Wolbachia is one of the most prevalent bacterial endosymbionts, infecting approximately 40% of terrestrial arthropod species. Wolbachia is often a reproductive parasite but can also provide fitness benefits to its host, as, for example, protection against viral pathogens. This protective effect is currently being applied to fight arboviruses transmission by releasing Wolbachia-transinfected mosquitoes. Titre regulation is a crucial aspect of Wolbachia biology. Higher titres can lead to stronger phenotypes and fidelity of transmission but can have a higher cost to the host. Since Wolbachia is maternally transmitted, its fitness depends on host fitness, and, therefore, its cost to the host may be under selection. Understanding how Wolbachia titres are regulated and other aspects of Wolbachia biology has been hampered by the lack of genetic tools. Here we developed a forward genetic screen to identify new Wolbachia over-proliferative mutant variants. We characterized in detail two new mutants, wMelPop2 and wMelOctoless, and show that the amplification or loss of the Octomom genomic region lead to over-proliferation. These results confirm previous data and expand on the complex role of this genomic region in the control of Wolbachia proliferation. Both new mutants shorten the host lifespan and increase antiviral protection. Moreover, we show that Wolbachia proliferation rate in Drosophila melanogaster depends on the interaction between Octomom copy number, the host developmental stage, and temperature. Our analysis also suggests that the life shortening and antiviral protection phenotypes of Wolbachia are dependent on different, but related, properties of the endosymbiont; the rate of proliferation and the titres near the time of infection, respectively. We also demonstrate the feasibility of a novel and unbiased experimental approach to study Wolbachia biology, which could be further adapted to characterize other genetically intractable bacterial endosymbionts. Wolbachia is one the most common of such bacteria and can strongly influence the insect biology. Its capacity to protect some hosts from viral infection is being used in the fight against mosquitoes-transmitted viruses by introducing Wolbachia in these insects. The amount of Wolbachia within the host can impact their interaction and must be well controlled. To understand this process we screened for new mutants of Wolbachia that proliferate too much in the fruit fly Drosophila melanogaster. We identified two mutants and characterized them in detail. One mutant has too many copies of a specific set of genes, confirming previous similar results. However, the other mutant Wolbachia lost those exact same genes, showing that they are particularly important in growth regulation. Moreover, we show that proliferation of different Wolbachia variants depends on temperature, and the developmental stage of the insect host. Finally, the data indicate that protection to viruses and cost of Wolbachia depend on related but different aspects of this control of growth. In summary, we show that we can screen for new mutants of Wolbachia and understand better how control of growth is genetically controlled by Wolbachia.Insects often carry bacteria that live within their cells and are transmitted from the mother to the progeny.  Intracellular maternally-transmitted bacterial symbionts are widespread in insects . These bWolbachia is one of the most prevalent bacterial endosymbionts in arthropods, being found in approximately 40% of terrestrial arthropod species [Wolbachia is broadly known as a host reproduction manipulator [ipulator . Howeveripulator  or proteipulator ,8.Wolbachia-induced protection against viruses in Drosophila melanogaster, prompted its use to control arboviruses transmission by insect vectors [Aedes aegypti mosquitoes trans-infected with Wolbachia have increased resistance to viruses, including dengue, chikungunya, Zika, and yellow fever viruses, and, therefore, reduced vector competence [Wolbachia-carrying mosquitoes in dengue-endemic areas is likely to reduce dengue burden [Wolbachia biology and interaction with viral pathogens, which hinders predicting the long-term outcome of Wolbachia-based interventions to control insect-vector transmitted viruses.The discovery of  vectors . Aedes ampetence –13. Relee burden ,15. DespWolbachia titres are a critical factor regulating its biology and interaction with the host [Wolbachia-induced phenotypes, including the Wolbachia pathogen blocking phenotype [Wolbachia, since as a vertically transmitted bacterium, its fitness depends on the host fitness. Thus, Wolbachia titres regulation by the symbiont or the host may be under selection. Although several host and environmental factors (e.g. temperature) have been shown to affect Wolbachia titres, less is known about Wolbachia genes that regulate its titres [the host . Titres henotype ,16–20. Ihenotype ,21,22. Ts titres .Wolbachia genetic factor, the Octomom region, has been shown to influence proliferation [wMelPop. Moreover, the degree of amplification of the Octomom region determines the proliferation rate of wMelPop and the strength of its life shortening phenotype [So far, a single feration ,17. ThisWolbachia, which remains unculturable so far, hampers the identification of more genetic modifications altering Wolbachia proliferation. Hence, unbiased approaches such as genetic screens could contribute to our understanding of the genetic bases of Wolbachia-host interactions. Here, we developed a screening strategy in Wolbachia to isolate novel over-proliferating variants. The strategy was based on random mutagenesis, which has been applied before to other unculturable bacteria [D. melanogaster females carrying Wolbachia and screened for over-proliferative Wolbachia in their progeny. This approach allowed us to isolate new over-proliferating Wolbachia mutants. We identified the genetic changes in Wolbachia causing over-proliferation and made a detailed phenotypical characterization in terms of proliferation, cost to the host, and antiviral protection. We identified a new mutation leading to Wolbachia over-proliferation and revealed a complex role for the Octomom region in regulating Wolbachia proliferation. Moreover, we demonstrated the feasibility of a novel and unbiased experimental approach to study Wolbachia biology.The genetic intractability of bacteria . We fed Wolbachia variants. We attempted to mutagenize Wolbachia by feeding the mutagen EMS to Wolbachia-carrying D. melanogaster females. EMS is extensively used in D. melanogaster [Wolbachia titres, by real-time quantitative PCR (qPCR), in the progeny of treated females, since this bacterium is maternally transmitted. We used flies with wMelCS_b as our starting variant because of its potential to easily become over-proliferative, given its genetic proximity to the over-proliferative and pathogenic wMelPop variant [We implemented a classical forward genetic screen in order to isolate new over-proliferative nogaster  and has nogaster . We then variant ,17,22,25Wolbachia cells within the host would be in a mixed population, which would make it harder to assess their specific phenotype. However, we hypothesized that over-proliferating Wolbachia cells could overtake the population and that the resulting higher titres could be detectable. Moreover, we decided to pre-treat some of the EMS exposed females with tetracycline to reduce the Wolbachia population in these females and their progeny. This Wolbachia titre reduction should decrease competition for any new mutated Wolbachia, increase drift during vertical transmission, and, therefore, potentially facilitate fixation of new variants. To set up the conditions for tetracycline treatment, we tested different doses of this antibiotic on females, without EMS. The progeny of treated females had from 0 to 90% of the Wolbachia titres in controls . We then followed the subsequent progeny of these flies to test how many fly generations it takes to recover normal Wolbachia titres. Except for higher tetracycline doses which lead to infection loss, Wolbachia titres recovered to normal within four fly generations .Putative mutagenized D. melanogaster females and Wolbachia titres. We observed that increasing doses of EMS reduce female fecundity . Moreover, we found that EMS feeding strongly reduces Wolbachia titres in the next generation, in a dose-dependent manner (p < 0.001). Titres were reduced by up to 90% when 8,000 mM EMS was supplied, leading to the loss of Wolbachia in the next generation in some lines (Wolbachia titres at the first generation (F1), the immediate progeny of EMS-treated females, and at the fourth generation after treatment (F4), when we would expect Wolbachia titres to recover after the severe reduction due to EMS treatment.We also tested for the effect of different EMS doses on the fecundity of me lines . Given tWolbachia titre was determined when females were ten days old, after they laid eggs, so that any putatively interesting progeny could be followed up.We screened approximately one thousand F1 progeny of EMS-treated females, in a range of experimental conditions, and at least one F4 female descendent per treated female. We varied EMS dose from 10 mM to 8,000 mM, and tetracycline dose from 0 μg/ml to 12.5 μg/ml, in different combinations . The relWolbachia than controls, suggesting the presence of over-proliferative variants .We designed the screen to find new mutants of omosomes . We thenWolbachia over-proliferation is mitochondria-determined. Thus, the mitogenome of the lines 1A and 2A, showing higher Wolbachia titres, were sequenced with Illumina short-reads and aligned to the mitochondrial reference genome release 6  and long-reads (Nanopore) and obtained single and circular genomes for each Wolbachia chromosome  [wMel genome (GenBank: CP046925.1) was also circular and comparable in size, structure and number of ORFs with previously published wMel genomes [wMel reference genome  . The new genomes ,27, incle genome . We foune genome . These rwMelCS_b using this pipeline (GenBank: CP046924.1), in order to be able to identify new mutations in the new variants. We also compared this new assembly of wMelCS_b with the wMel reference genome (GenBank: AE017196.1) and identified 37 indels and 146 SNPs between these variants (We assembled the genome of the control variant variants .Wolbachia variant in Line 1A (GenBank: CP046922.1) and wMelCS_b was an amplification of the Octomom region (wMelCS_b (GenBank: CP046924.1) and by qPCR  or high Octomom (8–9) copy number  and compared it to wMelPop2. We only detected the two SNPs previously identified between wMelCS_b and wMelPop  (wMelPop and wMelPop2 (We sequenced and assembled the wMelPop2 ). We alsMelPop2) , which wwMelPop2 , S8 Fig Wolbachia variant in line 2A (GenBank: CP046923.1) only differs from wMelCS_b by a deletion of a 20,938bp genomic fragment that includes the full-length Octomom region and one of its flaking direct repeats (wMelCS_b (GenBank: CP046924.1) confirmed this deletion as the only difference between the two . Since wMelOctoless and the variant in line 2B were identified in the same batch of mutagenesis, they may not be independent. However, and importantly, we obtained the same results with another independent over-proliferative line, isolated in a different batch of treatment, line 3A . Flies carrying wMelCS_b have the lowest relative titre of Wolbachia. Flies carrying variants with low amplification of the Octomom region have approximately twice the titres of Wolbachia, while flies carrying variants with high copy number of this region have three times more Wolbachia than wMelCS_b. Finally, flies carrying wMelOctoless have the highest titres, approximately four-fold higher than flies carrying wMelCS_b. Therefore, the deletion or amplification of the Octomom region impact Wolbachia titres at adult eclosion.In order to characterize better the phenotypes of the new and 29°C . The fliWolbachia variants, at different temperatures . We analysed this dataset by comparing specific set of variants to test differences between wMelOctoless and wMelCS_b, differences between wMelPop2 and wMelCS_b, and differences between levels of Octomom amplification in wMelPop and wMelPop2.To analyse proliferation during adult life, we fitted an exponential model to the titres over adult age and estimated doubling time of the eratures . DoublinwMelOctoless with wMelCS_b shows that this new variant replicates faster than wMelCS_b , although it is a relatively small difference at all temperatures , but increases at 29°C (p < 0.001).A direct comparison between wMelPop2 having high and low Octomom copy number with wMelCS_b and wMelOctoless shows that these variants with Octomom amplification have the highest growth rates at 25°C and 29°C  compared to wMelCS_b and wMelOctoless). At 18°C wMelPop2 with 3 copies of Octomom has a growth rate similar to wMelCS_b (p = 0.79) and lower than wMelOctoless (p < 0.001). While at this temperature the growth rate of wMelPop2 with 8–9 copies of Octomom is not significantly different from either wMelCS_b or wMelOctoless (p > 0.088 in both comparisons), and the estimated value is in-between the two .A comparison of  the two . The anawMelPop and wMelPop2, we compared these variants with low or high copy number of the Octomom region. The variants with high copy number have a higher growth rate than the variants with low copy number at all temperatures . These results confirm that the degree of amplification of the Octomom region controls the intensity of the over-proliferation of these variants, as shown before [wMelPop and wMelPop2 increase growth rate with temperature , confirming the analysis above.To test the effect of the degree of Octomom amplification on growth rate and differences between n before . Both lowMelPop and wMelPop2, which differ in two SNPs (see above), indicated a significant difference in growth between them at 25°C (p < 0.001). This could mean that these two SNPs also influence growth of Wolbachia. However, this could also be due to the fact that the copy number of the Octomom region was not equally controlled in wMelPop and wMelPop2 lines during these experiments. wMelPop low copy number line had 2–3 copies of Octomom, while the wMelPop2 line had 3 copies. To test if wMelPop and wMelPop2 indeed vary in proliferation rate, we repeated this experiment with a more tightly controlled Octomom copy number in these two lines, at 25°C  and there is no difference in growth between them (p = 0.39). This indicates that the genetic differences between these lines do not affect their growth and that they are equally influenced by Octomom copy number.The statistical model comparing  at 25°C . Both wMWolbachia variants, temperature and growth rate. There is a strong interaction between temperature and the increased proliferation of variants with amplification of the Octomom region, wMelPop and wMelPop2, when compared with wMelCS_b. The effect of the amplification is not significant at 18°C and becomes increasingly stronger at higher temperatures. On the other hand, loss of Octomom leads to a smaller effect in growth, but similar at all temperatures, when compared with wMelCS_b. Therefore, although both genomic mutations lead to an increase in Wolbachia titres they have different impacts in the growth rates and interaction with temperature.Overall, the data and analysis show a complex interaction between wMelCS_b, wMelOctoless and wMelPop2 (8–9 Octomom copies) during host development. D. melanogaster develops from egg to adult in only 10 days, at 25°C. We predicted that Wolbachia would grow much faster during this period than during adult life, considering changes in Wolbachia loads from eggs to adults [Wolbachia genome copies in individuals at the different stages of development using qPCR for the single copy gene wsp and a calibration curve using a plasmid with wsp cloned. Assuming one chromosome per Wolbachia cell [Wolbachia cells. Embryos with 0-2h have between 2,300 and 3,100 Wolbachia genome copies, with no significant difference between Wolbachia variants .We also analysed the growth of o adults . We, thehia cell , these ned above , there aWolbachia growth seems to be restricted to the period between egg and white prepupae (120h), since there is no significant growth from this stage to adults . From eggs to white prepupae there is rapid exponential growth of all variants . The growth rates of these variants are, therefore, very similar during this stage, and much faster than in adults. At the same temperature, we estimated doubling times in adults of wMelCS_b, wMelOctoless, and wMelPop2 (high-copy) to be, approximately, 13.9, 10.5, and 2.3 days, respectively , p < 0.001). All lines, including the Wolbachia-free line have a shorter lifespan at 25°C than at 18°C, and even shorter at 29°C . wMelCS_b did not affect the host lifespan at any temperature .The over-proliferation of lifespan ,22. We, wMelOctoless strongly reduces host lifespan at all tested temperatures  . The effect of wMelOctoless on host lifespan is weaker at 25°C than at 18°C (p = 0.001), and similar at 25°C and 29°C (p = 0.95). These results demonstrate that the new over-proliferative wMelOctoless also has a cost to the host in terms of lifespan and this effect interacts with temperature, being stronger at lower temperature._b) Figs  and S14.wMelPop2, similarly to wMelPop, also shortens host lifespan . This effect is much stronger at 25°C than at 18°C (p < 0.001 for contrasts between both lines and wMelCS_b), and similar at 25°C and 29°C (p > 0.21 for these contrasts). At these two higher temperatures the lines carrying the variants with high copy number of Octomom have the shortest lifespan of all tested lines . wMelPop2 and wMelPop with low copy number of Octomom (2–3 copies) always have a weaker effect on host lifespan shortening than high copy number variants . As observed with the high copy number variants, their effect increases with temperature, being stronger at 25°C than at 18°C, and even stronger at 29°C (p < 0.05 for these comparisons). In fact, wMelPop2 and wMelPop with low copy number are only pathogenic at 25°C and 29°C, not at 18°C. These data confirm the association of Octomom region amplification with host lifespan shortening, and the increase in the severity of this phenotype with an increase in Octomom copy number, and an increase in temperature.pan Figs  and S14.wMelPop2 and wMelPop differ significantly in their pathogenic phenotype (wMelPop2 and wMelPop lines with a tightly controlled Octomom copy number (wMelPop and wMelPop2 with 3 copies of the Octomom region had a shorter lifespan than the line with wMelCS_b (p < 0.001), and no difference between them (p = 0.29). These results show that wMelPop2 and wMelPop have the same phenotype.In some comparisons henotype . This coy number . At 25°CWolbachia variants, and not to EMS-induced mutations in the host nuclear genome, we performed reciprocal crosses between flies carrying wMelCS_b and flies carrying either wMelOctoless or wMelPop2 (with 3 or 8–9 copies of Octomom) and followed the survival of their female progeny at 29°C. The female progeny from reciprocal crosses should be identical in the nuclear genome but differ in the Wolbachia variant, which is maternally transmitted. The life-shortening phenotype segregated maternally, thus demonstrating that the Wolbachia variants carried by the lines are the cause of the phenotypes , indicating, as expected, no contribution of the host genotype in this set of experiments.To further demonstrate that the life shortening phenotypes were due to the new enotypes . The relwMelPop has been associated with its over-proliferation and higher titres since its discovery [Wolbachia doubling time, at all temperatures . These results show that over-proliferative variants shorten the host lifespan and the strength of this phenotype correlates with their proliferation rates.The life shortening phenotype of iscovery . We testWolbachia titres and the strength of anti-viral protection [wMelOctoless and wMelPop2 also provide a stronger protection against viruses, we infected flies with Drosophila C virus (DCV), by pricking, and followed their survival for 40 days at 18°C. All Wolbachia variants tested provided protection against DCV . wMelCS_b was the least protective variant, while wMelOctoless was the one providing the highest protection. In general, the over-proliferative Wolbachia variants confer stronger protection to DCV than wMelCS_b, although this difference is not always significant , p = 0.11).Previous studies established a link between otection –20. To tWolbachia proliferation, but we found no correlation neither with proliferation estimates at 18°C (p = 0.21), the temperature in which the flies were kept after