Source: HAWAI`I PACIFIC UNIVERSITY submitted to
INVESTIGATING LOW SALINITY PERFORMANCE OF PACIFIC WHITE SHRIMP, LITOPENAEUS VANNAMEI, USING A GENOMIC APPROACH TO BENEFIT AN EMERGING US INLAND SHRIMP FARMING INDUSTRY
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
COMPLETE
Funding Source
OTHER GRANTS
Reporting Frequency
Annual
Accession No.
1023868
Grant No.
2020-70007-32413
Cumulative Award Amt.
$310,000.00
Proposal No.
2020-05176
Multistate No.
(N/A)
Project Start Date
Sep 1, 2020
Project End Date
Aug 31, 2023
Grant Year
2020
Program Code
[AQUA]- Aquaculture Research
Project Director
Moss, D.
Recipient Organization
HAWAI`I PACIFIC UNIVERSITY
41-202 KALANIANAOLE HWY
WAIMANALO,HI 96795
Performing Department
Shrimp Department
Non Technical Summary
Shrimp are the most consumed seafood in the United States with annual per capita consumption of 4.6 pounds. Despite its popularity, about 90% of shrimp consumed in the U.S. are imported. This imbalance results in an annual trade deficit in shrimp products of ~$6.4B. Thus, there is incentive to increase domestic production. However, domestic shrimp landings have remained relatively constant over the last 50 years. Likewise, US shrimp aquaculture production has remained low over the last two decades, despite a 5-fold increase in global shrimp aquaculture production over the same period.Inland shrimp farming is one sector of the US industry that has shown growth. It is estimated that there are ~100 inland shrimp farms in operation and these produce 250-500 MT/year. Inland shrimp farming is attractive for several reasons. First, inland farms have increased biosecurity, as they are located away from sources of shrimp pathogens (i.e. the coast). Second, inland farms located indoors can produce shrimp year-round. This is a huge benefit over traditional, outdoor farms in the US which typically produce only one crop per year. Inland farms are located away from coastal areas and this reduces concerns about farm effluent and coastal eutrophication. Siting farms in rural farming areas can reduce land and labor costs, while allowing fresh product to be sold directly to consumers or the food service industry if farms are within reasonable driving distance to urban markets. This increases revenue to the farmer, due to a higher sales price, and eliminates the need to compete directly with lower-value, frozen, imported shrimp. Lastly, inland farms can take advantage of existing farm infrastructure such as local feed mills and agriculture equipment providers.Despite those potential benefits, inland shrimp farming has inherent challenges, most notably high capital and operational costs. For example, most inland farms have no natural source of seawater so they are reliant on "made" seawater using natural or synthetic sea salts. Salts are expensive (~$750/ton) and can represent large startup and operational costs. The tru Shrimp Company, an inland farm in Minnesota, estimates that ~1,700 MT of salt, costing ~$1.3M, will be required at startup of their planned expansion to achieve an operating salinity of 28 psu. In addition, the farm will require ~$0.5M worth of salt annually to support normal operations. Inland farms also must abide by local effluent standards, including allowable amounts of salts in farm discharge. Thus, efforts must be made to minimize effluent (recirculation/reuse of culture water) and/or reclaim salts prior to discharge. If salt usage can be reduced significantly, then farms could realize cost savings associated with reduced salt purchases and reduced efforts in salt reclamation from effluent.Pacific white shrimp, Litopenaeus vannamei, is the most common shrimp cultured worldwide, including in the US. This is largely due to the availability of specific pathogen free (SPF), selectively bred lines. Selected lines of L. vannamei have been bred primarily for fast growth, growout survival, and reproductive traits. L. vannamei is euryhaline and farming this species in brackish water is common on traditional farms around the world, as many farms get their source water from estuaries or "tidal creeks". While juvenile and adult L. vannamei are tolerant of low salinity water (<5 psu), they generally exhibit better growth and survival at salinities >15 psu.Despite the common practice of farming L. vannamei in low salinity water, no published research exists on targeted genetic improvement of shrimp performance in reduced salinity environments. Multiple studies have shown that growth is moderately heritable and that genetic improvement for growth can be rapid; however, these studies were carried out at relatively high salinities (>20 psu).To date, genetic improvement programs for L. vannamei have largely relied on family selection and the use of SPF stocks. While this approach has been effective, it is not ideal because it does not allow for the direct evaluation of potential breeders. For example, superior animals from commercial farms cannot to be directly incorporated into a SPF breeding program due to disease concerns. Instead, selection must be based on the performance of siblings. This requires large numbers of individuals per family to be evaluated to get representative phenotypic data. Also, selection accuracy, and therefore genetic gains, of sib-selection are limited due to within-family genetic variation.Recent advances in genomics offer breeders the opportunity to improve the efficacy and efficiency of shrimp breeding programs by: 1) simplifying breeding schemes; 2) using genotypic data from commercial evaluations; 3) breeding for hard-to-measure and low heritability traits; 4) estimating and controlling for inbreeding; and 5) increasing genetic gain by improving selection accuracy through selection of breeders based on genotypic data (not phenotypes of siblings).While the development and use of genomic tools for plants and livestock have progressed rapidly, their use in aquaculture has lagged far behind. For example, global aquaculture production of L. vannamei currently is 4.5 million MT/year, with a farm gate value of ~$24B. However, there is only one published genome wide association study (GWAS) for this species. Furthermore, there are only two commercially available genetic marker arrays available and one has low marker density (6,500 markers). The Center for Aquaculture Technologies (CAT) recently developed a high-density marker chip (AquaArray HD vannamei) for L. vannamei. Critically, a "customized" version of this chip has been optimized for OI's L. vannamei population and is available to use for this project. The chip contains over 50,000 genome-wide single nucleotide polymorphisms (SNPs). The array includes high-quality and informative SNPs that are distributed across the genome. In addition, CAT has a proprietary panel of 192 SNPs for pedigree assignment and population analyses in L. vannamei.The ultimate goal of this project is to develop and distribute lines of L. vannamei which exhibit high growth and survival,under low-salinity conditions, so that inland shrimp farmers in the US can realize improved farm productivity, efficiency, and profitability. Supporting objectives of this project include: 1) conduct a GWAS for growth and survival in high (28 psu) and reduced salinity (14 psu) commercial growout environments, and 2) conduct one generation of selection using phenotypic and genomic data (i.e. genomic prediction and selection) to estimate genetic parameters both within (heritability and selection response) and across the two salinities (phenotypic and genetic correlations - G×E). These objectives address knowledge gaps in breeding for shrimp performance under reduced salinity conditions (i.e. lack of genetic parameter estimates), while using the latest advances in genomic tools for shrimp to identify valuable markers for growth and survival (within and across salinities). In addition, this project would be the first (no published studies to date) to demonstrate the implementation of genomic selection for penaeid shrimp using commercial evaluation data. This project should provide valuable data on the impacts of reducing salinity (proposing a 50% reduction) on the performance of a selected line of L. vannamei, determine what trade-offs (in genetic gain) can be expected if selection occurs at one salinity and farming occurs at another and, ultimately, if developing separate lines for high and low/reduced salinity is warranted.
