1
|
Chen Y, Ji J, Kong D, Tang X, Wen M, Wang G, Dai K, Shi P, Zhang X, Zhang H, Jiao C, Wang Z, Sun L, Yuan C, Wang H, Zhang X, Sun B, Fei X, Guo H, Xiao J, Wang X. Resistance of QYm.nau-2D to wheat yellow mosaic virus was derived from an alien introgression into common wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:3. [PMID: 36651948 DOI: 10.1007/s00122-023-04286-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 10/31/2022] [Indexed: 06/17/2023]
Abstract
The QYm.nau-2D locus conferring wheat yellow mosaic virus resistance is an exotic introgression and we developed 11 diagnostic markers tightly linked to QYm.nau-2D. Wheat yellow mosaic virus (WYMV) is a serious disease of winter wheat in China. Breeding resistant varieties is the most effective strategy for WYMV control. A WYMV resistant locus QYm.nau-2D on the chromosome arm 2DL has been repeatedly reported but the mapped region is large. In the present study, we screened recombinants using a biparental population and mapped QYm.nau-2D into an 18.8 Mb physical interval. By genome-wide association studies of 372 wheat varieties for WYMV resistance in four environments, we narrowed down QYm.nau-2D into a 16.4 Mb interval. Haplotype analysis indicated QYm.nau-2D were present as six different states due to recombination during hybridization breeding. QYm.nau-2D was finally mapped into a linkage block of 11.2 Mb. Chromosome painting using 2D specific probes and collinearity analysis among the published sequences corresponding to QYm.nau-2D region indicated the block was an exotic introgression. The Illumina-sequenced reads of four diploid Aegilops species were mapped to the sequence of Fielder, a variety having the introgression. The mapping reads were significantly increased at the putative introgression regions of Fielder. Ae. uniaristata (NN) had the highest mapping reads, suggesting that QYm.nau-2D was possibly an introgression from genome N. We investigated the agronomic performances of different haplotypes and observed no linkage drag of the alien introgression for the 15 tested traits. For marker-assisted selection of QYm.nau-2D, we developed 11 diagnostic markers tightly linked to the locus. This research provided a case study of an exotic introgression, which has been utilized in wheat improvement for WYMV resistance.
Collapse
Affiliation(s)
- Yiming Chen
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
| | - Jialun Ji
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
| | - Dehui Kong
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
| | - Xiong Tang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
| | - Mingxing Wen
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
- Zhenjiang Institute of Agricultural Science, Jurong, Jiangsu, 212400, China
| | - Guoqing Wang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
| | - Keli Dai
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
- College of Agriculture, Shanxi Agricultural University, Taigu, Shanxi, 030801, China
| | - Peiyao Shi
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
| | - Xu Zhang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
| | - Huajian Zhang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
| | - Chengzhi Jiao
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
| | - Zongkuan Wang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
| | - Li Sun
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
| | - Chunxia Yuan
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
| | - Haiyan Wang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China
| | - Xueyong Zhang
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Science, Beijing, 100081, China
| | - Bingjian Sun
- College of Plant Protection, Henan Agricultural University, Zhengzhou, Henan, 450002, China
| | - Xinru Fei
- Yandu District Agricultural Science Research Institute, Yancheng, Jiangsu, 224011, China
| | - Hong Guo
- Yandu District Agricultural Science Research Institute, Yancheng, Jiangsu, 224011, China
| | - Jin Xiao
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China.
| | - Xiue Wang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University/JCIC-MCP, Nanjing, Jiangsu, 210095, China.
| |
Collapse
|
2
|
Development of genic SSR marker resources from RNA-seq data in Camellia japonica and their application in the genus Camellia. Sci Rep 2021; 11:9919. [PMID: 33972624 PMCID: PMC8110538 DOI: 10.1038/s41598-021-89350-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 04/26/2021] [Indexed: 11/12/2022] Open
Abstract
Camellia is a genus of flowering plants in the family Theaceae, and several species in this genus have economic importance. Although a great deal of molecular makers has been developed for molecular assisted breeding in genus Camellia in the past decade, the number of simple sequence repeats (SSRs) publicly available for plants in this genus is insufficient. In this study, a total of 28,854 potential SSRs were identified with a frequency of 4.63 kb. A total of 172 primer pairs were synthesized and preliminarily screened in 10 C. japonica accessions, and of these primer pairs, 111 were found to be polymorphic. Fifty-one polymorphic SSR markers were randomly selected to perform further analysis of the genetic relationships of 89 accessions across the genus Camellia. Cluster analysis revealed major clusters corresponding to those based on taxonomic classification and geographic origin. Furthermore, all the genotypes of C. japonica separated and consistently grouped well in the genetic structure analysis. The results of the present study provide high-quality SSR resources for molecular genetic breeding studies in camellia plants.
Collapse
|
3
|
Trigo BB, Oliveira-Rovai FMD, Milanesi M, Ito PKRK, Utsunomiya YT, Lopes FL, Paulan SDC, Nunes CM. In silico and in vitro evaluation of primers for molecular differentiation of Leishmania species. ACTA ACUST UNITED AC 2021; 30:e022020. [PMID: 33729316 DOI: 10.1590/s1984-296120201078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 10/22/2020] [Indexed: 11/22/2022]
Abstract
Leishmaniasis is a zoonotic disease caused by over 20 species of protozoan parasites of the genus Leishmania. Infection is commonly spread by sandflies and produces a wide spectrum of clinical signs and symptoms. Therefore, from an epidemiological and therapeutic standpoint, it is important to detect and differentiate Leishmania spp. The objective of this study was to combinate in silico and in vitro strategies to evaluate the analytical specificity of primers previously described in the literature. According to electronic PCR (e-PCR) analysis, 23 out of 141 pairs of primers selected through literature search matched their previously reported analytical specificity. In vitro evaluation of nine of these primer pairs by quantitative PCR (qPCR) confirmed the analytical specificity of five of them at the level of Leishmania spp., L. mexicana complex or Leishmania and Viannia subgenera. Based on these findings, the combination of e-PCR and qPCR is suggested to be a valuable approach to maximize the specificity of new primer pairs for the laboratory diagnosis of infections with Leishmania spp.
Collapse
Affiliation(s)
- Beatriz Batista Trigo
- Faculdade de Medicina Veterinária, Universidade Estadual Paulista - UNESP, Araçatuba, SP, Brasil
| | | | - Marco Milanesi
- Faculdade de Medicina Veterinária, Universidade Estadual Paulista - UNESP, Araçatuba, SP, Brasil.,Centro Colaborador da Agência Internacional de Energia Atômica - IAEA em Genômica Animal e Bioinformática, Araçatuba, SP, Brasil
| | | | - Yuri Tani Utsunomiya
- Faculdade de Medicina Veterinária, Universidade Estadual Paulista - UNESP, Araçatuba, SP, Brasil.,Centro Colaborador da Agência Internacional de Energia Atômica - IAEA em Genômica Animal e Bioinformática, Araçatuba, SP, Brasil
| | - Flávia Lombardi Lopes
- Faculdade de Medicina Veterinária, Universidade Estadual Paulista - UNESP, Araçatuba, SP, Brasil
| | - Silvana de Cássia Paulan
- Faculdade de Medicina Veterinária, Universidade Estadual Paulista - UNESP, Araçatuba, SP, Brasil
| | - Cáris Maroni Nunes
- Faculdade de Medicina Veterinária, Universidade Estadual Paulista - UNESP, Araçatuba, SP, Brasil
| |
Collapse
|
4
|
Leow SS, Lee WK, Khoo JS, Teoh S, Hoh CC, Fairus S, Sambanthamurthi R, Hayes KC. Identification of reference genes for real-time polymerase chain reaction gene expression studies in Nile rats fed Water-Soluble Palm Fruit Extract. Mol Biol Rep 2020; 47:9409-9427. [PMID: 33222119 DOI: 10.1007/s11033-020-06003-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 11/11/2020] [Indexed: 12/17/2022]
Abstract
The Nile rat (Arvicanthis niloticus) is a novel diurnal carbohydrate-sensitive rodent useful for studies on type 2 diabetes mellitus (T2DM) and the metabolic syndrome. Hepatic responses to T2DM and any interventions thereof can be evaluated via transcriptomic gene expression analysis. However, the study of gene expression via real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) requires identification of stably expressed reference genes for accurate normalisation. This study describes the evaluation and identification of stable reference genes in the livers from Control Nile rats as well as those supplemented with Water-Soluble Palm Fruit Extract, which has been previously shown to attenuate T2DM in this animal model. Seven genes identified as having stable expression in RNA-Sequencing transcriptome analysis were chosen for verification using real-time RT-qPCR. Six commonly used reference genes from previous literature and two genes from a previous microarray gene expression study in Nile rats were also evaluated. The expression data of these 15 candidate reference genes were analysed using the RefFinder software which incorporated analyses performed by various algorithms. The Hpd, Pnpla6 and Vpp2 genes were identified as the most stable across the 36 samples tested. Their applicability was demonstrated through the normalisation of the gene expression profiles of two target genes, Cela1 and Lepr. In conclusion, three novel reference genes which can be used for robust normalisation of real-time RT-qPCR data were identified, thereby facilitating future hepatic gene expression studies in the Nile rat.
