QTL Analysis of Growth Related Traits and Comparative Genome Analysis Based on the Genetic Linkage Map of Kelp Grouper Epinephelus Bruneus

TUMSAT-OACIS Repository - Tokyo University of Marine Science and Technology (東京海洋大学)

QTL analysis of growth related traits and comparative genome analysis based on the genetic linkage map of kelp grouper Epinephelus bruneus

学位名博士（海洋科学）学位授与機関東京海洋大学学位授与年度 2013 学位授与番号 12614博甲第298号 URL http://id.nii.ac.jp/1342/00000632/ Doctoral thesis

QTL analysis of growth related traits and comparative genome analysis based on the genetic linkage map of kelp grouper Epinephelus bruneus

September 2013

Graduate School of Marine Science and Technology Tokyo University of Marine Science and Technology Doctoral Course of Applied Marine Biosciences

Qi LIU

Content

Abstract ...... 1

Introduction ...... 5

Chapter 1 Isolation of genetic markers ...... 29

Chapter 2 Construction genetic linkage maps ...... 41

Chapter 3 Quantitative trait loci for body weight and condition factor ...... 68

Chapter 4 Comparative genome analysis ...... 93

Chapter 5 Prediction of candidate genes ...... 125

Conclusion ...... 132

Acknowledgements ...... 134

Abstract

Kelp grouper (Epinephelus bruneus), belonging to the subfamily Epinephelinae in the order

Perciformes, occurs in coastal waters of Japan, Korea and China. This species is a protogynous hermaphrodite with individuals beginning life as females and subsequently become males. They sexually mature as females at three years old and change sex from females to males at around six years old. Kelp grouper is highly valued in Asian markets. However, comparing with other cultured grouper species in Japan, kelp grouper has a low growth rate. Genetic improvement seems to be a good tool to resolve this problem. The author focused to genetic improvement of kelp grouper and carried out fundamental studies for this purpose. Results of the studies were summarized into five chapters.

Chapter 1: Isolation of genetic markers

A number of 2348 microsatellite enriched sequences obtained by next generation sequencing and 889 microsatellite enriched sequences collected from across species found in NCBI database were prepared and a total of 1826 microsatellite primers were designed. Of them, 1466 microsatellite markers were designed from kelp grouper genome (denoted as EBR series), and 360 microsatellite markers (named as STR series) were designed from across species. Polymorphism test was performed in 1004 EBR primer pairs and 360 STR primer pairs, respectively and a number of 621 EBR primer pairs had polymorphisms in contact with only 122 STR microsatellite markers, showing 61.9% (family A and B) and 33.9% polymorphisms (family A and B), respectively. Finally, a total number of 470 markers (including 393 EBR series and 77 STR series markers) were used to construct the genetic linkage map (family B). Marker polymorphisms were also tested in sevenband grouper, giant grouper, orange-spotted grouper, malabar grouper and

` coral trout. The results showed that the primers (EBR and STR series) could be partially amplified and exhibited polymorphisms in these species.

Chapter 2: Construction of genetic linkage maps

A reference family was obtained through the mating between one male and one female grouper. The broodstock groupers were raised after being captured from the wild. After 11 months

from hatching, a total of 163 F1 juvenile were remained, body weight (BW) and total length (TL) were measured in all the juveniles. The 90 progenies (no. of 45 individuals presented the smallest body weight and no. of 45 individuals presented the largest body weight) were selected as well as the parental fish for construction of the sex specific maps. The female linkage map contained 334 markers distributing in 23 linkage groups (EBR1F-EBR23F). The total length of the female map was 1225.6 cM and the length of each group was ranged from 42.8 to 65.2 cM. The framework marker interval was 6.1 cM. On the other hand, the male linkage map contained 341 markers distributing in 24 linkage groups (EBR1M-EBR24M). The total length of the male map was

1031.1 cM and the length of each group was ranged from 13.4 to 57.1 cM. The framework marker interval was 5.0 cM.

Chapter 3: Quantitative trait loci for body weight and condition factor

In this study, the same progenies collected in chapter 2 were used for QTL mapping. Body weight (BW) and condition factor (K) were selected as the growth-related traits for QTL mapping.

One major body weight-related QTL region consisting of five loci (four genome wide and one linkage group wide) on a linkage group of 17 and other nineteen body weight-related QTL

(linkage group wide) on five different linkage groups were identified in female genetic linkage map. Eight QTL for body weight (linkage group wide) on three linkage groups were detected in a male linkage map. Moreover, six and twelve condition factor-related QTL (linkage group wide) were identified in female and male linkage groups, respectively. The largest QTL effects for body weight and condition factor were explained 18.9% and 11.8% of the trait variations, respectively.

Chapter 4: Comparative genome analysis

Flanking sequences of the markers mapped onto the linkage map were used for Blast search against the whole genome of Nile tilapia, three-spined stickleback, green spotted puffer, medak,

Atlantic cod and zebrafish. This results showed the flanking sequence of mapped markers in kelp grouper shared the large no. hit with Nile tilapia (Oreochromis niloticus) and three-spined stickleback (Gasterosteus aculeatus), respectively. Oxford plots suggested that some putative ancestral chromosome lineage would be traced in kelp grouper linkage groups.

Chapter 5: Prediction of candidate genes

Potential candidate genes identification indicated that three markers of Ebr00153FRA,

Ebr00314FRA and Ebr00702FRA in the detected major body weight-related QTL region showed significant similarity with the PRICKLE2, ERC2 and SRPK3 gene, respectively. Especially,

SRPK3 gene which had a homologous to the flanking sequence of Ebr00702FRA had a directly role in muscle growth of animals.

Introduction

Groupers belong to the subfamily Epinepheliane, in the order of perciformes and contain more than 440 species (Tupper and Sheriff 2008). Most groupers are protogynous hermaphrodite, they begin life as females and become males subsequently (Tupper and

Sheriff 2008). Like other protogynous hermaphrodite groupers, the first sex of kelp groupers

(Epinephelus bruneus) are females and mature at about three years old (Song et al. 2005), then changing sex from females to males and males will mature at around six years old. This kind of grouper occurs in coastal waters of Japan, Korea and China (Heemstra and Randall

1993)

Groupers are highly valued in Asian markets. Among the species, kelp grouper has several advantages for commercial culture such as the quality of their flesh and the reliability of culture techniques. In addition, in this species, research on common problems of groupers such as viral nervous necrosis (Nakai et al. 1994) and low survival rate during the larval stage

(Teruya and Yoseda 2006) has enabled progress in mariculture technology. Therefore, studies of kelp grouper have contributed as a model for other groupers. However, comparing with other cultured grouper species in Japan, kelp grouper has a low growth rate. Although research on kelp grouper aquaculture has been spanned decades, the growth performance seems to be difficult to improve only by traditional tools.

Genetic improvements of economically traits have been extensively applied in domestication of animals as well as other crops, such as pig and rice. A linkage map could be considered as a process of ordering a series markers along the length of chromosome in the genome within a minimum number of recombination events (Yue 2013). It consists three steps for constructing linkage map. The first process is to assign the markers to their respective

` linkage groups; second is to order of these markers in relation to their proper position along the linkage groups; third is to calculate the map distance in each linkage group (Danzmann

2007). Genetic linkage maps have been accomplished for some major cultured species since the first research of genetic linkage map of tilapia in 1998 (Kocher et al. 1998). In recent years, genetic linkage maps have been constructed for Perciformes species: European seabass

(Dicentrarchus labrax) (Chistiakov et al. 2005, 2008), Asian seabass (Lates calcarifer)

(Wang et al. 2007, 2011a) and gilthead sea bream (Sparus aurata) (Franch et al. 2006) as well as other species. Since 1990, at least 40 aquaculture species have been constructed the genetic linkage maps including teleost fish, crustanceans and macroalgae (Yue 2013). A list of genetic linkage maps including teleost fish species is presented in Table 1. At least 36 teleost species have been constructed genetic linkage maps. Despite the genetic linkage maps have been progressed in recent 20 years, several issues should be considered before construction genetic linkage maps. 1) marker dominant, mapping of co-dominant markers on linkage maps could be used in different population in one species, which is facilitated the genotyping information integration between different programs and labs; 2) the number of samples for collecting genotypes should be large enough to calculate the recombination events; 3) marker density; marker density is critical for fine mapping the QTL region and identifying the potential candidate genes; the second generation genetic maps in such as Japanese flounder, tilapia, Asian seabass and salmonids are constructed, which make it possible to perform in genetic improvement.

Most economically important traits such as growth are quantitative in nature and affected by chromosomal regions known as quantitative trait loci (QTL) across the genome

(Mackay 2001). By identification one major QTL or a few QTL with large effect on the trait, the phenotype value of organisms could be improved by marker-assisted selection (MAS). In addition, fine mapping of QTL region may finally extend to identify particular gene(s) associated with trait. And it will greatly promote breeding program by gene-assisted selection

(GAS) (Sánchez-Molano et al. 2011).

Growth performance (including body weight, condition factor, length and growth rate) is a complex life process, and seems to be one of the most important traits for aquaculture.

Despite many environmental factors may influence the growth performance, previous founding confirmed that heritability of growth are relatively moderate to high throughout a wide range of fish species (e.g. rainbow trout, Kause et al. 2002; Tobin et al. 2006; Arctic charr, Nilsson 1990, 1992; European seabass, Saillant et al. 2006; Dupont-Nivet et al. 2008;

Massault et al. 2010), by which will greatly benefit the performance of QTL effect and may finally apply in genetic breeding programs for aquaculture. Considering traditional selection taking several generations for choosing the progeny with only one or few good performed traits, genetic breeding could assist in selective breeding to accelerate their process and selection power (Naish and Hard 2008). Integration of MAS (or GAS) with traditional selection might be the most effective breeding process and could be used in practice. Since

1990, more than 20 species including fish, shellfish and crustaceans have been performed

QTL analysis. These research has been accumulated the original data for final genetic improvement. A list of QTL mapping including teleost fish species is presented in Table 2. At least 13 teleost fish have been performed QTL analysis. To date, most of QTL detection for growth related traits were mainly performed in salmonid fishes (Reid et al. 2005; Sauvage et

` al. 2012; Küttner et al. 2011). In the order perciformes, only a few species were studied on

QTL underlying growth-related traits, such as European seabass (Chatziplis et al. 2007;

Massault et al. 2010), Asian seabass (Wang et al. 2006; Wang et al. 2008; Wang et al. 2011a) and tilapia (Cnaani et al. 2003; Cnaani et al. 2004). However, there is no study in the subfamily of Epinephelinae so far, which greatly obstructed the genetic improvement of the grouper species. In addition, previous research results confirmed that some QTL (e.g. QTL associated with growth) are conserved across related species in salmonids (Reid et al. 2005).

Hence, it is reasonable to infer that the study of QTL affecting growth performance of kelp grouper will contribute as a model to benefit for other grouper research.

Increased availability of linkage maps constructed from microsatellite markers and other sequence-based markers have led to enable opportunities to accelerate fish genome comparison research. Assembled whole genome sequences of aquatic species (five kinds of model fish and four other kinds of non-model fish species) accelerate the research of conserved synteny between target species with different taxa species (Liu et al. 2012; Reid et al. 2007; Kucuktas et al. 2009; Xia et al. 2010). By extensively syntenic sequence alignment, comparative maps give us a new understanding into fish genome origination, organization and evolution among different species (Jaillon et al. 2004; Kasahara et al. 2007). It is an effective tool to explain genome syntenic relationships, especially in demonstration of the non-model fish chromosome segments descending from which ancestral teleost ancestor lineage since undergoing 3-round whole genome duplication event (Danzmann et al. 2008). In addition, comparative genome analysis in cooperated with QTL analysis have been facilitated identifying potential candidate genes (Wang et al. 2011a, b). It is an effective tool for further

` identification really functional genes affecting economically important traits and enhancing the understanding of molecular mechanism within QTL regions.

The objective of current study focused to genetic improvement of kelp grouper and carried out fundamental studies for this purpose: 1) isolation of genetic markers, 2) construction of genetic linkage maps, 3) locate the position of QTL underlying body weight and condition factor, 4) test conserved synteny against other taxa species as well as tracing the distributions of putative ancestral chromosome lineage within kelp grouper genome and 5) identification of the potential candidate genes in the major QTL region.

