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Baloch FS, Altaf MT, Liaqat W, Bedir M, Nadeem MA, Cömertpay G, Çoban N, Habyarimana E, Barutçular C, Cerit I, Ludidi N, Karaköy T, Aasim M, Chung YS, Nawaz MA, Hatipoğlu R, Kökten K, Sun HJ. Recent advancements in the breeding of sorghum crop: current status and future strategies for marker-assisted breeding. Front Genet 2023; 14:1150616. [PMID: 37252661 PMCID: PMC10213934 DOI: 10.3389/fgene.2023.1150616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 04/17/2023] [Indexed: 05/31/2023] Open
Abstract
Sorghum is emerging as a model crop for functional genetics and genomics of tropical grasses with abundant uses, including food, feed, and fuel, among others. It is currently the fifth most significant primary cereal crop. Crops are subjected to various biotic and abiotic stresses, which negatively impact on agricultural production. Developing high-yielding, disease-resistant, and climate-resilient cultivars can be achieved through marker-assisted breeding. Such selection has considerably reduced the time to market new crop varieties adapted to challenging conditions. In the recent years, extensive knowledge was gained about genetic markers. We are providing an overview of current advances in sorghum breeding initiatives, with a special focus on early breeders who may not be familiar with DNA markers. Advancements in molecular plant breeding, genetics, genomics selection, and genome editing have contributed to a thorough understanding of DNA markers, provided various proofs of the genetic variety accessible in crop plants, and have substantially enhanced plant breeding technologies. Marker-assisted selection has accelerated and precised the plant breeding process, empowering plant breeders all around the world.
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Affiliation(s)
- Faheem Shehzad Baloch
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye
| | - Muhammad Tanveer Altaf
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye
| | - Waqas Liaqat
- Department of Field Crops, Faculty of Agriculture, Çukurova University, Adana, Türkiye
| | - Mehmet Bedir
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye
| | - Muhammad Azhar Nadeem
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye
| | - Gönül Cömertpay
- Eastern Mediterranean Agricultural Research Institute, Adana, Türkiye
| | - Nergiz Çoban
- Eastern Mediterranean Agricultural Research Institute, Adana, Türkiye
| | - Ephrem Habyarimana
- International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, Telangana, India
| | - Celaleddin Barutçular
- Department of Field Crops, Faculty of Agriculture, Çukurova University, Adana, Türkiye
| | - Ibrahim Cerit
- Eastern Mediterranean Agricultural Research Institute, Adana, Türkiye
| | - Ndomelele Ludidi
- Plant Stress Tolerance Laboratory, Department of Biotechnology, University of the Western Cape, Bellville, South Africa
- DSI-NRF Centre of Excellence in Food Security, University of the Western Cape, Bellville, South Africa
| | - Tolga Karaköy
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye
| | - Muhammad Aasim
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye
| | - Yong Suk Chung
- Department of Plant Resources and Environment, Jeju National University, Jeju, Republic of Korea
| | | | - Rüştü Hatipoğlu
- Kırşehir Ahi Evran Universitesi Ziraat Fakultesi Tarla Bitkileri Bolumu, Kırşehir, Türkiye
| | - Kağan Kökten
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye
| | - Hyeon-Jin Sun
- Subtropical Horticulture Research Institute, Jeju National University, Jeju, Republic of Korea
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Abstract
Pinus koraiensis is a well-known precious tree species in East Asia with high economic, ornamental and ecological value. More than fifty percent of the P. koraiensis forests in the world are distributed in northeast China, a region with abundant germplasm resources. However, these natural P. koraiensis sources are in danger of genetic erosion caused by continuous climate changes, natural disturbances such as wildfire and frequent human activity. Little work has been conducted on the population genetic structure and genetic differentiation of P. koraiensis in China because of the lack of genetic information. In this study, 480 P. koraiensis individuals from 16 natural populations were sampled and genotyped. Fifteen polymorphic expressed sequence tag-simple sequence repeat (EST-SSR) markers were used to evaluate genetic diversity, population structure and differentiation in P. koraiensis. Analysis of molecular variance (AMOVA) of the EST-SSR marker data showed that 33% of the total genetic variation was among populations and 67% was within populations. A high level of genetic diversity was found across the P. koraiensis populations, and the highest levels of genetic diversity were found in HH, ZH, LS and TL populations. Moreover, pairwise Fst values revealed significant genetic differentiation among populations (mean Fst = 0.177). According to the results of the STRUCTURE and Neighbor-joining (NJ) tree analyses and principal component analysis (PCA), the studied geographical populations cluster into two genetic clusters: cluster 1 from Xiaoxinganling Mountains and cluster 2 from Changbaishan Mountains. These results are consistent with the geographical distributions of the populations. The results provide new genetic information for future genome-wide association studies (GWAS), marker-assisted selection (MAS) and genomic selection (GS) in natural P. koraiensis breeding programs and can aid the development of conservation and management strategies for this valuable conifer species.
