BAC-End Sequence-Based SNP Mining in Allotetraploid Cotton (Gossypium) Utilizing Resequencing Data, Phylogenetic Inferences, and Perspectives for Genetic Mapping

Abstract

A bacterial artificial chromosome library and BAC-end sequences for cultivated cotton (Gossypium hirsutum L.) have recently been developed. This report presents genome-wide single nucleotide polymorphism (SNP) mining utilizing resequencing data with BAC-end sequences as a reference by alignment of 12 G. hirsutum L. lines, one G. barbadense L. line, and one G. longicalyx Hutch and Lee line. A total of 132,262 intraspecific SNPs have been developed for G. hirsutum, whereas 223,138 and 470,631 interspecific SNPs have been developed for G. barbadense and G. longicalyx, respectively. Using a set of interspecific SNPs, 11 randomly selected and 77 SNPs that are putatively associated with the homeologous chromosome pair 12 and 26, we mapped 77 SNPs into two linkage groups representing these chromosomes, spanning a total of 236.2 cM in an interspecific F2 population (G. barbadense 3-79 × G. hirsutum TM-1). The mapping results validated the approach for reliably producing large numbers of both intraspecific and interspecific SNPs aligned to BAC-ends. This will allow for future construction of high-density integrated physical and genetic maps for cotton and other complex polyploid genomes. The methods developed will allow for future Gossypium resequencing data to be automatically genotyped for identified SNPs along the BAC-end sequence reference for anchoring sequence assemblies and comparative studies.

Uncovering SNP and indel variations of tetraploid cottons by SLAF-seq

“…Similar observations were detected in rice and citrus [23, 26], which is remained to be explained as an unexpected observation. The ratio of transitions and transversions (Ts/Tv) for Gh_E22, Gb_3–79, Gt, Gm and Gd were 2.315, 2.487, 2.498, 2.516 and 2.483, respectively, which were slightly higher than G. hirsutum (2.194) and G. barbadense (2.210) of a previous report in cotton [16], IR64/Pokkali (2.340) and IR64/N22 (2.370) in rice [12], and JS-335 (1.978) and UPSM-534 (1.961) in soybean [22]. Further, AT-to-GC conversion in Gb_3–79 significantly outnumbered Gh_E22, followed in descending order by Gd, Gm and Gt (Fig.…”

“…Therefore, the discovery of polymorphisms is very important in the study of genomic variation in crop species. To date, SNP discoveries have been applied in other crops beyond cotton [16]. SNP discoveries in cotton have progressed using different methods, such as BAC-end sequences [16], single copy sequences [17], transcriptome sequencing [18], reduced representation libraries (RRL) techniques [19].…”

Genetic Diversity and Population Structure in the Landrace Accessions of Gossypium hirsutum

“…There is wide range of genetic markers available today for crop plant genotyping (Multani and Lyon, 1995; Abdalla et al, 2001; Van Becelaere et al, 2005; Rahman et al, 2008). The rapid developments in next‐generation sequencing technology and cheaper sampling costs have enabled the high‐throughput genomewide marker discovery in cotton (Hulse‐Kemp et al, 2015a). Single‐nucleotide polymorphism (SNP) arrays are now available in many crop species, which can be used to evaluate genetic diversity, for marker discovery, and for understanding the genetic bases of agronomic traits (Ganal et al, 2011; Truco et al, 2013; Wang et al, 2014b; Hulse‐Kemp et al, 2015b).…”

Genome mapping and molecular markers identification for yield, yield component and fibre quality traits in tetraploid cotton

“…The large number of SNP markers detected in different cotton species (Byers, Harker, Yourstone, Maughan, & Udall, ; Van Deynze et al, ; Gore et al, ; Hulse‐Kemp, Ashrafi, et al, ; Hulse‐Kemp et al, ; Islam, Thyssen, Jenkins, & Fang, ; Lacape et al, ; Rai et al, ; Zhu, Spriggs, Taylor, Llewellyn, & Wilson, ) have helped the cotton researchers in genome‐based identification and mapping of QTL. Till now, only a few mapping studies in cotton have been based on SNP markers (Gore et al, ; Kumar et al, ; Li et al, ; Yu et al, ; Zhang et al, ).…”