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Betto A, Palumbo F, Riommi D, Vannozzi A, Barcaccia G. Harnessing Genomics for Breeding Lantana camara L.: Genotyping and Ploidy Testing of Clonal Lines Through ddRADseq Applications. Int J Mol Sci 2025; 26:4898. [PMID: 40430036 PMCID: PMC12112523 DOI: 10.3390/ijms26104898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2025] [Revised: 05/05/2025] [Accepted: 05/10/2025] [Indexed: 05/29/2025] Open
Abstract
Lantana camara L. is sold worldwide for ornamental purposes, although it is also characterized by high invasiveness potential. Genetic and molecular data available for L. camara are still poor, and breeding is performed through conventional methods. This study focused on a molecular genotyping analysis through the ddRADseq method on an experimental collection of lantana clonal lines to evaluate the potential of molecular techniques in performing marker-assisted breeding, in favour of variety registration and in guaranteeing plant variety protection for the species. Although high genetic uniformity was observed in the population, a unique molecular profile was assigned to every line, indicating the effectiveness of the approach used. Interestingly, low degrees of heterozygosity were observed. In addition, the possibility of inferring ploidy levels through SNP profiles was assessed since it would avoid the necessity of previous biological knowledge and the use of fresh materials. Ploidy analysis is of high interest for lantana breeding to obtain less invasive triploids. Flow cytometry and chromosome counting were used for inference assessment. An nQuack framework provided correct results for the majority of the clonal lines, confirming its effectiveness. These findings encourage the adoption of molecular systems to help breed minor species such as L. camara.
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Affiliation(s)
| | - Fabio Palumbo
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), Campus of Agripolis, University of Padova, Viale dell’Università 16, 35020 Legnaro, PD, Italy; (A.B.); (D.R.); (A.V.); (G.B.)
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Scariolo F, Palumbo F, Farinati S, Barcaccia G. Pipeline to Design Inbred Lines and F1 Hybrids of Leaf Chicory (Radicchio) Using Male Sterility and Genotyping-by-Sequencing. PLANTS (BASEL, SWITZERLAND) 2023; 12:1242. [PMID: 36986929 PMCID: PMC10055022 DOI: 10.3390/plants12061242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 03/03/2023] [Accepted: 03/07/2023] [Indexed: 06/18/2023]
Abstract
Chicory, a horticultural crop cultivated worldwide, presents many botanical varieties and local biotypes. Among these, cultivars of the Italian radicchio group of the pure species Cichorium intybus L. and its interspecific hybrids with Cichorium endivia L.-as the "Red of Chioggia" biotype-includes several phenotypes. This study uses a pipeline to address the marker-assisted breeding of F1 hybrids: it presents the genotyping-by-sequencing results of four elite inbred lines using a RADseq approach and an original molecular assay based on CAPS markers for screening mutants with nuclear male sterility in the radicchio of Chioggia. A total of 2953 SNP-carrying RADtags were identified and used to compute the actual estimates of homozygosity and overall genetic similarity and uniformity of the populations, as well as to determine their genetic distinctiveness and differentiation. Molecular data were further used to investigate the genomic distribution of the RADtags among the two Cichorium species, allowing their mapping in 1131 and 1071 coding sequences in chicory and endive, respectively. Paralleling this, an assay to screen the genotype at the male sterility locus Cims-1 was developed to discriminate wild-type and mutant alleles of the causative gene myb80-like. Moreover, a RADtag mapped close to this genomic region proved the potential application of this method for future marker-assisted selection tools. Finally, after combining the genotype information of the core collection, the best 10 individuals from each inbred line were selected to compute the observed genetic similarity as a measure of uniformity as well as the expected homozygosity and heterozygosity estimates scorable by the putative progenies derived from selfing (pollen parent) and full-sibling (seed parent) or pair-wise crossing (F1 hybrids). This predictive approach was conducted as a pilot study to understand the potential application of RADseq in the fine tuning of molecular marker-assisted breeding strategies aimed at the development of inbred lines and F1 hybrids in leaf chicory.
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Taniguti CH, Taniguti LM, Amadeu RR, Lau J, Gesteira GDS, Oliveira TDP, Ferreira GC, Pereira GDS, Byrne D, Mollinari M, Riera-Lizarazu O, Garcia AAF. Developing best practices for genotyping-by-sequencing analysis in the construction of linkage maps. Gigascience 2022; 12:giad092. [PMID: 37889010 PMCID: PMC10603770 DOI: 10.1093/gigascience/giad092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 06/27/2023] [Accepted: 10/06/2023] [Indexed: 10/28/2023] Open
Abstract
BACKGROUND Genotyping-by-sequencing (GBS) provides affordable methods for genotyping hundreds of individuals using millions of markers. However, this challenges bioinformatic procedures that must overcome possible artifacts such as the bias generated by polymerase chain reaction duplicates and sequencing errors. Genotyping errors lead to data that deviate from what is expected from regular meiosis. This, in turn, leads to difficulties in grouping and ordering markers, resulting in inflated and incorrect linkage maps. Therefore, genotyping errors can be easily detected by linkage map quality evaluations. RESULTS We developed and used the Reads2Map workflow to build linkage maps with simulated and empirical GBS data of diploid outcrossing populations. The workflows run GATK, Stacks, TASSEL, and Freebayes for single-nucleotide polymorphism calling and updog, polyRAD, and SuperMASSA for genotype calling, as well as OneMap and GUSMap to build linkage maps. Using simulated data, we observed which genotype call software fails in identifying common errors in GBS sequencing data and proposed specific filters to better handle them. We tested whether it is possible to overcome errors in a linkage map using genotype probabilities from each software or global error rates to estimate genetic distances with an updated version of OneMap. We also evaluated the impact of segregation distortion, contaminant samples, and haplotype-based multiallelic markers in the final linkage maps. Through our evaluations, we observed that some of the approaches produce different results depending on the dataset (dataset dependent) and others produce consistent advantageous results among them (dataset independent). CONCLUSIONS We set as default in the Reads2Map workflows the approaches that showed to be dataset independent for GBS datasets according to our results. This reduces the number of required tests to identify optimal pipelines and parameters for other empirical datasets. Using Reads2Map, users can select the pipeline and parameters that best fit their data context. The Reads2MapApp shiny app provides a graphical representation of the results to facilitate their interpretation.