Animal Health Component
80%
Research Effort Categories
Basic
20%
Applied
80%
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
30337211080100%
Knowledge Area
303 - Genetic Improvement of Animals;

Subject Of Investigation
3721 - Marine shrimp;

Field Of Science
1080 - Genetics;
Goals / Objectives
The US currently has a large annual trade deficit in shrimp products, as imports far exceed domestic production from fisheries and aquaculture. Disadvantages and liabilities associated with a large reliance on imported shrimp include: 1) no control over the supply chain; 2) limited quality control of product (e.g. contamination from banned antibiotics); 3) a large carbon footprint from shipping product from developing countries to the US; and 4) exporting jobs overseas. In the US, domestic landings of shrimp have remained relatively constant over the last 50 years, so it is unlikely domestic fisheries can significantly reduce the reliance on imports. Furthermore, domestic shrimp aquaculture has remained relatively low over the last two decades, despite global shrimp aquaculture production increasing by >5-fold over the same period. Traditional shrimp farms in the US (mostly located along the Gulf and Atlantic coasts) are highly impacted by farm-gate prices, as they compete directly with frozen, imported shrimp on the global commodities market and, thus, must have costs of production similar to foreign farmers to be competitive. This is difficult given on-going disease issues, US market conditions (land and labor costs), and regulatory/permitting hurdles. High cost of production (relative to the price of imports) is a primary reason for the lack of growth in traditional shrimp farming (new farms or farms expansion) in the US. In fact, some farms shift to other species (non-shrimp) when shrimp prices are too low.Interest in inland shrimp farming has grown rapidly over the last 10 years and an estimated 100 inland shrimp farms are currently in operation. These farms are mostly small startups and "backyard" farms; however, combined production of inland farms is estimated to be 250-500 MT/year. This is equivalent to 15-30% of total US shrimp aquaculture production. Inland shrimp farming is attractive for several reasons including: 1) increased biosecurity; 2) year-round production with multiple crops per year; 3) farms can be located away from sensitive coastal areas; 4) reducing land and labor costs; 5) direct marketing to consumers or the food service industry; and 6) using existing farm resources and infrastructure. Inland shrimp farming does have inherent challenges though, most notably high capital and operating costs. Reducing capital costs industry-wide will be difficult, as all inland farms will require buildings and filtration/recirculation systems, and solutions for capital reduction may be region specific (i.e. differences in construction design and building materials). Thus, to support the continued growth of inland shrimp farming, efforts are needed to reduce production costs.Most inland farms (with exception to a few farms using low saline groundwater), have no natural source of seawater so they are reliant on "made" seawater using natural or synthetic sea salts. High quality salts can cost >$750/ton and this, along with shrimp seed and feed, are the major input costs for an inland farm. For example, The tru Shrimp Company, an inland farm in Balaton, Minnesota, estimates that reducing salt usage by 50% (achieved by reducing salinity of culture water by 50%) at a large inland farm could save >$600,000 at startup and an additional ~$250,000/yr. While this sounds promising, a reduction in shrimp performance (growth or survival) directly attributed to reduced salinity could offset most or all savings from reduced salt usage.In addition to reducing input costs, inland farms need to have efficient production to offset high capital and operations costs. Selective breeding of Pacific white shrimp, Litopenaeus vannamei, has been effective in improving several commercially important traits, including growth. However, given the small size of the inland shrimp farming industry (in the US and globally), selection efforts have not focused on improving shrimp performance in high-density, recirculating aquaculture systems which are common at inland farms. In addition, new genomic approaches should allow breeders to improve genetic gains over those obtained through traditional selective breeding. It's estimated that using genomic information (i.e. genomic selection) could increase genetic improvement by as much as 48% compared to current industry practices. Genomic selection has proven revolutionary in driving genetic improvement in terrestrial agriculture and has been widely adopted in salmon breeding. Tremendous potential also exists in translating this approach to other aquaculture species. Recent development of genomic tools for shrimp now make genomic selection a possibility for shrimp breeding programs.The long-term goal of this project is to develop and distribute lines of L. vannamei which exhibit high growth and survival, under low-salinity conditions, so that inland shrimp farmers in the US can realize improved farm productivity, efficiency, and profitability. Supporting objectives of this project include: 1) conduct a genome-wide association study (GWAS) for growth and survival in high (28 psu) and reduced salinity (14 psu) growout environments to identify genes associated with these traits, and 2) conduct one generation of selection using phenotypic and genomic data to estimate genetic parameters both within (heritability and selection response) and across the two salinities (phenotypic and genetic correlations - G×E). These objectives address knowledge gaps in breeding for shrimp performance under reduced salinity conditions (i.e. lack of genetic parameter estimates), while using the latest advances in genomic tools for shrimp to identify valuable markers for growth and survival (within and across salinities). In addition, this project would be the first (no published studies to date) to demonstrate the implementation of genomic selection for penaeid shrimp using commercial evaluation data. This project should provide valuable data on the impacts of reducing salinity (proposing a 50% reduction) on the performance of a selected line of L. vannamei, determine what trade-offs (in genetic gain) can be expected if selection occurs at one salinity and farming occurs at another and, ultimately, if developing separate lines for high and low/reduced salinity is warranted.In addition to the two primary objectives, this project has a series of secondary objectives:Objective 1: Conduct a GWAS for growth and survival in high (28 psu) and reduced salinity (14 psu) environments under commercial growout conditions.Objective 1.1: Production of 50 families of L. vannamei (Generation 0, G0).Objective 1.2: Growout evaluation of 50 families at high (28 psu) and reduced salinity (14 psu).Objective 1.3: Genotyping and GWAS analysis.Objective 1.4: Estimation of breeding values and genetic parameters.Objective 2: Conduct one generation of selection using a genomic selection approach.Objective 2.1: Selection of breeders and the production of 50 families of L. vannamei (G1).Objective 2.2: Growout evaluation of 50 families at high (28 psu) and reduced salinity (14 psu).Objective 2.3: Genotyping and genetic analysis.Objective 2.4: Dissemination of results.
