**4. QTL mapping**

on the genetic map. Eventually, we constructed a high density *B. rapa* genetic map consist‐

Genetic maps are extensively used in gene mapping, QTL mapping and assembly of whole genome sequence. High density molecular markers in genetic maps are advantageous and necessary in most applications. The detection of multiple loci in a SRAP PCR reaction can be automated through fluorescently labelled SRAP primers so it is feasible to construct a high

In *B. napus*, we used a five-color fluorescent dye set including '6-FAM', 'VIC', 'Pet', 'NED' and 'LIZ' to perform SRAP fragment analysis with the ABI genetic analyzer (Sun et al., 2007). 'LIZ' was used as the internal standard while the other four fluorescent dyes were used to label SRAP primers and combined with unlabeled primers. After obtaining SRAP products with four fluorescently labeled and four unlabeled primers, all the products from four SRAP primer combinations were pooled to increase the detection throughput by four fold. We used 1,634 SRAP primer combinations selected from 12 labeled and 442 unlabeled SRAP primers to produce 13,472 SRAP markers. Together with 79 SSR markers, we assem‐

Using cDNA-SRAP technology, we first constructed a transcriptome map based on *B. olera‐ cea* cDNAs obtained from leaf tissue (Li et al., 2003). In cDNA-SRAP, one step PCR allows the amplification of single strand cDNAs after the first strand cDNA is synthesized using reverse transcriptase. Since most cDNA-SRAP markers come from differences in gene se‐ quence, these markers are considered to be functional markers. SRAP products can be easily isolated from polyacrylamide gels for sequencing so we sequenced 190 fragments that corre‐ sponded to 190 polymorphic loci from cDNA-SRAP. Through analysis of sequence similari‐ ty, 169 out of 190 cDNA marker sequences were homologous to genes reported in Arabidopsis, which allowed the identification of extensive colinearity between the two ge‐ nomes according to the gene-for-gene alignment. Later, we developed over 1,000 SRAP markers using genomic DNA from the same mapping population and assembled these SRAP markers from both genomic DNA and cDNA samples on the same genetic map (Gao et al., 2007). In addition, we integrated 10 SCAR markers using sequences of genes with known functions in the biosynthesis of glucosinolates and inflorescence architecture, and

SRAP technology can be combined with other markers to construct genetic maps. For exam‐ ple, Yu et al., (2007) constructed a high-density genetic map in a cultivated allotetraploid cotton population using SSR, SRAP, AFLP, and target region amplification polymorphism (TRAP). This high density cotton genetic map consists of 697 SSR, 171 TRAP, 129 SRAP, 98 AFLP, and two morphological markers, covering a genetic distance of 4,536.7 cM with the average genetic distance of 4.1 cM per marker. Gulsen et al., (2010) reported a new citrus linkage map using SRAP, RAPD, SSR, ISSR, peroxidase gene polymorphism (POGP), resist‐

ing of 1,737 paired-end Solexa sequences, 9,177 SRAP markers and 46 SSR markers.

**3. Genetic map construction**

26 Plant Breeding from Laboratories to Fields

density genetic map using SRAP technology.

bled currently the most saturated genetic map in *B. napus*.

one SCAR marker flanking a resistance gene to downy mildew.

A common application of genetic maps is QTL mapping of complex traits. Since QTL are often underpinned by multiple genes in a genome, it is difficult to tag QTL using proce‐ dures for tagging Mendelian loci. In general, if a complex trait is changed into a simple Mendelian trait and the underlying QTL is Mendelized, many strategies are available to map and clone the Mendelized genes. In fact, most cloned QTL have been accomplished through such a Mendelized strategy by developing near-isogenic lines (NILs). However, most QTL are not easily Mendelized, so it is necessary to construct genetic maps first and then perform QTL mapping.