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Affiliation(s)
- Cristiane Hayumi Taniguti
- Department of Genetics, University of São Paulo, São Paulo 13418-900, Brazil
- Department of Horticultural Sciences, Texas A&M University, College Station, TX 77843-0001, USA
| | - Lucas Mitsuo Taniguti
- Department of Genetics, University of São Paulo, São Paulo 13418-900, Brazil
- Mendelics Genomic Analysis, São Paulo 02511-000, Brazil
| | | | - Jeekin Lau
- Department of Horticultural Sciences, Texas A&M University, College Station, TX 77843-0001, USA
| | - Gabriel de Siqueira Gesteira
- Department of Genetics, University of São Paulo, São Paulo 13418-900, Brazil
- Bioinformatics Research Center, Department of Horticultural Sciences, North Carolina State University, Raleigh, NC 27695-7566, USA
| | | | | | | | - David Byrne
- Department of Horticultural Sciences, Texas A&M University, College Station, TX 77843-0001, USA
| | - Marcelo Mollinari
- Bioinformatics Research Center, Department of Horticultural Sciences, North Carolina State University, Raleigh, NC 27695-7566, USA
| | - Oscar Riera-Lizarazu
- Department of Horticultural Sciences, Texas A&M University, College Station, TX 77843-0001, USA
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A Novel Strategy for Constructing an Integrated Linkage Map in an F1 Hybrid Population of Populus deltoides and Populus simonii. Genes (Basel) 2022; 13:genes13101731. [PMID: 36292616 PMCID: PMC9601732 DOI: 10.3390/genes13101731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 09/20/2022] [Accepted: 09/21/2022] [Indexed: 11/17/2022] Open
Abstract
The genetic linkage maps of the traditional F2 population in inbred lines were estimated from the frequency of recombination events in both parents, providing full genetic information for genetic and genomic studies. However, in outbred forest trees, it is almost impossible to generate the F2 population because of their high heterozygosity and long generation times. We proposed a novel strategy to construct an integrated genetic linkage map that contained both parental recombination information, with restriction-site-associated DNA sequencing (RADSeq) data in an F1 hybrid population of Populus deltoides and Populus simonii. We selected a large number of specific RAD tags to construct the linkage map, each of which contained two SNPs, one heterozygous only in the female parent and the other heterozygous only in the male. Consequently, the integrated map contained a total of 1154 RAD tags and 19 linkage groups, with a total length of 5255.49 cM and an average genetic distance of 4.63 cM. Meanwhile, the two parent-specific linkage maps were also constructed with SNPs that were heterozygous in one parent and homozygous in the other. We found that the integrated linkage map was more consensus with the genomic sequences of P. simonii and P. deltoides. Additionally, the likelihood of the marker order in each linkage group of the integrated map was greater than that in both parental maps. The integrated linkage map was more accurate than the parent-specific linkage maps constructed in the same F1 hybrid population, providing a powerful genetic resource for identifying the quantitative trait loci (QTLs) with dominant effects, assembling genomic sequences, and performing comparative genomics in related Populus species. More importantly, this novel strategy can be used in other outbred species to build an integrated linkage map.
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Jinnan W, Ruyue W, Jihong L, Yanting T, Haoping G, Lili H, Dongyue W, Xueling W. Construction of a high-density genetic map using specific-length amplified fragment markers and identification of QTLs for branching angle in poplar. Mol Genet Genomics 2022; 297:345-356. [PMID: 35015131 DOI: 10.1007/s00438-021-01850-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 12/18/2021] [Indexed: 11/28/2022]
Abstract
Branching angle is a critical factor that determines the morphological establishment and is a typical quantitative trait controlled by multiple genes. In this study, we used SLAF-seq to construct a high-density genetic map, to investigate the genetic architecture of branching angle in poplar (Populus leucopyramidalis). A total of 240,672 SLAF tags were obtained, including 103,691 polymorphic SLAF tags. After filtering, 53,407 polymorphic markers were sorted into eight segregation types, and 11,162 of them were used to construct the genetic map. 8447 were on the female parent map, 8532 were on the male parent map, and 11,162 were on the integrated map. The marker coverage was 4820.84 and 5044.80 cM for the female and male maps, and 3142.61 cM for the integrated map. The average intervals between two adjacent mapped markers were 0.55, 0.59, and 0.28 cM for the three maps, respectively. Two quantitative trait loci (QTLs) were detected. Seven markers that exceeded the threshold in these two regions were considered as being associated with branching angle and the phenotypic variance explained by each of these marker was 10.64-11.66%. After functional annotation, we identified 15 candidate genes and analyzed the expression of candidate genes in narrow and wide crown progenies by qRT-PCR. These results show that the combination of QTL and SLAF-seq will contribute to future breeding plans in poplar breeding, especially in narrow crown poplar breeding.
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Affiliation(s)
- Wang Jinnan
- College of Forestry, Shandong Agricultural University, Taian, 271018, Shangdong, China.,Mountain Tai Forest Ecosystem Research Station of State Forestry and Grassland Administration, Shandong Agricultural University, Taian, 271018, Shangdong, China.,State Forestry and Grassland Administration Key Laboratory of Silviculture in Downstream Areas of the Yellow River, Taian, 271018, Shangdong, China
| | - Wang Ruyue
- College of Forestry, Shandong Agricultural University, Taian, 271018, Shangdong, China.,Mountain Tai Forest Ecosystem Research Station of State Forestry and Grassland Administration, Shandong Agricultural University, Taian, 271018, Shangdong, China.,State Forestry and Grassland Administration Key Laboratory of Silviculture in Downstream Areas of the Yellow River, Taian, 271018, Shangdong, China
| | - Li Jihong
- College of Forestry, Shandong Agricultural University, Taian, 271018, Shangdong, China. .,Mountain Tai Forest Ecosystem Research Station of State Forestry and Grassland Administration, Shandong Agricultural University, Taian, 271018, Shangdong, China. .,State Forestry and Grassland Administration Key Laboratory of Silviculture in Downstream Areas of the Yellow River, Taian, 271018, Shangdong, China.