Collapse
Affiliation(s)
- Soon-Sen Leow
- Malaysian Palm Oil Board, No. 6, Persiaran Institusi, Bandar Baru Bangi, 43000, Kajang, Selangor, Malaysia.
| | - Wei-Kang Lee
- Codon Genomics Sdn Bhd, No. 26, Jalan Dutamas 7, Taman Dutamas Balakong, 43200, Seri Kembangan, Selangor, Malaysia
| | - Jia-Shiun Khoo
- Codon Genomics Sdn Bhd, No. 26, Jalan Dutamas 7, Taman Dutamas Balakong, 43200, Seri Kembangan, Selangor, Malaysia
| | - Seddon Teoh
- Codon Genomics Sdn Bhd, No. 26, Jalan Dutamas 7, Taman Dutamas Balakong, 43200, Seri Kembangan, Selangor, Malaysia
| | - Chee-Choong Hoh
- Codon Genomics Sdn Bhd, No. 26, Jalan Dutamas 7, Taman Dutamas Balakong, 43200, Seri Kembangan, Selangor, Malaysia
| | - Syed Fairus
- Malaysian Palm Oil Board, No. 6, Persiaran Institusi, Bandar Baru Bangi, 43000, Kajang, Selangor, Malaysia
| | - Ravigadevi Sambanthamurthi
- Malaysian Palm Oil Board, No. 6, Persiaran Institusi, Bandar Baru Bangi, 43000, Kajang, Selangor, Malaysia
| | - K C Hayes
- Brandeis University, 415 South Street, Waltham, MA, 02454, USA
| |
Collapse
|
5
|
Guo L, Yang Q, Yang JW, Zhang N, Liu BS, Zhu KC, Guo HY, Jiang SG, Zhang DC. MultiplexSSR: A pipeline for developing multiplex SSR-PCR assays from resequencing data. Ecol Evol 2020; 10:3055-3067. [PMID: 32211176 PMCID: PMC7083706 DOI: 10.1002/ece3.6121] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 02/02/2020] [Accepted: 02/05/2020] [Indexed: 12/15/2022] Open
Abstract
Next-generation sequencing has greatly promoted the investigation of single nucleotide polymorphisms, while studies of simple sequence repeats are sharply decreasing. However, simple sequence repeats still present some advantages in conservation genetics. In this study, an end-to-end pipeline referred to as MultiplexSSR was established to develop multiplex PCR assays in batches with highly polymorphic simple sequence repeats for capillary platforms from resequencing data. The distribution of single sequence repeats in the genome, the error profiles of genotypes and allelotypes, and the increase in the allele length range depending on the number of individuals were investigated. A total of 98% of single sequence repeats presented lengths of less than 100 bp. The error rate of the genotyping and allelotyping of dimeric patterns was ten times higher than those for other patterns. The error rate of allelotyping was less than that of genotyping. The allele length range reached approximate saturation with 10 individuals. This pipeline uses allele numbers to select highly polymorphic loci, masks loci with variation, and applies in silico PCR to improve primer specificity. The application of the developed multiplex SSR-PCR assays validated the pipeline's robustness, showing higher polymorphism and stability for the developed simple sequence repeats and a lower cost for genotyping and providing low-depth resequencing data from less than a dozen individuals for the development of markers. This pipeline fills the gap between next-generation sequencing and multiplex SSR-PCR.
Collapse
Affiliation(s)
- Liang Guo
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization Ministry of Agriculture and Rural Affairs South China Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Guangzhou China
- Guangdong Provincial Engineer Technology Research Center of Marine Biological Seed Industry Guangzhou China
| | - Quan Yang
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization Ministry of Agriculture and Rural Affairs South China Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Guangzhou China
- Guangdong Provincial Engineer Technology Research Center of Marine Biological Seed Industry Guangzhou China
- National Demonstration Center for Experimental Fisheries Science Education Shanghai Ocean University Shanghai China
| | - Jing-Wen Yang
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization Ministry of Agriculture and Rural Affairs South China Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Guangzhou China
- Guangdong Provincial Engineer Technology Research Center of Marine Biological Seed Industry Guangzhou China
| | - Nan Zhang
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization Ministry of Agriculture and Rural Affairs South China Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Guangzhou China
- Guangdong Provincial Engineer Technology Research Center of Marine Biological Seed Industry Guangzhou China
| | - Bao-Suo Liu
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization Ministry of Agriculture and Rural Affairs South China Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Guangzhou China
- Guangdong Provincial Engineer Technology Research Center of Marine Biological Seed Industry Guangzhou China
| | - Ke-Cheng Zhu
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization Ministry of Agriculture and Rural Affairs South China Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Guangzhou China
- Guangdong Provincial Engineer Technology Research Center of Marine Biological Seed Industry Guangzhou China
| | - Hua-Yang Guo
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization Ministry of Agriculture and Rural Affairs South China Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Guangzhou China
- Guangdong Provincial Engineer Technology Research Center of Marine Biological Seed Industry Guangzhou China
| | - Shi-Gui Jiang
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization Ministry of Agriculture and Rural Affairs South China Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Guangzhou China
- Guangdong Provincial Engineer Technology Research Center of Marine Biological Seed Industry Guangzhou China
| | - Dian-Chang Zhang
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization Ministry of Agriculture and Rural Affairs South China Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Guangzhou China
- Guangdong Provincial Engineer Technology Research Center of Marine Biological Seed Industry Guangzhou China
| |
Collapse
|
6
|
Fredua-Agyeman R, Yu Z, Hwang SF, Strelkov SE. Genome-Wide Mapping of Loci Associated With Resistance to Clubroot in Brassica napus ssp. napobrassica (Rutabaga) Accessions From Nordic Countries. FRONTIERS IN PLANT SCIENCE 2020; 11:742. [PMID: 32595668 PMCID: PMC7303339 DOI: 10.3389/fpls.2020.00742] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 05/08/2020] [Indexed: 05/12/2023]
Abstract
Rutabaga [Brassica napus ssp. napobrassica (L.) Hanelt] is reported to be an excellent source of clubroot (Plasmodiophora brassicae) resistance genes. In this study, 124 rutabaga accessions from the Nordic countries (Norway, Sweden, Finland, Denmark, and Iceland) were evaluated for their reaction to five single-spore isolates representing P. brassicae pathotypes 2F, 3H, 5I, 6M, and 8N and 12 field isolates representing pathotypes 2B, 3A, 3O, 5C, 5G, 5K, 5L, 5X (two isolates, L-G2 and L-G3), 8E, 8J, and 8P. The accessions were also genotyped using a 15K Brassica SNP array and 60 PCR-based primers linked to previously identified clubroot resistance genes. Six thousand eight hundred sixty-one SNP markers were retained after filtering with TASSEL 5.0, and used to evaluate four general linear models (GLM) and four mixed linear models (MLM). The PCA + K and Q + K MLM models gave the minimal deviance of the observed from the expected distribution in quantile-quantile plots, and hence were used for SNP-clubroot association analyses. In addition, 108 alleles derived from the PCR-based markers and the phenotypic data were analyzed with the PCA + K model. Forty-five SNPs and four PCR-based markers were identified to be associated strongly with resistance to isolates representing 13 pathotypes (2F, 3H, 5I, 6M, 8N, 2B, 3A, 3O, 5C, 5G, 5K, 5L, and 8P). These markers revealed the top and bottom segments of rutabaga chromosome A03 and the middle segment of chromosome A08 as genomic hotspots associated with resistance to the different P. brassicae pathotypes.
Collapse
|
7
|
Lu Q, Hong Y, Li S, Liu H, Li H, Zhang J, Lan H, Liu H, Li X, Wen S, Zhou G, Varshney RK, Jiang H, Chen X, Liang X. Genome-wide identification of microsatellite markers from cultivated peanut (Arachis hypogaea L.). BMC Genomics 2019; 20:799. [PMID: 31675924 PMCID: PMC6824139 DOI: 10.1186/s12864-019-6148-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Accepted: 09/29/2019] [Indexed: 12/03/2022] Open
Abstract
Background Microsatellites, or simple sequence repeats (SSRs), represent important DNA variations that are widely distributed across the entire plant genome and can be used to develop SSR markers, which can then be used to conduct genetic analyses and molecular breeding. Cultivated peanut (A. hypogaea L.), an important oil crop worldwide, is an allotetraploid (AABB, 2n = 4× = 40) plant species. Because of its complex genome, genomic marker development has been very challenging. However, sequencing of cultivated peanut genome allowed us to develop genomic markers and construct a high-density physical map. Results A total of 8,329,496 SSRs were identified, including 3,772,653, 4,414,961, and 141,882 SSRs that were distributed in subgenome A, B, and nine scaffolds, respectively. Based on the flanking sequences of the identified SSRs, a total of 973,984 newly developed SSR markers were developed in subgenome A (462,267), B (489,394), and nine scaffolds (22,323), with an average density of 392.45 markers per Mb. In silico PCR evaluation showed that an average of 88.32% of the SSR markers generated only one in silico-specific product in two tetraploid A. hypogaea varieties, Tifrunner and Shitouqi. A total of 39,599 common SSR markers were identified among the two A. hypogaea varieties and two progenitors, A. duranensis and A. ipaensis. Additionally, an amplification effectiveness of 44.15% was observed by real PCR validation. Moreover, a total of 1276 public SSR loci were integrated with the newly developed SSR markers. Finally, a previously known leaf spot quantitative trait locus (QTL), qLLS_T13_A05_7, was determined to be in a 1.448-Mb region on chromosome A05. In this region, a total of 819 newly developed SSR markers were located and 108 candidate genes were detected. Conclusions The availability of these newly developed and public SSR markers both provide a large number of molecular markers that could potentially be used to enhance the process of trait genetic analyses and improve molecular breeding strategies for cultivated peanut.
