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| 1 | A Collinearity-Incorporating Homology Inference Strategy for Connecting Emerging Assemblies in the Triticeae Tribe as a Pilot Practice in the Plant Pangenomic Era显示文摘Plant genome sequencing has dramatically increased,and some species even have multiple high-quality reference versions.Demands for clade-specific homology inference and analysis have increased in the pangenomic era.Here we present a novel method,GeneTribe(https://chenym1.github.io/genetribe/),for homology inference among genetically similar genomes that incorporates gene collinearity and shows bet-ter performance than traditional sequence-similarity-based methods in terms of accuracy and scalability.The Triticeae tribe is a typical allopolyploid-rich clade with complex species relationships that includes many important crops,such as wheat,barley,and rye.We built Triticeae-GeneTribe(http://wheat.cau.edu.cn/TGT/),a homology database,by integrating 12 Triticeae genomes and 3 outgroup model genomes and implemented versatile analysis and visualization functions.With macrocollinearity analysis,we were able to construct a refined model illustrating the structural rearrangements of the 4A-5A-7B chromosomes in wheat as two major translocation events.With collinearity analysis at both the macro-and microscale,we illustrated the complex evolutionary history of homologs of the wheat vernalization gene Vm2,which evolved as a combined result of genome translocation,duplication,and polyploidization and gene loss events.Our work provides a useful practice for connecting emerging genome assemblies,with awareness of the extensive polyploidy in plants,and will help researchers efficiently exploit genome sequence re-sources. | Yongming Chen Wanjun Song Xiaoming Xie Zihao Wang Panfeng Guan Huiru Peng Yuannian Jiao Zhongfu Ni Qixin Sun Weilong Guo | 2020 | Molecular Plant2020，13，12： | 14 |
| 2 | A wheat integrative regulatory network from large-scale complementary functional datasets enables trait-associated gene discovery for crop improvement显示文摘Gene regulation is central to all aspects of organism growth,and understanding it using large-scale functional datasets can provide a whole view of biological processes controlling complex phenotypic traits in crops.However,the connection between massive functional datasets and trait-associated gene discovery for crop improvement is still lacking.In this study,we constructed a wheat integrative gene regulatory network(wGRN)by combining an updated genome annotation and diverse complementary functional datasets,including gene expression,sequence motif,transcription factor(TF)binding,chromatin accessibility,and evolutionarily conserved regulation.wGRN contains 7.2 million genome-wide interactions covering 5947 TFs and 127439 target genes,which were further verified using known regulatory relationships,condition-specific expression,gene functional information,and experiments.We used wGRN to assign genome-wide genes to 3891 specific biological pathways and accurately prioritize candidate genes associated with complex phenotypic traits in genome-wide association studies.In addition,wGRN was used to enhance the interpretation of a spike temporal transcriptome dataset to construct high-resolution networks.We further unveiled novel regulators that enhance the power of spike phenotypic trait prediction using machine learning and contribute to the spike phenotypic differences among modern wheat accessions.Finally,we developed an interactive webserver,wGRN(http://wheat.cau.edu.cn/wGRN),for the community to explore gene regulation and discover trait-associated genes.Collectively,this community resource establishes the foundation for using large-scale functional datasets to guide trait-associated gene discovery for crop improvement. | Yongming Chen Yiwen Guo Panfeng Guan Yongfa Wang Xiaobo Wang Zihao Wang Zhen Qin Shengwei Ma Mingming Xin Zhaorong Hu Yingyin Yao Zhongfu Ni Qixin Sun Weilong Guo Huiru Peng | 2023 | Molecular Plant2023，16，2： | 1 |
