Genome-Wide Mining, Characterization and Development of Microsatellite Markers in Gossypium Species

Abstract

Although much research has been conducted to characterize microsatellites and develop markers, the distribution of microsatellites remains ambiguous and the use of microsatellite markers in genomic studies and marker-assisted selection is limited. To identify microsatellites for cotton research, we mined 100,290, 83,160, and 56,937 microsatellites with frequencies of 41.2, 49.1, and 74.8 microsatellites per Mb in the recently sequenced Gossypium species: G. hirsutum, G. arboreum, and G. raimondii, respectively. The distributions of microsatellites in their genomes were non-random and were positively and negatively correlated with genes and transposable elements, respectively. Of the 77,996 developed microsatellite markers, 65,498 were physically anchored to the 26 chromosomes of G. hirsutum with an average marker density of 34 markers per Mb. We confirmed 67,880 (87%) universal and 7,705 (9.9%) new genic microsatellite markers. The polymorphism was estimated in above three species by in silico PCR and validated with 505 markers in G. hirsutum. We further predicted 8,825 polymorphic microsatellite markers within G. hirsutum acc. TM-1 and G. barbadense cv. Hai7124. In our study, genome-wide mining and characterization of microsatellites, and marker development were very useful for the saturation of the allotetraploid genetic linkage map, genome evolution studies and comparative genome mapping.

Genome-wide characterization of microsatellites in Triticeae species: abundance, distribution and evolution

“…Results showed that greater physical densities of microsatellites were found in distal chromosomal regions than in the central regions, which was similar to the previous reports in Gossypium 23293031 and Brassica crops22. Specifically, the genomic distribution of microsatellites was positively correlated with genes and negatively correlated with TEs (Fig.…”

Comparative analyses of simple sequence repeats (SSRs) in 23 mosquito species genomes: Identification, characterization and distribution (Diptera: Culicidae)

“…sativa , Sorghum bicolor , Brachypodium distachyon and Arabidopsis thaliana genomes with mono‐ to trinucleotide SSRs comprising 94.05%, 97.45%, 98.21%, 90.26%, 88.48% and 82.25% of the total, respectively (Zhao et al ., ). Nevertheless, hexanucleotide SSRs are the dominant type in 30 marine animals (comprising 33.22%, Jiang et al ., ), 10 Poaceae species (58.82%, Wang et al ., ) and three Gossypium species (39.4%, Wang et al ., ). The occurrence frequency of different types of SSRs seems characteristic of different individual species, which needs further taxonomic clarification given the increasing number of SSR investigations at the genome level.…”

Assessment of Genetic Diversity, Population Structure, and Evolutionary Relationship of Uncharacterized Genes in a Novel Germplasm Collection of Diploid and Allotetraploid Gossypium Accessions Using EST and Genomic SSR Markers

“…Among those, four are cultivated throughout the world: two of these species are diploids (2 n = 2 x = 26) and two are allotetraploids (2 n = 4 x = 52). Global cotton production is manifested from the two allotetraploid species Gossypium hirsutum and Gossypium barbadense [7,8,9]. …”

“…G ossypium hirsutum , also called “Upland cotton”, represents 90% of global cotton fiber production [13], while Gossypium barbadense (also known as Pima) is valued for its extra-long staple fiber source, is domesticated in North-West South America, has its native origin in Egypt, and contributes around 8% of total world lint [9]. Wild Gossypium darwinii originated from Galapagos Island and, relative to G. barbadense, also has good fiber fineness characteristics and is a rich source of resistance to fusarium and verticillum wilts [14].…”

“…The DNA-based markers used for determining genetic diversity in cotton include restriction fragment length polymorphisms (RFLPs) [29], random amplified polymorphic DNA (RAPD) [30,31,32], amplified fragment length polymorphisms (AFLPs) [33], simple sequence repeat (SSR) [9,34,35,36], expressed sequence tags (ESTs) [37], inter-simple sequence repeat (ISSR) [38,39], and single nucleotide polymorphisms (SNPs) [40]. Compared with other biomarkers, SSR has advantages that include more reproducibility, co-dominant inheritance, distribution throughout the genome, and its being highly transferable, informative, and reliable [41].…”