Collapse
Affiliation(s)
- Qing Lu
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Guangdong Provincial Key Laboratory for Crop Genetic Improvement, Guangzhou, 510640, China
| | - Yanbin Hong
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Guangdong Provincial Key Laboratory for Crop Genetic Improvement, Guangzhou, 510640, China
| | - Shaoxiong Li
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Guangdong Provincial Key Laboratory for Crop Genetic Improvement, Guangzhou, 510640, China
| | - Hao Liu
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Guangdong Provincial Key Laboratory for Crop Genetic Improvement, Guangzhou, 510640, China
| | - Haifen Li
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Guangdong Provincial Key Laboratory for Crop Genetic Improvement, Guangzhou, 510640, China
| | - Jianan Zhang
- MolBreeding Biotechnology Co., Ltd., Shijiazhuang, China
| | - Haofa Lan
- MolBreeding Biotechnology Co., Ltd., Shijiazhuang, China
| | - Haiyan Liu
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Guangdong Provincial Key Laboratory for Crop Genetic Improvement, Guangzhou, 510640, China
| | - Xingyu Li
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Guangdong Provincial Key Laboratory for Crop Genetic Improvement, Guangzhou, 510640, China
| | - Shijie Wen
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Guangdong Provincial Key Laboratory for Crop Genetic Improvement, Guangzhou, 510640, China
| | - Guiyuan Zhou
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Guangdong Provincial Key Laboratory for Crop Genetic Improvement, Guangzhou, 510640, China
| | - Rajeev K Varshney
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Huifang Jiang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Xiaoping Chen
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Guangdong Provincial Key Laboratory for Crop Genetic Improvement, Guangzhou, 510640, China.
| | - Xuanqiang Liang
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Guangdong Provincial Key Laboratory for Crop Genetic Improvement, Guangzhou, 510640, China.
| |
Collapse
|
8
|
Guo L, Yao H, Shepherd B, Sepulveda-Villet OJ, Zhang DC, Wang HP. Development of a Genomic Resource and Identification of Nucleotide Diversity of Yellow Perch by RAD Sequencing. Front Genet 2019; 10:992. [PMID: 31681426 PMCID: PMC6802114 DOI: 10.3389/fgene.2019.00992] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Accepted: 09/18/2019] [Indexed: 01/28/2023] Open
Affiliation(s)
- Liang Guo
- Aquatic Genetics and Breeding Laboratory, Ohio State University South Centers, Piketon, OH, United States.,Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, South China Sea Fisheries Research Institutes, Chinese Academy of Fishery Sciences, Guangzhou, China
| | - Hong Yao
- Aquatic Genetics and Breeding Laboratory, Ohio State University South Centers, Piketon, OH, United States
| | - Brian Shepherd
- USDA-ARS-School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
| | - Osvaldo J Sepulveda-Villet
- USDA-ARS-School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI, United States.,School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
| | - Dian-Chang Zhang
- Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, South China Sea Fisheries Research Institutes, Chinese Academy of Fishery Sciences, Guangzhou, China
| | - Han-Ping Wang
- Aquatic Genetics and Breeding Laboratory, Ohio State University South Centers, Piketon, OH, United States
| |
Collapse
|
9
|
Genome-wide analysis of SSR and ILP markers in trees: diversity profiling, alternate distribution, and applications in duplication. Sci Rep 2017; 7:17902. [PMID: 29263331 PMCID: PMC5738346 DOI: 10.1038/s41598-017-17203-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Accepted: 11/22/2017] [Indexed: 12/15/2022] Open
Abstract
Molecular markers are efficient tools for breeding and genetic studies. However, despite their ecological and economic importance, their development and application have long been hampered. In this study, we identified 524,170 simple sequence repeat (SSR), 267,636 intron length polymorphism (ILP), and 11,872 potential intron polymorphism (PIP) markers from 16 tree species based on recently available genome sequences. Larger motifs, including hexamers and heptamers, accounted for most of the seven different types of SSR loci. Within these loci, A/T bases comprised a significantly larger proportion of sequence than G/C. SSR and ILP markers exhibited an alternative distribution pattern. Most SSRs were monomorphic markers, and the proportions of polymorphic markers were positively correlated with genome size. By verifying with all 16 tree species, 54 SSR, 418 ILP, and four PIP universal markers were obtained, and their efficiency was examined by PCR. A combination of five SSR and six ILP markers were used for the phylogenetic analysis of 30 willow samples, revealing a positive correlation between genetic diversity and geographic distance. We also found that SSRs can be used as tools for duplication analysis. Our findings provide important foundations for the development of breeding and genetic studies in tree species.
Collapse
|
10
|
Zhou X, Dong Y, Zhao J, Huang L, Ren X, Chen Y, Huang S, Liao B, Lei Y, Yan L, Jiang H. Genomic survey sequencing for development and validation of single-locus SSR markers in peanut (Arachis hypogaea L.). BMC Genomics 2016; 17:420. [PMID: 27251557 PMCID: PMC4888616 DOI: 10.1186/s12864-016-2743-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 05/14/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Single-locus markers have many advantages compared with multi-locus markers in genetic and breeding studies because their alleles can be assigned to particular genomic loci in diversity analyses. However, there is little research on single-locus SSR markers in peanut. Through the de novo assembly of DNA sequencing reads of A. hypogaea, we developed single-locus SSR markers in a genomic survey for better application in genetic and breeding studies of peanut. RESULTS In this study, DNA libraries with four different insert sizes were used for sequencing with 150 bp paired-end reads. Approximately 237 gigabases of clean data containing 1,675,631,984 reads were obtained after filtering. These reads were assembled into 2,102,446 contigs with an N50 length of 1,782 bp, and the contigs were further assembled into 1,176,527 scaffolds with an N50 of 3,920 bp. The total length of the assembled scaffold sequences was 2.0 Gbp, and 134,652 single-locus SSRs were identified from 375,180 SSRs. Among these developed single-locus SSRs, trinucleotide motifs were the most abundant, followed by tetra-, di-, mono-, penta- and hexanucleotide motifs. The most common motif repeats for the various types of single-locus SSRs have a tendency to be A/T rich. A total of 1,790 developed in silico single-locus SSR markers were chosen and used in PCR experiments to confirm amplification patterns. Of them, 1,637 markers that produced single amplicons in twelve inbred lines were considered putative single-locus markers, and 290 (17.7 %) showed polymorphisms. A further F2 population study showed that the segregation ratios of the 97 developed SSR markers, which showed polymorphisms between the parents, were consistent with the Mendelian inheritance law for single loci (1:2:1). Finally, 89 markers were assigned to an A. hypogaea linkage map. A subset of 100 single-locus SSR markers was shown to be highly stable and universal in a collection of 96 peanut accessions. A neighbor-joining tree of this natural population showed that genotypes have obviously correlation with botanical varieties. CONCLUSIONS We have shown that the detection of single-locus SSR markers from a de novo genomic assembly of a combination of different-insert-size libraries is highly efficient. This is the first report of the development of genome-wide single-locus markers for A. hypogaea, and the markers developed in this study will be useful for gene tagging, sequence scaffold assignment, linkage map construction, diversity analysis, variety identification and association mapping in peanut.
Collapse
Affiliation(s)
- Xiaojing Zhou
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, Hubei, China
| | - Yang Dong
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, Hubei, China
| | - Jiaojiao Zhao
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, Hubei, China
| | - Li Huang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, Hubei, China
| | - Xiaoping Ren
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, Hubei, China
| | - Yuning Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, Hubei, China
| | - Shunmou Huang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, Hubei, China.,Databridge Technologies Corporation, Wuhan, 430062, Hubei, China
| | - Boshou Liao
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, Hubei, China
| | - Yong Lei
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, Hubei, China
| | - Liying Yan
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, Hubei, China
| | - Huifang Jiang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, Hubei, China.
| |
Collapse
|
11
|
Hane JK, Anderson JP, Williams AH, Sperschneider J, Singh KB. Genome sequencing and comparative genomics of the broad host-range pathogen Rhizoctonia solani AG8. PLoS Genet 2014; 10:e1004281. [PMID: 24810276 PMCID: PMC4014442 DOI: 10.1371/journal.pgen.1004281] [Citation(s) in RCA: 101] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2013] [Accepted: 02/20/2014] [Indexed: 11/30/2022] Open
Abstract
Rhizoctonia solani is a soil-borne basidiomycete fungus with a necrotrophic lifestyle which is classified into fourteen reproductively incompatible anastomosis groups (AGs). One of these, AG8, is a devastating pathogen causing bare patch of cereals, brassicas and legumes. R. solani is a multinucleate heterokaryon containing significant heterozygosity within a single cell. This complexity posed significant challenges for the assembly of its genome. We present a high quality genome assembly of R. solani AG8 and a manually curated set of 13,964 genes supported by RNA-seq. The AG8 genome assembly used novel methods to produce a haploid representation of its heterokaryotic state. The whole-genomes of AG8, the rice pathogen AG1-IA and the potato pathogen AG3 were observed to be syntenic and co-linear. Genes and functions putatively relevant to pathogenicity were highlighted by comparing AG8 to known pathogenicity genes, orthology databases spanning 197 phytopathogenic taxa and AG1-IA. We also observed SNP-level "hypermutation" of CpG dinucleotides to TpG between AG8 nuclei, with similarities to repeat-induced point mutation (RIP). Interestingly, gene-coding regions were widely affected along with repetitive DNA, which has not been previously observed for RIP in mononuclear fungi of the Pezizomycotina. The rate of heterozygous SNP mutations within this single isolate of AG8 was observed to be higher than SNP mutation rates observed across populations of most fungal species compared. Comparative analyses were combined to predict biological processes relevant to AG8 and 308 proteins with effector-like characteristics, forming a valuable resource for further study of this pathosystem. Predicted effector-like proteins had elevated levels of non-synonymous point mutations relative to synonymous mutations (dN/dS), suggesting that they may be under diversifying selection pressures. In addition, the distant relationship to sequenced necrotrophs of the Ascomycota suggests the R. solani genome sequence may prove to be a useful resource in future comparative analysis of plant pathogens.
