Ximei Li

Genome structure of cotton revealed by a genome-wide SSR genetic map constructed from a BC1 population between gossypium hirsutum and G. barbadense.

BackgroundCotton, with a large genome, is an important crop throughout the world. A high-density genetic linkage map is the prerequisite for cotton genetics and breeding. A genetic map based on simple polymerase chain reaction markers will be efficient for marker-assisted breeding in cotton, and markers from transcribed sequences have more chance to target genes related to traits. To construct a genome-wide, functional marker-based genetic linkage map in cotton, we isolated and mapped expressed sequence tag-simple sequence repeats (EST-SSRs) from cotton ESTs derived from the A1, D5, (AD)1, and (AD)2 genome.ResultsA total of 3177 new EST-SSRs developed in our laboratory and other newly released SSRs were used to enrich our interspecific BC1 genetic linkage map. A total of 547 loci and 911 loci were obtained from our EST-SSRs and the newly released SSRs, respectively. The 1458 loci together with our previously published data were used to construct an updated genetic linkage map. The final map included 2316 loci on the 26 cotton chromosomes, 4418.9 cM in total length and 1.91 cM in average distance between adjacent markers. To our knowledge, this map is one of the three most dense linkage maps in cotton. Twenty-one segregation distortion regions (SDRs) were found in this map; three segregation distorted chromosomes, Chr02, Chr16, and Chr18, were identified with 99.9% of distorted markers segregating toward the heterozygous allele. Functional analysis of SSR sequences showed that 1633 loci of this map (70.6%) were transcribed loci and 1332 loci (57.5%) were translated loci.ConclusionsThis map lays groundwork for further genetic analyses of important quantitative traits, marker-assisted selection, and genome organization architecture in cotton as well as for comparative genomics between cotton and other species. The segregation distorted chromosomes can be a guide to identify segregation distortion loci in cotton. The annotation of SSR sequences identified frequent and rare gene ontology items on each chromosome, which is helpful to discover functions of cotton chromosomes.

QTL Mapping for Fiber and Yield Traits in Upland Cotton under Multiple Environments.

A population of 178 recombinant inbred lines (RILs) was developed using a single seed descendant from a cross between G. hirsutum. acc DH962 and G. hirsutum. cv Jimian5, was used to construct a genetic map and to map QTL for fiber and yield traits. A total of 644 polymorphic loci were used to construct a final genetic map, containing 616 loci and spanning 2016.44 cM, with an average of 3.27 cM between adjacent markers. Statistical analysis revealed that segregation distortion in the intraspecific population was more serious than that in the interspecific population. The RIL population and the two parents were phenotyped under 8 environments (two locations, six years), revealing a total of 134 QTL, including 64 for fiber qualities and 70 for yield components, independently detected in seven environments, explaining 4.40–15.28% of phenotypic variation (PV). Among the 134 QTL, 9 common QTL were detected in more than one environment, and 22 QTL and 19 new QTL were detected in combined analysis (E9). A total of 26 QTL hotspot regions were observed on 13 chromosomes and 2 larger linkage groups, and some QTL clusters related to fiber qualities or yield components were also observed. The results obtained in the present study suggested that to map accurate QTL in crops with larger plant types, such as cotton, phenotyping under multiple environments is necessary to effectively apply the obtained results in molecular marker-assisted selection breeding and QTL cloning.

Genetic Mapping and Characteristics of Genes Specifically or Preferentially Expressed during Fiber Development in Cotton

Cotton fiber is an ideal model to study cell elongation and cell wall construction in plants. During fiber development, some genes and proteins have been reported to be specifically or preferentially expressed. Mapping of them will reveal the genomic distribution of these genes, and will facilitate selection in cotton breeding. Based on previous reports, we designed 331 gene primers and 164 protein primers, and used single-strand conformation polymorphism (SSCP) to map and integrate them into our interspecific BC1 linkage map. This resulted in the mapping of 57 loci representing 51 genes or proteins on 22 chromosomes. For those three markers which were tightly linked with quantitative trait loci (QTLs), the QTL functions obtained in this study and gene functions reported in previous reports were consistent. Reverse transcription-polymerase chain reaction (RT-PCR) analysis of 52 polymorphic functional primers showed that 21 gene primers and 17 protein primers had differential expression between Emian22 (Gossypium hirsutum) and 3–79 (G. barbadense). Both RT-PCR and quantitative real-time PCR (qRT-PCR) analyses of the three markers tightly linked with QTLs were consistent with QTL analysis and field experiments. Gene Ontology (GO) categorization revealed that almost all 51 mapped genes belonged to multiple categories that contribute to fiber development, indicating that fiber development is a complex process regulated by various genes. These 51 genes were all specifically or preferentially expressed during fiber cell elongation and secondary wall biosynthesis. Therefore, these functional gene-related markers would be beneficial for the genetic improvement of cotton fiber length and strength.

