Heritability Estimates and Genetic Correlation for Growth Traits and LCDV Susceptibility in Gilthead Sea Bream (Sparus Aurata)

fishes

Article Heritability Estimates and Genetic Correlation for Growth Traits and LCDV Susceptibility in Gilthead Sea Bream (Sparus aurata)

Carlos Carballo 1,2, Hyun Suk Shin 3, Concepción Berbel 1, Maria Jesús Zamorano 3, Juan Jose Borrego 2 , Eva Armero 4, Juan Manuel Afonso 3 and Manuel Manchado 1,5,*

1 IFAPA Centro El Toruño, Junta de Andalucía, Camino Tiro Pichón s/n, 11500 El Puerto de Santa María, Cádiz, Spain; [email protected] (C.C.); [email protected] (C.B.) 2 Departamento de Microbiología, Campus de teatinos, Universidad de Málaga, 29071 Málaga, Spain; [email protected] 3 Aquaculture Research Group (GIA), IU-ECOAQUA, Universidad de Las Palmas de Gran Canaria, Crta. Taliarte s/n, 35214 Telde, Spain; [email protected] (H.S.S.); [email protected] (M.J.Z.); [email protected] (J.M.A.) 4 Animal Production group, Universidad Politecnica de Cartagena, Paseo Alfonso XIII, 48, 30203 Cartagena, Spain; [email protected] 5 “Crecimiento Azul”, Centro IFAPA El Toruño, Unidad Asociada al CSIC”, 11500 El Puerto de Santa María, Cádiz, Spain * Correspondence: [email protected]; Tel.: +34-671-532-088

Received: 26 October 2019; Accepted: 19 December 2019; Published: 25 December 2019

Abstract: The lymphocystis disease (LCD) is a viral infection with a high economic impact in gilthead sea bream aquaculture. In this study, genetic estimates associated with lymphocystis disease virus (LCDV) disease susceptibility and growth were determined in sea bream juveniles. Two fish batches (named batch 1 and batch 2) were built from mass spawning and reared under industrial conditions until disease outbreak. At the moment of the sampling (n = 500 specimens for each batch), all animals had the typical LCDV lesions in the skin. For phenotyping, animals were weighted and photographed for image analysis (surface covered and lesion intensity). LCDV DNA copies were quantified in the liver by qPCR. Batch 1 had a higher surface covered and lesion intensity than batch 2, and the body caudal region was the lowest affected region in both batches. The average LCDV DNA copies in liver were higher in the batch 1 than batch 2, and they were positively correlated with severity index (SI) categories (r2 = 0.90–0.94). The total number of families evaluated were 150 and 128 for batch 1 and batch 2, respectively, with a high bias in offspring contribution by family and broodstock. Heritabilities for weight and length were 0.18 and 0.14 in batch 1 and 0.06 and 0.05 in batch 2, respectively. Heritability for the number of viral DNA copies was low (<0.08) in both batches. Heritabilities for SI in binary scale were 0.32/0.33 and 0.21/0.24 (underlying liability/Bayesian approach) for batch 1 and batch 2, respectively. Genetic correlations were very high and positive when growth traits (weight and length) or disease traits (LCDV DNA copies and SI) were compared. In contrast, the genetic correlations between growth and disease traits were moderate–high and positive in the batch 1 but negative in batch 2. These results indicate the genetic selection for LCDV susceptibility and growth is feasible in sea bream juveniles, although estimates are highly dependent on the age. The information provided is relevant to designing selective breeding programs in sea bream.

Keywords: sea bream; LCDV; diseases; genetic selection

Fishes 2020, 5, 2; doi:10.3390/ﬁshes5010002 www.mdpi.com/journal/ﬁshes Fishes 2020, 5, 2 2 of 12

1. Introduction The lymphocystis disease (LCD) is a highly contagious viral infection responsible for high economic losses in the aquaculture industry worldwide [1]. The causative agent is the lymphocystis disease virus (LCDV) that belongs to the genus Lymphocystivirus, family Iridoviridae. This virus is hosted in the infected fish for long periods causing no clinical Iridoviridae signs (known as asymptomatic carriers) until host immunocompetence decreases due to different factors such as temperature shifts, grading operations, transport or high tank densities. Then, the virus actively multiplies in host cells giving rise to the typical lesions (named lymphocysts) consisting of irregularly shaped, randomly distributed white masses in the integumentary surfaces that in severe infections aggregate in nodular structures [2]. Experimental challenges have demonstrated that at least three weeks after LCDV injection are required for the observation of clinical signs [1,3,4]. Once the lesions appear, the disease spans for approximately 20 days, the time required for the hypertrophic dermal cells to mature and break resulting in high morbidity but low mortality rates unless secondary infections occur [2,3,5,6]. In spite of being a self-limiting benign process [3], LCDV infection has a high economic impact in hatcheries due to the important delay in fish growth, reducing feed conversion rates and making fish unavailable for commercialization due to external lesions and the lack of acceptance by the consumers. Several approaches have been established to control LCDV outbreaks in the hatcheries in the absence of efficient commercial vaccines. The most widespread approach is the monitoring and removal of asymptomatic carriers by using highly sensitive diagnostic methods [7,8]. This strategy has been successfully applied to prevent vertical transmission, but it requires a continuous evaluation of broodstocks and does not prevent horizontal transmission. A second approach is the use immunostimulants supplied through the diet to enhance immune response and block virus replication [9,10]. This strategy is especially useful when stressful operations in the hatcheries are planned and preventive measures can be implemented. A third approach is genetic selective breeding for resistance lineages. In Paralichthys olivaceous, a major locus associated with resistance against LCDV genotype II was identified [11] and used for the design of marker-assisted breeding programs and LCDV-resistant broodstocks [12]. This latter strategy has been revealed as one the most sustainable strategies to reduce and minimize the impact of LCDV outbreaks in aquaculture, although it requires evaluation of genetic variation in species-specific populations. The gilthead sea bream (Sparus aurata) is one the most cultured fish species in the Mediterranean basin. This species is infected by genotype VII, which is frequently observed in other Mediterranean species such as Senegalese sole [13,14]. LCDV outbreaks are recurrently observed every year and, occasionally, associated with high mortalities [3,15]. Currently, most ongoing genetic programs for this species are mostly focused on the improvement of growth, morphology and carcass quality [16–19]. Genetic estimates for disease resistance were only reported for the bacterial pathogen Photobacterium damselae subsp. piscicida [20,21]. However, the genetic variation controlling susceptibility to LCDV in sea bream remains still unexplored. This study aimed to estimate genetic parameters (heritabilities and genetic correlations) for LCDV susceptibility (as evaluated by the number of DNA viral copies and the severity of lesions as function of surface covered and intensity) and growth (weight and length) in gilthead sea bream. The results are the first step to create new genetically-improved broodstocks with a lower susceptibility to this disease that can enhance the sustainable production of this important aquacultured species.

