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Integrated linkage map of Haliotis midae Linnaeus based on microsatellite and SNP markers.

ABSTRACT The South African abalone Haliotis midae Linnaeus is the most important aquaculture species in South Africa. Marker-assisted selection is envisioned to play an integral part of the genetic improvement program of abalone, and therefore the generation of linkage maps for quantitative trait loci analyses are necessary. This study reports on a first-generation linkage map for H. midae based on microsatellite and single nucleotide polymorphism (SNP) markers. Ten full-sib families were screened with a total of 508 molecular markers derived from genomic and expressed sequence tag sequences. Linkage maps were constructed for each of the families and combined to create an integrated linkage map. The integrated linkage map consists of 186 markers that included 116 microsatellites and 70 SNPs. These markers mapped to 18 linkage groups, which corresponds to the haploid chromosome number of H. midae. The average genome length was estimated at 1,312 cM, displaying an average marker interval of 6.88 cM with 80% genome coverage. The female map is 1.16-fold longer than the male map, indicating differences in recombination rate between the sexes. The association of markers with known genes as well as with transposon elements was also investigated. This study resulted in the first linkage map constructed for any haliotid in which both microsatellite and SNP markers were used, and the results provide a framework for future applications in quantitative trait loci identification.

KEY WORDS: Haliotis midae, abalone, linkage map, microsatellites, single nucleotide polymorphisms

INTRODUCTION

The abalone Haliotis midae Linnaeus is 1 of 6 abalone species that inhabits the coastal waters of southern Africa, of which 5 are endemic to South Africa. Overfishing, increased predation, and destruction of natural habitat have led to a dramatic decrease in wild abalone stocks (Tarr et al. 1996, Hauck & Sweijd 1999, Sales & Britz 2001). Commercial aquaculture, therefore, provides a sustainable alternative to fisheries for maintaining the supply of abalone to the market. The abalone H. midae is the largest of the 5 local abalone species and is currently the only one to be cultured commercially in South Africa. Globally, the abalone aquaculture industry has expanded considerably during the past decade, increasing from 2,800 t produced in 2000 to 40,800 t in 2008 (Food and Agriculture Organization of the United Nations 2010). Similarly, in South Africa, abalone production has increased approximately 10-fold during the past decade (Department of Agriculture, Forestry and Fisheries 2011); currently, South Africa (together with Namibia) is the third largest producer of cultured abalone in the world (Allsopp et al. 2011). Therefore, there is great pressure to increase the productivity of abalone aquaculture for South Africa to remain competitive internationally. The economic value of H. midae has prompted various research initiatives, including optimization of husbandry practices and genetic improvement strategies.

Selective breeding programs have great potential to boost aquaculture production of abalone (Hayes et al. 2007) because strong evidence exists for a heritable component for growth-related traits. Studies on other commercially important abalone species, such as Haliotis discus hannai Linnaeus and Haliotis rufescens Swainson, demonstrated a significant increase in growth rate through selection (Hara & Kikuchi 1992, Kawahara et al. 1997, Jonasson et al. 1999). These studies also found low genetic correlation between the average daily growth rate measured at an early age and the same trait measured at a later age when abalone reached market size. Therefore, genetic improvement could be accelerated if the means for early identification of individuals with favorable production traits existed, highlighting the potential for marker-assisted selection in abalone. The application of marker-assisted selection requires the identification of quantitative trait loci (QTL)--specific gene regions responsible for variation of phenotypic traits such as growth rate or meat quality. The construction of dense linkage maps is necessary for accurate mapping and association with phenotypic traits in QTL identification (Liu et al. 2008).

Linkage maps have been constructed for various aquaculture species such as Oreochromis niloticus Linnaeus (Nile tilapia), Paralichthys olivaceus Temminck & Schlegel (Japanese flounder), Crassostrea gigas Thunberg (Pacific oyster), and Dicentrarchus labrax Linnaeus (European sea bass) (Kocher et al. 1998, Coimbra et al. 2003, Hubert & Hedgecock 2004, Chistiakov et al. 2005). In abalone specifically, linkage maps have been produced for the blacklip abalone Haliotis rubra Leach (Baranski et al. 2006), the Pacific abalone Haliotis discus hannai Ino (Liu et al. 2006, Sekino & Hara 2007), and small abalone Haliotis diversicolor Reeve (Shi et al. 2010, Zhan et al. 2011). Earlier linkage maps were constructed using random amplified polymorphic DNA (RAPD) or amplified fragment length polymorphism (AFLP) markers, but in recent years the majority of linkage maps have been constructed using microsatellite markers.

Microsatellites are polymorphic DNA sequences consisting of short tandem repeats. These short repeats are distributed throughout the genome in coding as well as noncoding regions. Microsatellites are known to have higher mutation rates than nonrepetitive DNA, causing these markers to be highly polymorphic (Weber & Wong 1993). It is this polymorphic nature that makes these markers ideal for linkage mapping because their multiallelic status allows for a high information content, facilitating the detection of segregating alleles (Hauser & Seeb 2008).

Recently, however, single nucleotide polymorphism (SNP) markers have gained popularity for linkage mapping, which is a result of the fact that single base changes may be responsible for most sequence variation among individuals and, therefore, are more frequently associated with QTLs (Beuzen et al. 2000). In addition, SNPs are the most frequent polymorphism in genomes, making them ideal for linkage map saturation (Kennedy et al. 2003). It has also been demonstrated that SNPs have lower genotyping error rates compared with microsatellites (Ewen et al. 2000) and, more recently, the developments in genotyping technology allow for high throughput SNP genotyping at comparatively lower costs (Liu et al. 2011).

This study aimed to construct a first-generation linkage map for Haliotis midae based on microsatellite and SNP markers that could be used for future QTL mapping of economically important traits in this cultured abalone.

MATERIALS AND METHODS

Mapping Families

Ten full-sib mapping families from 3 different abalone aquaculture farms--Roman Bay Sea Farm (Pty) Ltd. in Gansbaai (7B, DS1, and DS2), HIK Abalone Farm (Pty) Ltd. in Hermanus (42A, DS5, and DS6), and Abagold (Pty) Ltd. in Hermanus (FamD, FamH, FamI, and FamJ)--were used for the construction of the integrated linkage map (Table 1). Families DS1 and DS2 share a common parent with family 7B (Table 1); however, all the families were regarded as full-sib families and were analyzed individually when constructing family-specific linkage maps. The parents of all studied families are wild-caught individuals and, therefore, are expected not to demonstrate a genetic relationship to each other. Epipodial tentacles were clipped from the respective parents of each family and mantle tissue samples were collected from the offspring for DNA isolation. Extractions using DNA were performed using the CTAB extraction method of Saghai-Maroof et al. (1984). All mapping families were subjected to parentage analysis with a panel of 7 microsatellite markers to ensure accurate family structure within the selected families.

Molecular Markers

A large number of microsatellite markers have been developed previously for Haliotis midae, including 202 genomic markers from enrichment techniques, such as the FIASCO or SNX Unilinker methods (Bester et al. 2004, Slabbert et al. 2008, Slabbert et al. 2010, Slabbert et al. 2012), as well as 47 expressed sequence tag (EST)-derived markers developed from transcriptome sequence data (Hepple 2010, Jansen 2012), and 15 markers from a bioinformatic study by Rhode (2010). In addition, 10 cross-species microsatellite markers were developed from Haliotis rubra and Haliotis discus hannai (Rhode 2010). Optimized polymerase chain reaction (PCR) conditions and fluorescent labeling to allow for multiplex genotyping has been reported in the literature cited for the development of the markers.

Recently, numerous SNP markers have also been identified in Haliotis midae, including 28 EST-derived SNPs (Bester et al. 2008, Rhode 2010) and 12 genomic SNPs identified in the flanking regions of microsatellite markers (Rhode et al. 2008). The Illumina transcriptome data by Franchini et al. (2011) also provided a useful resource for SNP discovery. Putative SNPs were developed by identifying contigs that showed significant hits to genes of known function. Primers were designed for a number of these contigs, and were subsequently amplified and sequenced using standard Sanger sequencing. Sequences were aligned using ClustalW v1.4 and resulted in the identification of 105 EST SNPs (Blaauw 2012). In addition, 412 in silico EST SNPs were designed from the transcriptome data using the SNP discovery application available in CLC Genomics workbench v4.5 (Blaauw 2012, Du Plessis 2012).