Project Methods
The project has two primary objectives, as well as a series of secondary objectives.Objective 1: Conduct a genome-wide association study (GWAS) for growth and survival in high (28 psu) and reduced salinity (14 psu) farming environments.Objective 1.1: Production of 50 families of L. vannamei. Fifty families (G0) will be produced at using broodstock selected for growout and reproductive performance (P generation). Broodstock (~400) will be stocked into four 15-m2 maturation tanks with each tank receiving ~100 males or females. Maturation stocking and mating strategies will be used to minimize inbreeding. Hemolymph samples will be collected from all broodstock during stocking and submitted for genotyping (Objective 1.3). Maturation, spawning, and larval rearing protocols will match previously published OI protocols. Briefly, natural mating will be used and mated females will be transferred into 300-L spawning tanks (1 female/tank). Viable nauplii (15K) from each spawn will be transferred to 100-L larval rearing tanks (1 spawn/family per tank). Shrimp will be transferred to 1-m2 nursery tanks at 10-d postlarvae (PL10) with each tank receiving 1,500 shrimp from a single family.Objective 1.2: Growout evaluation of 50 families at high (28 psu) and reduced salinity (14 psu). At PL15-20, 200 shrimp from each family will be randomly harvested from the nursery system, packed in labeled, family-specific bags, and shipped to a farm in Balanton, MN (tr? Shrimp). The remaining PLs will be grown to ~1 g at OI. At this point, ~300 shrimp/family will be randomly tagged with elastomer implants, with each family receiving a unique tag code. Tagged juveniles will then be combined into a common tank for growout at OI. These shrimp will serve as candidate breeders for the production of G1 families.Upon arrival at tru Shrimp, PLs will be acclimated and stocked into six 10-m2 growout tanks. The goal is to stock ~30 shrimp/family/tank. Three tanks will be operated at 28 psu and the other three will be operated at 14 psu. Tanks will be randomly assigned to salinity treatments and operated using standard protocols. When mean shrimp weight in both treatments reaches >12 g, shrimp will be harvested, weighed, and sampled.Objective 1.3: Genotyping and GWAS analysis. At harvest, all shrimp from each tank will be weighed and "binned" based on weight. Next, 800 shrimp from each tank will be re-weighed and tissue sampled (a proportional number of samples taken from each bin). A portion of these samples (300/tank), along with 400 broodstock hemolymph samples (Objective 1.1), will be genotyped using a 50K marker (SNP) array. The other 500 samples/tank will be genotyped using a 192 SNP array to determine parentage and assign individual shrimp to a G0 family.SNP genotypes and phenotypes will be used for a GWAS for growth in each environment. The methodology will use a mathematical model where population structure will be considered using significant principal components and family structure will be obtained using a SNP-generated relationship matrix. Each marker will be evaluated individually using an approximated t-test with a false discovery rate of 2%. Pre-selected markers will be further evaluated by combining them into a single model to obtain final marker effects and their significance on the population. The final markers will be selected using backward selection with a significance level of 5%. Marker-trait associations for all responses will be performed with combined data and for separately for the two salinities. This will allow us to identify significant "general" (across salinities) and salinity-specific markers.GWAS analysis for survival is more problematic as shrimp that died during growout cannot be genotyped. However, parentage will be determined for 800 randomly sampled individuals per tank and relative family contributions to the surviving population can be used as a measure of family survivals. GWAS for survival will use estimated family survivals and average family allele frequencies, computed as the mean of parental allele frequencies, and will be carried out using similar procedures as those for growth.Objective 1.4: Estimation of breeding values and genetic parameters. A series of statistical models will be used to estimate pedigree- and genomic-based breeding values. A single-trait model using pedigree information or a SNP-generated relationship matrix and phenotypic data will be used to generate EBVs and GEBVs (respectfully) for growth and survival at each salinity. These analyses correspond to BLUP and Genomic-BLUP (G-BLUP). Bivariate models using data (either growth or survival) from both salinities will be used to estimate environment-specific heritabilities (h2i), together with a Type-B genetic correlation between these environments. In addition, multi-trait models will be fitted using growth and survival data to estimate Type-A genetic correlations between traits within each salinity. All EBVs and GEBVs will be studied to determine the dynamics of the GxE and to determine stability indices that will assist with selection of candidate breeders. G-BLUP will be used to make predictions on all other genotyped, but not phenotyped, individuals (i.e. candidate breeders).Objective 2: Conduct one generation of selection using a genomic selection approach.Objective 2.1: Selection of breeders and the production of 50 families of L. vannamei. Mean family GEBVs for growth and survival will be calculated for each G0 family. Families with mean GEBVs for survival 12 g, shrimp will be harvested, weighed, and sampled.Objective 2.3: Genotyping and genetic analysis. Harvesting, binning, sampling, data collection, and genotyping procedures are the same as those in Objective 1.3.A series of statistical models similar to those in Objective 1.4 will be used to estimate EBVs and GEBVs. Mean family EBVs and GEBVs will be used to determine selection responses and realized genetic gains. These results can be used to compare selection approaches and evaluate the benefits of incorporating genomic data together with different selection strategies. In addition, mean family EBVs and GEBVs will be used to directly measure the impacts (e.g. reduction in genetic gain) of selecting for performance at a salinity different from the farming environment.Objective 2.4: Dissemination of results. Results from this project will be presented at a US-aquaculture meeting and a manuscript detailing the full methods and findings of this project will be submitted for publication to a peer-reviewed journal.

Progress 09/01/20 to 08/31/23

Outputs
Target Audience:Shrimp breeding and genetic improvement companies - This project will addresses knowledge gaps in breeding for shrimp performance under reduced salinity conditions by utilizing the latest advances in genomic tools for shrimp. Valuable markers for growth and survival will be identified by a genome-wide association study. In addition, this project will be the first to demonstrate the implementation of genomic selection for penaeid shrimp. In addition, this project will generated and utilize several statistical models and genetic parameter estimates that will benefit shrimp breeders supplying germplasm to US farmers. Inland shrimp farmers - This project will provide valuable data on the impacts of reducing salinity on the performance of a selected line of L. vannamei, determine what trade-offs (in genetic gain) can be expected if selection occurs at one salinity and farming occurs at another and, ultimately, if developing separate lines for high and low/reduced salinity will be beneficial to US farmers. Rural communities - It is estimated that there are ~100 inland shrimp farms in operation in the US (including startups and "backyard" farms) and many of these farms are in rural areas. Combined these farms produce 250-500 MT/year, which accounts for 15-30% of total US shrimp aquaculture production. Inland farms can be located away from sensitive coastal areas and this reduces/eliminates concerns about farm effluent and coastal eutrophication. Siting farms in rural farming areas can reduce land and labor costs, while allowing live or fresh product to be sold directly to consumers or the food service industry if farms are within reasonable driving distance to urban markets. This increases revenue to the farmer, due to a higher sales price, and eliminates the need to compete directly with lower-value, frozen, imported shrimp. Lastly, inland farms can take advantage of existing farm infrastructure such as large buildings (suitable for farms), local feed mills (and feed ingredients), and agriculture equipment/technology providers. Improving breeding practices and developing shrimp lines