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Table 1 Current status of linkage maps in in teleost fish

Species Scientific name Marker types References Young et al. 1998; Sakamoto et al. 2000; Danzmann et al. Rainbow trout Oncorhynchus mykiss AFLP,SSR, SNP and genes 2005; Rexroad et al. 2008 Atlantic salmon Salmo salar AFLP,SSR and SNP Moen et al 2004; Danzmann et al. 2005; Lien et al. 2011 Brown trout Salmo trutta Genes and SSR Gharbi et al. 2006 Arctic char Clarias macrocephalus Genes, SSR and AFLP Woram et al. 2004 European sea bass Dicentrarchus labrax AFLP and SSR Chistiakov et al. 2005; Chistiakov et al. 2008 Asian seabass Lates calcarifer SSR and SNP Wang et al. 2007; Wang et al. 2011a Striped bass Morone saxatilis SSR Liu et al. 2012 Gilthead sea bream Sparus aurata SSR Franch et al. 2006 Three-spined Gasterosteus aculeatus SSR Peichel et al. 2001 stickleback Japanese eel Anguilla japonica AFLP and SSR Nomura et al. 2011 Zebrafish Danio rerio Genes, EST and SSLP Kelly et al. 2000; Singer et al. 2002 Grass carp Ctenopharyngodon idella SSR and SNP Xia et al. 2010 Common carp Cyprinus carpio Gene, SNP, SSR, AFLP and RAPD Sun and Liang 2004; Zheng et al. 2011 Tiger pufferfish Takifugu rubripes SSR Kai et al. 2005 Hippoglossus Atlantic Halibut AFLP and SSR Reid et al. 2007 hippoglossus Channel catfish Ictalurus punctatus SSR and SNP Waldbieser et al. 2001; Kucuktas et al. 2009 Atlantic cod Gadus morhua SNP and SSR Moen et al. 2009; Hubert et al. 2010 AFLP, APD, IRS, EST, STS and Medaka Oryzias latipes Naruse et al. 2000 phenotypic markers Turbot Scophthalmus maximus SSR Bouza et al. 2007; Ruan et al. 2010

Japanese flounder Paralichthys olivaceus SSR and AFLP Coimbra et al. 2003; Castaño-Sánchez et al. 2010 Barfin flounder Verasper moseri SSR and AFLP Ma et al. 2011 Spotted halibut Verasper variegatus SSR and AFLP Ma et al. 2011 Ayu Plecoglossus altivelis SSR and AFLP Watanabe et al. 2004 Seriola quinqueradiata; Yellowtail SSR Ohara et al. 2004 S. lalandi Sablefish Anoplopoma fimbria Genes, SNP and SSR Rondeau et al. 2013 Gnathopogon elongatus; Gudgeons RAD Kakioka et al. 2013 G. caerulescens Red drum Sciaenops ocellatus SSR Portnoy et al. 2011 Red sea bream Pagrus mojor SSR Inami et al. 2005

The summary including species name, scientific name, marker types and references is presented in Table 1.

Table 2 Current status of QTL mapping in teleost fish

Species Scientific name QTL mapped traits References Infectious pancreatic necrosis (IPN); Infectious Houston et al. 2008; Moen et al. 2009; Reid et al. Atlantic salmon Salmo salar Salmon Anemia, body weight and condition factor 2005; Li et al. 2011 Body weight, length, growth rate, Araneda et al. 2009; McClelland and Naish 2010; Coho salmon Oncorhynchus kisutch hatch time and spawn date O'Malley et al. 2010; Araneda et al.2012 Body weight, condition factor; age of sexual Küttner et al. 2011; Somorjai et al. 2003; Norman Arctic charr Clarias macrocephalus maturation; salt tolerance and et al. 2011 temperature tolerance Brook charr Salvelinus fontinalis Growth and stress-related traits Sauvage et al. 2012 IPN; spawning date; body weight and Jackson et al. 1998; Ozaki et al. 2003; O’Malley Rainbow trout Oncorhynchus mykiss Ceratomyxa shasta disease et al. 2003; Wringe et al. 2010; Nichols et al. 2003 Morphometric traits including total length and European sea bass Dicentrarchus labrax Chatziplis et al. 2007; Massault et al. 2009 body weight and stress response Gilthead sea bream Sparus aurata Body weight and age of sexual maturation Loukovitis et al. 2012 Growth-related traits incusing body weight, Wang et al. 2006; Wang et al. 2008; Wang et al. Asian sea bass Lates calcarifer standard length and 2011b condition factors Channel catfish Ictalurus punctatus Growth and morphometric traits Hutson 2008; Ninwichian et al. 2012 Oreochromis Cold tolerance and fish size (body Tilapia mossambicus; Cnaani et al. 2002 weight and standard length) Oreochromis aureus Lymphocystis disease and Japanese flounder Paralichthys olivaceus Fiji et al. 2006; Ozaki et al. 2010 Streptococcus iniae disease Turbot Scophthalmus maximus Body weight, length and condition factor Sánchez-Molano e al. 2011

Common carp Cyprinus carpio Cold tolerance and muscle fiber Sun and Liang 2004; Zhang et al. 2010

The summary including species name, scientific name, QTL mapped traits and references is presented in Table 2.

Chapter 1 Isolation of genetic markers

Introduction

Genetic marker is the basic to construction of genetic linkage maps. For linkage map, markers with relatively high variability are required. In the past, random amplified polymorphic DNAs (RAPDs) and amplified fragment length polymorphism (AFLPs) markers were often used to construct linkage maps due to their relatively low cost for genotyping (Liu et al. 2003; Khoo et al. 2003). However, genetic breeding requires markers that could be widely used to analyze different families and distributed throughout the whole genome.

Microsatellites are suitable for this purpose because of their co-dominant inheritance characteristics, high levels of polymorphism and their distributing throughout the genome

(Sakamoto et al. 2000).

In this experiment, I developed microsatellites from two kinks of sequences and tested the polymorphisms not only for kelp grouper but also in other species.

Materials and Methods

1. Development of genetic markers

Microsatellites enriched segments of kelp grouper genome were developed from next generation sequencing (NGS) by GS FLX system (Roche, Switzerland). Other microsatellite sequences were obtained from across species ranging in the subfamily of Epinephelinae according to the NCBI database (Chapman et al. 1999; Rivera et al. 2003; Zhu et al. 2005;

Ramirez et al. 2006; Lo and Yue 2007; Dong et al. 2008; Liu et al. 2008; Zeng et al. 2008;

Zhao et al. 2009a, b; Renshaw et al. 2010; Mokhtar et al. 2011). Application software

“Websat (www.wsmartins.net/websat)” was used for designing primer pairs. Primers were developed using the default settings, considering the product size from 100 to 250 bp. Marker polymorphisms were tested using the kelp grouper, sevenband grouper, coral trout, giant grouper, orange-spotted grouper and malabar grouper samples.

2. PCR reaction and genotyping

Forward primers for each pair were labeled with tetrachloro-6-carboxy-fluorescine (TET) fluorescent dye at the 5’-end. PCR for genotyping was performed in 11 μl volumes containing

0.05 pmol/μl of forward primer, 0.5 pmol/μl of reverse primer, 1 × reaction buffer, 2.0 mM

MgCl2, 0.2 mM dNTPs, 1% BSA, 0.025 U of Taq polymerase (Takara, Japan) and 25 ng of genomic DNA. Cycle Amplification was performed in MJ PTC-100 (Bio-Rad, USA) for 5 min at 95 °C as an initial denaturation, 36 cycles of 30 s at 95 °C, 1 min at an annealing temperature (56 °C), 1 min at 72 °C and 10 min at 72 °C for final extension. Amplification products were mixed with an equal volume of loading buffer (98% formaldehyde, 10 mM

EDTA and 0.05% bromophenol blue, heated for 10 min at 95 °C and then immediately cooled on ice. The mixture was loaded onto 6% Page-plus gel (Amresco, USA) containing 7 M urea and 0.5 × TBE buffer. Electrophoresis was performed in 0.5 × TBE buffer at 1800 V constant voltage for 1.5 h. After electrophoresis, the gel was scanned and imaged using an FMBIO III

Multi-View fluorescence image analyzer (Hitachi-soft, Japan).

Results

A number of 2348 microsatellite enriched sequences obtained by next generation sequencing and a number of 889 microsatellite enriched sequences collected from across species were collected as candidates for polymorphic markers. A total of 1826 microsatellite primers were designed. Of them, 1466 microsatellite markers were designed from kelp grouper genome (denoted as EBR series), and 360 microsatellite markers (named as STR series) were designed from across species (Table 3). Polymorphism test was performed in 1004 EBR primer pairs and 360 STR primer pairs, respectively and a number of 621 EBR primer pairs had polymorphisms in contrast with only 122 STR microsatellite markers, showing 61.9% (family A and B) and 33.9% polymorphisms (family A and B), respectively. Totally, a number of 743 polymorphic microsatellite markers were developed (Table 4).

Markers designed from kelp grouper genome showed higher polymorphisms (48.1%) than cross species markers such as in family B (27.8%) of kelp grouper samples. Furthermore, polymorphisms of the markers were tested in sevenband grouper, coral trout, giant grouper, orange-spotted grouper and malabar grouper. The results showed that the primers (EBR and

STR series) designed for kelp grouper could be partially amplified and exhibit polymorphisms in these species (Table 4).

Discussion

Microsatellite markers genetically presented highly conserved flanking regions in a diverse number of closely related species (Scribner et al. 1996). The way to choose which method for collecting microsatellites enriched sequences depends on study object. In most case, markers designed from their own genome sequences displayed higher polymorphisms than markers obtained from cross species. Next generation sequencing (NGS) seems to be a powerful tool to collect microsatellites. Its high-throughput sequencing could detect microsatellites more efficiency and accuracy (Gardner et al. 2011). Moreover, the cost of

NGS has been decreased comparing with a few years before. Thus, it is suitable to apply in isolation microsatellites for linkage analysis. However, such as for population research, a few numbers of microsatellites seems to be enough for initial study. Thus, collecting microsatellites from cross species sequences seems to be an effective method with low cost.

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Table 3 The summary of designed markers

Sources Methods Collected sequences Designed primers Cross species to kelp grouper NCBI database 889 360 (STR series) Kelp grouper (EBR series) Next generation sequencing 2348 1466 The summary including sources, methods, collected sequences and designed primers is presented in Table 3.

Table 4 The results of polymorphism test

Species Series of marker No. of tested primers No. of amplified primers No. of polymorphic primers Percent of polymorphism 122 (Family A: 99 and STR: 360 254 27.8% (for family B) Family B: 100) Kelp grouper 621(Family A: 480 and EBR: 1004 866 48.1% (for family B) Family B: 483) STR: 250 155 89 35.6% Senvenband grouper EBR: 1004 774 368 36.7% STR: 200 83 38 19.0% Coral trout grouper EBR: 1004 362 108 10.8% STR: 250 161 80 32.0% Giant grouper EBR: 1004 821 371 37.0% STR: 250 161 106 42.4% Orange-spotted grouper EBR: 1004 808 473 47.1% STR: 50 31 20 40.0% Malabar grouper EBR: - - - -

For kelp grouper, two families including family A and B were used to test polymorphism (for each family, the parents and four progenies were used to test polymorphism); for other species, three to twelve genetic unrelated fish were used to test polymorphism. Family B was used for construction the genetic

linkage map and QTL analysis in next chapters.

Chapter 2 Construction genetic linkage maps

Introduction

In meiosis, the closer two markers or (genes) are to one another on a chromosome, the greater their chance of being inherited together. In contrast, markers located far away from one another on a chromosome are more likely to be separated during recombination. So I can calculate the genetic distance between markers based on the frequency of their recombination and then constructing linkage map. Since 1990s, the first genetic linkage map in finfish has been reported in rainbow trout (Young et al 1998) by mainly AFLP markers. Then basing on co-dominant marker, the linkage map of rainbow trout based on microsatellite marker has been firstly constructed by Sakamoto et al. (2000). In recent 20 years, with marker developed methods in fin fish becoming available, genetic linkage maps have been constructed or updated mainly in salmonds, flat fish, seabass, Cyprinidae species and Cichlid species (Table

2). However, there is no related map in groupers. Therefore, construction of genetic linkage map is required for further genetic improvements. In this experiment, genetic linkage map of kelp grouper is being constructed based on microsatellite maker.

