@article{XUE2023, 
author = {YaPeng XUE and YiBing DING and YuZhuo WANG and XiaoDan WANG and XiaoNing CAO and Dipak K SANTRA and Ling CHEN and ZhiJun QIAO and RuiYun WANG},
title = {Construction of DNA Molecular Identity Card of Core Germplasm of Broomcorn Millet in China Based on Fluorescence SSR},
year = {2023},
journal = {Scientia Agricultura Sinica},
volume = {56},
number = {12},
pages = {2249-2261},
keywords = {broomcorn millet, capillary electrophoresis, fluorescent SSR, DNA molecular identification},
url = {https://www.sciopen.com/article/10.3864/j.issn.0578-1752.2023.12.002},
doi = {10.3864/j.issn.0578-1752.2023.12.002},
abstract = {【Objective】As an ancient minor grain crop, broomcorn millet ( Panicum miliaceum L. ) is abundant in germplasm. The construction of their DNA molecular identity based on fluorescent SSR markers would provide theoretical basis and molecular detection tool for digital management of resources.【Method】Two hundred and thirty five broomcorn millet core accessions from China were used as experimental material, polymerase chain reaction were conducted several times using the broomcorn millet specific SSR markers which developed previously by the Broomcorn Millet Crop Molecular Breeding Research Group of the Agronomy College in Shanxi Agricultural University, core markers were obtained. With the given reference genome information of broomcorn millet, the core markers were mapped on chromosomes through BLAST sequence alignment. Fluorescence (FAM/HEX) was labeled on the 5' end of the SSR primer, the genotype of the material was given by capillary electrophoresis. Using binary coding means of expression, “0, 1” was written representing the presence or absence of amplified bands, and the discrimination of the material was detected by the software ID Analysis 4.0. Decimal (0-9) coding methods were used to calculate the size of the amplified fragments so as to obtain the character string molecular identity card of the accession. Genetic diversity, genetic clustering and principal component analysis were performed using the softwares Popgene, Powermarker, MEGA and NTSYS. The two-dimensional code DNA molecular identity card of the accession was given using the two-dimensional code online software (https://cli.im/).【Result】PCR amplification results showed that all the 235 accessions could be separated by 7 fluorescent SSR markers (RYW3, RYW6, RYW11, RYW18, RYW37, RYW43 and RYW125) combined together. BLAST results showed that RYW18 and RYW37 were distributed on Chromosome 2, located at 0.60 cM and 0.80 cM, respectively. RYW125 is located on Chromosome 4 at 10.40 cM. RYW43 and RYW6 were distributed on Chromosome 5, located at 52.80 cM and 53.00 cM, respectively. RYW11 and RYW3 were located on Chromosome 6 at 2.10 cM and 20.70 cM, respectively. Genetic diversity analysis showed that 87 alleles were detected at 7 loci among all accessions, 3 (RYW11)-25 (RYW6) alleles were detected at each locus, with an average of 12.4286. Shannon diversity index (I) was detected and ranged from 0.2055 (RYW18) to 2.0587 (RYW6), with an average of 1.1398. The observed heterozygosity (Ho) was 0.0086 (RYW11)-0.9455 (RYW18). The expected observed heterozygosity (He) was 0.0795 (RYW18)-0.7469 (RYW11). Nei’s gene diversity index (Nei) was 0.0793 (RYW18)-0.7452 (RYW6). The polymorphism information content (PIC) was 0.0334 (RYW11)-0.8071 (RYW6), with an average of 0.5185. The results of cluster analysis and principal component analysis showed that 235 accessions were classified into 8 groups. The electrophoretic bands were number coding, and 7 marker combinations were used to construct the character string and two-dimensional code DNA molecular ID of all the accessions.【Conclusion】Two hundred and thirty five broomcorn millet core germplasms from China were used as material, polymerase chain reaction and capillary electrophoresis were conducted, 7 core SSR markers were screened. With the given reference genome information of broomcorn millet, the above markers were mapped on 4 chromosomes. Used the above SSR markers, genetic diversity analysis of all accessions was conducted and genetic diversity parameters were obtained. Based on Cluster analysis, all accessions were classified into 8 groups. Principal component analysis result resolved the deviation occured in Cluster analysis. According to the principle of most accessions were tell apart using the least markers, decimal (0-9) coding methods were used to calculate the size of the amplified fragments so as to obtain the character string molecular identity card of the accession. Combined the phenotype data with the above character string, two-dimensional code DNA molecular ID of all the accessions were developed.}
}