Thus, in total, 831 molecular markers (274 microsatellite markers and 557 SNP markers) were available for this study.

Marker Genotyping

The genotyping of markers in the mapping populations was done in an overlapping fashion to include as many markers as possible while maintaining economy of scale with regard to genotyping costs.

The parents of families 7B, 42A, DS1, DS2, DS5 and DS6 were screened with 204 genomic microsatellite markers (including 2 previously unpublished markers listed in Table 2) and 14 EST-derived microsatellite markers (Table 3). Parents for families DS1, DS2, DS5, and DS6 were screened with the additional 33 EST-derived microsatellite markers, the 15 markers from the bioinformatics study, and 10 cross-species microsatellite markers. Markers that were informative (in which the segregation pattern of alleles could be determined) were then used for genotyping the offspring. Microsatellite markers were grouped into multiplex reactions to reduce genotyping costs. Multiplex reactions were designed specifically for each family, because families had different sets of informative markers. The color of the fluorescent dyes, the respective lengths of the PCR products, and the PCR conditions of the markers were taken into consideration when grouping markers to ensure optimal multiplex reactions. Multiplex PCRs were performed using the QIAGEN multiplex kit: 10 ng template DNA was added to 3.5 [micro]L 2x QIAGEN Multiplex PCR master mix (containing HotStartTaq DNA Polymerase, Multiplex PCR Buffer with 6 mM Mg[Cl.sub.2] and dNTP mix), 0.9 [micro]L primer mix (20 [micro]M of each primer), and dd[H.sub.2]O to a final volume of 7 [micro]L. Polymerase chain reaction cycles consisted of a 10-min denaturing step at 95[degrees]C for 15 min, followed by 35 cycles of 30 sec at 94[degrees]C, 90 sec at TA, and 1 min at 72[degrees]C, which was then completed with an elongation step of 60[degrees]C for 30 min. Capillary electrophoresis of PCR products and GeneScan 600 LIZ[R] Size Standard (Applied Biosystems) was done on the ABI 3730xl DNA Analyser (Applied Biosystems). GeneMapper v4.1 software (Applied Biosystems) was used for allele scoring and assigning genotypes.

Single nucleotide polymorphism markers were genotyped using the Illumina GoldenGate assay with VeraCode technology on the BeadXpress platform. The mapping families DS1, DS2, DS5, and DS6 were included initially on a 48-plex GoldenGate assay that included 36 in vitro SNPs and 12 in silico SNPs (Blaauw 2012). The in silico SNPs were included to determine the efficiency and performance of SNPs identified using CLC workbench. Consequently, the mapping families DS1, DS2, FamD, FamH, FamI, and FamJ were genotyped on a 192-plex GoldenGate assay that contained an additional 186 in silico SNPs and 6 control SNPs (Du Plessis 2012). The control SNPs were SNPs that were included in the first GoldenGate assay, and were included in the second assay as positive controls. As a result of the assay setup, only 234 of the 557 available SNP markers could be tested in the mapping populations (Table 3). Genotyping analysis was performed using GenomeStudio Genotyping Module v1.0 software. Individuals that did not score reliable genotypes (GenCall rate < 0.80) or SNPs that failed in the initial clustering analysis (GenTrain rate < 0.45) were excluded before performing the final clustering analysis. After clustering analysis, genoplots were generated for each SNP separately, and SNPs that illustrated ambiguous clustering were omitted from further analysis.

Linkage Analysis

The genotype data for both SNP and microsatellite markers were converted into the appropriate Joinmap v4.1 format for outcross (CP) populations (Van Ooijen 2011). Markers or individuals that had more than 20% missing data were excluded from the data set. Polymorphic markers were tested for segregation distortion from expected Mendelian ratios with the chi square goodness-of-fit test (P < 0.05). These markers were not excluded, but rather were noted for further analyses. Markers were grouped into linkage groups based on a test for independent segregation, using a LOD score threshold of 3. Sex-specific maps were constructed using the Create Maternal and Paternal Node function in Joinmap, whereas sex-average maps were constructed using the Create Population Node function. Subsequently, the sex-specific and sex-average maps of each family were compared with each other to determine consensus marker order within linkage groups. In addition, both regression and maximum likelihood mapping algorithms were used and compared to confirm consensus marker order. Recombination rate estimates were converted to genetic distances in centiMorgans (cM) using the Kosambi mapping function. Individual linkage groups of the sex-average maps for each family were then combined using the Combine Groups for Map Integration function to generate an integrated linkage map. Average marker spacing per linkage group was calculated by dividing the total length of the linkage group by the number of intervals (Liu et al. 2006).

Genome Size Estimation and Genome Coverage

The genome length was estimated using 2 methods, taking into account the different calculations for approximating telomeric size, and are as follows:

[G.sub.e] = [summation] [G.sub.oi] ([[K.sub.i] + 1]/[[K.sub.i] - 1]), (1)

where [G.sub.oi] represents the observed length of the linkage group i, and [K.sub.i] represents the number of loci on linkage group i (Chakravarti et al. 1991) and

[G.sub.e] = [G.sub.o] + 2t[G.sub.o]/n, (2)

where [G.sub.o] represents the total observed length, t represents the number of linkage groups, and n denotes the number of intervals between the markers (Fishman et al. 2001).

Subsequently, genome coverage was calculated using the equation [G.sub.o]/[G.sub.e ave], where [G.sub.e ave] was the average expected genome length as calculated by Eqs (1) and (2) (Cervera et al. 2001).

Functional Annotation of Markers

After linkage map construction, all the mapped markers were subjected to BLAST analysis to determine whether markers were associated with known genes. The bioinformatics protocol of Farber and Medrano (2003, 2004) was followed. In brief, repeat regions were masked using RepeatMasker v3.3.0 to ensure hits were the result of homologous flanking sequences and not the result of superfluous hits because of repetitive motifs. The masked sequences were then used to conduct BLASTx and BLASTn searches (Altschul et al. 1997) against the nr-nucleotide and nr-protein databases of NCBI (http://blast.ncbi.nlm.nih. gov/Blast.cgi). Masked sequences were also screened against the Repbase database via the program CENSOR v4.2.27 (Jurka et al. 2005, www.girinst.org/repbase) to identify possible associations to dispersed repetitive elements. Hits with either the lowest e value (cutoff, e value = 1.0[e.sup.-4]), or the highest similarity or score were assumed to be the most likely homolog.

RESULTS

Molecular Markers

Across all 10 mapping families, a total of 314 markers were informative, of which 178 were microsatellites and 136 were SNPs. The informative microsatellites consisted of 141 genomic, 32 EST-derived, and 5 cross-species markers. Two genomic microsatellite markers that were found to be informative have not been published before and are listed in Table 2. Several markers were excluded from further analyses, either because they were noninformative or because of problematic genotyping (Table 3). Uninformative markers (59%), in which the segregation of alleles could not be traced through the pedigree, included markers that were monomorphic, markers for which both parents were homozygous for different alleles, and markers that could not be amplified within specific families. Markers that were excluded because of problematic genotyping included duplicated markers (4%) and markers with null alleles (4%). A total of 136 EST SNPs were found to be informative in the mapping population. None of the genomic SNPs were informative, but this could be attributed to the small number that was genotyped in the mapping families. Similarly, with regard to the microsatellite markers, several markers had to be excluded from linkage analysis (Table 3). On average, 22% of SNP markers were excluded because of failed genotyping, and 51% of SNP markers were excluded for not being informative (monomorphic or homozygous for different alleles in both parents).