| | - Tian Yanting
- College of Forestry, Shandong Agricultural University, Taian, 271018, Shangdong, China.,Mountain Tai Forest Ecosystem Research Station of State Forestry and Grassland Administration, Shandong Agricultural University, Taian, 271018, Shangdong, China.,State Forestry and Grassland Administration Key Laboratory of Silviculture in Downstream Areas of the Yellow River, Taian, 271018, Shangdong, China
| | - Guo Haoping
- College of Forestry, Shandong Agricultural University, Taian, 271018, Shangdong, China.,Mountain Tai Forest Ecosystem Research Station of State Forestry and Grassland Administration, Shandong Agricultural University, Taian, 271018, Shangdong, China.,State Forestry and Grassland Administration Key Laboratory of Silviculture in Downstream Areas of the Yellow River, Taian, 271018, Shangdong, China
| | - Hou Lili
- College of Forestry, Shandong Agricultural University, Taian, 271018, Shangdong, China.,Mountain Tai Forest Ecosystem Research Station of State Forestry and Grassland Administration, Shandong Agricultural University, Taian, 271018, Shangdong, China.,State Forestry and Grassland Administration Key Laboratory of Silviculture in Downstream Areas of the Yellow River, Taian, 271018, Shangdong, China
| | - Wang Dongyue
- College of Forestry, Shandong Agricultural University, Taian, 271018, Shangdong, China.,Mountain Tai Forest Ecosystem Research Station of State Forestry and Grassland Administration, Shandong Agricultural University, Taian, 271018, Shangdong, China.,State Forestry and Grassland Administration Key Laboratory of Silviculture in Downstream Areas of the Yellow River, Taian, 271018, Shangdong, China
| | - Wang Xueling
- College of Forestry, Shandong Agricultural University, Taian, 271018, Shangdong, China.,Mountain Tai Forest Ecosystem Research Station of State Forestry and Grassland Administration, Shandong Agricultural University, Taian, 271018, Shangdong, China.,State Forestry and Grassland Administration Key Laboratory of Silviculture in Downstream Areas of the Yellow River, Taian, 271018, Shangdong, China
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Development of SNP Set for the Marker-Assisted Selection of Guar ( Cyamopsis tetragonoloba (L.) Taub.) Based on a Custom Reference Genome Assembly. PLANTS 2021; 10:plants10102063. [PMID: 34685872 PMCID: PMC8539970 DOI: 10.3390/plants10102063] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 09/20/2021] [Accepted: 09/27/2021] [Indexed: 12/11/2022]
Abstract
Guar gum, a polysaccharide derived from guar seeds, is widely used in a variety of industrial applications, including oil and gas production. Although guar is mostly propagated in India, interest in guar as a new industrial legume crop is increasing worldwide, demanding the development of effective tools for marker-assisted selection. In this paper, we report a wide-ranging set of 4907 common SNPs and 327 InDels generated from RADseq genotyping data of 166 guar plants of different geographical origin. A custom guar reference genome was assembled and used for variant calling. A consensus set of variants was built using three bioinformatic pipelines for short variant discovery. The developed molecular markers were used for genome-wide association study, resulting in the discovery of six markers linked to the variation of an important agronomic trait—percentage of pods matured to the harvest date under long light day conditions. One of the associated variants was found inside the putative transcript sequence homologous to an ABC transporter in Arabidopsis, which has been shown to play an important role in D-myo-inositol phosphates metabolism. Earlier, we suggested that genes involved in myo-inositol phosphate metabolism have significant impact on the early flowering of guar plants. Hence, we believe that the developed SNP set allows for the identification of confident molecular markers of important agrobiological traits.
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Chernova AI, Gubaev RF, Singh A, Sherbina K, Goryunova SV, Martynova EU, Goryunov DV, Boldyrev SV, Vanyushkina AA, Anikanov NA, Stekolshchikova EA, Yushina EA, Demurin YN, Mukhina ZM, Gavrilova VA, Anisimova IN, Karabitsina YI, Alpatieva NV, Chang PL, Khaitovich P, Mazin PV, Nuzhdin SV. Genotyping and lipid profiling of 601 cultivated sunflower lines reveals novel genetic determinants of oil fatty acid content. BMC Genomics 2021; 22:505. [PMID: 34225652 PMCID: PMC8256595 DOI: 10.1186/s12864-021-07768-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 06/03/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Sunflower is an important oilseed crop domesticated in North America approximately 4000 years ago. During the last century, oil content in sunflower was under strong selection. Further improvement of oil properties achieved by modulating its fatty acid composition is one of the main directions in modern oilseed crop breeding. RESULTS We searched for the genetic basis of fatty acid content variation by genotyping 601 inbred sunflower lines and assessing their lipid and fatty acid composition. Our genome-wide association analysis based on the genotypes for 15,483 SNPs and the concentrations of 23 fatty acids, including minor fatty acids, revealed significant genetic associations for eleven of them. Identified genomic regions included the loci involved in rare fatty acids variation on chromosomes 3 and 14, explaining up to 34.5% of the total variation of docosanoic acid (22:0) in sunflower oil. CONCLUSIONS This is the first large scale implementation of high-throughput lipidomic profiling to sunflower germplasm characterization. This study contributes to the genetic characterization of Russian sunflower collections, which made a substantial contribution to the development of sunflower as the oilseed crop worldwide, and provides new insights into the genetic control of oil composition that can be implemented in future studies.
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Affiliation(s)
- Alina I Chernova
- Skolkovo Institute of Science and Technology (Skoltech), Bolshoy Boulevard 30, bld. 1, Moscow, 121205, Russia. .,LLC "OIL GENE", Skolkovo Innovation Center, Moscow, Russia.
