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Leveraging the potential of big genomic and phenotypic data for genome-wide association mapping in wheat

The crop Journal 2024年第3期12卷 803-813页

作者： Moritz Lell Yusheng Zhao jochen c.reif Leibniz Institute of Plant Genetics and crop Plant Research(IPK) Corrensstraße 3D-06466 SeelandGermany

Genome-wide association mapping studies(GWAS)based on Big Data are a potential approach to improve marker-assisted selection in plant breeding.The number of available phenotypic and genomic data sets in which medium-sized populations of several hundred individuals have been studied is rapidly increasing.combining these data and using them in GWAS could increase both the power of QTL discovery and the accuracy of estimation of underlying genetic effects,but is hindered by data heterogeneity and lack of interoperability.In this study,we used genomic and phenotypic data sets,focusing on central European winter wheat populations evaluated for heading date.We explored strategies for integrating these data and subsequently the resulting potential for GWAS.Establishing interoperability between data sets was greatly aided by some overlapping genotypes and a linear relationship between the different phenotyping protocols,resulting in high quality integrated phenotypic data.In this context,genomic prediction proved to be a suitable tool to study relevance of interactions between genotypes and experimental series,which was low in our case.contrary to expectations,fewer associations between markers and traits were found in the larger combined data than in the individual experimental series.However,the predictive power based on the marker-trait associations of the integrated data set was higher across data sets.Therefore,the results show that the integration of medium-sized to Big Data is an approach to increase the power to detect QTL in GWAS.The results encourage further efforts to standardize and share data in the plant breeding community.

关键词： Big Data Genome-wide association study Data integration Genomic prediction Wheat

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Filtering for SNPs with high selective constraint augments mid-parent heterosis predictions in wheat(Triticum aestivum L.)

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The crop Journal 2023年第1期11卷 166-176页

作者： Abhishek Gogna Jie Zhang Yong Jiang Albert W.Schulthess Yusheng Zhao jochen c.reif Leibniz Institute of Plant Genetics and crop Plant Research(IPK) 06466 Stadt SeelandGermany

To extend the contemporary understanding into the grain yield heterosis of wheat, the current study investigated the contribution of deleterious alleles in shaping mid-parent heterosis(MPH). These alleles occur at low frequency in the genome and are often missed by automated genotyping platforms like SNP arrays. The deleterious alleles herein were detected using a quantitative measurement of evolutionary conservation based on the phylogeny of wheat and investigations were made to:(1) assess the benefit of including deleterious alleles into MPH prediction models and(2) understand the genetic underpinnings of deleterious SNPs for grain yield MPH using contrasting crosses viz. elite × elite(Exp. 1) and elite × plant genetic resources(PGR;Exp. 2). In our study, we found a lower allele frequency of moderately deleterious alleles in elites compared to PGRs. This highlights the role of purifying selection for the development of elite wheat cultivars. It was shown that deleterious alleles are informative for MPH prediction models: modelling their additive-by-additive effects in Exp. 1 and dominance as well as associated digenic epistatic effects in Exp. 2 significantly boosts prediction accuracies of MPH. Furthermore,heterotic-quantitative trait loci's underlying MPH was investigated and their properties were contrasted in the two crosses. conclusively, it was proposed that incomplete dominance of deleterious alleles contributes to grain yield heterosis in elite crosses(Exp. 1).

关键词： Hybrid wheat Genomic evolutionary rate profiling Deleterious SNP Heterotic Quantitative trait loci

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Integration of genomic selection with doubled-haploid evaluation in hybrid breeding: From GS 1.0 to GS 4.0 and beyond

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Molecular Plant 2022年第4期15卷 577-580页

作者： Junjie Fu Yangfan Hao Huihui Li jochen c.reif Shaojiang chen changling Huang Guoying Wang Xinhai Li Yunbi Xu Liang Li Institute of crop Sciences Chinese Academy of Agricultural SciencesBeijing 100081China Leibniz Institute of Plant Genetics and crop Plant Research(IPK) 06466 Stadt SeelandGermany college of Agronomy and Biotechnology China Agricultural UniversityBeijing 100193China International Maize and Wheat Improvement center(cIMMYT) El BatanTexcoco 56130Mexico

DOUBLED-HAPLOID TEcHNOLOGY FAcES A GREAT cHALLENGE FOR HYBRID BREEDING,Ensuring food security for the ever-growing population is a common mission and a great challenge for agricultural scientists worldwide.Historically,advances in crop breeding and management practices have contributed substantially to crop productivity.Indeed,the substantial increase in global grain yields over the last eight decades is largely due to the adoption of hybrids.However,the rate of increase of hybrid yields began to slow down in the early 2000s,and since then,it has reached a plateau for many crops and regions(https://***).Therefore,we must find solutions to accelerating genetic gain and boost hybrid development,for which developing new breeding technologies provides novel creative opportunities.