infection, nor at 25°C (p = 0.35), the temperature in which flies developed and were kept until being infected with DCV . Overall, the new over-proliferative variants give more protection to viruses than wMelCS_b, and the strength of this protection is correlated with Wolbachia levels at the time of infection.We also tested the correlation between the antiviral protection and with DCV . HoweverWolbachia over-proliferative variants. We characterized in detail two of these mutants, wMelPop2 and wMelOctoless, and identified the genetic bases of their over-proliferation. wMelPop2 had an amplification of the Octomom region, which has been previously shown to lead to over-proliferation in the wMelPop variant [wMelOctoless, on the other hand, had a deletion of this same Octomom region. These results further confirm and develop the complex role of this genomic region in the control of Wolbachia proliferation. An extensive phenotypic characterization of two of these lines showed both Wolbachia variants to shorten the host lifespan, as well as to increase antiviral protection. Moreover, we show that Wolbachia proliferation rate in D. melanogaster depends on the interaction between Octomom copy number, the host developmental stage, and temperature. Our analysis also suggests that the Wolbachia-induced life shortening and antiviral protection phenotypes are dependent on its rate of proliferation in adults and titres near the time of infection, respectively. These are related, but different, properties of the endosymbiont.We developed a new forward genetic screen and identified new  variant ,17. wMelWolbachia and most endosymbionts remain non-culturable and genetically intractable, hindering their study. Here we aimed at mutagenizing and screening for new Wolbachia variants in the host. We expected that a main difficulty of this approach would be how to identify, via its phenotype, a new mutant present in the Wolbachia population within a host. We estimated here that a newly emerged wMelCS_b-carrying female harbours approximately 540,000 Wolbachia genome copies, which probably corresponds to the same number of Wolbachia cells [Wolbachia population at the individual fly level. Each new mutant, when generated, would be a unique cell within these approximately half a million other Wolbachia cells. Since the Wolbachia phenotypes are normally measured at the individual host levels , the properties of individual or small numbers of mutant Wolbachia could be diluted and unmeasurable.Given their dependence on the intracellular niche, ia cells . Since EWolbachia cells could overtake the population and that the resulting higher titres could be detectable. Indeed, fast proliferative Wolbachia can be selected at the level of a single host [Wolbachia variants, we also relied on the bottleneck imposed in the vertical transmission of Wolbachia. We calculated here that single embryos carry approximately 3,000 Wolbachia genomes, which is consistent with previous estimates [Wolbachia population. We expected this additional endosymbiont titre reduction to enhance genetic drift and potentially enrich or lead to the fixation of rare Wolbachia variants. By screening at the immediate progeny (F1) of EMS-treated females or three generations later (F4) we were able to select new over-proliferative Wolbachia mutants.We hypothesized, however, that over-proliferating gle host . To incrstimates . We alsoWolbachia over-proliferation, we performed de novo genome assembly of the ancestral, wMelCS_b, and the new variants, wMelPop2 and wMelOctoless. We also assembled wMel and wMelPop genomes. The assemblies generated complete full chromosomes of these Wolbachia and allowed us to identify single nucleotide differences and structural differences between these genomes. To validate our genome assembly pipeline we compared our wMel genome to the reference wMel genome. We identified only seven indels and two SNPs, which we confirmed to be present in our line, by Sanger sequencing. These indels and SNPs were also recently identified in a wMel that was transferred to D. simulans [wMelCS_b  and wMelPop. Additionally, our assembly provides an improvement over the previous wMelPop genome [After discarding the possibility that mutations in the host nuclear or mitochondrial genomes were the cause of simulans . Our assp genome .wMelCS_b were structural differences in the Octomom region. wMelPop2 has an amplification of this region. The assembly confirms that the Octomom region is amplified in tandem [Wolbachia genome. Previously we showed that amplification of the Octomom region and the degree of this amplification determined wMelPop over-proliferative phenotype [wMelPop Octomom copy number to one, through selection, resulted in loss of both over-proliferation and cost to the host, making the variant phenotypically identical to wMelCS_b, which also carries a single copy of Octomom [wMelCS_b also leads to an over-proliferative phenotype. Moreover, wMelPop and wMelPop2 variants, carrying the same copy number of Octomom, have identical phenotypes. These findings are unsurprising since wMelCS_b, the ancestor of wMelPop2, and wMelPop share an almost identical genome, differencing on two synonymous SNPs and Octomom amplification. Hence, our results further confirm the role of amplification of Octomom region in the over-proliferation of Wolbachia.The only differences between the new over-proliferative variants and n tandem , and thahenotype ,17. MorewMelOctoless, on the other hand, has a deletion of the entire Octomom region. The deletion leaves behind one of the direct repeats flanking the Octomom region [wMelOctoless2. This Wolbachia variant also has a deletion of Octomom as the only difference with wMelCS_b. These data show that deletion of the Octomom region also leads to an over-proliferative phenotype in Wolbachia. Thus, we identified the second known Wolbachia mutation with a clear link between genotype and phenotype.m region , suggestThe mutations identified in the new variants are deletions and amplifications. We did not detect any new SNPs in these variants, even if EMS is expected to mainly induce single nucleotide mutations . Thus, iBoth the deletion or the amplification of the Octomom region causing an over-proliferative phenotype seems to be a paradox. The resolution of this paradox and the mechanisms leading to these phenotypes will rely on the functional characterization of genes in the Octomom region. These genes may be involved in interaction with the host, transcriptional regulation or DNA repair .wMelPop2 and wMelOctoless have similar but not identical phenotypes, and interact differently with temperature. Furthermore, wMelPop and wMelPop2 have a higher rate of proliferation than wMelOctoless at 25°C and 29°C. Therefore, at these temperatures, the phenotype of Octomom amplification is stronger than the phenotype associated with the Octomom region loss-of-function.One possibility is that the amplification of the Octomom region and over-expression of a particular set of genes in this region lead, mechanistically, to the same result as the absence of the genes. There are many examples of over-expression of a gene leading to a dominant negative phenotype. For instance, both over-expression or loss of a protein forming a gradient, abolish the gradient . Also, oAedes aegypti. The D. melanogaster variant wMelPop was transinfected into Aedes albopictus cells, and then transinfected into A. aegypti. In the process of cell culture adaptation the Octomom region, which was amplified in wMelPop, was deleted [wMelPop-PGYP variant in A. aegypti lacks, therefore, the Octomom region. Nonetheless, this variant still over-proliferates and is highly pathogenic in A. aegypti [wMelPop in D. melanogaster and wMelPop-PGYP in A. aegypti, one might conclude that the Octomom region was not related with these phenotypes [wMelCS_b and the mutant variants show that both amplification and deletion of the Octomom region lead to increased Wolbachia pathogenicity. Thus, deletion of the Octomom region in wMelPop-PGYP may explain why this variant is also pathogenic. However, wMelPop-PGYP also accumulated other mutations when passaged in cell culture, and has many other genetic differences with wMel [wMelPop-PGYP being more pathogenic than wMel in A. aegypti.Although complex, these results help to explain some of the data from an over-proliferative variant trans-infected in  deleted . The wMe aegypti . If one enotypes . Howeverith wMel . These mWolbachia core genome, since many Wolbachia strains lack this region, and seems to be horizontally transferred between Wolbachia strains [wMel strain can lose this region and remain viable in laboratory conditions , natot known . Its oveWolbachia variants in adults. wMelOctoless proliferates faster than wMelCS_b, to a similar extent, at all temperatures. wMelPop and wMelPop2, however, strongly interact with temperature and proliferate much faster at higher temperatures. We also confirmed here that the degree of Octomom amplification in these variants modulates the proliferation rate [We found a complex interaction between temperature and proliferation of the different ion rate , and intwMelPop2 double every 2 days, while wMelCS_b titres double every 14 days. In contrast, during larval development the proliferation rates of wMelCS_b, wMelOctoless, and wMelPop2, are very similar and much faster than in adults. During development, at 25°C, Wolbachia titres double every 12 to 16 hours. These results show that wMelCS_b, which has a relatively low proliferation rate in adult flies, is capable of very fast proliferation during larval development, when the host is rapidly growing. In Brugia malayi, Wolbachia titres also increase rapidly during the first few weeks of the nematode’s development [Wolbachia strategy to recover from the bottleneck imposed during maternal transmission. This observed coordination between wMelCS_b proliferation and D. melanogaster developmental stage may be due to Wolbachia directly responding to host developmental cues, to differences in the metabolic profile of larvae and adults, or to differences in host cell divisions rates. Wolbachia could also control its proliferation in response to its own population density within the host.Throughout the range of tested temperatures, the different variants have very different proliferation rates in adults. At 25°C, where we observed the highest