| | - Rim F Gubaev
- Skolkovo Institute of Science and Technology (Skoltech), Bolshoy Boulevard 30, bld. 1, Moscow, 121205, Russia.,LLC "OIL GENE", Skolkovo Innovation Center, Moscow, Russia
| | - Anupam Singh
- Department of Biological Sciences, University of Southern California, Los Angeles, CA, 90089, USA
| | - Katrina Sherbina
- Department of Biological Sciences, University of Southern California, Los Angeles, CA, 90089, USA
| | - Svetlana V Goryunova
- Skolkovo Institute of Science and Technology (Skoltech), Bolshoy Boulevard 30, bld. 1, Moscow, 121205, Russia.,Vavilov Institute of General Genetics, Russian Academy of Sciences, Gubkin st. 3, Moscow, 119991, Russia.,FSBSI Lorch Potato Research Institute, Lorkha Str. 23, Kraskovo, 140051, Russia
| | - Elena U Martynova
- Skolkovo Institute of Science and Technology (Skoltech), Bolshoy Boulevard 30, bld. 1, Moscow, 121205, Russia
| | - Denis V Goryunov
- Skolkovo Institute of Science and Technology (Skoltech), Bolshoy Boulevard 30, bld. 1, Moscow, 121205, Russia.,MSU A.N. Belozersky Institute of Physico-Chemical Biology, Leninsky Gori 1, Building 40, Moscow, 119992, Russia
| | - Stepan V Boldyrev
- Skolkovo Institute of Science and Technology (Skoltech), Bolshoy Boulevard 30, bld. 1, Moscow, 121205, Russia.,LLC "OIL GENE", Skolkovo Innovation Center, Moscow, Russia
| | - Anna A Vanyushkina
- Skolkovo Institute of Science and Technology (Skoltech), Bolshoy Boulevard 30, bld. 1, Moscow, 121205, Russia
| | - Nikolay A Anikanov
- Skolkovo Institute of Science and Technology (Skoltech), Bolshoy Boulevard 30, bld. 1, Moscow, 121205, Russia
| | - Elena A Stekolshchikova
- Skolkovo Institute of Science and Technology (Skoltech), Bolshoy Boulevard 30, bld. 1, Moscow, 121205, Russia
| | - Ekaterina A Yushina
- Skolkovo Institute of Science and Technology (Skoltech), Bolshoy Boulevard 30, bld. 1, Moscow, 121205, Russia.,FSBSI N P Bochkov Research Center of Medical Genetics, Moskvorechye St.1, Moscow, 115522, Russia
| | - Yakov N Demurin
- Pustovoit All-Russia Research Institute of Oilseed Crops, Filatova St. 17, Krasnodar, 350038, Russia
| | | | - Vera A Gavrilova
- N. I. Vavilov Research Institute of Plant Genetic Resources (VIR), 42 B. Morskaja, St. Petersburg, 190000, Russia
| | - Irina N Anisimova
- N. I. Vavilov Research Institute of Plant Genetic Resources (VIR), 42 B. Morskaja, St. Petersburg, 190000, Russia
| | - Yulia I Karabitsina
- N. I. Vavilov Research Institute of Plant Genetic Resources (VIR), 42 B. Morskaja, St. Petersburg, 190000, Russia
| | - Natalia V Alpatieva
- N. I. Vavilov Research Institute of Plant Genetic Resources (VIR), 42 B. Morskaja, St. Petersburg, 190000, Russia
| | - Peter L Chang
- Department of Biological Sciences, University of Southern California, Los Angeles, CA, 90089, USA
| | - Philipp Khaitovich
- Skolkovo Institute of Science and Technology (Skoltech), Bolshoy Boulevard 30, bld. 1, Moscow, 121205, Russia
| | - Pavel V Mazin
- Skolkovo Institute of Science and Technology (Skoltech), Bolshoy Boulevard 30, bld. 1, Moscow, 121205, Russia
| | - Sergey V Nuzhdin
- Department of Biological Sciences, University of Southern California, Los Angeles, CA, 90089, USA
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Volynkin V, Vasylyk I, Volodin V, Grigoreva E, Karzhaev D, Lushchay E, Ulianich P, Volkov V, Risovannaya V, Blinova S, Alekseev J, Gorislavets S, Likhovskoi V, Beatovic A, Potokina E. The Assessment of Agrobiological and Disease Resistance Traits of Grapevine Hybrid Populations ( Vitis vinifera L. × Muscadinia rotundifolia Michx.) in the Climatic Conditions of Crimea. PLANTS 2021; 10:plants10061215. [PMID: 34203712 PMCID: PMC8232157 DOI: 10.3390/plants10061215] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/06/2021] [Accepted: 06/11/2021] [Indexed: 11/24/2022]
Abstract
The Crimean autochthonous grape varieties are unique by their origin and serve as a valuable source for breeding new cultivars with increased salt and frost resistance, as well as high-quality berries. However, they suffer from fungal pathogens, as the dry and hot summer months contribute to the epiphytotic course of diseases. An increase in the resistance of Crimean grape varieties is currently achieved through interspecific hybridization. In this study, we describe the genetic and agrobiological diversity of three hybrid populations obtained using the Vitis interspecific hybrid ‘Magarach 31-77-10′ as a female parent and Muscadinia rotundifolia × Vitis vinifera BC5 hybrid plants as male parents. The hybrid nature of the populations was assessed using RADseq high-throughput genotyping. We discovered 12,734 SNPs, which were common to all three hybrid populations. We also proved with the SSR markers that the strong powdery and downy mildew resistance of the paternal genotypes is determined by the dominant Run1/Rpv1 locus inherited from M. rotundifolia. As a result, the disease development score (R, %) for both mildew diseases in the female parent ‘Magarach 31-77-10’ was three times higher than in male parents 2000-305-143 and 2000-305-163 over two years of phytopathological assessment. The highest values of yield-contributing traits (average bunch weight ~197 g and 1.3 kg as yield per plant) were detected in the population 4-11 (♀M. No. 31-77-10 × 2000-305-163). Despite the epiphytotic development of PM, the spread of oidium to the vegetative organs of hybrids 4-11 did not exceed 20%. Some hybrid genotypes with high productivity and resistance to pathogens were selected for further assessment as promising candidates for new varieties.
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Affiliation(s)
- Vladimir Volynkin
- All-Russian National Research Institute of Viticulture and Winemaking ‘Magarach’ RAS, 298600 Yalta, Russia; (V.V.); (I.V.); (V.V.); (E.G.); (D.K.); (E.L.); (P.U.); (V.V.); (V.R.); (J.A.); (S.G.); (V.L.)
| | - Irina Vasylyk
- All-Russian National Research Institute of Viticulture and Winemaking ‘Magarach’ RAS, 298600 Yalta, Russia; (V.V.); (I.V.); (V.V.); (E.G.); (D.K.); (E.L.); (P.U.); (V.V.); (V.R.); (J.A.); (S.G.); (V.L.)
| | - Vitalii Volodin
- All-Russian National Research Institute of Viticulture and Winemaking ‘Magarach’ RAS, 298600 Yalta, Russia; (V.V.); (I.V.); (V.V.); (E.G.); (D.K.); (E.L.); (P.U.); (V.V.); (V.R.); (J.A.); (S.G.); (V.L.)
| | - Elizaveta Grigoreva
- All-Russian National Research Institute of Viticulture and Winemaking ‘Magarach’ RAS, 298600 Yalta, Russia; (V.V.); (I.V.); (V.V.); (E.G.); (D.K.); (E.L.); (P.U.); (V.V.); (V.R.); (J.A.); (S.G.); (V.L.)
