SummaryA single radish nuclear gene, Rfo, restores Ogura (ogu) cytoplasmic male sterility (CMS) in Brassica napus. A map-based cloning approach relying on synteny between radish and Arabidopsis was used to clone Rfo. A radish gene encoding a 687-amino-acid protein with a predicted mitochondrial targeting pre-sequence was found to confer male fertility upon transformation into ogu CMS B. napus. This gene, like the recently described Petunia Rf gene, codes for a pentatricopeptide repeat (PPR)-containing protein with multiple, in this case 16, PPR domains. Two similar genes that do not appear to function as Rfo flank this gene.Comparison of the Rfo region with the syntenic Arabidopsis region indicates that a PPR gene is not present at the Rfo-equivalent site in Arabidopsis, although a smaller and related PPR gene is found about 40 kb from this site. The implications of these findings for the evolution of restorer genes and other PPR encoding genes are discussed.

The capacity of conventional breeding to simultaneously improve the yield and quality of cotton fiber is limited. The accumulation of the plant hormone indole-3-acetic acid (IAA) in cotton fiber initials prompted us to investigate the effects of genetically engineering increased IAA levels in the ovule epidermis. Targeted expression of the IAA biosynthetic gene iaaM, driven by the promoter of the petunia MADS box gene Floral Binding protein 7 (FBP7), increased IAA levels in the epidermis of cotton ovules at the fiber initiation stage. This substantially increased the number of lint fibers, an effect that was confirmed in a 4-year field trial. The lint percentage of the transgenic cotton, an important component of fiber yield, was consistently higher in our transgenic plants than in nontransgenic controls, resulting in a >15% increase in lint yield. Fiber fineness was also notably improved.

BackgroundThe study of quantitative trait loci (QTL) in cotton (Gossypium spp.) is focused on traits of agricultural significance. Previous studies have identified a plethora of QTL attributed to fiber quality, disease and pest resistance, branch number, seed quality and yield and yield related traits, drought tolerance, and morphological traits. However, results among these studies differed due to the use of different genetic populations, markers and marker densities, and testing environments. Since two previous meta-QTL analyses were performed on fiber traits, a number of papers on QTL mapping of fiber quality, yield traits, morphological traits, and disease resistance have been published. To obtain a better insight into the genome-wide distribution of QTL and to identify consistent QTL for marker assisted breeding in cotton, an updated comparative QTL analysis is needed.ResultsIn this study, a total of 1,223 QTL from 42 different QTL studies in Gossypium were surveyed and mapped using Biomercator V3 based on the Gossypium consensus map from the Cotton Marker Database. A meta-analysis was first performed using manual inference and confirmed by Biomercator V3 to identify possible QTL clusters and hotspots. QTL clusters are composed of QTL of various traits which are concentrated in a specific region on a chromosome, whereas hotspots are composed of only one trait type. QTL were not evenly distributed along the cotton genome and were concentrated in specific regions on each chromosome. QTL hotspots for fiber quality traits were found in the same regions as the clusters, indicating that clusters may also form hotspots.ConclusionsPutative QTL clusters were identified via meta-analysis and will be useful for breeding programs and future studies involving Gossypium QTL. The presence of QTL clusters and hotspots indicates consensus regions across cultivated tetraploid Gossypium species, environments, and populations which contain large numbers of QTL, and in some cases multiple QTL associated with the same trait termed a hotspot. This study combines two previous meta-analysis studies and adds all other currently available QTL studies, making it the most comprehensive meta-analysis study in cotton to date.

Identification of stable quantitative trait loci (QTLs) across different environments and mapping populations is a prerequisite for marker-assisted selection (MAS) for cotton yield and fiber quality. To construct a genetic linkage map and to identify QTLs for fiber quality and yield traits, a backcross inbred line (BIL) population of 146 lines was developed from a cross between Upland cotton (Gossypium hirsutum) and Egyptian cotton (Gossypium barbadense) through two generations of backcrossing using Upland cotton as the recurrent parent followed by four generations of self pollination. The BIL population together with its two parents was tested in five environments representing three major cotton production regions in China. The genetic map spanned a total genetic distance of 2,895 cM and contained 392 polymorphic SSR loci with an average genetic distance of 7.4 cM per marker. A total of 67 QTLs including 28 for fiber quality and 39 for yield and its components were detected on 23 chromosomes, each of which explained 6.65-25.27% of the phenotypic variation. Twenty-nine QTLs were located on the At subgenome originated from a cultivated diploid cotton, while 38 were on the Dt subgenome from an ancestor that does not produce spinnable fibers. Of the eight common QTLs (12%) detected in more than two environments, two were for fiber quality traits including one for fiber strength and one for uniformity, and six for yield and its components including three for lint yield, one for seedcotton yield, one for lint percentage and one for boll weight. QTL clusters for the same traits or different traits were also identified. This research represents one of the first reports using a permanent advanced backcross inbred population of an interspecific hybrid population to identify QTLs for fiber quality and yield traits in cotton across diverse environments. It provides useful information for transferring desirable genes from G. barbadense to G. hirsutum using MAS.

Based on 1075 and 1059 QTL from intraspecific Upland and interspecific Upland × Pima populations, respectively, the identification of QTL clusters and hotspots provides a useful resource for cotton breeding. Mapping of quantitative trait loci (QTL) is a pre-requisite of marker-assisted selection for crop yield and quality. Recent meta-analysis of QTL in tetraploid cotton (Gossypium spp.) has identified regions of the genome with high concentrations of QTL for various traits called clusters and specific trait QTL called hotspots or meta-QTL (mQTL). However, the meta-analysis included all population types of Gossypium mixing both intraspecific G. hirsutum and interspecific G. hirsutum × G. barbadense populations. This study used 1,075 QTL from 58 publications on intraspecific G. hirsutum and 1,059 QTL from 30 publications on G. hirsutum × G. barbadense populations to perform a comprehensive comparative analysis of QTL clusters and hotspots between the two populations for yield, fiber and seed quality, and biotic and abiotic stress tolerance. QTL hotspots were further analyzed for mQTL within the hotspots using Biomercator V3 software. The ratio of QTL between the two population types was proportional yet differences in hotspot type and placement were observed between the two population types. However, on some chromosomes QTL clusters and hotspots were similar between the two populations. This shows that there are some universal QTL regions in the cultivated tetraploid cotton which remain consistent and some regions which differ between population types. This study for the first time elucidates the similarities and differences in QTL clusters and hotspots between intraspecific and interspecific populations, providing an important resource to cotton breeding programs in marker-assisted selection .