2. Results

2.1. Biometric Data Two ﬁsh experimental batches (batch 1 and batch 2) were evaluated for LCDV susceptibility after a disease outbreak in a commercial hatchery. These ﬁsh batches were built by collecting the eggs during four consecutive days (4DL model) for family production from three sea bream broodstocks, and they were always managed as a single unit under the same culture conditions from larval stages Fishes 2020, 5, x FOR PEER REVIEW 3 of 13 Fishes 2020, 5, 2 3 of 12 0.5 g for batch 1 (~80 days post-hatch—dph) and 3.8 ± 1.1 g for batch 2 (~140 dph) (p < 0.05; Figure Fishes 2020, 5, x FOR PEER REVIEW 3 of 13 1a). Average length was 3.8 ± 0.4 cm for batch 1 and 5.3 ± 0.4 cm for batch 2 (p < 0.05; Figure 1b). until disease outbreak and sampling. At the moment of disease outbreak, average weight was 1.3 0.5 ± 0.5g for g for batch batch 1 (~80 1 (~80 days days post-hatch—dph) post-hatch—dph) and and 3.8 3.81.1 ± 1.1 g for g for batch batch 2 (~140 2 (~140 dph) dph) (p < (p0.05; < 0.05; Figure Figure1a). ± 1a).Average Average length length was was 3.86 3.80.4 ± cm0.4 forcm batchfor batch 1 and 1 and 5.3 5.30.4 ± 0.4 cm7 cm for for batch batch 2 (p 2< (p0.05; < 0.05; Figure Figure1b). 1b). ± * ± * 5 6 6 7 5 4 * * 6 5 4 3 5 4 3 2 4 Weight (g) 3 2 Length (cm) Length 1 3 2 1 Weight (g) 2 0 (cm) Length 0 1 batch1 batch2 1 batch1 batch2

0 0 (a) (b) batch1 batch2 batch1 batch2 Figure 1. Weight (a) and length (b) for batch 1 and batch 2. The mean ± standard deviation is indicated (total n = 498 for each batch). (Asteriska) denotes significant differences between(b) batches.

FigureFigure 1. 1. WeightWeight ( (aa)) and and length length ( (bb)) for for batch batch 1 1 and and batch batch 2. 2. The The mean mean ± standardstandard deviation deviation is is indicated indicated 2.2. Disease Phenotyping ± (total(total nn == 498498 for for each each batch). batch). Asterisk Asterisk denotes denotes significant significant differences differences between between batches. batches. All sampled animals had external skin lesions compatible with the LCDV infection (100% 2.2.morbidity).2.2. Disease Disease Phenotyping PhenotypingTo quantify the percentage of surface covered by lesions and their intensity, each animal was AllphotographedAll sampled sampled animals animals and later had had analyzed external external by skin skinimage lesion lesions anals ysiscompatible compatible for three with withregions the the (R1–R3)LCDV LCDV infection infection(see Section (100% (100% 4.2 morbidity).andmorbidity). Figure S1).To To quantify quantifyPhenotype the the data percentage percentage for surface of of surface surfaceand intensit co coveredveredy traits by by lesions lesionsare depicted and and their their in Figure intensity, intensity, 2. Wilcoxon each each animal animal test wasshowedwas photographed that surface andand covered laterlater analyzed analyzedin batch by 2by was image image significantly analysis analysis for forlower three three than regions regions batch (R1–R3) (R1–R3)1 (p < (see 0.05; (see Section average Section 4.2 2.55and4.2 andandFigure Figure2.49 S1). for S1). Phenotypebatch Phenotype 1 and data batch data for 2, for surfacerespectively). surface and and intensity intensitAnalysisy traits traitsof the are are body depicted depicted region in in revealed FigureFigure2 2. .that WilcoxonWilcoxon the surface test showedofshowed regions that that 1 and surface 2 was coveredcovered more inaffectedin batch batch 2(2.73 2 was was ± significantly 0.47significantly and 2.66 lower lower± 0.55) than than than batch batchregion 1 ( p1 < 3( p(2.270.05; < 0.05; average± 0.77) average (p 2.55 < 0.05)2.55 and andin2.49 batch 2.49 for batchfor1 (Figure batch 1 and 12) and. batch In batchcontrast, 2, respectively). 2, respectively). a gradient Analysis from Analysis region of theof 1 the (2.86 body body ± region 0.35) region to revealed regionrevealed 3 that (1.92that the the± surface0.83) surface (p of< 0.05)regions was 1 anddetected 2 was in more batch a ff2.ected Lesion (2.73 intensities0.47 and were 2.66 also0.55) significantly than region (p < 30.05) (2.27 higher0.77) in (p batch< 0.05) 1 of regions 1 and 2 was more affected (2.73± ± 0.47 and 2.66± ± 0.55) than region 3 (2.27 ±± 0.77) (p < 0.05) thanin batch batch 1 (Figure2 (average2). In1.9 contrast, ± 0.7 vs. 1.5 a gradient ± 0.6) (Figure from region2). No differences 1 (2.86 0.35) in intensity to region among 3 (1.92 regions0.83) were (p < in batch 1 (Figure 2). In contrast, a gradient from region 1 (2.86 ± 0.35) to region 3 (1.92 ± 0.83) (p < 0.05)observed0.05) was (1.79–1.93 detected inin for batchbatch batch 2. 2. Lesion1 Lesion and 1.4–1.6 intensities intensities for batch were were also2). also significantly significantly (p <(p0.05) < 0.05) higher higher in batch in batch 1 than 1 batch 2 (average 1.9 0.7 vs. 1.5 0.6) (Figure2). No di fferences in intensity among regions were than batch 2 (average ±1.9 ± 0.7 vs. 1.5± ± 0.6) (Figure 2). No differences in intensity among regions were observedobserved (1.79–1.93 (1.79–1.93 for for batch batch 1 1 and and 1.4–1.6 1.4–1.6 for for batch batch 2). 2).