Linkage Analysis

Sex-specific and sex-average maps were constructed for each of the mapping families. Consensus order within each linkage group, for both the sex-specific and sex-average maps, was obtained using the regression and maximum likelihood mapping algorithms. The number of linkage groups among the different families ranged from 9-21, depending on the number of informative markers. The integrated map consisted of 186 markers that mapped to 18 linkage groups (Fig. 1). Linkage groups were arranged from the longest (in centiMorgans) to the shortest (in centiMorgans) and were named accordingly. The linkage groups ranged in length from 87.1 cM to only 1.3 cM, with an average marker spacing of 6.88 cM (Table 4). The number of loci per linkage group ranged from 3-20, with an average of 9 loci per linkage group.

Genome Size Estimation and Genome Coverage

Equation (1) estimated genome length at 1,327 cM, whereas Eq (2) provided an estimate of 1,297 cM. Average estimated genome length was thus calculated to be 1,312 cM. The observed genome length was 1,038 cM (Table 4). Genome coverage of approximately 80% was achieved. The female map had a total length of 757 cM and an estimated genome length of 1,080 cM (Eq (1)) and 1,019 cM (Eq (2)). The male map was considerably shorter, with a total map length of 650 cM and a genome length estimated at 895 cM (Eq (1)) and 859 cM (Eq (2)).

Functional Annotation of Markers

Molecular markers that mapped to the linkage map was subjected to BLAST analysis and subsequently identified 84 markers that showed significant association to known genes (indicated on Fig. 1, Table 7). In addition, the mapped markers were also investigated for associations with repetitive elements and recognized 55 markers showing significant hits with known transposable elements (indicated on Fig. 1, Table 8).

DISCUSSION

Molecular Markers

The construction of linkage maps require numerous informative molecular markers in which the segregation of alleles can be traced through pedigrees. In the current study, several markers within families were excluded from further analyses because they were monomorphic or demonstrated aberrant genotypes. On average, within a family only 29% of microsatellites and 29% of SNPs were found to be informative for linkage analysis. This was resolved in part by including multiple families for linkage map construction, which increased the number of informative markers to 64% (178 informative markers of a possible 274 markers) of the total microsatellites and 58% (136 informative SNPs from a possible 234 SNP markers) of the total SNPs across families. This clearly illustrates the benefit of multifamily testing in linkage mapping experiments, which aids in negating the effect of a small number of markers being informative in individual families.

Linkage Map Construction

The integrated map was obtained by amalgamating sex-average maps from the separate families, and resulted in a final map that contains 186 markers mapped to 18 linkage groups. The haploid chromosome number for Haliotis midae has been confirmed as 18 (Van der Merwe & Roodt-Wilding 2008), and was thus the expected number of linkage groups for map construction. Although the integrated map contains 18 linkage groups, the separate families seldom displayed this exact number. The families screened for the microsatellite markers (7B, 42A, DS1, DS2, DS5, and DS6) were more likely to generate approximately 18 linkage groups, which could be attributed to the larger number and polymorphic nature of microsatellite markers (Hauser & Seeb 2008). On the contrary, families (FamD, FamH, FamI, and FamJ) that were screened exclusively using the fewer number of biallelic SNP markers demonstrated fewer linkage groups. Preliminary maps often display a number of linkage groups different from the expected haploid number as a result of the underrepresentation of markers on particular chromosomes or chromosomal segments (Yu & Guo 2003, Chistiakov et al. 2005, Baranski et al. 2006). In this study, anchor loci were used to connect linkage groups across individual family sex-average maps for the construction of the integrated map, and thus resulted in the expected 18 linkage groups. However, the integration of linkage group 18 (INT_LG_18) remained problematic. This linkage group contains anchor loci that are informative across the families (HmNS6, HmidPS1.193, and HmidPS1.559), but these markers seem to be linked to different groups of markers in the separate families. Therefore, with map integration, 4 different maps can be drawn, each containing different markers, but not connecting all the markers. This situation is most likely attributed to the fact that recombination information of informative markers across families is absent and exists only between informative markers within a family.

Nearly all the linkage groups on the integrated sex-average map contain both microsatellite and SNP markers, illustrating good integration of both marker types. In the families screened with microsatellites only, only 2 markers mapped repeatedly to INT_LG_16 (HmNS21 and HmRS80); however, with the inclusion of SNPs, this linkage group consists of 10 markers. There are only 2 linkage groups that contain 1 marker type only: INT_LG_9 (only microsatellites) and INT_LG_11 (only SNPs). Future studies could attempt to saturate these linkage groups by screening the currently placed markers in mapping families that have been screened with the other marker type. For example, the SNP mapping families can be screened with the microsatellites on INT_LG_9 and the microsatellite mapping families can be genotyped with the SNPs on INT_LG_11.

The current map has an average intermarker spacing of 6.88 cM. Massault et al. (2008) found that a marker interval of 10 cM was sufficient for initial QTL detection. Therefore, this map provides a foundation for future QTL identification studies in Haliotis midae. It should, however, be noted that there are areas on the map that could be improved with regard to marker density, because the marker interval is not uniform throughout the map and there are linkage groups that are still poorly saturated. In addition, more markers could help to merge the separate groups of INT_LG_18.

Segregation Distortion

Informative markers were tested for segregation distortion using a chi square goodness-of-fit test. Markers that displayed segregation distortion (P < 0.05) were included for linkage analysis, and their map positions were investigated. Most of the markers that displayed segregation distortion were distorted in 1 family only and not across multiple families. One SNP marker (HmSNP1834_464) was, however, distorted in all the families for which it was informative (DS1, DS5, and DS6), but could not be assigned to any linkage group in these families. The locations of the distorted markers were investigated, because clusters of markers that display segregation distortion may be an indication of viability selection (Charlesworth & Charlesworth 1998). No clusters of distorted markers were found, however, on the sex-average maps of the individual families, suggesting that segregation distortion is probably a result of statistical bias or scoring error (Plomion et al. 1995). Another marker that demonstrated distortion in more than 1 family (HmidILL2.8738) did map to the integrated map; although it was informative in 4 families (DS1, DS2, DS5, and DS6), it displayed segregation distortion in only 2 (DS1 and DS5). As mentioned earlier, the segregation distortion is likely indicative of a genotyping error, and therefore the distance between HmidILL2.8738 and Hmid2015 might be inaccurate. Microsatellite markers are prone to genotyping errors and should be inspected carefully to avoid skewing of recombination rates and, consequently, estimates on map length and marker order. Ball et al. (2010) estimated that an error rate of 5% could cause map inflation of up to 50%. Nonetheless, HmidILL2.8738 mapped to the same position on LG-2 in all families where it was found to be informative, regardless of being distorted in some families.

Recombination Rates Between Sexes

Integrated sex-specific maps were also constructed to compare differences between the sexes (Table 5). The female map is 1.16-fold larger than the male map. Considering that approximately equal numbers of markers mapped to both sex-specific maps (118 on the male map and 121 on the female map), the difference in length could be attributed to a recombination rate differential between the sexes. This finding is in accordance with observations in other mollusc species, including other abalone species, which also demonstrated longer map lengths for female maps (Yu & Guo 2003, Hubert & Hedgecock 2004, Baranski et al. 2006, Liu et al. 2006, Sekino & Hara 2007, Zhan et al. 2011). Although sex-specific recombination rates are observed frequently, the biological mechanism remains poorly understood. Various hypotheses have been proposed, including the differences in meiotic prophase progression during spermatogenesis and oogenesis, variations in transcriptional activity of certain genes in each of the sexes, or the presence of sex-specific enzymes (Lindahl 1991). More recently, Singer et al. (2002) determined that the shorter male map is usually compressed at the centromeres and that distances closer to the telomeres are expanded and more comparable with the female map. The mechanism behind this phenomenon, however, remains elusive and further investigation is needed to explain its occurrence.

