The Anopheles gambiae 2La chromosomal inversion influences chromatin organization and 3D landscape of genes related to malaria transmission

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Taquet, Cameron E. Anderson, Kenneth D. Vernick, Michelle M. Riehle This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9213027/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background Malaria parasite transmission by Anopheles mosquitoes remains a worldwide health burden, and understanding factors underlying natural vector susceptibility would inform rational design of vector control. The 2La chromosomal inversion segregates in the major vectors of human malaria, Anopheles coluzzii and gambiae , and is associated with natural variation for malaria susceptibility, though underlying mechanisms are unknown. Here, we characterize alterations of chromatin conformation and gene expression induced by the two 2La inversion allelic forms, the ancestral 2La and the derived 2L + a forms. We employ several novel applications of proximity ligation sequencing to refine the mosquito regulatory genome to a new level of resolution. Results We analyzed the 2La inversion breakpoints in A. coluzzii hemocyte-like cell lines for the allelic 2La inversion karyotypes. Utilizing a novel combination of Micro-C and bulk RNA-sequencing, our results detected transcriptional enhancers and genes that are rewired by the physical rearrangement caused by the inversion. Through development and application of novel distance-normalized interaction frequency analysis on Micro-C data, we identify a novel candidate enhancer for LRIM1, a major parasite antagonist immune gene within the 2La inversion. Our genome-wide analysis examines the distribution of all chromatin interactions across the genome and identifies chromatin interaction hubs that are positively associated with enhancers. Conclusions This multifaceted approach yields high resolution characterization of gene cis -regulation within Anopheles mosquitoes, and specifically within the context of a malaria-associated paracentric inversion. Additionally, development and validation of analytical methods for proximity ligation data allow fine scale exploration of mosquito chromatin interactions and are broadly applicable across species. Anopheles gene regulation proximity-ligation Micro-C inversion biology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 BACKGROUND The Anopheles gambiae species complex contains the primary vectors of malaria, a disease caused by the Plasmodium parasite that continues to be a major worldwide health burden. Despite the implementation of widespread vector control strategies over 20 years ago, including insecticide-treated nets and indoor residual spraying, malaria still causes over 600,000 death per year – mainly in Sub-Saharan Africa 1 . Recent rising malaria case rates are the cumulative result of increased drug and insecticide resistance within the parasite and mosquito populations, respectively 1 , 2 . Efforts to understand the mechanisms underlying natural variation in mosquito susceptibility to Plasmodium infection would inform rational design of vector control tools. While the mosquito immune response to parasite infection has been well studied, the focus has largely been on candidate immune factors including APL1 3–8 , TEP1 3–5, 9 , LRIM1 3–6, 10–13 , and CEC 13 – 15 , and very little is known about how these agonists and antagonists of malaria infection are regulated. Recent work has begun to explore the role of regulatory elements and chromatin accessibility in response to parasite infection 16 , 17 . However, as regulatory elements can be located at significant distance from their target gene(s), a gap remains in linking regulatory elements with target genes. It is only with proximity ligation sequencing, or similar techniques providing insight into 3D chromatin folding, that Anopheles regulatory biology can be further refined. One form of genetic variation common to dipterans and prevalent across Anopheles species is the chromosomal inversion 18 – 21 . Primary vectors of malaria, Anopheles coluzzii and Anopheles gambiae , are polymorphic for the 2La inversion, a monophyletic 21.5MB paracentric chromosomal inversion on chromosome 2L 22 . The 2La inversion, whose allelic forms are denoted as 2La (ancestral) and 2L + a (derived) 22 , 23 , is associated with an intrinsic differential resistance to P. falciparum infection in Africa, in which 2L + a mosquitos are more susceptible to Plasmodium infection 24 , 25 . Additionally, the 2La inversion is associated with a number of other extrinsic vector competence factors, including differences in mosquito resting and biting behavior 24 , 26 , aridity 18 , 27 and thermal tolerance 27 – 29 , as well as insecticide resistance 30 . Mechanisms underlying the 2La inversion-associated phenotypes related to vector competence are not fully understood, but differences in chromatin conformation due to physical rearrangement of the chromosome likely play a role, particularly at inversion breakpoints where novel chromosome junctions were created. The hierarchy of chromatin folding includes, in ascending order from more local to more macro, chromatin loops which can bring enhancers (non-coding regulatory elements) into close proximity to promoters, enabling modulation of target gene(s) transcription; topologically-associating domains (TADs), which can be described as regulatory neighborhoods wherein enhancers are limited to acting on promoters located within the same TAD; and finally, A/B compartments, which are regions of active and inactive chromatin, respectively 31 , 32 . Chromatin conformation capture techniques, including 3C, 4C, and Hi-C/Micro-C, involve crosslinking chromatin within the nucleus, thus capturing the chromatin in its folded state, followed by fragmentation and proximity-ligation to enable identification of the interacting chromatin regions 33 . The different chromatin conformation capture techniques vary in their breadth of genomic coverage, ranging from locus-specific (e.g. 3C) to unbiased genome-wide (e.g. Hi-C) interrogation 33 . Micro-C, a variation of Hi-C that uses the unbiased cleaver micrococcal nuclease (MNase) for digestion instead of restriction enzymes thus enabling finer resolution, is a comprehensive and unbiased approach for determining chromatin conformation. Following fragmentation of crosslinked chromatin, the fragmented chromatin ends are repaired and biotinylated, proximity-ligation is performed, and the biotinylated DNA undergoes high-throughput paired-end sequencing. Therefore, chromatin interactions are queried on a genome-wide scale. Broad-scale analysis of Hi-C experimental data in Anopheles has been used to facilitate chromosome/genome assembly 34 – 37 , inversion breakpoint mapping 38 , and TAD structure determination 35 providing researchers with some understanding of the chromatin organization within Anopheles mosquitoes, but much remains unknown. Genome-wide maps of enhancers and chromatin accessibility in Anopheles have been generated by us using self-transcribing active regulatory region sequencing (STARR-seq) and assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) approaches, respectively. Additionally, well-annotated genomes (PEST version AgamP4 for the 2L + a inversion form 39 and MOPTI version 2021-03-25 for the 2La inversion form 34 ) are available for Anopheles gambiae and coluzzii , respectively. The integration of genomic datasets describing candidate regulatory elements and chromatin accessibility with proximity ligation sequencing enables fine-scale exploration of chromatin interactions, including the identification of enhancer-promoter interactions, which has been achieved in other organisms 40 – 42 . Here, we perform Micro-C and bulk RNA-sequencing on Anopheles coluzzii hemocyte-like cells fixed for alternate forms of the large paracentric 2La inversion to characterize inversion-associated changes in chromatin conformation. With the availability of genome-wide datasets of genes 39 , candidate enhancers 43 , and regions of open chromatin 16 , 17 , 44 , 45 coupled with the generation of proximity ligation sequencing data, we explore enhancer rewiring associated with the 2La inversion, prioritize a candidate regulatory element for malaria response immune gene LRIM1 that is located at a distance from the LRIM1 promoter region, and identify regulatory interaction hubs across the genome. RESULTS Micro-C and bulk RNA-sequencing of alternate 2La inversion karyotypes Micro-C and bulk RNA-sequencing libraries were generated from Anopheles coluzzii hemocyte-like cells confirmed to be homozygous for the ancestral (2La) or derived (2L + a ) form of the large 2La inversion using a previously published molecular karyotyping assay 46 (SUA4.0 = 2La/2La 47, 48 ; Ag55 = 2L + a /2L+ a47, 49, 50 ). Raw reads for both cell line samples were mapped to PEST (2L + a ) reference genome version AgamP4 (VectorBase release 68) to facilitate sample comparison. PEST was the reference genome of choice because it is the most mature chromosome-level Anopheline genome assembly 34 , 39 . When 2L + a /2L + a samples are mapped to PEST (2L + a reference genome), the resulting contact matrix of chromosome AgamP4_2L shows the classical pattern of a bright diagonal of nearby interactions (Fig. 1 A). Generally, when a sample of one inversion karyotype is mapped to a reference genome of the opposite inversion karyotype, the regions near the two inversion breakpoints that interact appear as a butterfly contact pattern 21 , 51 . Therefore, conversely, when 2La/2La samples are mapped to the 2L + a reference genome, a butterfly pattern emerges in chromosome AgamP4_2L, indicative of the 2La chromosomal inversion (Fig. 1 B). Ag55 (2L + a sample) contact matrices of chromosome AgamP4_2R revealed an irregular interaction structure, marked by the asterisks in Fig. 1 C. Approximate PEST positions of the three points of interactions are 19MB interacting with 26.6MB (consistent with the 2Rb inversion whose breakpoint positions are 19,023,925bp and 26,758,676bp 52 ), 26.6MB interacting with 32MB (consistent with the 2Rc inversion whose breakpoint positions are 26,758,676bp and 31,488,544bp 38 ), and 19MB interacting with 32MB (which is likely due to the two inverted regions being directly adjacent). This irregular interaction structure is in Ag55 samples (Fig. 1 C, E) but not SUA4.0 samples (Fig. 1 D,F), and it is present when mapping Ag55 samples to either PEST (Fig. 1 C) or MOPTI (Fig. 1 E) reference genomes, indicating that PEST and MOPTI are colinear for 2R + b and 2R + c which is consistent with the literature 34 . Other known inversions on chromosome 2R are 2Rj 53 and 2Ru 35 , whose PEST breakpoint coordinates are 3,262,186 − 15,750,717bp and 31,102,383 − 35,322,826bp, respectively. Both cell lines and both reference genomes are 2R + ju /2R + ju , evidenced by the lack of irregular interaction structure near 2Rj and 2Ru breakpoint coordinates (Fig. 1 C-F). We further investigated the Micro-C findings with the highest quality molecular karyotyping assays for 2Rb 54 , 2Rc 55 , 2Rj 56 , and 2Ru 57 on Ag55 and SUA4.0 cells. Ag55 was confirmed to be 2R + j bc+ u /2R + j bc+ u , and SUA4.0 was confirmed to be 2R+ jcbu / 2R+ jcbu (Additional File 1, FigS1). The 2Rc inversion has been reported to be in almost perfect linkage disequilibrium with the inverted form of either 2Rb or 2Ru 55 , which is consistent with our cell line karyotypes. Contact matrices of Ag55 and SUA4.0 replicates mapped to PEST and MOPTI for all chromosomes are in Additional File 1, FigS2. MultiHiCcompare 58 identifies differentially interacting regions between samples, regardless of distance between the interacting regions. The differential interactions that appear to span the entire length of the 2La inversion when 2La samples are mapped to PEST (2L + a reference genome) are actually an artifact of mapping to a reference genome of alternative inversion karyotype and provide quality control evidence that Micro-C of our 2La and 2L + a samples was successful (Fig. 1 G). MultiHiCcompare 58 identified 28,273 significant differentially interaction regions between 2La cells and 2L + a cells on chromosome AgamP4_2L (10,508 are more frequent in 2La/2La calls and 17,765 are more frequent in 2L + a /2L + a cells) (Fig. 1 H). Of these, 18,861 (~ 66.7% of differential interactions) have at least one anchor within the 2La inversion, which accounts for ~ 43.8% of the AgamP4_2L chromosome. DESeq2 59 was used to identify 2,297 differentially expressed genes (DEGs) between 2La and 2L + a cells genome-wide; 477 of these DEGs are on chromosome AgamP4_2L (205 are upregulated in 2La/2La cells, and 272 are upregulated in 2L + a /2L + a cells) (Fig. 1 I). The functional categories of the 477 DEGs on chromosomal AgamP4_2L were explored using the DAVID Functional Annotation Clustering tool 60 , 61 . The top 4 clusters were comprised of genes related to glycosyltransferase, nucleotide metabolism, serpins, and immunity (Additional File 2, Table S1 ). In the glycosyltransferase cluster, 6 of 7 genes (~ 86%) that contribute to that cluster are upregulated in 2La cells. In the nucleotide metabolism cluster, 8 of 11 genes (~ 73%) that contribute to that cluster are upregulated in 2La cells. In the serpins cluster, 5 of 5 genes (100%) that contribute to that cluster are upregulated in 2La cells. In the immunity cluster, 8 of 13 genes (~ 62%) that contribute to that cluster are upregulated in 2L + a cells. Evidence of novel enhancer rewiring associated with the 2La chromosomal inversion One interesting consequence of chromosomal inversions is that they can seed the process of enhancer rewiring - the evolution of novel interactions between enhancers and their target genes due to the change in physical proximity caused by the inversion 40 , 62 – 64 . To better understand the impact that chromatin conformation changes resulting from the 2La inversion have on gene expression, a focused analysis over the 2La breakpoints was performed, coupling Micro-C and bulk RNA-seq data. Enhancers were defined as being detected in at least 2 of 3 replicates from a previously published STARR-seq experiment 43 (Additional File 3). This includes the 788 previously published STARR-seq identified enhancers on the 2L chromosome detected in all 3 replicates (3288 genome wide enhancers) as well as 274 additional STARR-seq identified enhancers on 2L that were detected in 2 of 3 replicates (1,237 genome wide) for a total of 1062 STARR-seq candidate enhancers across 2L. Promoters were defined as the 1000bp region upstream of the protein coding gene as described by VEuPathDB 65 , 66 . These definitions of enhancers and promoters are used throughout all analyses. To identify evidence of novel enhancer rewiring associated with the 2La chromosomal inversion, three filters were applied to the 28,273 differential interactions between 2La and 2L + a samples identified via multiHiCcompare 58 : 1) the interaction had to occur over the proximal or distal breakpoint of the 2La inversion, 2) one anchor of the interaction had to contain at least one enhancer while the other anchor had to contain the promoter region of at least one DEG, and 3) the enhancers and promoter regions of the DEGs must interact over a 2La breakpoint in both 2La and 2L + a cell line samples (Fig. 2 A). Thirteen interactions met all three criteria, and they contained enhancers EP1, EP2 (located just outside of the proximal breakpoint), ED1, ED2, and ED3 (located just outside the distal breakpoint) and genes AGAP005781 (located inside the inversion on the proximal end in PEST), AGAP007066, AGAP007064, and AGAP007063 (located inside the inversion on the distal end in PEST) (Fig. 2 B). Near the proximal end of the inversion, in the cell line homozygous for the 2La ancestral form, EP1 and EP2 interact with AGAP007066, and EP2 additionally interacts with AGAP007064 and AGAP007063 while in the cell line homozygous for the 2L + a derived form, EP1 and EP2 interact with AGAP005781. Near the distal end of the inversion, in the cell line homozygous for the 2La ancestral form, ED1, ED2, and ED3 interact with AGAP005781 while in the cell line homozygous for the 2L + a derived form, those same enhancers instead interact with AGAP007066, and ED1 additionally interacts with AGAP007064 and AGAP007063 (Fig. 2 B). For each of these enhancers with evidence of rewiring associated with the inversion, we confirmed enhancer activity by luciferase assay, measuring activity of the 2L + a allele in a 2L + a /2L + a cellular background and the 2La allele in a 2La/2La cellular background (Fig. 2 C). EP1, EP2, and ED3 overlap with regions of open chromatin supported by our previously published ATAC-seq peaks 44 (Fig. 2 B) as well as FAIRE-seq peaks 45 , H3K27ac ChIP-seq peaks 16 , and ATAC-seq peaks 17 published from other labs, suggesting they are active enhancers across multiple tissues and cell types and in response to P. falciparum challenge. A table of all 329 differential interactions spanning either the proximal or distal 2La inversion breakpoint is in Additional File 4. A complete list of raw interaction counts for the 13 interactions involved in enhancer rewiring, with their log 2 FoldChange and adjusted p-values, is in Additional File 5. Methods validation of distance-decay correction analysis on interaction frequencies Beyond finding evidence of enhancer rewiring across the breakpoints of an inversion associated with factors affecting malaria vector competence, we developed and validated analytical approaches allowing broader use of our high-resolution Micro-C data to better inform our understanding of endogenous gene regulation in mosquitoes. These analyses were focused on only 2L + a sample data because their 2La inversion karyotype matches that of the PEST 2L + a reference genome, thus facilitating analysis. Enhancers are responsible for most regulated gene expression above basal levels in eukaryotes, but identifying candidate enhancers