Considering the large number of markers, the practical marker order is extremely difficult to calculate by manual. Thus, a few of software based on computer or web were developed. In this experiment, LINKFMEX software that was often experienced in fin-ray fish was used to generate sex-specific maps.

Materials and methods

1. Reference family and sample collection

A reference family was obtained through the mating between one male and one female groupers. The broodstock groupers were raised in the Ehime Fisheries Research Center, Japan after being captured from the wild. After 11 months from hatching, the parental fish and 90 progenies were used to construct a genetic linkage map. As all the progenies are not mature at this age, the phenotype of sex is not differentiated. DNA was isolated from fin clips using a

QuickGene kit (Fujifilm, Japan).

2. Genotyping of microsatellite markers

A total of 470 polymorphic markers were chosen (Chapter 1) to construct genetic linkage maps. It included 77 markers isolated from cross species and 393 markers developed from kelp grouper genome.

RCR reaction was same in Chapter 1.

3. Genome size estimation

Genome length was estimated in sex-specific maps using two methods. (1) Ge1 was calculated to account for chromosome ends by adding 2 times the average framework marker spacing to the length of each linkage group, where framework marker was denoted as cluster

of the marker (Fishman et al. 2001). (2) Ge2 was calculated by multiplying the length of each genetic linkage group by (m+1)/(m-1), where m means the number of framework markers on

the linkage groups (Chakravarti et al. 1991). The estimated genome length (Ge) for each sex was used as an average of the two estimates.

4. Linkage analysis

Genotype scoring was performed by using LINKMFEX ver. 2.3 application package

(Danzmann 2006). The application can separate the allele genotypes which originate from males or females, and check the accuracy of genotypes in their progeny from parental male and female alleles to avoid genotype scoring errors. Linkage analysis was performed using genotype data converted to a backcross format. As grandparent genotypes were unknown, pairwise analyses were performed, and markers were sorted in linkage groups at LOD threshold of 4.0. Linkage phases were determined retrospectively by examining the assortment of alleles among linked markers. Then the allele was tested for goodness-of-fit for

Mendelian segregation distortion using χ2-analysis. Also the order of the marker loci was confirmed to be correctly positioned, and was checked by double recombination events with the software application program in Map Manager QTX (Manly et al. 2001). Graphic representations of linkage groups were generated with MAPCHART version 2.1 (Voorrips

2002) using raw recombination fractions as estimation of map distances.

Results

Makers independently provided allele information were selected and a number of 470 markers were used to construct genetic linkage maps.

Three hundred and thirty four markers were assigned into 23 linkage groups

(EBR1F-EBR23F) (Fig. 1) in a female genetic linkage map. The total length of the female map was 1225.6 cM and the length of each linkage group was ranged from 42.8 to 65.2 cM

(Table 5). Three hundred and forty one markers were assigned into 24 linkage groups

(EBR1M-EBR24M) (Fig. 1) in a male genetic linkage map. The total length of the male map was 1031.1 cM and the length of each group was ranged from 13.4 to 57.1 cM (Table 5).

Co-segregation markers were used to estimate the recombination rate between the sexes.

Twenty-three linkage groups (EBR1-EBR23) in female and male maps shared at least 2 microsatellite loci and could be used to calculate the recombination rate among adjacently paired markers. When taking account of all the common intervals, the average ratio of recombination between sexes was 1.19:1. Female linkage groups had a higher recombination rate than male linkage groups except for linkage groups of EBR1, 11, 12, 14 and 19.

Estimated genome lengths based on the two methods were very similar. For females they

were 1517.7 cM (Ge1) and 1544.6 cM (Ge2) with an average of 1531.2 cM (Ge), and for males

they were 1288.9 cM (Ge1) and 1329.6 cM (Ge2) with an average of 1309.3 cM (Ge). Based on

the estimation of map lengths, the genome coverage of the female and male maps (Cf) were

80.04% and 78.75%, respectively. The female map was longer than the male map. A summary of the genetic linkage maps of kelp grouper is shown in Table 6.

Discussion

In a female linkage map, 334 markers were assigned to 23 linkage groups, whereas 341 markers were arranged into 24 linkage groups in a male linkage map. Kelp grouper is a diploid fish with 2n = 48 chromosomes (Guo et al. 2003), this number of female linkage groups is inconsistent with the haploid chromosome number (n=24) due to all the allele genotypes located in the linkage group 24 didn’t show polymorphisms in female parent. Thus, more markers are required in order to obtain the full genome coverage. Considering the marker density of first-generation linkage maps of other species such as Japanese eel

(male/female: 6.3/7.2 cM) (Nomura et al. 2011), turbot (sex averaged map 6.5 cM) (Bouza et al. 2007), grass carp (male/female: 4.2/5.2 cM ) (Xia et al. 2010), striped bass (sex averaged map, 5.8 cM) (Liu et al. 2012), tiger pufferfish (male/female: 4.1/7.1 cM) (Kai et al. 2005), barramundi (male/female: 4.7/6.2 cM) (Wang et al. 2007) and Japanese flounder (male/female:

8/6.6 cM) (Coimbra et al. 2003), the average resolution of this map was around in this range, being that female/male is 6.1/5 cM between framework markers. Therefore, the marker density of this map would be sufficient for the initial mapping of economically important traits.

In the present study, females had a higher recombination rate than males (female: male =

1.19:1) throughout all the linkage groups, although males indicated a higher recombination rate than females in some common marker intervals, which was similar to most fish species.

Haldane (1922) and Huxley (1928) suggested that the recombination rate at meiosis becomes different depending on the germline. It is usual that the heterogametic sex has a more suppressed recombination than the homogametic sex. In support of this hypothesis,

` suppressed recombination rates in the heterogametic sex have been observed in many species.

For example, in fish such as grass carp (1:2-2.03, Xia et al. 2010), channel catfish (1:3.18,

Waldbieser et al. 2001), rainbow trout (1:1.68-4.31, Sakamoto et al. 2000; Danzmann et al.

2005; Rexroad et al. 2008), European seabass (1:1.48, Chistiakov et al. 2005) and turbot

(1:1.3-1.6, Bouza et al. 2007; Ruan et al. 2010). However, with the increasing availability of genomic resources, some exceptions have been found. In medaka (Oryzias latipes), pseudo masculinization of genetic females which were hormonally treated produced a lower recombination rate than females to the level shown in males (Matsuda et al. 1999). Such observations have yielded new insight that males have lower recombination rates than females, regardless of whether they are the heterogametic sex (Coop and Przeworski 2007). Kelp grouper has an advantage to study the reason for different recombination rates in males and females, as it is a protogynous hermaphrodite species and an individual undergoes the physiological development of both sexes in its lifecycle as a sex-reversal. The linkage map obtained in this study indicated suppression of recombination in males (second sex). On the other hand, gilthead sea bream is a protandrous hermaphrodite species and an individual has an opposite sex-reversal compared to kelp grouper; nevertheless the linkage map of this fish indicated suppression of recombination in males (first sex, male/female =1:1.2) (Franch et al.

2006). Considering the results of protogynous and protandrous hermaphrodite species, genetic sex (heterogametic or homogametic sex) is not important to determine recombination rates, and the sexual environment in embryological stage derived from primordial germ cells seems to be the key to produce the different recombination rates between males and females. Further studies on the construction of the linkage maps using before and after sex-reversal of the same

` individual would enable insights on this subject.

According to my knowledge, this map is the first linkage map in the subfamily

Epinephelinae. Microsatellite markers genetically present highly conserved flanking regions in a diverse number of closely related species (Scribner et al. 1996). Using microsatellite markers developed from related species on fish research has led to extend the application to construct genetic linkage maps. Markers isolated from Atlantic halibut were approximately 9% and 5% available for mapping barfin flounder and spotted halibut, respectively (Ma et al.

2011) and markers from seven kinds of flatfish species showed 38% availability for mapping

Atlantic halibut (Reid et al. 2007). These findings also supported this result. Markers obtained from Epinephelinae species (Epinephelus acanthistius, E. akaara, E. awoara, E. coioides, E. fuscoguttatus, E. guttatus, E. itajara, E. lanceolatus, E. quernus, E. septemfasciatus,

Cephalopholis fulva, Mycteroperca microlepis, Plectropomus laevis, P. maculatus) worked well in the kelp grouper analysis. In total, 21% of 360 loci isolated from other groupers in this study could be used to construct kelp grouper genetic linkage maps, which were shown to be effective for common usage in groupers. Lack of specific genetic linkage maps for grouper species has delayed their genetic improvement for aquaculture. However, as grouper microsatellites can be widely amplified among closely related species, using “common” markers among related species will accelerate the construction of linkage maps in other groupers and allow the clarification of the inter-relationships among groupers.

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EBR1F EBR1M EBR2F EBR2M

Ebr00386FRA Ebr00236FRA EawSTR10DB Ebr00056FRA 0.0 0.0 Ebr00386FRA 0.0 0.0 Ebr00056FRA Ebr00069FRA Ebr00463FRA Ebr00069FRA 1.1 EguSTR129DB

5.6 EseSTR70DB 7.8 Ebr00775FRA 10.1 EguSTR129DB 11.3 Ebr00236FRA 13.4 Ebr00257FRA 14.5 Ebr00422FRA 14.9 Ebr00375FRA 15.6 Ebr00185FRA

Ebr00284FRA Ebr00715FRA 25.0 Ebr00806FRA

31.7 Ebr00075FRA 31.2 Ebr00375FRA Ebr00231FRA 34.0 Ebr00899FRA 34.0 Ebr00318FRA 35.1 Ebr00190FRA Ebr00888FRA 36.2 Ebr00014FRA 36.2 EawSTR30DB Ebr00284FRA 40.2 42.9 Ebr00256FRA 44.1 Ebr00859FRA 45.4 Ebr00033FRA 49.6 Ebr00257FRA 49.1 Ebr00899FRA 50.8 EawSTR8DB Ebr00190FRA EawSTR30DB 51.4 EitSTR384DB 54.0 Ebr00422FRA 54.1 EawSTR29DB 55.8 Ebr00458FRA 56.3 Ebr00880FRA EfuSTR309DB Ebr00063FRA Ebr00185FRA 55.2 EawSTR8DB EfuSTR309DB 57.4 Ebr00191FRA Ebr00800FRA 56.9 Ebr00063FRA EseSTR69DB 59.6 Ebr00307FRA Ebr00858FRA

Fig. 1 Kelp grouper female (left) and male (right) maps, linkage groups EBR1- EBR24.

Red letters indicate the co-segregation microsatellite loci between female and male maps. Map distances calculated between markers are expressed in Kosambi function (cM).