Comparison with Linkage Maps from Other Haliotis Species

Currently, there are linkage maps available for 3 haliotid species--Haliotis diversicolor, Haliotis rubra, and Haliotis discus hannai (Table 6). These linkage maps are based on AFLP, RAPD, and microsatellite markers. The current study produced the first linkage map for any haliotid species to include SNPs and is best compared with the integrated linkage map of Zhan et al. (2011). The studies by Baranski et al. (2006), Liu et al. (2006), Sekino and Hara (2007), and Shi et al. (2010) constructed sex-specific maps only. The genetic map presented for Haliotis midae has an average intermarker spacing of 6.88 cM. The resolution of the map by Zhan et al. (2011) was slightly higher, with a marker interval of 4.6 cM, but this could be the result of the smaller number of linkage groups (n = 16) found for H. diversicolor. The current map has an approximate genome coverage of 80%, which is similar to the genome coverage (approximately 78.1%) of the map by Zhan et al. (2011). In general, the estimated genome length of Haliotis midae was within the expected range as observed in other haliotids (e.g., Baranski et al. 2006, Zhan et al. 2011). Genome size for H. midae based on C value calculations via flow cytometry estimates it to be 1.43 pg or 1,398.54 Mb (Franchini et al. 2010), which equals roughly 1,398 cM, comparable with the currently calculated 1,312 cM.

Functional Annotation of Markers

This study used numerous markers that demonstrate associations to genes and/or transposable elements (indicated on Fig. 1). Such functional molecular markers are of particular importance in highlighting genomic regions that may contribute to phenotypic variation and may also elucidate structural and functional characteristics of the Haliotis midae genome. Although definitive conclusions cannot yet be drawn, the current data suggest a relatively even distribution of genes across the genome, with some gene clusters on, for example, LG_1, LG_4, LG_5, LG_8, LG_13, and LG_16 (Fig. 1). This information could also be used to correlate physical maps with genetic maps, and possibly enable the pairing of linkage groups with chromosomes if the chromosome positions of genes are known. A further point of interest could be marker H.rub13F06 (on linkage group 4), a transferred marker from the sister taxon, Haliotis rubra (Australia's blacklip abalone), which is also a gene-associated marker. This chromosomal segment may represent a region of synteny between the H. midae and H. rubra genomes, and warrants further investigation. Markers that show significant hits with known genes are shown in Table 7. There are numerous markers that displayed significant hits against genes involved in muscle formation. These genes include both the myosin heavy and light chain, and the phosphoglycerate mutase 2 (pgam2) gene. These markers could be of interest when looking for regions that could improve growth rates in abalone. When investigating growth rate traits, it would also be interesting to consider markers that associated with genes that could influence metabolic rate, such as the cellulase gene, hexokinase, and the beta 1,3-glucan binding protein. In addition, a marker that could be involved with cell growth (HMC1449_847) could also play a role in growth rate. On linkage groups INT_LG_2, -5, and -8, there are markers that could be targets for reproduction studies, because these markers showed significant association with fertilization protein and sperm lysin precursor genes. Another important trait of interest for abalone aquaculture is disease resistance. Genes that are involved in cell signaling and apoptosis regulation could be potential targets for such investigations.

Transposable elements are ubiquitous genomic features in most eukaryotic genomes (Biemont & Vieira 2005, Bennetzen 2000). In Haliotis midae, Rhode and Roodt-Wilding (2011) illustrated that approximately 21% of microsatellite loci showed similarity to known transposable elements, and recent transcriptomic work demonstrated that these transposable elements are active transcriptionally (unpublished data, Rhode et al. in prep.), which suggests that transposable elements may play a significant role in the genome dynamics of abalone. Microsatellites that showed significant hits with known transposable elements are distributed on various linkage groups (INT_LG_1, -3, -6, -8, -9, -10, -12, -14, -18), illustrating the widespread distribution of mobile elements in the H. midae genome. Interestingly, a significant number of loci that demonstrate association to genic regions also show association to transposable elements (Table 8). This is, however, not uncommon with various DNA transposons and LTR retrotransposons locating in both promoter and coding regions of genes. Such transposable elements have also been found to influence gene function by creating or abolishing regulatory motifs (Bennetzen 2000, Feschotte & Pritham 2007). These loci may prove to be interesting candidate loci for future genotypephenotype association- and gene expression studies. The presence of transposable elements--in particular, the association to commonly used molecular markers like microsatellites--may pose some technical challenges for linkage mapping, because transposable elements often facilitate unequal recombination (Lira & Simmons 1994). An example in point is INT_LG_18, which contains 5 markers and has shown significant hits with transposons, and could explain why this linkage group is divided across 4 groups. It is possible that these markers could be part of mobile elements and therefore link to various groups of markers, thus representing duplicated genomic regions. Subsequently, this could result in groups of markers being grouped together that have sufficient linkage with the transposon-associated markers but have insufficient linkage to the other markers in that linkage group, causing conflict in map construction.

Identification of Anchor Loci for Future Studies

The current study used numerous mapping families to construct the integrated linkage map for Haliotis midae and, consequently, provides a measure of marker informativeness across families. Markers that were mapped in 4 or more families have been identified that could be useful for future linkage or QTL mapping studies (Table 9, indicated on Fig. 1). These markers could function as anchor loci, enabling the integration of additional markers within the current linkage map. These markers could also be of use for studies in closely related species by testing the transferability of markers and, consequently, screening these markers in mapping families of those species. The absence of anchor loci on INT_LG_18 could explain further why this linkage group failed to generate 1 map.

CONCLUSIONS

Linkage maps remain an invaluable tool for genomic annotation, particularly in nonmodel organisms with genomic sequences that are still unknown. The linkage map constructed in this study is the first reported for Haliotis midae and is the first haliotid map to include SNP markers, providing improved genome coverage. This map could also serve as framework for future QTL analyses, especially considering the number of gene-linked markers used that provides candidate regions of interest for traits of economic importance.

ACKNOWLEDGMENTS

We acknowledge Dr. Ruhan Slabbert and Liana Swart for their technical assistance with the genotyping of markers. We thank the following abalone farms for their involvement and funding: Abagold (Pty) Ltd., Aquafarm Development (Pty) Ltd., HIK Abalone Farm (Pty) Ltd., Irvine and Johnston (I&J) Cape Cultured Abalone (Pty) Ltd., and Roman Bay Sea Farm (Pty) Ltd. This study was also funded by the Innovation Fund (Technology Innovation Agency, South Africa). Stellenbosch University is thanked for facilities provided.

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JESSICA VERVALLE, JULI-ANN HEPPLE, SUZAAN JANSEN, JANA DU PLESSIS, PEIZHENG WANG, CLINT RHODE AND ROUVAY ROODT-WILDING *

Molecular Aquatic Research Group, Department of Genetics, Stellenbosch University, Private Bag X1, Matieland, 7602, South Africa

* Corresponding author. E-mail: roodt@sun.ac.za

DOI: 10.2983/035.032.0115

TABLE 1.
Summary of the origin and number of offspring for the
mapping families.

Family   Female   Male     Location    Offspring
         parent   parent                  (n)

7B       F462     M342     Roman Bay      101
42A      F64      M18      HIK            105
DS1      F617     M342     Roman Bay      103
DS2      F462     M456     Roman Bay      104
DS5      88       W06      HIK            93
DS6      D06      V06      HIK            94
FamD     A22      B21      Abagold        72
FamH     A35      B43      Abagold        71
FamI     A17      B25      Abagold        81
FamJ     A24      B28      Abagold        72

TABLE 2.
Microsatellite markers found to be informative in the
mapping families but have not been published previously.

Marker name   Repeat sequence   Primer Sequence (5'-3')

HmNS17bT      [(CACT).sub.31]   F: AGTAAAGTGGCCGGCAATCGG
                                R: GAAAGAATTCCACTGGCCAC

HmidPS1.792   [(CA).sub.n]      F: TCAATGTAACATGCACACACA
                                R: AGTTTGAGCCTTGTCCTGAAT

Marker name   [T.sub.A]   Accession no.

HmNS17bT         65         EF367116

HmidPS1.792      63         JX853745

TABLE 3.
Summary of information regarding microsatellite
and SNP markers used in this study.

