cDNA-AFLP-based genetical genomics in cotton fibers

Differential transcript profiling alters regulatory gene expression during the development of Gossypium arboreum, G.stocksii and somatic hybrids

Polyploidy or genome doubling (i.e., the presence of two or more diploid parental genome sets within an organism) are very important in higher plants. Of particular interest are the mechanisms in the new microenvironment of the common nucleus, where doubled regulatory networks interact to generate a viable genetic system capable of regulating growth, development and responses to the environment. To determine the effects of whole genome merging and doubling on the global gene expression architecture of a new polyploid, derived from protoplast fusion of the A₁A₁ genome of Gossypium arboreum and the E₁E₁ genome of Gossypium stocksii, we monitored gene expression through cDNA-AFLP in the somatic hybrids (G. arboreum + G. stocksii). The genomic expression patterns of the somatic hybrids revealed that changes in expression levels mainly involved regulatory genes (31.8% of the gene expression profiles), and the AA and EE genomes contributed equally to genome-wide expression in the newly formed AAEE genome from additivity and dominance effects. These results provide a novel perspective on polyploid gene regulation and hint at the underlying genetic basis of allopolyploid adaption in the new microenvironmental nucleus.

Systems genetics reveals a transcriptional network associated with susceptibility in the maize-grey leaf spot pathosystem

We used a systems genetics approach to elucidate the molecular mechanisms of the responses of maize to grey leaf spot (GLS) disease caused by Cercospora zeina, a threat to maize production globally. Expression analysis of earleaf samples in a subtropical maize recombinant inbred line population (CML444 × SC Malawi) subjected in the field to C. zeina infection allowed detection of 20 206 expression quantitative trait loci (eQTLs). Four trans-eQTL hotspots coincided with GLS disease QTLs mapped in the same field experiment. Co-expression network analysis identified three expression modules correlated with GLS disease scores. The module (GY-s) most highly correlated with susceptibility (r = 0.71; 179 genes) was enriched for the glyoxylate pathway, lipid metabolism, diterpenoid biosynthesis and responses to pathogen molecules such as chitin. The GY-s module was enriched for genes with trans-eQTLs in hotspots on chromosomes 9 and 10, which also coincided with phenotypic QTLs for susceptibility to GLS. This transcriptional network has significant overlap with the GLS susceptibility response of maize line B73, and may reflect pathogen manipulation for nutrient acquisition and/or unsuccessful defence responses, such as kauralexin production by the diterpenoid biosynthesis pathway. The co-expression module that correlated best with resistance (TQ-r; 1498 genes) was enriched for genes with trans-eQTLs in hotspots coinciding with GLS resistance QTLs on chromosome 9. Jasmonate responses were implicated in resistance to GLS through co-expression of COI1 and enrichment of genes with the Gene Ontology term 'cullin-RING ubiquitin ligase complex' in the TQ-r module. Consistent with this, JAZ repressor expression was highly correlated with the severity of GLS disease in the GY-s susceptibility network.

Construction of an EST-SSR-based interspecific transcriptome linkage map of fibre development in cotton

Quantitative trait locus (QTL) mapping is an important method in marker-assisted selection breeding. Many studies on the QTLs focus on cotton fibre yield and quality; however, most are conducted at the DNA level, which may reveal null QTLs. Hence, QTL mapping based on transcriptome maps at the cDNA level is often more reliable. In this study, an interspecific transcriptome map of allotetraploid cotton was developed based on an F2 population (Emian22 x 3-79) by amplifying cDNA using EST-SSRs. The map was constructed using cDNA obtained from developing fibres at five days post anthesis (DPA). A total of 1270 EST-SSRs were screened for polymorphisms between the mapping parents. The resulting transcriptome linkage map contained 242 markers that were distributed in 32 linkage groups (26 chromosomes). The full length of this map is 1938.72 cM with a mean marker distance of 8.01 cM. The functions of some ESTs have been annotated by exploring homologous sequences. Some markers were related to the differentiation and elongation of cotton fibre, while most were related to the basic metabolism. This study demonstrates that constructing a transcriptome linkage map by amplifying cDNAs using EST-SSRs is a simple and practical method as well as a powerful tool to map eQTLs for fibre quality and other traits in cotton.