4 4 batch1 batch2 batch1 batch2 aaA B b 43 C 43 batch1 batch2 batch1 batch2 aaA B b 32 C 32 Surface Intensity

21 21 Surface Intensity

10 10 R1 R2 R3 R1 R2 R3

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Figure 2. RatesRates of of surface surface covered covered ( (aa)) and and lesion lesion intensity intensity ( (bb)) for for regions regions (R) (R) 1, 1, 2 2 and and 3 3 in in batch batch 1 1 and and batch 2. The The dashed dashed (line a) indicates the maximum rate value. Letters Letters indicate indicate(b )significant signiﬁcant differences diﬀerences between regions for batch 1 (lowercase) or batch 2 (uppercase). Mean standard deviation is indicated. Figure 2. Rates of surface covered (a) and lesion intensity (b) for regions± (R) 1, 2 and 3 in batch 1 and batch 2. The dashed line indicates the maximum rate value. Letters indicate significant differences

Fishes 2020, 5, x FOR PEER REVIEW 4 of 13

between regions for batch 1 (lowercase) or batch 2 (uppercase). Mean ± standard deviation is indicated. Fishes 2020, 5, x FOR PEER REVIEW 4 of 13 To better characterize the genetic variation and the correlations between productive traits, the severitybetween index regions (SI) was for usedbatch to 1 classify(lowercase) the oranimal batchs 2into (uppercase). four categories: Mean ±Weak, standard moderate, deviation severe is or Fishes 2020, 5, 2 4 of 12 veryindicated severe (Figure. 3). The average SI was 5.0 ± 2.6 and 3.9 ± 2.2 for batch 1 and batch 2, respectively. In batch 1, 60% of fish were considered as severe or very severe infected and this percentage dropped to 40%ToTo inbetter better batch characterize characterize 2 (Figure 3). the the genetic genetic variation variation and and the the correl correlationsations between between productive productive traits, traits, t thehe severityseverity index index ( (SI)SI) was was used used to to classify classify the the animals animals into into four four categories: categories: W Weak,eak, moderate, moderate, severe severe or or veryvery severe severe ( (FigureFigure 33).). TheBatch1 average SI was 5.05.0 ± 2.62.6 and and 3.9 3.9 ± 2.22.2 Batch2 for for batch batch 1 1and and batch batch 2, 2, respectively respectively.. ± ± InIn batch batch 1 1,, 6 60%0% of of fish fish were were considered considered as as severe severe or or very very severe severe infected infected and and this this percentage percentage dropped dropped toto 4 40%0% in in batch batch 2 2 ( (FigureFigure 33).). weak Very severe weak Very severe 11% 10% 8% Weak 23% Batch1 Batch2 Moderate Moderate Severe Severe 29% 30% Very severe Moderate Very severe weak weak 52% Very severe 11% 10% 8% Weak Severe23% Moderate 37% Moderate Severe Severe 29% 30% Very severe Moderate 52% Severe 37% Figure 3. Severity index (SI) categories in batch 1 and batch 2. The percentages for the four categories are indicated. The dashed line indicates the binary classifaction as low (weak and moderate) and high (severe and very severe) susceptible fish. Figure 3. Severity index (SI) categories in batch 1 and batch 2. The percentages for the four categories are indicated. The dashed line indicates the binary classifaction as low (weak and moderate) and high 2.3. QuantificationFigure(severe 3. and Severity very of severe)Viralindex DNA (SI susceptible) categories Copies fish. in batch 1 and batch 2. The percentages for the four categories are indicated. The dashed line indicates the binary classifaction as low (weak and moderate) and high Viral DNA copies were quantified in the liver of fish from batch 1 and batch 2 (Figure 4a). The 2.3. Quantification(severe and very of severe) Viral DNA susceptible Copies fish. average number of LCDV copies was 9.2 × 107 ± 7.2 × 108 µg total DNA−1 in batch 1 and 6.3 × 105 ± 5.9 × 106Viral µg total DNA DNA copies−1 in were batch quantified 2. Interestingly, in theliver a high of fishand frompositive batch correlation 1 and batch between 2 (Figure the4 a).average The 2.3. Quantification of Viral DNA Copies 7 8 1 5 averagenumber numberof viral DNA of LCDV particles copies in was liver 9.2 and10 the SI7.2 categories10 µg ( totalr2 = 0.90–0.94) DNA− in was batch determined 1 and 6.3 (Figure10 6 1 × ± × × ± 5.94b). Viral10 µ DNAg total copies DNA −werein batchquant 2.ified Interestingly, in the liver a of high fish and from positive batch correlation1 and batch between 2 (Figure the 4a). average The × averagenumber number of viral DNAof LCDV particles copies in liverwas 9.2 and × the107SI ± 7.2 categories × 108 µg (r total2 = 0.90–0.94) DNA−1 in was batch determined 1 and 6.3 (Figure× 105 ± 45.9b). × 106 µg total DNA−1 in batch 2. Interestingly, a high and positive correlation between the average 12 2 number of viralbatch1 DNA particles in liver and the SI categories (r = 0.90–0.94) was determined (Figure 9 batch1 4b). batch2 10 8 batch2 A) 7 B) 8 12 9 6 batch1 9 batch1 6 5 batch1 batch2 8 batch2