that perform well in the unique conditions of inland farms, should lead to the continued expansion of this farming sector and, ultimately, provide an economic boost to the communities that have inland shrimp farms. US consumers - Shrimp are the most consumed seafood in the US (27% of consumption), currently higher than salmon (16%) and canned tuna (15%). To support this level of consumption, the US is highly reliant on imported shrimp. The US currently imports ~660,000 MT of shrimp annually and this is valued at $6.5 billion. Foreign shrimp supplies are significantly larger than domestic supplies (fisheries and aquaculture combined) which are valued at ~$600M annually. The large reliance on imports results in a large trade deficit for shrimp products and creates incentive to increase domestic production. However, US landings of wild shrimp have remained relatively constant over the last 50 years, so it is unlikely domestic fisheries can significantly reduce the reliance on imports in the future. Global aquaculture production of shrimp has increased drastically over the last two decades, but US shrimp aquaculture production has remained relatively low over this same period. However, inland farming of shrimp is one sector of the US industry that has shown growth. This project aims to address knowledge gaps in genetics that are needed by US inland shrimp farmers (an expanding farming sector) to reduce operational costs and improve farm efficiency. Doing so should increase domestic shrimp production and reduce the trade deficit in shrimp products, while providing consumers with increased domestic options with purchasing shrimp. Changes/Problems:Survival in the 14 psu and 28 psu treatments were high for the G0 growout trial (Objective 1.2) and growth rates (by tank) were similar across the two treatments (Objective 1.2). In addition, genetic correlations (by trait) across the two salinities was high and approaching 1. This provided strong evidence that growth at 14 psu is essentially the same trait as growth at 28 psu. The same can be said for survival. Thus, in Year 2, the growout trial was repeated (Objective 2.2 - modified), but using a more extreme difference in salinity: 5 psu and 32 psu. The larger difference in salinity was anticipated to result in significant differences in performance across the two treatments (at the population and family level). These differences will aide in the estimation of genetic paremeters (e.g.. genetic correlations), as well as the impacts of selecting for performance at one salinity, but having commercial growout at the other. In addition, the benefits of GWAS selection for performance at one or both salinities can be determined. Due to operational and workforce reductions related to COVID-19, tru Shrimp was unable to assist with running of the Yr-1 and they unfortunately had to withdraw from the project. By the time tru Shrimp notified us of this, the production of shrimp families (Objective 1.1) for the Yr-1 trial was mostly complete. Thus, a new commercial partner would have been needed on very short notice (~30 days) and we felt that identifying a partner and arranging logistics on this timeline simply wasn't feasible. To keep the project on schedule, we decided the best option was to conduct the growout trials (Yr-1 and Yr-2) at Oceanic Institute (OI). Below are additional changes to the workplan: 1. Conducted trials at OI in replicate (6) 29-m2 round tanks. The number of replicate tanks was unchanged from the original research plan. 2. Test salinities remained as planned (14 psu and 28 psu) in Yr-1, but were adjusted to 5 psu and 32 psu in Yr-2. This was done because shrimp performance was essential the same across the two Yr-1 salinities (i.e. genetic correlations for growth and survival across the two salinities were approaching 1). 3. Two additional operational changes for the growout trials: (1) we used diluted natural seawater instead of aritificial seasalts; (2) instead of operating tanks on a water recirculation system, tanks were managed in a "batch exchange" manner (~5% of tank volume/tank/day). 4. Given difficulties with genotyping of growout and candidate breeder samples in Yr-1, the number of candidate breeders that were sampled was reduced slightly. In addition, family and within-family selection protocols had to be adjusted in response to: (1) delays in getting genotyping results, (2) reduced numbers of candidate breeders (high mortality associated with shrimp age), (3) little to any differences in family rankings for growth or survival across test salinities. What opportunities for training and professional development has the project provided?One graduate student and one undergraduate intern have worked on the project. Neither of these students had prior experience with shrimp spawning, larval rearing, growout or genetic sampling, but gained experience all three of the areas under the tutelage of PI Dustin Moss. How have the results been disseminated to communities of interest?Results of this project will be presented at Aquaculture America 2024 conference in February 2024 (abstract submitted and accepted). In addition, the manuscript is in prep and will be submitted to an aquaculture or genetics focused peer-reviewed journal. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Fifty-one G0 families were produced using SPF broodstock selected for growout and reproductive performance (P generation) according to methods detailed in the proposal. Shrimp (~532) from each family were stocked into six, 29-m2tanks (~87 shrimp/family/tank). Three tanks were operated at each salinity: 14 or 28 psu. At harvest, all shrimp were counted and 800/tank were randomly selected and tissue sampled. A portion of these samples (300/tank), along with broodstock hemolymph samples, were genotyped using a HD SNP array (50K). The other 500 samples/tank were genotyped using a LD SNP array (192). Parentage was determined for all 800 shrimp sampled per tank with each assigned to a G0family. An additional, ~150 shrimp/family were tagged with elastomer, with each family receiving a unique tag code. These shrimp served as candidate breeders for the production of G1families. Mean family GEBVs for growth and survival were calculated for each G0 family. Hemolymph was collected from 457 candidate broodstock and samples genotyped using the 50K array. GEBVs for growth and survival will be estimated for each sampled candidate breeders. Selected breeders (360 total) were used to produce 35 G1 families. Shrimp from each family (mean = 539) were stocked into six, 29-m2round tanks (~90 shrimp/family/tank). At harvest, all shrimp were counted and 800/tank were randomly selected and tissue sampled. A portion of these samples (300/tank), along with broodstock hemolymph samples, were genotyped using a HD SNP array (50K). The other 500 samples/tank were genotyped using a LD SNP array (192). Quality Control and Merged Final Dataset:A merged HD dataset was created including all G0 and G1 tank progeny and broodstock genotypes. Quality control metrics required less than 20% missing data for both markers and samples and a minor allele frequency of more than 2%. The final dataset consisted of 38,606 SNP mapped to theL. vannameireference genome assembly. Genetic Analyses: Statistical models were used to estimate heritability of ADG and genotype × salinity interactions using the assigned pedigree. The finalized model was then fit using genomic data using a single step GBLUP approach (ssGBLUP). The pedigree included 9675 shrimp, with genomic data available for 3639 shrimp and 38606 SNPs (after quality control). All models fit a mean effect, u, and sex as fixed effects, with environment also fit in any multivariate models, tank was included as a random effect with family and animal terms. In the multivariate model, separate environment specific residual variances were considered as there was some observed differences in the error variances in the different salinities. Sex was significant only in the 28 psu analyses. Family was included as the improvement in likelihood was significant for all salinities using the genomic model and for both salinities in the second generation using the pedigree. Including family reduced the overall narrow-sense heritability (h2) estimates as this term captures non-additive genetic effects. Without the family term, it appears that the non-additive genetic effects are partially captured by the additive genetic effects, inflating the h2. The ssGBLUP model had a higher loglikelihood for all models when compared to the pedigree model indicating a better fit to the overall data. A genetic correlation of >0.99 was found between all salinities, in the majority of cases, indicating