- Institute of Forest and Natural Resources Management, Saint Petersburg State Forest Technical University, 194021 St. Petersburg, Russia
- Information Technologies and Programming Faculty, ITMO University, 197101 St. Petersburg, Russia;
| | - Dmitry Karzhaev
- All-Russian National Research Institute of Viticulture and Winemaking ‘Magarach’ RAS, 298600 Yalta, Russia; (V.V.); (I.V.); (V.V.); (E.G.); (D.K.); (E.L.); (P.U.); (V.V.); (V.R.); (J.A.); (S.G.); (V.L.)
- Institute of Forest and Natural Resources Management, Saint Petersburg State Forest Technical University, 194021 St. Petersburg, Russia
| | - Ekaterina Lushchay
- All-Russian National Research Institute of Viticulture and Winemaking ‘Magarach’ RAS, 298600 Yalta, Russia; (V.V.); (I.V.); (V.V.); (E.G.); (D.K.); (E.L.); (P.U.); (V.V.); (V.R.); (J.A.); (S.G.); (V.L.)
| | - Pavel Ulianich
- All-Russian National Research Institute of Viticulture and Winemaking ‘Magarach’ RAS, 298600 Yalta, Russia; (V.V.); (I.V.); (V.V.); (E.G.); (D.K.); (E.L.); (P.U.); (V.V.); (V.R.); (J.A.); (S.G.); (V.L.)
- All-Russian Research Institute of Agricultural Microbiology, 196608 St. Petersburg, Russia
| | - Vladimir Volkov
- All-Russian National Research Institute of Viticulture and Winemaking ‘Magarach’ RAS, 298600 Yalta, Russia; (V.V.); (I.V.); (V.V.); (E.G.); (D.K.); (E.L.); (P.U.); (V.V.); (V.R.); (J.A.); (S.G.); (V.L.)
- Institute of Forest and Natural Resources Management, Saint Petersburg State Forest Technical University, 194021 St. Petersburg, Russia
| | - Valentina Risovannaya
- All-Russian National Research Institute of Viticulture and Winemaking ‘Magarach’ RAS, 298600 Yalta, Russia; (V.V.); (I.V.); (V.V.); (E.G.); (D.K.); (E.L.); (P.U.); (V.V.); (V.R.); (J.A.); (S.G.); (V.L.)
| | - Sofiya Blinova
- Syntol, 127434 Moscow, Russia;
- All-Russian Research Institute of Agricultural Biotechnology, 127434 Moscow, Russia
| | - Jakov Alekseev
- All-Russian National Research Institute of Viticulture and Winemaking ‘Magarach’ RAS, 298600 Yalta, Russia; (V.V.); (I.V.); (V.V.); (E.G.); (D.K.); (E.L.); (P.U.); (V.V.); (V.R.); (J.A.); (S.G.); (V.L.)
- Syntol, 127434 Moscow, Russia;
| | - Svetlana Gorislavets
- All-Russian National Research Institute of Viticulture and Winemaking ‘Magarach’ RAS, 298600 Yalta, Russia; (V.V.); (I.V.); (V.V.); (E.G.); (D.K.); (E.L.); (P.U.); (V.V.); (V.R.); (J.A.); (S.G.); (V.L.)
| | - Vladimir Likhovskoi
- All-Russian National Research Institute of Viticulture and Winemaking ‘Magarach’ RAS, 298600 Yalta, Russia; (V.V.); (I.V.); (V.V.); (E.G.); (D.K.); (E.L.); (P.U.); (V.V.); (V.R.); (J.A.); (S.G.); (V.L.)
| | - Aleksandar Beatovic
- Information Technologies and Programming Faculty, ITMO University, 197101 St. Petersburg, Russia;
| | - Elena Potokina
- All-Russian National Research Institute of Viticulture and Winemaking ‘Magarach’ RAS, 298600 Yalta, Russia; (V.V.); (I.V.); (V.V.); (E.G.); (D.K.); (E.L.); (P.U.); (V.V.); (V.R.); (J.A.); (S.G.); (V.L.)
- Institute of Forest and Natural Resources Management, Saint Petersburg State Forest Technical University, 194021 St. Petersburg, Russia
- Correspondence: ; Tel.: +7-911-084-1422
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9
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Chen M, Fan W, Ji F, Hua H, Liu J, Yan M, Ma Q, Fan J, Wang Q, Zhang S, Liu G, Sun Z, Tian C, Zhao F, Zheng J, Zhang Q, Chen J, Qiu J, Wei X, Chen Z, Zhang P, Pei D, Yang J, Huang X. Genome-wide identification of agronomically important genes in outcrossing crops using OutcrossSeq. MOLECULAR PLANT 2021; 14:556-570. [PMID: 33429094 DOI: 10.1016/j.molp.2021.01.003] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 12/07/2020] [Accepted: 01/06/2021] [Indexed: 05/27/2023]
Abstract
Many important crops (e.g., tuber, root, and tree crops) are cross-pollinating. For these crops, no inbred lines are available for genetic study and breeding because they are self-incompatible, clonally propagated, or have a long generation time, making the identification of agronomically important genes difficult, particularly in crops with a complex autopolyploid genome. In this study, we developed a method, OutcrossSeq, for mapping agronomically important loci in outcrossing crops based on whole-genome low-coverage resequencing of a large genetic population, and designed three computation algorithms in OutcrossSeq for different types of outcrossing populations. We applied OutcrossSeq to a tuberous root crop (sweet potato, autopolyploid), a tree crop (walnut tree, highly heterozygous diploid), and hybrid crops (double-cross populations) to generate high-density genotype maps for the outcrossing populations, which enable precise identification of genomic loci underlying important agronomic traits. Candidate causative genes at these loci were detected based on functional clues. Taken together, our results indicate that OutcrossSeq is a robust and powerful method for identifying agronomically important genes in heterozygous species, including polyploids, in a cost-efficient way. The OutcrossSeq software and its instruction manual are available for downloading at www.xhhuanglab.cn/tool/OutcrossSeq.html.