Collapse
Affiliation(s)
- James K. Hane
- Molecular Plant Pathology and Crop Genomics Laboratory, Centre for Environment and Life Sciences, Division of Plant Industry, Commonwealth Scientific and Industrial Research Organisation, Floreat, Western Australia, Australia
| | - Jonathan P. Anderson
- Molecular Plant Pathology and Crop Genomics Laboratory, Centre for Environment and Life Sciences, Division of Plant Industry, Commonwealth Scientific and Industrial Research Organisation, Floreat, Western Australia, Australia
- The University of Western Australia Institute of Agriculture, University of Western Australia, Crawley, Western Australia, Australia
| | - Angela H. Williams
- Molecular Plant Pathology and Crop Genomics Laboratory, Centre for Environment and Life Sciences, Division of Plant Industry, Commonwealth Scientific and Industrial Research Organisation, Floreat, Western Australia, Australia
| | - Jana Sperschneider
- Molecular Plant Pathology and Crop Genomics Laboratory, Centre for Environment and Life Sciences, Division of Plant Industry, Commonwealth Scientific and Industrial Research Organisation, Floreat, Western Australia, Australia
| | - Karam B. Singh
- Molecular Plant Pathology and Crop Genomics Laboratory, Centre for Environment and Life Sciences, Division of Plant Industry, Commonwealth Scientific and Industrial Research Organisation, Floreat, Western Australia, Australia
- The University of Western Australia Institute of Agriculture, University of Western Australia, Crawley, Western Australia, Australia
| |
Collapse
|
12
|
Mace ES, Hunt CH, Jordan DR. Supermodels: sorghum and maize provide mutual insight into the genetics of flowering time. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2013; 126:1377-95. [PMID: 23459955 DOI: 10.1007/s00122-013-2059-z] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2012] [Accepted: 02/08/2013] [Indexed: 05/22/2023]
Abstract
Nested association mapping (NAM) offers power to dissect complex, quantitative traits. This study made use of a recently developed sorghum backcross (BC)-NAM population to dissect the genetic architecture of flowering time in sorghum; to compare the QTL identified with other genomic regions identified in previous sorghum and maize flowering time studies and to highlight the implications of our findings for plant breeding. A subset of the sorghum BC-NAM population consisting of over 1,300 individuals from 24 families was evaluated for flowering time across multiple environments. Two QTL analysis methodologies were used to identify 40 QTLs with predominately small, additive effects on flowering time; 24 of these co-located with previously identified QTL for flowering time in sorghum and 16 were novel in sorghum. Significant synteny was also detected with the QTL for flowering time detected in a comparable NAM resource recently developed for maize (Zea mays) by Buckler et al. (Science 325:714-718, 2009). The use of the sorghum BC-NAM population allowed us to catalogue allelic variants at a maximal number of QTL and understand their contribution to the flowering time phenotype and distribution across diverse germplasm. The successful demonstration of the power of the sorghum BC-NAM population is exemplified not only by correspondence of QTL previously identified in sorghum, but also by correspondence of QTL in different taxa, specifically maize in this case. The unification across taxa of the candidate genes influencing complex traits, such as flowering time can further facilitate the detailed dissection of the genetic control and causal genes.
Collapse
Affiliation(s)
- E S Mace
- Department of Agriculture, Forestry and Fisheries, Hermitage Research Station, 604 Yangan Road, Warwick, QLD 4370, Australia.
| | | | | |
Collapse
|
13
|
Smith JD, Ray DA. Expedited batch processing and analysis of transposon insertions. BMC Res Notes 2011; 4:482. [PMID: 22054356 PMCID: PMC3222620 DOI: 10.1186/1756-0500-4-482] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2011] [Accepted: 11/04/2011] [Indexed: 11/10/2022] Open
Abstract
Background With advances in sequencing technology, greater and greater amounts of eukaryotic genome data are becoming available. Often, large portions of these genomes consist of transposable elements, frequently accounting for 50% or more in vertebrates. Each transposable element family may have thousands or tens of thousands of individual copies within a given genome, and therefore it can take an exorbitant amount of time and effort to process data in a meaningful fashion. Findings In order to combat this problem, we developed a set of bioinformatics techniques and programs to streamline the analysis. This includes a unique Perl script which automates the process of taking BLAST, Repeatmasker and similar data to extract and manipulate the hit sequences from the genome. This script, called Process_hits uses an object-oriented methodology to compile all hit locations from a given file for processing, organize this data into useable categories, and output it in multiple formats. Conclusions The program proved capable of handling large amounts of transposon data in an efficient fashion. It is equipped with a number of useful sub-functions, each of which is contained within its own sub-module to allow for greater expandability and as a foundation for future program design.
Collapse
Affiliation(s)
- Jeremy D Smith
- Department of Biology, West Virginia University, Morgantown, WV 26506, USA.
| | | |
Collapse
|
14
|
Mace ES, Jordan DR. Integrating sorghum whole genome sequence information with a compendium of sorghum QTL studies reveals uneven distribution of QTL and of gene-rich regions with significant implications for crop improvement. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2011; 123:169-91. [PMID: 21484332 DOI: 10.1007/s00122-011-1575-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2010] [Accepted: 03/18/2011] [Indexed: 05/03/2023]
Abstract
A comprehensive analysis was conducted using 48 sorghum QTL studies published from 1995 to 2010 to make information from historical sorghum QTL experiments available in a form that could be more readily used by sorghum researchers and plant breeders. In total, 771 QTL relating to 161 unique traits from 44 studies were projected onto a sorghum consensus map. Confidence intervals (CI) of QTL were estimated so that valid comparisons could be made between studies. The method accounted for the number of lines used and the phenotypic variation explained by individual QTL from each study. In addition, estimated centimorgan (cM) locations were calculated for the predicted sorghum gene models identified in Phytozome (JGI GeneModels SBI v1.4) and compared with QTL distribution genome-wide, both on genetic linkage (cM) and physical (base-pair/bp) map scales. QTL and genes were distributed unevenly across the genome. Heterochromatic enrichment for QTL was observed, with approximately 22% of QTL either entirely or partially located in the heterochromatic regions. Heterochromatic gene enrichment was also observed based on their predicted cM locations on the sorghum consensus map, due to suppressed recombination in heterochromatic regions, in contrast to the euchromatic gene enrichment observed on the physical, sequence-based map. The finding of high gene density in recombination-poor regions, coupled with the association with increased QTL density, has implications for the development of more efficient breeding systems in sorghum to better exploit heterosis. The projected QTL information described, combined with the physical locations of sorghum sequence-based markers and predicted gene models, provides sorghum researchers with a useful resource for more detailed analysis of traits and development of efficient marker-assisted breeding strategies.
Collapse
Affiliation(s)
- E S Mace
- Department of Employment, Economic Development and Innovation, Hermitage Research Station, 604 Yangan Road, Warwick, QLD, 4370, Australia.
| | | |
Collapse
|
15
|
Abstract
This unit includes a basic protocol with an introduction to the Map Viewer, describing how to perform a simple text-based search of genome annotations to view the genomic context of a gene, navigate along a chromosome, zoom in and out, and change the displayed maps to hide and show information. It also describes some of NCBI's sequence-analysis tools, which are provided as links from the Map Viewer. The alternate protocols describe different ways to query the genome sequence, and also illustrate additional features of the Map Viewer. Alternate Protocol 1 shows how to perform and interpret the results of a BLAST search against the human genome. Alternate Protocol 2 demonstrates how to retrieve a list of all genes between two STS markers. Finally, Alternate Protocol 3 shows how to find all annotated members of a gene family.
Collapse
|
16
|
Mace ES, Jordan DR. Location of major effect genes in sorghum (Sorghum bicolor (L.) Moench). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2010; 121:1339-56. [PMID: 20585750 DOI: 10.1007/s00122-010-1392-8] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2009] [Accepted: 06/14/2010] [Indexed: 05/22/2023]
Abstract
Major effect genes are often used for germplasm identification, for diversity analyses and as selection targets in breeding. To date, only a few morphological characters have been mapped as major effect genes across a range of genetic linkage maps based on different types of molecular markers in sorghum (Sorghum bicolor (L.) Moench). This study aims to integrate all available previously mapped major effect genes onto a complete genome map, linked to the whole genome sequence, allowing sorghum breeders and researchers to link this information to QTL studies and to be aware of the consequences of selection for major genes. This provides new opportunities for breeders to take advantage of readily scorable morphological traits and to develop more effective breeding strategies. We also provide examples of the impact of selection for major effect genes on quantitative traits in sorghum. The concepts described in this paper have particular application to breeding programmes in developing countries where molecular markers are expensive or impossible to access.