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i 7 s

4 i

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C 3 Weak Moderate Severe Very severe

L g

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2 l 2 o l 1 (a) 1 (b) 0 0 0 2 4 6 8 0 Weak Moderate Severe Very severe FigureFigure 4.4. Lymphocystis disease virus (LCDV) DNA copies in logaritmicWeak M scaleodera t fore batch Sever e1 and Ve rbatch y sever e2. ((aa)) DNADNA copiescopies asas functionfunctionWeigh oftof weight;weight; ((bb)) DNADNA copiescopies asas functionfunction ofof fourfour SISI categories.categories. 2.4. Parental Contribution( anda) Genetic Estimates (b)

FigTheure 95.9% 4. Lymphocystis of the progeny disease in virus batch (LCDV 1 were) DNA assigned copies toin onelogaritmic breeder scale and for 86%batch to 1 and a unique batch 2 parent. pair.(a These) DNA figurescopies as were function 93.4% of weight; and 84.0% (b) DNA in batchcopies 2.as function The total of numberfour SI categories. of families were 150 and 128 for batch 1 and batch 2, respectively with the 87% offspring assigned F2 broodstock, 9.7% to broodstock F1 + F2 and 3.3% to the non-selected control broodstock. A total of 54 out of the 82 breeders contributed offspring although with a high bias in contribution percentages (Figure S2). The reconstructed breeder sex ratio contributing offspring was 1M:2.8F and 1M:1.6F for batch 1 and batch

Fishes 2020, 5, x FOR PEER REVIEW 5 of 13

2.4. Parental Contribution and Genetic Estimates The 95.9% of the progeny in batch 1 were assigned to one breeder and 86% to a unique parent pair. These figures were 93.4% and 84.0% in batch 2. The total number of families were 150 and 128 for batch 1 and batch 2, respectively with the 87% offspring assigned F2 broodstock, 9.7% to broodstock F1 + F2 and 3.3% to the non-selected control broodstock. A total of 54 out of the 82 breedersFishes 2020 ,contributed5, 2 offspring although with a high bias in contribution percentages (Figure S2).5 The of 12 reconstructed breeder sex ratio contributing offspring was 1M:2.8F and 1M:1.6F for batch 1 and batch 2, respectively. Males showed a higher bias (p < 0.05) in offspring contribution per breeder than in females2, respectively. with maximal Males showed percentages a higher ranging bias (p between< 0.05) in 31% oﬀspring and 51% contribution for batch per 1 breeder and batch than 2, in respectivelyfemales with (9% maximal and 16%, percentages respectively, ranging in females) between. The 31% analysis and 51% of for SI batchand the 1and number batch of 2, LCDV respectively DNA copies(9% and by 16%, family respectively, indicated a in large females). variation The that analysis was even of SI more and the evident number in batch of LCDV 2 (Figure DNA 5). copies The bySI rangedfamily indicatedfrom 1.7 ato large 9 in variationboth batches that wasand eventhe lo moreg number evident of in viral batch DNA 2 (Figure copies5). between The SI ranged 4.6–7.9 from (in logarithmic1.7 to 9 in both scale) batches in batch and 1 the and log 1.8–6.2 number in the of viralbatch DNA 2. copies between 4.6–7.9 (in logarithmic scale) in batch 1 and 1.8–6.2 in the batch 2.

Batch1 Batch2 9 9 8 8 7 7 6 6 5 5 4 4 3 3 2 2 Log viral DNA copies Log viral DNA copies Log viral 1 1 0 0 93… 56… 54… 27… 34… 67… 98… C9 10… 65… c50 c43 c46 169… 148… 158… 109… C12 160… 279… 176… 121… 100… 155… C16 125… 208… 268… 173… 143… 237… 221…

Parents (sires and dams) F1_1 Parents (sires and dams) F1_21 F1_13

9 9 8 8 7 7 6 6 5 5 4 4 3 3 Severity index Severity index Severity 2 2 1 1 0 0 9… 10… 67… 81… 32… 54… c27 c47 c37 c53 c46 158… C20 138… Parents169… (sires197… 263… and243… dams)279… 107… C35 125… 320… C21 243… 107… 109… Parents (siresF1_1 and dams) F1_18 F1_22 F1_27 F1_21 F1_22 F1_13 F1_19 Figure 5. Variation in LCDV DNA copies in logaritmic scale and severity index of sire and dam families Figurefor batch 5. 1Variation (left panel) in andLCDV batch DNA 2 (right copies panel). in logaritmic scale and severity index of sire and dam families for batch 1 (left panel) and batch 2 (right panel). The heritability and genetic correlation estimates for weight, length, LCDV DNA copies and SI in binaryThe scale heritability (SI) are presentedand genetic in correlation Table1. Heritabilities estimates for for weight, weight length, and length LCDV were DNA 0.18 copies and 0.14and inSI inbatch binary 1,respectively, scale (SI) are andpresented they decreased in Table 1. to Heritabilities 0.06 and 0.05 for in weight batch 2.and Heritability length were for 0.18 the and number 0.14 in of batchviral DNA1, respectively, copies was and low they in both decreased batches to (0.04 0.06 and and 0.08 0.05 for in batchbatch 1 2. and Heritability batch 2, respectively). for the number of viral ToDNA estimate copies thewas genetic low in both susceptibility batches (0.04 to LCDV and 0.08 infection for batch under 1 and the batch threshold 2, respectively). model, animals were binary coded according toSI: Weak/moderate vs. severe/very severe. In the observed scale, the heritability for the binary SI was 0.20 0.10 and 0.14 0.08 for batch 1 and batch 2, respectively. When ± ± heritabilities were transformed to the liability scale, the values increased to 0.32 and 0.21, respectively. A Bayesian linear mixed model was also carried out to estimate heritability using the binary-coded LCDV susceptibility data. The Bayesian narrow-sense heritability estimate was 0.33 and 0.24 for batch 1 and batch 2, respectively, with a 95% Bayesian credibility interval for the additive genetic component of 0.12–0.67 and 0.01–0.53 (Figure6). The genetic and phenotypic correlations between the weight, length, LCDV DNA copies and SI are given in Table1. Genetic correlations were very high and positive between growth traits (weight and length) and between disease traits (number of LCDV DNA copies and SI) in both batches. However, when growth and disease traits were compared, the genetic correlations were positive and moderate–high in the batch 1 but negative in batch 2. It should be noted that for length and SI, the model converged but did not provide errors. Phenotypic correlations between weight and length were Fishes 2020, 5, x FOR PEER REVIEW 6 of 13

