Rémi Amiraux
email: remi.amiraux@takuvik.ulaval.ca

Philippe Archambault

Brivaëla Moriceau

Mélanie Lemire

Marcel Babin

Laurent Mémery

Guillaume Massé

Jean-Eric Tremblay

Brivaela Moriceau

Laurent Memery

Brivaela Moriceau

isoprenoids in two filter-feeding Arctic benthic molluscs: Mya truncata and Serripes groenlandicus

Keywords: Arctic shelves, Sympagic-benthic coupling, IP 25, HBI, n-3 PUFA, EPA, DHA, Mya truncata, Serripes groenlandicus, ice-derived HBI III

    Efficiency of sympagic-benthic coupling revealed by analyses of n-3 fatty acids, IP 25 and other highly branched

Introduction

Arctic marine food webs are classically viewed as being supported by two ecologically distinct types of primary production effected in sequence by sympagic (ice-associated) algae and pelagic (water column) algae or phytoplankton [START_REF] Gosselin | New measurements of phytoplankton and ice algal production in the Arctic Ocean[END_REF][START_REF] Horner | Relative contributions of ice algae, phytoplankton, and benthic microalgae to primary production in nearshore regions of the Beaufort Sea[END_REF][START_REF] Pabi | Primary production in the Arctic Ocean, 1998-2006[END_REF][START_REF] Wassmann | Footprints of climate change in the Arctic marine ecosystem[END_REF]. Among the essential organic molecules produced by algae, omega-3 polyunsaturated fatty acids (n-3 PUFA), such as eicosapentaenoic acid (EPA) 20:5(n-3) and docosahexaenoic acid (DHA) 22:6(n-3), are considered as highly relevant indicators of nutritional value for consumers [START_REF] Hendriks | Effect of dietary polyunsaturated fatty acids on reproductive output and larval growth of bivalves[END_REF]. These specific lipids are produced almost exclusively by algae and are necessary for the whole food web, from primary consumers (e.g., bivalves) to top predators and even human populations. As algal species differ in their lipid production and more specifically in their PUFA contents [START_REF] Leonardos | The nutritional value of algae grown under different culture conditions for Mytilus edulis L. larvae[END_REF][START_REF] Napolitano | Fatty acid composition of three cultured algal species (isochvysis galbana, chaetoceros gracilis and chaetoceros calcitrans) used as food for bivalve larvae[END_REF][START_REF] Volkman | Fatty acid and lipid composition of 10 species of microalgae used in mariculture[END_REF], it is not surprising that EPA and DHA derive from different sources of primary production. Indeed, EPA is mostly produced by diatoms, a dominant taxon of both sympagic and pelagic algae [START_REF] Kelly | Fatty acids as dietary tracers in benthic food webs[END_REF][START_REF] Poulin | The pan-Arctic biodiversity of marine pelagic and sea-ice unicellular eukaryotes: a firstattempt assessment[END_REF][START_REF] Viso | Fatty acids from 28 marine microalgae[END_REF], while DHA is associated with dinoflagellates, a mostly pelagic taxon [START_REF] Kelly | Fatty acids as dietary tracers in benthic food webs[END_REF][START_REF] Poulin | The pan-Arctic biodiversity of marine pelagic and sea-ice unicellular eukaryotes: a firstattempt assessment[END_REF][START_REF] Søreide | Seasonal feeding strategies of Calanus in the high-Arctic Svalbard region[END_REF].

Sympagic and pelagic contributions to total primary production are highly variable depending on the season and the region, but it is generally admitted that sympagic algae contribute less than phytoplankton to annual primary production [START_REF] Dupont | Impact of sea-ice biology on overall primary production in a biophysical model of the pan-Arctic Ocean[END_REF][START_REF] Fernández-Méndez | Photosynthetic production in the central Arctic Ocean during the record sea-ice minimum in 2012[END_REF]. In contrast, sympagic primary production is recognized as an important contributor of carbon (C) exported towards the seafloor [START_REF] Boetius | Export of Algal Biomass from the Melting Arctic Sea Ice[END_REF][START_REF] Mcmahon | Benthic community response to ice algae and phytoplankton in Ny Ålesund, Svalbard[END_REF]. This strong contribution results from the high sinking rates of ice-algal cells or aggregates [START_REF] Boetius | Export of Algal Biomass from the Melting Arctic Sea Ice[END_REF][START_REF] Riebesell | Aggregation of algae released from melting sea ice -Implications for seeding and sedimentation[END_REF] and their good preservation during transit [START_REF] Amiraux | Monitoring photo-oxidative and salinity-induced bacterial stress in the Canadian Arctic using specific lipid tracers[END_REF][START_REF] Amiraux | Stress factors resulting from the Arctic vernal sea ice melt: impact on the viability of the bacterial communities associated to sympagic algae[END_REF]. In contrast, phytoplankton have a longer residence time in the water column due to their slow sinking rates [START_REF] Van Der Loeff | Resuspension and particle transport in the benthic nepheloid layer in and near Fram Strait in relation to faunal abundances and 234 Th depletion[END_REF], which can lead to higher bacterial degradation and can reduce the quality of algal material reaching the seafloor [START_REF] Morata | Sedimentary pigments in the western Barents Sea: A reflection of pelagic-benthic coupling? Deep Sea Research Part II[END_REF][START_REF] Roy | Benthic faunal assimilation pathways and depth-related changes in food-web structure across the Canadian Arctic[END_REF]. It is therefore not surprising that the essential fatty acid content of this material is relatively high when it derives from sea ice [START_REF] Falk-Petersen | Lipids and fatty acids in ice algae and phytoplankton from the Marginal Ice Zone in the Barents Sea[END_REF][START_REF] Mcmahon | Benthic community response to ice algae and phytoplankton in Ny Ålesund, Svalbard[END_REF][START_REF] Sun | Different responses of two common Arctic macrobenthic species (Macoma balthica and Monoporeia affinis) to phytoplankton and ice algae: Will climate change impacts be species specific?[END_REF][START_REF] Wang | Fatty acid and stable isotope characteristics of sea ice and pelagic particulate organic matter in the Bering Sea: tools for estimating sea ice algal contribution to Arctic food web production[END_REF]. On this basis, sympagic algae are considered as a prime food source for benthic consumers that depend on these fatty acids for growth and reproduction [START_REF] Lovvorn | Organic matter pathways to zooplankton and benthos under pack ice in late winter and open water in late summer in the north-central Bering Sea[END_REF][START_REF] Mcmahon | Benthic community response to ice algae and phytoplankton in Ny Ålesund, Svalbard[END_REF][START_REF] North | Deposit-feeder diets in the Bering Sea: potential effects of climatic loss of sea ice-related microalgal blooms[END_REF].

Determining the impact of each primary production source on the quality of food for the benthic community requires an estimation of their relative contributions. Several approaches have been employed for estimating these contributions (e.g., stable isotopes and fatty acid biomarkers; [START_REF] Gaillard | Food resources of the bivalve Astarte elliptica in a sub-Arctic fjord: a multi-biomarker approach[END_REF][START_REF] Gaillard | Dietary tracers in Bathyarca glacialis from contrasting trophic regions in the Canadian Arctic[END_REF]. Among these, quantification of highly branched isoprenoid (HBI) alkenes has provided robust estimates of the relative share of different microalgal primary production sources in consumer biomass [START_REF] Brown | Transfer of ice algae carbon to ice-associated amphipods in the high-Arctic pack ice environment[END_REF][START_REF] Brown | Identification of the sea ice diatom biomarker IP 25 in Arctic benthic macrofauna: direct evidence for a sea ice diatom diet in Arctic heterotrophs[END_REF]. In recent years, the development of HBI-based proxies has highlighted the relatively high source-specificity of a number of these molecules. Among these, IP 25 (Ice Proxy with 25 carbon atoms; [START_REF] Belt | A novel chemical fossil of palaeo sea ice: IP 25[END_REF] is a mono-unsaturated C 25 HBI (Fig. 1) which seems to be produced exclusively by certain Arctic sympagic diatoms (e.g., Pleurosigma stuxbergii var. rhomboides (Cleve in Cleve & Grunow) Cleve, Haslea kjellmanii (Cleve) Simonsen, Haslea spicula (Hickie) Lange-Bertalot; Brown et al., 2014c;[START_REF] Limoges | Spring Succession and Vertical Export of Diatoms and IP 25 in a Seasonally Ice-Covered High Arctic Fjord[END_REF].

A close structural analogue of IP 25 , but with an additional double bond in its structure, is known as HBI IIa (Fig. 1) and this co-occurs with IP 25 in Arctic sea ice and associated sediments. In a recent study, [START_REF] Belt | Source identification and distribution reveals the potential of the geochemical Antarctic sea ice proxy IPSO25[END_REF] identified HBI IIa in the Southern Ocean and showed it to be produced by the sympagic diatom Berkeleya adeliensis (Medelin). The authors proposed the term IPSO 25 (ice proxy for the Southern Ocean with 25 carbon atoms) for this biomarker, at least when detected in this ocean [START_REF] Belt | Source identification and distribution reveals the potential of the geochemical Antarctic sea ice proxy IPSO25[END_REF]. Finally, a third (at least) HBI has been identified in several Rhizosolenia spp. isolated from polar and sub-polar locations [START_REF] Belt | Identification of C25 highly branched isoprenoid (HBI) alkenes in diatoms of the genus Rhizosolenia in polar and sub-polar marine phytoplankton[END_REF] and has been linked with pelagic primary production under ice-free conditions in both the Arctic and the Antarctic [START_REF] Belt | Source-specific biomarkers as proxies for Arctic and Antarctic sea ice[END_REF][START_REF] Belt | Identification of paleo Arctic winter sea ice limits and the marginal ice zone: Optimised biomarker-based reconstructions of late Quaternary Arctic sea ice[END_REF][START_REF] Collins | Evaluating highly branched isoprenoid (HBI) biomarkers as a novel Antarctic sea-ice proxy in deep ocean glacial age sediments[END_REF][START_REF] Massé | Highly branched isoprenoids as proxies for variable sea ice conditions in the Southern Ocean[END_REF]. As a common constituent of marine settings [START_REF] Belt | Highly branched isoprenoids (HBIs): identification of the most common and abundant sedimentary isomers[END_REF], this tri-unsaturated HBI, sometimes referred to as HBI III (Fig. 1), has shown potential as a proxy of pelagic production for the spring marginal ice zone (MIZ) in polar seas [START_REF] Belt | A novel biomarker-based proxy for the spring phytoplankton bloom in Arctic and sub-arctic settings-HBI T25[END_REF][START_REF] Collins | Evaluating highly branched isoprenoid (HBI) biomarkers as a novel Antarctic sea-ice proxy in deep ocean glacial age sediments[END_REF][START_REF] Köseoğlu | Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP 25 index[END_REF]Smik et al., 2016a;Smik et al., 2016b). More recently, HBI III has also shown potential as a proxy for pelagic productivity associated with arctic sea fronts [START_REF] Harning | Response of biological productivity to North Atlantic marine front migration during the Holocene[END_REF].