Collapse
Affiliation(s)
- E S Mace
- Department of Employment, Economic Development and Innovation, Hermitage Research Station, Warwick, QLD, Australia.
| | | |
Collapse
|
17
|
Abstract
This unit includes a Basic Protocol with an introduction to the Map Viewer, describing how to perform a simple text-based search of genome annotations to view the genomic context of a gene, navigate along a chromosome, zoom in and out, and change the displayed maps to hide and show information. It also describes some of NCBI's sequence-analysis tools, which are provided as links from the Map Viewer. The Alternate Protocols describe different ways to query the genome sequence, and also illustrate additional features of the Map Viewer. Alternate Protocol 1 shows how to perform and interpret the results of a BLAST search against the human genome. Alternate Protocol 2 demonstrates how to retrieve a list of all genes between two STS markers. Finally, Alternate Protocol 3 shows how to find all annotated members of a gene family.
Collapse
|
18
|
Salih H, Adelson DL. QTL global meta-analysis: are trait determining genes clustered? BMC Genomics 2009; 10:184. [PMID: 19393059 PMCID: PMC2683869 DOI: 10.1186/1471-2164-10-184] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2008] [Accepted: 04/24/2009] [Indexed: 12/04/2022] Open
Abstract
Background A key open question in biology is if genes are physically clustered with respect to their known functions or phenotypic effects. This is of particular interest for Quantitative Trait Loci (QTL) where a QTL region could contain a number of genes that contribute to the trait being measured. Results We observed a significant increase in gene density within QTL regions compared to non-QTL regions and/or the entire bovine genome. By grouping QTL from the Bovine QTL Viewer database into 8 categories of non-redundant regions, we have been able to analyze gene density and gene function distribution, based on Gene Ontology (GO) with relation to their location within QTL regions, outside of QTL regions and across the entire bovine genome. We identified a number of GO terms that were significantly over represented within particular QTL categories. Furthermore, select GO terms expected to be associated with the QTL category based on common biological knowledge have also proved to be significantly over represented in QTL regions. Conclusion Our analysis provides evidence of over represented GO terms in QTL regions. This increased GO term density indicates possible clustering of gene functions within QTL regions of the bovine genome. Genes with similar functions may be grouped in specific locales and could be contributing to QTL traits. Moreover, we have identified over-represented GO terminology that from a biological standpoint, makes sense with respect to QTL category type.
Collapse
Affiliation(s)
- Hanni Salih
- Department of Animal Science and Interdisciplinary Faculty of Genetics, Texas A&M University, 2471 TAMU, Kleberg Center, College Station, TX, USA.
| | | |
Collapse
|
19
|
Majewski T, Lee S, Jeong J, Yoon DS, Kram A, Kim MS, Tuziak T, Bondaruk J, Lee S, Park WS, Tang KS, Chung W, Shen L, Ahmed SS, Johnston DA, Grossman HB, Dinney CP, Zhou JH, Harris RA, Snyder C, Filipek S, Narod SA, Watson P, Lynch HT, Gazdar A, Bar-Eli M, Wu XF, McConkey DJ, Baggerly K, Issa JP, Benedict WF, Scherer SE, Czerniak B. Understanding the development of human bladder cancer by using a whole-organ genomic mapping strategy. J Transl Med 2008; 88:694-721. [PMID: 18458673 PMCID: PMC2849658 DOI: 10.1038/labinvest.2008.27] [Citation(s) in RCA: 49] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
The search for the genomic sequences involved in human cancers can be greatly facilitated by maps of genomic imbalances identifying the involved chromosomal regions, particularly those that participate in the development of occult preneoplastic conditions that progress to clinically aggressive invasive cancer. The integration of such regions with human genome sequence variation may provide valuable clues about their overall structure and gene content. By extension, such knowledge may help us understand the underlying genetic components involved in the initiation and progression of these cancers. We describe the development of a genome-wide map of human bladder cancer that tracks its progression from in situ precursor conditions to invasive disease. Testing for allelic losses using a genome-wide panel of 787 microsatellite markers was performed on multiple DNA samples, extracted from the entire mucosal surface of the bladder and corresponding to normal urothelium, in situ preneoplastic lesions, and invasive carcinoma. Using this approach, we matched the clonal allelic losses in distinct chromosomal regions to specific phases of bladder neoplasia and produced a detailed genetic map of bladder cancer development. These analyses revealed three major waves of genetic changes associated with growth advantages of successive clones and reflecting a stepwise conversion of normal urothelial cells into cancer cells. The genetic changes map to six regions at 3q22-q24, 5q22-q31, 9q21-q22, 10q26, 13q14, and 17p13, which may represent critical hits driving the development of bladder cancer. Finally, we performed high-resolution mapping using single nucleotide polymorphism markers within one region on chromosome 13q14, containing the model tumor suppressor gene RB1, and defined a minimal deleted region associated with clonal expansion of in situ neoplasia. These analyses provided new insights on the involvement of several non-coding sequences mapping to the region and identified novel target genes, termed forerunner (FR) genes, involved in early phases of cancer development.
Collapse
Affiliation(s)
- Tadeusz Majewski
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
20
|
Abstract
This unit includes an introduction to the Map Viewer, which describes how to perform a simple text-based search of genome annotations to view the genomic context of a gene, navigate along a chromosome, zoom in and out, and change the displayed maps to hide and show information. It also describes some of NCBI's sequence-analysis tools, which are provided as links from the Map Viewer. The Alternate Protocols describe different ways to query the genome sequence, and also illustrate additional features of the Map Viewer. Alternate Protocol 1 shows how to perform and interpret the results of a BLAST search against the human genome. Alternate Protocol 2 demonstrates how to retrieve a list of all genes between two STS markers. Finally, Alternate Protocol 3 shows how to find all annotated members of a gene family.
Collapse
|
21
|
Fernández-Suárez XM, Schuster MK. Using the Ensembl genome server to browse genomic sequence data. ACTA ACUST UNITED AC 2008; Chapter 1:Unit 1.15. [PMID: 18428779 DOI: 10.1002/0471250953.bi0115s16] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The Ensembl genome Web browser (http://www.ensembl.org) provides a comprehensive source of automatic annotation of the human genome sequence (as well as other species of biomedical interest), with confirmed gene predictions that have been integrated with external data sources. This unit describes how to use the Ensembl browser, how to find your gene or protein of interest and get information and external links about them, and how to use the comparative genomic data.
Collapse
|
22
|
Gourraud PA, Hoffman D, Cambon-Thomsen A, Feolo M. 14th International HLA and Immunogenetics Workshop: report on mapping microsatellite markers in the major histocompatibility complex region. ACTA ACUST UNITED AC 2007; 69 Suppl 1:206-9. [PMID: 17445202 DOI: 10.1111/j.1399-0039.2006.00770.x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
This paper describes the use of the program e-pcr to localize 687 known major histocompatability complex (MHC) microsatellite primer pairs to their sequence positions in several genomic assemblies across the MHC region. The sequences used were the Sequences of Sanger Institute's MHC Haplotype Project: COX, PGF, QBL, as well as the Celera, and Reference (PGF across extended MHC) sequences from the NCBI genomic build 36. More than 95% (664/687) of the markers mapped unambiguously to the Reference assembly sequence. All primer pairs used in this analysis, and those were previously unknown to UniSTS, have now been assigned permanent public UniSTS identifiers. Mapping and descriptive data for each primer pair are available at the publicly accessible dbMHC microsatellite resource: http://www.ncbi.nlm.nih.gov/projects/mhc/xslcgi.fcgi?cmd=mssearch.
Collapse
|
23
|
Ma JH, Wang L, Feng SJ, Lin F, Xiao Y, Pan QH. Identification and fine mapping of AvrPi15, a novel avirulence gene of Magnaporthe grisea. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2006; 113:875-83. [PMID: 16845520 DOI: 10.1007/s00122-006-0347-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2006] [Accepted: 06/13/2006] [Indexed: 05/10/2023]
Abstract
Avirulence of Magnaporthe grisea isolate CHL346 on rice cultivar GA25 was studied with 242 ascospore progenies derived from the cross CHL346 x CHL42. Segregation analysis of the avirulence in the progeny population was in agreement with the existence of a single avirulence (Avr) gene, designated as AvrPi15. For mapping the Avr gene, we developed a total of 121 microsatellite DNA markers [simple sequence repeat (SSR)], which evenly distributed in the whole-genome of M. grisea through bioinformatics analysis (BIA) using the publicly available sequence. Linkage analysis of the AvrPi15 gene with these SSR markers showed that six markers on chromosome 6, MS6-1, MS6-2, MS6-3, MS6-7, MS6-8 and MS6-10, were linked to the AvrPi15 locus. To further define the chromosomal location of the AvrPi15 locus, two additional markers, MS6-17 and STS6-6, which were developed based on the sequences of telomeric region 11 (TEL11), were subjected to linkage analysis. The results showed that MS6-17 and STS6-6 were associated with the locus by 3.3 and 0.8 cM, respectively. To finely map the Avr gene, two additional candidate avirulence gene (CAG) markers, CAG6-1 and CAG6-2, were developed based on the gene annotation of the sequence of TEL 11. Linkage analysis of the Avr gene with these two markers revealed that both of them completely cosegregated with the AvrPi15 locus. Finally, this locus was physically mapped into approximately 7.2-kb interval of the TEL11 by BIA using these sequence-ready markers. This is the key step toward positional cloning of the AvrPi15 gene.