for a given target gene is difficult, especially because enhancers can interact at a distance either upstream or downstream from their target gene(s) 67 . Most commonly, candidate enhancers are inferred by nearest proximity to the target gene of interest. This approach is logical given that enhancers function through physical contact with promoters via transcription factor binding and because nearby chromatin regions interact more frequently, with interaction frequency decaying with distance. However, this nearest-gene approach ignores longer range interactions that can have strong phenotypic effect 68 , 69 . After normalizing interaction frequency for distance, proximity ligation sequencing identifies chromatin interactions that are enriched, thereby enabling prioritization of candidate enhancers based on increased interaction with a candidate target gene promoter. Using this approach in lieu of the simpler nearest-gene model can pinpoint physical evidence-based candidate regulatory elements worthy of further investigation. Using Micro-C data and distance-decay correction analysis, we examined chromatin interactions anchored on the promoter region of three Anopheles genes from previously published work that validated the function of each gene’s candidate enhancer 70 : OVO (AGAP000114), KLF (AGAP007038), and RDL (AGAP006028). In all three cases, the promoter region and its previously identified candidate enhancer interact more frequently than expected given their distance (OVO: z-score 1.53, p-value 0.13 (Fig. 3 A); KLF: z-score 2.23, p-value 0.03 (Fig. 3 B); RDL: z-score 0.84, p-value 0.40 (Fig. 3 C)). Furthermore, of the interactions between the promoter containing anchor and the anchor containing a STARR-seq enhancer, interactions with the previously characterized candidate enhancer for OVO, KLF and RDL had the highest z-score in all three cases. Unique application of distance-decay correction analysis on interaction frequencies to identify a novel candidate enhancer of LRIM1, an immune gene important to malaria response The chromatin interactions of Leucine-Rich Immune protein 1 (LRIM1) were explored because LRIM1 plays an important role in the malaria response within the mosquito 5 , 10 – 12 . It is one component of the TEP1/LRIM1/APL1 protein complex that promotes Plasmodium parasite killing 4 . Insight into the cis-regulation of LRIM1 could prove useful in the advent of novel malaria control methods. When anchoring on the 1000bp region upstream of LRIM1 as a proxy for its promoter, the 5kb enhancer-containing region with the highest z-score contains an enhancer with coordinates AgamP4_2L: 30142958–30143475 (z-score 2.16, p-value 0.03), located 187,821bp downstream of the LRIM1 gene (Fig. 4 A). Additionally, this candidate enhancer overlaps with previously published ATAC peaks 17 , 44 , FAIRE-seq peaks 45 , and H3K27ac ChIP-seq peaks 16 , suggesting that it is an active enhancer (Fig. 4 A). Activity of this candidate LRIM1 enhancer was confirmed by a luciferase assay conducted in both 2La/2La and 2L + a /2L + a cell lines (p < 0.001) (Fig. 4 B). Reciprocally, when interactions were instead anchored on the newly identified candidate LRIM1 enhancer, the 5kb region containing LRIM1’s promoter displayed a high interaction frequency for its distance (z-score 1.64), which is the 2nd highest z-score of 5kb regions containing a promoter (Fig. 4 C). The 5kb promoter-containing region with the highest z-score contains the promoter for AGAP006346 (z-score 2.57). It is not uncommon for an enhancer to regulate transcription of multiple target genes. This observed reciprocity of enriched interaction further supports AgamP4_2L_30142958–30143475 as a candidate enhancer of LRIM1. Note, p-values are not reported for candidate LRIM1 enhancer interactions because the residuals failed the Shapiro-Wilk test for normality; however, z-scores greater than 0 still represent interactions that are enriched given their distance. Additional application of distance-decay correction analysis on interaction frequencies to identify target genes of 9 previously characterized enhancers on chromosome 2L Capitalizing on the novel distance-decay correction analysis method, we identified the top candidate target genes of the 9 previously characterized enhancers within the malaria susceptibility locus on chromosome 2L. 44, 71 Top candidate target genes were identified by the highest z-score of promoter-containing interactions when anchored on each enhancer. The top candidate target gene(s), their associated z-score, and their approximate distance from the enhancer are listed in Table 1 . Because analysis is performed at 5kb resolution, the nearest possible candidate target gene identified in this analysis would be in the adjacent 5kb region to the enhancer. Top candidate target genes ranged from ~ 4-564kb from each enhancer, demonstrating the variety of distances from which enhancers can act on their target gene(s). Table 1 Candidate target genes based on highest interaction frequency from distance-decay correction analysis for previously characterized enhancers in the Plasmodium resistance island. The top candidate target gene(s) were determined for the enhancers characterized in Zmarlak-Feher et al. 2025 by identifying the genes in the promoter-containing interactions with the highest interaction frequency z-score. Distances between candidate target gene and enhancer ranged from ~ 4-564kb. Enhancer Enhancer Coordinates Top candidate target gene(s) Interaction z-score Approximate distance from enhancer ENH_2L-01 AgamP4_2L: 20422499–20423038 AGAP005745 1.84 ~ 248kb ENH_2L-02 AgamP4_2L: 20475573–20476075 AGAP005749, AGAP005750 (both fall within same 5kb region) 1.68 ~ 172kb ENH_2L-03 AgamP4_2L: 41873775–41874329 AGAP007058 1.60 ~ 182kb ENH_2L-04 AgamP4_2L: 41822211–41822718 AGAP007044 1.64 ~ 255kb ENH_2L-05 AgamP4_2L: 41809557–41810116 AGAP007032 2.18 ~ 564kb ENH_2L-06 AgamP4_2L: 41732814–41733335 AGAP007046 3.20 ~ 4kb ENH_2L-07 AgamP4_2L: 41729411–41730122 AGAP007032 1.26 ~ 484kb ENH_2L-08 AgamP4_2L: 41716724–41717232 AGAP007040 1.34 ~ 376kb ENH_2L-09 AgamP4_2L: 41623777–41624334 AGAP007047 0.84 ~ 8kb Chromatin interaction hubs are nearby enhancers and distant from promoters Proximity ligation sequencing provides two metrics of chromatin interactions: interaction frequency (read counts per bin pair), which measures interaction strength, and partner count (number of distinct interacting partners per bin), which measures interaction breadth. While distance-decay correction analysis assesses interaction frequency of the interactions from a given anchor, we also wanted to identify and characterize chromatin interaction hubs by assessing partner count across chromosome AgamP4_2L. Chromatin interactions are clustered across the 2L Anopheles chromosome generating hot spots/hubs of interaction: regions that interact with at least 102 other regions (Fig. 5 A). The minimum raw partner count for a given 5kb anchor across the 2L chromosome was 1, meaning that at least one region interacted with only 1 other region. The maximum raw partner count was 182, meaning that a region interacted with no more than 182 other regions. The average raw partner count was 63.85, with a median of 62. Chromatin interaction hubs were defined as the regions with the top 10% of partner counts (which for chromosome AgamP4_2L equated to interacting with ≥ 102 other regions) (Fig. 5 A). Detected interaction hubs are significantly closer to enhancers (p = 0.001, z-score − 7.38) (Fig. 5 B) and significantly farther from promoters (p = 0.001, z-score 27.17) than expected by random chance (Fig. 5 C). These observations are consistent across all Anopheles coluzzii autosomal arms (AgamP4_2R, AgamP4_3L, and AgamP4_3R) (Additional File 1, FigS3). DISCUSSION The 2La chromosomal inversion is a large, monophyletic, polymorphic inversion in Anopheles coluzzii and A. gambiae mosquitoes, the two major malaria vectors in Sub-Saharan Africa where malaria morbidity and mortality are highest. This paracentric inversion is associated with an intrinsic resistance to malaria infection 24 , 25 , among other phenotypes affecting the mosquito’s ability to transmit malaria 18 , 24 , 26 – 30 . How the 2La inversion alters enhancer-mediated gene regulation remains unknown. While chromatin conformation capture techniques have been used to study fine-scale chromatin interactions, such as enhancer-promoter interactions, in other organisms 40 – 42 , to date, these proximity ligation techniques have only been used in Anopheles mosquitoes for broader scale applications like chromosome assemblies 34 – 37 , inversion breakpoint mapping 38 , determining TAD structure 35 , and broad-scale analysis of chromatin loops 35 . Our fine-scale exploration of chromatin interactions within A. coluzzii hemocyte-like cells complements more broad-scale applications by identifying enhancer-promoter interactions involved in wiring/rewiring over 2La inversion breakpoints, utilizing proximity-ligation data to prioritize candidate enhancers, and identifying chromatin interaction hot spot enrichment near enhancers. Transcriptional differences In total, 2,297 genes were differentially expressed between 2La/2La cells and 2L + a /2L + a cells, and 477 (21%) of those are on chromosome AgamP4_2L (21% of the mosquito genome). DAVID Functional Annotation Clustering analysis of the 477 DEGs identified clusters of genes with related function. Cluster 1 included genes related to glycosyltransferase, and UDP-glycosyltransferases have been reported to be associated with pyrethroid insecticide resistance in Anopheles 72 , 73 . Cluster 2 included genes related to nucleotide metabolism. Many of these genes have roles in purine and pyrimidine salvage and synthesis, and purine-based metabolites have been implicated in signaling, immunity, and host-pathogen interactions across kingdoms 74 . Increases in the overall nucleotide pool have been reported 24 hours after bloodmeal 75 . Cluster 3 included genes related to serpins, which are negative regulators of innate immune responses in insects 76 , 77 . Cluster 4 included genes related to immunity. The 2La inversion has been reported to be associated with an intrinsic resistance to malaria infection with 2La/2La mosquitoes being more resistant 24 , 25 . To our knowledge, gene expression differences between unperturbed samples fixed for alternate forms of the 2La inversion have not been published. Microarray studies have been performed in 2La and 2L + a homokaryotic mosquitoes under thermal stress to identify differentially expressed genes either in heat hardened 2La/2La or 2L + a /2L + a A. gambiae larvae 78 or in comparisons of sex, environment aridity, 2La inversion karyotype, 2Rb inversion karyotype, or interactions of those factors in A. gambiae adults 79 . However, direct comparison to our data is not possible due to a variety of factors including minimal accessible data and lack of a direct comparison between 2La and 2L + a samples. Enhancer rewiring and the 2La inversion We identified 13 differential interactions involved in enhancer rewiring across 2La inversion breakpoints, containing 5 candidate enhancer regions that interact with four different genes (AGAP005781, AGAP007066, AGAP007064, AGAP007063) in an inversion-specific manner. Using an independent computational method, PSYCHIC 80 , these results were confirmed. AGAP005781 is predicted to interact with an enhancer across the distal breakpoint in 2La fixed cells and across the proximal breakpoint in 2L + a fixed cells. Further, AGAP007066 interacts with an enhancer across the proximal breakpoint in 2La fixed cells. Little is known about the function of these four genes. AGAP005781 is a glycine C-acetyltransferase and has been documented as a predicted miR-276 target gene, supported by 2 out of 3 prediction algorithms 81 . miR-276 is a bloodmeal-induced protein that terminates the reproductive cycle 81 . AGAP007066 is tRNA-specific adenosine deaminase 3 65, 66 , and AGAP00763 is origin recognition complex subunit 4 65, 66 ; neither has been further investigated in the literature. AGAP007064 is an unspecified product 65 , 66 and has been reported as being significantly enriched in Anopheles gambiae salivary glands compare to whole larvae 82 . Evidence suggests these genes are important to Anopheles due to the association of their regulation with 2La inversion karyotype and the evolution of novel enhancer-promoter interactions. Utilizing interaction frequencies to prioritize candidate regulatory regions Previous studies have queried the most proximal enhancer (AgamP4_2L: 30333431–30334787) to LRIM1 as a candidate enhancer 17 , 70 . However, application of a novel distance-normalized interaction frequency approach facilitated discovery of an LRIM1 candidate enhancer, located ~ 188kb downstream from the promoter. Such a distance is not unreasonable for an enhancer-promoter interaction because others have reported long-range interactions of > 100kb in Drosophila 83 , 84 , and Anopheles coluzzii TADs sizes have been reported to be up to 1MB in size 35 . This novel interaction frequency-based approach prioritizes a candidate LRIM1 enhancer over 7 STARR-seq identified candidate enhancers that are closer to the LRIM1 promoter region along the linear chromosome (5 upstream and 2 downstream) than the candidate regulatory region identified here (Fig. 4 A). Despite its large physical distance from LRIM1 (AGAP006348, PEST positions 30329656–30331296), this newly discovered candidate enhancer contains conserved sequence regions related to immune regulation. A ~ 90bp region (PEST positions 30143151–30143240) has high levels of sequence conservation (e values < 4x10 − 4 ) amongst members of the A. gambiae complex, two species most closely related to the A. gambiae complex ( A. christyi and A. epiroticus ), and more distantly related anopheline vectors of malaria ( A. stephensi 85 and A. funestus 86 ). Given that regulation of LRIM1 via both the Rel1 and Rel2 pathways has been described 87 , 88 , we examined this conserved sequence region for evidence of Rel1 ( Drosophila Dif) or Rel2 ( Drosophila Relish) TFBSs using MEME Suite 89 and available data from Drosophila melanogaster in JASPAR 90 . Within this conserved region, 6 of the 8 species share significant sequence similarity (p < 0.01) with a TFBS for the Relish ( Anopheles Rel2) transcription factor at the 5’ end of the sequence, and 5 of the 8 species show significant similarity with the Relish TFBS on the 3’ end (p < 0.01) (Additional File 1, FigS4). A query of the other NF-kB-like TFBS in Drosophila , Dif ( Anopheles Rel1), shows 7 of the 8 species share significant similarity (p < 0.01) only at the 5’ end (Additional File 1, FigS4). For all members of the A. gambiae species complex as well as A. christyi and A. epiroticus , both Dif and Relish binding sites are significant while for A funestus , only Dif is significant, and for A. stephensi , only Relish is significant (Additional File 1, FigS4). The ~ 180kb distance between the LRIM1 gene and the Micro-C-identified LRIM1 candidate enhancer is also conserved across 6 of the Anopheles species tested, minimally 173,257bp in A. coluzzii MOPTI to maximally 186,416bp in A. gambiae PEST. It is impossible to determine the distance between LRIM1 and this candidate regulatory region in either A. christyi or A. epiroticus given that the sequences are present on distinct sequence contigs. While cementing the relative importance of the newly discovered LRIM1 regulatory element will require additional work, it is only through proximity ligation assays like the Micro-C performed here that we are able to prioritize regulatory elements at a distance from the genes they regulate. Chromatin Interaction Hubs Through an examination of the distribution of chromatin interactions across the genome, we identified chromatin interaction hubs and characterized them as positively associated with enhancers and negatively associated with promoters. This finding is unsurprising as enhancers can act on multiple genes and allow for fine-tuning of gene expression, so an enhancer having contacts with many genomic regions enables the fine tuning of gene regulation in tissue-, time-, and stress responsive-specific ways. Conversely, we speculate that a promoter having contacts with many genomic regions likely does not provide significant benefit, and excess chromatin in its 3D proximity could interfere with transcription machinery. An independent method for identifying chromatin interaction hubs has been reported and utilized in primary human tissues, which models interaction counts with Poisson regression 91 . Briefly, for each 40kb bin of a genome-wide contact matrix, the total number of intra-chromosomal interactions within 15-200kb of each bin was calculated. Interactions were modeled using a Poisson distribution that corrected for biases of three factors: effective fragment length, GC content, and mappability. Residuals were calculated then converted into a z-score and -ln(p-value). Frequently Interacting Regions (FIREs) were defined as bins with a one-sided p-value 3 91 . Consistent with our results, FIREs occurred near active enhancers 91 , 92 . This supports the promiscuous behavior of enhancers by which one enhancer may have multiple target genes 67 , 93 . Conclusions Here, we utilize high-resolution measures of chromatin conformation alongside gene expression to characterize the impact of chromatin conformational changes associated with the 2La inversion on gene expression and 3D chromatin structure. Coupling chromatin conformation and gene expression results from 2La and 2L + a A. coluzzii hemocyte-like cell lines, we identify sets of genes and enhancers that differentially interact over inversion breakpoints, suggestive of enhancer rewiring and the novel evolution of enhancer-promoter interactions over inversion breakpoints. Further investigation into these enhancers/genes, or other genomic elements near inversion breakpoints, could provide insight into the differential phenotypes associated with the 2La inversion, including an intrinsic resistance to malaria infection 24 , 25 and differences in mosquito resting and biting behavior 24 , 26 , aridity 18 , 27 and thermal tolerance 27 – 29 . Additionally, knowledge of unique regulatory circuitry across inversion forms could help design vector control tools targeting mosquitoes of a given karyotype. Novel analytical approaches applied to our Micro-C data enable the identification and prioritization of interacting chromatin regions and a greater understanding of regulatory hot spots across the genome. These novel approaches allow fine-scale exploration of mosquito chromatin interactions and are broadly applicable across species for which Micro-C/Hi-C data are available. METHODS Cell culture Hemocytes are innate immune cells that kill pathogens, including the malaria parasite, through phagocytosis, lysis, and melanization 94 . Two hemocyte-like Anopheles coluzzii cell lines SUA4.0 (cell line homozygous for the 2La karyotype, will be referred to as 2La cells throughout) 47 , 48 and Ag55 (cell line homozygous for the 2L + a karyotype, will be referred to as 2L + a cells throughout) 47 , 49 , 50 were seeded at a density of 0.9x10^6 cells/mL in a T75 flask (three flasks per cell line per replicate) in antibiotic-free media (Insect Xpress (Lonza) for SUA 4.0, and Leibovitz’s L-15 Medium (Millipore Sigma) for Ag55). 