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Affiliation(s)
- Mengjiao Chen
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Weijuan Fan
- Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Plant Science Research Center, Chinese Academy of Sciences, Shanghai Chenshan Botanical Garden, Shanghai 201602, China
| | - Feiyang Ji
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of the State Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Hua Hua
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Jie Liu
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Mengxiao Yan
- Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Plant Science Research Center, Chinese Academy of Sciences, Shanghai Chenshan Botanical Garden, Shanghai 201602, China
| | - Qingguo Ma
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of the State Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Jiongjiong Fan
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Qin Wang
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Shufeng Zhang
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Guiling Liu
- Tai'an Academy of Agricultural Sciences, Tai'an 271000, Shandong, China
| | - Zhe Sun
- Tai'an Academy of Agricultural Sciences, Tai'an 271000, Shandong, China
| | - Changgeng Tian
- Tai'an Academy of Agricultural Sciences, Tai'an 271000, Shandong, China
| | - Fengling Zhao
- Tai'an Academy of Agricultural Sciences, Tai'an 271000, Shandong, China
| | - Jianli Zheng
- Tai'an Academy of Agricultural Sciences, Tai'an 271000, Shandong, China
| | - Qi Zhang
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Jiaxin Chen
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Jie Qiu
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Xin Wei
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Ziru Chen
- National Genomics Data Center, Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China
| | - Peng Zhang
- CAS Center for Excellence of Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200233, China.
| | - Dong Pei
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of the State Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China.
| | - Jun Yang
- Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Plant Science Research Center, Chinese Academy of Sciences, Shanghai Chenshan Botanical Garden, Shanghai 201602, China.
| | - Xuehui Huang
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China.
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10
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Tong C, Yao D, Wu H, Chen Y, Yang W, Zhao W. High-Quality SNP Linkage Maps Improved QTL Mapping and Genome Assembly in Populus. J Hered 2020; 111:515-530. [PMID: 32930789 PMCID: PMC7751148 DOI: 10.1093/jhered/esaa039] [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: 06/15/2020] [Accepted: 09/11/2020] [Indexed: 12/15/2022] Open
Abstract
With the advances in high-throughput sequencing technologies and the development of new software for extracting single nucleotide polymorphisms (SNPs) across a mapping population, it is possible to construct high-quality genetic maps with thousands of SNPs in outbred forest trees. Two parent-specific linkage maps were constructed with restriction site-associated DNA sequencing data from an F1 hybrid population derived from Populus deltoides and Populus simonii, and applied in QTL mapping and genome assembly. The female P. deltoides map contained 4018 SNPs, which were divided into 19 linkage groups under a wide range of LOD thresholds from 7 to 55. The male P. simonii map showed similar characteristics, consisting of 2097 SNPs, which also belonged to 19 linkage groups under LOD thresholds of 7 to 29. The SNP order of each linkage group was optimal among different ordering results from several available software. Moreover, the linkage maps allowed the detection of 39 QTLs underlying tree height and 47 for diameter at breast height. In addition, the linkage maps improved the anchoring of 689 contigs of P. simonii to chromosomes. The 2 parental genetic maps of Populus are of high quality, especially in terms of SNP data quality, the SNP order within linkage groups, and the perfect match between the number of linkage groups and the karyotype of Populus, as well as the excellent performances in QTL mapping and genome assembly. Both approaches for extracting and ordering SNPs could be applied to other species for constructing high-quality genetic maps.
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Affiliation(s)
- Chunfa Tong
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing, China
| | - Dan Yao
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing, China
| | - Hainan Wu
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing, China
| | - Yuhua Chen
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing, China
| | - Wenguo Yang
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing, China
| | - Wei Zhao
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing, China
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11
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Update of Genetic Linkage Map and QTL Analysis for Growth Traits in Eucommia ulmoides Oliver. FORESTS 2020. [DOI: 10.3390/f11030311] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Eucommia ulmoides (Tu-chung) is an economically and ecologically important tree species which has attracted worldwide attention due to its application in pharmacology, landscaping, wind sheltering and sand fixation. Molecular marker technologies can elucidate the genetic mechanism and substantially improve the breeding efficiency of E. ulmoides. The current research updated the original linkage map, and quantitative trait loci (QTL) analysis was performed on tree growth traits measured over 10 consecutive years in an E. ulmoides F1 population (“Xiaoye” × “Qinzhong No.1”). In total, 452 polymorphic markers were scored from 365 simple sequence repeat (SSR) primers, with an average of 1.24 polymorphic markers per primer combination. The integrated map was 1913.29 cM (centimorgan) long, covering 94.10% of the estimated genome and with an average marker density of 2.20 cM. A total of 869 markers were mapped into 19 major independent linkage groups. Growth-related traits measured over 10 consecutive years showed a significant correlation, and 89 hypothetical QTLs were forecasted and divided into 27 distinct loci. Three traits for tree height, ground diameter and crown diameter detected 25 QTLs (13 loci), 32 QTLs (17 loci) and 15 QTLs (10 loci), respectively. Based on BLASTX search results in the NCBI database, six candidate genes were obtained. It is important to explore the growth-related genetic mechanism and lay the foundation for the genetic improvement of E. ulmoides at the molecular level.
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12
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Inferring the Genomic Landscape of Recombination Rate Variation in European Aspen ( Populus tremula). G3-GENES GENOMES GENETICS 2020; 10:299-309. [PMID: 31744900 PMCID: PMC6945010 DOI: 10.1534/g3.119.400504] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
The rate of meiotic recombination is one of the central factors determining genome-wide levels of linkage disequilibrium which has important consequences for the efficiency of natural selection and for the dissection of quantitative traits. Here we present a new, high-resolution linkage map for Populus tremula that we use to anchor approximately two thirds of the P. tremula draft genome assembly on to the expected 19 chromosomes, providing us with the first chromosome-scale assembly for P. tremula (Table 2). We then use this resource to estimate variation in recombination rates across the P. tremula genome and compare these results to recombination rates based on linkage disequilibrium in a large number of unrelated individuals. We also assess how variation in recombination rates is associated with a number of genomic features, such as gene density, repeat density and methylation levels. We find that recombination rates obtained from the two methods largely agree, although the LD-based method identifies a number of genomic regions with very high recombination rates that the map-based method fails to detect. Linkage map and LD-based estimates of recombination rates are positively correlated and show similar correlations with other genomic features, showing that both methods can accurately infer recombination rate variation across the genome. Recombination rates are positively correlated with gene density and negatively correlated with repeat density and methylation levels, suggesting that recombination is largely directed toward gene regions in P. tremula.