EBR3F EBR3M EBR4F EBR4M

EawSTR19DB EawSTR58DB Ebr00384FRA Ebr00293FRA EawSTR19DB EawSTR58DB 0.0 0.0 Ebr00099FRA Ebr00517FRA 0.0 Ebr00905FRA Ebr00298FRA 0.0 Ebr00340FRA Ebr00099FRA Ebr00242FRA Ebr00052FRA Ebr00226FRA 4.5 Ebr00299FRA 5.6 Ebr00384FRA 6.7 Ebr00517FRA 7.8 Ebr00200FRA 7.8 Ebr00678FRA Ebr00114FRA 8.9 Ebr00052FRA Ebr00472FRA 10.1 Ebr00005FRA 11.2 Ebr00897FRA

15.6 Ebr00426FRA 15.6 Ebr00812FRA 15.7 Ebr00293FRA 16.7 Ebr00286FRA 19.0 Ebr00047FRA Ebr00768FRA 23.7 25.7 Ebr00200FRA 27.1 Ebr00829FRA 28.2 EfuSTR320DB Ebr00678FRA Ebr00114FRA 30.3 Ebr00751FRA 30.4 EawSTR12DB 31.8 Ebr00450FRA 34.9 Ebr00116FRA CfuSTR293DB 34.0 Ebr00005FRA 37.1 Ebr00325FRA 40.7 Ebr00829FRA EfuSTR320DB EawSTR12DB Ebr00116FRA 42.7 Ebr00469FRA 41.8 Ebr00325FRA Ebr00417FRA 45.0 Ebr00493FRA Ebr00798FRA 45.6 Ebr00812FRA 47.2 Ebr00232FRA Ebr00552FRA 45.2 EguSTR122_reDB 48.4 EguSTR122_reDB 47.4 Ebr00415FRA 50.1 Ebr00047FRA 52.8 Ebr00110FRA

60.2 Ebr00751FRA Ebr00469FRA Ebr00232FRA 61.3 Ebr00552FRA Ebr00148FRA Ebr00408FRA

Fig. 1 (continued)

EBR5F EBR5M EBR5+2M EBR6F EBR6M

Ebr00781FRA Ebr00203FRA Ebr00157FRA 0.0 0.0 EawSTR20DB 0.0 Ebr00203FRA Ebr00068FRA 0.0 EawSTR20DB 0.0 Ebr00794FRA Ebr00041FRA 1.1 Ebr00297FRA 1.1 Ebr00041FRA EguSTR130_reDB 3.3 PmaSTR301DB 4.4 Ebr00009FRA Ebr00066FRA 2.2 PmaSTR301DB 5.6 Ebr00893FRA Ebr00345FRA MmiSTR266DB 7.8 6.7 Ebr00824FRA 6.7 Ebr00032FRA 7.8 Ebr00685FRA Ebr00761FRA Ebr00776FRA 9.0 Ebr00372FRA 10.0 Ebr00287FRA Ebr00474FRA Ebr00602FRA 14.5 Ebr00559FRA Ebr00486FRA 16.7 Ebr00734FRA Ebr00736FRA 20.4 Ebr00066FRA 23.7 Ebr00685FRA 25.9 Ebr00383FRA 28.0 Ebr00673FRA

33.7 Ebr00287FRA 33.6 Ebr00730FRA 37.0 Ebr00734FRA 38.1 Ebr00736FRA

49.0 Ebr00345FRA Ebr00253FRA Ebr00270FRA 48.5 Ebr00282FRA Ebr00305FRA MmiSTR266DB 51.8 Ebr00282FRA EguSTR133_r 50.1 Ebr00761FRA Ebr00776FRA Ebr00372FRA Ebr00474FRA 55.2 Ebr00221FRA

Fig. 1 (continued)

EBR8F EBR8M EBR7F EBR7M

ElaSTR220DB Ebr00850FRA 0.0 Ebr00139FRA Ebr00149FRA 0.0 Ebr00822FRA Ebr00166FRA 0.0 EseSTR68DB Ebr00181FRA Ebr00218FRA 0.0 ElaSTR220DB Ebr00850FRA 1.1 Ebr00204FRA Ebr00158FRA EfuSTR319DB 2.2 4.5 Ebr00181FRA Ebr00204FRA Ebr00672FRA 5.6 Ebr00149FRA Ebr00218FRA 6.7 Ebr00628FRA 10.0 Ebr00158FRA 12.3 EfuSTR319DB Ebr00391FRA 14.5 Ebr00810FRA 16.9 Ebr00663FRA 17.2 Ebr00663FRA 18.0 Ebr00034FRA 19.6 Ebr00351FRA Ebr00693FRA 20.1 Ebr00693FRA 20.3 Ebr00786FRA Ebr00361FRA

24.5 Ebr00762FRA Ebr00352FRA 25.8 Ebr00797FRA 27.3 Ebr00183FRA Ebr00786FRA 27.8 Ebr00465FRA EfuSTR192DB Ebr00704FRA 30.7 30.9 Ebr00762FRA Ebr00003FRA Ebr00462FRA Ebr00797FRA 32.3 Ebr00506FRA Ebr00808FRA 34.0 EfuSTR328DB Ebr00398FRA 35.3 Ebr00352FRA

43.2 EfuSTR328DB 46.6 Ebr00465FRA 51.0 Ebr00182FRA

65.2 Ebr00266FRA

Fig. 1 (continued)

EBR10F EBR10M EBR9F EBR9M

EquSTR247DB Ebr00132FRA 0.0 Ebr00774FRA 0.0 EquSTR247DB 0.0 Ebr00134FRA Ebr00199FRA 0.0 Ebr00117FRA 1.1 EfuSTR339DB Ebr00872FRA Ebr00764FRA 3.3 Ebr00774FRA 2.2 Ebr00712FRA Ebr00636FRA 5.6 EguSTR148DB Ebr00155FRA Ebr00134FRA Ebr00199FRA 7.8 EfuSTR339DB 7.8 Ebr00317FRA 10.1 Ebr00300FRA Ebr00872FRA 10.0 Ebr00903FRA 11.2 Ebr00308FRA Ebr00764FRA 12.3 Ebr00807FRA 11.1 Ebr00743FRA 13.4 EawSTR35DB 13.4 Ebr00636FRA 14.5 Ebr00739FRA 15.7 EguSTR148DB Ebr00155FRA 15.6 EawSTR36DB 20.0 Ebr00629FRA 21.2 EcoSTR231DB 22.4 Ebr00317FRA 21.2 Ebr00827FRA Ebr00128FRA 22.3 Ebr00531FRA 23.5 24.6 Ebr00903FRA 24.5 Ebr00546FRA 25.7 EguSTR157DB 25.7 Ebr00743FRA EseSTR95DB 26.9 Ebr00807FRA 27.8 Ebr00020FRA 32.5 EawSTR35DB

39.4 EawSTR36DB 39.1 Ebr00262FRA 41.8 Ebr00378FRA 41.6 Ebr00629FRA Ebr00827FRA 42.5 Ebr00445FRA 44.9 EcoSTR231DB Ebr00531FRA 43.6 Ebr00265FRA 46.0 EguSTR157DB 47.2 Ebr00262FRA Ebr00265FRA 50.8 Ebr00557FRA Ebr00378FRA Ebr00557FRA 51.9 Ebr00606FRA 53.9 Ebr00690FRA

Fig. 1 (continued)

EBR11F EBR11M EBR12F EBR12M

Ebr00006FRA Ebr00894FRA EawSTR49DB Ebr00728FRA Ebr00106FRA Ebr00186FRA Ebr00106FRA Ebr00186FRA EawSTR49DB Ebr00728FRA 0.0 0.0 Ebr00832FRA 0.0 Ebr00733FRA 0.0 Ebr00382FRA Ebr00832FRA Ebr00267FRA 5.6 Ebr00573FRA 6.7 Ebr00777FRA 6.7 Ebr00103FRA 6.7 Ebr00180FRA 7.8 EfuSTR330DB 10.1 Ebr00245FRA 13.4 EfuSTR357DB Ebr00267FRA 15.6 Ebr00416FRA 17.9 Ebr00170FRA 22.3 Ebr00010FRA 26.8 Ebr00840FRA 28.0 Ebr00215FRA 29.0 Ebr00179FRA Ebr00464FRA 32.0 Ebr00659FRA 31.3 Ebr00836FRA 31.3 Ebr00573FRA Ebr00180FRA 34.2 Ebr00687FRA

40.2 Ebr00793FRA 41.7 Ebr00777FRA 43.6 Ebr00035FRA 44.7 Ebr00857FRA 46.2 Ebr00010FRA 48.0 Ebr00097FRA Ebr00331FRA 49.5 Ebr00840FRA 50.6 Ebr00179FRA 52.8 Ebr00312FRA 53.0 Ebr00687FRA 51.7 Ebr00793FRA Ebr00831FRA Ebr00165FRA Ebr00528FRA 56.3 Ebr00093FRA Ebr00338FRA 55.1 Ebr00874FRA

Fig. 1 (continued)

EBR13F EBR13M EBR14F EBR14M

Ebr00163FRA Ebr00254FRA 0.0 Ebr00841FRA 0.0 Ebr00011FRA Ebr00109FRA 0.0 0.0 Ebr00163FRA Ebr00147FRA 3.3 EfuSTR358DB 5.6 Ebr00387FRA 4.5 Ebr00254FRA 6.7 EawSTR31DB Ebr00783FRA 7.8 Ebr00090FRA Ebr00861FRA EBR13+2M 11.2 Ebr00500FRA

17.3 Ebr00784FRA EfuSTR358DB 16.8 Ebr00809FRA

21.8 Ebr00783FRA

0.0 Ebr00090FRA EguSTR143DB Ebr00235FRA 24.8 EfuSTR342DB 1.1 Ebr00861FRA 28.1 Ebr00615FRA 2.2 ElaSTR225DB 30.8 Ebr00801FRA 32.6 Ebr00430FRA Ebr00520FRA 30.4 EitSTR377DB 6.7 Ebr00500FRA 33.7 Ebr00303FRA 32.6 Ebr00707FRA Ebr00263FRA 10.0 EitSTR377DB 39.8 Ebr00390FRA Ebr00235FRA 40.4 Ebr00209FRA 37.1 Ebr00575FRA 40.9 Ebr00833FRA 15.6 Ebr00263FRA Ebr00575FRA 41.5 Ebr00635FRA Ebr00695FRA 42.0 Ebr00520FRA Ebr00303FRA Ebr00187FRA Ebr00826FRA Ebr00292FRA Ebr00209FRA 43.7 16.7 Ebr00579FRA Ebr00802FRA 45.3 48.7 Ebr00479FRA 46.1 Ebr00825FRA 50.4 Ebr00399FRA 47.2 Ebr00826FRA Ebr00113FRA Ebr00187FRA Ebr00554FRA 53.1 Ebr00024FRA Ebr00393FRA 53.8 Ebr00084FRA 56.0 Ebr00554FRA 57.1 Ebr00024FRA Ebr00336FRA 56.2 Ebr00292FRA

64.0 Ebr00429FRA

Fig. 1 (continued)

EBR15F EBR15M EBR16F EBR16M EBR16+2M

Ebr00714FRA Ebr00156FRA 0.0 EfuSTR191DB EfuSTR360DB 0.0 Ebr00507FRA Ebr00156FRA Ebr00876FRA 0.0 0.0 EfuSTR360DB 0.0 EseSTR78DB Ebr00583FRA CfuSTR202DB 1.1 Ebr00737FRA Ebr00529FRA 2.2 Ebr00769FRA 2.2 Ebr00260FRA 1.1 Ebr00064FRA Ebr00244FRA 3.3 Ebr00580FRA 4.4 Ebr00876FRA Ebr00853FRA 4.4 Ebr00072FRA 9.0 Ebr00138FRA 10.0 Ebr00085FRA EitSTR375DB Ebr00428FRA 8.9 Ebr00206FRA Ebr00708FRA Ebr00446FRA 10.1 11.1 Ebr00205FRA 12.2 Ebr00529FRA Ebr00131FRA 12.3 EseSTR78DB Ebr00184FRA Ebr00441FRA 13.4 Ebr00064FRA 12.3 Ebr00504FRA 11.2 Ebr00820FRA 15.6 Ebr00244FRA 13.4 Ebr00051FRA 17.8 Ebr00008FRA 19.0 Ebr00643FRA 20.1 Ebr00283FRA 22.4 Ebr00555FRA 23.5 Ebr00048FRA

29.2 Ebr00072FRA 31.3 Ebr00489FRA

35.1 Ebr00222FRA Ebr00138FRA EitSTR375DB 40.3 Ebr00428FRA Ebr00078FRA Ebr00710FRA 45.3 Ebr00131FRA 44.8 Ebr00205FRA 46.4 Ebr00504FRA 46.4 Ebr00819FRA 48.7 Ebr00051FRA 52.0 Ebr00008FRA 54.3 Ebr00380FRA Ebr00222FRA Ebr00819FRA 57.6 Ebr00380FRA Ebr00521FRA

Fig. 1 (continued)