Collapse
Affiliation(s)
- Jun-Hong Ma
- Laboratory of Plant Resistance and Genetics, College of Resources and Environmental Sciences, South China Agricultural University, Guangzhou 510642, China
| | | | | | | | | | | |
Collapse
|
24
|
Chen JW, Wang L, Pang XF, Pan QH. Genetic analysis and fine mapping of a rice brown planthopper (Nilaparvata lugens Stål) resistance gene bph19(t). Mol Genet Genomics 2006; 275:321-9. [PMID: 16395578 DOI: 10.1007/s00438-005-0088-2] [Citation(s) in RCA: 36] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2005] [Accepted: 12/07/2005] [Indexed: 10/25/2022]
Abstract
Genetic analysis and fine mapping of a resistance gene against brown planthopper (BPH) biotype 2 in rice was performed using two F(2) populations derived from two crosses between a resistant indica cultivar (cv.), AS20-1, and two susceptible japonica cvs., Aichi Asahi and Lijiangxintuanheigu. Insect resistance was evaluated using F(1) plants and the two F(2) populations. The results showed that a single recessive gene, tentatively designated as bph19(t), conditioned the resistance in AS20-1. A linkage analysis, mainly employing microsatellite markers, was carried out in the two F(2) populations through bulked segregant analysis and recessive class analysis (RCA), in combination with bioinformatics analysis (BIA). The resistance gene locus bph19(t) was finely mapped to a region of about 1.0 cM on the short arm of chromosome 3, flanked by markers RM6308 and RM3134, where one known marker RM1022, and four new markers, b1, b2, b3 and b4, developed in the present study were co-segregating with the locus. To physically map this locus, the bph19(t)-linked markers were landed on bacterial artificial chromosome or P1 artificial chromosome clones of the reference cv., Nipponbare, released by the International Rice Genome Sequencing Project. Sequence information of these clones was used to construct a physical map of the bph19(t) locus, in silico, by BIA. The bph19(t) locus was physically defined to an interval of about 60 kb. The detailed genetic and physical maps of the bph19(t) locus will facilitate marker-assisted gene pyramiding and cloning.
Collapse
Affiliation(s)
- J W Chen
- Laboratory of Plant Resistance and Genetics, College of Natural Resources and Environment, South China Agricultural University, 510642, Guangzhou, China
| | | | | | | |
Collapse
|
25
|
Baross A, Butterfield YSN, Coughlin SM, Zeng T, Griffith M, Griffith OL, Petrescu AS, Smailus DE, Khattra J, McDonald HL, McKay SJ, Moksa M, Holt RA, Marra MA. Systematic recovery and analysis of full-ORF human cDNA clones. Genome Res 2004; 14:2083-92. [PMID: 15489330 PMCID: PMC528924 DOI: 10.1101/gr.2473704] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
The Mammalian Gene Collection (MGC) consortium (http://mgc.nci.nih.gov) seeks to establish publicly available collections of full-ORF cDNAs for several organisms of significance to biomedical research, including human. To date over 15,200 human cDNA clones containing full-length open reading frames (ORFs) have been identified via systematic expressed sequence tag (EST) analysis of a diverse set of cDNA libraries; however, further systematic EST analysis is no longer an efficient method for identifying new cDNAs. As part of our involvement in the MGC program, we have developed a scalable method for targeted recovery of cDNA clones to facilitate recovery of genes absent from the MGC collection. First, cDNA is synthesized from various RNAs, followed by polymerase chain reaction (PCR) amplification of transcripts in 96-well plates using gene-specific primer pairs flanking the ORFs. Amplicons are cloned into a sequencing vector, and full-length sequences are obtained. Sequences are processed and assembled using Phred and Phrap, and analyzed using Consed and a number of bioinformatics methods we have developed. Sequences are compared with the Reference Sequence (RefSeq) database, and validation of sequence discrepancies is attempted using other sequence databases including dbEST and dbSNP. Clones with identical sequence to RefSeq or containing only validated changes will become part of the MGC human gene collection. Clones containing novel splice variants or polymorphisms have also been identified. Our approach to clone recovery, applied at large scale, has the potential to recover many and possibly most of the genes absent from the MGC collection.
Collapse
Affiliation(s)
- Agnes Baross
- Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, British Columbia, V5Z 4E6, Canada
| | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
26
|
Abstract
'Electronic PCR' (e-PCR) refers to a computational procedure that is used to search DNA sequences for sequence tagged sites (STSs), each of which is defined by a pair of primer sequences and an expected PCR product size. To gain speed, our implementation extracts short 'words' from the 3' end of each primer and stores them in a sorted hash table that can be accessed efficiently during the search. One recent improvement is the use of overlapping discontinuous words to allow matches to be found despite the presence of a mismatch. Moreover, it is possible to allow gaps in the alignment between the primer and the sequence. The effect of these changes is to improve sensitivity without significantly affecting specificity. The new software provides a search mode using a query STS against a sequence database to augment the previously available mode using a query sequence against an STS database. Finally, e-PCR may now be used through a web service, with search results linked to other web resources such as the UniSTS database and the MapViewer genome browser. The e-PCR web server may be found at www.ncbi.nlm.nih.gov/sutils/e-pcr.
Collapse
Affiliation(s)
- Kirill Rotmistrovsky
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20984, USA
| | | | | |
Collapse
|
27
|
Dyer KD, Nitto T, Moreau JM, McDevitt AL, Rosenberg HF. Identification of a purine-rich intronic enhancer element in the mouse eosinophil-associated ribonuclease 2 (mEar 2) gene. Mamm Genome 2004; 15:126-34. [PMID: 15058383 DOI: 10.1007/s00335-003-2304-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
The Mus musculus eosinophil-associated ribonuclease (mEar) gene cluster includes multiple distinct coding sequences that are highly divergent orthologs of the human eosinophil ribonucleases, eosinophil-derived neurotoxin (EDN/RNase 2) and eosinophil cationic protein (ECP/RNase 3). We present a transcriptional analysis of the gene encoding mEar 2, the only member of this cluster with a well-defined expression profile. In this work, we demonstrate that the presence of non-coding exon 1 and the intron in tandem with a 361-bp 5' promoter of mEar 2 results in enhanced reporter gene expression, as much as 6-to 10-fold over the activity observed with the 5' promoter alone. We have identified a conserved purine-rich element in the intron of the mEar 2 gene that is necessary for maximum transcription and that interacts specifically with NFAT-binding proteins in nuclear extracts derived from the mouse LA4 epithelial cell line. Similar intronic enhancers have been described as regulating transcription of the human EDN gene, suggesting an overall conservation of an important regulatory strategy.
Collapse
Affiliation(s)
- Kimberly D Dyer
- Eosinophil Pathophysiology Section, LHD, NIAID, National Institutes of Health, Bethesda, Maryland 20892, USA.
| | | | | | | | | |
Collapse
|
28
|
Greshock J, Naylor TL, Margolin A, Diskin S, Cleaver SH, Futreal PA, deJong PJ, Zhao S, Liebman M, Weber BL. 1-Mb resolution array-based comparative genomic hybridization using a BAC clone set optimized for cancer gene analysis. Genome Res 2003; 14:179-87. [PMID: 14672980 PMCID: PMC314295 DOI: 10.1101/gr.1847304] [Citation(s) in RCA: 87] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Array-based comparative genomic hybridization (aCGH) is a recently developed tool for genome-wide determination of DNA copy number alterations. This technology has tremendous potential for disease-gene discovery in cancer and developmental disorders as well as numerous other applications. However, widespread utilization of a CGH has been limited by the lack of well characterized, high-resolution clone sets optimized for consistent performance in aCGH assays and specifically designed analytic software. We have assembled a set of approximately 4100 publicly available human bacterial artificial chromosome (BAC) clones evenly spaced at approximately 1-Mb resolution across the genome, which includes direct coverage of approximately 400 known cancer genes. This aCGH-optimized clone set was compiled from five existing sets, experimentally refined, and supplemented for higher resolution and enhancing mapping capabilities. This clone set is associated with a public online resource containing detailed clone mapping data, protocols for the construction and use of arrays, and a suite of analytical software tools designed specifically for aCGH analysis. These resources should greatly facilitate the use of aCGH in gene discovery.
Collapse
Affiliation(s)
- Joel Greshock
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | | | | | | | | | | | | | | | | | | |
Collapse
|
29
|
Woodfine K, Fiegler H, Beare DM, Collins JE, McCann OT, Young BD, Debernardi S, Mott R, Dunham I, Carter NP. Replication timing of the human genome. Hum Mol Genet 2003; 13:191-202. [PMID: 14645202 DOI: 10.1093/hmg/ddh016] [Citation(s) in RCA: 245] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
We have developed a directly quantitative method utilizing genomic clone DNA microarrays to assess the replication timing of sequences during the S phase of the cell cycle. The genomic resolution of the replication timing measurements is limited only by the genomic clone size and density. We demonstrate the power of this approach by constructing a genome-wide map of replication timing in human lymphoblastoid cells using an array with clones spaced at 1 Mb intervals and a high-resolution replication timing map of 22q with an array utilizing overlapping sequencing tile path clones. We show a positive correlation, both genome-wide and at a high resolution, between replication timing and a range of genome parameters including GC content, gene density and transcriptional activity.