Table 1. Heritabilities (in bold) and the phenotypic (below the diagonal) and genetic correlations Fishes 2020, 5, 2 6 of 12 (above the diagonal). Means ± standard deviations (SD) are indicated for body weight, fork length, LCDV DNA copies and SI in binary scale (SI). high and positiveBatch and moderate1 Weight and positive betweenLength LCDVDNA DNA Copies particles andSI SI. In batch 1, the phenotypic correlationsWeight between 0.18 biometric ± 0.10 and 0.98 susceptibility ± 0.03 0.50traits ± were0.68 close 0.67 to ± zero 0.30 while in batch 2 they were low andLength negative. 0.93 ± 0.01 0.14 ± 0.09 0.34 ± 0.65 0.44 ± 0.39 DNA copies −0.04 ± 0.05 −0.04 ± 0.05 0.04 ± 0.05 0.99 ± 0.35 Table 1. HeritabilitiesSI (in bold) 0.10 and ± the 0.05 phenotypic 0.03 (below± 0.05 the diagonal) 0.32 ± 0.05 and genetic 0.20 correlations± 0.10 § (above the diagonal). Means- standard deviations - (SD) are- indicated for - body weight, 0.32 fork± 0.16 length, ‡ LCDV ± DNA copies andBatch SI in 2 binary scaleWeight (SI). Length DNA Copies SI Weight 0.06 ± 0.07 0.94 ± 0.12 −0.90 ± 0.64 −0.79 ± 0.65 BatchLength 1 0.89 Weight ± 0.01 0.05 Length ± 0.08 DNA−0.99 ± Copies 0.72 −0.80 SI * DNAWeight copies 0.18−0.12 ±0.10 0.05 − 0.980.16 ± 0.030.05 0.08 0.50 ± 0.080.68 0.99 0.67 ± 0.430.30 ± ± ± ± LengthSI 0.93−0.25 ±0.01 0.05 − 0.140.24 ± 0.090.05 0.20 0.34 ± 0.050.65 0.14 0.44 ± 0.080.39 § ± ± ± ± DNA copies 0.04 0.05 0.04 0.05 0.04 0.05 0.99 0.35‡ - − ± - − - ± -± 0.21 ± ±0.09 SI 0.10 0.05 0.03 0.05 0.32 0.05 0.20 0.10 § * No SD was retrieved after convergence.± § heritability± for binary SI in ±the observed scale.± ‡ heritability for binary SI in---- the liability scale. 0.32 0.16 ± ‡ Batch 2 Weight Length DNA Copies SI To estimate the genetic susceptibility to LCDV infection under the threshold model, animals Weight 0.06 0.07 0.94 0.12 0.90 0.64 0.79 0.65 were binary coded according to SI:± Weak/moderate± vs. severe/very− severe.± In the− observed± scale, the Length 0.89 0.01 0.05 0.08 0.99 0.72 0.80 * heritability for the binary SI was 0.20± ± 0.10 and 0.14± ± 0.08 for batch− 1± and batch 2, −respectively. When DNA copies 0.12 0.05 0.16 0.05 0.08 0.08 0.99 0.43 heritabilities were transformed− to the± liability −scale, the± values increased± to 0.32 and 0.21,± respectively. SI 0.25 0.05 0.24 0.05 0.20 0.05 0.14 0.08 § A Bayesian linear mixed model− was± also carried− out± to estimate heritability± using ±the binary-coded ---- 0.21 0.09 LCDV susceptibility data. The Bayesian narrow-sense heritability estimate was 0.33 ±and 0.24‡ for batch § 1* Noand SD batch was retrieved 2, respectively, after convergence. with a heritability95% Bayesian for binary credibility SI in the observed interval scale. for‡ heritabilitythe additive for binarygenetic SI componentin the liability of scale. 0.12–0.67 and 0.01–0.53 (Figure 6).

FigureFigure 6. 6.Posterior Posterior distributionsdistributions of of the the heritability heritability estimates estimates for LCDV for LCDV susceptibility susceptibility in batch in1 (red) batch 1 (red)and and batch batch 2 2(blue) (blue) generated generated from from Bayesian Bayesian MCMCglmm MCMCglmm models. models. Dashed Dashed lines lines correspond correspond to to distributiondistribution modes. modes.