关键词： breeding crops doubled

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QTL mapping of qScN3-1 for resistance to soybean cyst nematode in soybean line Zhongpin 03-5373

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The crop Journal 2021年第2期9卷 351-359页

作者： Lei Yang Yu Tian Yulin Liu jochen c.reif Yinghui Li Lijuan Qiu The National Key Facility for crop Gene Resources and Genetic Improvement(NFcRI)/Key Lab of Germplasm Utilization(MOA) Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijing 100081China college of Forestry Northwest A&F UniversityYangling 712100ShaanxiChina Department of Breeding Research Leibniz Institute of Plant Genetics and Crop Plant Research(IPK)GaterslebenGermany

Soybean cyst nematode(ScN,Heterodera glycines Ichinohe)is one of the most economically destructive pathogens.The soybean line Zhongpin03-5373(ZP),which combines resistance genes from several donors,is highly resistant to ScN race 3(ScN3).In our previous study,two QTL(rhg1 and GmSNAP11)were identified in a population of recombinant inbred lines derived from a cross between ZP and the susceptible parent Zhonghuang 13.The two QTL explained around one-third of the resistance,suggesting the presence of further QTL contributing to ScN resistance.In the present study,we used an improved version of the geneticmap comprising the previously applied 1062 molecular markers and 47 newly developed InDel(insertion-deletion)markers.The improved map revealed a novel locus contributing to ScN3 resistance:qScN3-1,flanked by InDelmarker InDel1-7 and SNPmarker Map-0047,explained 4.55%of the phenotypic variance for resistance to ScN3 and was not involved in digenic epistatic interaction with rhg1 and GmSNAP11.Haplotypes of Map-0047_cAPS(a cAPS marker developed for Map-0047)and InDel1-7 were significantly associated with ScN3 resistance in a panel of 209 resistant and susceptible accessions.Using further allele-combination analysis for three functional markers representing three cloned resistance genes(rhg1,Rhg4,andGmSNAP11)and twomarkers flanking qScN3-1,we found that adding the resistance allele of qScN3-1 greatly increased soybean resistance to ScN,even in diverse genetic backgrounds.The qScN3-1 locus will be useful for marker-assisted polygene pyramid breeding and should be targeted for the future identification of candidate genes.

关键词： Allelic combination InDel Pyramid Soybean cyst nematode

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Deep genotyping of the gene GmSNAP facilitates pyramiding resistance to cyst nematode in soybean

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The crop Journal 2019年第5期7卷 677-684页

作者： Yu Tian Bo Liu Xuehui Shi jochen c.reif Rongxia Guan Ying-hui Li Li-juan Qiu The National Key Facility for crop Gene Resources and Genetic Improvement(NFcRI)/Key Lab of Germplasm Utilization(MOA) Institute of Crop SciencesChinese Academy of Agricultural Sciences100081 BeijingChina Department of Breeding Research Leibniz Institute of Plant Genetics and Crop Plant Research(IPK)GaterslebenGermany

Soybean cyst nematode(ScN)is a highly destructive pathogen.The soybean host genome harbors at least two major genes for resistance(rhg1 and Rhg4),as well as a minor locus(ScN3-11).In the present study,a splicing site in GmSNAP11,the potential causal gene of ScN3-11,was identified by comparison of the GmSNAP11 cDNA sequences generated from resistant and susceptible soybean accessions.The sequence information was used to design a codominant cAPS marker,GmSNAP11-2565,which was used to genotype a panel of 209 soybean accessions varying with respect to ScN resistance.Analyses of the effect of the haplotypes formed by GmSNAP11-2565 and another large-effect(nonsynonymous)locus,GmSNAP11-2307,previously identified in GmSNAP11,revealed linkage disequilibrium(Pci,suggesting that GmSNAP11-2565 could be used as a marker for GmSNAP11.GmSNAP11-2565 was accordingly used,along with established markers for GmSNAP18(rhg1)and GmSHMT(Rhg4),to characterize the panel accessions.The mean ScN female index of accessions carrying only the GmSNAP11 allele associated with resistance(20.3%)was higher than that associated with accessions carrying alleles for resistance at both GmSNAP11 and GmSNAP18(12.4%),while the index for accessions carrying alleles for resistance at all of GmSNAP11,GmSNAP18,and GmSHMT was very low(1.9%).Selection on all three markers was effective for maintaining a high level of resistance to ScN race 3.