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Chen Z, Tang D, Ni J, Li P, Wang L, Zhou J, Li C, Lan H, Li L, Liu J. Development of genic KASP SNP markers from RNA-Seq data for map-based cloning and marker-assisted selection in maize. BMC PLANT BIOLOGY 2021; 21:157. [PMID: 33771110 PMCID: PMC8004444 DOI: 10.1186/s12870-021-02932-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/01/2021] [Accepted: 03/10/2021] [Indexed: 05/25/2023]
Abstract
BACKGROUND Maize is one of the most important field crops in the world. Most of the key agronomic traits, including yield traits and plant architecture traits, are quantitative. Fine mapping of genes/ quantitative trait loci (QTL) influencing a key trait is essential for marker-assisted selection (MAS) in maize breeding. However, the SNP markers with high density and high polymorphism are lacking, especially kompetitive allele specific PCR (KASP) SNP markers that can be used for automatic genotyping. To date, a large volume of sequencing data has been produced by the next generation sequencing technology, which provides a good pool of SNP loci for development of SNP markers. In this study, we carried out a multi-step screening method to identify kompetitive allele specific PCR (KASP) SNP markers based on the RNA-Seq data sets of 368 maize inbred lines. RESULTS A total of 2,948,985 SNPs were identified in the high-throughput RNA-Seq data sets with the average density of 1.4 SNP/kb. Of these, 71,311 KASP SNP markers (the average density of 34 KASP SNP/Mb) were developed based on the strict criteria: unique genomic region, bi-allelic, polymorphism information content (PIC) value ≥0.4, and conserved primer sequences, and were mapped on 16,161 genes. These 16,161 genes were annotated to 52 gene ontology (GO) terms, including most of primary and secondary metabolic pathways. Subsequently, the 50 KASP SNP markers with the PIC values ranging from 0.14 to 0.5 in 368 RNA-Seq data sets and with polymorphism between the maize inbred lines 1212 and B73 in in silico analysis were selected to experimentally validate the accuracy and polymorphism of SNPs, resulted in 46 SNPs (92.00%) showed polymorphism between the maize inbred lines 1212 and B73. Moreover, these 46 polymorphic SNPs were utilized to genotype the other 20 maize inbred lines, with all 46 SNPs showing polymorphism in the 20 maize inbred lines, and the PIC value of each SNP was 0.11 to 0.50 with an average of 0.35. The results suggested that the KASP SNP markers developed in this study were accurate and polymorphic. CONCLUSIONS These high-density polymorphic KASP SNP markers will be a valuable resource for map-based cloning of QTL/genes and marker-assisted selection in maize. Furthermore, the method used to develop SNP markers in maize can also be applied in other species.
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Affiliation(s)
- Zhengjie Chen
- Maize Research Institute, Sichuan Agricultural University, 211 Huiming Road, Wenjiang District, Chengdu City, 611000 Sichuan China
- Industrial Crop Research Institute, Sichuan Academy of Agricultural Science, No.159 Huajin Avanue, Qingbaijiang District, Chengdu City, 610300 Sichuan China
| | - Dengguo Tang
- Maize Research Institute, Sichuan Agricultural University, 211 Huiming Road, Wenjiang District, Chengdu City, 611000 Sichuan China
| | - Jixing Ni
- Maize Research Institute, Sichuan Agricultural University, 211 Huiming Road, Wenjiang District, Chengdu City, 611000 Sichuan China
| | - Peng Li
- Maize Research Institute, Sichuan Agricultural University, 211 Huiming Road, Wenjiang District, Chengdu City, 611000 Sichuan China
| | - Le Wang
- Maize Research Institute, Sichuan Agricultural University, 211 Huiming Road, Wenjiang District, Chengdu City, 611000 Sichuan China
| | - Jinhong Zhou
- Maize Research Institute, Sichuan Agricultural University, 211 Huiming Road, Wenjiang District, Chengdu City, 611000 Sichuan China
| | - Chenyang Li
- Maize Research Institute, Sichuan Agricultural University, 211 Huiming Road, Wenjiang District, Chengdu City, 611000 Sichuan China
| | - Hai Lan
- Maize Research Institute, Sichuan Agricultural University, 211 Huiming Road, Wenjiang District, Chengdu City, 611000 Sichuan China
| | - Lujiang Li
- Maize Research Institute, Sichuan Agricultural University, 211 Huiming Road, Wenjiang District, Chengdu City, 611000 Sichuan China
| | - Jian Liu
- Maize Research Institute, Sichuan Agricultural University, 211 Huiming Road, Wenjiang District, Chengdu City, 611000 Sichuan China
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Salgotra RK, Stewart CN. Functional Markers for Precision Plant Breeding. Int J Mol Sci 2020; 21:E4792. [PMID: 32640763 PMCID: PMC7370099 DOI: 10.3390/ijms21134792] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 06/19/2020] [Accepted: 07/02/2020] [Indexed: 01/24/2023] Open
Abstract
Advances in molecular biology including genomics, high-throughput sequencing, and genome editing enable increasingly faster and more precise cultivar development. Identifying genes and functional markers (FMs) that are highly associated with plant phenotypic variation is a grand challenge. Functional genomics approaches such as transcriptomics, targeting induced local lesions in genomes (TILLING), homologous recombinant (HR), association mapping, and allele mining are all strategies to identify FMs for breeding goals, such as agronomic traits and biotic and abiotic stress resistance. The advantage of FMs over other markers used in plant breeding is the close genomic association of an FM with a phenotype. Thereby, FMs may facilitate the direct selection of genes associated with phenotypic traits, which serves to increase selection efficiencies to develop varieties. Herein, we review the latest methods in FM development and how FMs are being used in precision breeding for agronomic and quality traits as well as in breeding for biotic and abiotic stress resistance using marker assisted selection (MAS) methods. In summary, this article describes the use of FMs in breeding for development of elite crop cultivars to enhance global food security goals.