                                             Mapping families

                                       7B    42A   DS1   DS2   DS5

Microsatellites
  Total no. microsatellites screened   216   216   274   274   274
  Null alleles                           4     7    13    16    11
  Duplicated                            10     9    21    14     5
  Noninformative                       106   108   151   163   191
  Informative markers                   96    92    89    81    67
  Mapped markers                        86    75    76    67    57
SNPs
  Total no. SNPs screened              --    --    234   196    48
  Failed to genotype                   --    --     49    50     7
  Monomorphic                          --    --     95    56    26
  Homozygous parents                   --    --     14    15     5
  Informative markers                  --    --     76    75    10
  Mapped markers                       --    --     63    66     3

                                             Mapping families

                                       DS6   FamD   FamH   Faml   FamJ

Microsatellites
  Total no. microsatellites screened   274    --     --     --     --
  Null alleles                          10    --     --     --     --
  Duplicated                             6    --     --     --     --
  Noninformative                       198    --     --     --     --
  Informative markers                   60    --     --     --     --
  Mapped markers                        52    --     --     --     --
SNPs
  Total no. SNPs screened               48    196    196    196    196
  Failed to genotype                     7     48     49     49     49
  Monomorphic                           30     93     86     92     89
  Homozygous parents                   --       6      9      9     11
  Informative markers                   11     49     52     46     47
  Mapped markers                         8     31     25     30     25

TABLE 4.
Summary of integrated sex-average linkage map
for H. midae.

Linkage   Length    Loci    Average spacing   Largest
group      (cM)      (n)         (CM)         interval

1            87.1      15        6.22            28.93
2            86.5      10        9.61            40.79
3            67.5       5        16.88           24.91
4            64.7      10        7.19            21.44
5            64.3      19        3.57            15.14
6            64.0      12        5.82            18.96
7            62.5       9        7.81            16.25
8            62.0      20        3.26            11.98
9            58.7       8        8.39            12.13
10           51.0      10        5.67             9.86
11           50.9       6        10.18           27.84
12           46.4       6        9.28            17.09
13           43.2      13        3.60            10.31
14           42.6       7        7.10            10.75
15           33.6       7        5.60            10.20
16           29.3      10        3.26            10.60
17           15.2       3        7.60            11.93
18A           1.3       4        0.43             0.64
18B         64          6        12.80           25.54
18C          36.8       6        7.36            20.28
18D           5.9       3        2.95             3.57
Total     1,038       189        6.88            40.79

TABLE 5.
Summary of integrated sex-specific linkage maps for Haliotis midge.

                                   Female map

                                           Average      Largest
Linkage group   Length (cM)   Loci (n)   spacing (cM)   interval

1                  25.1          9           3.14        13.56
2                  86.8         11           8.68        28.91
3                  28.8          3          14.40        22.92
4                Eq (1) 24       7           8.17        14.43
                 Eq (2) 57       4           8.00        10.47
5                  57           13           4.75        11.17
6                  30.8          7           5.13        11.51
7                  54.8          5          13.70        28.35
8                  57.5         21           2.88        10.75
9               Eq (1) 35.6      3          17.80        34.98
                Eq (2) 30.4      3          15.20        22.56
10                 43.8          7           1.17        15.50
11                 50.9          6          10.18        29.17
12                 18.9          4           6.30        14.60
13                 42.5         13           3.54        11.86
14                 35.9          6           7.18        10.56
15                  --           --           --           --
16              Eq (1) 7.6       3           3.80         4.85
                Eq (2) 27.1      5           6.78        25.24
17                  6.8          3           3.40         4.66
18A                 --           --           --           --
18B                39.3          5           9.83        24.39
18C                 --           --           --           --
18D                 4.4          4           1.47         1.88

                               Male map

                Length                Average      Largest
Linkage group    (cM)    Loci (n)   spacing (cM)   interval

1                28.3      12           2.57         8.73
2                 8.7       4           2.90         4.09
3                49         4          16.33        28.99
4                33.1       5           8.28        23.53
5                60.3      16           4.02         9.04
6                39.6       8           5.66        17.18
7                20.4       5           5.10         8.19
8                33.8      11           3.38        25.99
9                50.7       6          10.14        23.98
10               54         9           6.75        18.41
11                --       --           --           --
12               45.8       5          11.45        20.78
13               35.7      16           2.38         9.93
14               44.7       6           8.94        17.52
15               18.6       6           3.72         7.26
16               25.4       6           5.08        10.06
17               13.7       3           6.85        10.74
18A               2.9       3           1.45         2.84
18B              46.8       7           7.80        15.06
18C              38.4       5           9.60        20.25
18D               --       --           --           --

TABLE 6.
Comparison of the current study with
other abalone linkage mapping studies.

       Species                    Markers

Haliotis diversicolor    412 AFLP markers
H. diversicolor          182 Microsatellite markers
Haliotis rubra           122 Microsatellite markers
                         365 AFLP markers
Haliotis discus hannai   10 RAPD markers
                         9 Microsatellite markers
H. discus hannai         180 Microsatellite markers

                                                        Linkage
       Species               Segregation families       groups

Haliotis diversicolor    1 family (76 offspring)         16-18
H. diversicolor          1 family (96 offspring)          16
Haliotis rubra           1 family (95 offspring)         17-20
Haliotis discus hannai   1 family (106 offspring)        19-22
H. discus hannai         3 families (60-96 offspring)    18-19

                          Average marker         Mapped
       Species            interval (cM)         markers

Haliotis diversicolor     [female] 25.7       [female] 90
                           [male] 25.0         [male] 94
H. diversicolor          4.6 (integrated)   175 (integrated)
Haliotis rubra             [female] 9.8       [female] 98
                            [male] 7.3         [male] 102
                          [female] 18.3       [female] 119
Haliotis discus hannai     [male] 318.2        [male] 147
H. discus hannai           [female] 6.3       [female] 160
                            [male] 4.7         [male] 167

                            Expected map
       Species              length (cM)             Map coverage

Haliotis diversicolor     [female] 2,773.0         [female] 67.6%
                           [male] 2,817.1           [male] 67.3%
H. diversicolor          943.8 (integrated)   [male] 80.7% (integrated)
Haliotis rubra            [female] 1,586.2          [female] 64%
                            [male] 940.5             [male] 80%
                          [female] 2,584.4         [female] 68.6%
Haliotis discus hannai     [male] 2,054.8           [male] 66.5%
H. discus hannai          [female] 1,156.7         [female] 76.6%
                            [male] 899.1            [male] 78.4%

       Species                 Reference

Haliotis diversicolor    Shi et al. (2010)
H. diversicolor          Zhan et al. (2011)
Haliotis rubra           Baranski et al. (2006)
Haliotis discus hannai   Liu et al. (2006)
H. discus hannai         Sekino and Hara (2007)

TABLE 7.
BLAST alignments of markers that mapped to
the integrated Haliotis midae linkage map.