3. DiscussionThe genetic and phenotypic correlations between the weight, length, LCDV DNA copies and SI are given in Table 1. Genetic correlations were very high and positive between growth traits (weight andSelective length) breeding and between for diseasedisease resistancetraits (number is considered of LCDV DNA as a copies sustainable and SI) approach in both batches. to support aquacultureHowever, growth. when growth Previous and disease studies traits in fish were demonstrated compared, the thatgenetic heritabilities correlations for were disease positive resistance and traitsmoderate–high oscillate from in moderatethe batch 1 tobut high, negative and in hence batch they 2. It should can be be incorporated noted that for to length breeding and SI, programs the to minimizemodel converged fish losses but anddid not enhance provide fish errors. welfare Phenotypic [22]. Incorrelations sea bream, between genetic weight selection and length programs have focused mainly on growth, morphology and carcass quality traits [16–18,23]. To date, only heritabilities for fish survival after challenging with the pathogenic bacteria P. damselae subsp. piscicida were estimated, ranging from 0.12–0.28 [20,21]. In the case of LCDV, previous studies in P. olivaceous demonstrated that marker-assisted selection programs were successful to control the LCDV-C (genotype II) disease outbreaks [12]. In spite of the high incidence of LCDV in sea bream hatcheries, no report about the genetic variance for resistance is still available in part due to the difficulty to experimentally Fishes 2020, 5, 2 7 of 12 reproduce the disease, highly dependent on environmental conditions and fish immunological status. In the present study, two fish batches generated by mass spawning from three broodstocks were produced in a commercial hatchery in which LCDV outbreaks were previously reported. In both fish batches, the same environmental conditions under standard production procedures were carried out except for grading operations. A cross-sectional model was followed and fish were sampled for phenotyping and genotyping just when typical LCDV skin lesions were evident, assuming that LCDV infections occurred at least three weeks earlier [3]. As LCDV outbreaks are benign infections with low mortality rates [2,3,5,6], the measurement of traits associated to disease susceptibility should be carried out by quantifying the degree of clinical signs, such as body surface covered by lesions and their intensity. In our study, no mortality was observed at the sampling time, although all animals had the typical LCDV lesions (Figure S1). To quantify the infection degree, an image analysis was carried out identifying a high variability in the body distribution and intensity of the lesions. Moreover, the numbers of LCDV DNA copies were calculated to determine the correlation with the severity of clinical signs. The qPCR analysis confirmed that all animals were positive to viral MCP protein [8], as expected by the lesions, although with a huge range of variation in viral loads. Moreover, the high correlation (>90%) between LCDV DNA copies and the four SI categories confirmed this index is a good indicator of viral replication. It should be noted that although the liver is not the target organ for LCDV viral replication, this virus is able to replicate on it before spreading in integumentary system [3,14,24]. The selection of this organ appears also as a key point to precisely quantify DNA copies to prevent cross-contaminations between skin lesions in highly infected fish populations. The reconstructed familial structure revealed a high variance in the offspring contribution, a feature previously reported for mass-spawning in photoperiod-controlled sea bream broodstocks [20,25]. In the present study, only 59% of breeders contributed progeny with a higher contribution of female breeders that fit to the broodstock structure established at the beginning of the breeding period. The most striking was the strong bias for offspring contribution between F2 and the control broodstocks in spite of containing a similar number of breeders. Although the weight of breeders (average 1875 240 ± vs. 731 144 for F2 and control, respectively) could be a major factor behind the differences in egg ± production, the quadratic relationship reported for parental weights and progeny production [25] does not fully support this hypothesis. We cannot exclude that selective breeding for growth in F2 could also indirectly improved relative fecundity, a hypothesis that needs to be tested. Heritability estimates for the hepatic number of LCDV DNA copies were almost negligible in both batches (0.04 and 0.08), but they showed a high genetic correlation with SI (>0.99). Nevertheless, the heritability in the liability scale for binary SI was estimated to be 0.32–0.33 and 0.22–0.24 for batch 1 and batch 2, respectively, indicating that this index could be a useful trait to evaluate the genetic susceptibility to LCDV. The heritabilities were moderate but similar to those reported for nodavirus resistance on the liability scale in the European sea bass (0.26 0.11) [26] or against P. ± damselae subsp. piscicida in sea bream (0.12–0.28) [20,21], supporting the idea that selective breeding for LCDV susceptibility is feasible. Previous reports indicated that heritabilities for furcal length in juvenile sea bream specimens are moderate (h2 = 0.31 0.07 for fish of 6.6 cm in length and age 130 dph [23] and h2 = 0.38 0.08 for ± ± fish of ~2.3 cm in length and age 110 dph [20]. For weight, Navarro, Zamorano, Hildebrandt, Ginés, Aguilera and Afonso [23] showed that heritability at age 130 dph was 0.28 0.07. Although the fish ± weight and length values in the present study are closer to those reported by Navarro et al. (2009), our heritability estimates are still a bit lower for both traits (0.18 and 0.14 for batch 1 for weight and length, respectively, and very close to zero in batch 2). These lower genetic estimates could be due to the energy reallocation mediated by LCDV from somatic growth to virus replication and fibroblast hyperplasia in the integumentary tissues. Moreover, the heritability differences between batches with different age, weight and SI suggest that bigger fish can mobilize energy towards the immune system response to fight against the LCDV infection masking the genetic effects on growth. Supporting this Fishes 2020, 5, 2 8 of 12 hypothesis are the genetic correlations between growth traits (weight and length) and the SI in both batches: Positive and high in batch 1 but negative in batch 2. One major constraint in this study is the lack of longitudinal information to span whole infection period, but the sampling of two aged batches with contrary genetic correlations indicates that susceptibility is highly dependent on fish age. Resistance to viral diseases is generally negatively correlated with weight [26,27]. In sea bream, the resistance to P. damselae subsp. piscicida was positively correlated to fork length, although the authors could not explain if the association was due to the survival time or the weight itself [20]. In our study, a high variation in weight was found within each batch, and the differences in genetic correlation seem to be more associated to development and a putative enhancement of immunocompetence than size itself, which allows fish to better deal with this benign infection. According to this hypothesis a mixed selection index that combines length and SI could be useful for selective breeding of superior animals, preserving growth potential but limiting the viral replication and phenotypic lesions.