In canola, we used SRAP and SSR to construct a genetic map in a doubled haploid (DH) line population that was developed from a synthetic yellow-seeded line and a conventional can‐ ola cultivar through microspore culture (Chen et al., 2009). Data for three complex traits in‐ cluding days to flowering, oil content and seed yield at three locations for three years were collected and used in QTL mapping. For oil content, 27 QTL on 14 linkage groups and for seed yield, 18 QTL on 11 linkage groups were identified while days to flowering was sug‐ gested to be controlled by a single genetic locus in this mapping population. In rapeseed, Chen et al., (2007) used 208 SSR and 189 SRAP markers to construct a genetic map for a DH line population and performed QTL mapping of yield-related traits in *B. napus*. They also developed a fixed immortalized population from randomly permutated intermating of these DH lines. They collected data for six yield-related traits, plant height, height of lowest pri‐ mary effective branch, length of main inflorescence, silique length, number of primary branches and silique density. After QTL mapping in the DH line and immortalized popula‐ tions, they identified 29 common QTL between the two populations, suggesting that there are some chromosomal regions containing QTL for multiple traits. In another QTL mapping report, Fu et al., (2007) constructed a genetic map in *B. napus* to map gene loci controlling the yellow seeded trait. They developed 420 SSR, RAPD and SRAP markers and assembled two genetic maps, of which one contained 26 linkage groups and another which had 20 linkage groups. After QTL analysis, they identified 19 QTL with one common in the two mapping populations. Further analysis allowed them to identify the collinear genomic region of chro‐ mosome 5 in Arabidopsis.

In cotton, Lin et al., (2005) developed a mapping population by crossing *G. hirsutum* and *G. barbadense* and performed QTL mapping with a genetic map constructed with SRAP, SSR and RAPD markers. Using 437 SRAP, 107 RAPD and 205 SSR markers, they constructed a genetic map with 566 markers assembled into 41 linkage groups, of which 28 were assigned to the corresponding known chromosomes. This genetic map was used to perform QTL mapping for fiber traits. In total, 13 QTL for fibre traits including two QTL for fibre strength, four QTL for fibre length and seven QTL for micronaire value were identified, of which six QTL were assigned into the A-subgenome, another six QTL into the D-subgenome while one QTL was not assigned. Three QTL for micronaire value were identified to cluster on linkage group 1, suggesting that the flanking molecular markers of these three QTL might be useful in marker-assisted selection for this trait.

Similarly, Zhang et al., (2009b) reported on QTL mapping in cotton using SRAP and other markers. They assembled a genetic map containing 509 SSR, 58 intron targeted intron/exon splice junction (IT-ISJ), 29 SRAP and 8 morphological loci in 60 linkage groups. Among these 60 linkage groups, 54 were assigned into 26 chromosomes. This genetic map was used to identify QTL for fiber quality traits in five environments. In total, thirteen QTL including four QTL for fiber length, two QTL for fiber strength, two QTL for fiber fineness, three QTL for fiber length uniformity, and two QTL for fiber elongation were identified. Eleven out of 13 QTL were assigned into the A-subgenome and other two QTL, into the D-subgenome.

In chrysanthemum (*Dendranthema morifolium*), Zhang et al., (2011b) performed QTL map‐ ping of inflorescence-related traits using SRAP markers. They constructed two genetic maps in a F1 segregating population using a double pseudo-testcross mapping strategy. With 500 SRAP primer combinations, they produced 896 polymorphic loci and assembled 333 SRAP markers into 57 linkage groups on one genetic map, 342 SRAP markers into 55 linkage groups on the second genetic map. The results indicated that the distribution of these SRAP markers on these two genetic maps was quite uniform. Using these two genetic maps, they mapped 12 QTL for three inflorescence traits, of which each four QTL underpinned speci‐ fied flower diameter, ray floret layer number, and ray floret length, respectively.

In radish, Xu et al., (2012) recently constructed a genetic map with 592 molecular markers including 287 SRAP, 135 RAPD, 78 SSR, 49 ISSR, 29 randomly amplified microsatellite poly‐ morphism (RAMP), and 14 resistant gene analogs (RGA). They used this genetic map to an‐ alyze QTL that controlled root cadmium accumulation. They mapped four QTL on linkage groups 1. 4. 6 and 9. The QTL on linkage group 9 was a major one that accounted for 48.64% of phenotypic variance, suggesting that this QTL might be applied for marker assisted selec‐ tion to improve radish root quality by reducing cadmium concentration.