A negative MYB regulator of proanthocyanidin accumulation, identified through expression quantitative locus mapping in the grape berry

Flavonoids are secondary metabolites with multiple functions. In grape (Vitis vinifera), the most abundant flavonoids are proanthocyanidins (PAs), major quality determinants for fruit and wine. However, knowledge about the regulation of PA composition is sparse. Thus, we aimed to identify novel genomic regions involved in this mechanism. Expression quantitative trait locus (eQTL) mapping was performed on the transcript abundance of five downstream PA synthesis genes (dihydroflavonol reductase (VvDFR), leucoanthocyanidin dioxygenase (VvLDOX), leucoanthocyanidin reductase (VvLAR1), VvLAR2 and anthocyanidin reductase (VvANR)) measured by real-time quantitative PCR on a pseudo F1 population in two growing seasons. Twenty-one eQTLs were identified; 17 of them did not overlap with known candidate transcription factors or cis-regulatory sequences. These novel loci and the presence of digenic epistasis support the previous hypothesis of a polygenic regulatory mechanism for PA biosynthesis. In a genomic region co-locating eQTLs for VvDFR, VvLDOX and VvLAR1, gene annotation and a transcriptomic survey suggested that VvMYBC2-L1, a gene coding for an R2R3-MYB protein, is involved in regulating PA synthesis. Phylogenetic analysis showed its high similarity to characterized negative MYB factors. Its spatiotemporal expression profile in grape coincided with PA synthesis. Its functional characterization via overexpression in grapevine hairy roots demonstrated its ability to reduce the amount of PA and to down-regulate expression of PA genes.

Integrated analysis of transcriptomic and proteomic data

Until recently, understanding the regulatory behavior of cells has been pursued through independent analysis of the transcriptome or the proteome. Based on the central dogma, it was generally assumed that there exist a direct correspondence between mRNA transcripts and generated protein expressions. However, recent studies have shown that the correlation between mRNA and Protein expressions can be low due to various factors such as different half lives and post transcription machinery. Thus, a joint analysis of the transcriptomic and proteomic data can provide useful insights that may not be deciphered from individual analysis of mRNA or protein expressions. This article reviews the existing major approaches for joint analysis of transcriptomic and proteomic data. We categorize the different approaches into eight main categories based on the initial algorithm and final analysis goal. We further present analogies with other domains and discuss the existing research problems in this area.

Cotton fiber cell walls of Gossypium hirsutum and Gossypium barbadense have differences related to loosely-bound xyloglucan

Cotton fiber is an important natural textile fiber due to its exceptional length and thickness. These properties arise largely through primary and secondary cell wall synthesis. The cotton fiber of commerce is a cellulosic secondary wall surrounded by a thin cuticulated primary wall, but there were only sparse details available about the polysaccharides in the fiber cell wall of any cotton species. In addition, Gossypium hirsutum (Gh) fiber was known to have an adhesive cotton fiber middle lamella (CFML) that joins adjacent fibers into tissue-like bundles, but it was unknown whether a CFML existed in other commercially important cotton fibers. We compared the cell wall chemistry over the time course of fiber development in Gh and Gossypium barbadense (Gb), the two most important commercial cotton species, when plants were grown in parallel in a highly controlled greenhouse. Under these growing conditions, the rate of early fiber elongation and the time of onset of secondary wall deposition were similar in fibers of the two species, but as expected the Gb fiber had a prolonged elongation period and developed higher quality compared to Gh fiber. The Gb fibers had a CFML, but it was not directly required for fiber elongation because Gb fiber continued to elongate rapidly after CFML hydrolysis. For both species, fiber at seven ages was extracted with four increasingly strong solvents, followed by analysis of cell wall matrix polysaccharide epitopes using antibody-based Glycome Profiling. Together with immunohistochemistry of fiber cross-sections, the data show that the CFML of Gb fiber contained lower levels of xyloglucan compared to Gh fiber. Xyloglucan endo-hydrolase activity was also higher in Gb fiber. In general, the data provide a rich picture of the similarities and differences in the cell wall structure of the two most important commercial cotton species.