48hr post-seeding, cells were washed with 1X PBS, scraped, and aliquots of ~ 1 million cells were spun at 3,000g for 5min. Supernatants were removed and cell pellets flash frozen in liquid nitrogen and stored at -80C until shipment for bulk RNA-sequencing (Azenta, South Plainfield, NJ) or Micro-C (Dovetail Genomics, part of Cantata Bio, Scotts Valley, CA). Four biological replicates were submitted for RNA-seq with the three most similar RNA-seq replicates (as determined by PCA analysis, Additional File 1, FigS5) also submitted for Micro-C. RNA-seq RNA-sequencing library preparation and sequencing Azenta performed RNA extraction, strand-specific library preparation, and sequencing to a depth of ~ 20 million paired-end reads per sample from flash frozen cell pellets of either SUA4.0 cells (2La) or Ag55 cells (2L + a ). Four biological replicates were performed for each cell line. Briefly, total RNA was extracted, and mRNA was enriched by Poly(A) selection. RNA integrity was assessed via TapeStation, and all samples had an RIN ≥ 9. After library preparation, sequencing was performed on an Illumina NovaSeq platform to generate 2x150bp paired end reads. 17.7–18.9 million reads were obtained per sample. Read preprocessing alignment and quantification Raw reads were assessed for quality using FastQC 95 . All samples showed high per-base quality (≥ 90% bases above Q30), and all reads had a mean quality score > 35. Adapter sequences and low-quality bases were trimmed using Trimmomatic-0.38 96 with parameters ILLUMINACLIP:TruSeq3-PE.fa:3:30:10:2:keepBothReads LEADING:3 TRAILING:3 MINLEN:26. Post-trimming quality was reassessed using FastQC. Cleaned reads were aligned to PEST version AgamP4 (VectorBase release 68) 65 , 66 using STAR (v2.7.10b) 97 , resulting in 90.26%-92.18% uniquely mapped reads. Annotation was based on VectorBase-68_AgambiaePEST.gff. Gene-level read counts were obtained using featureCounts (v2.0.6) 98 . Differential expression analysis Raw counts data were loaded into R, then normalized and analyzed using DESeq2 (v1.46.0) 59 . Prefiltering removed genes with fewer than 10 reads total, summed across all 8 samples being compared. DEGs between hemocyte-like cells homozygous for the 2La karyotype and those homozygous for 2L + a were defined as having a |log 2 foldchange| ≥1 and adjusted p-value ≤ 0.05. All RNA-seq reads are accessible at PRJNA1439337. Functional enrichment analysis The 477 differentially expressed genes between 2La and 2L + a samples on chromosome AgamP4_2L were assessed for functional gene annotation clustering using the DAVID 6.8 Functional Annotation Clustering tool using the DAVID Knowledgebase v2024q4 60, 61 . Classification Stringency was set to Medium (default), and EASE threshold was set to 1.3 (p < 0.05). Micro-C Micro-C library preparation and sequencing Because 2–3 biological replicates is standard for Hi-C/Micro-C, we performed PCA analysis on our four RNA-seq samples to determine the three most similar biological replicates (Additional File 1, FigS5). Biological replicates 1, 2, and 3 were submitted to Dovetail Genomics for Micro-C library preparation and sequencing. Briefly, the chromatin was fixed with disuccinimidyl glutarate (DSG) and formaldehyde in the nucleus. The cross-linked chromatin was then digested in situ with micrococcal nuclease (MNase). Following digestion, the cells were lysed with SDS to extract the chromatin fragments, and the chromatin fragments were bound to Chromatin Capture Beads. Next, the chromatin ends were repaired and ligated to a biotinylated bridge adapter followed by proximity ligation of adapter-containing ends. After proximity ligation, the crosslinks were reversed, the associated proteins were degraded, and the DNA was purified then converted into a sequencing library using Illumina-compatible adaptors. Biotin-containing fragments were isolated using streptavidin beads prior to PCR amplification. The library was sequenced on an Illumina NovaSeq platform to generate 201–234 million 2 x 150bp read pairs per sample. Samples were 3 biological replicates each of hemocyte-like cells homozygous for the 2La karyotype and hemocyte-like cells homozygous for the 2L + a karyotype for a total of 6 samples. After sequencing, we obtained ~ 100 million unique mappable reads for each replicate. Non-duplicate cis read pairs accounted for > 40% of total read pairs for all replicates, passing the QC metric for deep sequencing for Dovetail Genomics. Library statistics for Micro-C data are available in Additional File 6. All Micro-C data is available at PRJNA1439337. Micro-C Analysis Micro-C read processing and mapping Read processing and mapping was performed based on the workflow developed by Dovetail Genomics ( https://dovetail-analysis.readthedocs.io/en/latest/ ). Briefly, fastq files were aligned to the A. gambiae PEST reference genome (VectorBase-68_AgambiaePEST_Genome.fasta) or A. coluzzii MOPTI reference genome (VectorBase-68_AcoluzziiMOPTI_Genome.fasta) using BWA-MEM (v.0.7.17) 99 with options − 5SP -T0 -t16 for each replicate independently. Pairtools parse (v.1.0.3) 100 with options --min-mapq 40 --walks-policy 5unique --max-inter-align-gap 30 --nproc-in 8 --nproc-out 8 was used to find ligation events. Parsed pairs were sorted and PCR duplicates were removed using pairtools sort with --nproc16 and pairtools dedup with --nproc-in 8 --nproc-out 8 --mark-dups, respectively. Pairtools split with --nproc-in 8 --nproc-out 8 generated a .pairs file and a .bam file, which was sorted and indexed using samtools (v1.20) 101 . Generation of Contact Matrices Contact matrices were generated using Juicer Tools (v1.22.01) 102 with -Xmx48000m -Djava.awt.headless=true --threads 16. Contact matrices were visualized using Juicebox 103 , 104 . Determining inversion karyotype of cell line samples Genomic DNA was isolated from SUA4.0 (2La/2La hemocyte-like cells) and Ag55 (2L + a /2L + a hemocyte-like cells). The 2La inversion karyotype of each cell line was confirmed using a previously published PCR assay for 2La molecular karyotyping 46 . The two cell lines were selected for their known alternate 2La inversion karyotypes. The karyotypes of known chromosome 2R inversions for which there are molecular assays (2Rj 56 , 2Rb 54 , 2Rc 55 , and 2Ru 57 ) were also determined for each cell line, confirming Micro-C results. Both SUA4.0 and Ag55 are 2R + j /2R + j and 2R + u /2R + u . They differ in 2Rb and 2Rc inversion karyotype where SUA4.0 are 2R + b /2R + b and 2R + c /2R + c while Ag55 are 2Rb/2Rb and 2Rc/2Rc (Additional File 1, FigS1). Using multiHiCcompare to identify interacting regions MultiHiCcompare 58 was used for both within-group replicate analysis and comparative analysis of Micro-C datasets. Both analyses used make_hicexp and cyclic_loess functions to normalize and identify chromatin interactions supported by all three biological replicates from each cell line while comparative analysis additionally used the hic_exactTest function to identify differentially interacting regions between cell lines. MultiHiCcompare was selected as the program of choice for its comprehensive, unbiased approach. Chromatin loops are defined as extrusions of DNA through the ring-shaped cohesion protein that are arrested by CTCF protein binding to CTCF binding sites on the DNA 105 . In general, chromatin loop callers identify regions of increased interaction frequency compared to background or neighboring regions, using either algorithms on the contact matrix counts or on the visual image created by contact matrices 105 , 106 . Because chromatin loops are better understood in humans and mice and loop formation in insects may be slightly different, involving other CTCF-like insulator proteins like Beaf-32 107–109 , CP190 109, 110 , and Chromator 109 , 110 , we found existing chromatin loop callers to be biased in their identification of interacting regions and produce a limited number of chromatin interactions. For example, the loop caller Mustache 111 , which identifies a higher number of published ChIA-PET and HiChIP loops as compared to other loop callers HiCCUPS and SIP, identified 648 interactions on chromosome AgamP4_2L in 2L + a cells at 5kb resolution. In contrast, multHiCcompare 58 identified 309,139 interactions on chromosome AgamP4_2L in 2L + a cells at 5kb resolution. MultiHiCcompare identified 470 of 648 interactions that Mustache identified (72.5%), and the 178 interactions identified by Mustache that were not identified by multiHiCcompare all had average raw read counts ≤ 5, which multiHiCcompare considers low average read count and intentionally filters out. If the low read count filter is removed, the overlap of Mustache-identified interactions also identified by multiHiCcompare increases from 72.5% to 100%. In addition to identifying the same interactions as Mustache, multiHiCcompare has a number of other advantages including (1) it takes multiple biological replicates as input data to identify interacting regions, and (2) it does not implement a distance cut off (as evidenced in Fig. 1 G). Given these advantages, we used multiHiCcompare for an agnostic identification of chromatin interactions. For comparative analysis, three biological replicates of 2La samples were compared to three biological replicates of 2L + a samples, both mapped to PEST (2L + a reference genome) version Agam_P4 (VectorBase release 68) 65 , 66 . Within-group replicate analysis was performed only on 2L + a samples mapped to PEST to facilitate analysis. Contact matrices generated by Juicer Tools 102 were converted into sparse files for each chromosome independently using straw (v0.1.0) 104 . R package multiHiCcompare (v1.24.0) 58 was used to import the sparse files of Micro-C replicates at 5kb resolution, perform cyclic loess normalization, and detect interaction differences, if applicable. The hicexp object was created using the default parameters, except for remove.regions = NULL because a non-human genome was used. Default parameters zero.p and Amin filtered out low interaction counts, thus only keeping interactions supported by all biological replicates. Zero.p = 0.8 removed interactions in which > 80% of samples had a raw interaction count of 0, and Amin = 5 removed interactions in which the raw interaction counts across the biological replicates being analyzed averaged ≤ 5. Normalization was performed across the biological replicates using the cyclic_loess function with default parameters. For comparative analysis, the hic_exactTest function was used with default parameters. Differentially interacting regions were defined as regions where |log 2 foldchange| ≥1, log counts per million ≥ 0.5, and adjusted p-value ≤ 0.05. Identifying differentially interacting regions over inversion breakpoints Defining the 2La breakpoint Positions of 2La inversion breakpoints in PEST version AgamP4 (VectorBase release 68) were determined using PCR primers for molecular karyotyping of 2La and 2L + a chromosomes 46 . Primer DPCross5 46 blasts to PEST positions 20,528,072 − 20,528,094bp; therefore 20,528,072bp is used as the proximal breakpoint. Primer 27A2 46 blasts to PEST positions 42,165,607 − 42,165,626bp; therefore 42,165,626bp is used as the distal breakpoint. All mapping was to the PEST 2L + a reference genome. For visualization, the schematic of the 2La chromosome in Fig. 2 B was shown on the MOPTI 2La reference genome background (version 2021-03-25, VectorBase release 68). MOPTI breakpoints were assigned to a region analogous to PEST based on the position of genes internal vs external to each inversion breakpoint. MOPTI position 86,510,662bp is used for the proximal breakpoint, and 107,557,222bp is used for the distal breakpoint. Defining differential interactions over inversion breakpoints containing enhancer-promoter pairs 28,273 differential interactions between 2La and 2L + a samples on chromosome AgamP4_2L were determined from multiHiCcompare exactTest 58 (see above). Three filters were applied to these AgamP4_2L differential interactions to find evidence of enhancer rewiring associated with the 2La inversion: 1) the interaction had to occur over a 2La breakpoint, 2) one anchor had to contain at least 1 enhancer and the other anchor had to contain the promoter region (defined as the 1000bp region upstream of the protein coding gene) for at least one DEG, and 3) each enhancer and DEG promoter had to interact over a 2La breakpoint in both 2La and 2L + a samples. For filtering criteria (1), an interaction was defined as occurring over an inversion breakpoint if the breakpoint coordinate fell between the outermost coordinates of the two interaction anchors. There were 153 differential interactions over the proximal breakpoint (using PEST position 20528073bp), and 183 differential interactions over the distal breakpoint (using PEST position 42165625bp). Seven interactions occur over both the proximal and distal breakpoint, i.e. the interaction spans across the entire inversion and both breakpoints. All 7 of these interactions are present in 2La samples and absent in 2L + a samples; therefore, they are likely an artifact of mapping 2La samples to a 2L + a reference genome. These seven interactions were not double counted to arrive at the 329 total unique differential interactions occurring over a 2La inversion breakpoint, and they were filtered out in the downstream criteria. For filtering criteria (2), an enhancer was defined as being detected in at least 2 of 3 replicates from a previously published STARR-seq experiment 43 , and DEGs were defined as having a |log 2 foldchange| ≥1 and adjusted p-value ≤ 0.05 from our RNA-seq data. Promoters of the DEGs were defined as the 1000bp region upstream of the protein coding gene as described by VEuPathDB 65 , 66 . A bed file of enhancers detected in at least 2 of 3 replicates from a previously published STARR-seq experiment 43 is found in Additional File 3. This list is inclusive of the previously published 3288 STARR-seq Anopheles enhancers 43 . Of the 329 total unique differential interactions occurring over a 2La inversion breakpoint, 17 interactions contained at least 1 enhancer and at least one DEG promoter in each anchor (Fig. 2 A). Because of our interest in identifying enhancer rewiring, filtering criteria (3) required that each enhancer and DEG promoter interacted over a breakpoint in both 2La and 2L + a cells. This resulted in 13 interactions that satisfied all criteria, involving 5 candidate enhancers that interact with the promoter region of four different genes in an inversion-specific manner (Fig. 2 A). A table of all 329 differential interactions and their reason for inclusion/exclusion are found in Additional File 4. Comparing STARR-seq peaks with other published datasets Published open chromatin and epigenetics marker information was extracted from previously published work, and STARR-seq peaks were compared to identify active enhancers as previously described 45 . Briefly, peaks within +/- 1500bp of a given STARR-seq peak were considered to be overlapping. Candidate STARR-seq peaks were compared to ATAC-seq data from 4a-3A hemocyte-like cells from our previous work 45 , FAIRE-seq data from 4a-3B hemocyte-like cells 45 , ChIP-seq data from blood-fed and Plasmodium -infected mosquitoes 16 , and ATAC-seq data from midgut and salivary gland tissues of Plasmodium -infected mosquitoes 17 . Predicting enhancer-promoter interactions using PSYCHIC PSYCHIC 80 was run on a MacBook Pro using Python2.7 to enable python scripts to interact with MATLAB. PSYCHIC was run according to its GitHub instructions ( https://github.com/dhkron/PSYCHIC ). For input, PSYCHIC takes a Hi-C contact matrix, promoter bed file, and a series of other information including resolution of the contact matrix, interaction distance cutoff, chromosome name, and chromosome size. The output from PSYCHIC is a bed file of predicted enhancer-promoter interactions with coordinates of the putative enhancer, the name of its candidate target gene, distance of the gene to putative enhancer, FDR, p-value, number of expected interactions, and number of observed interactions. Using a p-value cutoff of ≤ 0.05, we identified putative enhancer-promoter pairs in our 2L + a samples mapped to PEST 2L + a reference genome version AgamP4 (VectorBase release 68) and our 2La samples mapped to MOPTI 2La reference genome version 2021-03-25 (VectorBase release 68). We filtered to identify enhancer-DEG promotor pairs occurring over a 2La breakpoint, with PEST positions 20,528,072bp as the proximal breakpoint and 42,165,626bp as the distal breakpoint and MOPTI positions 86,510,662bp as the proximal