It is commonly accepted that a large proportion of the sympagic algal biomass released during sea ice melt, sinks to the seafloor, where it provides an important initial C and n-3 PUFA source for benthos growth and reproduction after the food limited winter [START_REF] Mcmahon | Benthic community response to ice algae and phytoplankton in Ny Ålesund, Svalbard[END_REF][START_REF] North | Deposit-feeder diets in the Bering Sea: potential effects of climatic loss of sea ice-related microalgal blooms[END_REF]. However, to the best of our knowledge, no studies have jointly monitored the temporal evolution of primary production quality (n-3 PUFA) and source (HBIs) in sea ice and the benthic filter-feeders underneath. In order to enhance our understanding of pelagic-benthic coupling in the Arctic, the present study monitored the temporal evolution of n-3 PUFAs and HBIs in sea ice and two benthic filter-feeder bivalve molluscs (Mya truncata and Serripes groenlandicus) during two melting periods in southwest Baffin Bay. Our objectives were: (i) to determine the seasonal and interannual variability of sea ice high-quality lipid production in sea ice, (ii) to determine the seasonal and interannual enrichment of these lipids in the two bivalve species and (iii) to confirm the use of M. truncata and S. groenlandicus as indicators of the tightness of pelago-benthic coupling. This study will enhance our understanding of the Arctic pelagic-benthic coupling, as well as highlight the seasonal and annual influences of sea ice lipid production on the quality of bivalves and of their reproductive capacity.

Materials and Methods

Study site and sampling

Sampling was conducted in 2015 and 2016 at a landfast-ice station located near Qikiqtarjuaq Island (Fig. 2) in southwest Baffin Bay (Canadian Arctic) within the framework of the GreenEdge project. Sea ice sampling was conducted every 2-3 days from 24 April to 24 June 2015 and from 16 May to 08 July 2016 (67°28.766'N; 63°47.579'W; water column depth: 350 m; Fig. 2). Bivalves (mean wet mass ± SE= 53.3 ± 3.5 and 42.4 ± 3.0 g for the truncate softshell clam (Mya truncata) and the Greenland cockle (Serripes groenlandicus) respectively; Table S1), were collected every 2-3 weeks from 18 January to 11 June 2015 and from 07 January to 19 June 2016, by scuba diving, at the closest coastal area from the sea ice sampling location (ca. 7.5 km west; 67°29.07'N; 63°57.92'W; Fig. 2).

Sea ice, sampled using a Kovacs Mark V 14 cm diameter corer focusing on the bottommost three centimeters of the core, where the bulk of ice biota occur [START_REF] Smith | Polynyas and leads: An overview of physical processes and environment[END_REF], was retained for subsequent analyses of particulate organic matter (POM). To compensate for the horizontal heterogeneity of ice-algal biomass, which is typical of sea ice [START_REF] Gosselin | Physical control of the horizontal patchiness of sea ice microalgae[END_REF], sections from three or four equivalent cores were pooled in isothermal containers for each sampling.

Pooled sea-ice sections were then melted with 0.2 μm filtered seawater (FSW; 3 parts of FSW to 1 part of melted ice) to minimize osmotic stress on the microbial community during melting [START_REF] Bates | Fluorescence induction and photosynthetic responses of Arctic ice algae to sample treatement and salinity[END_REF][START_REF] Garrison | Organism losses during ice melting: A serious bias in sea ice community studies[END_REF] and subsequently filtered for the several analyses (i.e., lipids, Chl a; Sections 2.2-2.3). Sea ice core parameters (e.g., snow thickness, air temperature and photosynthetically active radiation (PAR) estimated at the bottom of sea ice) were collected during both 2015 and 2016 campaigns and have already been published elsewhere [START_REF] Amiraux | Temporal evolution of IP 25 and other highly branched isoprenoid lipids in sea ice and the underlying water column during an Arctic melting season[END_REF][START_REF] Massicotte | Green Edge ice camp campaigns: understanding the processes controlling the under-ice Arctic phytoplankton spring bloom[END_REF][START_REF] Oziel | Environmental factors influencing the seasonal dynamics of under-ice spring blooms in Baffin Bay[END_REF]. Briefly, for each sampling date, 5-8 snow depth measurements were made with a ruler. Air temperature records were made with a meteorological station: an automated Meteo Mat equipped with temperature sensor (HC2S3; Campbell Scientific) sensor positioned near (< 100 m) the sea ice station.

Photosynthetically active radiation (PAR) below the sea ice was estimated at 1.3 m using the multispectral data collected with a Compact -Optical Profiling System (C-OPS; version Ice-PRO; Biospherical instruments Inc.; [START_REF] Oziel | Environmental factors influencing the seasonal dynamics of under-ice spring blooms in Baffin Bay[END_REF]. To reduce the effect of sea ice surface heterogeneity on irradiance measurements (e.g., [START_REF] Katlein | Influence of ice thickness and surface properties on light transmission through A rctic sea ice[END_REF], the vertical attenuation coefficients of PAR were calculated by fitting a single exponential function on PAR profiles between 10 and 50 m, then used to estimate PAR at 1.3 m (more details are given by [START_REF] Massicotte | Estimating underwater light regime under spatially heterogeneous sea ice in the Arctic[END_REF]. Note that 1.3 m corresponds to the highest average ice thickness measured during the two field campaigns and therefore to the first measurement under the ice (122.1 and 129.9 cm in 2015 and 2016 respectively).

After collection, bivalve samples were kept frozen (< -20°C) at the shore laboratory, before further treatment at the university laboratory. At Université Laval, bivalve individuals were freeze-dried and subsequently crushed (with exception of the shell), homogenized and kept frozen (< -20°C) prior to analysis.

Chlorophyll a

At the shore laboratory and within 24 h of sampling, sea ice samples originating from the pooled ice cores melted in isothermal containers were filtered in duplicates for chlorophyll a (Chl a) analyses through Whatman GF/F glass fiber filters. The Chl a retained on the filters was measured using a TD-700 Turner Design fluorimeter, after 18-24 h extraction in 90% acetone at 4°C in the dark [START_REF] Parsons | A manual of chemical and biological methods for seawater analysis[END_REF]. The fluorimeter was calibrated with commercially available Chl a (Anacystis nidulans, Sigma).

Lipid analyses

At the shore laboratory, sea ice samples originating from pooled ice cores in isothermal containers were filtered in duplicate for lipid analyses through Whatman GF/F glass fiber filters (porosity 0.7 μm, pre-combusted 4 h at 450°C) and stored at -20°C before further treatment at the university laboratory. At Université Laval, extraction of lipids was carried out in duplicate on the algal filters (ca. 50-2500 mL filtered) and on bivalves (ca. 0.5 g dry mass). To enable HBI and fatty acid quantification, two or three internal standards were added to each sample prior to extraction. For HBI quantification, 7-hexylnonadecane (7-HND; 0.01 µg) was added to sea ice samples, while 9-octylheptadecene (9-OHD; 0.02 µg) was added to bivalve samples.

For fatty acid quantification, 100 µg and 500 µg of 5β-cholanic acid were added to sea ice and bivalve samples respectively. Samples were saponified (5% KOH; 90°C, 120 min; 4 mL) in a flask, then extracted three times with hexane to recover HBI fractions and subsequently collected using open column silica chromatography (ca. 1 g silica; 6-7 mL hexane; [START_REF] Belt | A reproducible method for the extraction, identification and quantification of the Arctic sea ice proxy IP 25 from marine sediments[END_REF]. The remainder of the flask was acidified with HCl to pH 1 and extracted again three times with hexane (6-7 mL hexane). The combined hexane extracts were dried over anhydrous Na 2 SO 4 , filtered and concentrated to obtain the fatty acid fraction and methylated for further detection by gas chromatography-mass spectrometry (GC-MS). Analysis of lipids was carried out using GC-MS in selected ion monitoring (e.g., SIM, m/z 350 (IP 25 ), 348 (HBI IIa, b) and 346 (HBI III, IV); Fig. 1) mode using an Agilent 7890A series gas chromatograph (DB 5MS fused silica column; 50 m x 0.25 mm i.d., 0.25 μm film thickness) coupled to an Agilent 5975C mass spectrometric detector [START_REF] Belt | A reproducible method for the extraction, identification and quantification of the Arctic sea ice proxy IP 25 from marine sediments[END_REF]. HBIs were identified by comparison of retention indices (RI DB5-MS ) and mass spectra to those of authentic standards [START_REF] Belt | Source-specific biomarkers as proxies for Arctic and Antarctic sea ice[END_REF][START_REF] Belt | Highly branched isoprenoids (HBIs): identification of the most common and abundant sedimentary isomers[END_REF][START_REF] Tesi | Resolving sea ice dynamics in the northwestern Ross Sea during the last 2.6 ka: From seasonal to millennial timescales[END_REF][START_REF] Tesi | Carbon geochemistry of plankton-dominated samples in the Laptev and East Siberian shelves: contrasts in suspended particle composition[END_REF]. Quantification of HBIs was carried out by comparing mass spectral intensities of molecular ions to that of the internal standard and normalizing for differences in mass spectral fragmentation efficiency and volume/mass sampled. Fatty acid quantification was made in a similar manner to that of HBIs, although using different standards (Supelco® 37 Component FAME Mix, Supelco).

Statistical analyses

Sea ice

Principal Component analysis (PCA) biplots of the environmental variables was used to reduce the dimensionality of the dataset using the "FactoMineR" package [START_REF] Pagès | Analyse factorielle de donnees mixtes: principe et exemple d'application[END_REF].

Environmental variables used into the PCA were total fatty acid (TFA), polyunsaturated fatty acid (PUFA), air temperature, PAR, snow thickness and Chl a, to describe the 28 and 23 sea ice sampling dates from 2015 and 2016, respectively. Wilcoxon tests were performed to test the effect of year (fixed with two levels: 2015 and 2016) on sea ice fatty acid (TFA, monounsaturated fatty acid (MUFA), PUFA, saturated fatty acid (SFA)) and HBI (IP 25 , HBI IIa, IIb, III and IV) contents. Spearman's rank order correlation (r) was used to infer the strength of associations between HBI variables and correlation significance was determined at p-value < 0.01.

Bivalves

Non-metric multidimensional scaling (nMDS), based on the Euclidean distance on normalized lipid data, was employed to graphically represent the position of the 75 bivalve specimens on the ordination diagram.