EBR17F EBR17M EBR18F EBR18M

0.0 EawSTR15DB 0.0 Ebr00674FRA 3.3 Ebr00683FRA Ebr00731FRA Ebr00621FRA 4.4 Ebr00882FRA 0.0 Ebr00360FRA EquSTR249DB Ebr00813FRA Ebr00403FRA EakSTR184DB 0.0 1.1 Ebr00360FRA 1.1 EguSTR150DB Ebr00896FRA Ebr00884FRA 6.7 EfuSTR351DB 16.1 Ebr00686FRA 19.3 Ebr00788FRA 20.4 EawSTR290DB Ebr00443FRA 21.7 21.5 Ebr00610FRA 16.8 Ebr00153FRA 26.0 Ebr00144FRA 21.3 Ebr00702FRA 29.3 Ebr00686FRA 22.4 Ebr00314FRA 30.4 Ebr00443FRA 23.5 EguSTR119DB 26.4 EguSTR150DB 25.7 Ebr00092FRA 27.5 Ebr00096FRA 36.5 Ebr00171FRA 28.6 Ebr00896FRA Ebr00697FRA 37.6 Ebr00111FRA 38.3 ElaSTR366DB 29.7 Ebr00153FRA Ebr00702FRA 41.6 Ebr00698FRA Ebr00414FRA 35.3 Ebr00314FRA EguSTR119DB 46.1 Ebr00111FRA 49.4 Ebr00241FRA 41.8 Ebr00177FRA Ebr00545FRA Ebr00448FRA 48.9 Ebr00241FRA Ebr00348FRA Ebr00268FRA Ebr00402FRA Ebr00401FRA 42.9 45.5 Ebr00401FRA Ebr00173FRA 50.5 Ebr00091FRA EitSTR378DB EcoSTR261DB EcoSTR261DB 53.4 Ebr00091FRA Ebr00202FRA Ebr00549FRA 47.4 Ebr00150FRA Ebr00012FRA 56.7 EitSTR378DB Ebr00202FRA 46.6 Ebr00207FRA

57.5 Ebr00012FRA 58.6 Ebr00207FRA

Fig. 1 (continued)

EBR19F EBR19M EBR20F EBR20M

Ebr00855FRA Ebr00724FRA Ebr00855FRA Ebr00724FRA 0.0 EguSTR139DB EfuSTR321DB 0.0 EfuSTR321DB 0.0 EguSTR126DB Ebr00713FRA 0.0 EguSTR126DB Ebr00522FRA 2.2 Ebr00898FRA 4.5 EacSTR234DB 7.8 PlaSTR269DB 9.0 Ebr00713FRA

14.5 Ebr00508FRA Ebr00313FRA

19.0 Ebr00122FRA 21.2 Ebr00280FRA 22.3 Ebr00055FRA 23.4 Ebr00280FRA Ebr00269FRA Ebr00273FRA 25.6 EguSTR164DB 25.6 Ebr00753FRA Ebr00269FRA Ebr00273FRA 28.9 EacSTR234DB 27.9 30.1 Ebr00601FRA 30.0 EfuSTR312DB PlaSTR269DB 30.1 Ebr00412FRA

34.6 EguSTR151DB Ebr00043FRA 35.5 Ebr00508FRA Ebr00313FRA 35.7 Ebr00046FRA 36.8 Ebr00060FRA 37.8 Ebr00770FRA EguSTR152DB

EguSTR151DB PlaSTR271DB 41.3 Ebr00666FRA 42.6 Ebr00533FRA 43.5 43.7 Ebr00195FRA Ebr00105FRA Ebr00533FRA Ebr00350FRA Ebr00043FRA 44.8 Ebr00333FRA 45.6 Ebr00105FRA Ebr00302FRA 45.8 Ebr00666FRA Ebr00333FRA 46.9 Ebr00526FRA 48.0 Ebr00162FRA

Fig. 1 (continued)

EBR21F EBR21M EBR22F EBR22M

EguSTR158DB EguSTR167DB Ebr00470FRA 0.0 Ebr00470FRA 0.0 2.2 Ebr00622FRA

6.7 Ebr00773FRA 0.0 EguSTR141DB Ebr00891FRA 0.0 EguSTR141DB 7.8 Ebr00238FRA 1.1 Ebr00891FRA 11.3 EguSTR147DB 3.3 Ebr00192FRA Ebr00136FRA 4.4 Ebr00192FRA Ebr00136FRA 6.7 Ebr00594FRA 7.8 Ebr00212FRA 21.5 Ebr00711FRA 13.4 Ebr00212FRA 15.7 EguSTR155DB 26.2 Ebr00152FRA Ebr00779FRA Ebr00633FRA 17.9 29.3 EacSTR236DB ElaSTR367DB Ebr00067FRA 21.2 Ebr00588FRA Ebr00013FRA 34.9 Ebr00623FRA EguSTR147DB 22.7 Ebr00633FRA 23.4 Ebr00159FRA Ebr00007FRA

27.1 Ebr00067FRA 29.3 Ebr00365FRA 42.3 Ebr00369FRA Ebr00558FRA

47.3 EfuSTR308DB 50.1 Ebr00095FRA Ebr00339FRA 49.6 Ebr00152FRA Ebr00558FRA Ebr00095FRA Ebr00023FRA Ebr00030FRA 51.8 38.3 Ebr00588FRA 52.3 Ebr00868FRA Ebr00868FRA

42.8 Ebr00582FRA

Fig. 1 (continued)

EBR23F EBR23M EBR24M

Ebr00045FRA Ebr00249FRA Ebr00045FRA Ebr00249FRA 0.0 Ebr00421FRA Ebr00436FRA 0.0 Ebr00371FRA Ebr00461FRA 0.0 Ebr00461FRA Ebr00605FRA 4.5 Ebr00499FRA 6.7 Ebr00605FRA

22.8 Ebr00720FRA

31.2 MmiSTR267DB Ebr00028FRA

17.3 Ebr00002FRA MmiSTR267DB Ebr00324FRA 45.3 46.1 Ebr00538FRA Ebr00538FRA Ebr00689FRA 46.4 Ebr00817FRA

52.8 EguSTR125DB 21.8 Ebr00385FRA Ebr00758FRA 53.9 Ebr00817FRA 55.4 Ebr00845FRA 22.9 Ebr00572FRA

Fig. 1 (continued)

Table 5 The summary of sex specific maps

Linkage group Total Mapped Framework Framework Linkage group Total Mapped Framework Framework for female length markers markers marker interval for male length markers markers marker interval EBR1F 55.2 18 10 5.5 EBR1M 56.9 15 8 7.1 EBR2F 59.6 13 11 5.4 EBR2M 45.4 9 8 5.7 EBR3F 52.8 17 11 4.8 EBR3M 47.4 16 9 5.3 EBR4F 61.3 18 10 6.1 EBR4M 47.2 15 10 4.7 EBR5F 50.1 14 7 7.2 EBR5M 7.8 5 4 1.9 - EBR5+2M 14.5 10 4 3.6 EBR6F 51.8 10 7 7.4 EBR6M 55.2 14 10 5.5 EBR7F 65.2 14 7 9.3 EBR7M 32.3 17 10 3.2 EBR8F 51.0 11 8 6.4 EBR8M 34.0 11 6 5.7 EBR9F 53.9 18 10 5.4 EBR9M 51.9 16 10 5.2 EBR10F 47.2 13 10 4.7 EBR10M 43.6 16 15 2.9 EBR11F 52.8 10 5 10.6 EBR11M 56.3 12 8 7.0 EBR12F 48.0 17 13 3.7 EBR12M 55.1 14 8 6.9 EBR13F 64.0 16 11 5.8 EBR13M 4.5 2 2 2.2 - EBR13+2M 16.7 11 7 2.4 EBR14F 53.1 16 10 5.3 EBR14M 57.1 22 15 3.8 EBR15F 57.6 19 14 4.1 EBR15M 54.3 18 11 4.9 EBR16F 44.8 16 10 4.5 EBR16M 2.2 2 2 1.1 - EBR16+2M 11.2 8 4 2.8 EBR17F 58.6 21 13 4.5 EBR17M 46.6 19 9 5.2 EBR18F 56.7 9 8 7.1 EBR18M 50.5 19 14 3.6

EBR19F 44.8 16 11 4.1 EBR19M 45.6 17 7 6.5 EBR20F 48.0 13 9 5.3 EBR20M 41.3 10 7 5.9 EBR21F 42.8 11 9 4.8 EBR21M 23.4 13 8 2.9 EBR22F 52.3 12 6 8.7 EBR22M 51.8 14 10 5.2 EBR23F 53.9 12 6 9.0 EBR23M 55.4 11 6 9.2 - EBR24M 22.9 5 4 5.7 Total 1225.6a 334c 216e - 1031.1a 341c 216 e - Average 53.3b 15d 9f 6.1g 41.8b 13d 9f 5g a; indicates the total length of linkage groups. b; indicates averaged length in each linkage group. c; indicates total no. of markers mapped in linkage groups. d; indicates averaged number of markers mapped in each linkage group. e; indicates total no. of framework markers in linkage groups. f; indicates averaged number of framework markers in each linkage group. g; indicates averaged intervals of framework markers.

Table 6 The information of genetic linkage maps

Female genetic linkage map Male genetic linkage map No. of mapped marker 334 341 No. of genetic linkage groups 23 24 Minimum length of genetic linkage group (cM) 42.8 13.4 Maximum length of genetic linkage group (cM) 65.2 57.1 Total length (cM)

Gtotal 1225.6 1031.1 Estimated genome length (cM)

Ge1 1517.7 1288.9

Ge2 1544.6 1329.6

Ge 1531.2 1309.3 Genome coverage %

Cf 80.04% 78.75% Recombination rate 1.19 1

The estimated genome length (Ge) is an averaged value of Ge1 (Fishman et al. 2001) and Ge2 (Chakravarti et al. 1991). Genome coverage (Cf) is denoted by

total length (Gtotal) dividing by estimated genome length (Ge). Recombination rate is ratio by the sum of genetic distances of all the co-segregation markers located in both of female and male maps.

Chapter 3 Quantitative trait loci for body weight and condition factor

Introduction

Research on kelp grouper aquaculture has continued for more than 40 years in Japan.

Although advances in management have been successfully applied to kelp grouper aquaculture, the yield is still at a low level for markets due to some problems mentioned before. Genetic improvement would be an effective approach to solve these problems, compared with traditional tools, which have been found to be effective for flounder and salmonids aquaculture. Based on genetic linkage map, QTL or even gene(s) underlying economically important traits such as growth related QTL might be detected. Furthermore it would assist the selection of the best “broodstock” to construct high quality strains for further genetic improvement of this species. For finfish, with the developed genetic linkage map,

QTL mapping of economically important traits have been available. The first QTL research in finfish since 1990s has been reported in rainbow trout for temperature tolerance (Jackson et al.

1998). In recent, QTL analysis of economically important traits have been extended to growth, adaption traits, disease resistance, stress response, sex-determination. However, no any of

QTL research in groupers has been reported. In this experiment, I attempted to whole genome scan for QTL related to growth by analysis the associations between genotypes and phenotypes in kelp grouper.

Materials and Methods

1. Reference family, sample collection and traits measurement

The reference family was the same as used in Chapter 2. Briefly, after mating between two unrelated brooders, for maintain same environment situation, thousands of eggs were formed and reared together in one independent breeding tank after hatching. At beginning, rotifer and artemia were fed until around 30 day-old firstly. Then fish were fed daily to satiation with commercial diet. Other environment conditions such as photoperiod, water flow, air flow were maintained at the suitable situation for grouper growth. After 11 month post

hatch, a total of 163 F1 juvenile were remained and presented continuous variations. Body weight (BW) in g and total length (TL) in cm were measured in all the juveniles. However, since the highly correlative between BW and TL was found, in this study, only BW and K were used for QTL analysis. The K is a measurement of the fish fatness and calculated as

100×BW×TL-3.

In addition, since the phenotype of sex was not differentiated at 11 months old, the sex of individuals were not considered in this experiment. Hence, the 90 progenies (no. of 45 individuals presented smallest body weight and no. of 45 individuals presented largest body

weight) were selected from F1 progenies to analysis in order to obtain largest phenotypic variations. Fin clips of the broodstock and 90 progenies were collected and stored in absolute ethanol. Then DNA was isolated from fin clips by using QuickGene kit (Fujifilm, Japan).