breakpoint and 107,557,222bp as the distal breakpoint, as described in above methods. Calculating distance-normalized interaction frequencies to correct for distance-decay Chromatin interactions are expected to decay with physical distance because regions that are physically closer will inherently interact more frequently. To evaluate whether chromatin interactions are enriched, one must first understand the null expectation for interactions given the distance between two anchors. To achieve this, we calculated a local null distribution of expected interaction frequency for each distance by performing linear regression analysis on log 10 -transformed distance and log 10 -transformed average interaction frequency for all interactions with a given anchor. With a null distribution, we were able to calculate residuals, a z-score, and a corresponding two-tailed p-value to indicate how frequent or infrequent an interaction is relative to other interactions of that same distance. A Shapiro-Wilk test was performed to confirm a normal distribution of residuals prior to calculating a p-value for each z-score. If a p-value is not reported for a z-score (as was the case for candidate LRIM1 enhancer interactions), it is because the residuals failed the Shapiro-Wilk test for normality. However, even without a p-value, a z-score > 0 still indicates that an interaction occurs more frequently than expected for its distance. These analytical and statistical methods enabled prioritization of enhancers or promoters for future investigation based on the z-score/p-value of their interaction. As above, an enhancer was defined as being detected in at least 2 of 3 replicates from a previously published STARR-seq experiment 43 . The 1000bp region upstream of the protein coding gene as described by VEuPathDB is used as a proxy for a gene’s promoter. For visualization in Integrative Genomics Viewer (IGV) 112 , z-scores were plotted as a heatmap, and the colorimetric scale in Fig. 3 , Fig. 4 A, and Fig. 4 C was set to red for a z-score ≥ 2 (p-value ≤ 0.0455), white for a z-score = 0 (p-value = 1), and blue for a z-score ≤-2 (p-value ≤ 0.0455). Measurement of enhancer activity by luciferase reporter assays Cloning of candidate enhancers As previously described 43 , 44 , candidate enhancer regions were PCR amplified from genomic DNA isolated from either SUA4.0 (2La) or Ag55 (2L + a ) cells. PCR reactions consisted of 10ng template DNA, 1X High-Fidelity PCR Master Mix with HF (Thermo), and 0.5uM of each forward and reverse primer. Cycling conditions were initial denaturation at 98C for 30s, 30 cycles of a 10s denaturation at 98C, 55-62C annealing temperature for 30s, and a 45s extension at 72C, followed by a final 10min extension at 72C. Resulting PCR products were either restriction enzyme cloned or Gateway cloned into a Firefly luciferase reporter vector pGL-Gateway-DSCP (AddGene, vector ID# 71506). Ligation products were transformed into OneShot OmniMax 2T1 Phage-Resistant Cells (Invitrogen), then grown overnight, plasmid purified, and sequenced. Amplification primers for candidate enhancers can be found in Additional File 5. Note these primers are designed to be inclusive of published enhancers 43 ; therefore, the amplicons are slightly larger than the STARR-seq published enhancer. Sequences of cloned alleles can be found in Additional File 7. Lipid based transfection and luciferase reporter assays Anopheles coluzzii SUA4.0 or Ag55 cells were seeded at 2.5x10^4 cells/well in 65ul in a 96 well plate. Cells were agitated on a MixMate (Eppendorf) for 30s at 300rpm for even distribution. Following a 24hr incubation period, lipid-based transfections were performed using Lipofectamine3000 (Invitrogen). Cells were transfected with two plasmids (1) the pGL-Gateway-DSCP (described above) carrying a single amplified fragment of the candidate enhancer upstream of a firefly luciferase gene and (2) a renilla control vector pRL-ubi-63E (AddGene, #74280). Plasmids were transfected at a ratio of 1:5 (renilla:firefly). Plates were agitated again for 30s at 300rpm on a MixMate (Eppendorf) and incubated for 24h at 27C. The Dual-Glo Luciferase Assay System (Promega) was used for luciferase assays, according to supplier instructions. Measurements were recorded on the GloMax Discover (Promega) at 25°C. All test plates contained cells transfected with control plasmid constructs: a negative control fragment, which was a size-matched fragment within intron 1 of AGAP007058 (DLX), and a highly active positive control enhancer peak nearby AGAP008980 70 . All samples were run in 6-fold technical replication within a single plate and across at least two independent plates for at least two biological replicates. Firefly luciferase measurements were normalized to renilla measurements from the same well. These measurements were then expressed relative to the firefly/renilla mean for the negative control on the same plate. An unpaired t-test comparing the mean enhancer activity with the mean of background (the negative control 43 ) was the statistical test used to validate enhancer function. Identifying chromatin interaction hubs Within-group replicate analysis by multiHiCcompare 58 identified interacting regions supported by 3 biological replicates of 2L + a cells. To identify chromatin interaction hubs, partner count (number of distinct interacting partners per bin) was determined for each 5kb anchor region by counting the number of unique partner anchors it had. Chromatin interaction hubs were defined as the 5kb regions with the top 10% of partner counts (which for chromosome AgamP4_2L equated to interacting with ≥ 102 other regions). Results were visualized in IGV 112 . Permutation testing using RegioneR To determine whether the identified interaction hubs were closer to or farther from various genomic elements than expected by random chance, permutation testing was performed using R package regioneR (v1.38.0) 113 . The reference genome was manually set to the A. gambiae PEST reference genome version AgamP4 (VectorBase release 68) for the chromosome of interest. We used the permTest meanDistance function to evaluate the statistical significance of the average distance between interaction hub (top 10% of interacting regions, described above) and enhancer (as defined as a genomic fragment detected in at least 2 of 3 replicates from a previous STARR-seq experiment 43 ). To establish the null distribution and determine whether the identified interaction hubs were closer to or farther from enhancers than expected by random chance, the genomic coordinates of the interaction hubs were randomized using the randomizeRegions function. 1000 permutation tests were performed to generate the null distribution. RegioneR calculated the observed mean distance, the distribution of mean distances under randomization, z-score, and empirical p-value. Results were visualized using the plot function. Analysis was repeated replacing enhancers with promoters. The promoter bed file contained the 1000bp region upstream of each protein coding gene as described by VEuPathDB. Abbreviations DEG differentially expressed gene DIR differentially interacting region IGV Integrative Genomics Viewer TFBS transcription factor binding site TAD topologically associating domain Declarations Ethics Approval and consent to participate Not applicable Consent for publication All authors have seen and approved the manuscript, and it has not been accepted for publication elsewhere. Funding This study received financial support to KST National Institutes of Health, # AI188600 and to MMR from National Institutes of Health, NIAID #AI145999 and #AI191531. Author Contribution KST, KDV, MMR designed the research. KST and CEA and performed the research. KST analyzed the data, and KST and MMR wrote the manuscript with input from all authors. Acknowledgement We thank Hans-Michael Müller (Sua4.0) and Michael Adang (Ag55) for sharing the cell lines. 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Supplementary Files AdditionalFilesCombined.pdf Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 30 Apr, 2026 Reviews received at journal 27 Apr, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers agreed at journal 03 Apr, 2026 Reviewers invited by journal 02 Apr, 2026 Editor assigned by journal 25 Mar, 2026 Submission checks completed at journal 25 Mar, 2026 First submitted to journal 24 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9213027","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":617650586,"identity":"05b042e3-4851-478a-95fb-84bc4cdbd05c","order_by":0,"name":"Kathryn S. Taquet","email":"","orcid":"","institution":"Medical College of Wisconsin","correspondingAuthor":false,"prefix":"","firstName":"Kathryn","middleName":"S.","lastName":"Taquet","suffix":""},{"id":617650588,"identity":"5ffcf668-6ab0-4af9-98c3-a71a6526fb72","order_by":1,"name":"Cameron E. Anderson","email":"","orcid":"","institution":"Medical College of Wisconsin","correspondingAuthor":false,"prefix":"","firstName":"Cameron","middleName":"E.","lastName":"Anderson","suffix":""},{"id":617650590,"identity":"d53f18ca-322f-46ad-97b2-9928205e3460","order_by":2,"name":"Kenneth D. Vernick","email":"","orcid":"","institution":"Institut Pasteur","correspondingAuthor":false,"prefix":"","firstName":"Kenneth","middleName":"D.","lastName":"Vernick","suffix":""},{"id":617650592,"identity":"10b09bd5-68cb-4c50-85b9-792fd758ce26","order_by":3,"name":"Michelle M. Riehle","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArElEQVRIiWNgGAWjYFACxgZmhgIGOQiHjWgtBgzGpGhhYABpSWwgWovu7MONjwsMbNLXtp8xYPhQdpiwFrNzic3GMwzScredyTFgnHGOGC1nGNukeQwO5267wbuBmbeNOC3tv3kM/qebgbT8JVJLGzOPwYEEsBZGIrU0Ax2WbLjtTP6Hgz3n0onRwv7wM0+FnbzZ8WOJD36UWRPWggIOkKh+FIyCUTAKRgEuAAAsbjmXR6BNWgAAAABJRU5ErkJggg==","orcid":"","institution":"Medical College of Wisconsin","correspondingAuthor":true,"prefix":"","firstName":"Michelle","middleName":"M.","lastName":"Riehle","suffix":""}],"badges":[],"createdAt":"2026-03-24 14:09:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9213027/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9213027/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106552548,"identity":"e3116b71-5a13-40bd-bebc-a965185950b4","added_by":"auto","created_at":"2026-04-09 18:45:56","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":588149,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProximity ligation and transcriptomic characterization of hemocyte-like cell lines fixed for alternate 2La inversion karyotypes. A-B)\u003c/strong\u003e Chromosome 2L contact matrices of 2L+\u003csup\u003ea\u003c/sup\u003e fixed samples (\u003cstrong\u003eA\u003c/strong\u003e) or 2La fixed samples (\u003cstrong\u003eB\u003c/strong\u003e) mapped to the \u003cem\u003eA. gambiae\u003c/em\u003e 2L+\u003csup\u003ea\u003c/sup\u003e PEST reference genome. In B, the butterfly pattern (circled) indicates the 2La inversion (labeled line) when a sample of one inversion karyotype (2La) is mapped to a reference genome of the alternate karyotype (2L+\u003csup\u003ea\u003c/sup\u003e). \u003cstrong\u003eC-D)\u003c/strong\u003e Chromosome 2R contact matrices of 2L+\u003csup\u003ea\u003c/sup\u003e fixed samples (\u003cstrong\u003eC\u003c/strong\u003e) or 2La fixed samples (\u003cstrong\u003eD\u003c/strong\u003e) mapped to the 2L+\u003csup\u003ea\u003c/sup\u003e PEST reference genome. In C, the asterisks mark irregular interaction structure, and the labeled lines show 2Rb and 2Rc inversions. \u003cstrong\u003eE-F)\u003c/strong\u003e Chromosome 2 contact matrices of 2L+\u003csup\u003ea\u003c/sup\u003e fixed samples (\u003cstrong\u003eE\u003c/strong\u003e) or 2La fixed samples (\u003cstrong\u003eF\u003c/strong\u003e) mapped to the \u003cem\u003eA. coluzzii\u003c/em\u003e 2La MOPTI reference genome. Chromosome CM029348 in the MOPTI genome is chromosome 2 with both L and R arms. In E, the asterisks mark irregular interaction structure, the 2La inversion butterfly pattern is circled, and the labeled lines show 2Rb, 2Rc, and 2La inversions. MOPTI is non-colinear to PEST regarding the 2La inversion, evidenced by the 2La butterfly pattern in 2La samples when mapped to PEST 2L+\u003csup\u003ea\u003c/sup\u003e reference (\u003cstrong\u003eB\u003c/strong\u003e) but in 2L+\u003csup\u003ea\u003c/sup\u003e samples when mapped to MOPTI 2La reference (\u003cstrong\u003eE\u003c/strong\u003e). MOPTI is co-linear to PEST regarding the 2Rb and 2Rc inversions, evidenced by the irregular interaction structure in both PEST- (\u003cstrong\u003eC\u003c/strong\u003e) and MOPTI-mappings (\u003cstrong\u003eE\u003c/strong\u003e) of 2La+ fixed sample. \u003cstrong\u003eG)\u003c/strong\u003e Interactions (shown as arcs) from multiHiCcompare within-group replicate analysis of 5kb region with PEST positions 42260000-42265000bp (94,375bp outside the 2La inversion) that are present in 2La sample (top, red) and 2L+\u003csup\u003ea\u003c/sup\u003e sample (bottom, blue) mapped to the 2L+\u003csup\u003ea\u003c/sup\u003e PEST reference genome. The ~21MB red arc depicts interactions between physically proximal regions in the 2La karyotype, but here when mapped to the 2L+\u003csup\u003ea\u003c/sup\u003e reference genome, the interaction spans ~21MB (the length of the 2La inversion). \u003cstrong\u003eH) \u003c/strong\u003eVolcano plot of differentially interacting regions (DIRs) on chromosome 2L between 2La fixed and 2L+\u003csup\u003ea\u003c/sup\u003e fixed samples as determined by multiHiCcompare comparative analysis of Micro-C data. DIRs were defined as having |log2foldchange| ≥1, log counts per million ≥0.5, and adjusted p-value≤0.05. \u003cstrong\u003eI)\u003c/strong\u003e Volcano plot of differentially expressed genes (DEGs) on chromosome 2L between 2La fixed and 2L+\u003csup\u003ea\u003c/sup\u003e fixed samples as determined by DESeq2 analysis of RNA-seq data. DEGs were defined as having a |log2foldchange| ≥1 and adjusted p-value ≤0.05.\u003c/p\u003e","description":"","filename":"Fig1v21.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9213027/v1/f1ac642acf64420d75c5adbc.jpg"},{"id":106552550,"identity":"ac96a868-c78a-4b21-b26f-c430646ca08c","added_by":"auto","created_at":"2026-04-09 18:45:56","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":443119,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProximity ligation uncovers novel enhancer rewiring over 2La inversion breakpoints. A)\u003c/strong\u003e Flow chart showing filtering criteria of differential interactions on chromosome 2L between samples from 2La and 2L+\u003csup\u003ea\u003c/sup\u003e cell lines to identify interactions of interest. Differentially interacting regions between 2La and 2L+\u003csup\u003ea\u003c/sup\u003e samples were determined using multiHiCcompare comparative analysis of 5kb resolution Micro-C data. Filter (1) required that differential interactions occur over a 2La inversion breakpoint (PEST: 20,528,073bp, proximal; 42,165,625bp, distal). Filter (2) required that one anchor of the interaction contained at least one enhancer (EN), and the other anchor contained the promoter region of at least one differentially expressed gene (DEG). To identify evidence of enhancer wiring and re-wiring, filter (3) required that each enhancer and promoter had to interact over a 2La breakpoint in both 2La and 2L+\u003csup\u003ea\u003c/sup\u003e samples. \u003cstrong\u003eB)\u003c/strong\u003e Schematics depicting the 13 differential chromatin interactions occurring over a 2La inversion breakpoint, involving enhancers and promoters that differentially interact in an inversion-specific manner. Upper image is a 30MB window around the 2La inversion (gray bar) with distributions of STARR-seq peaks (green), ATAC-seq peaks (purple), promoter regions of DEGs (blue for upregulated in 2L+\u003csup\u003ea\u003c/sup\u003e sample, red for upregulated in 2La sample), and genes (teal). Black boxes at both ends of the inversion highlight the regions where chromatin interactions occur over the breakpoint, and these regions are shown at high resolution below. Lower images show 2L+\u003csup\u003ea\u003c/sup\u003e interactions (in blue) and 2La interactions (in red) in 150kb windows around the proximal (left) and distal (right) breakpoints of the 2La inversion. For illustration purposes, the 2La interactions (red) are shown on the MOPTI (2La reference genome) background to emphasize that in the 2La karyotype, genes 7066, 7064, and 7063 are near the proximal breakpoint and gene 5781 is near the distal breakpoint. Horizontal blocks connected by arcs represent 5kb genomic regions and an interaction between the two 5kb anchor regions. The gray bar indicates the extent of the 2La inversion. Genomic elements in the tracks below the 2La inversion (gray bar) are colored as in the upper image: STARR-seq peaks (green), ATAC-seq peaks (purple), promoter regions of DEGs (blue for upregulated in 2L+\u003csup\u003ea\u003c/sup\u003e sample, red for upregulated in 2La sample), and genes (teal). The labeled promoters (5781, 7063, 7064, 7066) meet the filtering criteria from panel A. Note: the leading “AGAP00” for the labeled gene promoters has been omitted. Enhancer rewiring is evidenced by a number of interactions: in 2L+\u003csup\u003ea\u003c/sup\u003e cells, EP1 and EP2 interact with 5781 while in 2La cells, they interact with 7066, and EP2 additionally interacts with 7064 and 7063. In 2L+\u003csup\u003ea\u003c/sup\u003e cells, ED1, ED2, and ED3 interact with 7066, and ED1 additionally interacts with 7064 and 7063 while in 2La cells, they interact with 5781. \u003cstrong\u003eC)\u003c/strong\u003e All five candidate enhancers involved in chromatin interactions spanning an inversion breakpoint were tested for enhancer activity with a luciferase assay. Candidate enhancer alleles were cloned from 2L+\u003csup\u003ea\u003c/sup\u003e cells or 2La cells into luciferase reporter plasmid pGL_Gateway-DSCP, and enhancer activity was tested using a dual glo luciferase assay system. Enhancer activity of 2L+\u003csup\u003ea\u003c/sup\u003e alleles was tested in 2L+\u003csup\u003ea\u003c/sup\u003e homokaryotic cells (blue bars) and 2La alleles in 2La homokaryotic cells (red bars) to quantify luciferase activity above background, defined as negative control (dotted line, y=1) as used previously\u003csup\u003e70\u003c/sup\u003e. Y-axis indicates the relative luciferase activity for each measurement, expressed as firefly luciferase corrected to the renilla luciferase internal control value, and normalized for the value of the negative control. All samples were run in 6-fold technical replication, across two biological replicates. All alleles of all candidate enhancers displayed normalized luciferase activity significantly above background (p-values ranged from \u0026lt;0.001-0.035), thus validating the candidate enhancers as functional. Comparisons were made using an unpaired t-test comparing the mean enhancer activity with the mean of background (negative control). Error bars represent +/- 1 standard deviation.