variation, the titres of elopment . Thus, rwMelPop and wMelPop2 proliferate similarly to wMelCS_b during larval stages, they over-proliferate in adults. Thus, this over-proliferative phenotype of variants with amplification of the Octomom region can be interpreted as an inability to properly respond to the conditions of the host adult stage. On the other hand, the deletion of Octomom seems to lead to a similar increase in the proliferation rate during development and adult life, although the difference with wMelCS_b is not significant during development in our analysis.While D. melanogaster, as wMelPop does. Furthermore, we showed this phenotype to result from the interaction of Wolbachia genotype and temperature. wMelOctoless had a similar life shortening phenotype at all temperatures, although stronger at 18°C. wMelPop and wMelPop2 responded strongly to temperature, being much more costly at higher temperatures, as shown before for wMelPop [wMelPop and wMelPop2 are pathogenic also at this temperature. Therefore, these variants can also be pathogenic at 18°C, contrary to previous data [Wolbachia variants and the life shortening phenotype. The faster the variants proliferate the shorter the host lifespan.The new over-proliferative variants shorten the lifespan of  wMelPop ,22,41. Tous data ,41,42. IwMelOctoless conferring the strongest protection. This phenotype correlated poorly with proliferation rates at 25°C or 18°C, the temperature before and after infection with DCV, respectively. However, the strength of the antiviral resistance correlated with the titres of Wolbachia near the day of infection. Thus, the cost of harbouring Wolbachia in terms of lifespan, and the benefit of the antiviral protection, correlate with related but different parameters. In the future it will be important to understand why these different correlations. For instance, Wolbachia titres at the point of viral infection are probably important because the anti-viral protection is observed early in the infection [Wolbachia proliferation rate could impact longevity either by the cumulative cost of the proliferation process itself or by determining the time to reach a lethal threshold of Wolbachia titres. Nonetheless, these results indicate that it may be possible to select for highly protective Wolbachia variants without necessarily having a high cost to the host. These would be Wolbachia variants with high titres but low proliferation in adults. Such variants would be particularly useful in the use of Wolbachia-transinfected mosquito to prevent arboviruses transmission.All the over-proliferative variants also increased antiviral resistance, with nfection . WolbachWolbachia biology. Similar strategies may be used in the future to study other aspects of Wolbachia-host interactions or the biology of other genetically intractable endosymbionts. The new over-proliferative variant wMelPop2 confirms the causal link between amplification of the Octomom region and Wolbachia over-proliferation. Whereas the new loss-of-function mutant wMelOctoless reveals that this region is also required to control Wolbachia proliferation. These results give new insight on the complex role this genomic region plays in Wolbachia biology. Moreover, this collection of variants, similarly to an allelic series, allow a finer dissection of the consequences of Wolbachia over-proliferation to the host.In summary, our results show the feasibility of forward genetic screens to study Flies were reared on fly food, supplemented with live yeast, at 25°C, 70% humidity. Fly food was composed of molasses (37.5g/L), sugar (62.5g/L), cornflour (58.3g/L), yeast extract (16.7g/L), and agar (8.3g/L) in distilled water. The mixture was sterilized by autoclaving and cooled to 45°C. For each litre of food, we added 29.2 mL of a solution with 100g of methylparaben and 0.2g of Carbendazim for 1L absolute ethanol.w1118 isogenic background [All fly stocks used had the Drosdel ckground ,44.et al. [Acectobater OTU 2753 and Lactobacillus OTU 1865 [The bacterial community associated with the fly stocks was homogenized as in Pais et al. , with miOTU 1865 . We confwMelPop and wMelPop2 with a desired Octomom copy number, we proceeded as in Chrostek and Teixeira [Wolbachia-uninfected males of the Drosdel w1118 isogenic background in individual vials, and lay eggs for 3–4 days. Females were then collected in individual tubes for DNA extraction and Octomom copy number determination by qPCR. The progeny of females with specific copy numbers were then followed-up.To select for flies carrying Teixeira , with miwMelCS_b developed in fly food supplemented with tetracycline at the concentrations 1.5625μg/ml, 3.125μg/ml, 6.25μg/ml, 12.5μg/ml, 25μg/ml, and 50μg/ml. Three isofemale lines were established from each dose. In the F1, we randomly selected four virgin females for egg-laying and Wolbachia titre measurement using qPCR. From this moment on, the flies were kept on fly food without tetracycline. We set up the next four generations using the progeny of a female with the median Wolbachia titres.Flies with Wolbachia in vivo by feeding its host with the mutagen EMS. DrosDel w1118 isogenic flies carrying wMelCS_b were raised in standard fly food or fly food supplemented with tetracycline (from 1.5625 to 12.5μg/ml). Virgin females were collected, starved for 6h, and then fed EMS concentrations ranging from 10 to 8,000mM diluted in 1% sucrose. Control flies fed on sucrose solution only. A dye was added to the feeding solution to confirm intake and feeding proceeded for 13h (overnight).We attempted to mutagenize Wolbachia-free Drosdel w1118 isogenic males, egg-laying was allowed for 3–4 days, and parents discarded. From the F1 progeny, we collected virgin females, mated them individually with 2–3 Wolbachia-free Drosdel w1118 isogenic males, and allowed egg laying for 3–4 days. These females were collected when 10 day-old, and Wolbachia titres determined by qPCR. We followed the progeny of F1 females showing 50% or higher increase in Wolbachia titres relative to control flies in the same conditions. We also transferred the progeny of these F1 for three more generations, without selection, and repeated the determination of Wolbachia titres in F4 females. In the same experimental batch we may have tested more than one F1 or F4 progeny from each G0 female. Hence, over-proliferative Wolbachia variants isolated in the same batch of treated females may be a result of a single event in the G0 female.EMS-fed females (G0), and control females, were mated individually with 2–3 DNA extraction for qPCR was performed as described before .The qPCR reactions were performed in the QuantStudio 7 Flex (Applied Biosystems). The reaction mix and PCR program used were described before . The speWolbachia titres we used Drosophila RpL32 gene as calibrator, and Wolbachia wsp as the target gene. To determine the copy number of the Octomom region, Wolbachia wsp gene was used as the calibrator and WD0513 used as the target gene. For determination of copy number of other Octomom region genes, or control genes, wsp was also used as a calibrator.Relative levels of the target genes were determined using the Pfaffl method . To quanWolbachia genome copies the full-length Wolbachia wsp gene was cloned into a pMT/V5 Drosophila expression vector (Invitrogen). The plasmid was amplified in Escherichia coli strain DH5-α, purified using midiprep (QIAGEN) and its concentration determined using Qubit 2.0 (Thermo Fisher Scientific). Molecular weight of the plasmid was calculated assuming a nucleotide average weight of 325 Da to determine the number of plasmid molecules in the calibration curve. Standard curves of 1:10 serial dilutions were run to calibrate the assay each time.For absolute quantification of Primers used in qPCR reactions are given in For each replicate, a total of 50 males or 50 females were collected on the day of eclosion. Flies  were then incubated at 18°C, 25°C or 29°C, and transferred to new fresh vials every four  or five  days. The number of dead flies was recorded daily until all the flies died. Censored observations  were recorded and taken into account during data analysis.Drosophila C virus solution as described in Teixeira et al. [9 TCID50/ml in 50mM Tris-HCl, pH 7.5) and pricking in the thorax flies anaesthetized under CO2. An equal number of males were pricked with a buffer only solution  and served as controls. After pricking, flies were incubated in groups of 10 individuals per vial, and kept at 18°C. Survival was followed as above.We produced and titrated the a et al. . We infeWolbachia growth during development, flies carrying wMelCS_b, wMelOctoless, and wMelPop2 (high-copy), laid eggs for 2 hours in apple juice agar plates supplemented with live yeast. Eggs were transferred to fly food-containing bottles and allowed to develop at 25°C. For Wolbachia titre assessment, we sampled eggs (2 hours), L1 larvae (24 hours later), newly moulted L2 larvae (48 hours later), L3 larvae (72 and 84 hours), white prepupae pupae (120 hours), P8 staged pupae (168 hours), and newly eclosed adult males and females (240 hours). Ten samples per time point were analysed. Samples included ten individuals each for eggs and larvae and one individual each for pupae and adults. To collect newly molted larva, all larvae of the target stage were discarded at the respective time-point and the newly molted larvae were collected within two hours after the established time-point. The white prepupae were collected by staging and the remaining stages were collected according to the set time-point. Except for adults, which were collected within 24 hours post-emergence, all samples were collected within two hours interval.To determine Wolbachia titre measurement. Ten individuals were processed for each time point, and the experiment was performed twice. Each sample consisted of a single fly.For assessment of titres dynamics in adult flies, newly eclosed males, raised at 25°C, were incubated at 18°C, 25°C, and 29°C. Flies were collected every three (29°C), seven (25°C) or ten days (18°C) for Wolbachia genomic sequencing (Illumina and Oxford Nanopore), we enriched the sample for Wolbachia cells before DNA purification. To this end, approximately 500 10 day-old flies were squashed for 5 minutes in 10ml Schneider’s Insect Medium (Thermo Fisher Scientific) using glass beads. Next, we pelleted host debris by centrifugation