2. Microsatellites and genotyping

The genetic linkage map containing 470 markers were used to compare the associations 70

` between genotypes and phenotypes for detection of QTL regions.

3. QTL analyses

Prior to the QTL detection, Pearson’s correlation test was performed in order to determine the linear correlation between the traits of BW and K of the samples (IBM SPSS

Statistics 20.0, America). QTL analysis was performed using MapQTL 5.0 (Van Ooijen 2004) with genotype data of all the markers mapped in the sex specific genetic linkage maps and phenotype data of 90 progenies. The simple interval mapping was initially performed and

QTL position was identified where the LOD score assume its maximum. The genome wide and linkage group wide significant thresholds for QTL were estimated by implementing of permutation test, p < 5%, no. of replications = 1000. In addition, the genome wide threshold at p < 1%, no. of replications = 10000 was also estimated. The QTL regions were graphically visualized by combination of MapChart 2.2 (Voorrips 2002) and MapQTL 5.0 (Van Ooijen

2004). The non-parametric Kruskal-Wallis test, which could detect the association between the markers and traits individually without any assumption for the distributions of the trait, was also conducted.

Results

The phenotypic values of the two traits (BW and K) in the samples were checked.

Distinct variations were observed for them. BW ranged from 93 to 253.3 g with an average of

161.4 ± 35.8 g (mean ± S.D.) The K values were from 1.2 to 1.6 with an average of 1.2 ± 0.07

(mean ± S.D.). BW and K was not significant correlated (r = 0.102, P > 5%), which indicated that loci affecting both traits may be independent.

For simple interval mapping, based on the female genetic linkage map, one major candidate QTL region for BW including four genome wide significant QTL (p < 5%) as well as one linkage group wide significant QTL (p < 5%) were detected in EBR17F (Fig. 2, Table

7). QTL for BW with linkage group wide threshold were also located on five linkage groups

(EBR17F, EBR13F, EBR5F, EBR21F and EBR19F) (p < 5%). The peak LOD score of

Ebr00314FRA was reached to genome wide significant level at p < 1% (LOD = 3.8). The

QTL for BW were accounted from 7.8% - 18.9% of phenotypic variations. Based on the male genetic linkage map, eight linkage group significant QTL affecting BW were detected in male linkage groups (EBR18M, EBR15M and EBR10M) (p < 5%) explained 7.9% - 11.9% phenotypic variations. No genome wide significant QTL was located (Fig. 3, Table 8).

By simple interval mapping of K, in total, eighteen linkage group wide significant QTL were identified in both of female and male linkage maps (EBR8F, EBR10F in the female linkage map; EBR1M, EBR20M and EBR21M in the male linkage map, respectively). The

QTL in female linkage map can explain 7.1% - 9.2% phenotypic variations (Fig. 4, Table 9).

In contrast, in male linkage map, the QTL underlying K can explain 6.8% - 11.8% phenotypic variations (Fig. 5, Table 10).

The Kruskal-Wallis test was used to identify whether the significant QTL detected by simple interval mapping was also reliable in one way ANOVA analysis. These results confirmed that all the significant loci detected from simple interval test were also significant in Kruskal-Wallis test at P < 5% (Table 7, Table 8, Table 9 and Table 10). The Kruskal-Wallis test suggested that the results of QTL analysis were not influenced by segregation distortion or non-normal distribution of traits. Moreover, other significant QTL underlying BW and K, respectively were also detected in the Kruskal-Wallis test, even though their detected significant level is relatively low (data not show).

Discussion

This study allowed the first time QTL detection of growth-related traits in kelp grouper. I identified several QTL located in different linkage groups underlying BW and K with small to medium effect, respectively. Similar results were reported in Arctic charr (Küttner et al. 2011) and Brook Charr (Sauvage et al. 2012). These foundlings suggested that BW and K were determined by multiple genes. In addition, although both of chromosome significant QTL associated with BW and K were found in linkage group EBR10 inferred linkage of these QTL under some degree, most of the QTL regions affecting BW and K were separated and located in different position of the linkage groups, which may explain the phenomenon of no significant correlation between traits. Previous research also suggested that the genetic correlation was not obvious between BW and K and different genes might be involved

(Fishback et al. 2002). Moreover, QTL affecting same trait located in different loci of sex specific maps were observed. The QTL for the same traits located in different position of female and male maps suggested that distinct differences of recombination between adjacent markers and the association between traits and genotypes may have roles in QTL detection

(Fuji et al. 2006, 2007). In the present study, besides a few QTL with small effect accounted for BW, a major candidate QTL region (ranging of 8.9 cM) affecting BW was located in linkage group EBR17F which could be explained that although BW in this reference family is under control of multiple genes distributed in chromosomes, a few major genes with large effect could be characterized. The results of detection of few number of genome wide significant QTL (four for female) in contrast with relatively large number of chromosome wide significant QTL (twenty for female and eight for male) are consistent with other growth-

` related QTL studies (Wang et al. 2006; Sauvage et al. 2012; Küttner et al. 2011; Wringe et al.,

2010). Kelp grouper is a protogynous hermaphrodite species and their life history experiences phenotype development of both sexes. The genome between sexes seemed to be same with each other. In this study, only female map detected genome wide significant QTL accounted for 14.6% - 18.9% phenotypic variations. It may be contributed to the female broodstock exhibited fast growth trait. For 11 month old progenies; genes inherited from female may play an important role in determining the BW in reference family. It is uncertain whether sex influences BW, even though BW and sex seemed to have some degree of genetic correlation in gilthead sea bream, a protandrous hermaphrodite species (Loukovitis et al. 2012). Further studies on QTL detection both of BW and sex in this family after progenies mature would enable to demonstrate this subject. Moreover, for the trait K, only linkage group wide significant QTL (a total no. of eighteen) accounted for 6.8% - 11.8% of trait variations, respectively were found, which suggested that environmental factors may have a main role in affecting this trait.

Kruskal-Wallis test is considered as the one-way analysis of variance

(ANOVA) (Lehmann and D’Abrera 1975). In the present study, the existences of OTL in simple interval mapping were also significant (p < 0.05) in Kruskal-Wallis test, which ensured the accuracy and reliability of detected QTL in this study.

Considering relatively small sample size in this experiment, statistical method may influence the QTL power that underestimates the number of QTL associated a trait and the overestimation of QTL effect (Mackay 2001; Beavis 1998, Xu 2003). In addition, heritability of growth-related traits may influence the QTL power (Sánchez-Molano et al. 2010). Hence,

` increasing the marker density, using different families within large number of progeny, measurement the heritability of BW and K should be performed in the next step in order to increase the QTL power and fine mapping the major candidate region. These will assist the final genetic improvement in kelp grouper.

References

Beavis WD (1998) In Patterson AH (ed) Molecular dissection of complex traits. CRC Press,

NewYork

Fishback AG, Danzmann RG, Ferguson MM, Gibson JP (2002) Estimates of genetic

parameters and genotype by environment interactions for growth traits of rainbow trout

(Oncorhychus mykiss) as inferred using molecular pedigree. Aquaculture 206:137-150

Fuji K, Kobayashi K, Hasegawa O, Coimbra MRM, Sakamoto T, Okamoto N (2006)

Identification of a single major genetic locus controlling the resistance to lymphocystis

disease in Japanese flounder (Paralichthys olivaceus). Aquaculture 254:203-210

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(Paralichthys olivaceus). Aquaculture 272:291-295

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(1998) Identification of two QTL influencing upper temperature tolerance in three

rainbow trout (Oncorhynchus mykiss) half-sib families. Heredity 80:143-151

Küttner E, Moghadam HK, Skúlason S, Danzmann RG, Ferguson MM (2011) Genetic

architecture of body weight, condition factor and age of sexual maturation in Icelandic

Arctic charr (Salvelinus alpinus). Mol Genet Genomics 286:67-79

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and statistics. Holden-Day, San Francisco

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303-339

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spawning date and body weight in rainbow trout: testing for conserved effects across

ancestrally duplicated chromosomes. J Hered 94:273-284

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Fernández J, Martínez P (2010) Detection of growth-related QTL in turbot

(Scophthalmus maximus). BMC Genomics 12:473

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Fig. 2-1 (continued)

Simple interval mapping of body weight-related QTL regions in female linkage groups (Fig.

2-1: EBR 17F; Fig. 2-2: EBR13F; Fig. 2-3: EBR5F; Fig. 2-4: EBR21F; Fig. 2-5: EBR19F).

Map position is expressed by centimorgans (cM). The genome wide significant threshold (p for 1% and 5%, respectively) and linkage group wide significant threshold (p for 5%,) are presented in the figures.

Fig. 2-2 (Continued)

Fig. 2-3 (continued)

Fig. 2-4 (continued)

Fig. 2-5

Fig. 3-1 (continued)

Simple interval mapping of body weight-related QTL regions in male linkage groups (Fig. 3-1:

EBR 18M; Fig. 3-2: EBR15M; Fig. 3-3: EBR10M). Map position is expressed by centimorgans (cM). The genome wide significant threshold (p for 5%) and linkage group wide significant threshold (p for 5%) are presented in the figures.

Fig. 3-2 (continued)

Fig. 3-3

Fig. 4-1 (continued)

Simple interval mapping of condition factor-related QTL regions in female linkage groups

(Fig. 4-1: EBR 8F; Fig. 4-2: EBR10F). Map position is expressed by centimorgans (cM). The genome wide significant threshold (p for 5%) and linkage group wide significant threshold (p for 5%) are presented in the figures.

Fig. 4-2

Fig. 5-1 (continued)

Simple interval mapping of condition factor-related QTL regions in male linkage groups (Fig.

5-1: EBR 1M; Fig. 5-2: EBR20M; Fig. 5-3: EBR21M). Map position is expressed by centimorgans (cM). The genome wide significant threshold (p for 5%) and linkage group wide significant threshold (p for 5%) are presented in the figures.

Fig. 5-2 (continued)

Fig. 5-3

Table 7 QTL underlying body weight in female linkage map of kelp grouper

Simple interval mapping Kruskal-Wallis test LOD thresholds PVE Trait Locus name LGa LOD Se Sig.f Genome wideb Linkage group widec (%)d Ebr00314FRA EBR17F 4.09 3.0 1.5 18.9 17.3 ******* EguSTR119DB EBR17F 3.80 3.0 1.5 17.7 16.1 ******* Ebr00702FRA EBR17F 3.24 3.0 1.5 15.3 14.3 ****** Ebr00153FRA EBR17F 3.08 3.0 1.5 14.6 14.7 ****** Ebr00092FRA EBR17F 2.99 3.0 1.5 14.2 12.6 ****** Ebr00896FRA EBR17F 2.10 3.0 1.5 10.2 10.2 **** Ebr00884FRA EBR17F 2.10 3.0 1.5 10.2 10.2 **** EfuSTR351DB EBR17F 2.10 3.0 1.5 10.2 10.2 **** Ebr00177FRA EBR17F 1.55 3.0 1.5 7.6 7.6 *** Body Ebr00163FRA EBR13F 2.50 3.0 1.6 12.0 9.0 **** weight Ebr00254FRA EBR13F 2.50 3.0 1.6 12.0 9.0 **** Ebr00147FRA EBR13F 2.50 3.0 1.6 12.0 9.0 **** Ebr00345FRA EBR5F 1.81 3.0 1.5 8.9 5.7 ** Ebr00253FRA EBR5F 1.60 3.0 1.5 7.8 4.7 ** Ebr00270FRA EBR5F 1.60 3.0 1.5 7.8 4.7 ** Ebr00305FRA EBR5F 1.60 3.0 1.5 7.8 4.7 ** MmiSTR266DB EBR5F 1.60 3.0 1.5 7.8 4.7 ** Ebr00761FRA EBR5F 1.60 3.0 1.5 7.8 4.7 ** Ebr00776FRA EBR5F 1.60 3.0 1.5 7.8 4.7 ** Ebr00372FRA EBR5F 1.60 3.0 1.5 7.8 4.7 **

Ebr00474FRA EBR5F 1.60 3.0 1.5 7.8 4.7 ** EguSTR141DB EBR21F 1.69 3.0 1.5 8.3 5.9 ** Ebr00891FRA EBR21F 1.69 3.0 1.5 8.3 5.9 ** PlaSTR269DB EBR19F 1.66 3.0 1.6 8.1 6.1 **

For each detected QTL underlying body weight, their locus name, linkage group, maximum LOD value, LOD significant thresholds, PVE were obtained from simple interval mapping, their S value and significance level were obtained by Kruskal-Wallis test. a; the number of linkage group. b; the genome wide significant threshold at p value for 5%. c; the linkage group wide significant threshold at p value for 5%. d; percentage of the phenotypic variance explained. e; statistical values for associations between phenotypes and genotypes. f; significant level: as P < 0.05 (**), 0.01 (***), 0.005 (****), 0.0005 (******) and

0.0001 (*******).