that ADG was controlled by the same genes and had the same genetic expression in each salinity. Survival was characterized as the change in the relative proportion of families within each tank for the salinities for which the family was present. A total of 84 families were utilized, 49 in G0 and 35 in G1. The initial analyses for survival were run using a sire and dam model (separate variances). All models fit a mean effect, u, age were fit as fixed effects with tank, dam, and sire fit as random. Previously sire and dam variances were modelled using a single variance; however, allowing the two terms to have differing variances revealed significantly higher dam variances in some instances where the sire variance was close to zero (0.0442-0.1633 for dams compared to 0.0000-0.1081 for sires). As a consequence, h2 resulting from modelling the sire and dam variances separately are higher than those using a single variance. This result indicates that the selecting dams with the highest genetic merit for survival may be a viable approach to increase gains. Regardless of the model utilized the use of the genomic data resulted in a higher proportion of genetic variance captured as indicated by the higher h2. Type-B genetic correlations were calculated using both the pedigree and genomic models. The two salinities in G0 (14 & 28 psu) were found to exhibit identical trait expression. However, a slightly lower genetic correlation of 70% was found between 5 psu and 32 psu in G1, indicating that while there is a high proportion of shared genetic control there are some differences in the genes and the expression of the trait across the two salinities. Survival measured in the two generations appears to highly impacted by genotype × trait interactions indicated by the zero or negative correlation between survival for G0 (14 and 28 psu) and G1 (5 psu and 32 psu). Correlations suggest that survival measured in the two years could effectively be different traits. Type-A genetic and phenotypic correlations between survival and ADG were calculated using mean ADG per family and relative survival. A increasing positive trend relative to salinity is consistent (~0.1 at 5 psu to ~0.8 at 32 psu). This indicates that selection for ADG or survival will indirectly select for the other trait. In addition to improving model fits and increased genetic variances, the using genomic data can improve the accuracy of genetic merit estimates (i.e. selection accuracy). For ADG, the use of genomics provides a minimum of 6% improvement in the ability to predict the best candidate for selection. Additionally, the EBVs produced by the pedigree had very low variance and range [-0.00015, 0.00014] compared to the GEBV [-0.03089, 0.04133] indicating the genomics data is contributing significant more information to better rank and discriminate between candidates. Prediction accuracy for survival were negative and this was expected due to the substantial genotype by environment interactions for salinity across generations. Survival results are varied, primarily because of the different expression of the trait between generations. This means prediction using only one generation of data is not expected to accurately predict the genetic merit of the parents based on the performance of their progeny. The genomic model had more accurate predictions at 32 psu compared to 5 psu. Genetic gains are shown by comparing the genetic merit of the parents of each generation and the overall population's genetic merit (for each salinity). Gains for were clearly made for ADG (up to 20%). Unexpectedly, small gains for survival were also observed (given the different expression of survival across the two generations). Genome-wide-association study (GWAS) analysis:Harvest Weight and relative survival were used as the phenotypes for the GWAS studies. GWAS analysis for survival used the repeated relative phenotypes and all available genomic data on the parents. In total, there were 991 phenotypic records for the 141 parents. Analyses were conducted across and within salinities, and for the sexes separately. Very few significant associations were identified, none of which are significant after multiple testing correction. The GWAS analysis for harvest weight, when tank and salinity modeled as fixed effects, found only a few significant SNPs. The most promising SNP (AX-249950810) is located at the beginning of chromosome 12 but there is no indication for a significant peak at that area.

Publications

  • Type: Conference Papers and Presentations Status: Accepted Year Published: 2024 Citation: Moss, D., Buchanan, J., Verbyla, K., Gutierrez, A., Kube, P., Prochaska, J., and Wong, C. 2024. Improving Low Salinity Performance of Pacific white shrimp Litopenaeus vannamei using a genomic selection approach. Book of Abstracts, Aquaculture America, San Antonio, TX, World Aquaculture Society.
  • Type: Journal Articles Status: Other Year Published: 2024 Citation: Moss, D., Buchanan, J., Verbyla, K., Gutierrez, A., Kube, P., Prochaska, J., and Wong, C. In prep. Selection for Low Salinity Performance in Pacific white shrimp Litopenaeus vannamei using a genomic approach.


Progress 09/01/21 to 08/31/22

Outputs
Target Audience:Shrimp breeding and genetic improvement companies - This project will addresses knowledge gaps in breeding for shrimp performance under reduced salinity conditions by utilizing the latest advances in genomic tools for shrimp. Valuable markers for growth and survival will be identified by a genome-wide association study. In addition, this project will be the first to demonstrate the implementation of genomic selection for penaeid shrimp. In addition, this project will generated and utilize several statistical models and genetic parameter estimates that will benefit shrimp breeders supplying germplasm to US farmers. Inland shrimp farmers - This project will provide valuable data on the impacts of reducing salinity on the performance of a selected line of L. vannamei, determine what trade-offs (in genetic gain) can be expected if selection occurs at one salinity and farming occurs at another and, ultimately, if developing separate lines for high and low/reduced salinity will be beneficial to US farmers. Rural communities - It is estimated that there are ~100 inland shrimp farms in operation in the US (including startups and "backyard" farms) and many of these farms are in rural areas. Combined these farms produce 250-500 MT/year, which accounts for 15-30% of total US shrimp aquaculture production. Inland farms can be located away from sensitive coastal areas and this reduces/eliminates concerns about farm effluent and coastal eutrophication. Siting farms in rural farming areas can reduce land and labor costs, while allowing live or fresh product to be sold directly to consumers or the food service industry if farms are within reasonable driving distance to urban markets. This increases revenue to the farmer, due to a higher sales price, and eliminates the need to compete directly with lower-value, frozen, imported shrimp. Lastly, inland farms can take advantage of existing farm infrastructure such as large buildings (suitable for farms), local feed mills (and feed ingredients), and agriculture equipment/technology providers. Improving breeding practices and developing shrimp lines that perform well in the unique conditions of inland farms, should lead to the continued expansion of this farming sector and, ultimately, provide an economic boost to the communities that have inland shrimp farms. US consumers - Shrimp are the most consumed seafood in the US (27% of consumption), currently higher than salmon (16%) and canned tuna (15%). To support this level of consumption, the US is highly reliant on imported shrimp. The US currently imports ~660,000 MT of shrimp annually and this is valued at $6.5 billion. Foreign shrimp supplies are significantly larger than domestic supplies (fisheries and aquaculture combined) which are valued at ~$600M annually. The large reliance on imports results in a large trade deficit for shrimp products and creates incentive to increase domestic production. However, US landings of wild shrimp have remained relatively constant over the last 50 years, so it is unlikely domestic fisheries can significantly reduce the reliance on imports in the future. Global aquaculture production of shrimp has increased drastically over the last two decades, but US shrimp aquaculture production has remained relatively low over this same period. However, inland farming of shrimp is one sector of the US industry that has shown growth. This project aims to address knowledge gaps in genetics that are needed by US inland shrimp farmers (an expanding