                  Linkage
Marker name        group               BLAST hit

HmC2040_1251         1      Collagen pro alpha-chain

HmC300_1828          1      Myosin light-chain kinase
HmC300_4738          1      Myosin light-chain kinase
HmC300_4982          1      Myosin light-chain kinase
HmC300_6993          1      Myosin light-chain kinase
HmC5634_234          1      Hypothetical protein
HmC1813_300          2      B-cell translocation gene 1
HmC4600_1745         2      Sec61 alpha 1 subunit
Hmid12015            2      Sperm lysin precursor
HmidILL1.140027      2      RAP1B, member
                              of RAS oncogene family
HmidILL2.76149       2      S-adenosylhomocysteine
                              hydrolaselike 1
HmidILL2.8738        2      B-cell translocation gene 1
H.rub13F06           4      Neuron navigator 2
HmC1630_199          4      Cytosolic malate dehydrogenase
HmC2122_257          4      Ependymin-related protein-1
                              precursor
HmC387_215           4      Myoglobin
HmC387_582           4      Myoglobin
HmC5433_233          4      Mitochondrial cytochrome
                              c oxidase subunit
HmLCS67              4      Cysteine aspartic acid-specific
                              protease
HmRS38               4      NAC-like protein 13
HmC1462_825          5      Elongation factor 2
HmC20682_843         5      Hypothetical protein
HmC22491-595         5      Translation elongation factor 2
HmC22491_727         5      Elongation factor 2
HmC911-1343          5      Mitochondrial H + ATPase
                              a subunit
HmC911_290           5      Mitochondrial H + ATPase
                              a subunit
HmidILL1.2192        5      Tyrosine 3-monooxygenase/
                              tryptophan 5-monooxygenase
                              activation protein
HmidILL1.47613       5      Transmembrane emp24
                              protein transport domain
                              containing 7 (tmed7)
HmidPS1.374          5      Sperm lysin precursor
HmNR281              5      Sperm lysin precursor
HmC2028_1228         6      Hypothetical protein
HmC2028_1328         6      Hypothetical protein
HmC2903_1043         6      Ribosomal protein s17
HmC2406_641          7      Ribosomal protein 123a
HmC31_1387           7      Tyrosine 3-monooxygenase
                              tryptophan 5-monooxygenase
                              activation epsilon polypeptide
HmC31_1488           7      Tyrosine 3-monooxygenase
                              tryptophan 5-monooxygenase
                              activation epsilon polypeptide
HmSNP1001_388        7      Myosin heavy chain
HmC1363_269          8      Na(+)/H(+) exchange regulatory
                              cofactor NHE-RF2-like with
                              PDZ domain
HmC394_1510          8      Heat shock protein 20
HmC428_2186          8      Myosin light-chain kinase
HmC428_225           8      Myosin light-chain kinase
HmidILL1.72605       8      Translocase of outer
                              mitochondrial membrane
                              7 homolog
HmidILL2.71359       8      Ubiquitin-specific peptidase 50
HmSSRex446a          8      Cellulase gene
HmSSRex489a          8      Fertilization protein
HmSSRex489b          8      Fertilization protein
H.rub15AO1           9      HoxBa gene cluster
HmidILL1.46687       9      Calmodulin 3
HmC20267_102        10      Polcalcin bra r
HmC2558_743         10      Predicted protein: Notch
                              homolog, scalloped wings
HmC327_1076         10      Beta 1,3-glucan binding protein
HmC1002_85          11      Eukaryotic translation
                              initiation factor 1
HmC1254_187         11      Beta-tubulin
HmC1254_529         11      Beta-tubulin
HmC6012_280         11      Mitochondrial ATP synthase
                              subunit 9
HmSNP149.1_374      11      Heat shock protein (hsp71 gene)
HmC4181_893         12      Hypothetical protein
HmNR20              12      SH2 domain-containing
                              protein 3C
HmC1384_655         13      Voltage-dependent anion
                              channel 2
HmC1384_793         13      Voltage-dependent anion
                              channel 2
HmC14033_777        13      Myosin heavy chain
HmC2141_504         13      Mitochondrial ATP synthase
HmC22568_597        13      60S Ribosomal protein L3
HmC5339_366         13      Myosin heavy chain
HmC618_116          13      Methionine adenosyllransferase
HmC853_1199         13      Myosin heavy chain
HmSNP1949_235       13      Putative 60S ribosomal
                              protein L3 (RPL3)
HmSNP449.2_110      13      Cytidine deaminase
HmC4778_234         14      Fasciclin domain-containing
                              protein
HmSNP4691_183       14      Heat shock protein 70
Hm3Dl0_1            15      Hemocyaninlike
HmC4791_1099        15      Hypothetical protein
HmC1449_847         16      Insulinlike growth factor
                              binding protein 7
HmC18774_676        16      3-Hydroxy-3-methylglutaryl-CoA
HmC22449_261        16      Protein disulfide isomerase
HmC3835_411         16      Sorbitol dehydrogenase
HmC45_3002          16      Hillarin
HmC6061_1289        16      Phosphoglycerate mutase 2
HmC929_2563         17      Hexokinase
Hm3B4_2             18A     Ribosomal protein 1
Hm3B4_7             18A     Ribosomal protein l
HmC253_1545         18C     PDZ and LIM domain
                              protein Zasp
Hmid2044            18C     Hemocyanin Isoform 1
HmidILL2.66010a     18D     MGC97814 protein

                                                    Genbank
Marker name            Gene name/function        accession no.

HmC2040_1251      Synthesis of connective        BAA75669
                    tissue
HmC300_1828       Muscle formation               XP_003214935
HmC300_4738       Muscle formation               XP_003214935
HmC300_4982       Muscle formation               XP_003214935
HmC300_6993       Muscle formation               XP_003214935
HmC5634_234       Unknown                        ACP18834
HmC1813_300       Cell cycle                     ACH92125
                    regulation
HmC4600_1745      Protein transport              NP_001119639
Hmid12015         Fertilization                  FJ940473
HmidILL1.140027   Cell signaling                 AY423018
HmidILL2.76149    Hydrolysis of                  CAN87933
                    S-adenosylhomocysteine
HmidILL2.8738     Cell cycle                     ACH92125
                    regulation
H.rub13F06        Neural development             NG_030347
HmC1630_199       Enzyme modification            ACJ64673
HmC2122_257       Role in memory                 EF103395
                    function
HmC387_215        Oxygen transport               Q01966.2
HmC387_582        Oxygen transport               Q01966.2
HmC5433_233       Electron transport             XP_685495
HmLCS67           Apoptosis regulation           HQ529712
HmRS38            Transcription factor           EF535584
HmC1462_825       Cell signaling                 NP_492457
HmC20682_843      Unknown                        XP_001625221
HmC22491-595      Peptide synthesis              ABX75376
HmC22491_727      Peptide synthesis              ABX75376
HmC911-1343       Energy metabolism              DQ986328
HmC911_290        Energy metabolism              DQ986328
HmidILL1.2192     Signal transduction            DQ437106
HmidILL1.47613    Transmembrane transport        NM_203930
HmidPS1.374       Fertilization                  FJ940391
HmNR281           Fertilization                  FJ940473
HmC2028_1228      Unknown                        XP_002154876
HmC2028_1328      Unknown                        XP_002154876
HmC2903_1043      Protein synthesis              AF548334
HmC2406_641       Protein synthesis              EU302546
HmC31_1387        Signal transduction            NP_001080705
HmC31_1488        Signal transduction            NP_001080705
HmSNP1001_388     Muscle formation               AF134172
HmC1363_269       Ion transport/cell signaling   XP_003198121
HmC394_1510       Protein folding regulation     AET13647
HmC428_2186       Muscle formation               XP_003425477
HmC428_225        Muscle formation               XP_003425477
HmidILL1.72605    Mitochondria                   NM_001113306
                    transmembrane transport
HmidILL2.71359    Protein modification           BC102596
HmSSRex446a       Cellulose metabolism           AB125892
HmSSRex489a       Fertilization                  AF076827
HmSSRex489b       Fertilization                  AF076827
H.rub15AO1        Morphogenesis                  DQ481665
HmidILL1.46687    Cell signaling                 NM_001132483
HmC20267_102      Cellular transport and         XP_001449509
                    signaling
HmC2558_743       Cell signaling                 XP_782555
HmC327_1076       Carbohydrate metabolism        EF103355
HmC1002_85        Gene expression                EU244348
HmC1254_187       Maintain cell structure        BAG55008
HmC1254_529       Maintain cell structure        BAG55008
HmC6012_280       Energy metabolism              HQ729933
HmSNP149.1_374    Protein folding regulation     AM283516
HmC4181_893       Unknown                        XP_001625221
HmNR20            Cell signaling                 XP_687225.2
HmC1384_655       Mitochondrial ion transport    AD156517
HmC1384_793       Mitochondria ion transport     AD156517
HmC14033_777      Muscle formation               CAB64664
HmC2141_504       Energy metabolism              EF103399
HmC22568_597      Protein synthesis              JN997411
HmC5339_366       Muscle formation               AAB03660
HmC618_116        Energy metabolism              AAZ30689
HmC853_1199       Muscle formation               U09782
HmSNP1949_235     Protein synthesis              JN997411
HmSNP449.2_110    Deamination of cytidine        EU101721
HmC4778_234       Cell adhesion                  GQ903764
HmSNP4691_183     Protein folding                ADC32121
                    regulation
Hm3Dl0_1          Oxygen transport               EU135917
HmC4791_1099      Unknown                        EFX83250
HmC1449_847       Cell growth                    JF501214
HmC18774_676      Leucine metabolism             NM_001126700
HmC22449_261      Protein folding                AB026667
                    regulation
HmC3835_411       Carbohydrate metabolism        XP_413719
HmC45_3002        Cell division                  AF339450
HmC6061_1289      Muscle formation               ABZ82035
HmC929_2563       Glucose metabolism             AM076954
Hm3B4_2           Protein synthesis              EF103429
Hm3B4_7           Protein synthesis              EF103429
HmC253_1545       Cellular phosphate             GAA56670
                    regulation
Hmid2044          Oxygen transport               GQ352369
HmidILL2.66010a   Paracellular barrier           BC090128