Results

Sea ice

On average, Chl a concentration in sea ice was ca. 6 times higher in 2015 than in 2016 (mean ± SE = 646.7 ± 69.4 µg L -1 and 119.8 ± 17.4 µg L -1 , respectively; Fig. 3). A unique Chl a peak in production was observed in 2015 (May 31 st ; 1661.8 µg L -1 ) while two peaks were observed in 2016 (317.3 and 306.9 µg L -1 on June 1 st and 13 rd respectively). TFA content in sea ice was ca. 5 times higher in 2015 than 2016 (mean ± SE = 57.9 ± 14.0 mg L -1 and 11.0 ± 2.7 mg L -1 , respectively; Fig. 3,Table 1). In 2015, the TFA maximum was observed on 15 June (332.0 mg L -1 ; Fig. 3, Table S2) i.e., 15 days after the Chl a peak, while in 2016 it occurred on 20 June (35.2 mg L -1 ) i.e., 7 days after the second Chl a peak. Fatty acid profiles of sea ice samples were dominated in both 2015 and 2016 by C 16:17 (palmitoleic; 68.9 and 53.6% respectively) and C 16:0 (palmitic; 26.1 and 30.8% respectively) acids; they also exhibited smaller proportions of C 14:0 (4.7 and 4.2% respectively), C 18:19 (oleic; 5.4 and 0.3% respectively), EPA (0.4 and 10.3% respectively) and DHA acids (0.0 and 1.2% respectively;

Table 1). Among the TFA, the contribution of SFA (C 14:0 and C 16:0 ) was relatively similar in 2015 and 2016 (mean ± SE = 30.7 ± 1.9 % and 35.0 ± 2.8 %, respectively). Contributions of MUFA (palmitoleic and oleic acids) were higher in 2015 than in 2016 (mean ± SE = 68.9 ± 2.0 % and 53.6 ± 3.2 %, respectively), while the PUFA (n-3 PUFA EPA and DHA) contribution was lower in 2015 than 2016 (mean ± SE = 0.4 ± 0.3 % and 11.4 ± 1.9 %, respectively; Table 1). Absolute concentrations of the different lipid classes were significantly different between the years (Wilcoxon test; p-value < 10 -4 ). Although the 2016 Spring was less productive than 2015 Spring in terms of TFA, MUFA and SFA, the PUFA content was higher (mean ± SE = 0.9 ± 0.2 % and 0.2 ± 0.1 mg L -1 , respectively; Table 1). To unravel how sea ice sampling dates (variables) could be described by their environment (Chl a, snow thickness (snow), PAR, air temperature (Temperature), TFA and PUFA), a biplot PCA was performed (Fig. 4). The PCA accounted for 64.1% of the total variation among sea ice sampling dates (Axis 1: 44.2% and Axis 2: 19.9%). The sea ice stations (variables) are displayed according to their contribution (in %) to the dimensions of the biplot. The quality of the contribution is colored. In Fig. 4, contributions higher than 15 are considered as good (orange, indicator length of arrows). The analysis revealed that TFA, PAR, snow and Chl a are key environmental factors for describing the sea-ice sampling dates, while air temperature and PUFA are of less importance. Overall, the 2015 sea-ice sampling stations were characterized by high snow thickness, Chl a and TFA concentrations associated with low PAR, air temperature and PUFA content. Conversely, the 2016 sea-ice sampling period was characterized by relatively low snow thickness and concentrations of Chl a and TFA associated with high PAR, air temperature and PUFA content (Fig. 4).

HBIs were detected during both sampling years. Because of the slightly different analytical methodology employed for the analysis of HBIs in sea-ice and bivalves, no comparison of absolute HBIs values can be made between the two types of samples. A Wilcoxon test on the different HBIs investigated showed no significant differences between 2015 and 2016 (p-value > 0.05). During both years, IP 25 and HBI IIa were well correlated in sea ice (Spearman's r = 0.92, p-value < 0.01, n = 51) as well as HBI IIa, III and IV (Spearman's r ranged from 0.87 to 0.94, p-value < 0.01, n = 51) (Table 2). Conversely, IP 25 and HBI IIa were not well correlated with HBI IIb, III or IV (Table 2).

Bivalves

We monitored HBIs in M. truncata and S. groenlandicus from winter to summer 2015 and 2016 (Fig. 6). With the exception of the four last 2015 and two last 2016 sampling dates, M. truncata presented higher IP 25 contents than S. groenlandicus (Fig. 5A,B). However, the mean IP 25 content of S. groenlandicus was higher than that of M. truncata in both 2015 (mean ± SE = 127.9 ± 63.9 and 57.0 ± 15.9 ng g -1 dry mass, respectively) and 2016 (mean ± SE = 86.5 ± 52.0 and 37.3 ± 8.0 ng g -1 dry mass, respectively). The IP 25 contents of S. groenlandicus collected in 2015 and 2016 presented similar seasonal trends, i.e., an exponential-like curve with low values observed from January to early May, followed by increasing values from May to late June (Fig. 5A,B). These increases in S. groenlandicus IP 25 content corresponded to the sea ice production period of IP 25 . IP 25 content in M. truncata followed the same trend as S. groenlandicus during both years, although the trend was not as clear (Fig. 5A,B). Similarly to IP 25 , S. groenlandicus HBI III content was higher than in M. truncata in both 2015 (mean ± SE = 19.3 ± 4.4 and 5.3 ± 0.8 ng g -1 dry mass, respectively) and 2016 (mean ± SD = 6.8 ± 3.2 and 3.0 ± 0.5 ng g -1 dry mass, respectively). The HBI III contents of S. groenlandicus collected in 2015 and 2016 presented similar seasonal trends, i.e., low values observed from January to April/May followed by increasing values from May to late June (Fig. 5A,B). In both instances, the increase of S. groenlandicus HBI III occurred after HBI III production in sea ice and before IP 25 accumulation in S. groenlandicus. Although the general trend of low HBI III values from January to April/May followed by increasing values from May to late June was also observed for M. truncata (at least for 2016; Fig. 5D), the increase did not clearly precede that of IP 25 ; nor did it occur after sea-ice HBI production.

A strong correlation was observed between IP 25 and HBI IIa in S. groenlandicus over the two years (Spearman's r = 0.99, p-value < 0.01, n = 38; Table 2). This correlation was also present, but weaker, in sea-ice POM and M. truncata (r = 0.92 and 0.44, respectively).

Correlations between HBI IIb, III and IV were strong for sea-ice POM, moderate in S. groenlandicus (r ranged from 0.70 to 0.87) and relatively weak in M. truncata (r ranged from 0.21 to 0.70).

Non-metric multidimensional scaling (nMDS) of bivalve lipid data (i.e., fatty acid and HBI contents) showed that M. truncata samples were well grouped, at both seasonal and interannual scales. In contrast, S. groenlandicus samples formed a more diffusive group at those same scales (Fig. 6). The fatty acid profiles of bivalves were similar to those of sea-ice POM, but occurred in different proportions (Tables 1,3, Table S2-S4). For instance, S. groenlandicus samples during both 2015 and 2016 were dominated by EPA (mean ± SE = 44.9 ± 4.1 and 35.3 ± 5.9% respectively), C 16:0 (mean ± SE = 20.7 ± 1.0% and 25.6 ± 2.7% respectively) and C 16:17 acids (mean ± SE = 15.8 ± 1.3% and 20.0 ± 2.9% respectively), while exhibiting lower proportions of DHA (mean ± SE = 8.5 ± 0.5% and 6.8 ± 1.0% respectively), C 14:0 (mean ± SE = 5.7 ± 0.4 and 6.9 ± 0.6% respectively) and C 18:19 acid (mean ± SE = 4.3 ± 0.3% and 5.3 ± 0.8% respectively; Table 3). The M. truncata samples during both 2015 and 2016 were dominated by EPA (mean ± SE = 42.7 ± 5.9% and 37.4 ± 6.0% respectively), C 16:0 (mean ± SE = 23.8 ± 2.5% and 30.2 ± 3.4% respectively), C 16:17 acids (mean ± SE = 12.0 ± 1.7% and 16.5 ± 3.0% respectively) and DHA (mean ± SE = 16.2 ± 1.4% and 9.3 ± 0.8% respectively). They also exhibited smaller proportions of C 18:19 (mean ± SE = 4.3 and 3.8 ± 0.7% respectively) and C 14:0 acids (mean ± SE = 1.9 ± 0.3% and 2.7 ± 0.5% respectively; Table 3). TFA contents were higher in S. groenlandicus than in M. truncata during both 2015 (mean ± SE = 233.5 ± 19.7 and 40.1 ± 5.0 mg g -1 dry mass, respectively) and 2016 (mean ± SE = 167.6 ± 25.2 and 54.6 ± 5.0 mg g -1 dry mass, respectively). Among the TFA, the contribution of SFA was relatively similar for the two species during 2015 (mean ± SE = 25.7 ± 2.8 % and 26.4 ± 1.4 %, respectively) and 2016 (mean ± SE = 32.9 ± 3.8 % and 32.5 ± 3.7 %, respectively), while the contribution of MUFA was slightly lower in M. truncata than in S. groenlandicus during 2015 (mean ± SE = 15.2 ± 2.2 % and 20.1 ± 1.6 %, respectively) and 2016 (mean ± SE = 20.3 ± 3.7 % and 25.3 ± 3.7 %, respectively; Table 3). Conversely, the contribution of PUFA was slightly higher in M. truncata than in S. groenlandicus during 2015 (mean ± SE = 58.9 ± 7.2 % and 53.5 ± 4.6 %, respectively) and 2016 (mean ± SE = 46.7 ± 6.8 % and 42.2 ± 6.9 %, respectively).

The temporal evolution of palmitoleic/palmitic acid ratios and of the TFA and PUFA contents of bivalves were monitored during both 2015 and 2016 (Fig. 7; Table S3, S4). Values were seasonally steady in M. truncate , but for TFA in S. groenlandicus, declined from a seasonal maximum at the beginning of sampling (Fig. 7). The importance of diatoms for bivalve diet was assessed here with the palmitoleic/palmitic acid ratio, which increases with the contribution of diatoms to animal biomass [START_REF] Pedersen | The significance of food web structure for the condition and tracer lipid content of juvenile snail fish (Pisces: Liparis spp.) along 65-72°N off West Greenland[END_REF][START_REF] Reuss | Evaluation of fatty acids as biomarkers for a natural plankton community. A field study of a spring bloom and a post-bloom period off West Greenland[END_REF].