关键词： ScN α-SNAP Allelic combination Marker-assisted selection(MAS) Haplotype analysis

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Genome-wide prediction for hybrids between parents with distinguished difference on exotic introgressions in Brassica napus

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The crop Journal 2021年第5期9卷 1169-1178页

作者： Dandan Hu Yusheng Zhao Jinxiong Shen Xiangxiang He Yikai Zhang Yong Jiang Rod Snowdon Jinling Meng jochen c.reif Jun Zou National Key Laboratory of crop Genetic Improvement College of Plant Science&TechnologyHuazhong Agricultural UniversityWuhan 430070HubeiChina Department of Breeding Research Leibniz Institute of Plant Genetics and Crop Plant Research(IPK)Stadt Seeland 06466Germany Department of Plant Breeding IFZ Research Centre for BiosystemsLand Use and NutritionJustus Liebig UniversityGiessen 35392Germany

Extensive exotic introgression could significantly enlarge the genetic distance of hybrid parental populations to promote strong heterosis.The goal of this study was to investigate whether genome-wide prediction can support pre-breeding in populations with exotic introgressions.We evaluated seed yield,seed yield related traits and seed quality traits of 363 hybrids of Brassica napus (AAcc) derived from two parental populations divergent on massive exotic introgression of related species in three environments.The hybrids presented strong heterosis on seed yield,which was much higher than other investigated traits.Five genomic best linear unbiased prediction models considering the exotic introgression and different marker effects (additive,dominance,and epistatic effects) were constructed to test the prediction ability for different traits of the hybrids.The analysis showed that the trait complexity,exotic introgression,genetic relationship between the training set and testing set,training set size,and environments affected the prediction ability.The models with best prediction ability for different traits varied.However,relatively high prediction ability (e.g.,0.728 for seed yield) was also observed when the simplest models were used,excluding the effects of the special exotic introgression and epistasis effect by5-fold cross validation,which would simplify the prediction for the trait with complex architecture for hybrids with exotic introgression.The results provide novel insights and strategies for genome-wide prediction of hybrids between genetically distinct parent groups with exotic introgressions.

关键词： Hybrid Genome-wide prediction Exotic introgression Brassica napus Heterosis

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Genome-wide prediction in a hybrid maize population adapted to Northwest china

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The crop Journal 2020年第5期8卷 830-842页

作者： Guoliang Li Yuan Dong Yusheng Zhao Xiaokang Tian Tobias Würschum Jiquan Xue Shaojiang chen jochen c.reif Shutu Xu Wenxin Liu National Maize Improvement center of china Key Laboratory of Crop Heterosis and Utilization(MOE)China Agricultural UniversityBeijing 100193China Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region(Ministry of Agriculture) College of AgronomyNorthwest A&F UniversityYangling 712100ShaanxiChina Department of Breeding Research Leibniz Institute of Plant Genetics and Crop Plant Research(IPK)06466 Stadt SeelandGermany Institute of Plant Breeding Seed Science and Population GeneticsUniversity of Hohenheim70599 StuttgartGermany

Genome-wide prediction is a promising approach to boost selection gain in hybrid breeding.Our main objective was to evaluate the potential and limits of genome-wide prediction to identify superior hybrid combinations adapted to Northwest china.A total of 490 hybrids derived from crosses among 119 inbred lines from the Shaan A and Shaan B heterotic pattern were used for genome-wide prediction of ten agronomic traits.We tested eight different statistical prediction models considering additive(A)effects and in addition evaluated the impact of dominance(D)and epistasis(E)on the prediction ability.Employing five-fold cross validation,we show that the average prediction ability ranged from 0.386 to 0.794 across traits and models.Six parametric methods,i.***.ridge regression,LASSO,Elastic Net,Bayes B,Bayes c and reproducing kernel Hilbert space(RKHS)approach,displayed a very similar prediction ability for each trait and two non-parametric methods(random forest and support vector machine)had a higher prediction performance for the trait rind penetrometer resistance of the third internode above ground(RPR_TIAG).The models of A+D RKHS and A+D+E RKHS were slightly better for predicting traits with a relatively high non-additive variance.Integrating trait-specific markers into the A+D RKHS model improved the prediction ability of grain yield by 3%,from 0.528 to 0.558.Of all 6328 potential hybrids,selection of the top 44 hybrids would lead to a 6%increase in grain yield compared with Zhengdan 958,a commercially successful hybrid variety.In conclusion,our results substantiate the value of genome-wide prediction for hybrid breeding and suggest dozens of promising single crosses for developing high-yielding hybrids for Northwest china.