\u003c/p\u003e","description":"","filename":"Fig1v22.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9213027/v1/5387a5a77add17a7e706c540.jpg"},{"id":106725207,"identity":"98203f69-30b7-4cd2-a352-2476635c9b72","added_by":"auto","created_at":"2026-04-12 18:31:50","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":480550,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNovel analysis of Micro-C data validates interaction between candidate enhancers and their target gene. \u003c/strong\u003eSchematic of chromatin interactions anchored on the promoter region of three genes and their distance-normalized interaction frequency z-scores. Interactions (purple arcs and their associated 5kb anchors) for each promoter region (black vertical box), as defined by the 1000bp region upstream of a given protein coding gene, were generated from multiHiCcompare within-group replicate analysis of 5kb resolution 2L+\u003csup\u003ea\u003c/sup\u003e Micro-C contact matrices. For each interaction, a z-score of the residual interaction frequency relative to the expected interaction frequency for that distance was computed. The z-score quantifies how frequent or infrequent an interaction is, corrected for its distance. Colored vertical boxes indicate z-score where red ≥2 (interaction is more frequent than expected for its distance), white = 0 (interaction frequency is as expected for its distance), and blue ≤-2 (interaction is less frequent than expected for its distance). In each panel, STARR-seq identified candidate enhancers are shown in green, and annotated genes in teal with the gene of interest in black. The arrowheads indicate the candidate enhancer for each gene as described by Nardini et al. Each window depicted in A-C is approximately 810kb. Enlargement of each candidate enhancer interaction is shown to the right. \u003cstrong\u003eA)\u003c/strong\u003e OVO’s (AGAP000114) interaction with the candidate enhancer region has a z-score of 1.53 (p-value 0.13). \u003cstrong\u003eB)\u003c/strong\u003e KLF’s (AGAP007038) interaction with candidate enhancer region has a z-score of 2.23 (p-value 0.03). \u003cstrong\u003eC)\u003c/strong\u003e RDL’s (AGAP006028) interaction with candidate enhancer region has a z-score of 0.84 (p-value 0.40). In all three cases depicted in A-C, the previously characterized candidate enhancers overlap with regions of enriched interaction with the OVO, KLF, and RDL promoters, respectively. Additionally, of the 5kb regions containing a STARR-seq candidate enhancer, the previously characterized candidate enhancers are in the 5kb region with the highest z-score in all three cases.\u003c/p\u003e","description":"","filename":"Fig1v23.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9213027/v1/b574be641a6c2123bbac1026.jpg"},{"id":106552553,"identity":"ee0d3163-53d4-4d45-9040-9c608c2928bb","added_by":"auto","created_at":"2026-04-09 18:45:56","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":349777,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMicro-C enables prioritization of a candidate enhancer located ~180kb downstream of LRIM1 promoter. A)\u003c/strong\u003e Interactions (purple arcs and their associated 5kb anchors) anchored on the LRIM1promoter region (AGAP006348, black box) were generated from multiHiCcompare within-group replicate analysis of 5kb resolution 2L+\u003csup\u003ea\u003c/sup\u003e Micro-C contact matrices. Interaction frequency z-scores were calculated as in Fig3, and the z-score scale is shown, where red ≥2 (interaction is more frequent than expected for its distance), white = 0 (interaction frequency is as expected for its distance), and blue ≤-2 (interaction is less frequent than expected for its distance). The arrowhead points to the STARR-seq peak (AgamP4_2L:30142958-30143475) that is a novel candidate LRIM1 enhancer (z-score 2.16, p-value \u0026lt;0.05); enlarged on the right. This enhancer overlaps with an ATAC-seq peak (purple) and is marked by the histone mark H3K27ac\u003csup\u003e17\u003c/sup\u003e, suggesting it is an active enhancer. \u003cstrong\u003eB)\u003c/strong\u003e This novel candidate LRIM1 enhancer sequence was cloned from 2L+\u003csup\u003ea\u003c/sup\u003e cells (the same sample that generated the interaction arcs), and enhancer activity was tested using a luciferase assay. Y-axis indicates the relative luciferase activity for each measurement, expressed as firefly luciferase corrected to the renilla luciferase internal control value, and normalized for the value of the negative control. All samples were run in 6-fold technical replication, across two biological replicates. The candidate LRIM1 enhancer displayed normalized luciferase activity significantly above background (negative control, dotted line, y=1) (p\u0026lt;0.0001) when assayed in both 2L+\u003csup\u003ea\u003c/sup\u003e and 2La cells, thus demonstrating enhancer activity for the candidate LRIM1 enhancer. Comparisons were made using an unpaired t-test comparing the mean enhancer activity with the mean of background (negative control). Error bars represent +/- 1 standard deviation. \u003cstrong\u003eC)\u003c/strong\u003e A reciprocal analysis instead anchored on the newly identified LRIM1 enhancer (AgamP4_2L:30142958-30143475) indicates the interaction between the candidate LRIM1 enhancer (black box) and the LRIM1 promoter region (arrowhead) occurs more frequently than expected for its distance (z-score 1.64); enlarged on the right. Apart from the regions immediately proximal to the enhancer-containing anchor, the LRIM1 promoter-containing anchor has the highest z-score.\u003c/p\u003e","description":"","filename":"Fig1v24.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9213027/v1/a145252369af53eb948b849a.jpg"},{"id":106552552,"identity":"abb8142f-eaf3-4a32-a118-39d7145b99f1","added_by":"auto","created_at":"2026-04-09 18:45:56","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":272603,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChromatin interaction hubs are located near enhancers. A)\u003c/strong\u003e Schematic of the partner counts across chromosome 2L (red) and the 5kb regions with the top 10% of partner counts (gold) in relation to STARR-seq peaks (green), promoters (dark blue), and the 2La inversion (gray). Chromosome 2L chromatin interactions were generated from multiHiCcompare within-group replicate analysis of 5kb resolution 2L+\u003csup\u003ea\u003c/sup\u003e Micro-C contact matrices. The partner count (number of distinct interacting partners per bin) for each 5kb region was determined and plotted as a heatmap (min = 1 (white), max = 182 (red)). Chromatin interaction hubs were defined as the regions with the top 10% of partner counts (which for chromosome AgamP4_2L equated to interacting with ≥102 other regions). \u003cstrong\u003eB)\u003c/strong\u003e To assess whether identified interaction hubs were closer to or farther from enhancers than expected by random chance, permutation testing was performed using R package regioneR. The permTest meanDistance function was used, interaction hubs were set as region set A, and STARR-seq peaks were set as region set B (1062 STARR-seq peaks on AgamP4_2L). The PEST reference genome was manually set, and the randomizeRegions function was used to perform 1000 permutation tests, creating the null distribution (gray histogram and black bell curve) whose average distance to nearest STARR-seq peak is highlighted by the black line (Ev\u003csub\u003eperm\u003c/sub\u003e = mean of the randomized permutations). The red line and red shading represent the significance limit, set to p=0.05. The green line is the average distance between interaction hub and nearest STARR-seq peak (Ev\u003csub\u003eobs\u003c/sub\u003e = mean of the observed region set). The average distance between an interaction hub and the nearest STARR-seq peak was significantly smaller compared to a random null distribution, evidenced by the green line being to the left of the red line, indicating that interaction hubs are closer to enhancers than expected by random chance (z-score -7.379, p-value = 0.001). \u003cstrong\u003eC)\u003c/strong\u003e The same permutation testing was performed using promoters, defined as the 1000bp region upstream of a protein coding gene, as region set B (3089 promoters on AgamP4_2L). The average distance between an interaction hub and the nearest promoter was significantly larger compared to a random null distribution, shown by the green line being to the right of the red line, indicating that interaction hubs are farther from promoters than expected by random chance (z-score 27.173, p-value = 0.001). Interaction hubs are closer to enhancers and farther from promoters across all \u003cem\u003eA. coluzzii\u003c/em\u003e autosomal arms (Additional File 1, FigS3).\u003c/p\u003e","description":"","filename":"Fig1v25.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9213027/v1/3576a71776ce8f5f083525a6.jpg"},{"id":106728236,"identity":"ded90c01-7f51-4eff-8aaa-a911983c906b","added_by":"auto","created_at":"2026-04-12 18:42:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4206742,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9213027/v1/623a9f2e-3585-4bc2-96cd-c9e4bca3dd7b.pdf"},{"id":106727116,"identity":"b27150e4-545e-4a6b-90ed-629be1559ac2","added_by":"auto","created_at":"2026-04-12 18:38:09","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1534405,"visible":true,"origin":"","legend":"","description":"","filename":"AdditionalFilesCombined.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9213027/v1/66837e6d35be5d827ef8b7fd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Anopheles gambiae 2La chromosomal inversion influences chromatin organization and 3D landscape of genes related to malaria transmission","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eThe \u003cem\u003eAnopheles gambiae\u003c/em\u003e species complex contains the primary vectors of malaria, a disease caused by the \u003cem\u003ePlasmodium\u003c/em\u003e parasite that continues to be a major worldwide health burden. Despite the implementation of widespread vector control strategies over 20 years ago, including insecticide-treated nets and indoor residual spraying, malaria still causes over 600,000 death per year \u0026ndash; mainly in Sub-Saharan Africa\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Recent rising malaria case rates are the cumulative result of increased drug and insecticide resistance within the parasite and mosquito populations, respectively\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Efforts to understand the mechanisms underlying natural variation in mosquito susceptibility to \u003cem\u003ePlasmodium\u003c/em\u003e infection would inform rational design of vector control tools. While the mosquito immune response to parasite infection has been well studied, the focus has largely been on candidate immune factors including APL1\u003csup\u003e3\u0026ndash;8\u003c/sup\u003e, TEP1\u003csup\u003e3\u0026ndash;5, 9\u003c/sup\u003e, LRIM1\u003csup\u003e3\u0026ndash;6, 10\u0026ndash;13\u003c/sup\u003e, and CEC\u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, and very little is known about how these agonists and antagonists of malaria infection are regulated. Recent work has begun to explore the role of regulatory elements and chromatin accessibility in response to parasite infection\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, as regulatory elements can be located at significant distance from their target gene(s), a gap remains in linking regulatory elements with target genes. It is only with proximity ligation sequencing, or similar techniques providing insight into 3D chromatin folding, that \u003cem\u003eAnopheles\u003c/em\u003e regulatory biology can be further refined.\u003c/p\u003e \u003cp\u003eOne form of genetic variation common to dipterans and prevalent across \u003cem\u003eAnopheles\u003c/em\u003e species is the chromosomal inversion\u003csup\u003e\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Primary vectors of malaria, \u003cem\u003eAnopheles coluzzii\u003c/em\u003e and \u003cem\u003eAnopheles gambiae\u003c/em\u003e, are polymorphic for the 2La inversion, a monophyletic 21.5MB paracentric chromosomal inversion on chromosome 2L\u003csup\u003e22\u003c/sup\u003e. The 2La inversion, whose allelic forms are denoted as 2La (ancestral) and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e (derived)\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, is associated with an intrinsic differential resistance to \u003cem\u003eP. falciparum\u003c/em\u003e infection in Africa, in which 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e mosquitos are more susceptible to \u003cem\u003ePlasmodium\u003c/em\u003e infection\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Additionally, the 2La inversion is associated with a number of other extrinsic vector competence factors, including differences in mosquito resting and biting behavior\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, aridity\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e and thermal tolerance\u003csup\u003e\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, as well as insecticide resistance\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Mechanisms underlying the 2La inversion-associated phenotypes related to vector competence are not fully understood, but differences in chromatin conformation due to physical rearrangement of the chromosome likely play a role, particularly at inversion breakpoints where novel chromosome junctions were created.\u003c/p\u003e \u003cp\u003eThe hierarchy of chromatin folding includes, in ascending order from more local to more macro, chromatin loops which can bring enhancers (non-coding regulatory elements) into close proximity to promoters, enabling modulation of target gene(s) transcription; topologically-associating domains (TADs), which can be described as regulatory neighborhoods wherein enhancers are limited to acting on promoters located within the same TAD; and finally, A/B compartments, which are regions of active and inactive chromatin, respectively\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Chromatin conformation capture techniques, including 3C, 4C, and Hi-C/Micro-C, involve crosslinking chromatin within the nucleus, thus capturing the chromatin in its folded state, followed by fragmentation and proximity-ligation to enable identification of the interacting chromatin regions\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. The different chromatin conformation capture techniques vary in their breadth of genomic coverage, ranging from locus-specific (e.g. 3C) to unbiased genome-wide (e.g. Hi-C) interrogation\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Micro-C, a variation of Hi-C that uses the unbiased cleaver micrococcal nuclease (MNase) for digestion instead of restriction enzymes thus enabling finer resolution, is a comprehensive and unbiased approach for determining chromatin conformation. Following fragmentation of crosslinked chromatin, the fragmented chromatin ends are repaired and biotinylated, proximity-ligation is performed, and the biotinylated DNA undergoes high-throughput paired-end sequencing. Therefore, chromatin interactions are queried on a genome-wide scale.\u003c/p\u003e \u003cp\u003eBroad-scale analysis of Hi-C experimental data in \u003cem\u003eAnopheles\u003c/em\u003e has been used to facilitate chromosome/genome assembly\u003csup\u003e\u003cspan additionalcitationids=\"CR35 CR36\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, inversion breakpoint mapping\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, and TAD structure determination\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e providing researchers with some understanding of the chromatin organization within \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes, but much remains unknown. Genome-wide maps of enhancers and chromatin accessibility in \u003cem\u003eAnopheles\u003c/em\u003e have been generated by us using self-transcribing active regulatory region sequencing (STARR-seq) and assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) approaches, respectively. Additionally, well-annotated genomes (PEST version AgamP4 for the 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e inversion form\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e and MOPTI version 2021-03-25 for the 2La inversion form\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e) are available for \u003cem\u003eAnopheles gambiae\u003c/em\u003e and \u003cem\u003ecoluzzii\u003c/em\u003e, respectively. The integration of genomic datasets describing candidate regulatory elements and chromatin accessibility with proximity ligation sequencing enables fine-scale exploration of chromatin interactions, including the identification of enhancer-promoter interactions, which has been achieved in other organisms\u003csup\u003e\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHere, we perform Micro-C and bulk RNA-sequencing on \u003cem\u003eAnopheles coluzzii\u003c/em\u003e hemocyte-like cells fixed for alternate forms of the large paracentric 2La inversion to characterize inversion-associated changes in chromatin conformation. With the availability of genome-wide datasets of genes\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e, candidate enhancers\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, and regions of open chromatin\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e coupled with the generation of proximity ligation sequencing data, we explore enhancer rewiring associated with the 2La inversion, prioritize a candidate regulatory element for malaria response immune gene LRIM1 that is located at a distance from the LRIM1 promoter region, and identify regulatory interaction hubs across the genome.