During both years, the ratios of S. groenlandicus were higher early in the sampling period (0.98 from 18 January to 21 March 2015 and 0.96 from 07 January to 10 May 2016) than afterwards (0.56 from 03 May to 26 June 2015 and 0.58 from 30 May to 19 June 2016). These low ratios corresponded to the period when bivalve consume sympagic algae (Fig. 7A,B). The TFA and PUFA contents of S. groenlandicus followed similar qualitative trends. TFA contents were highest early in the season (304.8 and 196 mg g -1 dry mass in 2015 and 2016, respectively) and lowest afterwards (108.9 and 82.1 mg g -1 dry mass in 2015 and 2016). For PUFA, the values declined from 180.5 and 82.7 in early 2015 and 2016, respectively, to 47.1 and 34.7 mg g -1 dry subsequently (Fig. 7C-F).

Discussion

Sea ice seasonal and inter-annual lipid productivity

A Principal Component Analysis (PCA) biplot of environmental variables was used to reduce the dimensionality of the sea ice samples (Fig. 4). This highlighted that in 2015 the snow cover was thicker than in 2016, which resulted in reduced under-ice PAR. In terms of biomarkers, the 2015 sea ice was characterized by higher Chl a concentrations and TFA contents than in 2016, associated with lower PUFA (EPA and DHA) contents. The great difference in Chl a productivity may derive from the contrasted atmospheric forcings present during the winters preceding each sampling period. Indeed, the winter of 2014-2015 was colder and with less snowfall than the 2015-2016 winter. As a consequence, twice the amount of light was transmitted to the bottom ice prior to sampling, which could in large part explain the average six times larger sympagic production of Chl a in 2015 than 2016 [START_REF] Oziel | Environmental factors influencing the seasonal dynamics of under-ice spring blooms in Baffin Bay[END_REF] Fig. 3). Since larger sympagic Chl a biomass was observed in 2015 than 2016, it is not surprising to also observe the largest total fatty acid production in 2015 (Figs. 3,4; Table 1).

Interestingly, a mismatch between TFA and Chl a peaks was observed over the two years (Fig. 3). This result has already been pointed out by [START_REF] Amiraux | Stress factors resulting from the Arctic vernal sea ice melt: impact on the viability of the bacterial communities associated to sympagic algae[END_REF] during the 2016 melting season in the same area. Those authors attributed this phenomenon to the photoacclimation of sympagic algae to higher light intensities (derived from snow melting) and the consequent reduction of their Chl a content per cell, resulting in a mismatch between Chl a and fatty acid peaks. Thus, based on the observation of Chl a and fatty acid peak mismatches over the two years, we suggest that this particular feature is probably common to sea ice melt.

The fatty acid profiles of the sea-ice POM obtained in southwest Baffin Bay were similar to those previously reported during spring in Svalbard and the Barents Sea [START_REF] Henderson | Seasonal variation in lipid and fatty acid composition of ice algae from the Barents Sea[END_REF][START_REF] Leu | Consequences of changing sea-ice cover for primary and secondary producers in the European Arctic shelf seas: Timing, quantity, and quality[END_REF][START_REF] Leu | Increased irradiance reduces food quality of sea ice algae[END_REF]. However, the relative contribution of different lipid classes somewhat differed from the proportions found in the literature. PUFA contributions were notably low here (0.4 and 11.4% in 2015 and 2016 respectively) relative to those measured in Svalbard and the Barents Sea (> 17%). While the threshold percentage at which the relative contribution of a fatty acid is accounted for differ among fatty acid studies (e.g., 1 or 3%; 3% in the present study) and may have contributed to this contrast, the most likely explanation is a regional or annual difference in the relative production of fatty acids. Absolute concentrations of the different fatty acid classes greatly differed between the sampling years with higher TFA, MUFA and SFA concentration in Spring 2015 than 2016 (Table 1). Conversely, sympagic algae collected in Spring 2016 presented higher PUFA absolute concentrations than those of 2015 (mean ± SE = 0.9 ± 0.2 and 0.2 ± 0.1 mg L -1 in 2016 and 2015 respectively; Table 1; Fig. 4). While the total algal biomass that reaches the seafloor is important for the feeding ecology of bivalves, the nutritional value of this biomass is determined by the essential fatty acids EPA and DHA [START_REF] Hendriks | Effect of dietary polyunsaturated fatty acids on reproductive output and larval growth of bivalves[END_REF][START_REF] Lane | The effect of a microencapsulated fatty acid diet on larval production in the European flat oyster Ostrea edulis L. University of Wales[END_REF]. These PUFAs are essential because most bivalve species are unable to synthesize them from shorter chain precursors [START_REF] Chu | Metabolism of palmitic, linoleic, and linolenic acids in adult oysters, Crassostrea virginica[END_REF][START_REF] Delaunay | The effect of monospecific algal diets on growth and fatty acid composition of Pecten maximus (L.) larvae[END_REF]. Thus, we suggest that, although sympagic production was higher in 2015 than 2016 (as attested by e.g., Chl a and TFA content), the 2016 sea ice was more useful for bivalves (at least for essential fatty acids) than the 2015 production.

In a previous investigation, [START_REF] Amiraux | Temporal evolution of IP 25 and other highly branched isoprenoid lipids in sea ice and the underlying water column during an Arctic melting season[END_REF] conducted the first analysis of the temporal evolution of IP 25 and other HBIs during the 2016 melting season in the same area. In the present study, sea ice HBI analysis was performed on both 2015 and 2016 samples with a different methodology and filters to those reported by [START_REF] Amiraux | Temporal evolution of IP 25 and other highly branched isoprenoid lipids in sea ice and the underlying water column during an Arctic melting season[END_REF] in their studies. [START_REF] Belt | An inter-laboratory investigation of the Arctic sea ice biomarker proxy IP 25 in marine sediments: key outcomes and recommendations[END_REF] warned the 'HBI scientific community' that the absolute quantification of HBIs obtained from different laboratories and/or using different methodologies (e.g., standard: 9-OHD or 7-HND) may be relatively different. Thus, in order to prevent this bias, the present study only discusses the absolute values obtained by the same method, or else the relative values obtained from different methods (e.g., biomarker correlations).

Overall, we confirmed the general findings of [START_REF] Amiraux | Temporal evolution of IP 25 and other highly branched isoprenoid lipids in sea ice and the underlying water column during an Arctic melting season[END_REF] for sea-ice POM; namely, the co-occurrences of: (i) IP 25 and HBI IIa, which is consistent with a single source (sympagic) for the two compounds (Brown et al., 2014a;Brown et al., 2014b;[START_REF] Limoges | Spring Succession and Vertical Export of Diatoms and IP 25 in a Seasonally Ice-Covered High Arctic Fjord[END_REF], and (ii) HBIs IIb, III and IV (Table 2). The latter was most likely attributed to a pelagic production at the early sea ice melts stages and within sea ice, by the tube-dwelling diatom Berkeleya rutilens [START_REF] Amiraux | Temporal evolution of IP 25 and other highly branched isoprenoid lipids in sea ice and the underlying water column during an Arctic melting season[END_REF]. In recent years, numerous HBI-based proxies have been developed [START_REF] Belt | Source-specific biomarkers as proxies for Arctic and Antarctic sea ice[END_REF]. Among them, the so-called PIP 25 index (phytoplankton marker-IP 25 ;[START_REF] Müller | Towards quantitative sea ice reconstructions in the northern North Atlantic: A combined biomarker and numerical modelling approach[END_REF] has provided, in some cases, more detailed descriptions of palaeo Arctic sea-ice conditions in sediment records than using IP 25 alone (e.g., [START_REF] Belt | Source-specific biomarkers as proxies for Arctic and Antarctic sea ice[END_REF][START_REF] Berben | Holocene sub-centennial evolution of Atlantic water inflow and sea ice distribution in the western Barents Sea[END_REF][START_REF] Fahl | Modern seasonal variability and deglacial/Holocene change of central Arctic Ocean sea-ice cover: New insights from biomarker proxy records[END_REF][START_REF] Müller | High-resolution record of late glacial and deglacial sea ice changes in Fram Strait corroborates ice-ocean interactions during abrupt climate shifts[END_REF][START_REF] Müller | Holocene cooling culminates in sea ice oscillations in Fram Strait[END_REF]. On the other hand, the HBI biomarker-based 'H-print' has provided valuable estimates of the relative contributions of sympagic-and pelagic-derived primary production in a variety of Arctic animals [START_REF] Brown | Stability of the lipid biomarker H-Print within preserved animals[END_REF][START_REF] Brown | High contributions of sea ice derived carbon in polar bear (Ursus maritimus) tissue[END_REF]Brown et al., 2014d). The robustness of these proxies depends on whether the markers are unequivocally specific to sympagic and pelagic growth environments, or not. Although IP 25 appears to represent a suitable sympagic biomarker, due to its source specificity (Brown et al., 2014c), identification of the most suitable pelagic counterpart remains challenging [START_REF] Belt | Source-specific biomarkers as proxies for Arctic and Antarctic sea ice[END_REF]. In recent studies, the use of some other HBIs (including HBI III) has been suggested as preferable pelagic counterparts to IP 25 , owing to their apparently greater source specificity [START_REF] Belt | Source-specific biomarkers as proxies for Arctic and Antarctic sea ice[END_REF][START_REF] Belt | Sterol identification in floating Arctic sea ice algal aggregates and the Antarctic sea ice diatom Berkeleya adeliensis[END_REF][START_REF] Belt | A novel biomarker-based proxy for the spring phytoplankton bloom in Arctic and sub-arctic settings-HBI T25[END_REF][START_REF] Köseoğlu | Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP 25 index[END_REF][START_REF] Smik | Development of biomarker-based proxies for paleo sea-ice reconstructions[END_REF]. However, data from the current study confirm the findings of [START_REF] Amiraux | Temporal evolution of IP 25 and other highly branched isoprenoid lipids in sea ice and the underlying water column during an Arctic melting season[END_REF]; namely, that HBI III can occur in sea ice and is not as specific of the pelagic environment as originally believed (Fig. 5C,D).

HBI production in sea-ice (including IP 25 ) did not significantly differ between years (Wilcoxon test; p-value > 0.05). Since IP 25 -producing species are normally only present as minor components of the ice-algal assemblage (typically 1-5%; Brown et al., 2014c), the combination of a nearly stable IP 25 -production in years with reduced ice-algal production (as indicated by the Chl a or TFA; Fig. 3) indicates a relatively high contribution of IP 25 -producing species in 2016.