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13
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Zhebentyayeva TN, Sisco PH, Georgi LL, Jeffers SN, Perkins MT, James JB, Hebard FV, Saski C, Nelson CD, Abbott AG. Dissecting Resistance to Phytophthora cinnamomi in Interspecific Hybrid Chestnut Crosses Using Sequence-Based Genotyping and QTL Mapping. PHYTOPATHOLOGY 2019; 109:1594-1604. [PMID: 31287366 DOI: 10.1094/phyto-11-18-0425-r] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
The soilborne oomycete Phytophthora cinnamomi-which causes root rot, trunk cankers, and stem lesions on an estimated 5,000 plant species worldwide-is a lethal pathogen of American chestnut (Castanea dentata) as well as many other woody plant species. P. cinnamomi is particularly damaging to chestnut and chinquapin trees (Castanea spp.) in the southern portion of its native range in the United States due to relatively mild climatic conditions that are conductive to disease development. Introduction of resistant genotypes is the most practical solution for disease management in forests because treatment with fungicides and eradication of the pathogen are neither practical nor economically feasible in natural ecosystems. Using backcross families derived from crosses of American chestnuts with two resistant Chinese chestnut cultivars Mahogany and Nanking, we constructed linkage maps and identified quantitative trait loci (QTLs) for resistance to P. cinnamomi that had been introgressed from these Chinese chestnut cultivars. In total, 957 plants representing five cohorts of three hybrid crosses were genotyped by sequencing and phenotyped by standardized inoculation and visual examination over a 6-year period from 2011 to 2016. Eight parental linkage maps comprising 7,715 markers were constructed, and 17 QTLs were identified on four linkage groups (LGs): LG_A, LG_C, LG_E, and LG_K. The most consistent QTLs were detected on LG_E in seedlings from crosses with both 'Mahogany' and 'Nanking' and LG_K in seedlings from 'Mahogany' crosses. Two consistent large and medium effect QTLs located ∼10 cM apart were present in the middle and at the lower end of LG_E; other QTLs were considered to have small effects. These results imply that the genetic architecture of resistance to P. cinnamomi in Chinese chestnut × American chestnut hybrid progeny may resemble the P. sojae-soybean pathosystem, with a few dominant QTLs along with quantitatively inherited partial resistance conferred by multiple small-effect QTLs.
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Affiliation(s)
- Tetyana N Zhebentyayeva
- Department of Ecosystem Science and Management, The Pennsylvania State University, University Park, PA 16802
- Clemson University Genomics and Computational Biology Laboratory, Clemson, SC 29634
| | - Paul H Sisco
- Meadowview Research Farms, The American Chestnut Foundation, Meadowview, VA 24361
| | - Laura L Georgi
- Meadowview Research Farms, The American Chestnut Foundation, Meadowview, VA 24361
| | - Steven N Jeffers
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC 29634
| | - M Taylor Perkins
- Department of Biology, Geology, and Environmental Science, University of Tennessee at Chattanooga, Chattanooga, TN 37403
| | | | - Frederick V Hebard
- Meadowview Research Farms, The American Chestnut Foundation, Meadowview, VA 24361
| | - Christopher Saski
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC 29634
| | - C Dana Nelson
- Southern Institute of Forest Genetics, Southern Research Station, U.S. Department of Agriculture Forest Service, Saucier, MS 39574
- Forest Health Research and Education Center, University of Kentucky, Lexington, KY 40546
| | - Albert G Abbott
- Forest Health Research and Education Center, University of Kentucky, Lexington, KY 40546
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14
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Dong M, He Q, Zhao J, Zhang Y, Yuan D, Zhang AJ. Genetic Mapping of Prince Rupprecht's Larch ( Larix principis-rupprechtii Mayr) by Specific-Locus Amplified Fragment Sequencing. Genes (Basel) 2019; 10:genes10080583. [PMID: 31370324 PMCID: PMC6723236 DOI: 10.3390/genes10080583] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2019] [Revised: 07/12/2019] [Accepted: 07/29/2019] [Indexed: 11/24/2022] Open
Abstract
A high-density genetic linkage map is essential for plant genetics and genomics research. However, due to the deficiency of genomic data and high-quality molecular markers, no genetic map has been published for Prince Rupprecht’s larch (Larix principis-rupprechtii Mayr), a conifer species with high ecological and commercial value in northern China. In this study, 145 F1 progeny individuals from an intraspecific cross between two elite clones of L. principis-rupprechtii and their parents were employed to construct the first genetic map in this important tree species using specific-locus amplified fragment sequencing (SLAF-seq). After preprocessing, the procedure yielded 300.20 Gb of raw data containing 1501.22 M pair-end reads. A total of 324,352 SNP markers were detected and 122,785 of them were polymorphic, with a polymorphism rate of 37.86%. Ultimately, 6099 SNPs were organized into a genetic map containing 12 linkage groups, consistent with the haploid chromosome number of larch and most other species in the Pinaceae family. The linkage map spanned 2415.58 cM and covered 99.6% of the L. principis-rupprechtii genome with an average of 0.4 cM between adjacent markers. To the best of our knowledge, this map is the first reference map for L. principis-rupprechtii, as well as the densest one obtained in larch species thus far. The genome-wide SNPs and the high-resolution genetic map will provide a foundation for future quantitative trait loci mapping, map-based cloning, marker-assisted selection, comparative genomics, and genome sequence assembly for larch trees.
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Affiliation(s)
- Mingliang Dong
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, National Engineering Laboratory for Tree Breeding, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, Key Laboratory of Forest Trees and Ornamental Plants Biological Engineering of State Forestry Administration, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
| | - Qingwei He
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, National Engineering Laboratory for Tree Breeding, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, Key Laboratory of Forest Trees and Ornamental Plants Biological Engineering of State Forestry Administration, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
| | - Jian Zhao
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, National Engineering Laboratory for Tree Breeding, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, Key Laboratory of Forest Trees and Ornamental Plants Biological Engineering of State Forestry Administration, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
| | - Yan Zhang
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, National Engineering Laboratory for Tree Breeding, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, Key Laboratory of Forest Trees and Ornamental Plants Biological Engineering of State Forestry Administration, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
| | - Deshui Yuan
- National Key Seed Base of Larch, Weichang, Chengde 068450, China
| | - And Jinfeng Zhang
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, National Engineering Laboratory for Tree Breeding, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, Key Laboratory of Forest Trees and Ornamental Plants Biological Engineering of State Forestry Administration, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China.