4. Materials and Methods

4.1. Animals Three broodstocks hosted at center IFAPA El Toruño (El Puerto de Santa María, Spain) belonging to the Spanish genetic breeding program PROGENSA® were used for family production: (a) Non-selected animals or control broodstock (52 breeders, 4 years old); (b) F1 + F2 broodstock that included animals of two 1st (females) and 2nd (males) generations selected for growth (30 breeders; 7 years old in the case of females and 4 years old for males); (c) F2 broodstock that included only animals selected for growth of the 2nd generation (57 breeders; 4 years old). The female/male ratio was approximately 2:1 in the tanks. The three broodstocks were under a controlled photoperiod (8L:16D) to synchronize maturation and egg release that was initiated at the beginning of December 2016. During this period, animals were fed ad libitum Vitalis Cal (Skretting), and egg production was monitored daily. When total egg production became stable, two egg batches were established: One at the end of February and another in early April 2017. In both cases, eggs from the three broodstocks were collected and pooled for 4 consecutive days to maximize family production according to the 4DL model (Elalfy et al., unpublished). Incubation was carried out in cylinder conical tanks (1000 L) at a density of 500–1000 larvae L 1. Water conditions were as follows: Temperature 19.0 C, salinity 34% and dissolved oxygen · − ◦ 6.4 mg L 1. All spawns were checked by PCR to confirm the absence of LCDV infections as previously · − reported [8]. As the LCD is very difficult to experimentally reproduce in the lab due to the highly dependence on environmental factors, viable non-hatched eggs and hatched larvae were transported to an industrial hatchery in Huelva (Spain) in which LCDV outbreaks were previously observed. Both larval batches were reared at an initial density of 100 larvae L 1 in 5 m3 tanks. Rearing protocols · − were those used in the hatchery at commercial scale, and these two batches were always managed as experimental units not graded until sampling. The LCDV outbreak occurred in June 2017 with temperature 26 ◦C and salinity 36 ppt. At the moment of the sampling, clear lesions compatible with LCDV infections were evident in the animals. As our animals were cultivated under industrial conditions and all tanks were managed in the same way, no negative tanks were available. LCDV infection was confirmed by qPCR, and the degree of lesion intensities were determined image analysis. A total of 500 animals were randomly sampled from each batch and in situ sacrificed in slurring ice to preserve external lesions and thereafter transported to center IFAPA “El Toruño” for phenotyping and samplings. The two batches were named batch 1 (eggs from April; age ~80 days post-hatch—dph) with a high number of typical lymphocysts and batch 2 (eggs from February; ~140 dph) with less prominent lesions but all characteristic of LCDV infection.

4.2. Data Collection and Image Analysis All animals were handled under strict biosecurity measures to avoid virus propagation in the facilities. All animals were photographed individually using a Canon EOs1300D camera following Fishes 2020, 5, 2 9 of 12 the methodology previously established in PROGENSA® [19]. Then, animals were weighted and individually frozen at 20 C for later tissue sampling. All procedures were authorized by the Bioethics − ◦ and Animal Welfare Committee of IFAPA. Image analysis was carried out using the Fiji 2.0.0-rc-69/1.52i [28]. All fish specimens were measured for furcal length and later evaluated for the extent of surface covered by lesions and their intensity by dividing the specimens in three corporal regions (Figure S1): Region 1 (R1) that spanned from the caudal part of the operculum to the end of the pectoral fin; region 2 (R2) that spanned from the end of pectoral fin to the base of the caudal fin; region 3 (R3), caudal fin. Each region was ranked as 1 if lesions were covering less than 30% of the surface, 2 if between 30 and 70% and 3 if more than 70% (Table2). The head was not considered due to the di fficulty of clearly visualizing the lesions. Moreover, lesion intensities were established for each region as 1 if they were not prominent, 2 if slightly prominent and 3 when lymphocysts were evident (Table2). All animals were independently evaluated by two researchers for phenotypic traits (surface and intensity), and both evaluations were used to build a consensus rating for each animal. Moreover, the severity index from surface (S) covered by lesions and their intensity (I) was calculated as follows: SI = S I) using the mean of the three × regions for S and I. Such an index oscillates between 1 and 9 and was used to define 4 categories for genetic analysis: Weak, moderate, severe or very severe (Table2).

Table 2. Rates (R) for LCDV lesions according to surface covered and intensity. Categories for severity index are also shown.

Surface Intensity Severity Index (SI) R % R Type R Category 1 <30 1 White layer but not prominent 1–2 weak 2 30–70 2 Slightly prominent 2–4 moderate 3 >70 3 lymphocysts 4–8 severe - - - - 8–9 very severe

4.3. Quantification of Viral DNA Although the skin is the organ with the highest number of viral DNA copies, LCDV also replicates in the liver [3,24]. This organ was selected as the target organ to quantify the viral DNA copies in each specimen, since it provides enough biomass for the nucleic acid isolation minimizing the risk of cross-contamination between individuals. Livers were aseptically dissected, individually separated in eppendorf tubes and kept frozen at 20 C until processing. All materials were cleaned with − ◦ ethanol and distilled water between animals. In the case of batch 1, total DNA was isolated using Isolate II Genomic DNA Kit (Bioline) and in the case of batch 2, DNA samples were purified using phenol/chloroform/isoamyl alcohol (Sigma) following the manufacturer’s instructions. DNA samples were treated with RNase A (Bioline) and quantified spectrophotometrically using the Nanodrop ND-8000. Absolute quantification of viral DNA copies was carried out according to the protocol specified by Valverde, Cano, Labella, Borrego and Castro [8] based on the quantification of the major capsid protein (mcp). Assays were run in a CFX96TM Real-Time System (Bio-Rad) in a 10 µL final volume containing 200 ng of DNA, 300 nM each of specific forward and reverse primers and 10 µL of iQ™ SYBR® Green Supermix (Bio-Rad). The amplification protocol used was as follows: Initial 7 min denaturation and enzyme activation at 95 ◦C, 40 cycles of 30 s at 95 ◦C and 1 min at 59 ◦C.