Efficiency of benthic-pelagic coupling

Pelagic-benthic coupling is known to be particularly tight on Arctic shelves [START_REF] Ambrose | Does a pulsed food supply to the benthos affect polychaete recruitment patterns in the Northeast Water Polynya[END_REF][START_REF] Clough | Impacts of water depth, sediment pigment concentration, and benthic macrofaunal biomass on sediment oxygen demand in the western Arctic Ocean[END_REF][START_REF] Hobson | Sources of primary production, benthic-pelagic coupling, and trophic relationships within the Northeast Water Polynya: insights from d 13 C and d 15 N analysis[END_REF][START_REF] Renaud | Pelagicbenthic coupling in the western Barents Sea: Processes and time scales[END_REF][START_REF] Olivier | Shells of the bivalve Astarte moerchi give new evidence of a strong pelagic-benthic coupling's shift occurring since the late 70s in the NOW Polynya[END_REF], with a large portion (48 to 96%) of the carbon produced in the water column falling to the seafloor each year [START_REF] Wassmann | Dynamics of primary production and sedimentation in shallow fjords and polls of western Norway[END_REF]. Although the relative contribution of sympagic algae and phytoplankton to total marine primary production varies with ice cover and water column productivity, it has been shown that a significant fraction of the carbon reaching the seafloor derives from sympagic algal material [START_REF] Belt | Source-specific biomarkers as proxies for Arctic and Antarctic sea ice[END_REF]. The joint monitoring of the sea-ice proxy IP 25 in both sea ice and the bivalves beneath, allowed us to determine the efficiency of the benthic-pelagic (and more precisely: benthic-sympagic) coupling for two years (Fig. 5). Both M. truncata and S. groenlandicus presented depleted IP 25 concentrations during winter months, followed by days of rapid enrichment once IP 25 was produced in sea ice (Fig. 5 A,B). This pattern confirms that benthos rapidly responded to the influx of sympagic organic matter (days to weeks; [START_REF] Graf | Benthic-pelagic coupling in a deep-sea benthic community[END_REF][START_REF] Renaud | Pelagicbenthic coupling in the western Barents Sea: Processes and time scales[END_REF]. Similarly, bivalves presented depleted HBI III concentrations in winter, followed by a rapid enrichment from ca. April/May (Fig. 5). From its presupposed pelagic origin in the marginal ice zone [START_REF] Belt | Identification of paleo Arctic winter sea ice limits and the marginal ice zone: Optimised biomarker-based reconstructions of late Quaternary Arctic sea ice[END_REF][START_REF] Collins | Evaluating highly branched isoprenoid (HBI) biomarkers as a novel Antarctic sea-ice proxy in deep ocean glacial age sediments[END_REF][START_REF] Köseoğlu | Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP 25 index[END_REF][START_REF] Smik | Development of biomarker-based proxies for paleo sea-ice reconstructions[END_REF]Smik et al., 2016b), HBI III has only been reported in phytoplankton collected during summer and autumn [START_REF] Belt | Identification of C25 highly branched isoprenoid (HBI) alkenes in diatoms of the genus Rhizosolenia in polar and sub-polar marine phytoplankton[END_REF]. Thus, the enrichment of HBI III in bivalves observed from ca. April/May unlikely derived from open water production. Moreover, in sea ice, the production of HBI III has been reported to occur before that of IP 25 (Fig. 5; [START_REF] Amiraux | Temporal evolution of IP 25 and other highly branched isoprenoid lipids in sea ice and the underlying water column during an Arctic melting season[END_REF]. Thus, the earlier HBI III enrichment in bivalve flesh compared to IP 25 strongly supports the notion that these animals ingest sea ice-derived HBI III.

Consequently, we suggest that in coastal regions at least, HBI III derived from sea ice reaches the seafloor and contributes to the diet of arctic animals, potentially lowering the robustness of the PIP 25 and H-print indices.

For both years, IP 25 and HBI III concentrations were more than twice higher in S.

groenlandicus than in M. truncata. Moreover, the response of M. truncata to sympagic POM, as identified by their HBI enrichment (IP 25 and HBI III) was less evident than for S. groenlandicus (Fig. 5). An explanation may be found in the size of the organisms collected. Indeed, it has been shown that bivalve filtration rate is to some extent a function of their body size [START_REF] Riisgård | An improved automatic recording apparatus for determining the filtration rate of Mytilus edulis as a function of size and algal concentration[END_REF][START_REF] Riisgård | Filtration rates in the soft clam Mya arenaria: effects of temperature and body size[END_REF][START_REF] Sylvester | Filtration rates of the invasive pest bivalve Limnoperna fortunei as a function of size and temperature[END_REF]. It follows that the consumption of large-sized sympagic algae by small bivalves should be relatively weak, resulting in a low and more variable HBI enrichment than in large bivalves. In the present study however, this argument is countered by the heavier mass of M. truncata samples compared to S. groenlandicus (Table S1). A more likely explanation lies in the feeding behaviors of these two bivalves. Indeed, although S. groenlandicus and M. truncata are both slow-mobile burrowing suspension feeders [START_REF] Gulliksen | Svalbard and life in polar oceans[END_REF][START_REF] Huber | Compendium of Bivalves[END_REF][START_REF] Mctigue | Trophodynamics and organic matter assimilation pathways in the northeast Chukchi Sea, Alaska[END_REF][START_REF] Shojaei | Developments in German Bight benthic ecology driven by climate change and anthropogenic utilisation[END_REF], their bioturbation affinity differs. Unlike S. groenlandicus, M. truncata induces diffusive mixing bioturbation [START_REF] Lacoste | Bioturbation activity of three macrofaunal species and the presence of meiofauna affect the abundance and composition of benthic bacterial communities[END_REF], and is expected to ingest a variable and non-negligible quantity of buried sediment. Although M. truncata had higher IP 25 content than S. groenlandicus during winter months (Fig. 5A,B), its IP 25 content was half that of S. groenlandicus over the entire season. This result supports the notion that sediment represents a non-negligible part of the diet in M. truncata. Indeed, the higher IP 25 content of M. truncata compared to S. groenlandicus in winter suggests that sediment POM represents a better source of IP 25 than primary production during this season.

Conversely, the higher spring IP 25 content in S. groenlandicus compared to M. truncata suggests that primary production is the better source of IP 25 during this season. Moreover, since unsaturated lipids (including HBIs) are susceptible to degradative processes in the upper centimeters of the sediment [START_REF] Rontani | Photo-and autoxidation of unsaturated algal lipids in the marine environment: an overview of processes, their potential tracers, and limitations[END_REF][START_REF] Rontani | Biotic and abiotic degradation of the sea ice diatom biomarker IP 25 and selected algal sterols in near-surface Arctic sediments[END_REF], the consumption of sediment POM by M. truncata should provide less and more variable lipid contents (including HBI) than the supposed strict diet of sympagic and pelagic material in S. groenlandicus. Lipid contents (Fig. 5,7) and the positive correlations between different HBIs support this interpretation (Table 2). Indeed, the correlations between different HBIs in S. groenlandicus (i.e., Spearmans'r = 0.99 for IP 25 and HBI IIa; r ranged from 0.70 to 0.87 for HBI IIb, III and IV; Table 2) were as strong as those observed in sea ice, which attests to the almost exclusive contribution of sympagic algae to their diet during the sampling period. By contrast, the relatively weak correlations among HBIs in M. truncata (i.e., spearmans'r = 0.44 for IP 25 and HBI IIa; r ranged from 0.21 to 0.70 for HBI IIb, III and IV) imply a reduced sympagic contribution to their diet.

Effectiveness of essential fatty acid transfer from sea ice to bivalve

Based on lipid data, nMDS was employed to graphically represent the position of the 75 bivalves by year and species (Fig. 6). Unlike for S. groenlandicus, data for M. truncata samples were well clustered, suggesting low lipid variability among seasons or years. Indeed, M. truncata samples were distinguished from those of S. groenlandicus by relatively constant and lower fatty acid contents (ca. 6 and 3 times lower in 2015 and 2016 respectively; Table 3). This general pattern is reminiscent of that of the HBIs (as previously discussed) and reinforces the interpretation that M. truncata relies to a greater extent than S. groenlandicus on sedimentary organic matter for feeding.

Although the absolute quantities of lipid classes differed between years and bivalve species, their relative contribution was somewhat similar, with a mean PUFA (herein n-3 PUFA EPA and DHA) contribution to TFA above 40%, irrespective of species and sampling year (Table 3). This contribution is similar to those observed in other Arctic bivalves such as Astarte elliptica or Bathyarca glacialis [START_REF] Gaillard | Food resources of the bivalve Astarte elliptica in a sub-Arctic fjord: a multi-biomarker approach[END_REF][START_REF] Gaillard | Dietary tracers in Bathyarca glacialis from contrasting trophic regions in the Canadian Arctic[END_REF] and underscores the strong accumulation of these essential plant-derived molecules in benthic filter feeders. The benthos is known to respond rapidly to the influx of sympagic organic matter (days to weeks; [START_REF] Graf | Benthic-pelagic coupling in a deep-sea benthic community[END_REF][START_REF] Renaud | Pelagicbenthic coupling in the western Barents Sea: Processes and time scales[END_REF], principally due to its relatively high content in n-3 PUFAs [START_REF] Arrigo | Large scale importance of sea ice biology in the Southern Ocean[END_REF]. We confirmed, through HBI analysis, that sympagic material was quickly assimilated by M. truncata and S. groenlandicus after 21 April in 2015 and after 10

May in 2016 (Fig. 5A,B).

Since we argued previously that sympagic/pelagic-benthic coupling is relatively weak for M. truncate, we will hereafter focus on S. groenlandicus to assess the impact of sympagic fatty acid deliveries on the quality of bivalve flesh. Diatoms represent the dominant taxon of sympagic algae [START_REF] Amiraux | Temporal evolution of IP 25 and other highly branched isoprenoid lipids in sea ice and the underlying water column during an Arctic melting season[END_REF][START_REF] Brown | Quantitative estimates of sinking sea ice particulate organic carbon based on the biomarker IP 25[END_REF][START_REF] Ratkova | Sea ice algae in the White and Barents seas: composition and origin[END_REF] and are known as good producers of EPA [START_REF] Kelly | Fatty acids as dietary tracers in benthic food webs[END_REF][START_REF] Viso | Fatty acids from 28 marine microalgae[END_REF], which was the main n-3 PUFA present in our bivalve samples (Table 3). It is therefore not surprising that the palmitoleic/palmitic acid ratio, as well as the TFA and PUFA contents, were similar during both sampling years (Fig. 7). S. groenlandicus harvested before the period of peak algal production were then characterized by relatively high palmitoleic/palmitic ratios consistent with relatively strong diatom contribution to their lipid reserves. By contrast, these ratios were low in S. groenlandicus specimens feeding on sympagic algae (as attested by HBI measurements), at or near the apogee of the productive period in sea ice (Table 3; Fig. 7).