at 1,000g for 5 min and filtered the supernatant solution thought a 5μm pore. Bacterial cells were pelleted by centrifugation at 13,000rpm for 15 minutes, and DNA was extracted. All centrifugations were carried out at 4°C. DNA was extracted with a phenol-chloroform isolation protocol and resuspended in 10mM Tris-HCl (pH 8).For Sequencing was performed at the Genomics Facility at the Instituto Gulbenkian de Ciência, Portugal. Both Illumina and Oxford Nanopore sequencing was done on genomic DNA extracted from the same biological material. Illumina 300bp paired-end libraries were prepared using the Pico Nextera kit according to the manufacturer’s instructions and sequenced with MiSeq. Data quality was assessed via FastQC v.0.11.5  and readD. melanogaster genome (BioProject: PRJNA13812) using BWA mem v0.7.12-r1039 [D. melanogaster genome were removed from the datasets before proceeding with Wolbachia genome assembly. We used Unicycler v0.4.8-beta [Wolbachia genomes. Briefly, Unicycler uses Illumina reads to produce a repeats-limited image graph using Spades v3.9.0 [wMel genome (AE017196.1) upon blastn v2.8.1+ [dnaA gene .Illumina and Oxford Nanopore reads were first mapped to 12-r1039  and mini12-r1039 , respect4.8-beta  assemblys v3.9.0 , which ws v3.9.0 . Both sm v2.8.1+  search w v2.8.1+  and Pilo v2.8.1+  and rotaWe further refined our genome assemblies by mapping the Illumina reads to the corresponded draft genomes to identify mismatches, which were later corrected via Sanger sequencing . Primers used are in wMelPop, wMelCS_b, wMelPop2, and wMelOctoless using Mauve v2.4.0 [Wolbachia variants or still genome assembly artefacts. All detected differences were analysed by Sanger sequencing .Next, we compared the draft 2 genome assemblies by aligning e v2.4.0 . The difWolbachia variants using custom Python and R scripts. The only difference we detected between these genomes was higher coverage or deletion of Octomom region.We further tried to identify mutations in the over-proliferative variants following a previously published pipeline . It consWolbachia variant, we mapped Illumina reads to the D. melanogaster Release 6 genome sequence  and proceed as previously. Mutations following the criteria previously described were also compared by using custom scripts.To compare the set of mutations in the mitochondria of flies infected with different All the statistical comparisons were performed in R v4.0.0 .Wolbachia titres across multiple groups, we used linear models (LM) or linear mixed models (LMM). The effect of EMS on Wolbachia titre was tested using non-linear regression. We estimated the doubling time of Wolbachia variants using the equation log (2)/β, with β being the coefficients of an exponential model.To compare The lifespan datasets and survival curves after challenge with DCV were analysed with mixed effect Cox models .The significance of correlations were tested using Pearson’s correlation coefficient.If multiple comparisons were necessary, the p-values were adjusted as proposed by Holm . When muhttps://doi.org/10.6084/m9.figshare.14079920.v1 [All statistical analysis and supporting data is deposited in 79920.v1 .S1 FigWolbachia titres of the progeny of tetracycline-treated flies. wMelCS_b-carrying females laid eggs in food containing varying doses of tetracycline. The progeny of three females were used to set up the experiment. At the first generation, four females were randomly selected for egg-laying in antibiotic-free fly food and Wolbachia titre was measured using qPCR. Titres of untreated females were used to normalize the qPCR results. The progeny of a female with the median titre was used to set up the next generation. Wolbachia titre in the F1 was significantly determined by the concentration of the antibiotic , but recovered to normal within four fly generations .Relative (TIFF)Click here for additional data file.S2 Figp < 0.001 for both numbers of eggs and adults per female). (C and D) Wolbachia titres in the F1 progeny of females treated with varying EMS doses. Wolbachia titre was quantified on individual females (n = 5–13 per dose), after laying eggs for three days. Wolbachia titres were normalized against the titres of untreated females. Dashed red lines represent the mean value predicted using non-linear models. The effect of EMS on Wolbachia titres in the next generation was highly significant (p < 0.001 for both panels).The total number of eggs (A) and adults (B) from females treated with varying doses of EMS. The reproductive output of 10 females was determined in the first ten days after EMS treatment by daily transferring females to new vials for egg laying. Females fed on a sucrose solution served as controls. Each dot represents the total number of eggs (A) or adults (B) laid by individual females during ten days. The effect of EMS on the reproductive output of females was estimated using a non-linear model and was highly significant ((TIFF)Click here for additional data file.S3 FigWolbachia titres in a control (wMelCS_b) and EMS-treated D. melanogaster lines. Flies to set up the next generation was selected as described for wMelOctoless2), 3B, and 3C were also isolated in a same batch.(A-D) Relative (TIFF)Click here for additional data file.S4 FigwMelPop2, wMelOctoless, and wMelOctoless2 were replaced through the use of balancer chromosomes. Wolbachia infection  was kept in the stock by crossing females with Wolbachia with indicated males. The mitochondria are only shown in females because of its strictly maternal transmission. All males were free of Wolbachia infection. Dashed lines indicate the genotype selected from the previous cross. Virgin female in the first cross were considered mutant in all chromosomes (*), for illustrative purposes. Question marks (?) represent recombined chromosomes.The first, second and third chromosomes of flies carrying (TIFF)Click here for additional data file.S5 FigWolbachia titres in D. malanogaster males carrying wMelOctoless and wMelOctoless2 at 0 and 7 days post adult eclosion, at 25°C. This experiment was set-up as described in Wolbachia titre was determined using qPCR and normalized to that of 0–1 days-old wMelCS_b-infected males. Each dot represents the relative titre of a single male.Relative (TIFF)Click here for additional data file.S6 FigwMel loci WD0507–WD0514) was confirmed using qPCR in wMelPop2 and wMelOctoless, respectively. The copy number of three genes outside the Octomom region  were also determined. Five females carrying wMelCS_b, wMelPop2, and wMelOctoless were used in the analysis. The copy number of wMelPop2 and wMelOctoless genes is relative to that of wMelCS_b.The amplification and deletion of individual Octomom genes ((TIFF)Click here for additional data file.S7 FigWD0513 in Wolbachia-carrying stocks throughout 30 fly generations. Each generation, 5–20 females were randomly collected for egg-laying for 3–4 days and used to determine the relative copy number of WD0513, as a proxy for the Octomom copy number. The progeny of a single female was used to set up the next generation. qPCR results were normalized to that of wMelCS_b, which has a single copy of Octomom per genome.The relative copy number of genomic (TIFF)Click here for additional data file.S8 FigwMelPop2 and wMelPop Wolbachia variants. We mapped wMelPop2 and wMelPop long reads (BioProject: PRJNA587443) to the the Octomom region in their genomes  using minimap2 v2.17-r941 [Oxford Nanopore MinION reads supporting the amplification of the Octomom region in tandem in .17-r941  and plot(TIF)Click here for additional data file.S9 FigwMelCS_b (GenBank: CP046924.1) genome, and the number of reads mapping to each position were normalized by dividing to the median coverage across the genome. Coverage information for wMelCS_b, wMelPop2 and wMelOctoless is also given in wMelOctoless2), as no other difference was found when compared to wMelCS_b.Relative coverage in the genomic region containing the Octomom region. As in (TIFF)Click here for additional data file.S10 FigWolbachia titres in adults at 18°C (A), 25°C (B) and 29°C (C) with different Wolbachia variants. Replicate of experiment shown in Wolbachia titres were determined and analysed as described for Time-course of relative (TIFF)Click here for additional data file.S11 FigWolbachia titres on the day of adults eclosion. Males developed at 25°C were collected within 24 hours after eclosion for Wolbachia titre measurement using qPCR. Data used in this figure are also shown in p-value correction.Relative (TIFF)Click here for additional data file.S12 FigWD0513 copy number of wMelPop2 and wMelPop in two experimental replicates. Using WD0513 as a proxy, the Octomom copy number of wMelPop2 and wMelPop was tightly controlled prior to phenotypic comparison. (B) Wolbachia relative titres at 25°C. The progeny of wMelPop2- and wMelPop-infected females carrying three copies of Octomom was used to set up the experiments. Males that developed at 25°C were collected upon eclosion, aged to specific time-points and used to determine Wolbachia titres using qPCR. Wolbachia titres were normalized to that of wMelCS_b-carrying flies collected on the day of eclosion. Proliferation rates of wMelPop2 and wMelPop were not different (p = 0.32). (C) Lifespan of males (solid lines) and females (dashed lines) flies at 25°C. Males were transferred to new vials every five days, while females every four days. (D) Coefficients of a Cox mixed model, representing the effect of wMelPop2 and wMelPop on the lifespan relative to wMelCS_b-carrying flies. wMelPop2 and wMelPop was equally pathogenic (p = 0.29).