Abstract
BackgroundAmong SNP markers that become increasingly valuable in molecular breeding of crop plants are the CAPS and dCAPS markers derived from the genes of interest. To date, the number of such gene-based markers is small in polyploid crop plants such as allotetraploid cotton that has A- and D-sub-genomes. The objective of this study was to develop and map new CAPS and dCAPS markers for cotton developmental-regulatory genes that are important in plant breeding programs.Results Gossypium hirsutum and G. barbadense, are the two cultivated allotetraploid cotton species. These have distinct fiber quality and other agronomic traits. Using comparative sequence analysis of characterized GSTs of the PHYA1, PHYB, and HY5 genes of G. hirsutum and G. barbadense one PHYA1-specific Mbo I/Dpn II CAPS, one PHYB-specific Alu I dCAPS, and one HY5-specific Hinf I dCAPS cotton markers were developed. These markers have successfully differentiated the two allotetraploid genomes (AD1 and AD2) when tested in parental genotypes of ‘Texas Marker-1’ (‘TM-1’), ‘Pima 3–79’ and their F1 hybrids. The genetic mapping and chromosome substitution line-based deletion analyses revealed that PHYA1 gene is located in A-sub-genome chromosome 11, PHYB gene is in A-sub-genome chromosome 10, and HY5 gene is in D-sub-genome chromosome 24, on the reference ‘TM-1’ x ‘Pima 3–79’ RIL genetic map. Further, it was found that genetic linkage map regions containing phytochrome and HY5-specific markers were associated with major fiber quality and flowering time traits in previously published QTL mapping studies.ConclusionThis study detailed the genome mapping of three cotton phytochrome genes with newly developed CAPS and dCAPS markers. The proximity of these loci to fiber quality and other cotton QTL was demonstrated in two A-subgenome and one D-subgenome chromosomes. These candidate gene markers will be valuable for marker-assisted selection (MAS) programs to rapidly introgress G. barbadense phytochromes and/or HY5 gene (s) into G. hirsutum cotton genotypes or vice versa.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0448-4) contains supplementary material, which is available to authorized users.
Highlights
Among Single nucleotide polymorphism (SNP) markers that become increasingly valuable in molecular breeding of crop plants are the cleaved amplified polymorphic sequences (CAPS) and dCAPS markers derived from the genes of interest
Gene-specific CAPS and dCAPS marker development Previously, one PHYA1 gene specific Bbv I CAPS marker targeting the 213 bp hinge region of cotton PHYA1 genes and detecting a G to A transition, was developed and validated in an interspecific mapping population that was segregating for fiber length [35]
The 2.1 kb cotton PHYB Genome sequence tag (GST) of cotton corresponding to the part of first exon, first intron and part of the second exon of PHYB genes (PHYB1 and PHYB2) were already characterized [46], and these GSTs were searched to find suitable Genome-specific polymorphism (GSP) for marker development
Summary
Among SNP markers that become increasingly valuable in molecular breeding of crop plants are the CAPS and dCAPS markers derived from the genes of interest. The objective of this study was to develop and map new CAPS and dCAPS markers for cotton developmental-regulatory genes that are important in plant breeding programs. Single nucleotide polymorphisms (SNPs) and small insertion/deletion (indel) polymorphisms are widely-used molecular marker systems in plants [1]. A SNP can be detected and utilized through different methods that include, but are not limited to, enzymatic and chemical mismatch assays, allele-specific PCR (ASP), nucleotide-amplified polymorphisms (SNAP), ligase chain reaction, single stranded confirmation polymorphism analysis (SSCP), di-deoxy fingerprinting, cleaved amplified polymorphic sequences (CAPS) and derived-CAPS [2, 4,5,6], and genotyping by sequencing (GBS) using generation sequencing technology [7]. Each method has particular advantages and disadvantages, and the use of particular SNP detection methods depends on many factors including prior expertise and the availability of the suitable platform and equipment [2]
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