While this apparent diminution of the diatom signal is unexpected at a time when ice algal deliveries to the sea floor increase, prior studies have shown that the deposition of sympagic algal biomass onto the seafloor is particularly important early in the spring when the intake of C and n-3 PUFA is required to jumpstart benthic growth and reproduction after the food limited winter [START_REF] Mcmahon | Benthic community response to ice algae and phytoplankton in Ny Ålesund, Svalbard[END_REF][START_REF] North | Deposit-feeder diets in the Bering Sea: potential effects of climatic loss of sea ice-related microalgal blooms[END_REF]. Thus, these seemingly low sympagic POM intakes by bivalves result most likely from their quick utilization of this organic matter (newly delivered or previously stored), rather than from a low contribution.

The reproduction of intertidal bivalves includes gametogenesis, development and metamorphosis, all of which are energy-consuming processes [START_REF] Martinez | Effect of diet and temperature upon muscle metabolic capacities and biochemical composition of gonad and muscle in Argopecten purpuratus Lamarck 1819[END_REF]. The success of these processes depends on the overall physiological condition and especially the pre-spawning condition of the adults. The larger the build-up of storage material, the more weight loss the animal can incur at spawning without endangering its subsequent survival and growth [START_REF] Beukema | Maximizing lifetime egg production in a Wadden Sea population of the tellinid bivalve Macoma balthica: a trade-off between immediate and future reproductive outputs[END_REF]. In the present study, we identified the spawning period from the intake of sympagic material by the bivalves (indicated by IP 25 enrichment; Fig. 5) and the steep concurrent decrease in their fatty acid content (Fig. 7). Although the pre-spawning conditions were different among years and bivalve species (e.g., the initial PUFA dry mass of S. groenlandicus was two-fold higher from 18 January to 21 April 2015 and from 07 January to 10 May 2016 respectively), on the last sampling day of both years the two species presented similar n-3 PUFA contents, but differed in their TFA contents (Table S3, S4). This pattern suggests that the n-3 PUFA content observed at the end of the sampling period represents the residual amount necessary to ensure organism survival once it has completed its spawning effort. The fact that pre-spawning n-3 PUFA and TFA contents in M. truncata were lower than their post-spawning values in 2015 (Fig. 7), suggests that the animals were then unable to acquire enough essential fatty acids for the reproductive effort, which may have been delayed

or suppressed in that year.

Conclusion

We examined the contents of n-3 PUFA and HBIs of sea ice POM and two different filterfeeding bivalve species during two Arctic melting seasons that took place in southwest Baffin Bay. The results underscored a relatively strong seasonal and interannual variability in the production of organic matter (whether fatty acid or chlorophyll a) and biomarkers in sea ice, due to different conditions of air temperature, snow deposition and transmitted PAR. The sea ice nevertheless shared many common characteristics during the two melting seasons, including (i) a similar productivity of IP 25 , (ii) a production of the so-called HBI pelagic biomarker HBI III that seasonally preceded that of IP 25 , (iii) a temporal mismatch between chlorophyll a and fatty acid production peaks. Although Spring 2015 was the most productive for nearly all the parameters analyzed (e.g., TFA, Chl a), Spring 2016 was the most productive in terms of the lipids considered essential (the n-3 PUFAs EPA and DHA) for the growth and reproduction of bivalves. By tracking the different HBIs, their levels and the correlations between each of those, we (i) confirmed that sympagic-benthic coupling is tight on Arctic shelves (ii) showed that unlike M. truncata, S. groenlandicus can be used as a responsive sentinel of pelagic-benthic coupling, and (iii) confirmed that HBI III is present in sea ice, which may weaken the robustness of some HBI-based proxies. By monitoring the fatty acid content of bivalves from winter to late spring, we (i) showed that these animals greatly accumulate essential fatty acids (mean relative contributions exceeding 40%), (ii) identified their pre-spawning and post-spawning periods, and (iii) proposed that M. truncata may fail to store enough essential fatty acids to support its reproductive effort in some years. Table S1: Shell, wet, dry mass and dry/wet ratio of Mya truncata and Serripes groenlandicus collected in Davis strait between (A) January and June 2015 and (B) January and June 2016.

Figure caption

Values are means (SE).

Table S2: Fatty acid composition, expressed as mass % of total fatty acids (TFA), of POM collected in the 0-3 cm of sea ice in Davis strait between 24 April to 24 June 2015 and, 16 May to 8 July 2016. Fatty acids above > 3% in at least one of the sea ice sampling investigated were included. TFA = total fatty acids expressed in mg L -1 ; SFA = saturated fatty acid; MUFA = monounsaturated fatty acid; PUFA = polyunsaturated fatty acid. Values are means (SE).

Table S3: Fatty acid composition, expressed as mass % of total fatty acids (TFA), of (A) Serripes groenlandicus and (B) Mya truncata collected in Davis strait between January and June 2015. Fatty acids above >3% in at least one of the bivalve sampling investigated were included. TFA = total fatty acids expressed in mg g -1 dry mass; SFA = saturated fatty acid; MUFA = monounsaturated fatty acid; PUFA = polyunsaturated fatty acid. Values are means (SE).

Table S4: Fatty acid composition, expressed as mass % of total fatty acids (TFA), of (A) Serripes groenlandicus and (B) Mya truncata collected in Davis strait between January and June 2016. Fatty acids above > 3% in at least one of the bivalve sampling investigated were included. TFA = total fatty acids expressed in mg g -1 dry mass; SFA = saturated fatty acid; MUFA = monounsaturated fatty acid; PUFA = polyunsaturated fatty acid. Values are means (SE).

Figure 1 :

 1 Figure 1: Numbering system used to describe structural characteristics of highly branched isoprenoids (I) and structures of some common C 25 highly branched isoprenoids (IP 25 -IV).

Figure 2 :

 2 Figure 2: Map of the study area with location of the station investigated in southwest Baffin Bay.

Figure 3 :

 3 Figure 3: Time series of chlorophyll a and total fatty acid concentration in the bottom 0-3 cm sea ice section from (A) 25 April to 24 June 2015 and from (B) 16 May to 8 July 2016 at the sampling location in southwest Baffin Bay (Fig. 2).

Figure 4 :

 4 Figure4: Principal Component analysis (PCA) biplot representing the distribution of sea ice samples collected at different sampling time and year according to the environmental core variables: chlorophyll a (Chl a), snow thickness (Snow), air temperature (Temperature), photosynthetically active radiation (PAR). total fatty acid (TFA) and polyunsaturated fatty acid content (PUFA). The PCA accounts for 64.1% of the total variation among sea ice sampling dates (Axis 1: 44.2% and Axis 2: 19.9%). The environmental variables are displayed according to their contribution (%) to the dimensions of the biplot. The quality of the contribution is colored (good contribution should be higher than 15: orange, indicator length of arrow).

Figure 5 :

 5 Figure 5: Time series of IP 25 (A, B) and HBI III (C, D) in sea ice (watermark) and bivalve collected from (A, C) 25 April to 24 June 2015 and from (B, D) 16 May to 8 July 2016 at the sampling location in southwest Baffin Bay (Fig. 2).

Figure 6 :

 6 Figure 6: Non-metric multidimensional scaling (nMDS), based on the Euclidean distance on normalized lipid data (HBI and fatty acids) representing the position of the 75 bivalves collected species (Mya truncata or Serripes groenlandicus) and sampling year (2015 or 2016) on the ordination diagram. 2D stress = 0.06.

Figure 7 :Table 1 :

 71 Figure 7: Time series of palmitoleic/palmitic acid ratio (A, B), total fatty acid (C, D) and polyunsaturated fatty acid content (E, F) in Mya truncata and Serripes groenlandicus collected from (A, C, E) 25 April to 24 June 2015 and from (B, D, F) 16 May to 8 July 2016 at the sampling location in southwest Baffin Bay (Fig. 2).

Table 2 :Table 3 :

 23 Correlation coefficients between chlorophyll a (Chl a) and HBI biomarkers in sea ice POM, Serripes groenlandicus and Mya truncata collected in 2015 and 2016 in southwest Baffin Bay (Fig.2). Mean fatty acid composition, expressed as mass % of total fatty acids (TFA), of (A) Serripes groenlandicus and (B) Mya truncata collected in Davis strait between January and June 2015 and between January and June 2016. Fatty acids above >3% in at least one of the bivalve sampling investigated were included. TFA = total fatty acids expressed in mg g -1 dry mass; SFA = saturated fatty acid; MUFA = monounsaturated fatty acid; PUFA = polyunsaturated fatty acid. Values are mean (SE).

Table 1 :

 1 Mean fatty acid composition, expressed as mass % of total fatty acids (TFA), of POM collected in the 0-3 cm of sea ice in Davis strait between 24 April to 24 June 2015 and, 16 May to 8 July 2016. Fatty acids above > 3% in at least one of the sea ice sampling investigated were included. TFA = total fatty acids expressed in mg L -1 ; SFA = saturated fatty acid; MUFA = monounsaturated fatty acid; PUFA = polyunsaturated fatty acid. Values are mean (SE).

	Fatty acid	Sea ice sampling year
		2015	2016
	14:00	4.7 (0.4)	4.2 (0.3)
	16:00	26.1 (1.9)	30.8 (2.8)
	∑SFA	30.7 (1.9)	35.0 (2.8)
	16:1ω7	68.9 (2.0)	53.6 (3.2)
	18:1ω9	5.4 (0.1)	0.3 (0.1)
	∑MUFA	68.9 (2.0)	53.6 (3.2)
	EPA	0.5 (0.3)	10.3 (1.7)
	DHA	0.0 (0.0)	1.2 (0.3)
	∑PUFA	0.4 (0.3)	11.4 (1.9)
	TFA a	57.9 (14.0)	11.0 (2.7)

a Expressed in mg L -1

Acknowledgements

We especially thank E. Brossier for the sampling of bivalves, C. Guilmette and F. Dufour for providing preliminary lipid results. This project was made possible by the support of the hamlet of Qikiqtarjuaq and the members of the community together with the Inuksuit School and its Principal, Jacqueline Arsenault. It was conducted under the scientific coordination of the Canada Excellence Research Chair on Remote Sensing of Canada's new Arctic frontier and the CNRS & Université Laval Takuvik Joint International Laboratory (UMI3376). The field campaigns (Scientific Research License # 01 010 15N-M and # 01 001 16R-M) owed its success to the contribution of J. Ferland, G. Bécu, C. Marec, J. Lagunas, F. Bruyant, J. Larivière, E. Rehm, S. Lambert-Girard, C. Aubry, C. Lalande, A. LeBaron, C. Marty, J. Sansoulet, D. Christiansen-Stowe, A. Wells, M. Benoît-Gagné, E. Devred and M.-H. Forget from the Takuvik Laboratory, C.J. Mundy from the University of Manitoba and F. Pinczon du Sel and E. Brossier from Vagabond. We also thank the FRQNT strategic network Québec-Océan, the CCGS Amundsen and the Polar Continental Shelf Program for their in-kind contribution in polar logistics and scientific equipment. We especially thank C. Nozais from the Université du Québec à Rimouski for providing the sediment traps, C. Lalande (Project leader), C. Aubry, and T. Dezutter from the Université Laval Joint International Laboratory and Takuvik Laboratory for allowing the 2016 short-term sediment trap deployment. This work contributes to the scientific programs of Takuvik and Québec-Océan. We are grateful to the two anonymous reviewers, for providing helpful comments on a previous version of the manuscript.