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15
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Mariotti R, Fornasiero A, Mousavi S, Cultrera NG, Brizioli F, Pandolfi S, Passeri V, Rossi M, Magris G, Scalabrin S, Scaglione D, Di Gaspero G, Saumitou-Laprade P, Vernet P, Alagna F, Morgante M, Baldoni L. Genetic Mapping of the Incompatibility Locus in Olive and Development of a Linked Sequence-Tagged Site Marker. FRONTIERS IN PLANT SCIENCE 2019; 10:1760. [PMID: 32117338 PMCID: PMC7025539 DOI: 10.3389/fpls.2019.01760] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 12/16/2019] [Indexed: 05/20/2023]
Abstract
The genetic control of self-incompatibility (SI) has been recently disclosed in olive. Inter-varietal crossing confirmed the presence of only two incompatibility groups (G1 and G2), suggesting a simple Mendelian inheritance of the trait. A double digest restriction associated DNA (ddRAD) sequencing of a biparental population segregating for incompatibility groups has been performed and high-density linkage maps were constructed in order to map the SI locus and identify gene candidates and linked markers. The progeny consisted of a full-sib family of 229 individuals derived from the cross 'Leccino' (G1) × 'Dolce Agogia' (G2) varieties, segregating 1:1 (G1:G2), in accordance with a diallelic self-incompatibility (DSI) model. A total of 16,743 single nucleotide polymorphisms was identified, 7,006 in the female parent 'Leccino' and 9,737 in the male parent 'Dolce Agogia.' Each parental map consisted of 23 linkage groups and showed an unusual large size (5,680 cM in 'Leccino' and 3,538 cM in 'Dolce Agogia'). Recombination was decreased across all linkage groups in pollen mother cells of 'Dolce Agogia,' the parent with higher heterozygosity, compared to megaspore mother cells of 'Leccino,' in a context of a species that showed exceptionally high recombination rates. A subset of 109 adult plants was assigned to either incompatibility group by a stigma test and the diallelic self-incompatibility (DSI) locus was mapped to an interval of 5.4 cM on linkage group 18. This region spanned a size of approximately 300 Kb in the olive genome assembly. We developed a sequence-tagged site marker in the DSI locus and identified five haplotypes in 57 cultivars with known incompatibility group assignment. A combination of two single-nucleotide polymorphisms (SNPs) was sufficient to predict G1 or G2 phenotypes in olive cultivars, enabling early marker-assisted selection of compatible genotypes and allowing for a rapid screening of inter-compatibility among cultivars in order to guarantee effective fertilization and increase olive production. The construction of high-density linkage maps has led to the development of the first functional marker in olive and provided positional candidate genes in the SI locus.
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Affiliation(s)
- Roberto Mariotti
- CNR - Institute of Biosciences and Bioresources (IBBR), Perugia, Italy
| | - Alice Fornasiero
- Institute of Applied Genomics, Udine, Italy
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, Udine, Italy
| | - Soraya Mousavi
- CNR - Institute of Biosciences and Bioresources (IBBR), Perugia, Italy
| | | | - Federico Brizioli
- CNR - Institute of Biosciences and Bioresources (IBBR), Perugia, Italy
| | - Saverio Pandolfi
- CNR - Institute of Biosciences and Bioresources (IBBR), Perugia, Italy
| | - Valentina Passeri
- CNR - Institute of Biosciences and Bioresources (IBBR), Perugia, Italy
| | - Martina Rossi
- CNR - Institute of Biosciences and Bioresources (IBBR), Perugia, Italy
| | - Gabriele Magris
- Institute of Applied Genomics, Udine, Italy
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, Udine, Italy
| | | | | | | | | | - Philippe Vernet
- University of Lille, CNRS, UMR 8198 - Evo-Eco-Paleo, F-59000, Lille, France
| | | | - Michele Morgante
- Institute of Applied Genomics, Udine, Italy
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, Udine, Italy
| | - Luciana Baldoni
- CNR - Institute of Biosciences and Bioresources (IBBR), Perugia, Italy
- *Correspondence: Luciana Baldoni,
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16
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De-Kayne R, Feulner PGD. A European Whitefish Linkage Map and Its Implications for Understanding Genome-Wide Synteny Between Salmonids Following Whole Genome Duplication. G3 (BETHESDA, MD.) 2018; 8:3745-3755. [PMID: 30297382 PMCID: PMC6288842 DOI: 10.1534/g3.118.200552] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Accepted: 10/03/2018] [Indexed: 12/11/2022]
Abstract
Genomic datasets continue to increase in number due to the ease of production for a wider selection of species including non-model organisms. For many of these species, especially those with large or polyploid genomes, highly contiguous and well-annotated genomes are still rare due to the complexity and cost involved in their assembly. As a result, a common starting point for genomic work in non-model species is the production of a linkage map. Dense linkage maps facilitate the analysis of genomic data in a variety of ways, from broad scale observations regarding genome structure e.g., chromosome number and type or sex-related structural differences, to fine scale patterns e.g., recombination rate variation and co-localization of differentiated regions. Here we present both sex-averaged and sex-specific linkage maps for Coregonus sp. "Albock", a member of the European whitefish lineage (C. lavaretus spp. complex), containing 5395 single nucleotide polymorphism (SNP) loci across 40 linkage groups to facilitate future investigation into the genomic basis of whitefish adaptation and speciation. The map was produced using restriction-site associated digestion (RAD) sequencing data from two wild-caught parents and 156 F1 offspring. We discuss the differences between our sex-averaged and sex-specific maps and identify genome-wide synteny between C. sp. "Albock" and Atlantic Salmon (Salmo salar), which have diverged following the salmonid-specific whole genome duplication. Our analysis confirms that many patterns of synteny observed between Atlantic Salmon and Oncorhynchus and Salvelinus species are also shared by members of the Coregoninae subfamily. We also show that regions known for their species-specific rediploidization history can pose challenges for synteny identification since these regions have diverged independently in each salmonid species following the salmonid-specific whole genome duplication. The European whitefish map provided here will enable future studies to understand the distribution of loci of interest, e.g., FST outliers, along the whitefish genome as well as assisting with the de novo assembly of a whitefish reference genome.
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Affiliation(s)
- Rishi De-Kayne
- Department of Fish Ecology and Evolution, Centre of Ecology, Evolution and Biogeochemistry, EAWAG Swiss Federal Institute of Aquatic Science and Technology, Switzerland
- Division of Aquatic Ecology and Evolution, Institute of Ecology and Evolution, University of Bern, Switzerland
| | - Philine G D Feulner
- Department of Fish Ecology and Evolution, Centre of Ecology, Evolution and Biogeochemistry, EAWAG Swiss Federal Institute of Aquatic Science and Technology, Switzerland
- Division of Aquatic Ecology and Evolution, Institute of Ecology and Evolution, University of Bern, Switzerland
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