关键词： breeding prediction forest

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Genome-wide signatures of the geographic expansion and breeding of soybean

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Science china(Life Sciences) 2023年第2期66卷 350-365页

作者： Ying-Hui Li chao Qin Li Wang chengzhi Jiao Huilong Hong Yu Tian Yanfei Li Guangnan Xing Jun Wang Yongzhe Gu Xingpeng Gao Delin Li Hongyu Li Zhangxiong Liu Xin Jing Beibei Feng Tao Zhao Rongxia Guan Yong Guo Jun Liu Zhe Yan Lijuan Zhang Tianli Ge Xiangkong Li Xiaobo Wang Hongmei Qiu Wanhai Zhang Xiaoyan Luan Yingpeng Han Dezhi Han Ruzhen chang Yalong Guo jochen c.reif Scott A.Jackson Bin Liu Shilin Tian Li-juan Qiu The National Key Facility for crop Gene Resources and Genetic Improvement(NFcRI)/Key Laboratory of crop Gene Resource and Germplasm Enhancement(MOA)/Key Laboratory of Soybean Biology(Beijing)(MOA) Institute of Crop ScienceChinese Academy of Agricultural SciencesBeijing 100081China Shenzhen Branch Guangdong Laboratory for Lingnan Modern Agriculture/Genome Analysis Laboratory of the Ministry of Agriculture/Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural SciencesShenzhen 518000China Novogene Bioinformatics Institute Beijing 100098China State Key Laboratory of crop Genetics and Germplasm Enhancement/cytogenetics Institute Nanjing Agricultural UniversityNanjing 210095China Soybean Research Institute/MOA National center for Soybean Improvement/MOA Key Laboratory for Biology and Genetic Improvement of Soybean(General)/State Key Laboratory for crop Genetics and Germplasm Enhancement Nanjing Agricultural UniversityNanjing 210095China college of Agriculture Yangtze UniversityJingzhou 451199China School of Agronomy Anhui Agricultural UniversityHefei 230036China Jilin Academy of Agricultural Sciences Changchun 130119China Hulun Buir Institution of Agricultural Sciences Hulun Buir 021008China Soybean Research Institute Heilongjiang Academy of Agricultural SciencesHarbin 150086China Key Laboratory of Soybean Biology in chinese Ministry of Education(Key Laboratory of Soybean Biology and Breeding/Genetics of chinese Agriculture Ministry) Northeast Agricultural UniversityHarbin 150030China Heihe Branch of Heilongjiang Academy of Agricultural Sciences Harbin 150086China State Key Laboratory of Systematic and Evolutionary Botany Institute of BotanyChinese Academy of SciencesBeijing 100093China Department of Breeding Research Leibniz Institute of Plant Genetics and Crop Plant Research(IPK)Gatersleben DE D-06466Germany center for Applied Genetic Technologies University of GeorgiaAthens 30602USA Department of Ecology/Tibetan centre for Ecology and conservation at WHU-TU/Hubei Key

Soybean is a leguminous crop that provides oil and protein. Exploring the genomic signatures of soybean evolution is crucial for breeding varieties with improved adaptability to environmental extremes. We analyzed the genome sequences of 2,214 soybeans and proposed a soybean evolutionary route, i.e., the expansion of annual wild soybean(Glycine soja Sieb. & Zucc.) from southern china and its domestication in central china, followed by the expansion and local breeding selection of its landraces(G. max(L.) Merr.). We observed that the genetic introgression in soybean landraces was mostly derived from sympatric rather than allopatric wild populations during the geographic expansion. Soybean expansion and breeding were accompanied by the positive selection of flowering time genes, including GmSPA3c. Our study sheds light on the evolutionary history of soybean and provides valuable genetic resources for its future breeding.

关键词： soybean adaptation introgression flowering time breeding

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ALS-linked c9orf72 dipeptide repeats inhibit starvation-induced autophagy through modulating BcL2–BEcN1 interaction

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Acta Pharmaceutica Sinica B 2024年第5期14卷 2026-2038页

作者： Shiqiang Xu Qilian Ma Junwen Shen Ningning Li Shan Sun Nana Wang Yang chen chunsheng Dong Kin Yip Tam jochen H.M.Prehn Hongfeng Wang Zheng Ying Jiangsu Key Laboratory of Neuropsychiatric Diseases and college of Pharmaceutical Sciences Soochow UniversitySuzhou 215123China MOE Key Laboratory of Geriatric Diseases and Immunology College of Pharmaceutical SciencesSuzhou Medical College of Soochow UniversitySuzhou 215123China Jiangsu Province Engineering Research center of Precision Diagnostics and Therapeutics Development Soochow UniversitySuzhou 215123China Dept.of Physiology&Medical Physics and FUTURE-NEURO Research centre Royal College of Surgeons in IrelandDublin D02 YN77Ireland Faculty of Health Sciences University of MacaoTaipaMacao 999078China Insititutes of Biology and Medical Science Soochow UniversitySuzhou 215123China