Data accessibility statement

All data are accessible at the Green Edge database (http://www.obsvlfr.fr/proof/php/GREENEDGE/greenedge.php) and will be made public after publication.

Funding information

The first author (RA) received financial support from the Université Bretagne Loire (UBL)

Competing interests

The authors declare that they have no competing interests.

Supplemental material

There are four pieces of supplemental material (Table S1, S2, S3, S4).

Declaration of interests

☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Highlights  Spring sea ice has strong interannual IP 25, TFA and PUFA production variability  Production of the 'pelagic' biomarker HBI III observed in sea ice  Incorporation of sea ice-derived HBI III observed in bivalves  S. groenlandicus is a responsive sentinel of Arctic sympagic-benthic coupling  M. truncata did not store enough essential fatty acids to support reproduction


Maria V Murgia

Lesley Bell-Sakyi

Timothy J Kurtti

Benjamin L Makepeace

Ben Mans

Karen D Mccoy

Uli Munderloh

Olivier Plantard

Claude Rispe

Manuel Rodriguez Valle

Ala Tabor

Saravanan Thangamani

Catherine A Hill
email: hillca@purdue.edu

"Meeting the challenge of tick-borne disease control: A proposal for 1000 Ixodes genomes" Ixodes 1000 Genomes Consortium, Leadership Team

Keywords: Ixodes, Ixodida, Genomics, Tick, Tick-borne diseases, Ultra-long

Introduction

At the 'One Health' 9th Tick and Tick-borne Pathogen Conference and 1 st Asia Pacific Rickettsia Conference (TTP9-APRC1; http://www.ttp9-aprc1.com), 27 August-1 September 2017 in Cairns, Australia, members of the tick and tick-borne disease (TBD) research communities assembled to discuss a high priority research agenda. Diseases transmitted by hard ticks (subphylum Chelicerata; subclass Acari; family Ixodidae) have substantial impacts on public health and are on the rise globally due to human population growth and change in geographic ranges of tick vectors (de la [START_REF] De La Fuente | Tick Genome Assembled: New Opportunities for Research on Tick-Host-Pathogen Interactions[END_REF]. The genus Ixodes is a global menace. Members of the genus impact human and animal health directly via host parasitism, and indirectly via transmission of multiple viral, bacterial and protozoan diseases. The first tick genome assembly was completed in 2016 for Ixodes scapularis (blacklegged tick), the North American vector of Lyme disease (LD), human babesiosis, human anaplasmosis and Powassan virus (Gulia-Nuss et al., 2016). The assembly provided insight into the genome biology of hard (ixodid) ticks and supported molecular studies for many species of Acari (ticks and mites). Draft genome assemblies are available for Ixodes ricinus (castor bean tick; [START_REF] Cramaro | Integration of Ixodes ricinus genome sequencing with transcriptome and proteome annotation of the naïve midgut[END_REF]2017) and Rhipicephalus (Boophilus) microplus (southern cattle tick; [START_REF] Barrero | Gene-enriched draft genome of the cattle tick Rhipicephalus microplus: assembly by the hybrid Pacific Bioscience/Illumina approach enabled analysis of the highly repetitive genome[END_REF]. However, high quality reference assemblies to rival those produced for the mosquito vectors Anopheles gambiae (Neafsey et al., 2015) and Aedes aegypti (Mathews et al., 2017), have not been produced for a tick vector. Conference attendees identified the need to expand genomic resources for tick research, beginning with the genus Ixodesone of the most important phyletic groups affecting human and animal health worldwide. Inspired by the 1000 Anopheles genomes effort (Malaria Genomic Epidemiology Network, Ag1000G), an ambitious goal to sequence and assemble the genomes of 1000 Ixodes ticks was proposed. The Ixodes 1000 genomes project (Ix1000G) outlines a "hub and spoke" model to sequence both laboratory reference strains and natural populations of Ixodes. The project is aligned with other ambitious genome initiatives such as the i5K effort that proposes to sequence 5000 arthropod species [START_REF] Evans | The i5K Initiative: advancing arthropod genomics for knowledge, human health, agriculture, and the environment[END_REF] and the Earth BioGenomes project, a moonshot to sequence and catalog all of Earth's biodiversity [START_REF] Lewin | Earth BioGenome Project: Sequencing life for the future of life[END_REF]. The Ixodes 1000 Genomes Consortium (IGC) represents an international scientific collaboration formed to launch and guide the initiative. This Letter to the Editor defines the strategic vision of the Ix1000G and serves as a call to the broader scientific community for engagement.

The need for tick genome resources

Tick-borne diseases affect human and animal health globally. Lyme disease (LD) is one of the most important TBDs in North America and Europe. It is estimated that the approximately 30,000 human cases reported to the U.S. Centers for Disease Control and Prevention (CDC) each year represent only about 10% of actual cases (CDC; [START_REF] Hinckley | Lyme disease testing by large commercial laboratories in the United States[END_REF][START_REF] Nelson | Incidence of clinician-diagnosed Lyme disease, United States, 2005-2010[END_REF]. In Europe, roughly 85,000 LD cases are reported annually, although actual case numbers are unknown (European Centre for Disease Prevention and Control (ECDC), 2012). Recent studies are also shedding light on the transmission of human and animal pathogens by Australian ticks and the role of Ixodes holocyclus, as a vector (reviewed in [START_REF] Graves | Tick-borne infectious diseases in Australia[END_REF]Greay et al., 2018). Options to control hard ticks and the pathogens they transmit are limited. Human vaccines are not available, except against the tick-borne encephalitis virus (Heinz and Stiasny, 2017). Diagnosis and treatment of many TBDs is a challenge because reliable, comprehensive molecular and immunological diagnostics are lacking. Control is also complicated by environmental impacts of acaricides and development of resistant tick populations. Human-tick encounters and pathogen transmission are increasing as geographic ranges of ticks expand and humans exploit new habitats. The need for new strategies to control ticks has never been greater. This need is reflected in recent funding announcements from the U.S. National Institutes of Health (NIH), the Department of Defense (DoD) Congressionally Directed Medical Research Programs (CDMRP), FY17 "Tick-Borne Disease Research Program (TBDRP)", and the U.K. Biotechnology and Biological Sciences Research Council (BBSRC) and Medical Research Council (MRC) "Networks in Vector Borne Disease Research". Pressing questions remain in TBD research: how do pathogen complements vary in tick populations at local and regional scales? How do tick microbiomes (including symbionts) and vector genetics affect pathogen transmission and disease outcome? How can scientists best develop comprehensive, region-specific diagnostics, risk matrices and treatment regimes? Fortunately, advances in sequencing and the rapidly-evolving field of data science offer the tools to address many of these questions. The I. scapularis genome sequence (Gulia-Nuss et al., 2016) and other molecular and genetic resources for a number of Ixodes species such as transcriptome, sialome and mialome datasets (reviewed in [START_REF] Chmelař | Sialomes and mialomes: a systems biology view of tick tissues and tick-host interactions[END_REF]Rodriguez Valle et al., 2018), and the establishment of the DNA and tissue repository via the Global Genome Biodiversity Network (Gonzales et al, 2017), are an important beginning. However, incremental advances in science will not be adequate to meet pressing public health needs; ambitious goals must be proposed to effect a rapid paradigm shift in TBD research.

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M A N U S C R I P T

Data-driven solutions for tick and tick-borne disease control

Multiple species of ticks and mites of medical significance have been recognized as high priority targets for sequencing by the NIH [START_REF] Hill | Genome analysis of major tick and mite vectors of human pathogens[END_REF]Gulia-Nuss et al., 2016). These projects were not advanced due to the limitations of sequencing platforms available at the time. Recently, ultra-long read, single-molecule and genome scaffolding technologies have enabled production of genome assemblies for multiple eukaryotes, including mosquitoes [START_REF] Jiao | Improved maize reference genome with single-molecule technologies[END_REF]Zimin et al., 2017;Ag1000G, 2017Mathews et al., 2017). The genomes of 765 field-collected Anopheles gambiae and Anopheles coluzzii from 15 locations were sequenced by the Ag1000G project (Ag1000G, 2017). The Ae. aegypti L5 genome assembly produced by [START_REF] Matthews | Improved Aedes aegypti mosquito reference genome assembly enables biological discovery and vector control[END_REF] comprises chromosome-length scaffolds produced via a hybrid PacBio (Pacific Biosciences) and HiC (Dovetail Genomics) approach. These landmark achievements suggest that modern sequencing technologies will have utility for assembling the large, repeat-rich genomes of ixodid ticks.

The broad objectives of the Ix1000G are to: (1) build multiple reference assemblies to support research on Ixodes vectors in North America, Europe, Africa and the Asia-Pacific, (2) catalogue natural genetic variation among wild populations of Ixodes and their microbial assemblies, (3) describe the genetic history and population structure of Ixodes species, and (4) combine genetic variation with biological data to understand tick ecology, epidemiology and disease transmission. The Ix1000G will generate fundamental resources for identification and analysis of tick genes and other genomic features, and will support three critical areas needed to advance research on tick and TBD control:

The systems biology of tick-host-pathogen interactions. Every tick bite represents a unique, complex molecular interaction between the tick, the pathogen and the immunological landscape of the vertebrate host. Potentially hundreds of tick salivary factors and microbes are delivered to the host dermis during blood feeding, which lasts for days to over a week. Furthermore, molecular interactions between ticks and commensal or pathogenic microorganisms within tick microbiota may also shape pathogen infection and transmission. Genomics offers opportunities to unravel the systems biology of tick-host-pathogen interactions across multiple Ixodes species.

The link between tick genetics, vector competence and disease transmission. To understand this link, there is need to evaluate the correlation between the genetic structure of tick populations and their microbial complement, including pathogens and symbionts. Molecular studies have revealed multiple genetic clades, signatures of north-south population structure (Gulia-Nuss et al., 2016), and evidence for gene flow between populations of I. scapularis (Van Zee et al., 2015), but implications for pathogen transmission remain unclear. As sequences of tick-associated microbes are typically recovered with tick genome data, results from the Ix1000G will provide fundamental insight into this tripartite relationship.

