Development of SNP markers using RNA-seq technology and tetra-primer ARMS-PCR in sweetpotato

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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Machine learning, transcriptome, and genotyping chip analyses provide insights into SNP markers identifying flower color in Platycodon grandiflorus

Scientific Reports ◽

10.1038/s41598-021-87281-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Go-Eun Yu ◽

Younhee Shin ◽

Sathiyamoorthy Subramaniyam ◽

Sang-Ho Kang ◽

Si-Myung Lee ◽

...

Keyword(s):

Machine Learning ◽

Random Forest ◽

Feature Selection Method ◽

Flower Color ◽

Classification Performance ◽

Snp Markers ◽

Rna Seq ◽

Color Classification ◽

Dna Pcr ◽

Selection Of

AbstractBellflower is an edible ornamental gardening plant in Asia. For predicting the flower color in bellflower plants, a transcriptome-wide approach based on machine learning, transcriptome, and genotyping chip analyses was used to identify SNP markers. Six machine learning methods were deployed to explore the classification potential of the selected SNPs as features in two datasets, namely training (60 RNA-Seq samples) and validation (480 Fluidigm chip samples). SNP selection was performed in sequential order. Firstly, 96 SNPs were selected from the transcriptome-wide SNPs using the principal compound analysis (PCA). Then, 9 among 96 SNPs were later identified using the Random forest based feature selection method from the Fluidigm chip dataset. Among six machines, the random forest (RF) model produced higher classification performance than the other models. The 9 SNP marker candidates selected for classifying the flower color classification were verified using the genomic DNA PCR with Sanger sequencing. Our results suggest that this methodology could be used for future selection of breeding traits even though the plant accessions are highly heterogeneous.

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RNA-Seq-Mediated Transcriptome Analysis of a Fiberless Mutant Cotton and Its Possible Origin Based on SNP Markers

PLoS ONE ◽

10.1371/journal.pone.0151994 ◽

2016 ◽

Vol 11 (3) ◽

pp. e0151994 ◽

Cited By ~ 13

Author(s):

Qifeng Ma ◽

Man Wu ◽

Wenfeng Pei ◽

Xiaoyan Wang ◽

Honghong Zhai ◽

...

Keyword(s):

Transcriptome Analysis ◽

Snp Markers ◽

Rna Seq

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The five Urochola spp. used in development of tropical forage cultivars originate from defined subpopulations with differentiated gene pools

10.1101/2021.07.21.453213 ◽

2021 ◽

Author(s):

Janet Higgins ◽

Paulina Tomaszewska ◽

Till K Pellny ◽

Valheria Castiblanco ◽

Jacobo Arango ◽

...

Keyword(s):

Gene Pool ◽

Geographical Origin ◽

Snp Markers ◽

Gene Pools ◽

Rna Seq ◽

Genome Composition ◽

Ploidy Levels ◽

Centre Of Origin ◽

Tropical Forage ◽

The Tropics

Background and Aims: Urochola (syn. Brachiaria, and including some Panicum and Megathyrus) is a genus of tropical and subtropical grasses widely sown as forage to feed ruminants in the tropics. A better understanding of the diversity among Urochola spp. allow us to leverage its varying ploidy levels and genome composition to accelerate its improvement, following the example from other crop genera. Methods: We explored the genetic make-up and population structure in 111 accessions, which comprise the five Urochola species used for the development of commercial cultivars. These accessions are conserved from wild materials from collection sites at their centre of origin in Africa. We used RNA-seq, averaging 40M reads per accession, to generate 1,167,542 stringently selected SNP markers that tentatively encompassed the complete Urochola gene pool used in breeding. Key Results: We identified ten subpopulations, which had no relation with geographical origin and represented ten independent gene pools, and two groups of admixed accessions. Our results support a division in U. decumbens by ploidy, with a diploid subpopulation closely related to U. ruziziensis, and a tetraploid subpopulation closely related to U. brizantha. We observed highly differentiated gene pools in U. brizantha, which were not related with origin or ploidy. Particularly, one U. brizantha subpopulation clustered distant from the other U. brizantha and U. decumbens subpopulations, so likely containing unexplored alleles. We also identified a well-supported subpopulation containing both polyploid U. decumbens and U. brizantha accessions; this was the only group containing more than one species and tentatively constitutes an independent "mixed" gene pool for both species. We observed two gene pools in U. humidicola. One subpopulation, "humidicola-2", was much less common but likely includes the only known sexual accession in the species. Conclusions: Our results offered a definitive picture of the available diversity in Urochola to inform breeding and resolve questions raised by previous studies. It also allowed us identifying prospective founders to enrich the breeding gene pool and to develop genotyping and genotype-phenotype association mapping experiments.

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Genome-wide discovery and characterization of long noncoding RNAs in African oil palm (Elaeis guineensis Jacq.)

PeerJ ◽

10.7717/peerj.9585 ◽

2020 ◽

Vol 8 ◽

pp. e9585

Author(s):

Wei Xia ◽

Yajing Dou ◽

Rui Liu ◽

Shufang Gong ◽

Dongyi Huang ◽

...

Keyword(s):

Fatty Acid ◽

Oil Palm ◽

Target Genes ◽

De Novo ◽

Elaeis Guineensis ◽

Expression Patterns ◽

Noncoding Rnas ◽

Snp Markers ◽

Long Noncoding Rnas ◽

Rna Seq

Long noncoding RNAs (lncRNAs) are an important class of genes and play important roles in a range of biological processes. However, few reports have described the identification of lncRNAs in oil palm. In this study, we applied strand specific RNA-seq with rRNA removal to identify 1,363 lncRNAs from the equally mixed tissues of oil palm spear leaf and six different developmental stages of mesocarp (8–24 weeks). Based on strand specific RNA-seq data and 18 released oil palm transcriptomes, we systematically characterized the expression patterns of lncRNA loci and their target genes. A total of 875 uniq target genes for natural antisense lncRNAs (NAT-lncRNA, 712), long intergenic noncoding RNAs (lincRNAs, 92), intronic-lncRNAs (33), and sense-lncRNAs (52) were predicted. A majority of lncRNA loci (77.8%–89.6%) had low expression in 18 transcriptomes, while only 89 lncRNA loci had medium to high expression in at least one transcriptome. Coexpression analysis between lncRNAs and their target genes indicated that 6% of lncRNAs had expression patterns positively correlated with those of target genes. Based on single nucleotide polymorphism (SNP) markers derived from our previous research, 6,882 SNPs were detected for lncRNAs and 28 SNPs belonging to 21 lncRNAs were associated with the variation of fatty acid contents. Moreover, seven lncRNAs showed expression patterns positively correlated expression pattern with those of genes in de novo fatty acid synthesis pathways. Our study identified a collection of lncRNAs for oil palm and provided clues for further research into lncRNAs that may regulate mesocarp development and lipid metabolism.

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