Growing evidences indicate that dysfunction of autophagy contributes to the disease pathogenesis of amyotrophic lateral sclerosis(ALS)and frontotemporal dementia(FTD),two neurodegenerative disorders.The GGGGcc·GGcccc repeat RNA expansion in chromosome 9 open reading frame 72(c9orf72)is the most genetic cause of both ALS and FTD.According to the previous studies,GGGGcc·GGcccc repeat undergoes the unconventional repeat-associated non-ATG translation,which produces dipeptide repeat(DPR)proteins.Although there is a growing understanding that c9orf72 DPRs have a strong ability to harm neurons and induce c9orf72-linked ALS/FTD,whether these DPRs can affect autophagy remains unclear.In the present study,we find that poly-GR and poly-PR,two arginine-containing DPRs which display the most cytotoxic properties according to the previous studies,strongly inhibit starvation-induced autophagy.Moreover,our data indicate that arginine-rich DPRs enhance the interaction between BcL2 and BEcN1/Beclin 1 by inhibiting BcL2 phosphorylation,therefore they can impair autophagic clearance of neurodegenerative disease-associated protein aggregates under starvation condition in cells.Importantly,our study not only highlights the role of c9orf72 DPR in autophagy dysfunction,but also provides novel insight that pharmacological intervention of autophagy using SW063058,a small molecule compound that can disrupt the interaction between BEcN1 and BcL2,may reduce c9orf72 DPR-induced neurotoxicity.

关键词： Amyotrophic lateral sclerosis Frontotemporal dementia c9orf72 Autophagy BcL2 BEcN1/Beclin 1 Dipeptide repeat Neurodegeneration

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群体构成方式对大豆百粒重全基因组选择预测准确度的影响

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作物学报 2018年第1期44卷 43-52页

作者：马岩松刘章雄文自翔魏淑红杨春明王会才杨春燕卢为国徐冉张万海吴纪安胡国华栾晓燕付亚书郭泰王曙明韩天富张孟臣张磊苑保军郭勇 jochen c.reif 江勇李文滨王德春邱丽娟中国农业科学院作物科学研究所/国家农作物基因资源与遗传改良重大科学工程/农业部作物种质资源与生物技术重点开放实验室北京100081 东北农业大学农学院黑龙江哈尔滨150030 DepartmentofPlant SoilandMicrobialSciencesMichiganStateUniversityEastLansingMI48824USA 黑龙江省农业科学院育种研究所黑龙江哈尔滨150081 吉林省农业科学院大豆研究所吉林长春130033 内蒙古

百粒重是大豆产量的重要构成因子,在一定条件下与产量呈显著正相关。百粒重是一个复杂的数量性状,用传统的育种方法其遗传增益不明显。本研究对280份大豆品种进行了多年多点田间鉴定,通过混合线性模型预测获得品种百粒重的最佳线性无偏... 详细信息

百粒重是大豆产量的重要构成因子,在一定条件下与产量呈显著正相关。百粒重是一个复杂的数量性状,用传统的育种方法其遗传增益不明显。本研究对280份大豆品种进行了多年多点田间鉴定,通过混合线性模型预测获得品种百粒重的最佳线性无偏预测值。同时利用分布在大豆全基因组的5361个SNP标记鉴定参试品种基因型,结合随机回归最佳线性无偏预测模型和交互验证方法,探讨了群体构成方式对大豆百粒重的全基因组选择预测准确度的影响。结果表明,大豆百粒重的全基因组选择预测准确度变化范围为–0.15^+0.75;群体构成方式对百粒重的预测准确度影响明显;亚群内的预测准确度(+0.24^+0.75)高于亚群间(-0.15^+0.29);当群体间遗传距离由0.1566增加到0.2201时,预测准确度下降27.87%;相比随机构建的训练群体,基于群体遗传结构构建的训练群体能将百粒重的预测准确度提高2.34%。本研究明确了大豆百粒重的全基因组选择预测准确度,阐明了群体结构对大豆百粒重的全基因组选择预测准确度的影响,为大豆分子育种提供了新的思路和方法。

关键词：大豆百粒重全基因组选择预测准确度遗传结构

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