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMicro-C and bulk RNA-sequencing of alternate 2La inversion karyotypes\u003c/h2\u003e \u003cp\u003eMicro-C and bulk RNA-sequencing libraries were generated from \u003cem\u003eAnopheles coluzzii\u003c/em\u003e hemocyte-like cells confirmed to be homozygous for the ancestral (2La) or derived (2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e) form of the large 2La inversion using a previously published molecular karyotyping assay\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e (SUA4.0\u0026thinsp;=\u0026thinsp;2La/2La\u003csup\u003e47, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e; Ag55\u0026thinsp;=\u0026thinsp;2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e/2L+\u003csup\u003ea47, 49, 50\u003c/sup\u003e). Raw reads for both cell line samples were mapped to PEST (2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e) reference genome version AgamP4 (VectorBase release 68) to facilitate sample comparison. PEST was the reference genome of choice because it is the most mature chromosome-level Anopheline genome assembly\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. When 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e/2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e samples are mapped to PEST (2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e reference genome), the resulting contact matrix of chromosome AgamP4_2L shows the classical pattern of a bright diagonal of nearby interactions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Generally, when a sample of one inversion karyotype is mapped to a reference genome of the opposite inversion karyotype, the regions near the two inversion breakpoints that interact appear as a butterfly contact pattern\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. Therefore, conversely, when 2La/2La samples are mapped to the 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e reference genome, a butterfly pattern emerges in chromosome AgamP4_2L, indicative of the 2La chromosomal inversion (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAg55 (2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e sample) contact matrices of chromosome AgamP4_2R revealed an irregular interaction structure, marked by the asterisks in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC. Approximate PEST positions of the three points of interactions are 19MB interacting with 26.6MB (consistent with the 2Rb inversion whose breakpoint positions are 19,023,925bp and 26,758,676bp\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e), 26.6MB interacting with 32MB (consistent with the 2Rc inversion whose breakpoint positions are 26,758,676bp and 31,488,544bp\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e), and 19MB interacting with 32MB (which is likely due to the two inverted regions being directly adjacent). This irregular interaction structure is in Ag55 samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, E) but not SUA4.0 samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD,F), and it is present when mapping Ag55 samples to either PEST (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC) or MOPTI (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE) reference genomes, indicating that PEST and MOPTI are colinear for 2R\u0026thinsp;+\u0026thinsp;\u003csup\u003eb\u003c/sup\u003e and 2R\u0026thinsp;+\u0026thinsp;\u003csup\u003ec\u003c/sup\u003e which is consistent with the literature\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Other known inversions on chromosome 2R are 2Rj\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e and 2Ru\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, whose PEST breakpoint coordinates are 3,262,186\u0026thinsp;\u0026minus;\u0026thinsp;15,750,717bp and 31,102,383\u0026thinsp;\u0026minus;\u0026thinsp;35,322,826bp, respectively. Both cell lines and both reference genomes are 2R\u0026thinsp;+\u0026thinsp;\u003csup\u003eju\u003c/sup\u003e/2R\u0026thinsp;+\u0026thinsp;\u003csup\u003eju\u003c/sup\u003e, evidenced by the lack of irregular interaction structure near 2Rj and 2Ru breakpoint coordinates (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC-F). We further investigated the Micro-C findings with the highest quality molecular karyotyping assays for 2Rb\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e, 2Rc\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e, 2Rj\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e, and 2Ru\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e on Ag55 and SUA4.0 cells. Ag55 was confirmed to be 2R\u0026thinsp;+\u0026thinsp;\u003csup\u003ej\u003c/sup\u003ebc+\u003csup\u003eu\u003c/sup\u003e/2R\u0026thinsp;+\u0026thinsp;\u003csup\u003ej\u003c/sup\u003ebc+\u003csup\u003eu\u003c/sup\u003e, and SUA4.0 was confirmed to be 2R+\u003csup\u003ejcbu\u003c/sup\u003e/ 2R+\u003csup\u003ejcbu\u003c/sup\u003e (Additional File 1, FigS1). The 2Rc inversion has been reported to be in almost perfect linkage disequilibrium with the inverted form of either 2Rb or 2Ru\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e, which is consistent with our cell line karyotypes. Contact matrices of Ag55 and SUA4.0 replicates mapped to PEST and MOPTI for all chromosomes are in Additional File 1, FigS2.\u003c/p\u003e \u003cp\u003eMultiHiCcompare\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e identifies differentially interacting regions between samples, regardless of distance between the interacting regions. The differential interactions that appear to span the entire length of the 2La inversion when 2La samples are mapped to PEST (2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e reference genome) are actually an artifact of mapping to a reference genome of alternative inversion karyotype and provide quality control evidence that Micro-C of our 2La and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e samples was successful (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG). MultiHiCcompare\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e identified 28,273 significant differentially interaction regions between 2La cells and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e cells on chromosome AgamP4_2L (10,508 are more frequent in 2La/2La calls and 17,765 are more frequent in 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e/2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e cells) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH). Of these, 18,861 (~\u0026thinsp;66.7% of differential interactions) have at least one anchor within the 2La inversion, which accounts for ~\u0026thinsp;43.8% of the AgamP4_2L chromosome. DESeq2\u003csup\u003e59\u003c/sup\u003e was used to identify 2,297 differentially expressed genes (DEGs) between 2La and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e cells genome-wide; 477 of these DEGs are on chromosome AgamP4_2L (205 are upregulated in 2La/2La cells, and 272 are upregulated in 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e/2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e cells) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI). The functional categories of the 477 DEGs on chromosomal AgamP4_2L were explored using the DAVID Functional Annotation Clustering tool\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. The top 4 clusters were comprised of genes related to glycosyltransferase, nucleotide metabolism, serpins, and immunity (Additional File 2, Table\u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). In the glycosyltransferase cluster, 6 of 7 genes (~\u0026thinsp;86%) that contribute to that cluster are upregulated in 2La cells. In the nucleotide metabolism cluster, 8 of 11 genes (~\u0026thinsp;73%) that contribute to that cluster are upregulated in 2La cells. In the serpins cluster, 5 of 5 genes (100%) that contribute to that cluster are upregulated in 2La cells. In the immunity cluster, 8 of 13 genes (~\u0026thinsp;62%) that contribute to that cluster are upregulated in 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e cells.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEvidence of novel enhancer rewiring associated with the 2La chromosomal inversion\u003c/h3\u003e\n\u003cp\u003eOne interesting consequence of chromosomal inversions is that they can seed the process of enhancer rewiring - the evolution of novel interactions between enhancers and their target genes due to the change in physical proximity caused by the inversion\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e. To better understand the impact that chromatin conformation changes resulting from the 2La inversion have on gene expression, a focused analysis over the 2La breakpoints was performed, coupling Micro-C and bulk RNA-seq data. Enhancers were defined as being detected in at least 2 of 3 replicates from a previously published STARR-seq experiment\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e (Additional File 3). This includes the 788 previously published STARR-seq identified enhancers on the 2L chromosome detected in all 3 replicates (3288 genome wide enhancers) as well as 274 additional STARR-seq identified enhancers on 2L that were detected in 2 of 3 replicates (1,237 genome wide) for a total of 1062 STARR-seq candidate enhancers across 2L. Promoters were defined as the 1000bp region upstream of the protein coding gene as described by VEuPathDB\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. These definitions of enhancers and promoters are used throughout all analyses. To identify evidence of novel enhancer rewiring associated with the 2La chromosomal inversion, three filters were applied to the 28,273 differential interactions between 2La and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e samples identified via multiHiCcompare\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e: 1) the interaction had to occur over the proximal or distal breakpoint of the 2La inversion, 2) one anchor of the interaction had to contain at least one enhancer while the other anchor had to contain the promoter region of at least one DEG, and 3) the enhancers and promoter regions of the DEGs must interact over a 2La breakpoint in both 2La and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e cell line samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Thirteen interactions met all three criteria, and they contained enhancers EP1, EP2 (located just outside of the proximal breakpoint), ED1, ED2, and ED3 (located just outside the distal breakpoint) and genes AGAP005781 (located inside the inversion on the proximal end in PEST), AGAP007066, AGAP007064, and AGAP007063 (located inside the inversion on the distal end in PEST) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Near the proximal end of the inversion, in the cell line homozygous for the 2La ancestral form, EP1 and EP2 interact with AGAP007066, and EP2 additionally interacts with AGAP007064 and AGAP007063 while in the cell line homozygous for the 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e derived form, EP1 and EP2 interact with AGAP005781. Near the distal end of the inversion, in the cell line homozygous for the 2La ancestral form, ED1, ED2, and ED3 interact with AGAP005781 while in the cell line homozygous for the 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e derived form, those same enhancers instead interact with AGAP007066, and ED1 additionally interacts with AGAP007064 and AGAP007063 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). For each of these enhancers with evidence of rewiring associated with the inversion, we confirmed enhancer activity by luciferase assay, measuring activity of the 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e allele in a 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e/2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e cellular background and the 2La allele in a 2La/2La cellular background (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). EP1, EP2, and ED3 overlap with regions of open chromatin supported by our previously published ATAC-seq peaks \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB) as well as FAIRE-seq peaks\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, H3K27ac ChIP-seq peaks\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, and ATAC-seq peaks\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e published from other labs, suggesting they are active enhancers across multiple tissues and cell types and in response to \u003cem\u003eP. falciparum\u003c/em\u003e challenge. A table of all 329 differential interactions spanning either the proximal or distal 2La inversion breakpoint is in Additional File 4. A complete list of raw interaction counts for the 13 interactions involved in enhancer rewiring, with their log\u003csub\u003e2\u003c/sub\u003eFoldChange and adjusted p-values, is in Additional File 5.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eMethods validation of distance-decay correction analysis on interaction frequencies\u003c/h3\u003e\n\u003cp\u003eBeyond finding evidence of enhancer rewiring across the breakpoints of an inversion associated with factors affecting malaria vector competence, we developed and validated analytical approaches allowing broader use of our high-resolution Micro-C data to better inform our understanding of endogenous gene regulation in mosquitoes. These analyses were focused on only 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e sample data because their 2La inversion karyotype matches that of the PEST 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e reference genome, thus facilitating analysis.\u003c/p\u003e \u003cp\u003eEnhancers are responsible for most regulated gene expression above basal levels in eukaryotes, but identifying candidate enhancers for a given target gene is difficult, especially because enhancers can interact at a distance either upstream or downstream from their target gene(s)\u003csup\u003e67\u003c/sup\u003e. Most commonly, candidate enhancers are inferred by nearest proximity to the target gene of interest. This approach is logical given that enhancers function through physical contact with promoters via transcription factor binding and because nearby chromatin regions interact more frequently, with interaction frequency decaying with distance. However, this nearest-gene approach ignores longer range interactions that can have strong phenotypic effect\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e. After normalizing interaction frequency for distance, proximity ligation sequencing identifies chromatin interactions that are enriched, thereby enabling prioritization of candidate enhancers based on increased interaction with a candidate target gene promoter. Using this approach in lieu of the simpler nearest-gene model can pinpoint physical evidence-based candidate regulatory elements worthy of further investigation.\u003c/p\u003e \u003cp\u003eUsing Micro-C data and distance-decay correction analysis, we examined chromatin interactions anchored on the promoter region of three \u003cem\u003eAnopheles\u003c/em\u003e genes from previously published work that validated the function of each gene\u0026rsquo;s candidate enhancer\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e: OVO (AGAP000114), KLF (AGAP007038), and RDL (AGAP006028). In all three cases, the promoter region and its previously identified candidate enhancer interact more frequently than expected given their distance (OVO: z-score 1.53, p-value 0.13 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA); KLF: z-score 2.23, p-value 0.03 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB); RDL: z-score 0.84, p-value 0.40 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC)). Furthermore, of the interactions between the promoter containing anchor and the anchor containing a STARR-seq enhancer, interactions with the previously characterized candidate enhancer for OVO, KLF and RDL had the highest z-score in all three cases.