(A) (TIF)Click here for additional data file.S13 FigWD0513 throughout D. melanogaster development (A) and during adult life (B). WD0513 relative copy numbers were determined in samples shown in WD0513 copies were normalized to that of 0–1 old wMelCS_b-infected males. (A) Vertical dashed lines separate developmental stages . The x-axis is not in a continuous scale. (B) The two replicates are represented by different symbols.Relative copies of (TIFF)Click here for additional data file.S14 FigD. melanogaster males at 18°C (A), 25°C (B), and 29°C (C). Survivorship was determined as in D. melanogaster females at 25°C. Survival was determined as in Wolbachia-free control. Both replicate experiments were pooled for statistical comparisons. Bars represent the standard error of the coefficient, and letters the statistically significant groups.Lifespan of (TIFF)Click here for additional data file.S15 FigD. melanogaster females at 29°C. Virgin wMelCS_b-carrying females were crossed with males carrying wMelOctoless or wMelPop2 (with 3 or 8–9 Octomom copies) and vice-versa. The resulting progeny developed at 25°C and was placed at 29°C after adult eclosion. The survival of 50 female progeny, which have the same genetic background but differ in Wolbachia infection, was determined per condition, per replicate. Females were maintained in groups of ten and transferred to new vial every four days. The experiment was performed twice. (C) Coefficients of a Cox mixed model representing the effect of the parental crosses on the survivorship of females. Significance was accessed after p-value correction for multiple comparisons, and significant groups are represented by letters.(A-B) Survival of (TIFF)Click here for additional data file.S16 FigWolbachia titre at the day of eclosion and the strength of life-shortening phenotype determined at 18°C (A), 25°C (B), and 29°C (C). The y-axis represents the strength of Wolbachia life-shortening phenotype , or 25°C (E) (shown in (A-C) Correlation between shown in . (D and shown in . The Pea(TIF)Click here for additional data file.S17 FigWolbachia variants after a challenge with DCV (A) or a buffer solution (B and C). Fifty 3–5 days-old Drosophila males, per line, were pricked with DCV (109 TCID50/ml) or buffer and survival curves were determined at 18°C for 40 days. A is a replicate of (A) Survival of males carrying different (TIFF)Click here for additional data file.S1 TablewMelCS_b-infected G0 females, raised in control or antibiotic-treated food (12.5 μg/ml), were fed different doses of ethyl-methanesulfonate (EMS) and allowed to lay eggs in individual vials. F1 females were collected as virgins, mated to non-mutagenized males and also allowed to lay eggs individually. F1 females were used for Wolbachia titre measurement when were 10-days old. Number of F1 females tested per experimental condition is shown.(XLS)Click here for additional data file.S2 TableWolbachia or mitochondria of D. melanogaster Release 6 genome sequence . Sequencing data of each Wolbachia variants are mapped to own genome assembly (BioProject ID: PRJNA587443), except for Wolbachia in Line 2B and wMelOctoless2 which were mapped to wMelCS_b genome (Accession: CP046924.1). ND–not determined.Coverage statistics (mean and range) of Illumina reads mapped to either (XLS)Click here for additional data file.S3 TableWolbachia variants were mapped to the mitochondria of D. melanogaster Release 6 genome sequence . A summary of the mapping is given in wMelCS_b, wMelOctoless and wMelPop2 was identical. We found an SNP unique to flies infected with wMelCS-like variants  but absent in flies infected with wMelPop. We confirmed this SNP using Sanger sequencing.Illumina reads on flies infected with different (XLS)Click here for additional data file.S4 TableWolbachia genomes were assembled using the Unicycler v0.4.8-beta pipeline and annotated using NCBI Prokaryotic Genome Annotation Pipeline v4.10. wMel reference genome (Accession: AE017196.1) is included for comparison purposes.(XLS)Click here for additional data file.S5 TablewMel Wolbachia variant (Accession: CP046925.1) was aligned to wMel reference genome (Accession: AE017196.1) using Mauve v2.4.0. All the differences were confirmed via Sanger sequencing.The genome of a newly assembled Cluster III (XLS)Click here for additional data file.S6 TablewMelCS_b (Accession: CP046924.1) was aligned to wMel reference genome (Accession: AE017196.1) using Mauve v2.4.0.The genome of (XLS)Click here for additional data file.S7 TablewMelPop2 (Accession: CP046922.1) and wMelPop (Accession: CP046921.1) genomes. Long reads were mapped to Octomom region using minimap2 v2.17-r941 and the number of Octomom copies determined using blastn v2.8.1+.Long reads  reads supporting the amplification of the Octomom region in tandem in (XLS)Click here for additional data file.S8 TablePrimers used in this study have been previously described ,17.(XLS)Click here for additional data file.S9 TableWolbachia draft genomes.Primers used to amplify and sequence, using Sanger technology, genomic regions containing predicted differences between (XLS)Click here for additional data file.S1 TextwMelCS_b, wMelPop2 and wMelOctoless were aligned using Mauve v2.4.0. The three-fold amplification of Octomom in wMelPop2 and its deletion in wMelOctoless were the only difference identified when compared with wMelCS_b.The genomes of (TXT)Click here for additional data file. This paper was transferred from another journal. As a result, its full editorial history  may not be present.10 May 2021AttachmentResponse to reviewers.docxSubmitted filename: Click here for additional data file. 18 May 2021Dear Dr Teixeira,We are pleased to inform you that your manuscript entitled "Forward genetics in Wolbachia: Regulation of Wolbachia proliferation by the amplification and deletion of an addictive genomic island" has been editorially accepted for publication in PLOS Genetics. Congratulations!Before your submission can be formally accepted and sent to production you will need to complete our formatting changes, which you will receive in a follow up email. Please be aware that it may take several days for you to receive this email; during this time no action is required by you. 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MT3, which is involved in growth, nervous, and immune processes, is identified. We demonstrate the genetic differences between direct genetic effects and social genetic effects and provide an anchor for investigating the genetic architecture underlying direct genetic effects and social genetic effects on socially affected traits in pigs.Socially affected traits in pigs are controlled by direct genetic effects and social genetic effects, which can make elucidation of their genetic architecture challenging. We evaluated the genetic basis of direct genetic effects and social genetic effects by combining single-locus and haplotype-based GWAS on imputed whole-genome sequences. Nineteen SNPs and 25 haplotype loci are identified for direct genetic effects on four traits: average daily feed intake, average daily gain, days to 100 kg and time in feeder per day. Nineteen SNPs and 11 haplotype loci are identified for social genetic effects on average daily feed intake, average daily gain, days to 100 kg and feeding speed. Two significant SNPs from single-locus GWAS  are shared by a significant haplotype locus with haplotype alleles ‘GGG’ for both direct genetic effects and social genetic effects in average daily feed intake. A candidate gene,  Pingxian Wu and Kai Wang et al. perform single-locus and haplotype-based GWAS in Yorkshire pigs to evaluate genetic factors involved in socially affected traits, like feed intake and weight gain. These results indicate several genetic factors that may ultimately be targeted to improve livestock breeding. In current pig production systems, pigs are penned together into contemporary groups, social interactions, and observed phenotypes genetically contribute to socially affected traits of individuals and their group mates2. Socially affected traits are influenced both by the genes of the individual itself  and by the genotype of other individuals in the same group 5. Previous research has proven that many phenotypes are affected by both DGE and SGE and the contribution of SGE to total genetic variance is large in pigs, such as growth rate, body weight (BW)7, feed intake, backfat thickness (BFT), muscle depth2, behavior9, and average daily gain (ADG)11. The existence of SGE affect the estimation of DGE and therefore result in unfavorable consequence on genetic improvement of complex traits. Until recently, the genetic architecture of socially affected traits that involve both DGE and SGE is still poorly understood in pigs.Social interactions inevitably occur among groups of individuals and these interactions influence the genetic variation of a trait in livestock2. Based on the social genetic model, the classical (direct) genetic model is expanded with SGE12. This model simultaneously contains both DGE and SGE that enables researchers to simultaneously estimate DGE and SGE values.With the availability of genomic information, GWAS have increased the understanding of the contributions of genetic variants toward various complex traits. However, previous studies have mainly focused on DGE and have not considered the contributions of SGE. For many phenotypes, DGE and SGE can be directly quantified using a social genetic model13. In pigs, five SNPs on chromosome 6 associated with social ADG were detected with an Illumina panel14. Additionally, in our previous study, a total of 27 SNPs associated with six growth traits were identified using whole-genome sequences (WGS) of 40 Yorkshire pigs 15. However, because of the limited sample size, the study was not efficient in detecting credible associations with DGE and SGE.Detecting the genetic architecture of DGE and SGE may provide deeper insight into a better understanding of complex traits. To date, only a few studies have identified some SNPs associated with SGE. Using the Illumina 60 K SNP BeadChip, an important SNP was identified to be associated with DGE and SGE in chickens16. Therefore, to better investigate the genetic architecture of socially affected traits in pigs, the present study used both GWAS approaches to estimate the DGE and SGE on each trait by employing a social genetic model, WGS of 60 pigs, and genotyping of 1204 Yorkshire pigs with Illumina 50 K SNP chips. Therefore, the main objectives of this study were (i) to construct haplotype loci based on imputed WGS data and identify associations between haplotype-DGE and haplotype-SGE by GWAS; (ii) to perform single-locus analysis to explore SNPs associated with socially affected traits by considering both DGE and SGE in Yorkshire pigs; (iii) to compare the results of GWAS based on haplotypes and SNPs for DGE and SGE; and (iv) to combine single-locus and haplotype-based GWAS to reveal important SNPs and genes for DGE and SGE in pigs.Assessing the impact of SGE on socially affected traits is challenging. Haplotype-based GWAS can capture those genetic variants that are not detected by single-locus GWASSummary statistics for all phenotypic data from 1204 