farming sector) to reduce operational costs and improve farm efficiency. Doing so should increase domestic shrimp production and reduce the trade deficit in shrimp products, while providing consumers with increased domestic options with purchasing shrimp. Changes/Problems:Survival in the 14 psu and 28 psu treatments were high for the G0 growout trial (Objective 1.2) and growth rates (by tank) were similar across the two treatments(Objective 1.2). In addition, genetic correlations (by trait) acrossthe two salinities was high and approaching 1. This provided strong evidence that growth at 14 psu is essentially the same trait as growth at 28 psu. The same can be said for survival. Thus, in Year 2, the growout trial was repeated (Objective 2.2 - modified), but using a more extreme difference in salinity: 5 psu and 32 psu. The larger difference in survival is anticipated to result in significant differences in performance across the two treatments (at the population and family level). These differences will allow for the estimation of genetic paremeters (e.g.. genetic correlations), as well as the impacts of selecting for performance at one salinity, but having commercial growout at the other. In addition, the benefits of GWAS selection for performance at one or both salinities can be determined. Due to operational and workforce reductions related to COVID-19, tru Shrimp was unable to assist with running of the Yr-1 and they unfortunately had to withdraw from the project.By the time tru Shrimp notified us of this, the production of shrimp families (Objective 1.1) for the Yr-1 trial was mostly complete. Thus, a new commercial partner would have been needed on very short notice (~30 days) and we felt that identifying a partner and arranging logistics on this timeline simply wasn't feasible. To keep the project on schedule, we decided the best option was to conduct the growout trials (Yr-1 and Yr-2)at Oceanic Institute (OI). Below are additional changes to the workplan: 1. Conducted trials at OI in replicate (6) 29-m2 round tanks. The number of replicate tanks was unchanged from the original research plan. 2. Test salinities remained as planned (14 psu and 28 psu) in Yr-1, but were adjusted to 5 psu and 32 psu in Yr-2. This was done because shrimp performance was essential the same across the two Yr-1 salinities (i.e. genetic correlations for growth and survival across the two salinities were approaching 1). 3. Two additional operational changes for the growout trials:(1) weused diluted natural seawater instead of aritificial seasalts; (2)instead of operating tanks on a water recirculation system, tanks were managed in a "batch exchange" manner, (~5% of tank volume/tank/day). 4. Given difficulties with genotyping of growout and candidate breeder samples in Yr-1, the number of candidate breeders that were sampled was reduced slightly. In addition, family and within-family selection protocols had to be adjusted in response to: (1) delays in getting genotyping results, (2) reduced numbers of candidate breeders (high mortality associated with shrimp age), (3) little to any differences in family rankings for growth or survival across test salinities. What opportunities for training and professional development has the project provided?One graduate student and one undergraduate intern have worked on the project. Neither of these students had prior experience with shrimp spawning, larval rearing, or growout or genetic sampling, but gained experience all three of the areas under the tutelage of PI Dustin Moss. How have the results been disseminated to communities of interest? Nothing Reported What do you plan to do during the next reporting period to accomplish the goals?All genotyping is complete and genetic analyses are ongoing. During the next reporting period, we will finish all analyses including a reanalysis of G0, as well as G1 analysis, and combined analyses of G0 and G1 data. The benefits of GWAS (both realized and theoritical will be reported, along with the potential impacts of GWAS on selection for growth and survival at low salinity. In addition, a manuscript for submission to a peer-reviewed journal will be prepared and the results will be presented at an aquaculture or genetics conference.

Impacts
What was accomplished under these goals? Objective 1.1: Production of 50 families of L. vannamei. Fifty-one families (G0 ) were produced using Specific pathogen free (SPF) broodstock selected for growout and reproductive performance (P generation). Broodstock were stocked into four 15- m2 maturation tanks with each tank receiving ~100 males or females. Briefly, natural mating was used with females displaying mature ovaries being transferred to appropriate male tanks (to avoid mating with closely related males) daily. Mated females were transferred into 300-L spawning tanks (1 female/tank), whereas un-mated females were returned to their respective maturation tanks. The morning following mating, females in spawning tanks were collected, eye-tagged (with specific color/number combination), sampled (hemolymph), and then returned to their respective maturation tanks. Viable nauplii (15K) from each spawn/family (dam-sire combination) was transferred to 100-L larval rearing tanks (1 family per tank). Shrimp were then transferred to 1-m2 nursery tanks at 10-d postlarvae (PL10) with each tank receiving 1,500 shrimp from a single family. A total of 47 female broodstock were sampled and broodstock hemolymph samples were submitted for genotyping (Objective 1.3). Objective 1.2: Growout evaluation of 50 families at high (28 psu) and reduced salinity (14 psu). At PL15-30, 525-540 shrimp from each family were randomly harvested from the nursery system, and stocked into six (6), 29-m2 round tanks, with each tank receiving 84-90 shrimp from each family. The remaining PLs will be grown to ~2.6 g and, at this point, 106-195 shrimp/family were tagged with elastomer implants, with each family receiving a unique tag code. Tagged juveniles (n = 8,066) were then combined into a 75-m2 raceway for growout at OI. An additional, 10,087 untagged tagged shrimp (siblings of tagged shrimp) were added to the raceway to achieve a commercially relevant stocking density (242 shrimp/m2 ). Tagged shrimp were evaluated for growth and survival at 35 psu. At ~29 g, tagged shrimp (n = 7,189) were harvested with weights and tag codes recorded for each individual shrimp. After data collection, all shrimp with harvest weights greater than or equal to their families mean harvest weight were restocked into the raceway for growout to broodstock (process of within-family selection). These shrimp served as candidate breeders for the production of G1 families (Objective 2.1). Objective 1.3: Genotyping and GWAS analysis. At harvest, all shrimp were counted and 800/tank were randomly selected and tissue sampled. A portion of these samples (300/tank), along with broodstock hemolymph samples (Objective 1.1), were genotyped using a HD SNP array (50K). The other 500 samples/tank were genotyped using a LD SNP array (192). Parentage was determined for all 800 shrimp sampled per tank with each assigned to a G0 family. The methodology used a mathematical model where population structure was considered using significant principal components and family structure was obtained using a SNP-generated relationship matrix. Each marker was evaluated individually using an approximated t-test with a false discovery rate of 2%. Pre-selected markers were further evaluated by combining them into a single model to obtain final marker effects and their significance on the population. The final markers were selected using backward selection with a significance level of 5%. Marker-trait associations for all responses were performed with combined data (both salinities) and separately for the two salinities. For the combined analysis, the model included a K-matrix (kinship), Q-matrix (of structure based on 5 principal components), the fixed effects of Salinity and Sex, random effect of Tank, and the covariate of Age. Heritability estimates are in line with previously published estimates for growth in this species. Using a threshold p-value of < 1e-6, a total of 120 markers were found for the combined, 100 for 14 psu, and 34 for the 28 psu analyses. There is a high level of agreement in significant markers between the combined and 14 psu analyses. However, only three (3) markers were found to be significant across all three analyses, denoting the presence of a genotype x environment interaction (G×E). Objective 1.4: Estimation of breeding values and genetic parameters. A series of statistical models were used to estimate pedigree- and genomic-based breeding values. A single-trait