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Affiliation(s)
- Romesh K. Salgotra
- School of Biotechnology, Sher-e-Kashmir University of Agricultural Sciences & Technology of Jammu, Chatha, Jammu 190008, India
| | - C. Neal Stewart
- Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA
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Zhu Y, Wang X, Huang L, Lin C, Zhang X, Xu W, Peng J, Li Z, Yan H, Luo F, Wang X, Yao L, Peng D. Transcriptomic Identification of Drought-Related Genes and SSR Markers in Sudan Grass Based on RNA-Seq. FRONTIERS IN PLANT SCIENCE 2017; 8:687. [PMID: 28523007 PMCID: PMC5415614 DOI: 10.3389/fpls.2017.00687] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Accepted: 04/13/2017] [Indexed: 05/24/2023]
Abstract
Sudan grass (Sorghum sudanense) is an annual warm-season gramineous forage grass that is widely used as pasture, hay, and silage. However, drought stress severely impacts its yield, and there is limited information about the mechanisms of drought tolerance in Sudan grass. In this study, we used next-generation sequencing to identify differentially expressed genes (DEGs) in the Sudan grass variety Wulate No.1, and we developed simple sequence repeat (SSR) markers associated with drought stress. From 852,543,826 raw reads, nearly 816,854,366 clean reads were identified and used for analysis. A total of 80,686 unigenes were obtained via de novo assembly of the clean reads including 45,065 unigenes (55.9%) that were identified as coding sequences (CDSs). According to Gene Ontology analysis, 31,444 unigenes were annotated, 11,778 unigenes were identified to 25 categories in the clusters of orthologous groups of proteins (KOG) classification, and 11,223 unigenes were assigned to 280 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Additionally, there were 2,329 DEGs under a short-term of 25% polyethylene glycol (PEG) treatment, while 5,101 DEGs were identified under the long-term of 25% PEG treatment. DEGs were enriched in pathways of carbon fixation in photosynthetic organisms and plant hormone signal transduction which played a leading role in short-term of drought stress. However, DEGs were mainly enriched in pathway of plant hormone signal transduction that played an important role under long-term of drought stress. To increase accuracy, we excluded all the DEGs of all controls, specifically, five DEGs that were associated with high PEG concentrations were found through RNA-Seq. All five genes were up-regulated under drought stress, but the functions of the genes remain unclear. In addition, we identified 17,548 SSRs obtained from 80,686 unigenes. The newly identified drought tolerance DEGs will contribute to transgenic breeding efforts, while SSRs developed from high-throughput transcriptome data will facilitate marker-assisted selection for all traits in Sudan grass.
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Affiliation(s)
- Yongqun Zhu
- Department of Grassland Science, Animal Science and Technology College, Sichuan Agricultural UniversityChengdu, China
- Soil and Fertilizer Research Institute, Sichuan Academy of Agricultural SciencesChengdu, China
| | - Xia Wang
- Department of Grassland Science, Animal Science and Technology College, Sichuan Agricultural UniversityChengdu, China
| | - Linkai Huang
- Department of Grassland Science, Animal Science and Technology College, Sichuan Agricultural UniversityChengdu, China
| | - Chaowen Lin
- Soil and Fertilizer Research Institute, Sichuan Academy of Agricultural SciencesChengdu, China
| | - Xinquan Zhang
- Department of Grassland Science, Animal Science and Technology College, Sichuan Agricultural UniversityChengdu, China
| | - Wenzhi Xu
- Soil and Fertilizer Research Institute, Sichuan Academy of Agricultural SciencesChengdu, China
| | - Jianhua Peng
- Sichuan Academy of Agricultural SciencesChengdu, China
| | - Zhou Li
- Department of Grassland Science, Animal Science and Technology College, Sichuan Agricultural UniversityChengdu, China
| | - Haidong Yan
- Department of Grassland Science, Animal Science and Technology College, Sichuan Agricultural UniversityChengdu, China
| | - Fuxiang Luo
- Soil and Fertilizer Research Institute, Sichuan Academy of Agricultural SciencesChengdu, China
| | - Xie Wang
- Soil and Fertilizer Research Institute, Sichuan Academy of Agricultural SciencesChengdu, China
| | - Li Yao
- Soil and Fertilizer Research Institute, Sichuan Academy of Agricultural SciencesChengdu, China
| | - Dandan Peng
- Soil and Fertilizer Research Institute, Sichuan Academy of Agricultural SciencesChengdu, China
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