Table 8 QTL underlying body weight in male linkage map of kelp grouper

Simple interval mapping Kruskal-Wallis test LOD threshold Trait Locus name LG LODa PVE (%)d Se Sig.f Genome wideb Linkage group widec ElaSTR366DB EBR18M 2.47 3.0 1.6 11.9 10.0 **** Ebr00443FRA EBR18M 1.74 3.0 1.6 8.5 8.3 **** Ebr00698FRA EBR18M 1.68 3.0 1.6 8.2 6.9 *** Ebr00414FRA EBR18M 1.68 3.0 1.6 8.2 6.9 *** Body weight Ebr00008FRA EBR15M 1.81 3.0 1.6 8.8 7.4 *** EfuSTR339DB EBR10M 1.76 3.0 1.6 8.6 5.0 ** Ebr00903FRA EBR10M 1.63 3.0 1.6 8.0 5.8 ** Ebr00774FRA EBR10M 1.62 3.0 1.6 7.9 4.8 **

Table 9 QTL underlying condition factor in female linkage map of kelp grouper

Simple interval mapping Kruskal-Wallis test LOD threshold a PVE e f Trait Locus name LG LOD d S Sig. Genome wideb Linkage group widec (%) Ebr00181FRA EBR8F 1.89 2.6 1.4 9.2 10.3 **** Ebr00204FRA EBR8F 1.89 2.6 1.4 9.2 10.3 **** Ebr00822FRA EBR8F 1.83 2.6 1.4 8.9 10.5 **** Condition factor Ebr00166FRA EBR8F 1.83 2.6 1.4 8.9 10.5 **** Ebr00262FRA EBR10F 1.45 2.6 1.4 7.1 4.4 ** Ebr00265FRA EBR10F 1.45 2.6 1.4 7.1 4.4 **

For each detected QTL underlying condition factor, their locus name, linkage group, maximum LOD value, LOD significant thresholds, PVE were obtained

from simple interval mapping, their S value and significance level were obtained by Kruskal-Wallis test. a; the number of linkage group. b; the genome wide

significant threshold at p value for 5%. c; the linkage group wide significant threshold at p value for 5%. d; percentage of the phenotypic variance explained.

e; statistical values for associations between phenotypes and genotypes. f; significant level: as P < 0.05 (**) and 0.005 (****).

Table 10 QTL underlying condition factor in male linkage map of kelp grouper

Simple interval mapping Kruskal-Wallis test LOD threshold PVE Trait Locus name LG LOD Se Sig. Genome wide Linkage group wide (%) Ebr00386FRA EBR1M 2.45 2.7 1.4 11.8 10.5 **** Ebr00236FRA EBR1M 2.36 2.7 1.4 11.4 9.2 **** Ebr00375FRA EBR1M 2.15 2.7 1.4 10.4 8.0 **** Ebr00231FRA EBR1M 2.15 2.7 1.4 10.4 8.0 **** Ebr00284FRA EBR1M 1.43 2.7 1.4 7.1 4.9 ** Ebr00060FRA EBR20M 2.33 2.7 1.4 11.3 10.7 **** Condition factor EguSTR151DB EBR20M 1.87 2.7 1.3 9.1 8.7 **** Ebr00043FRA EBR20M 1.87 2.7 1.3 9.1 8.7 **** Ebr00666FRA EBR20M 1.43 2.7 1.3 7.1 8.8 **** Ebr00159FRA EBR21M 1.4 2.7 1.2 6.9 5.0 ** Ebr00007FRA EBR21M 1.4 2.7 1.2 6.9 5.0 ** Ebr00212FRA EBR21M 1.39 2.7 1.2 6.8 5.0 **

For each detected QTL underlying condition factor, their locus name, linkage group, maximum LOD value, LOD significant thresholds, PVE were obtained from simple interval mapping, their S value and significance level were obtained by Kruskal-Wallis test. a; the number of linkage group. b; the genome wide significant threshold at p value for 5%. c; the linkage group wide significant threshold at p value for 5%. d; percentage of the phenotypic variance explained. e; statistical values for associations between phenotypes and genotypes. f; significant level: as P < 0.05 (**) and 0.005 (****).

Chapter 4 Comparative genome analysis

Introduction

In evolution, one obvious phenomenon is to share homozygous sequences among species.

With the development of high-throughput next generation sequencing techniques, large amount of genome sequences are available. It provides basic information to estimation of similarity of sequence segments between target species against whole genome assembled species in order to identify conserved genes or protein as well as conserved chromosome segments. Thus, in this experiment, I did a Blast against other species for evaluation the syntenic relationships with kelp grouper genome.

Materials and methods

Microsatellite markers mapped in the genetic linkage map were used in comparative genome analysis. The similarity search of the flanking sequences of mapped markers against the whole genome sequences of three-spined stickleback, green spotted puffer, medaka,

Atlantic cod, Nile tilapia and zebrafish were performed. BLASTN

(http://asia.ensembl.org/Multi/blastview) searches were conducted via Ensemble default settings except from repeat masked DNA database added before sequence alignment. Only the sequence matches having a minimum alignment length over 50 bp and hits with e less than

10-5 were considered as significant. For the most conserved species between kelp grouper and whole genome assembled species, the comparative map was drawn by MapDisto (Ver. 1.7.6)

(Lorieux, 2012) and Excel 2010. Moreover, due to distributions of putative ancestral chromosome segments have been identified in some whole genome assembled species, such as green spotted puffer and medaka (Kasahara et al. 2007), I attempted to locate the orthologous ancestral chromosome segments in the linkage groups of kelp grouper by similarity Blast.

Results

The flanking sequences consisting of 393 kelp grouper genome markers and 77 cross species markers were used to compare the similarities with whole genome assembled species.

Although strong indications of orthologous relationships between kelp grouper and whole genome assembled species were not found, the results were obvious to infer that kelp grouper share large no. of hit with Nile tilapia and three-spined stickleback rather than green spotted puffer, medaka, Atlantic cod and zebrafish (Table 11). 180 and 153 of kelp grouper sequences

(38.3% and 32.6%) had significant homology to the Nile tilapia and three-spined stickleback genome, respectively. Only 2.8% (zebrafish sequences: 13 hits) to 16.6% (green spotted puffer: 78 hits, respectively) of the sequences were significantly similarity between kelp grouper and other four species. Detailed of sequence alignment results are shown in Table 12.

In addition, all the linkage groups of kelp grouper showed homologous sequences with Nile tilapia and three-spined stickleback, respectively. The most conserved homology was found in linkage group EBR17, which shared 17 and 12 syntenic sequences against Nile tilapia and three-spined stickleback, respectively. However, due to lack of chromosome information in

Nile tilapia, I couldn’t locate these syntenic sequences along chromosomes. In this study, a comparison map between kelp grouper and three-spined stickleback is presented (Fig. 5), 22 pairs of syntenic blocks could be defined based on sharing at least two or more orthologous loci by one kelp grouper linkage group against one chromosome of three-spined stickleback except from EBR5 and EBR21. Of them, marker orders were different in 10 syntenic blocks.

However, others were consistent, e.g. the marker orders of EBR10 were assigned into the genome segment of chromosome no. 6 (STICH6) of three-spined stickleback without any inversion. Furthermore, more than half of the kelp grouper linkage groups had one-to-one relationships against three-spined stickleback chromosomes (a total number of 16 kelp grouper chromosomes). Taking account of the Blast results against green spotted puffer and medaka, although the number of sequence alignment was not enough to cover all the position of linkage groups in kelp grouper, still I could infer that some kelp grouper linkage group

` segments come from which putative ancestral chromosome lineage. The distributions of ancestral segments lineage are presented in Table 13. Due to few putative syntenic pairs were found against the genome of zebrafish, the putative ancestral chromosome lineage was absent.

Discussion

Comparisons of the flanking sequence of kelp grouper markers with assembled whole

genome from cross species revealed that the no. of hit of kelp grouper against Nile tilapia

and three-spined stickleback reached to more than 30%. The lowest level of significant

similarity rate of 2.8% was detected in zebrafish. According to my knowledge, this study

seems to be the first time to use genetic linage map information Blast against Nile tilapia

genome. The relatively extensive sequence similarity is accordance with their taxonomy,

both of which belong to Perciformes. However, lack of chromosome information in Nile

tilapia leads to be difficult to compare genomes comparatively. Furthermore, this result is

also similar with striped bass which belongs to the same order of Perciformes. Liu (2012)

found an even larger percentage (58.9%) of orthologous sequences between striped bass and

three-spined stickleback genome. Since kelp grouper (2n=48) and three-spined stickleback

(2n=42) have different karyotypes, the large syntenic block of chromosome pairs are not

expected. A total number of ten blocks with conformed maker orders in contrast twelve

blocks with different marker orders between the two species may also indicate even though

relatively wide-ranging conserved sequences were anchored in both chromosomes, some

degree of chromosomal rearrangements were occurred since the species appeared. This result

supports previous researches that marker order variations among syntenic blocks are

extensively existent among teleost (Reid et al. 2007, Liu et al. 2012, Wang et al. 2011,

Kucuktas et al. 2009). However, phylogenetic closer species might show alleviative disorder

in syntenic blocks (Xia et al. 2010, Zheng et al. 2011). Marker density of genetic linkage

map might also play an important role in determining some degree of homozygous blocks

(Guyomard et al. 2012). Furthermore, the modern teleosts seem to descend from ancestry

fish with 12 or 13 chromosomes (Nakatani et al. 2007). Most teleosts are hypothesized to

have experienced the third duplication event (3R) and then undergoing chromosome

rearrangements (Meyer et al. 2005). In the present study, some ancestral chromosome

lineage has been identified within kelp grouper linkage groups. The number of similarity

alignment ≥ 3 was considered as significant due to increase the reliability of comparison.

Medaka and green spotted puffer have the common ancestor, and both of them have

experienced at least 8 major inter-chromosome rearrangements (Kasahara et al. 2007).

Comparing with the whole genome of green spotted puffer, no major rearrangements were

occurred in medaka genome after undergoing the “common” inter-chromosome

rearrangements (Kasahara et al. 2007). Since the kelp grouper linkage groups had

one-to-one relationships with medaka (Table 10), it appear to be reasonable to suppose that

there is no so many “special” or few major rearrangements occurred in kelp group genome

since descending from the ancestral chromosomes. However, a detailed image of genome

evolution in kelp grouper requires a larger number of sequence-based markers mapped in

genetic linkage map. Here, this study could be the first step that provides the basic

information for further understanding the kelp grouper genome evolution.

Since the ability to use cross species microsatellites on fish research have extended their application in QTL analysis (Somorjai et al. 2003, Reid et al. 2005) and comparative mapping

(Rexroad et al. 2008). In this experiment, both of microsatellites derived from kelp grouper genome and cross species sequences were used in comparative genome analysis.

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Table 11 The syntenic relationships between kelp grouper with other whole genome assembled species

Species No. of hits (%) Average E-value Nile tilapia 180 (38.3%) 6.65E-9 Three-spined stickleback 153 (32.6%) 4.93E-9 Green spotted puffer 78 (16.6%) 1.94E-7 Medaka 75 (16.0%) 603E-9 Atlantic cod 55 (11.7%) 7.53E-8 Zebrafish 13 (2.8%) 8.75E-10

Percentage (%) is calculated by the no. of similar sequences division by the no. of mapped markers.