model using pedigree information or a SNP-generated relationship matrix and phenotypic data were used to generate EBVs and GEBVs (respectfully) for growth and survival in salinity-specific and combined analyses. Family (and individual) GEBVs for bodyweight from salinity-specific and combined analyses were highly correlated. This shows that growth at 14 and 28 psu are essentially the same trait and that selection for growth at one salinity should lead to similar genetic improvement for growth across salinities from 14-28 psu. The same trend was seen for survival, as well. Growth and survival were positively correlated, but the correlations were of low magnitude (0.15 for all analyses). This suggests that selection for growth will not negatively impact survival; however, positive effects on survival are likely to be small at best. This is consistent with findings from previous studies looking at growth and growout survival. It also should be noted that overall survival in the G0 trial was high (83-91% for all tanks) and that growth and survival correlations may vary as survival decreases (a harsher growout environment). ?Objective 2.1: Selection of breeders and the production of 50 families ofL. vannamei(G1). Mean family GEBVs for growth and survival were calculated for each G0 family. The original plan was for families with mean GEBVs for survival below 1 sd - to be culled (threshold selection) and, from the remaining families, the 10 families with the highest mean GEBVs for growth at each salinity would be selected (i.e. family selection) However, given difficulties with genotyping the estimation of GEBVs was delayed and the candidate breeder pool was depleted (due to excessive shrimp age). So, the plan was followed as closely as possible, but there will many exceptions.Hemolymph was collected from 457 candidate broodstock and samples genotyped using the 50K array. At the time of sampling, an eyestalk of each shrimp will be tagged with a colored and numbered plastic ring (size XB, A.C. Huges, Ltd., Middlesex, UK), so individual shrimp can be identified and linked with samples collected for SNP genotyping. GEBVs for growth and survival will be estimated for each sampled candidate breeders.Selected breeders (360 total) were stocked into four (4) maturation tanks. Thirty-five (35) families (G1) were produced by natural matings. Objective 2.2: Growout evaluation of 50 families at high (32 psu) and reduced salinity (5 psu).At PL15-30,shrimp from each family (mean = 539) were randomly harvested from the nursery system, and stocked into six (6), 29-m2 round tanks, with each tank receiving ~90 shrimp from each family. The remaining PLs will be grown to ~3.5 g and, at this point, ~150 shrimp/family were tagged with elastomer implants, with each family receiving a unique tag code. Tagged juveniles (n = 5,245) were then combined into a 75-m2 raceway for growout at OI. An additional, 3,552 untagged tagged shrimp (siblings of tagged shrimp) were added to the raceway to achieve astocking density (120 shrimp/m2 ). Tagged shrimp were evaluated for growth and survival at 35 psu. Objective 2.3: Genotyping and genetic analysis. At harvest, all shrimp were counted and 800/tank were randomly selected and tissue sampled. A portion of these samples (300/tank), along with broodstock hemolymph samples (Objective 2.1), were genotyped using a HD SNP array (50K). The other 500 samples/tank were genotyped using a LD SNP array (192). All genotyping is completed and genetic analyses are on going.

Publications


    Progress 09/01/20 to 08/31/21

    Outputs
    Target Audience: Nothing Reported Changes/Problems:Due to operational and workforce reductions related to COVID-19, tr? Shrimp was unable to assist with running of the Yr-1 growout trial. By the time tr? Shrimp notified us of this, the production of shrimp families (Objective 1.1) for the Yr-1 trial was mostly complete. Thus, a new commercial partner would have been needed on very short notice (~30 days) and we felt that identifying a partner and arranging logistics on this timeline simply wasn't feasible. To keep the project on schedule, we decided the best option was to conduct the trial at Oceanic Institute (OI). Below are details related to this change: Conducted trial at OI in replicate (6) 29-m2 round tanks. The number of replicate tanks was unchanged from the original research plan. The experimental tanks at OI are a good bit larger, than the small mesocosms tanks at tr? Shrimp (10 m2). There was some concern about scalability related to the size of the mesocosm tanks (10 m2) at tru Shrimp, so the change to larger tanks may help reduce/eliminate these concerns. Test salinities remained as planned (14 ppt and 28 ppt). However, the main difference was that we didn't use artificial sea salts to achieve desired salinities. Rather, we used diluted natural seawater. Also, instead of operating tanks on a water recirculation system, tanks were managed in a "batch exchange" manner, (~5% of tank volume/tank/day). Despite the mechanical and operational differences of these two approaches, both have the goal of maintaining water quality parameters (e.g. dissolved oxygen, pH, and nitrogenous wastes) within acceptable ranges. To date, we have been able to do so for all six experimental tanks. The larger tanks required us to stock more shrimp to achieve a commercially relevant density (~4,400 shrimp/tank; 150 shrimp/m2). We had originally planned to stock 1,500 shrimp/tank at tr? Shrimp and then sample 800 at harvest (4,800 total). That equates to sampling 53% of the number stocked. The number of shrimp sampled at harvest will not change (i.e. 800/tank), but now this amount equates to ~18% of the number stocked. Thus, there is some concern about sampling error (i.e. samples not being representative of population), but measures to randomize sampling will be taken. The money budgeted for tr? Shrimp ($5,000) and majority of the money budgeted for air freight and postage (~$1,800 of the $2,000) were reallocated to cover (partially) the cost to run the trial at OI. What opportunities for training and professional development has the project provided?One graduate student and one undergraduate intern have worked on the project. Neither of these students had prior experience with shrimp spawning, larval rearing, or growoutor genetic sampling, but gained experience all three of the areas under the tutelage of PI Dustin Moss. How have the results been disseminated to communities of interest? Nothing Reported What do you plan to do during the next reporting period to accomplish the goals?The project goals and ojectives for Project Year 2 are unchanged from the Initiation Report, except for the following: Growout evaluation of 50 G1 families will be conducted at OI. As previously reported, the commercial partner on the project (tru Shrimp) pulled out of the project due to COVID-related financial difficulties. (Objective 2.2) Conducttrial in replicate (6) 29-m2 round tanks. The number of replicate tanks was unchanged from the original research plan. The experimental tanks at OI are a good bit larger, than the small mesocosms tanks at tr? Shrimp (10 m2). There was some concern about scalability related to the size of the mesocosm tanks (10 m2) at tru Shrimp, so the change to larger tanks may help reduce/eliminate these concerns. These will be the same tanks used for the Year 1 growout trial. (Objective 2.2). Test salinities will be changed from 14 psu and 28 psu to 5 psu and 28 psu. Year 1 results show that growout peformance (growth and survival) at 14 and 28 psu is highly correlated (at phenotypically and genetically). This knowledge is helpful to inland farmers, as it shows that salinity can be reduced to 14 psu without any significant consequence on shrimp growout performance. However, in Year 2 we feel that a further reduction in the lower salinity (from 14 to 5 psu) will (1) generate potentially more valuable genetic data (e.g. heritability and genetic correlations for growth and survival at 5 psu) and (2) allow farmers to guage the impacts of further reducing salinity on shrimp performance.As in Year 1, we will dilute natural seaswater to achieve desired salinities, instead of using artificial seasalts. (Objectives 2.2 and 2.3) As in Year 1, the use of larger tanks will require us to stock more shrimp to achieve a commercially relevant density (~4,400 shrimp/tank; 150 shrimp/m2). We had originally planned to stock 1,500 shrimp/tank at tr? Shrimp and then sample 800 at harvest (4,800 total). That equates to sampling 53% of the number stocked. The number of shrimp sampled at harvest will not change (i.e. 800/tank), but now this amount will equate to ~18% of the number stocked.