| 3 | Genome-wide linkage mapping of QTL for root hair length in a Chinese common wheat population显示文摘Root hairs are fast growing,ephemeral tubular extensions of the root epidermis that aid nutrient and water uptake.The aim of the present study was to identify QTL for root hair length(RHL)using 227 F8 recombinant inbred lines(RILs)derived from a cross of Zhou 8425 B(Z8425 B)and Chinese Spring(CS),and to develop convenient molecular markers for markerassisted breeding in wheat.Analysis of variance of root hair length showed significant differences(P<0.01)among RILs.The genetic map for QTL analysis consisted of 3389 unique SNP markers.Using composite interval mapping,four major QTL(LOD>2.5)for RHL were identified on chromosomes 1 B(2),2 D and 6 D and four putative QTL(2≤LOD≤2.5)were detected on chromosomes 1 A,3 A,6 B,and 7 B,explaining 3.32%–6.52%of the phenotypic variance.The positive alleles for increased RHL of QTL on chromosomes 2 D,6 B and 6 D(QRhl.cau-2 D,q Rhl.cau-6 B,and QRhl.cau-6 D)were contributed by Z8425 B,and CS contributed positive QTL alleles on chromosomes 1 A(q Rhl.cau-1 A),1 B(QRhl.cau-1 B.1 and QRhl.cau-1 B.2),3 A(q Rhl.cau-3 A)and 7 B(q Rhl.cau-7 B).STARP markers were developed for QRhl.cau-1 B.1,QRhl.cau-2 D,QRhl.cau-6 D,and q Rhl.cau-7 B.Haplotype and association analysis indicated that the positive allele of QRhl.cau-6 D had been strongly selected in Chinese wheat breeding programs.Collectively,the identified QTL for root hair length are likely to be useful for marker-assisted selection. | Feng Huang Zhaoyan Chen Dejie Du Panfeng Guan Lingling Chai Weilong Guo Zhaorong Hu Mingming Xin Huiru Peng Yingyin Yao Zhongfu Ni | 2020 | The Crop Journal2020，8，6： | 0 |
| 4 | Breeding design in wheat by combining the QTL information in a GWAS panel with a general genetic map and computer simulation显示文摘A large amount of genome-wide association study(GWAS)panels together with quantitative-trait locus(QTL)information associated with breeding-targeted traits have been described in wheat(Triticum aestivum L.).However,the application of mapping results from a GWAS panel to conventional wheat breeding remains a challenge.In this study,we first report a general genetic map which was constructed from 44 published linkage maps.It permits the estimation of genetic distances between any two genetic loci with physical map positions,thereby unifying the linkage relationships between QTL,genes,and genomic markers from multiple genetic populations.Second,we describe QTL mapping in a wheat GWAS panel of 688 accessions,identifying 77 QTL associated with 12 yield and grain-quality traits.Because these QTL have known physical map positions,they could be mapped onto the general map.Finally,we present a design approach to wheat breeding by using known QTL information and computer simulation.Potential crosses between parents in the GWAS panel may be evaluated by the relative frequency of the target genotype,trait correlations in simulated progeny populations,and genetic gain of selected progenies.It is possible to simultaneously improve yield and grain quality by suitable parental selection,progeny population size,and progeny selection scheme.Applying the design approach will allow identifying the most promising crosses and selection schemes in advance of the field experiment,increasing predictability and efficiency in wheat breeding. | Xiaobo Wang Weiwei Mao Yongfa Wang Hongyao Lou Panfeng Guan Yongming Chen Huiru Peng Jiankang Wang | 2023 | The Crop Journal2023，11，6： | 0 |
| 5 | Factors influencing volatile hydrocarbon pollution in urban areas显示文摘Volatile hydrocarbons in urban environments pose significant risks to human and ecosystem health,resulting from wash-off into receiving waters during storm events.Effective mitigation strategies require understanding of the significance of contributing factors to pollutant generation and their processes.This study employed Bayesian Network modelling to investigate how anthropogenic and environmental factors influence volatile hydrocarbons build-up.The volatile hydrocarbons investigated were,benzene,toluene,ethylbenzene and xylene and styrene.Most volatile hydrocarbons showed statistically significant relationships with environmental factors rather than with anthropogenic factors.Additionally,the research study found that anthropogenic factors could largely contribute to releasing volatile hydrocarbon into the urban environment,while environmental factors are likely to determine their prevalence.The research outcomes will contribute to improving stormwater quality modelling approaches and strengthen the assessment of risk associated with stormwater pollutants in order to enhance stormwater reuse. | Buddhi Wijesiri An Liu Nian Hong Panfeng Zhu Bo Yang Xu Zhao Yuntao Guan Ashantha Goonetilleke | 2019 | Emerging Contaminants2019，5，1： | 0 |
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