Yorkshire pigs were shown in Table A total of 60 pigs were sequenced and the statistic results were list in Supplementary Data This study conducted genotype imputation from a 50 K SNP chip to WGS data in Yorkshire pigs using a two-breed reference population (20 Landrace and 40 Yorkshire pigs). In total, 36,969 and 14,539,997 SNPs were identified in the target and reference populations, respectively. Beagle 5.1 software was used to impute the WGS reference panel across the 1204 genotyped pigs. After genotype imputation, a total of 14,539,997 SNPs with an average accuracy of 0.63 were available for this study. For each chromosome, the average imputation accuracy was in the range of 0.59–0.67  were calculated and are shown in Fig. 17. The λ calculated for the DGE on ADFI was 1.01; implying no population stratification , days to 100 kg (D100), feed conversion ratio (FCR), residual feed intake (RFI), time in feeder per day (TPD), and feeding speed (FS) traits  for both DGE and SGE on ADFI. A candidate gene, 18. Using the social genetic model12, we estimated the DGE and SGE of each socially affected trait in Yorkshire pigs. Then the single-locus and haplotype-based GWAS were performed to investigate associations for DGE and SGE using imputed data.The socially affected traits are influenced by multiple genes. This study is designed to investigate DGE and SGE for eight socially affected traits using imputed WGS, as there is strong evidence that these traits are socially affected in pigs19. The use of multi-breed reference populations is an effective way to improve the accuracy of imputation20. However, a large genetic distance between the reference and target populations can result in extremely low accuracies (less than 0.49)21. Landrace and Yorkshire pigs are bred according to the same breeding goals and are therefore likely genetically similar22. Additionally, because of the small effective population size for pigs23, the imputation parameter of effective population size was set at 100 in the Beagle 5.1 software. After imputation, the average accuracy at the whole-genome level was 0.63, and 3,072,572 SNPs had a Beagle R2 higher than 0.80 in the imputed WGS dataset. The imputation accuracy observed in the current study was higher than that reported in other studies21, for example, a study using a ten-breed reference population of 168 pigs and using imputation from low- or high-density SNP data to WGS resulted in relatively low accuracy (0.39–0.49)21. Our results were more similar to the accuracy obtained from a multi-breed reference population of cattle (>0.70)20. Thus, the present study indicates that using mixed reference populations with similar genetic backgrounds can result in reasonable imputation accuracy in pigs. The imputation accuracy increased with reference population size24. In this study, a total of 40 sequenced pigs was used. Although the reference population size is smaller than that used in previous studies (>100) for pigs25, this study also obtained a high imputation accuracy, and therefore, the imputed data can provide important information regarding socially affected traits in pigs.Different imputation strategies can result in different levels of accuracy26. Rare variants with a low MAF result in poor imputation accuracy and therefore decrease the average imputation accuracy. In our study, the accuracy decreased sharply when the MAF was lower than 0.10. Filtering out the SNPs with MAF < 0.10 from the imputed data increased the average imputation accuracy from 0.63 to 0.71. In our study, the imputation accuracy increased with the MAF, which is in agreement with previous studies in livestock28. Rare variants are expected to have larger effects on complex traits than common variants29. It is also harder to construct the haplotype background using rare SNPs and they decrease the set of template haplotypes for genotype imputation because they are observed only a few times in reference genotype datasets26. Thus, genotype imputation of rare SNPs does not provide high accuracy levels. It is important to investigate imputation methods for rare variants in further studies.Imputation accuracy is heavily affected by the MAF13, but this method has only identified a small fraction of genetic variants in pigs. Haplotype-based GWAS is a complementary method that intensifies the benefits from linkage disequilibrium (LD) and enables the evaluation of the genetic determinants of complex traits. The use of haplotype information in GWAS would likely be beneficial for detecting further genetic variants30. However, haplotype-based GWAS using imputed WGS has not yet been reported in pigs. The rare variants may contribute large effects to complex traits29. Our analysis were done on imputed sequence data, which may contain imputation errors31. To alleviate this issue, further quality control was also conducted on the imputed sequence genotypes, rare variants with a MAF lower than 0.01 were moved. After quality control, the average MAF is 0.30 for chip-based data, 0.27 for imputed data, and 0.09 for haplotype alleles. Our results show that haplotype-based GWAS can be effective and can provide more genetic information than single-locus GWAS. These results are in agreement with previous studies; for example, haplotype-based GWAS in plants32 and cattle16 captured genetic variants that were not identified by single-locus analysis. Importantly, by combining single-locus and haplotype-based GWAS, we confirmed the presence of two important SNPs  for DGE and SGE in ADFI. Therefore, our results highlight the advantages of haplotype-based GWAS for detecting genetic variants that influence complex traits in pigs. The power of GWAS is limited by sample size and SNP density. Using the imputed WGS instead of the 50 K SNP chip is powerful to investigate socially affected traits in pigs. Although only 1204 imputed WGS were used in this study, our results also provided important genetic variation for socially affected traits. Further studies are recommended to validate these results using a larger sample size.In the processes of natural selection and the artificial selection of pigs, complex traits have developed high levels of genetic variation. The single-locus analysis focuses on identifying SNPs and mining functional genes for complex traits33. However, these studies have mainly focused on investigations of DGE, despite the majority of complex traits in pigs being affected by social interactions among individuals2. Pigs are highly social animals, so ignoring SGE could incorrectly estimate genetic variance and restrict genetic improvement.Socially affected traits are known to be affected by SGE, but the mechanisms of SGE are not fully known. Many studies have been conducted to understand the genetic architecture of complex traits and they have identified many important SNPs and genes associated with these traits10. However, few studies have investigated the genetic architecture of DGE and SGE in pigs34. On the basis of our GWAS results, we found that the significant loci and candidate genes of DGE are different from SGE for each trait in Yorkshire pigs. These results are in agreement with previous studies, for example, a distinct difference was found between DGE and SGE for socially affected traits in laying hens13, and a study based on single-step GWAS found only one QTL (SSC6: 19.9–20.9 Mb) for DGE and SGE on ADG in pigs34. The population composition may affect the estimation of DGE and SGE. An experimental design using groups comprising two families is optimal for estimating SGE35. Our group’s composed of numerous families because all pigs in our study were from a commercial pig performance testing station. The group design in this study may have affected the estimation of DGE and SGE; however, it is difficult to conduct an experiment containing only two families from a commercial breeding program. Moreover, in our study, all pigs were derived from the same herd and there were 20 pigs in each group, which made it easier to estimate DGE and SGE5.Recently, numerous studies have shown that using social genetic models during genetic evaluation can enhance the genetic improvement of socially affected traits in pigsOur results provide further evidence for the genetic differences in DGE and SGE with regard to socially affected traits. Economically important traits are selected by artificial selection when based on the classical model that only considers DGE. SGE is, therefore, less frequently selected when compared with DGE. The complex traits in pigs are highly polygenic, and more research is required to understand the genetic architecture of the SGE on the complex traits of pigs.12. Thus, the investigation of the genetic architecture of SGE has important implications for pig breeding programs.To assess whether the identified SNPs associated with socially affected traits in our study replicate previously identified QTL, we compared our results with the PigQTL database based on the genome position of each SNP and QTL. A total of 78 important QTL were found to overlap with previously identified QTL for DGE of complex traits in pigs  between group pigs would influence their health. Interestingly, the significant SNPs within the region SSC6: 45.95–46.95 Mb were located within 20 QTL known to be associated with health traits50 in pigs .In the region of 45.95–46.95 Mb on SSC6, numerous zinc-finger protein family genes were found to be associated with both DGE and SGE. The zinc-finger protein is one of the most abundant classes of transcription factors and regulates cell growth and differentiation. According to our gene ontology (GO) analysis, these genes regulate transcription, nucleic acid binding, and metal ion binding. Furthermore, this chromosome region overlapped with four reported QTL affecting ADGMT3 gene was found in both single-locus and haplotype-based GWAS for socially affected traits. This gene encodes a growth inhibitory factor that regulates many biological processes, particularly within the nervous and immune systems, and thereby influences health. MT3 plays an important role in zinc homeostasis and cell death51, and inhibits cell growth under zinc-deficient conditions52. Interestingly, our study also identified numerous zinc-finger protein family genes to be associated with DGE and SGE in SSC6: 45.95–46.95 Mb.In the region of SSC6: 18.14–19.14 Mb, 34. The QTL (SSC6: 18.14–19.14 Mb) in the