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eUnique application of distance-decay correction analysis on interaction frequencies to identify a novel candidate enhancer of LRIM1, an immune gene important to malaria response\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe chromatin interactions of Leucine-Rich Immune protein 1 (LRIM1) were explored because LRIM1 plays an important role in the malaria response within the mosquito\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. It is one component of the TEP1/LRIM1/APL1 protein complex that promotes \u003cem\u003ePlasmodium\u003c/em\u003e parasite killing\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Insight into the cis-regulation of LRIM1 could prove useful in the advent of novel malaria control methods. When anchoring on the 1000bp region upstream of LRIM1 as a proxy for its promoter, the 5kb enhancer-containing region with the highest z-score contains an enhancer with coordinates AgamP4_2L: 30142958\u0026ndash;30143475 (z-score 2.16, p-value 0.03), located 187,821bp downstream of the LRIM1 gene (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Additionally, this candidate enhancer overlaps with previously published ATAC peaks\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, FAIRE-seq peaks\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, and H3K27ac ChIP-seq peaks\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, suggesting that it is an active enhancer (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Activity of this candidate LRIM1 enhancer was confirmed by a luciferase assay conducted in both 2La/2La and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e/2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e cell lines (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Reciprocally, when interactions were instead anchored on the newly identified candidate LRIM1 enhancer, the 5kb region containing LRIM1\u0026rsquo;s promoter displayed a high interaction frequency for its distance (z-score 1.64), which is the 2nd highest z-score of 5kb regions containing a promoter (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). The 5kb promoter-containing region with the highest z-score contains the promoter for AGAP006346 (z-score 2.57). It is not uncommon for an enhancer to regulate transcription of multiple target genes. This observed reciprocity of enriched interaction further supports AgamP4_2L_30142958\u0026ndash;30143475 as a candidate enhancer of LRIM1. Note, p-values are not reported for candidate LRIM1 enhancer interactions because the residuals failed the Shapiro-Wilk test for normality; however, z-scores greater than 0 still represent interactions that are enriched given their distance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAdditional application of distance-decay correction analysis on interaction frequencies to identify target genes of 9 previously characterized enhancers on chromosome 2L\u003c/b\u003e \u003c/p\u003e \u003cp\u003eCapitalizing on the novel distance-decay correction analysis method, we identified the top candidate target genes of the 9 previously characterized enhancers within the malaria susceptibility locus on chromosome 2L.\u003csup\u003e44, 71\u003c/sup\u003e Top candidate target genes were identified by the highest z-score of promoter-containing interactions when anchored on each enhancer. The top candidate target gene(s), their associated z-score, and their approximate distance from the enhancer are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Because analysis is performed at 5kb resolution, the nearest possible candidate target gene identified in this analysis would be in the adjacent 5kb region to the enhancer. Top candidate target genes ranged from ~\u0026thinsp;4-564kb from each enhancer, demonstrating the variety of distances from which enhancers can act on their target gene(s).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eCandidate target genes based on highest interaction frequency from distance-decay correction analysis for previously characterized enhancers in the Plasmodium resistance island.\u003c/b\u003e The top candidate target gene(s) were determined for the enhancers characterized in Zmarlak-Feher et al. 2025 by identifying the genes in the promoter-containing interactions with the highest interaction frequency z-score. Distances between candidate target gene and enhancer ranged from ~\u0026thinsp;4-564kb.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnhancer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnhancer Coordinates\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTop candidate target gene(s)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInteraction z-score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eApproximate distance from enhancer\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENH_2L-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgamP4_2L: 20422499\u0026ndash;20423038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGAP005745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e~\u0026thinsp;248kb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENH_2L-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgamP4_2L: 20475573\u0026ndash;20476075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGAP005749, AGAP005750\u003c/p\u003e \u003cp\u003e\u003cem\u003e(both fall within same 5kb region)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e~\u0026thinsp;172kb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENH_2L-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgamP4_2L: 41873775\u0026ndash;41874329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGAP007058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e~\u0026thinsp;182kb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENH_2L-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgamP4_2L: 41822211\u0026ndash;41822718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGAP007044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e~\u0026thinsp;255kb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENH_2L-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgamP4_2L: 41809557\u0026ndash;41810116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGAP007032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e~\u0026thinsp;564kb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENH_2L-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgamP4_2L: 41732814\u0026ndash;41733335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGAP007046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e~\u0026thinsp;4kb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENH_2L-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgamP4_2L: 41729411\u0026ndash;41730122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGAP007032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e~\u0026thinsp;484kb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENH_2L-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgamP4_2L: 41716724\u0026ndash;41717232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGAP007040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e~\u0026thinsp;376kb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENH_2L-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgamP4_2L: 41623777\u0026ndash;41624334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGAP007047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e~\u0026thinsp;8kb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eChromatin interaction hubs are nearby enhancers and distant from promoters\u003c/h3\u003e\n\u003cp\u003eProximity ligation sequencing provides two metrics of chromatin interactions: interaction frequency (read counts per bin pair), which measures interaction strength, and partner count (number of distinct interacting partners per bin), which measures interaction breadth. While distance-decay correction analysis assesses interaction frequency of the interactions from a given anchor, we also wanted to identify and characterize chromatin interaction hubs by assessing partner count across chromosome AgamP4_2L. Chromatin interactions are clustered across the 2L \u003cem\u003eAnopheles\u003c/em\u003e chromosome generating hot spots/hubs of interaction: regions that interact with at least 102 other regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The minimum raw partner count for a given 5kb anchor across the 2L chromosome was 1, meaning that at least one region interacted with only 1 other region. The maximum raw partner count was 182, meaning that a region interacted with no more than 182 other regions. The average raw partner count was 63.85, with a median of 62. Chromatin interaction hubs were defined as the regions with the top 10% of partner counts (which for chromosome AgamP4_2L equated to interacting with \u0026ge;\u0026thinsp;102 other regions) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Detected interaction hubs are significantly closer to enhancers (p\u0026thinsp;=\u0026thinsp;0.001, z-score\u0026thinsp;\u0026minus;\u0026thinsp;7.38) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB) and significantly farther from promoters (p\u0026thinsp;=\u0026thinsp;0.001, z-score 27.17) than expected by random chance (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). These observations are consistent across all \u003cem\u003eAnopheles coluzzii\u003c/em\u003e autosomal arms (AgamP4_2R, AgamP4_3L, and AgamP4_3R) (Additional File 1, FigS3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe 2La chromosomal inversion is a large, monophyletic, polymorphic inversion in \u003cem\u003eAnopheles coluzzii\u003c/em\u003e and \u003cem\u003eA. gambiae\u003c/em\u003e mosquitoes, the two major malaria vectors in Sub-Saharan Africa where malaria morbidity and mortality are highest. This paracentric inversion is associated with an intrinsic resistance to malaria infection\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, among other phenotypes affecting the mosquito\u0026rsquo;s ability to transmit malaria\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan additionalcitationids=\"CR27 CR28 CR29\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. How the 2La inversion alters enhancer-mediated gene regulation remains unknown.\u003c/p\u003e \u003cp\u003eWhile chromatin conformation capture techniques have been used to study fine-scale chromatin interactions, such as enhancer-promoter interactions, in other organisms\u003csup\u003e\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, to date, these proximity ligation techniques have only been used in \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes for broader scale applications like chromosome assemblies\u003csup\u003e\u003cspan additionalcitationids=\"CR35 CR36\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, inversion breakpoint mapping\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, determining TAD structure\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, and broad-scale analysis of chromatin loops\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Our fine-scale exploration of chromatin interactions within \u003cem\u003eA. coluzzii\u003c/em\u003e hemocyte-like cells complements more broad-scale applications by identifying enhancer-promoter interactions involved in wiring/rewiring over 2La inversion breakpoints, utilizing proximity-ligation data to prioritize candidate enhancers, and identifying chromatin interaction hot spot enrichment near enhancers.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eTranscriptional differences\u003c/h2\u003e \u003cp\u003eIn total, 2,297 genes were differentially expressed between 2La/2La cells and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e/2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e cells, and 477 (21%) of those are on chromosome AgamP4_2L (21% of the mosquito genome). DAVID Functional Annotation Clustering analysis of the 477 DEGs identified clusters of genes with related function. Cluster 1 included genes related to glycosyltransferase, and UDP-glycosyltransferases have been reported to be associated with pyrethroid insecticide resistance in \u003cem\u003eAnopheles\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e. Cluster 2 included genes related to nucleotide metabolism. Many of these genes have roles in purine and pyrimidine salvage and synthesis, and purine-based metabolites have been implicated in signaling, immunity, and host-pathogen interactions across kingdoms\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e. Increases in the overall nucleotide pool have been reported 24 hours after bloodmeal\u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e. Cluster 3 included genes related to serpins, which are negative regulators of innate immune responses in insects\u003csup\u003e\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e. Cluster 4 included genes related to immunity. The 2La inversion has been reported to be associated with an intrinsic resistance to malaria infection with 2La/2La mosquitoes being more resistant\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo our knowledge, gene expression differences between unperturbed samples fixed for alternate forms of the 2La inversion have not been published. Microarray studies have been performed in 2La and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e homokaryotic mosquitoes under thermal stress to identify differentially expressed genes either in heat hardened 2La/2La or 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e/2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e \u003cem\u003eA. gambiae\u003c/em\u003e larvae\u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e or in comparisons of sex, environment aridity, 2La inversion karyotype, 2Rb inversion karyotype, or interactions of those factors in \u003cem\u003eA. gambiae\u003c/em\u003e adults\u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e. However, direct comparison to our data is not possible due to a variety of factors including minimal accessible data and lack of a direct comparison between 2La and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e samples.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEnhancer rewiring and the 2La inversion\u003c/h3\u003e\n\u003cp\u003eWe identified 13 differential interactions involved in enhancer rewiring across 2La inversion breakpoints, containing 5 candidate enhancer regions that interact with four different genes (AGAP005781, AGAP007066, AGAP007064, AGAP007063) in an inversion-specific manner. Using an independent computational method, PSYCHIC\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e, these results were confirmed. AGAP005781 is predicted to interact with an enhancer across the distal breakpoint in 2La fixed cells and across the proximal breakpoint in 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e fixed cells. Further, AGAP007066 interacts with an enhancer across the proximal breakpoint in 2La fixed cells. Little is known about the function of these four genes. AGAP005781 is a glycine C-acetyltransferase and has been documented as a predicted miR-276 target gene, supported by 2 out of 3 prediction algorithms\u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. miR-276 is a bloodmeal-induced protein that terminates the reproductive cycle\u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. AGAP007066 is tRNA-specific adenosine deaminase 3\u003csup\u003e65, 66\u003c/sup\u003e, and AGAP00763 is origin recognition complex subunit 4\u003csup\u003e65, 66\u003c/sup\u003e; neither has been further investigated in the literature. AGAP007064 is an unspecified product\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e and has been reported as being significantly enriched in \u003cem\u003eAnopheles gambiae\u003c/em\u003e salivary glands compare to whole larvae\u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e. Evidence suggests these genes are important to \u003cem\u003eAnopheles\u003c/em\u003e due to the association of their regulation with 2La inversion karyotype and the evolution of novel enhancer-promoter interactions.\u003c/p\u003e\n\u003ch3\u003eUtilizing interaction frequencies to prioritize candidate regulatory regions\u003c/h3\u003e\n\u003cp\u003ePrevious studies have queried the most proximal enhancer (AgamP4_2L: 30333431\u0026ndash;30334787) to LRIM1 as a candidate enhancer\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. However, application of a novel distance-normalized interaction frequency approach facilitated discovery of an LRIM1 candidate enhancer, located ~\u0026thinsp;188kb downstream from the promoter. Such a distance is not unreasonable for an enhancer-promoter interaction because others have reported long-range interactions of \u0026gt;\u0026thinsp;100kb in \u003cem\u003eDrosophila\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e, and \u003cem\u003eAnopheles coluzzii\u003c/em\u003e TADs sizes have been reported to be up to 1MB in size\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. This novel interaction frequency-based approach prioritizes a candidate LRIM1 enhancer over 7 STARR-seq identified candidate enhancers that are closer to the LRIM1 promoter region along the linear chromosome (5 upstream and 2 downstream) than the candidate regulatory region identified here (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eDespite its large physical distance from LRIM1 (AGAP006348, PEST positions 30329656\u0026ndash;30331296), this newly discovered candidate enhancer contains conserved sequence regions related to immune regulation. A ~\u0026thinsp;90bp region (PEST positions 30143151\u0026ndash;30143240) has high levels of sequence conservation (e values\u0026thinsp;\u0026lt;\u0026thinsp;4x10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e) amongst members of the \u003cem\u003eA. gambiae\u003c/em\u003e complex, two species most closely related to the \u003cem\u003eA. gambiae\u003c/em\u003e complex (\u003cem\u003eA. christyi and A. epiroticus\u003c/em\u003e), and more distantly related anopheline vectors of malaria (\u003cem\u003eA. stephensi\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eA. funestus\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e). Given that regulation of LRIM1 via both the Rel1 and Rel2 pathways has been described\u003csup\u003e\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u003c/sup\u003e, we examined this conserved sequence region for evidence of Rel1 (\u003cem\u003eDrosophila\u003c/em\u003e Dif) or Rel2 (\u003cem\u003eDrosophila\u003c/em\u003e Relish) TFBSs using MEME Suite\u003csup\u003e\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e\u003c/sup\u003e and available data from \u003cem\u003eDrosophila melanogaster\u003c/em\u003e in JASPAR\u003csup\u003e\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e\u003c/sup\u003e. Within this conserved region, 6 of the 8 species share significant sequence similarity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) with a TFBS for the Relish (\u003cem\u003eAnopheles\u003c/em\u003e Rel2) transcription factor at the 5\u0026rsquo; end of the sequence, and 5 of the 8 species show significant similarity with the Relish TFBS on the 3\u0026rsquo; end (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Additional File 1, FigS4). A query of the other NF-kB-like TFBS in \u003cem\u003eDrosophila\u003c/em\u003e, Dif (\u003cem\u003eAnopheles\u003c/em\u003e Rel1), shows 7 of the 8 species share significant similarity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) only at the 5\u0026rsquo; end (Additional File 1, FigS4). For all members of the \u003cem\u003eA. gambiae\u003c/em\u003e species complex as well as \u003cem\u003eA. christyi\u003c/em\u003e and \u003cem\u003eA. epiroticus\u003c/em\u003e, both Dif and Relish binding sites are significant while for \u003cem\u003eA funestus\u003c/em\u003e, only Dif is significant, and for \u003cem\u003eA. stephensi\u003c/em\u003e, only Relish is significant (Additional File 1, FigS4).