Development of EST-based SNP and InDel markers and their utilization in tetraploid cotton genetic mapping

BackgroundAvailability of molecular markers has proven to be an efficient tool in facilitating progress in plant breeding, which is particularly important in the case of less researched crops such as cotton. Considering the obvious advantages of single nucleotide polymorphisms (SNPs) and insertion-deletion polymorphisms (InDels), expressed sequence tags (ESTs) were analyzed in silico to identify SNPs and InDels in this study, aiming to develop more molecular markers in cotton.ResultsA total of 1,349 EST-based SNP and InDel markers were developed by comparing ESTs between Gossypium hirsutum and G. barbadense, mining G. hirsutum unigenes, and analyzing 3′ untranslated region (3′UTR) sequences. The marker polymorphisms were investigated using the two parents of the mapping population based on the single-strand conformation polymorphism (SSCP) analysis. Of all the markers, 137 (10.16%) were polymorphic, and revealed 142 loci. Linkage analysis using a BC1 population mapped 133 loci on the 26 chromosomes. Statistical analysis of base variations in SNPs showed that base transitions accounted for 55.78% of the total base variations and gene ontology indicated that cotton genes varied greatly in harboring SNPs ranging from 1.00 to 24.00 SNPs per gene. Sanger sequencing of three randomly selected SNP markers revealed discrepancy between the in silico predicted sequences and the actual sequencing results.ConclusionsIn silico analysis is a double-edged blade to develop EST-SNP/InDel markers. On the one hand, the designed markers can be well used in tetraploid cotton genetic mapping. And it plays a certain role in revealing transition preference and SNP frequency of cotton genes. On the other hand, the developmental efficiency of markers and polymorphism of designed primers are comparatively low.

Structure, evolution, and comparative genomics of tetraploid cotton based on a high-density genetic linkage map

A high-density linkage map was constructed using 1,885 newly obtained loci and 3,747 previously published loci, which included 5,152 loci with 4696.03 cM in total length and 0.91 cM in mean distance. Homology analysis in the cotton genome further confirmed the 13 expected homologous chromosome pairs and revealed an obvious inversion on Chr10 or Chr20 and repeated inversions on Chr07 or Chr16. In addition, two reciprocal translocations between Chr02 and Chr03 and between Chr04 and Chr05 were confirmed. Comparative genomics between the tetraploid cotton and the diploid cottons showed that no major structural changes exist between DT and D chromosomes but rather between AT and A chromosomes. Blast analysis between the tetraploid cotton genome and the mixed genome of two diploid cottons showed that most AD chromosomes, regardless of whether it is from the AT or DT genome, preferentially matched with the corresponding homologous chromosome in the diploid A genome, and then the corresponding homologous chromosome in the diploid D genome, indicating that the diploid D genome underwent converted evolution by the diploid A genome to form the DT genome during polyploidization. In addition, the results reflected that a series of chromosomal translocations occurred among Chr01/Chr15, Chr02/Chr14, Chr03/Chr17, Chr04/Chr22, and Chr05/Chr19.

Development and Evaluation of Intron and Insertion–Deletion Markers for Gossypium barbadense

A total of 588 Gossypium barbadense coding sequences (CDSs) from nucleotide databases were selected for marker development. After selection, 125 CDSs were used to design 126 markers, including 39 intron polymorphisms (GbIPs) and 87 insertion–deletion polymorphisms (GbIDPs). These markers were evaluated by analyzing the genetic diversity of 66 tetraploid cotton accessions including 56 G. barbadense accessions and 10 Gossypium hirsutum accessions. The amplification efficiencies of the GbIPs and GbIDPs were 0.560 and 0.489 for polymorphism information content, 0.744 and 0.690 for effective multiplex ratio (E), 0.653 and 0.438 for qualitative of nature of data, and 0.272 and 0.148 for effective marker index. Principal coordinate analysis showed profound differences between G. hirsutum and G. barbadense accessions. In addition, most of the G. barbadense accessions of Xinjiang, China were clearly different from foreign and other Chinese G. barbadense accessions. The 126 markers were also evaluated for their ability to enrich genetic maps, and 16 polymorphic loci were mapped on nine chromosomes with six loci on A subgenome and 10 loci on D subgenome. The mapping efficiencies of GbIPs and GbIDPs primers were 15.38% and 11.49%, respectively. This study well proves that GbIPs and GbIDPs can be successfully applied to the analysis of genetic diversity and construction of genetic maps.

Mining, genetic mapping and expression analysis of EST-derived resistance gene homologs (RGHs) in cotton