Genetic frameworks for Ixodes control. Population genomic studies can directly inform pest management strategies for Ixodes and other tick pests. Applications may involve the development of acaricides with speciesselective activity and innovative approaches through microbiome manipulation to disrupt pathogen transmission similar to strategies being explored for triatomine bugs and tsetse flies [START_REF] Hurwitz | A Paratransgenic Strategy for the Control of Chagas Disease[END_REF][START_REF] Medlock | Evaluating Paratransgenesis as a Potential Control Strategy for African Trypanosomiasis[END_REF]. Population genetics data can also support the development of resistance management and genetic control strategies. For example, genome-wide analyses revealed high levels of heterogeneity between hundreds of Anopheles in Africa, suggesting potential for introduction of resistance alleles and evolution of insecticide resistance (Ag1000G, 2017). This indicates the need for genetic control programs tailored to the genetic background of local mosquito populations, and molecular analyses of resistance alleles suggest the same phenomenon will apply to tick populations.

The Ix1000G roadmap

The Ix1000G strategy calls for whole genome deep sequencing to generate reference assemblies for multiple Ixodes species (Priority Area 1) as well as a high-resolution view of genetic variation and microbiome structure in natural populations across the genus (Priority Area 2). Global project partners will source materials and work with teams skilled in data analysis to execute the project in phases, with oversight provided by the IGC. Importantly, the IGC will define a set of standards for genome assembly and annotation aligned with those recognized by sequencing institutes and the Genomic Standards Consortium (Chain et al., 2009; http://gensc.org/).

Priority area 1: High quality reference assemblies for Ixodes node species

The Consortium proposes sequencing and assembly of up to six node species via a combination of PacBio ultra-long-read technology and Hi-C scaffolding of assembled regions. This approach has been used to

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generate high quality reference assemblies for An. gambiae and Ae. aegypti (Ag1000G, 2017[START_REF] Matthews | Improved Aedes aegypti mosquito reference genome assembly enables biological discovery and vector control[END_REF]. The Ixodes species listed in Figure 1 have been identified as high priority sequencing targets on the basis of medical significance and potential to anchor additional genome studies across the genus Ixodes. This includes population genomic studies as described under Priority Area 2 below. Sequencing will generate a high-quality reference assembly for I. scapularis, building on the existing draft genome. Efforts to generate an improved assembly for I. ricinus are already underway via the GenIric project (http://www.angersnantes.inra.fr/en/All-the-news/GenIric). Reference genomes will support production of assemblies for other species of Ixodes, as well as alignment and analysis of genomic data from field-caught specimens. Species such as Ixodes affinis, Ixodes uriae and Ixodes cookei that are thought to play a minor role in disease transmission, or that do not primarily parasitize humans, are recommended for comparative analyses. The engagement of laboratories with the capability to source ticks and prepare genetic material for sequencing will be critical to these efforts (see Table 1). To obtain sufficient DNA for long read libraries (PacBio, 10X or Nanopore) and reduce heterogeneity in sequenced samples, the IGC proposes to sequence one individual of each node species (or a minimal number). In-bred reference strains should be established via sib-matings for each node species in the case of species listed in Table 1 that have not already been colonized. This would provide source material of similar genetic background for Chicago and Hi-C libraries to support genome scaffolding, and complementary transcriptomic and proteomic studies to validate predicted coding sequences and analyses of gene expression.

The IGC also identified the generation of reference assemblies for tick cell lines in regular use by the scientific community as a priority [START_REF] Oliver | An Ixodes scapularis cell line with a predominantly neuron-like phenotype[END_REF][START_REF] Miller | A draft genome sequence for the Ixodes scapularis cell line[END_REF]Tick Cell Biobank: https://www.liverpool.ac.uk/infection-and-global-health/research/tick-cell-biobank/; Table 1). Forward genetic approaches can be used to identify genes associated with vector competence and acaricide resistance. Inbred strains of ticks with quantifiable traits will facilitate genome-wide association studies (GWAS) and mapping of quantitative trait loci (QTL) that must be developed.

Priority area 2: Genomics of natural Ixodes populations and microbiome composition/structure

Under this priority area, the Consortium recommends deep sequencing of several hundred individual ticks belonging to the six node species via an Illumina approach. These should be collected from 10 or more geographic locations across North America, Europe, Africa and Asia. Dual digest Restriction Site Associated DNA sequencing (ddRADseq) may offer a complementary and more financially-viable strategy to generate population genomic data. These studies will also reveal sequences of symbionts and pathogens, and provide insight into the microbiome structure of Ixodes at macro-geographic scales. The initial Ix1000G goal proposes a target of 1000 genomes, but the effort is expected to encourage generation of genome data from many thousands of individual ticks in subsequent phases.

Conclusions and Broader Impacts

The Ix1000G will provide a critical framework to support genome studies of other ticks, and mites, of medical importance, including members of the metastriate genera Amblyomma, Rhipicephalus and Dermacentor that include multiple vector species. Moreover, genomes for several mite species of medical importance are already available [START_REF] Chan | The draft genome, transcriptome, and microbiome of Dermatophagoides farinae reveal a broad spectrum of dust mite allergens[END_REF][START_REF] Mofiz | Genomic resources and draft assemblies of the human and porcine varieties of scabies mites, Sarcoptes scabiei var. hominis and var. suis[END_REF][START_REF] Rider | Allergen homologs in the Euroglyphus maynei draft genome[END_REF], including a recent genomic analysis of the scrub typhus vector Leptotrombidium deliense [START_REF] Dong | Genomes of trombidid mites reveal novel predicted allergens and laterallytransferred genes associated with secondary metabolism[END_REF]. These members of the Acari, with smaller nuclear genomes compared to hard tick species, will support genomic analyses while the more challenging reference assemblies and population genomic studies of wild Ixodes populations are in development. Given the worldwide medical and veterinary importance and smaller nuclear genome size of Ixodes species as compared to metastriate ticks, coupled with the availability of supporting genomic resources, the genus Ixodes represents a logical starting point for generation of high quality reference assemblies and population genomic data. This Letter to the Editor is an official call for project partners and strategic investment to advance the Ix1000G initiative. The broader, long-term vision is an assemblage of data from many thousands of Ixodes ticks and a detailed understanding of genetic diversity among Ixodes populations worldwide. Data will be used to understand the transmission of TBDs in the context of tick genetics and microbiome communities. The Ix1000G will operate across geographic boundaries to provide the first global genomic resource for tick research and help meet the Grand Challenge of tick and TBD control on a global scale.

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M A N U S C R I P T A C C E P T E D M A N U S C R I P T A C C E P T E D M A N U S C R I P T
Rodriguez-Valle, M., Moolhuijzen, P., Barrero, R.A., Ong, C.T., Busch, G., Karbanowicz, T., Booth, M., Clark, R., Koehbach, J., Ijaz, H., Broady, K., Agnew, K., Knowles, A.G., Bellgard, M.I., Tabor, A.E., 2018. Transcriptome and

A

  .V.,Puiu, D., Hall, R., Kingan, S., Clavijo, B.J., Salzberg, S.L., 2017. The first near-complete assembly of the hexaploid bread wheat genome, Triticum aestivum. GigaScience 6, 1-7. https://doi.org/10.1093/gigascience/gix097

Figure 1 .

 1 Figure 1. Schematic showing six "node" species of Ixodes recommended as targets for deep genome sequencing. The species Ixodes scapularis, Ixodes pacificus, Ixodes ricinus, Ixodes persulcatus, Ixodes rubicundus and Ixodes holocyclus were selected based on status as disease vectors and their potential to anchor population genomic studies across the genus Ixodes. Segments of the pie chart show diseases transmitted or caused by ticks: BAC, Bacterial Artificial Chromosome library; LD, Lyme disease; HGA, Human granulocytic anaplasmosis; TBE, Tick-borne encephalitis; SFGR, Spotted fever group rickettsiosis.

  Figr-1

  toxin family analysis of the paralysis tick, Ixodes holocyclus. Int. J. Parasitol. 48, 71-82. doi: 0.1016/j.ijpara.2017.07.007. The Tick Cell Biobank: https://www.liverpool.ac.uk/infection-and-global-health/research/tick-cell-biobank/ Van Zee, J., Piesman, J.F., Hojgaard, A., Black, W.C. IV., 2015. Nuclear markers reveal predominantly North to South gene flow in Ixodes scapularis, the tick vector of the Lyme Disease spirochete. PLoS One. 10, e0139630. doi:10.1371/journal.pone.0139630

Table 1 . Ixodes species proposed for genome sequencing (priority area 1) and availability of colonies and cell lines for sequencing. Tick Species Pathogen Transmitted Disease Genome Project Resource s Scientific Name Common Name North America

 1

	Ixodes	Blacklegg	Borrelia burgdorferi	LD	Colonies;
	scapularis	ed tick	Babesia microti	Babesiosis	UTMB;
			Anaplasma phagocytophilum	HGA	BEI
			Powassan virus	Powassan	Resource
			Borrelia miyamotoi	encephalitis	s a ; field
				Borrelia miyamotoi	specimen
				disease	s
	Ixodes	Western	Borrelia burgdorferi	LD	Colonies;
	pacificus	blacklegg	Anaplasma phagocytophilum	HGA	BEI
		ed tick	Borrelia miyamotoi	Borrelia miyamotoi	Resource
				disease	s
			Europe
	Ixodes	Castor	Borrelia spp	LD	Colonies;
	ricinus	bean tick	Borrelia miyamotoi	Borrelia miyamotoi	UTMB
			TBE virus	disease
			Candidatus Neoehrlichia	TBE
			mikurensis	Neoehrlichiosis
			Anaplasma phagocytophilum	Tick-borne fever of
			Francisella tularensis	ruminants, HGA
			Louping ill virus	Tularemia
			Babesia divergens, Babesia	Louping ill of sheep
			microti, other Babesia spp.	and grouse
			Rickettsia helvetica	Babesiosis
				Human SFGR
			Asia-Pacific
	Ixodes	Australian	Rickettsia australis	Tick paralysis	Field
	holocyclus	paralysis tick	Coxiella burnetti		specimen s;
	Ixodes	Taiga tick Borrelia spp.	LD	-
	persulcatu		Borrelia miyamotoi	Borrelia miyamotoi
	s		TBE virus	disease
			Anaplasma phagocytophilum,	TBE
			Ehrlichia spp.	HGA
				Ehrlichiosis
			Africa
	Ixodes	South	No known etiological agents	Tick paralysis	Laborator
	rubicundus	African			y colonies;
		Karoo			Univ.
		paralysis			South
		tick			Africa
			Minor species
	Ixodes		Borrelia burgdorferi	LD	-
	affinis
	Ixodes uriae	Seabird tick	Borrelia garinii	LD	-

Acknowledgements:

The authors thank Ben Matthews, The Rockefeller University, New York, United States and Martin Donnelly, Liverpool School of Tropical Medicine, Liverpool, United Kingdom for helpful discussions.

Declaration of interest:

The authors declare no competing interests.

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