4.4. Genotyping and Parentage Assignment DNA for oﬀspring parentage assignment was isolated from liver as previously reported in Section 2.3. Breeders were sampled before the spawning season, and blood (~0.5 mL) was taken by puncturing in the caudal vein using a heparinized syringe, adding heparin (100 mU) and keeping at 20 C until use. DNA from breeders was extracted from blood using the Isolate II Genomic DNA Kit − ◦ and treated with RNase A (Bioline, London, UK) following the manufacturer’s instructions. Fishes 2020, 5, 2 10 of 12

Genotyping was carried out using multiplex PCR SMsa-1 and SMsa-2 [29]. PCRs were run on an ABI3130 Genetic Analyzer (Applied Biosystems, Foster City, CA, USA) and data analyzed using the Genemapper v3.8. Parentage assignment was determined using the exclusion method using Vitassign v8.2.1 [30]. The breeder gender was considered as unknown.

4.5. Statistical Analysis Comparison of rates for surface covered by lesions and their intensity was carried out by nonparametric tests Wilcoxon test or Kruskal–Wallis. Data for weight and number of LCDV DNA copies were log-transformed to achieve adjustment to normality. Statistical analysis to test phenotype differences was carried out using Prism8 (GraphPad, San Diego, CA, USA). Variance components associated with the susceptibility to LCDV were estimated separately for batch 1 and batch 2 based on bivariate linear mixed models fitted by restricted maximum likelihood (REML) in Wombat (Meyer, 2007): y = Xβ + Zu + e, where y is the observed trait, β is the vector for fixed factor (broodstock origin), u is the vector for animal random factor and e is the error. Heritability and the phenotypic and genotypic correlations were calculated for four traits: Weight, length, number of LCDV DNA copies and LCDV susceptibility as defined by SI in binary scale: 0 = weak/moderate and 1 = severe/very severe. Some runs using the weight as covariate for SI were also carried out, but no effect on genetic estimates was determined and hence was not included in the analyses. Heritability estimates for binary LCDV susceptibility in the observed scale were later transformed to the underlying liability scale according to Dempster and Lerner [31] using the formula h2 = [p(1 − p)/z2] h2 , where h2 is the heritability on the observed scale (binary trait), h2 is the heritability on × obs obs the liability scale, p is the proportion of affected individuals and z is the density of a standard normal distribution at the pth quantile. In addition, heritability estimates for binary LCDV susceptibility were also calculated using a Bayesian framework under the threshold model as implemented in the MCMCglmm R package [32]. A χ2 distribution with one degree of freedom was used as the prior distribution and we applied a probit scale and fixed the value of the residual variance to 1. MCMC ran for 1 million iterations with a thinning interval of 100 after a burn-in of 100,000 (de Villemereuil et al., 2013). Binary trait heritability was estimated as h2 = Va/(Va + 1 + 1) as described in the course notes for the program MCMCglmm [32].

5. Conclusions This study has optimized a methodology to phenotypically evaluate LCDV susceptibility and rank the animals according to SI, which is a mixed index combining surface covered by lesions and their intensity. Severity categories according to SI were highly correlated with hepatic viral DNA copies and demonstrated a moderate heritability, although they were highly dependent on the age, indicating that it could be a good trait to select animals with a lower LCDV susceptibility. The genetic correlations between growth and disease traits were moderate–high and positive in younger ﬁsh, indicating that a combined index should be established to successfully select stocks with low LCDV susceptibility and enhanced growth.

Supplementary Materials: The following are available online at http://www.mdpi.com/2410-3888/5/1/2/s1, Figure S1. Images of evaluated fish for batch 1 and batch 2. Length scale is indicated. Regions 1, 2 and 3 and the SI for each animal are indicated, Figure S2. Parental offspring contributions in batch 1 and batch 2. The circle size is proportional to the offspring family sizes. The dataset of images used to measure the LCDV suscpetibility was deposited in Zenodo with DOI: 10.5281/zenodo.3519325 Author Contributions: Conceptualization, M.M., E.A., J.M.A., M.J.Z. and J.J.B.; Methodology, M.M., J.M.A. and C.C.; Investigation, C.C., C.B., M.J.Z., H.S.S.; Data Curation, M.M., J.M.A., C.C., H.S.S.; Writing—Original Draft Preparation, M.M.; Writing—Review and Editing, E.A., C.C., J.J.B., J.M.A.; Funding Acquisition, M.M., E.A., C.B., M.J.Z. and J.M.A. All authors have read and agreed to the published version of the manuscript. Funding: This project has received funding from the European Maritime and Fisheries Fund (EMFF) through the PROGENSA III project (Mejora de la Competitividad del Sector de la Dorada a Través de la Selección Genética, JACUMAR program) and the BioBream project (Estudio genético y control sanitario de un núcleo de selección de Fishes 2020, 5, 2 11 of 12 dorada para transferencia de tecnología al sector acuícola andaluz) PP.FEM.PPA201700.14 to MM for technology transfer to the Andalusian sector. C. Carballo was supported by an INIA PhD grant (2014). Acknowledgments: We thank the hatchery involved in the project for helping us to host the animals during the trial. Conflicts of Interest: The authors declare no conflict of interest. M.M. is member of the editorial board of “Fishes journal”. This does not alter the authors’ adherence to Fishes’ policies on sharing data and materials. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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