BackgroundCotton is the dominant textile crop and also serves as an important oil crop. An estimated 15% economic loss associated with cotton production in China has been caused by diseases, and no resistance genes have been cloned in this crop. Molecular markers developed from resistance gene homologues (RGHs) might be tightly linked with target genes and could be used for marker-assisted selection (MAS) or gene cloning.ResultsTo genetically map expressed RGHs, 100 potential pathogenesis-related proteins (PRPs) and 215 resistance gene analogs (RGAs) were identified in the cotton expressed sequence tag database, and 347 specific primers were developed. Meanwhile, 61 cotton genome-derived RGA markers and 24 resistance gene analog polymorphism (RGAP) markers from published papers were included to view their genomic distribution. As a result, 38 EST-derived and 17 genome-derived RGH markers were added to our interspecific genetic map. These 55 markers were distributed on 18 of the 26 cotton chromosomes, with 34 markers on 6 chromosomes (Chr03, Chr04, Chr11, Chr17, Chr19 and Chr26). Homologous RGHs tended to be clustered; RGH clusters appeared on 9 chromosomes, with larger clusters on Chr03, Chr04 and Chr19, which suggests that RGH clusters are widely distributed in the cotton genome. Expression analysis showed that 19 RGHs were significantly altered after inoculation with the V991 stain of Verticillium dahliae. Comparative mapping showed that four RGH markers were linked with mapped loci for Verticillium wilt resistance.ConclusionsThe genetic mapping of RGHs confirmed their clustering in cotton genome. Expression analysis and comparative mapping suggest that EST-derived RGHs participate in cotton resistance. RGH markers are seemed to be useful tools to detected resistance loci and identify candidate resistance genes in cotton.

Genome-Wide Identification of Genes Responsive to ABA and Cold/Salt Stresses in Gossypium hirsutum by Data-Mining and Expression Pattern Analysis

Abstract For making better use of nucleic acid resources of Gossypium hirsutum , a data-mining method was used to identify putative genes responsive to various abiotic stresses in G. hirsutum . Based on the compiled database including genes involved in abiotic stress response in Arabidopsis thaliana and the comprehensive analysis tool of GENEVESTIGATOR v3, 826 genes up-regulated or down-regulated significantly in roots or leaves during salt or cold treatment in Arabidopsis were identified. As compared to these 826 Arabidopsis genes annotated, 38 homologous expressed sequence tags (ESTs) from G. hirsutum were selected randomly and their expression patterns were studied using a quantitative real-time reverse transcription-polymerase chain reaction method. Among these 38 ESTs, about 55% of the genes (21 of 38) were different in response to ABA between cotton and Arabidopsis , whereas >70% of genes had similar responses to cold and salt treatments, and some of them which had not been characterized in Arabidopsis are now being investigated in gene function studies. According to these results, this approach of analyzing ESTs appears effective in large-scale identification of cotton genes involved in abiotic stress and might be adopted to determine gene functions in various biologic processes in cotton.

Genome-wide recombination rate variation in a recombination map of cotton

Recombination is crucial for genetic evolution, which not only provides new allele combinations but also influences the biological evolution and efficacy of natural selection. However, recombination variation is not well understood outside of the complex species’ genomes, and it is particularly unclear in Gossypium. Cotton is the most important natural fibre crop and the second largest oil-seed crop. Here, we found that the genetic and physical maps distances did not have a simple linear relationship. Recombination rates were unevenly distributed throughout the cotton genome, which showed marked changes along the chromosome lengths and recombination was completely suppressed in the centromeric regions. Recombination rates significantly varied between A-subgenome (At) (range = 1.60 to 3.26 centimorgan/megabase [cM/Mb]) and D-subgenome (Dt) (range = 2.17 to 4.97 cM/Mb), which explained why the genetic maps of At and Dt are similar but the physical map of Dt is only half that of At. The translocation regions between A02 and A03 and between A04 and A05, and the inversion regions on A10, D10, A07 and D07 indicated relatively high recombination rates in the distal regions of the chromosomes. Recombination rates were positively correlated with the densities of genes, markers and the distance from the centromere, and negatively correlated with transposable elements (TEs). The gene ontology (GO) categories showed that genes in high recombination regions may tend to response to environmental stimuli, and genes in low recombination regions are related to mitosis and meiosis, which suggested that they may provide the primary driving force in adaptive evolution and assure the stability of basic cell cycle in a rapidly changing environment. Global knowledge of recombination rates will facilitate genetics and breeding in cotton.

Genetic mapping and comparative expression analysis of transcription factors in cotton.

Transcription factors (TFs) play an important role in the regulation of plant growth and development. The study of the structure and function of TFs represents a research frontier in plant molecular biology. The findings of these studies will provide significant information regarding genetic improvement traits in crops. Currently, a large number of TFs have been cloned, and their function has been verified. However, relatively few studies that genetically map TFs in cotton are available. To genetically map TFs in cotton in this study, specific primers were designed for TF genes that were published in the Plant Transcription Factor Database. A total of 977 TF primers were obtained, and 31 TF polymorphic loci were mapped on 15 cotton chromosomes. These polymorphic loci were clearly preferentially distributed on chromosomes 5, 11, 19 and 20; and TFs from the same family mapped to homologous cotton chromosomes. In-silico mapping verified that many mapped TFs were mapped on their corresponding chromosomes or their homologous chromosomes’ corresponding chromosomes in the diploid genomes. QTL mapping for fiber quality revealed that TF-Ghi005602-2 mapped on Chr19 was associated with fiber length. Eighty-five TF genes were selected for RT-PCR analysis, and 4 TFs were selected for qRT-PCR analysis, revealing unique expression patterns across different stages of fiber development between the mapping parents. Our data offer an overview of the chromosomal distribution of TFs in cotton, and the comparative expression analysis between Gossypium hirsutum and G. barbadense provides a rough understanding of the regulation of TFs during cotton fiber development.