Collapse
Affiliation(s)
- Kathryn Woodfine
- The Welcome Trust Sanger Institute, Welcome Genome Campus, Cambridge, UK
| | | | | | | | | | | | | | | | | | | |
Collapse
|
30
|
A User's Guide to the Human Genome. Question 3. During a positional cloning project aimed at finding a human disease gene, linkage data have been obtained suggesting that the gene of interest lies between two sequence-tagged site markers. How can all the known and predicted candidate genes in this interval be identified? What BAC clones cover that particular region? Nat Genet 2003; 35 Suppl 1:21-8. [PMID: 14578894 DOI: 10.1038/ng1191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
|
31
|
A User's Guide to the Human Genome. Question 10. For a given protein, how can one determine whether it contains any functional domains of interest? What other proteins contain the same functional domains as this protein? How can one determine whether there is a similarity to other proteins, not only at the sequence level, but also at the structural level? Nat Genet 2003; 35 Suppl 1:57-62. [PMID: 14578901 DOI: 10.1038/ng1198] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
32
|
A User's Guide to the Human Genome. Question 5. Given a fragment of mRNA sequence, how would one find where that piece of DNA mapped in the human genome? Once its position has been determined, how would one find alternatively-spliced transcripts? Nat Genet 2003; 35 Suppl 1:33-9. [PMID: 14578896 DOI: 10.1038/ng1193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
|
33
|
Kiger AA, Baum B, Jones S, Jones MR, Coulson A, Echeverri C, Perrimon N. A functional genomic analysis of cell morphology using RNA interference. J Biol 2003; 2:27. [PMID: 14527345 PMCID: PMC333409 DOI: 10.1186/1475-4924-2-27] [Citation(s) in RCA: 308] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2003] [Revised: 07/17/2003] [Accepted: 08/12/2003] [Indexed: 01/23/2023] Open
Abstract
Background The diversity of metazoan cell shapes is influenced by the dynamic cytoskeletal network. With the advent of RNA-interference (RNAi) technology, it is now possible to screen systematically for genes controlling specific cell-biological processes, including those required to generate distinct morphologies. Results We adapted existing RNAi technology in Drosophila cell culture for use in high-throughput screens to enable a comprehensive genetic dissection of cell morphogenesis. To identify genes responsible for the characteristic shape of two morphologically distinct cell lines, we performed RNAi screens in each line with a set of double-stranded RNAs (dsRNAs) targeting 994 predicted cell shape regulators. Using automated fluorescence microscopy to visualize actin filaments, microtubules and DNA, we detected morphological phenotypes for 160 genes, one-third of which have not been previously characterized in vivo. Genes with similar phenotypes corresponded to known components of pathways controlling cytoskeletal organization and cell shape, leading us to propose similar functions for previously uncharacterized genes. Furthermore, we were able to uncover genes acting within a specific pathway using a co-RNAi screen to identify dsRNA suppressors of a cell shape change induced by Pten dsRNA. Conclusions Using RNAi, we identified genes that influence cytoskeletal organization and morphology in two distinct cell types. Some genes exhibited similar RNAi phenotypes in both cell types, while others appeared to have cell-type-specific functions, in part reflecting the different mechanisms used to generate a round or a flat cell morphology.
Collapse
Affiliation(s)
- AA Kiger
- Department of Genetics, Harvard Medical School, Howard Hughes Medical Institute, Boston, MA 02115, USA
| | - B Baum
- Department of Genetics, Harvard Medical School, Howard Hughes Medical Institute, Boston, MA 02115, USA
- Current address: Ludwig Institute for Cancer Research, University College London W1W 7BS, UK
| | - S Jones
- Genome Sciences Centre, British Columbia Cancer Research Centre, Vancouver V5Z 4E6, Canada
| | - MR Jones
- MRC Laboratory of Molecular Biology, Cambridge CB2 2QH, UK
| | - A Coulson
- MRC Laboratory of Molecular Biology, Cambridge CB2 2QH, UK
| | - C Echeverri
- Cenix BioScience GmbH, D-01307 Dresden, Germany
| | - N Perrimon
- Department of Genetics, Harvard Medical School, Howard Hughes Medical Institute, Boston, MA 02115, USA
| |
Collapse
|
34
|
Engler FW, Hatfield J, Nelson W, Soderlund CA. Locating sequence on FPC maps and selecting a minimal tiling path. Genome Res 2003; 13:2152-63. [PMID: 12915486 PMCID: PMC403717 DOI: 10.1101/gr.1068603] [Citation(s) in RCA: 34] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
This study discusses three software tools, the first two aid in integrating sequence with an FPC physical map and the third automatically selects a minimal tiling path given genomic draft sequence and BAC end sequences. The first tool, FSD (FPC Simulated Digest), takes a sequenced clone and adds it back to the map based on a fingerprint generated by an in silico digest of the clone. This allows verification of sequenced clone positions and the integration of sequenced clones that were not originally part of the FPC map. The second tool, BSS (Blast Some Sequence), takes a query sequence and positions it on the map based on sequence associated with the clones in the map. BSS has multiple uses as follows: (1) When the query is a file of marker sequences, they can be added as electronic markers. (2) When the query is draft sequence, the results of BSS can be used to close gaps in a sequenced clone or the physical map. (3) When the query is a sequenced clone and the target is BAC end sequences, one may select the next clone for sequencing using both sequence comparison results and map location. (4) When the query is whole-genome draft sequence and the target is BAC end sequences, the results can be used to select many clones for a minimal tiling path at once. The third tool, pickMTP, automates the majority of this last usage of BSS. Results are presented using the rice FPC map, BAC end sequences, and whole-genome shotgun from Syngenta.
Collapse
Affiliation(s)
- Friedrich W Engler
- Arizona Genomics Computational Laboratory, University of Arizona, Tucson, Arizona 85721, USA
| | | | | | | |
Collapse
|
35
|
Introduction: putting it together. Nat Genet 2003; 35 Suppl 1:5-8. [PMID: 14578891 DOI: 10.1038/ng1188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
36
|
Question 11 An investigator has identified and cloned a human gene, but no corresponding mouse ortholog has yet been identified. How can a mouse genomic sequence with similarity to the human gene sequence be retrieved? Nat Genet 2003; 35 Suppl 1:63-5. [PMID: 14578902 DOI: 10.1038/ng1199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
37
|
|
38
|
Question 1 How does one find a gene of interest and determine that gene's structure? Once the gene has been located on the map, how does one easily examine other genes in that same region? Nat Genet 2003; 35 Suppl 1:9-17. [PMID: 14578892 DOI: 10.1038/ng1189] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
|
39
|
Question 4 A user wishes to find all the single nucleotide polymorphisms that lie between two sequence-tagged sites. Do any of these single nucleotide polymorphisms fall within the coding region of a gene? Where can any additional information about the function of these genes be found? Nat Genet 2003; 35 Suppl 1:29-32. [PMID: 14578895 DOI: 10.1038/ng1192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
|
40
|
Question 7 How would an investigator easily find compiled information describing the structure of a gene of interest? Is it possible to obtain the sequence of any putative promoter regions? Nat Genet 2003; 35 Suppl 1:44-8. [PMID: 14578898 DOI: 10.1038/ng1195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
|
41
|
Question 12 How does a user find characterized mouse mutants corresponding to human genes? Nat Genet 2003; 35 Suppl 1:66-9. [PMID: 14578903 DOI: 10.1038/ng1200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
42
|
Question 2 How can sequence-tagged sites within a DNA sequence be identified? Nat Genet 2003; 35 Suppl 1:18-20. [PMID: 14578893 DOI: 10.1038/ng1190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
|
43
|
Rockne KJ, Strand SE. Amplification of marine methanotrophic enrichment DNA with 16S rDNA PCR primers for type II alpha proteobacteria methanotrophs. JOURNAL OF ENVIRONMENTAL SCIENCE AND HEALTH. PART A, TOXIC/HAZARDOUS SUBSTANCES & ENVIRONMENTAL ENGINEERING 2003; 38:1877-1887. [PMID: 12940489 DOI: 10.1081/ese-120022886] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Type II alpha proteobacteria methanotrophs are capable of a wide range of cometabolic transformations of chlorinated solvents and polycyclic aromatic hydrocarbons (PAHs), and this activity has been exploited in many terrestrial bioremediation systems. However, at present, all known obligately marine methanotrophic isolates are Type I gamma proteobacteria which do not have this activity to the extent of Type II methanotrophs. In previous work in our laboratory, determining the presence of Type II alpha proteobacteria methanotrophs in marine enrichment cultures that co-metabolized PAHs required a more sensitive assay. 16S rDNA PCR primers were designed based on oligonucleotide probes for serine pathway methanotrophs and serine pathway methylotrophs with an approximate amplification fragment size of 870 base pairs. Comparison of the primers using double primer BLAST searches in established nucleotide databases showed potential amplification with all Methylocystis and Methylosinus spp., as well as potential amplification with Methylocella palustrus. DNA from Methylosinus trichosporium OB3b, a Type II methanotroph, amplified with the primers with a fragment size of approximately 850 base pairs, whereas DNA extracted from Methylomonas methanica, a Type I methanotroph, did not. The primers were used to amplify DNA extracted from two marine methanotrophic enrichment cultures: a low nitrogen/low copper enrichment to select for Type II methanotrophs and a high nitrogen/high copper enrichment to select for Type I methanotrophs. Although DNA from both cultures amplified with the PCR primers, amplification was stronger in cultures that were specifically enriched for Type II methanotrophs, suggesting the presence of higher numbers of Type II methanotrophs. These results provide further evidence for the existence of Type II marine methanotrophs, suggesting the possibility of exploiting cometabolic activity in marine systems.