Deep sequencing reveals differences in the transcriptional landscapes of fibers from two cultivated species of cotton

Cotton (Gossypium) fiber is the most prevalent natural product used in the textile industry. The two major cultivated species, G. hirsutum (Gh) and G. barbadense (Gb), are allotetraploids with contrasting fiber quality properties. To better understand the molecular basis for their fiber differences, EST pyrosequencing was used to document the fiber transcriptomes at two key development stages, 10 days post anthesis (dpa), representing the peak of fiber elongation, and 22 dpa, representing the transition to secondary cell wall synthesis. The 617,000 high quality reads (89% of the total 692,000 reads) from 4 libraries were assembled into 46,072 unigenes, comprising 38,297 contigs and 7,775 singletons. Functional annotation of the unigenes together with comparative digital gene expression (DGE) revealed a diverse set of functions and processes that were partly linked to specific fiber stages. Globally, 2,770 contigs (7%) showed differential expression (>2-fold) between 10 and 22 dpa (irrespective of genotype), with 70% more highly expressed at 10 dpa, while 2,248 (6%) were differentially expressed between the genotypes (irrespective of stage). The most significant genes with differential DGE at 10 dpa included expansins and lipid transfer proteins (higher in Gb), while at 22 dpa tubulins, cellulose, and sucrose synthases showed higher expression in Gb. DGE was compared with expression data of 10 dpa-old fibers from Affymetrix microarrays. Among 543 contigs showing differential expression on both platforms, 74% were consistent in being either over-expressed in Gh (242 genes) or in Gb (161 genes). Furthermore, the unigene set served to identify 339 new SSRs and close to 21,000 inter-genotypic SNPs. Subsets of 88 SSRs and 48 SNPs were validated through mapping and added 65 new loci to a RIL genetic map. The new set of fiber ESTs and the gene-based markers complement existing available resources useful in basic and applied research for crop improvement in cotton.

A high density consensus genetic map of tetraploid cotton that integrates multiple component maps through molecular marker redundancy check

A consensus genetic map of tetraploid cotton was constructed using six high-density maps and after the integration of a sequence-based marker redundancy check. Public cotton SSR libraries (17,343 markers) were curated for sequence redundancy using 90% as a similarity cutoff. As a result, 20% of the markers (3,410) could be considered as redundant with some other markers. The marker redundancy information had been a crucial part of the map integration process, in which the six most informative interspecific Gossypium hirsutum×G. barbadense genetic maps were used for assembling a high density consensus (HDC) map for tetraploid cotton. With redundant markers being removed, the HDC map could be constructed thanks to the sufficient number of collinear non-redundant markers in common between the component maps. The HDC map consists of 8,254 loci, originating from 6,669 markers, and spans 4,070 cM, with an average of 2 loci per cM. The HDC map presents a high rate of locus duplications, as 1,292 markers among the 6,669 were mapped in more than one locus. Two thirds of the duplications are bridging homoeologous A(T) and D(T) chromosomes constitutive of allopolyploid cotton genome, with an average of 64 duplications per A(T)/D(T) chromosome pair. Sequences of 4,744 mapped markers were used for a mutual blast alignment (BBMH) with the 13 major scaffolds of the recently released Gossypium raimondii genome indicating high level of homology between the diploid D genome and the tetraploid cotton genetic map, with only a few minor possible structural rearrangements. Overall, the HDC map will serve as a valuable resource for trait QTL comparative mapping, map-based cloning of important genes, and better understanding of the genome structure and evolution of tetraploid cotton.

Genomes for jeans: cotton genomics for engineering superior fiber

Twenty years ago, scientists predicted that better understanding of fiber development would lead to novel ways to engineer superior cotton fiber. Advances in genetic resources, DNA markers, DNA sequence information, and gene expression data have indeed provided new insights into fiber initiation, elongation and maturation. Many exciting applications of this knowledge offer the potential to select better cotton genotypes more effectively in mainstream breeding programs or engineer genotypes with improved agronomic and/or quality traits. Here, we discuss recent progress in understanding genes involved in fiber development, and their regulation and manipulation to engineer improved fibers. Better understanding of quantitative trait loci/gene interactions that influence fiber quality and yield may help to tailor superior cotton genotypes to diverse environments.