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Table 12 Oxford plot comparing the linkage map of kelp grouper against the genome of three-spined stickleback (Gasterosteus aculeatus)

Kelp grouper Chromosome number of three-spined stickleback (Gasterosteus aculeatus) linkage group 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 others EBR1 11 EBR2 4 scaffold_133 EBR3 1 1 1 4 EBR4 114 EBR5 2 EBR6 3 scaffold_37 EBR7 6 EBR8 4 EBR9 7 scaffold_69 EBR10 7 EBR11 3 1 scaffold_88 EBR12 1 4 EBR13 9 1 EBR14 10 EBR15 10 EBR16 4 EBR17 10 scaffold_68;scaffold_365 EBR18 9 EBR19 7 EBR20 3 1 EBR21 1 EBR22 4 scaffold_120 EBR23 5 scaffold_159;scaffold_715

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EBR24 2

Numbers indicate the number of kelp grouper sequences with significant similarity to sequences on a three-spined stickleback chromosome. Putative syntenic pairs (no. 》3) are indicated by grey boxes. Scaffolds are presented in the column of others. (Continued)

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Table 12 Oxford plot comparing the linkage map of kelp grouper against the genome of green spotted puffer (Tetraodon nigroviridis)

kelp grouper Chromosome number of green spotted puffer (Tetraodon nigroviridis) linkage group 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Un-random ancestral chromosome segments EBR1 8 1 b EBR2 2 1 i EBR3 3 1 l EBR4 1 g, h EBR5 1 EBR6 2 2 m EBR7 1 1 a, h, m EBR8 2 2 k EBR9 2 c, d, e EBR10 4 d EBR11 1 1 2 i, EBR12 3 j, k EBR13 4 1 j EBR14 2 d, e, f EBR15 4 1 1 f, j ,m, i EBR16 EBR17 4 1 1 l, d, e, f EBR18 3 2 h, m EBR19 2 1 1 f, g, m, j EBR20 2 b EBR21 2 EBR22 1 m EBR23 2 a, h, m

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EBR24 2 c, e

Numbers indicate the number of kelp grouper sequences with significant similarity to sequences on a green spotted puffer chromosome. Characters in the boxes of the ancestral chromosome segments are referred on teleost ancestral chromosome. Putative syntenic pairs (no. 》3) are indicated by grey boxes.

Red letters in the column of ancestral chromosome segments indicate the number of putative syntenic pairs 》3. (Continued)

106

Table 12 Oxford plot comparing the linkage map of kelp grouper against the genome of medaka (Oryzias latipes)

kelp Chromosome number of medaka (Oryzias latipes) grouper linkage 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 ancestral chromosome 1 2 3 4 5 6 7 8 9 Others group 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 segments EBR1 9 b EBR2 5 i EBR3 3 l EBR4 1 g, h EBR5 1 f EBR6 3 m EBR7 2 a EBR8 4 k EBR9 5 c EBR10 5 d EBR11 4 i EBR12 2 j, k EBR13 4 j EBR14 3 d, e, f EBR15 5 m EBR16 1 ultracontig222 d, e ultracontig90;scaffo EBR17 3 l ld1216 EBR18 6 scaffold660 h, m EBR19 3 f, g EBR20 1 scaffold794 b

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EBR21 1 b EBR22 1 m EBR23 3 a EBR24

Numbers indicate the number of kelp grouper sequences with significant similarity to sequences on a medaka chromosome. Characters in the boxes of the ancestral chromosome segments are referred on teleost ancestral chromosome. Putative syntenic pairs (no. 》3) are indicated by grey boxes.

Red letters in the column of ancestral chromosome segments indicate the number of putative syntenic pairs 》3. Scaffolds are presented in the column of others. (Continued)

108

Table 12 Oxford plot comparing the linkage map of kelp grouper against the genome of zebrafish (Danio rerio) kelp grouper Chromosome number of zebrafish (Danio rerio) linkage group 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Others EBR1 1 EBR2 11 EBR3 EBR4 EBR5 EBR6 1 EBR7 1 EBR8 EBR9 1 EBR10 1 EBR11 1 EBR12 1 EBR13 1 EBR14 EBR15 1 EBR16 EBR17 EBR18 1 Zv9_scaffold3467 EBR19 EBR20 EBR21 EBR22 EBR23

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EBR24

Numbers indicate the number of kelp grouper sequences with significant similarity to sequences on a zebrafish chromosome. Scaffolds are presented in the column of others.

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Table 13 The distributions of putative ancestral chromosome lineage

Kelp grouper Putative ancestral chromosome lineage linkage group EBR1 b EBR2 i EBR3 l EBR4 EBR5 EBR6 m EBR7 EBR8 k EBR9 c EBR10 d EBR11 i EBR12 j, k EBR13 j EBR14 d, e, f EBR15 f, g, m EBR16 EBR17 l EBR18 h, m EBR19 f, g EBR20 EBR21 EBR22 EBR23 a EBR24

The putative ancestral chromosome lineage is showed only if the number of putative syntenic pairs 》3 between one linkage group of kelp grouper and one chromosome of medaka or green spotted, respectively.

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Fig. 5 (continued)

Comparing of the kelp grouper sex-specific linkage group (EBR) with three-spined stickleback genome sequence (STICH). Both flanking vertical lines represent kelp grouper linkage groups (female linkage group: left; male linkage group: right), whereas the middle vertical line represents three-spined stickleback chromosomes. Map distance (cM) or physical distance (Mbp) are given behind homozygous locus name. For example, kelp grouper linkage group

112

EBR1 has a significant similarity with the chromosome 2 (STICH2) of three-spined stickleback.

113

Fig. 5 (continued)

114

Fig. 5 (continued)

115

Fig. 5 (continued)

116

Fig. 5 (continued)

117

Fig. 5 (continued)

118

Fig. 5 (continued)

119

Fig. 5 (continued)

120

Fig. 5 (continued)

121

Fig. 5 (continued)

122

Fig. 5 (continued)

123

Fig. 5 (continued)

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Chapter 5 Prediction of candidate genes

125

Introduction

In genetics, there are at least two ways to find target genes along the genome. One way is to use the makers derived from EST sequences to construct genetic map than QTL mapping of target trait in order to find important genes. Another way is based on comparative genome analysis for detection candidate genes. In this experiment, I attempt to find gens associated with growth in the QTL region via comparative genome analysis.

126

Materials and methods

For those microsatellite markers, which located in the major QTL candidate region around the genome wide threshold, I identified their potential candidate genes based on the results of comparative genome analysis. Only the flanking sequence of marker was within the candidate gene, the potentially homology was considered as significant.

127

Results

In this study, since no genome wide significant QTL for condition factor was detected, I did a Blast search of the makers located in the major candidate region affecting body weight in linkage group Ebr17F based on the results of comparative genome analysis. Among these markers, Ebr00153FRA was syntenic to PRICKLE2 gene at 17.13 Mbp on the chromosome

17 of medaka. The strongest QTL for BW located in position of Ebr00314FRA, whose sequence was homologous to the gene ERC2 located at 3.14 Mbp on GL831196.1 of Nile tilapia. The flanking sequence of Ebr00702FRA had a significant similarity to SRPK3 gene located at the position of 0.34 Mbp on GL831387.1 of Nile tilapia. Marker EguSTR119DB and Ebr00092FRA showed no hits within any of the whole genome assembled species in this experiment.

128

Discussion

QTL detection and comparative genome gives us a new insight into identify genes involved in the QTL region (Doust et al. 2004). In the present study, based on comparative genome results, I did a search of potential candidate genes within the major candidate QTL region obtained from simple interval mapping. Three of the flanking sequences of maker

Ebr00702FRA, Ebr00314FRA and Ebr00153FRA showed significant synteny with gene

PRICKLE2, ERC2 and SRPK3, respectively. PRICKLE genes that had a homologue to

Ebr00702FRA encode the planar cell polarity (PCP) protein and include at least PRICKLE1 and PRICKLE2 families, both of which are expressed in the brain (Hida et al. 2011). In mouse embryonic stages, PRICKLE2 is expressed in the postmitotic neurons and has a role in regulating positive neurite formation during brain development (Okuda et al. 2007). In zebrafish, PRICKLE2 and PRICKLE1 regulate cell movement in the early embryonic stages during gastrulation (Veeman et al. 2003). The function of PRICKLE2 has also been reported in adult mouse which is closely associated with the postsynaptic density (PSD) fraction in the brain (Hida et al. 2011). ERC2 that had a homologue to Ebr00314FRA interacts with other proteins, such as Piccolo and Bassoon (Jin and Garner 2008). ERC2 may have organizational and functional role in neurotransmitter release (Kiyonaka et al. 2012). The most remarkable founding is that SPRK3 gene that showed a homologue to Ebr00153FRA has a directly role in muscle growth. Serine/arginine protein kinases (SRPK) family has function in phosphorylation of serine/arginine repeat-containing proteins (Xu et al. 2011). SRPK3 is one of the genes belonging to this family (Giannakouros et al. 2011). SRPK3 is specifically expressed in the heart and skeletal muscle from embryogenesis to adulthood, which plays a main role in muscle growth and development in human and mouse (Xu et al. 2011;

Bassel-Duby and Olson 2006). In pig, the high expression of SRPK3 in skeletal muscle and heart is in accordance with the research mentioned above. Considering the importance of the potential candidate genes located in the major QTL region affecting BW, especially SRPK3 gene, further cloning and functional analysis are required. However, in order to isolate genes 129

` involving growth performance and understand the genome basis of QTL region, construction of the high density genetic linkage map and fine mapping the QTL region are required before comparative analysis of candidate genes.

130

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Doust AN, Devos KM, Gadberry MD, Gale MD, Kellogg EA (2004) Genetic control of

branching in foxtail millet. Proc Natl Acad Sci USA 101:9045-9050

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131

Conclusion

132

In this experiment, I constructed genetic linkage map for QTL and comparative genome analysis. Considering a part of the isolated makers in this study also displayed polymorphisms in other five cross species, these results could assist population or genetic linkage map research in these species. Generally, sex-specific maps seem to be more precise in QTL detection and genetic breeding programs. Because some significant QTL may be identified in one sex map due to the differences of recombination as well as the association relationship between genotype and traits. Also, marker order can be checked by comparing sex-specific maps. Thus, I constructed sex-specific maps in this study. Taking account of the body shape of kelp grouper, BW and K seem to be the most desirable traits for being improved. This results are the first step for initial locating QTL affecting growth performance. The conserved QTL among species (such as growth related QTL) detected in Salmonidae, seem to infer that this research in kelp grouper may contribute to other grouper breeding programs. Furthermore, comparative genome analysis of kelp grouper gives us a primarily information on kelp grouper genome evolution. By further gene cloning and expression, perdition of candidate genes involved in major candidate QTL region will help to identify the potential genes influencing growth performance.

133

Acknowledgements

134

First, I would like to thank my supervisor Associate Professor T. Sakamoto for his guidance, support, trusting me and giving me the opportunity to participate in this great project.

I would also like to thank Professor N. Okamoto and Dr. A. Ozaki for their patience to train a foreigner student and let me know how to think and judge as a scientist researcher, Dr.

K. Fuji for her great tenacity and perseverance during the experiments and daily life, which have been influenced me so much, Mrs. K. Kubo for her selfless assistance during the whole experiments, Professor M. Sano, Dr. M. Takagi, Dr. Y. Shigenobu, Dr. T. Sugaya and Dr. Y.

Nakamura for their suggestions as well as providing sequences information, Dr. E. Koshimizu,

Mr. T. Mori, Mrs. Fujii and all the members of the laboratory of aquatic physiology for giving me a relaxed environment to enjoy this study, and Dr. H. Yamashita for his assistance to deal with all the samples.

I would like to thank all my colleagues at the laboratory of aquatic pathology, especially to those who supported me during the study: Mr. S. Kubota, Miss. X.Z. Weng, Dr. T. Koyama,

Dr. R. Sudo, Dr. T. Utino, Mr. K. Akita, and Mr. R. Kumagai.

And also thanks to my supervisor in China, Professor T.X. Gao and Prodessor X.M.

Zhang for let me know the enchantment of aquaculture and fishery, my parents, my girlfriend for allow me to concentrate on study without considering anything else.

Finally, special thanks to the CSC scholarship and all my friends for encourage and support me during the study period in Japan.

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