Marker name               Organism             e Value

HmC2040_1251      Haliotis discus             1.00E-58

HmC300_1828       Anolis carolinensis         3.00E-166
HmC300_4738       Anolis carolinensis         3.00E-166
HmC300_4982       Anolis carolinensis         3.00E-166
HmC300_6993       Anolis carolinensis         3.00E-166
HmC5634_234       Chrrsontela trenuda         4.30E-19
HmC1813_300       Crasso,strea gigas          1.OOE-45
HmC4600_1745      Acvrthosiphon pisum             0
Hmid12015         Haliotis corrugate          4.00E-58
HmidILL1.140027   Danio rerio                 3.00E-86
HmidILL2.76149    Dania rerio                 5.00E-76
HmidILL2.8738     Crasso.strea gigas          2.00E-45
H.rub13F06        Homo sapiens                2.00E-13
HmC1630_199       Lottia pelta                3.66E-151
HmC2122_257       Haliotis discus discus          0
HmC387_215        Haliotis diversicolor           0
HmC387_582        Haliotis diversicolor           0
HmC5433_233       Danio rerio                 1.28E-04
HmLCS67           Haliotis diversicolor       2.00E-23
HmRS38            Crocus sativus              2.00E-05
HmC1462_825       Caenorhabditis elegans          0
HmC20682_843      Nematostella vectensis      4.25E-33
HmC22491-595      Lycosa singoriensis             0
HmC22491_727      Lycosa singoriensis             0
HmC911-1343       Pinctada fucata                 0
HmC911_290        Pinetada fucata                 0
HmidILL1.2192     Bufo gargarizans            6.00E-44
HmidILL1.47613    Xenopus (Silurana)          2.00E-25
                    tropicalis
HmidPS1.374       Haliotis discus             3.00E-08
HmNR281           Haliotis corrugate          6.00E-50
HmC2028_1228      Hydra magnipapillata        9.00E-05
HmC2028_1328      Hydra magnipapillata        9.00E-05
HmC2903_1043      Branchiostoma belcheri      1.00E-24
HmC2406_641       Lineus viridis              2.00E-73
HmC31_1387        Xenopus laevis              8.00E-135
HmC31_1488        Xenopus laeviss             8.00E-135
HmSNP1001_388     Pecten maximus              2.00E-26
HmC1363_269       Danio rerio                 1.00E-47
HmC394_1510       Cyclina sinensis            7.00E-39
HmC428_2186       Nasonia vitripennis         2.76E-32
HmC428_225        Nasonia vitripennis         2.76E-32
HmidILL1.72605    Bos taurus                  8.00E-30
HmidILL2.71359    Bos taurus                  2.00E-38
HmSSRex446a       Haliotis discus hannai      6.00E-39
HmSSRex489a       Haliotis rufescens          8.00E-08
HmSSRex489b       Haliotis rufescens          8.00E-08
H.rub15AO1        Takifugu rubripes           1.00E-16
HmidILL1.46687    Pongo abelii                2.00E-30
HmC20267_102      Paramecium tetraurelia      2.49E-05
                    strain d4-2
HmC2558_743       Strongylocentrotus          0.00E+00
                    purpuratus
HmC327_1076       Haliotis discus discus          0
HmC1002_85        Haliotis diversicolor           0
HmC1254_187       Saccostrea kegaki               0
HmC1254_529       Saccostrea kegaki               0
HmC6012_280       Glycera tridactyla          8.00E-69
HmSNP149.1_374    Haliotis tuberculata        1.00E-65
HmC4181_893       Nematostella vectensis      9.59E-32
HmNR20            Danio rerio                 3.00E-05
HmC1384_655       Haliotis diversicolor           0
HmC1384_793       Haliotis diversicolor           0
HmC14033_777      Mytilus galloprovincialis   2.23E-149
HmC2141_504       Haliotis discus discus          0
HmC22568_597      Haliotis diversicolor           0
HmC5339_366       Placopecten magellanicus    1.79E-122
HmC618_116        Haliotis rufescens              0
HmC853_1199       Argopecten irradians        4.00E-169
HmSNP1949_235     Haliotis diversicolor       1.00E-73
HmSNP449.2_110    Haliotis diversicolor       6.00E-27
HmC4778_234       Haliotis discus discus          0
HmSNP4691_183     Columba livia               4.00E-61
Hm3Dl0_1          Haliotismidae               2.00E-155
HmC4791_1099      Daphnia pulex               2.530-65
HmC1449_847       Haliotis diversicolor       1.00E-173
HmC18774_676      Xenopus (Silurana)          8.00E-69
                    tropicalis
HmC22449_261      Haliotis discus discus          0
HmC3835_411       Gallus gallus               3.00E-114
HmC45_3002        Hirudo medicinales          7.00E-22
HmC6061_1289      Clonorchis sinensis         6.18E-115
HmC929_2563       Crassostrea gigas           9.48E-91
Hm3B4_2           Haliotis discus discus      6.00E-160
Hm3B4_7           Haliotis discus discus      6.00E-160
HmC253_1545       Clonorchis sinensis         2.00E-29
Hmid2044          Haliotis diversicolor       3.00E-29
HmidILL2.66010a   Xenopus tropicales          2.00E-55

Marker name       Similarity (%)

HmC2040_1251            92
HmC300_1828             32
HmC300_4738             32
HmC300_4982             32
HmC300_6993             32
HmC5634_234             44
HmC1813_300             81
HmC4600_1745            94
Hmid12015               85
HmidILL1.140027         84
HmidILL2.76149          71
HmidILL2.8738           45
H.rub13F06              96
HmC1630_199             83
HmC2122_257             87
HmC387_215              96
HmC387_582              96
HmC5433_233             55
HmLCS67                 88
HmRS38                  85
HmC1462_825             83
HmC20682_843            66
HmC22491-595            88
HmC22491_727            88
HmC911-1343             79
HmC911_290              79
HmidILL1.2192           72
HmidILL1.47613          96
HmidPS1.374             87
HmNR281                 84
HmC2028_1228            34
HmC2028_1328            34
HmC2903_1043            88
HmC2406_641             76
HmC31_1387              84
HmC31_1488              84
HmSNP1001_388           83
HmC1363_269             52
HmC394_1510             64
HmC428_2186             57
HmC428_225              57
HmidILL1.72605          95
HmidILL2.71359          93
HmSSRex446a             84
HmSSRex489a             79
HmSSRex489b             79
H.rub15AO1              89
HmidILL1.46687          94
HmC20267_102            51
HmC2558_743             89
HmC327_1076             83
HmC1002_85              91
HmC1254_187            100
HmC1254_529            100
HmC6012_280             83
HmSNP149.1_374         100
HmC4181_893             66
HmNR20                  50
HmC1384_655             98
HmC1384_793             98
HmC14033_777            61
HmC2141_504             91
HmC22568_597            96
HmC5339_366             85
HmC618_116              97
HmC853_1199             75
HmSNP1949_235           97
HmSNP449.2_110          83
HmC4778_234             78
HmSNP4691_183           83
Hm3Dl0_1               100
HmC4791_1099            52
HmC1449_847             98
HmC18774_676            93
HmC22449_261            96
HmC3835_411             49
HmC45_3002              77
HmC6061_1289            67
HmC929_2563             67
Hm3B4_2                 93
Hm3B4_7                 93
HmC253_1545             39
Hmid2044                82
HmidILL2.66010a         97

TABLE 8.
Mapped markers that produced significant hits with
known transposable elements in the Repbase database.