Collapse
Affiliation(s)
- Karl J Rockne
- Department of Civil and Materials Engineering, University of Illinois-Chicago, Chicago, Illinois 60607-7023, USA.
| | | |
Collapse
|
44
|
Liu C, Bonner TI, Nguyen T, Lyons JL, Christian SL, Gershon ES. DNannotator: Annotation software tool kit for regional genomic sequences. Nucleic Acids Res 2003; 31:3729-3735. [PMID: 12824405 PMCID: PMC168949 DOI: 10.1093/nar/gkg542] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2003] [Revised: 03/21/2003] [Accepted: 03/31/2003] [Indexed: 11/12/2022] Open
Abstract
Sequence annotation is essential for genomics-based research. Investigators of a specific genomic region who have developed abundant local discoveries such as genes and genetic markers, or have collected annotations from multiple resources, can be overwhelmed by the difficulty in creating local annotation and the complexity of integrating all the annotations. Presenting such integrated data in a form suitable for data mining and high-throughput experimental design is even more daunting. DNannotator, a web application, was designed to perform batch annotation on a sizeable genomic region. It takes annotation source data, such as SNPs, genes, primers, and so on, prepared by the end-user and/or a specified target of genomic DNA, and performs de novo annotation. DNannotator can also robustly migrate existing annotations in GenBank format from one sequence to another. Annotation results are provided in GenBank format and in tab-delimited text, which can be imported and managed in a database or spreadsheet and combined with existing annotation as desired. Graphic viewers, such as Genome Browser or Artemis, can display the annotation results. Reference data (reports on the process) facilitating the user's evaluation of annotation quality are optionally provided. DNannotator can be accessed at http://sky.bsd.uchicago.edu/DNannotator.htm.
Collapse
Affiliation(s)
- Chunyu Liu
- Department of Psychiatry, University of Chicago, Chicago, IL, USA.
| | | | | | | | | | | |
Collapse
|
45
|
Liu H, Ye SL, Yang J, Tang ZY, Liu YK, Qin LX, Qiu SJ, Sun RX. The microcell mediated transfer of human chromosome 8 into highly metastatic rat liver cancer cell line C5F. World J Gastroenterol 2003; 9:449-53. [PMID: 12632495 PMCID: PMC4621559 DOI: 10.3748/wjg.v9.i3.449] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
AIM: Our previous research on the surgical samples of primary liver cancer with CGH showed that the loss of human chromosome 8p had correlation with the metastatic phenotype of liver cancer. In order to seek the functional evidence that there could be a metastatsis suppressor gene (s) for liver cancer on human chromosome 8, we tried to transfer normal human chromosome 8 into rat liver cancer cell line C5F, which had high metastatic potential to lung.
METHODS: Human chromosome 8 randomly marked with neo gene was introduced into C5F cell line by MMCT and positive microcell hybrids were screened by double selections of G418 and HAT. Single cell isolation cloning was applied to clone microcell hybrids. Finally, STS-PCR and WCP-FISH were used to confirm the introduction.
RESULTS: Microcell hybrids resistant to HAT and G418 were obtained and 15 clones were obtained by single-cell isolation cloning. STS-PCR and WCP-FISH proved that human chromosome 8 had been successfully introduced into rat liver cancer cell line C5F. STS-PCR detected a random loss in the chromosome introduced and WCP-FISH found a consistent recombination of the introduced human chromosome with the rat chromosome.
CONCLUSION: The successful introduction of human chromosome 8 into highly metastatic rat liver cancer cell line builds the basis for seeking functional evidence of a metastasis suppressor gene for liver cancer harboring on human chromosome 8 and its subsequent cloning.
Collapse
Affiliation(s)
- Hu Liu
- Liver Cancer Institute, Zhong Shan Hospital, Fudan University, Shanghai 200032, China
| | | | | | | | | | | | | | | |
Collapse
|
46
|
Blair IP, Adams LJ, Badenhop RF, Moses MJ, Scimone A, Morris JA, Ma L, Austin CP, Donald JA, Mitchell PB, Schofield PR. A transcript map encompassing a susceptibility locus for bipolar affective disorder on chromosome 4q35. Mol Psychiatry 2003; 7:867-73. [PMID: 12232780 DOI: 10.1038/sj.mp.4001113] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2001] [Revised: 11/12/2001] [Accepted: 11/29/2001] [Indexed: 12/15/2022]
Abstract
Bipolar affective disorder is one of the most common mental illnesses with a population prevalence of approximately 1%. The disorder is genetically complex, with an increasing number of loci being implicated through genetic linkage studies. However, the specific genetic variations and molecules involved in bipolar susceptibility and pathogenesis are yet to be identified. Genetic linkage analysis has identified a bipolar disorder susceptibility locus on chromosome 4q35, and the interval harbouring this susceptibility gene has been narrowed to a size that is amenable to positional cloning. We have used the resources of the Human Genome Project (HGP) and Celera Genomics to identify overlapping sequenced BAC clones and sequence contigs that represent the region implicated by linkage analysis. A combination of bioinformatic tools and laboratory techniques have been applied to annotate this DNA sequence data and establish a comprehensive transcript map that spans approximately 5.5 Mb. This map encompasses the chromosome 4q35 bipolar susceptibility locus, which localises to a "most probable" candidate interval of approximately 2.3 Mb, within a more conservative candidate interval of approximately 5 Mb. Localised within this map are 11 characterised genes and eight novel genes of unknown function, which together provide a collection of candidate transcripts that may be investigated for association with bipolar disorder. Overall, this region was shown to be very gene-poor, with a high incidence of pseudogenes, and redundant and novel repetitive elements. Our analysis of the interval has demonstrated a significant difference in the extent to which the current HGP and Celera sequence data sets represent this region.
Collapse
Affiliation(s)
- I P Blair
- Garvan Institute of Medical Research, 384 Victoria Street, Sydney 2010, Australia
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|
47
|
Glienke J, Sturz A, Menrad A, Thierauch KH. CRIM1 is involved in endothelial cell capillary formation in vitro and is expressed in blood vessels in vivo. Mech Dev 2002; 119:165-75. [PMID: 12464430 DOI: 10.1016/s0925-4773(02)00355-6] [Citation(s) in RCA: 35] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
In endothelial cells that form capillary-like structures in vitro a variety of genes is upregulated as we have demonstrated previously. In addition to well known genes, we also identified genes never described in endothelial cells before. Here, we report the further characterization of one selected gene called cysteine-rich motor neuron 1 (CRIM1). CRIM1 is strongly upregulated in endothelial cells during tube formation and is expressed by a variety of adherent growing cell lines whereas cell lines grown in suspension do not express CRIM1. By using antisense technology we were able to inhibit CRIM1 expression and demonstrate impaired formation of capillary-like structures in vitro in transfected endothelial cells. Furthermore, we show that CRIM1 is a glycosylated type I transmembrane protein, that accumulates at sites of close cell-to-cell contact upon stimulation. Finally, we found CRIM1 protein to be expressed by endothelial cells of the inner lining of blood vessels in vivo. Taken together our results imply a possible role of CRIM1 in capillary formation and maintainance during angiogenesis.
Collapse
MESH Headings
- Amino Acid Sequence
- Animals
- Blotting, Northern
- Blotting, Western
- Bone Morphogenetic Protein Receptors
- Capillaries/metabolism
- Cell Membrane/metabolism
- Cells, Cultured
- Collagen/metabolism
- DNA, Complementary/metabolism
- Down-Regulation
- Drug Combinations
- Endothelium, Vascular/cytology
- Gene Expression Regulation, Developmental
- Glycosylation
- Humans
- Immunohistochemistry
- Laminin/metabolism
- Membrane Proteins
- Mice
- Mice, Inbred BALB C
- Microscopy, Fluorescence
- Models, Genetic
- Molecular Sequence Data
- Neovascularization, Physiologic
- Nuclear Proteins/biosynthesis
- Nuclear Proteins/physiology
- Oligonucleotides, Antisense/pharmacology
- Protein Structure, Tertiary
- Proteins
- Proteoglycans/metabolism
- RNA, Messenger/metabolism
- Reverse Transcriptase Polymerase Chain Reaction
- Tissue Distribution
- Transfection
- Up-Regulation
Collapse
Affiliation(s)
- Jens Glienke
- Experimental Oncology, Research Laboratories of Schering AG, Müllerstrasse 178, D-13342 Berlin, Germany
| | | | | | | |
Collapse
|
48
|
Church D, Pruitt KD. Accessing the human genome. CURRENT PROTOCOLS IN HUMAN GENETICS 2002; Chapter 6:Unit 6.9. [PMID: 18428332 DOI: 10.1002/0471142905.hg0609s34] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
The majority of the sequence for the human genome is now available. Regardless of the researcher's area of interest, it is quite likely that they will want to use some aspect of this data. This unit helps researchers achieve that goal. It presents the gene models available at NCBI, the UCSC Genome Browser, and Ensembl. It reviews the features and options available from the three web sites to query, display, and download the data. In addition, the unit illustrates how to query each of the databases in order to identify information, such as the genomic location of a novel cDNA, a BAC clone that contains a particular gene, and homologous human genes to a particular protein sequence from a different organism.
Collapse
Affiliation(s)
- Deanna Church
- National Center for Biotechnology Information, NIH, Bethesda, MaryLand, USA
| | | |
Collapse
|
49
|
Question 8 How can one find all the members of a human gene family? Nat Genet 2002. [DOI: 10.1038/ng973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
50
|
Question 6 How would one retrieve the sequence of a gene, along with all annotated exons and introns, as well as a certain number of flanking bases for use in primer design? Nat Genet 2002. [DOI: 10.1038/ng971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|