current study was close to the reported QTL (SSC6: 19.9–20.9 Mb) for both DGE and SGE on ADG in pigs34. Furthermore, there were eight reported QTL associated with growth traits in the region of SSC6: 18.14–19.14 Mb. Among them, five QTL were related to ADG53 and feeding intake54. The significant SNPs associated with DGE and SGE are located in nine reported QTL for health traits46. And, it was reported that three QTL located on SSC6: 18.14–19.14 Mb in pigs were associated with social interaction traits, and health traits55.The previous studies identified several QTL on SSC6 for DGE and SGE in pigsIn summary, we report the study employing combined single-locus and haplotype-based GWAS to identify the genetic architecture of socially affected traits that are influenced by both DGE and SGE in pigs. Our study shows the feasibility of mapping genomic variants that underlie SGE and provides genomic information for socially affected traits in pigs. These results provide evidence that the genomic architecture of SGE and DGE is different for socially affected traits. Hence, we recommend the use of both DGE and SGE to evaluate genetic architecture for socially affected traits in pigs.All experimental procedures were performed in accordance with the Institutional Review Board (IRB14044) and the Institutional Animal Care and Use Committee of the Sichuan Agricultural University under permit number DKY-B20140302.During the period of 2017–2019, phenotypic data were collected for Yorkshire pigs from the national nucleus pig breeding farm of New Hope Group, Co., Ltd.  using the Osborne FIRE Pig Performance Testing System . As target population, a total of 1204 Yorkshire pigs were placed in a temperature-controlled room at 25 ± 2 °C and relative humidity of 65–80% during the period of performance test from 30 to 110 kg. As reference population, a total of 60 pigs (20 Landrace and 40 Yorkshire pigs) were randomly selected from core populations. These pigs were group-housed in cement-floor pens (20 pigs in each pen) and the nutrient requirements were met as recommended by the National Research Council (NRC 2012).57. FCR, D100, B100, and RFI were calculated as follows58:59. The true days and B100 were firstly obtained based on two data that were the closest to 100 kg using linear interpolation. Then the nonlinear models of D100 and B100 were constructed based on linear interpolation as models (2) and (3). Finally, the A and B were calculated based on models (2) and (3) using the NLIN procedure in SAS software, respectively. BFT is the tested backfat thickness at the end of a performance test. AMW is an average metabolic BW.A total of 1112 pigs’ phenotypic data were collected, including ADG (kg/d), D100, B100, ADFI (kg/d), RFI, FCR, TPD (min/d), and FS (g/min). In this study, each pig was labeled with a unique electric identification tag on ear that was detected by the Osborne FIRE Pig Performance Testing System. The feed time, feed consumption, and BW were recorded at each visit to the feeder for each pig. At the end of the performance test, BFT between the third and fourth last ribs of each pig was calculated by PIGLOG 105B ultrasound machine . ADG was calculated as linear regressions of BW from 30 to 110 kg on the performance test days. ADFI was calculated based on the total amount of recorded total feed intake (TFI) divided by the number of corresponding feed days at the feeder. TPD was calculated based on the total amount of recorded total time divided by the number of corresponding feed days (min/d), and FS = ADFI/TPD (g/min)12, as follows:60. The estimated accuracies of DGE and SGE were calculated based on the formula 61. Then, the deregressed EBVs were used to implement for association analysis.The DGE and SGE were estimated for eight socially affected traits using a social genetic effect modelThe ear tissue samples were collected and stored in 75% alcohol. Genomic DNA from 1264 ear tissues was extracted using the Tissues Genomic DNA  kit according to the manufacturer’s instructions, and then the quality and quantity were measured using a Nanodrop-2000 spectrophotometer. The genomic DNA with the ratio of light absorption (A260/280) between 1.8 and 2.0, concentration ≥50 ng/µL, and total volume ≤50 µL were eligible.62. The SNPs with call rate < 0.90, MAF < 0.05, and Hardy–Weinberg equilibrium test (HWE) <10−6, were excluded from the dataset. After quality control, a total of 1854 SNPs were removed. Finally, a total of 36,969 SNPs were used as target genotype data.A total of 1204 Yorkshire pigs, 442 boars and 762 gilts, were genotyped by the Illumina Porcine 50K SNP Chip , which contained 50,697 SNPs. Firstly, the SNPs with no position information and located on sex chromosomes were removed from the genotype data, which contains 11,874 SNPs. Then, quality control of the genotype data was performed using PLINK softwareN reads (where N > 10% of one read) to produce clean reads by FastQC (http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc/). Then the clean reads were mapped to the pig reference genome (Sscrofa11.1) using BWA (version 0.7.15) software with the parameters mem -t 10 -k 32 -M63. The SAM files produced from BWA were converted to BAM files using SAMtools (version 1.19)64. The potential PCR duplicates were removed by MarkerDuplicates utility in Picard release 1.119 (https://sourceforge.net/projects/picard/files/picardtools/1.119/). After that, BAM files were used to call SNPs using GATK (version 3.5) software65 with multi-sample approaches. The raw SNPs generated from GATK were filtered with QualByDepth (QD) < 2.0, FisherStrand (FS) < 60.0, RMSMappingQuality (MQ) < 40.0, MappingQualityRankSumTest < –12.5, and ReadPosRankSumTest < –8.0. After the initial filtering, a total of 21,104,245 SNPs remained. For further analyses, the SNPs with MAF >0.05, missing rate <0.1, HWE <10−6, read depth (dp) >6, and the SNPs located on autosomes were considered as reference genotype data.The WGS reference data were obtained for 60 pigs (20 Landrace and 40 Yorkshire pigs), with 150 bp paired-end reads on the Illumina HiSeq PE150 platform. The sequencing was performed by BGI Co., Ltd. . After sequencing, the quality of raw reads was checked with a Phred score of 20 as the minimum to filter the adapter polluted reads and multiple 66 with default parameter settings, except for setting the effective population size to 10022. The imputation accuracy of each SNP was assessed using the Beagle R2, which is the estimated squared correlation between the estimated allele dosage and the true allele dosage67. A two-breed reference population (20 Landrace and 40 Yorkshire pigs) with a small genetic distance22 was used to perform genotype imputation from 50 K SNPs to WGS. After imputation, to maintain a balance between the average accuracy and the number of SNPs, SNPs with a Beagle R2 < 0.8 were excluded. Furthermore, SNPs with MAF less than 0.01 and HWE less than 10−6 were removed from imputed data. Finally, a total of 3,072,572 SNPs were retained for further analyses.Genotype imputation between target and reference genotype data were performed by Beagle (version 5.1)68 using PLINK v1.90 software62. The parameters were set to “-blocks no-pheno-req -blocks-max-kb 1000 -blocks-strong-lowci 0.8 -geno 0.1”. A haplotype block containing two or more SNPs with high LD was defined, and loci with a confidence interval of r2 higher than 0.8 were considered into one block. Then, the haplotype calling and identification of haplotype alleles were performed by GHap package69. Furthermore, haplotype loci were transformed into multi-allelic markers, and the haplotype genotype matrix was used to perform GWAS. Using the imputed data with 3,072,572 SNPs, a total of 33,708 haplotype loci were constructed and each haplotype loci contained 34.8 alleles. Finally, 274,741 haplotype alleles with MAF >0.01 were retained.Haplotype loci were identified from the imputed WGS data in 1204 pigs. Haplotype loci were detected for each chromosome as proposed by Gabriel et al.65. Before association analysis, the centered genotypes were used to estimate the n × n genomic relationship matrix between the individuals. The genomic relatedness matrix was calculated as follows:n × p matrix of genotypes; n × 1 vector of 1’s.GWAS were performed independently for eight socially affected traits by considering both DGE and SGE using GEMMA softwareG is a genomic relationship matrix, The deregressed EBVs were used to perform single-locus GWAS (including chip-based GWAS and imputed-GWAS) and haplotype-based GWAS, the following unified mixed linear model was used:70. For chip-based GWAS, the genome-wide significant and suggestive levels were set as P = 0.05/N1 = 1.35 × 10−6 and P = 1/N1 = 2.70 × 10−5, respectively, where N1 is the number of analyzed SNPs. For imputed-GWAS, the genome-wide significant and suggestive levels were set as P = 0.05/N2 = 1.63 × 10−8 and P = 1/N2 = 3.25 × 10−7, respectively, where N2 is the number of analyzed SNPs. For haplotype-based GWAS, the genome-wide significant and suggestive levels were calculated as P = 0.05/N3 = 1.82 × 10−7 and P = 1/N3 = 3.64 × 10−6, respectively, where N3 is the number of studied haplotype alleles.The genome-wide significant threshold value was determined using the Bonferroni correction method71. Genomic inflation factor (λ) was calculated to judge the extent of false-positive signals with estlambda function in GenABEL package (72.The Manhattan plots were drawn using qqman packagehttps://asia.ensembl.org/Sus_scrofa/Info/Index). Then, the biological functions of these candidate genes were investigated on PubMed (https://www.ncbi.nlm.nih.gov/pubmed) and the reported literature. For functional annotation, GO analysis was performed on DAVID Bioinformatics Resources (https://david.ncifcrf.gov). The Fisher’s test was used to assess the significance of the determined enriched terms74. Enriched GO terms (P < 0.05) were selected to investigate the genes involved in biological processes75.The region within a 1 Mb region centering each significant SNP was defined as the QTL region. The candidate functional genes were searched within the identified QTL regions on the pig genome assembly 11.1 (Further information on research design is available in the Supplementary Data 1-2COMMSBIO-21-0181B-nr-editorial-policy-checklistSupplementary InformationDescription of Additional Supplementary FilesReporting Summary