    Impacts
    What was accomplished under these goals? Objective 1: Conduct a genome-wide association study (GWAS) for growth and survival in high (28 psu) and reduced salinity (14 psu) farming environments. Objective 1.1: Production of 50 families of L. vannamei. Fifty-one families (G0) were produced using Specific pathogen free (SPF) broodstock selected for growout and reproductive performance (P generation). Broodstock were stocked into four 15-m2 maturation tanks with each tank receiving ~100 males or females. Briefly, natural mating was used with females displaying mature ovaries being transferred to appropriate male tanks (to avoid mating with closely related males) daily. Mated females were transferred into 300-L spawning tanks (1 female/tank), whereas un-mated females were returned to their respective maturation tanks. The morning following mating, females in spawning tanks were collected, eye-tagged (with specific color/number combination), sampled (hemolymph), and then returned to their respective maturation tanks. Viable nauplii (15K) from each spawn/family (dam-sire combination) was transferred to 100-L larval rearing tanks (1 family per tank). Shrimp were then transferred to 1-m2 nursery tanks at 10-d postlarvae (PL10) with each tank receiving 1,500 shrimp from a single family. A total of 47 female broodstock were sampled and broodstock hemolymph samples were submitted for genotyping (Objective 1.3). Objective 1.2: Growout evaluation of 50 families at high (28 psu) and reduced salinity (14 psu). At PL15-30, 525-540 shrimp from each family were randomly harvested from the nursery system, and stocked into six (6), 29-m2 round tanks, with each tank receiving 84-90 shrimp from each family. The remaining PLs will be grown to ~2.6 g and, at this point, 106-195 shrimp/family were tagged with elastomer implants, with each family receiving a unique tag code. Tagged juveniles (n = 8,066) were then combined into a 75-m2 raceway for growout at OI. An additional, 10,087 untagged tagged shrimp (siblings of tagged shrimp) were added to the raceway to achieve a commercially relevant stocking density (242 shrimp/m2). Tagged shrimp were evaluated for growth and survival at 35 psu. At ~29 g, tagged shrimp (n = 7,189) were harvested with weights and tag codes recorded for each individual shrimp. After data collection, all shrimp with harvest weights greater than or equal to their families mean harvest weight were restocked into the raceway for growout to broodstock (process of within-family selection). These shrimp served as candidate breeders for the production of G1 families (Objective 2.1). Objective 1.3: Genotyping and GWAS analysis. At harvest, all shrimp were counted and 800/tank were randomly selected and tissue sampled. A portion of these samples (300/tank), along with broodstock hemolymph samples (Objective 1.1), were genotyped using a HD SNP array (50K). The other 500 samples/tank were genotyped using a LD SNP array (192). Parentage was determined for all 800 shrimp sampled per tank with each assigned to a G0 family. The methodology used a mathematical model where population structure was considered using significant principal components and family structure was obtained using a SNP-generated relationship matrix. Each marker was evaluated individually using an approximated t-test with a false discovery rate of 2%. Pre-selected markers were further evaluated by combining them into a single model to obtain final marker effects and their significance on the population. The final markers were selected using backward selection with a significance level of 5%. Marker-trait associations for all responses were performed with combined data (both salinities) and separately for the two salinities. For the combined analysis, the model included a K-matrix (kinship), Q-matrix (of structure based on 5 principal components), the fixed effects of Salinity and Sex, random effect of Tank, and the covariate of Age. Hence, the model for the combined analysis was: y = mu + Salinity + Sex + Tank + Age + {PC1 + PC2 + PC3 + PC4 + PC5} + ai + e, where ai refers to the genetic effect associated with the kinship matrix K, and e is the error assumed to be normally distributed. Phenotypic data was assessed and two observations were eliminated as they appear to be outliers (samples T02_097 & T10-170). The same molecular data was used for the salinity-specific analyses, and the model was: y = mu + Sex + Tank + Age + {PC1 + PC2 + PC3 + PC4 + PC5} + ai + e, where all the terms are the same as previously described for the combined analysis, except the factor of Salinity is not included. Heritability estimates (narrow-sense, h2), number of significant markers, and Manhattan plots from the three analyses are presented below (Table 1, Fig. 1). Heritability estimates are in line with previously published estimates for growth in this species. Using a threshold p-value of < 1e-6, a total of 120 markers were found for the combined, 100 for 14 psu, and 34 for the 28 psu analyses. There is a high level of agreement in significant markers between the combined and 14 psu analyses. However, only three (3) markers were found to be significant across all three analyses, denoting the presence of a genotype x environment interaction (G×E). Table 1. Heritability and number of significant markers for shrimp growth obtained from GWAS analyses of G0 salinity trial data. Analysis Narrow-sense heritability (h2) Significant Markers (p<1e-6) 14 psu 0.204 100 28 psu 0.257 34 Combined 0.219 120 A. B. C. Figure 1. Manahattan plots for 14 psu (A), 28 psu (B), and combined (C) GWAS analyses. Objective 1.4: Estimation of breeding values and genetic parameters. A series of statistical models were used to estimate pedigree- and genomic-based breeding values. A single-trait model using pedigree information or a SNP-generated relationship matrix and phenotypic data were used to generate EBVs and GEBVs (respectfully) for growth and survival in salinity-specific and combined analyses. Family (and individual) GEBVs for bodyweight from salinity-specific and combined analyses were highly correlated (Table 2). This shows that growth at 14 and 28 psu are essentially the same trait and that selection for growth at one salinity should lead to similar genetic improvement for growth across salinities from 14-28 psu. The same trend was seen for survival, as well. Growth and survival were positively correlated, but the correlations were of low magnitude (0.15 for all analyses). This suggests that selection for growth will not negatively impact survival; however, positive effects on survival are likely to be small at best. This is consistent with findings from previous studies looking at growth and growout survival. It also should be noted that overall survival in the G0 trial was high (83-91% for all tanks) and that growth and survival correlations may vary as survival decreases (a harsher growout environment). Table 2. Correlations of family (G0) GEBVs from salinity-specific and combined analyses. BWT 14 BWT 28 BWT Comb Surv 14 Surv 28 Surv Comb BWT 14 BWT 28 0.99 BWT Comb 1.00 1.00 Surv 14 0.15 0.15 0.15 Surv 28 0.15 0.15 0.15 1.00 Surv Comb 0.15 0.15 0.15 1.00 1.00 There was a large range of GEBVs within each family regardless of the overall family performance (Figure 2). This suggests that within family selection for growth could be highly effective for increasing selection intensity and rate of genetic improvement. For example, selecting the individuals with the highest GEBVs from the top ranked family will increase selection intensity by ~37% compared to randomly selected individuals from the same family (breeders would have GEBVs approximately equal to the family GEBV). Figure 2. Plots of individual GEBVs from salinity-specific and combined analyses for the top and lowest ranked families for bodyweight.

    Publications