Marker            Linkage group   Class of mobile element

HmC1878_506             1         LTR retrotransposon (Copia)
HmC2040_1251            1         LTR retrotransposon (Gypsy)
HmC300_1828             1         Endogenous retrovirus (ERV1)
HmC300_4738             1         Endogenous retrovirus (ERV1)
HmC300_4982             1         Endogenous retrovirus (ERV1)
HmC300_6993             1         Endogenous retrovirus (ERVI)
HmNS19L                 1         DNA transposon (Helitron)
HmC1813_300             2         Non-LTR retrotransposon R1
HmC460_1745             2         LTR retrotransposon (Copia)
HmidILL1.140027         2         Non-LTR retrotransposon R4
HmidILL2.76149          2         Non-LTR retrotransposon
HmidILL2.8738           2         Non-LTR retrotransposon RI
HmC102_1408             3         DNA transposon (EnSpm)
HmC1462_825             5         DNA transposon (Transib)
HmC20682_843            5         LTR retrotransposon (Gypsy)
HmC22491_595            5         DNA transposon (Transib)
HmC22491_727            5         DNA transposon (Transib)
HmC911_1343             5         LTR retrotransposon (Copia)
HmC911_290              5         LTR retrotransposon (Copia)
HmidILL1.2192           5         DNA transposon (EnSpm)
HmidILL1.47613          5         LTR retrotransposon (Gypsy)
HmidPS1.228             5         DNA transposon
HmC2028_1228            6         DNA transposon (MuDR)
HmC2028_1328            6         DNA transposon (MuDR)
HmC2903_1043            6         DNA transposon (Sola)
HmRS129D                6         DNA transposon (EnSpm)
HmSNP1001_388           7         Non-LTR retrotransposon L2
HmC394_1510             8         DNA transposon (hAT)
mC428_2186              8         LTR retrotransposon (Copia)
HmC428_225              8         LTR retrotransposon (Copia)
HmD59                   8         DNA transposon (MuDR)
HmidILL2.71359          8         DNA transposon (Kolobok)
HmRS62D                 8         DNA transposon (MuDR)
HmSSRex446a             8         Non-LTR retrotransposon (SINE)
HmidPS1.638             9         Interspersed repeat
HmLCS48M                9         DNA transposon (Polinton)
HmC20267_102           10         DNA transposon (EnSpm)
HmC327_1076            10         Non-LTR retrotransposon (Ambal)
HmC1254_187            11         LTR retrotransposon (Gypsy)
HmC1254_529            11         LTR retrotransposon (Gypsy)
HmC250_199             I1         Non-LTR retrotransposon (Jockey)
HmC4181_893            12         DNA transposon (EnSpm)
HmC14033_777           13         DNA transposon (MuDR)
HmC853_1199            13         LTR retrotransposon (Copia)
HmC4778_234            14         Non-LTR retrotransposon (RTE)
HmidPS1.1063           14         Non-LTR retrotransposon Ll
HmC18774_676           16         Non-LTR retrotransposon (Daphne)
HmC22449_261           16         LTR retrotransposon (BEL)
HmC3835_411            16         LTR retrotransposon (Gypsy)
HmC45_3002             16         DNA transposon
HmC11784_1697          18         LTR retrotransposon (Gypsy)
HmC253_1545            18         Non-LTR retrotransposon Ll
HmidILL2.66010a        18         LTR retrotransposon (Gypsy)
HmidPS1.559            18         Non-LTR retrotransposon (CR1)
HmidPS1.890            18         DNA transposon (hAT)

Marker            Score   Similarity

HmC1878_506        284       0.84
HmC2040_1251       263       0.71
HmC300_1828        325       0.75
HmC300_4738        325       0.75
HmC300_4982        325       0.75
HmC300_6993        325       0.75
HmNS19L            237       1.00
HmC1813_300        211       0.77
HmC460_1745        245       0.77
HmidILL1.140027    261       0.70
HmidILL2.76149     310       0.89
HmidILL2.8738      396       0.81
HmC102_1408        251       0.79
HmC1462_825        238       0.79
HmC20682_843       268       0.76
HmC22491_595       238       0.79
HmC22491_727       238       0.79
HmC911_1343        250       0.78
HmC911_290         250       0.78
HmidILL1.2192      214       0.72
HmidILL1.47613     258       0.72
HmidPS1.228        240       0.86
HmC2028_1228       236       0.70
HmC2028_1328       236       0.70
HmC2903_1043       241       0.75
HmRS129D           216       0.80
HmSNP1001_388      227       0.89
HmC394_1510        232       0.82
mC428_2186         243       0.75
HmC428_225         243       0.75
HmD59              217       0.86
HmidILL2.71359     346       0.77
HmRS62D            217       0.86
HmSSRex446a        274       0.70
HmidPS1.638        227       0.80
HmLCS48M           291       0.74
HmC20267_102       205       0.74
HmC327_1076        215       0.81
HmC1254_187        467       0.70
HmC1254_529        467       0.70
HmC250_199         270       0.82
HmC4181_893        238       0.72
HmC14033_777       231       0.74
HmC853_1199        256       0.78
HmC4778_234        234       0.80
HmidPS1.1063       223       0.82
HmC18774_676       314       0.86
HmC22449_261       259       0.78
HmC3835_411        238       0.84
HmC45_3002         225       0.83
HmC11784_1697      253       0.75
HmC253_1545        232       0.76
HmidILL2.66010a    264       0.79
HmidPS1.559        327       0.80
HmidPS1.890        289       0.79

TABLE 9.
Identification of anchor loci information across 4 families
or more in Haliotis midae.

Linkage group                Anchor loci

1               HmD14, HmNR54, HmNS19, HmC2040_1251,
                  HmC300_6993
2               HmidILLI.140027, HmD55, HmidILL2.8738
3               Hmid65
4               HmidPS1.1058, HmC5433_233, HmC387_582,
                  HmC387_215
5               HmidPS1.374, HmidPS1.228, HmidPS1.551,
                  HmidILL1.47613, Hmid221
6               HmRS129
7               HmLCS388, HmidPS1.860, Hmid310
8               HmC1363_269, HmC428_2186, HmLCS37,
                  HmC428_225
9               HmidPS1.638, HinidPS1.549
10              HmNR120, HmNS100
11              HmC1254_187, HmC1254_529
12              HmNR20, Hmid553, Hmid610, HmidPS1.874
13              HmSNP449.2_110, Hmid4010, HmC2141_504,
                  Hmid563, HmSNP1949_235
14              HmidPS1.1063, HmidPS1.818, HmidPS1.247
15                                --
16              HmNS21, HmRS80
17                                --
18                                --
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Article Details
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Title Annotation:single nucleotide polymorphism
Author:Vervalle, Jessica; Hepple, Juli-Ann; Jansen, Suzaan; Plessis, Jana Du; Wang, Peizheng; Rhode, Clint;
Publication:Journal of Shellfish Research
Article Type:Report
Geographic Code:6SOUT
Date:Apr 1, 2013
Words:10793
Previous Article:Sensory and physicochemical assessment of wild and aquacultured green and black lip abalone (Haliotis Laevigata and Haliotis Rubra).
Next Article:Assessment of self-recruitment in a pink abalone (Haliotis corrugata) aggregation by parentage analyses.
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