the last decade.Early studies commonly concentrated on morphology,phylogenetics,development,growth,reproduction manipulation,and disease control.Recent studies have mostly focused on genetics,molecular biology,genomics,and genome biotechnologies,which have provided a solid foundation for enhancing aquaculture to ensure food security and improving aquatic environments to sustain ecosystem health.Here,we review research advances in five major areas:(1)biological innovations and genomic evolution of four significant fish lineages including non-teleost ray-finned fishes,northern hemisphere sticklebacks,East African cichlid fishes,and East Asian cyprinid fishes;(2)evolutionary fates and consequences of natural polyploid fishes;(3)biological consequences of fish domestication and selection;(4)development and innovation of fish breeding biotechnologies;and(5)applicable approaches and potential of fish genetic breeding biotechnologies.Moreover,five precision breeding biotechniques are examined and discussed in detail including gene editing for the introgression or removal of beneficial or detrimental alleles,use of sex-specific markers for the production of mono-sex populations,controllable primordial germ cell on-off strategy for producing sterile offspring,surrogate broodstock-based strategies to accelerate breeding,and genome incorporation and sexual reproduction regainbased approach to create synthetic polyploids.Based on these scientific and technological advances,we propose a blueprint for genetic improvement and new breed creation for aquaculture species and analyze the potential of these new breeding strategies for improving aquaculture seed industry and strengthening food security.
基金supported by grants from the National High Technology Research and Development Program of China(2014AA10A601-5)the National Key Research and Development Program of China(2016YFD0100303)+5 种基金the National Natural Science Foundation of China(91535103)the Natural Science Foundations of Jiangsu Province(BK20150010)the Natural Science Foundation of the Jiangsu Higher Education Institutions(14KJA210005)the Open Research Fund of State Key Laboratory of Hybrid Rice(Wuhan University)(KF201701)the Science and Technology Innovation Fund Project in Yangzhou University(2016CXJ021)the Priority Academic Program Development of Jiangsu Higher Education Institutions and the Innovative Research Team of Universities in Jiangsu Province
文摘With marker and phenotype information from observed populations, genomic selection （GS） can be used to establish associations between markers and phenotypes. It aims to use genome-wide markers to estimate the effects of all loci and thereby predict the genetic values of untested populations, so as to achieve more comprehensive and reliable selection and to accelerate genetic progress in crop breeding. GS models usually face the problem that the number of markers is much higher than the number of phenotypic observations. To overcome this issue and improve prediction accuracy, many models and algorithms, including GBLUP, Bayes, and machine learning have been employed for GS. As hot issues in GS research, the estimation of non-additive genetic effects and the combined analysis of multiple traits or multiple environments are also important for improving the accuracy of prediction. In recent years, crop breeding has taken advantage of the development of GS. The principles and characteristics of current popular GS methods and research progress in hese methods for crop improvement are reviewed in this paper.