\u003c/p\u003e \u003cp\u003eThe ~\u0026thinsp;180kb distance between the LRIM1 gene and the Micro-C-identified LRIM1 candidate enhancer is also conserved across 6 of the \u003cem\u003eAnopheles\u003c/em\u003e species tested, minimally 173,257bp in \u003cem\u003eA. coluzzii\u003c/em\u003e MOPTI to maximally 186,416bp in \u003cem\u003eA. gambiae\u003c/em\u003e PEST. It is impossible to determine the distance between LRIM1 and this candidate regulatory region in either \u003cem\u003eA. christyi\u003c/em\u003e or \u003cem\u003eA. epiroticus\u003c/em\u003e given that the sequences are present on distinct sequence contigs.\u003c/p\u003e \u003cp\u003eWhile cementing the relative importance of the newly discovered LRIM1 regulatory element will require additional work, it is only through proximity ligation assays like the Micro-C performed here that we are able to prioritize regulatory elements at a distance from the genes they regulate.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eChromatin Interaction Hubs\u003c/h2\u003e \u003cp\u003eThrough an examination of the distribution of chromatin interactions across the genome, we identified chromatin interaction hubs and characterized them as positively associated with enhancers and negatively associated with promoters. This finding is unsurprising as enhancers can act on multiple genes and allow for fine-tuning of gene expression, so an enhancer having contacts with many genomic regions enables the fine tuning of gene regulation in tissue-, time-, and stress responsive-specific ways. Conversely, we speculate that a promoter having contacts with many genomic regions likely does not provide significant benefit, and excess chromatin in its 3D proximity could interfere with transcription machinery. An independent method for identifying chromatin interaction hubs has been reported and utilized in primary human tissues, which models interaction counts with Poisson regression\u003csup\u003e\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u003c/sup\u003e. Briefly, for each 40kb bin of a genome-wide contact matrix, the total number of intra-chromosomal interactions within 15-200kb of each bin was calculated. Interactions were modeled using a Poisson distribution that corrected for biases of three factors: effective fragment length, GC content, and mappability. Residuals were calculated then converted into a z-score and -ln(p-value). Frequently Interacting Regions (FIREs) were defined as bins with a one-sided p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05, which equates to a -ln(p-value) \u0026gt;3\u003csup\u003e91\u003c/sup\u003e. Consistent with our results, FIREs occurred near active enhancers\u003csup\u003e\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e\u003c/sup\u003e. This supports the promiscuous behavior of enhancers by which one enhancer may have multiple target genes\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eHere, we utilize high-resolution measures of chromatin conformation alongside gene expression to characterize the impact of chromatin conformational changes associated with the 2La inversion on gene expression and 3D chromatin structure. Coupling chromatin conformation and gene expression results from 2La and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e \u003cem\u003eA. coluzzii\u003c/em\u003e hemocyte-like cell lines, we identify sets of genes and enhancers that differentially interact over inversion breakpoints, suggestive of enhancer rewiring and the novel evolution of enhancer-promoter interactions over inversion breakpoints. Further investigation into these enhancers/genes, or other genomic elements near inversion breakpoints, could provide insight into the differential phenotypes associated with the 2La inversion, including an intrinsic resistance to malaria infection\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e and differences in mosquito resting and biting behavior\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, aridity\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e and thermal tolerance\u003csup\u003e\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Additionally, knowledge of unique regulatory circuitry across inversion forms could help design vector control tools targeting mosquitoes of a given karyotype. Novel analytical approaches applied to our Micro-C data enable the identification and prioritization of interacting chromatin regions and a greater understanding of regulatory hot spots across the genome. These novel approaches allow fine-scale exploration of mosquito chromatin interactions and are broadly applicable across species for which Micro-C/Hi-C data are available.\u003c/p\u003e "},{"header":"METHODS","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003eCell culture\u003c/h2\u003e \u003cp\u003eHemocytes are innate immune cells that kill pathogens, including the malaria parasite, through phagocytosis, lysis, and melanization\u003csup\u003e\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e\u003c/sup\u003e. Two hemocyte-like \u003cem\u003eAnopheles coluzzii\u003c/em\u003e cell lines SUA4.0 (cell line homozygous for the 2La karyotype, will be referred to as 2La cells throughout)\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e and Ag55 (cell line homozygous for the 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e karyotype, will be referred to as 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e cells throughout)\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e were seeded at a density of 0.9x10^6 cells/mL in a T75 flask (three flasks per cell line per replicate) in antibiotic-free media (Insect Xpress (Lonza) for SUA 4.0, and Leibovitz\u0026rsquo;s L-15 Medium (Millipore Sigma) for Ag55). 48hr post-seeding, cells were washed with 1X PBS, scraped, and aliquots of ~\u0026thinsp;1\u0026nbsp;million cells were spun at 3,000g for 5min. Supernatants were removed and cell pellets flash frozen in liquid nitrogen and stored at -80C until shipment for bulk RNA-sequencing (Azenta, South Plainfield, NJ) or Micro-C (Dovetail Genomics, part of Cantata Bio, Scotts Valley, CA). Four biological replicates were submitted for RNA-seq with the three most similar RNA-seq replicates (as determined by PCA analysis, Additional File 1, FigS5) also submitted for Micro-C.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eRNA-seq\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003eRNA-sequencing library preparation and sequencing\u003c/h2\u003e \u003cp\u003eAzenta performed RNA extraction, strand-specific library preparation, and sequencing to a depth of ~\u0026thinsp;20\u0026nbsp;million paired-end reads per sample from flash frozen cell pellets of either SUA4.0 cells (2La) or Ag55 cells (2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e). Four biological replicates were performed for each cell line. Briefly, total RNA was extracted, and mRNA was enriched by Poly(A) selection. RNA integrity was assessed via TapeStation, and all samples had an RIN\u0026thinsp;\u0026ge;\u0026thinsp;9. After library preparation, sequencing was performed on an Illumina NovaSeq platform to generate 2x150bp paired end reads. 17.7\u0026ndash;18.9\u0026nbsp;million reads were obtained per sample.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eRead preprocessing alignment and quantification\u003c/h2\u003e \u003cp\u003eRaw reads were assessed for quality using FastQC\u003csup\u003e\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e\u003c/sup\u003e. All samples showed high per-base quality (\u0026ge;\u0026thinsp;90% bases above Q30), and all reads had a mean quality score\u0026thinsp;\u0026gt;\u0026thinsp;35. Adapter sequences and low-quality bases were trimmed using Trimmomatic-0.38\u003csup\u003e96\u003c/sup\u003e with parameters ILLUMINACLIP:TruSeq3-PE.fa:3:30:10:2:keepBothReads LEADING:3 TRAILING:3 MINLEN:26. Post-trimming quality was reassessed using FastQC. Cleaned reads were aligned to PEST version AgamP4 (VectorBase release 68)\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e using STAR (v2.7.10b)\u003csup\u003e\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e\u003c/sup\u003e, resulting in 90.26%-92.18% uniquely mapped reads. Annotation was based on VectorBase-68_AgambiaePEST.gff. Gene-level read counts were obtained using featureCounts (v2.0.6)\u003csup\u003e98\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eDifferential expression analysis\u003c/h2\u003e \u003cp\u003eRaw counts data were loaded into R, then normalized and analyzed using DESeq2 (v1.46.0)\u003csup\u003e59\u003c/sup\u003e. Prefiltering removed genes with fewer than 10 reads total, summed across all 8 samples being compared. DEGs between hemocyte-like cells homozygous for the 2La karyotype and those homozygous for 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e were defined as having a |log\u003csub\u003e2\u003c/sub\u003efoldchange| \u0026ge;1 and adjusted p-value\u0026thinsp;\u0026le;\u0026thinsp;0.05. All RNA-seq reads are accessible at PRJNA1439337.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eFunctional enrichment analysis\u003c/h2\u003e \u003cp\u003eThe 477 differentially expressed genes between 2La and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e samples on chromosome AgamP4_2L were assessed for functional gene annotation clustering using the DAVID 6.8 Functional Annotation Clustering tool using the DAVID Knowledgebase v2024q4\u003csup\u003e60, 61\u003c/sup\u003e. Classification Stringency was set to Medium (default), and EASE threshold was set to 1.3 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eMicro-C\u003c/h2\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003eMicro-C library preparation and sequencing\u003c/h2\u003e \u003cp\u003eBecause 2\u0026ndash;3 biological replicates is standard for Hi-C/Micro-C, we performed PCA analysis on our four RNA-seq samples to determine the three most similar biological replicates (Additional File 1, FigS5). Biological replicates 1, 2, and 3 were submitted to Dovetail Genomics for Micro-C library preparation and sequencing. Briefly, the chromatin was fixed with disuccinimidyl glutarate (DSG) and formaldehyde in the nucleus. The cross-linked chromatin was then digested in situ with micrococcal nuclease (MNase). Following digestion, the cells were lysed with SDS to extract the chromatin fragments, and the chromatin fragments were bound to Chromatin Capture Beads. Next, the chromatin ends were repaired and ligated to a biotinylated bridge adapter followed by proximity ligation of adapter-containing ends. After proximity ligation, the crosslinks were reversed, the associated proteins were degraded, and the DNA was purified then converted into a sequencing library using Illumina-compatible adaptors. Biotin-containing fragments were isolated using streptavidin beads prior to PCR amplification. The library was sequenced on an Illumina NovaSeq platform to generate 201\u0026ndash;234\u0026nbsp;million 2 x 150bp read pairs per sample. Samples were 3 biological replicates each of hemocyte-like cells homozygous for the 2La karyotype and hemocyte-like cells homozygous for the 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e karyotype for a total of 6 samples. After sequencing, we obtained\u0026thinsp;~\u0026thinsp;100\u0026nbsp;million unique mappable reads for each replicate. Non-duplicate \u003cem\u003ecis\u003c/em\u003e read pairs accounted for \u0026gt;\u0026thinsp;40% of total read pairs for all replicates, passing the QC metric for deep sequencing for Dovetail Genomics. Library statistics for Micro-C data are available in Additional File 6. All Micro-C data is available at PRJNA1439337.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eMicro-C Analysis\u003c/h2\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eMicro-C read processing and mapping\u003c/h2\u003e \u003cp\u003eRead processing and mapping was performed based on the workflow developed by Dovetail Genomics (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dovetail-analysis.readthedocs.io/en/latest/\u003c/span\u003e\u003cspan address=\"https://dovetail-analysis.readthedocs.io/en/latest/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Briefly, fastq files were aligned to the \u003cem\u003eA. gambiae\u003c/em\u003e PEST reference genome (VectorBase-68_AgambiaePEST_Genome.fasta) or \u003cem\u003eA. coluzzii\u003c/em\u003e MOPTI reference genome (VectorBase-68_AcoluzziiMOPTI_Genome.fasta) using BWA-MEM (v.0.7.17)\u003csup\u003e\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e\u003c/sup\u003e with options \u0026minus;\u0026thinsp;5SP -T0 -t16 for each replicate independently. Pairtools parse (v.1.0.3)\u003csup\u003e100\u003c/sup\u003e with options --min-mapq 40 --walks-policy 5unique --max-inter-align-gap 30 --nproc-in 8 --nproc-out 8 was used to find ligation events. Parsed pairs were sorted and PCR duplicates were removed using pairtools sort with --nproc16 and pairtools dedup with --nproc-in 8 --nproc-out 8 --mark-dups, respectively. Pairtools split with --nproc-in 8 --nproc-out 8 generated a .pairs file and a .bam file, which was sorted and indexed using samtools (v1.20)\u003csup\u003e\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eGeneration of Contact Matrices\u003c/h2\u003e \u003cp\u003eContact matrices were generated using Juicer Tools (v1.22.01)\u003csup\u003e\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u003c/sup\u003e with -Xmx48000m -Djava.awt.headless=true --threads 16. Contact matrices were visualized using Juicebox\u003csup\u003e\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e, \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eDetermining inversion karyotype of cell line samples\u003c/h2\u003e \u003cp\u003eGenomic DNA was isolated from SUA4.0 (2La/2La hemocyte-like cells) and Ag55 (2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e/2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e hemocyte-like cells). The 2La inversion karyotype of each cell line was confirmed using a previously published PCR assay for 2La molecular karyotyping\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. The two cell lines were selected for their known alternate 2La inversion karyotypes. The karyotypes of known chromosome 2R inversions for which there are molecular assays (2Rj\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e, 2Rb\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e, 2Rc\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e, and 2Ru\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e) were also determined for each cell line, confirming Micro-C results. Both SUA4.0 and Ag55 are 2R\u0026thinsp;+\u0026thinsp;\u003csup\u003ej\u003c/sup\u003e/2R\u0026thinsp;+\u0026thinsp;\u003csup\u003ej\u003c/sup\u003e and 2R\u0026thinsp;+\u0026thinsp;\u003csup\u003eu\u003c/sup\u003e/2R\u0026thinsp;+\u0026thinsp;\u003csup\u003eu\u003c/sup\u003e. They differ in 2Rb and 2Rc inversion karyotype where SUA4.0 are 2R\u0026thinsp;+\u0026thinsp;\u003csup\u003eb\u003c/sup\u003e/2R\u0026thinsp;+\u0026thinsp;\u003csup\u003eb\u003c/sup\u003e and 2R\u0026thinsp;+\u0026thinsp;\u003csup\u003ec\u003c/sup\u003e/2R\u0026thinsp;+\u0026thinsp;\u003csup\u003ec\u003c/sup\u003e while Ag55 are 2Rb/2Rb and 2Rc/2Rc (Additional File 1, FigS1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eUsing multiHiCcompare to identify interacting regions\u003c/h2\u003e \u003cp\u003eMultiHiCcompare\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e was used for both within-group replicate analysis and comparative analysis of Micro-C datasets. Both analyses used make_hicexp and cyclic_loess functions to normalize and identify chromatin interactions supported by all three biological replicates from each cell line while comparative analysis additionally used the hic_exactTest function to identify differentially interacting regions between cell lines. MultiHiCcompare was selected as the program of choice for its comprehensive, unbiased approach. Chromatin loops are defined as extrusions of DNA through the ring-shaped cohesion protein that are arrested by CTCF protein binding to CTCF binding sites on the DNA\u003csup\u003e\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e\u003c/sup\u003e. In general, chromatin loop callers identify regions of increased interaction frequency compared to background or neighboring regions, using either algorithms on the contact matrix counts or on the visual image created by contact matrices\u003csup\u003e\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e, \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e\u003c/sup\u003e. Because chromatin loops are better understood in humans and mice and loop formation in insects may be slightly different, involving other CTCF-like insulator proteins like Beaf-32\u003csup\u003e107\u0026ndash;109\u003c/sup\u003e, CP190\u003csup\u003e109, 110\u003c/sup\u003e, and Chromator\u003csup\u003e\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e, \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e\u003c/sup\u003e, we found existing chromatin loop callers to be biased in their identification of interacting regions and produce a limited number of chromatin interactions. For example, the loop caller Mustache\u003csup\u003e\u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e\u003c/sup\u003e, which identifies a higher number of published ChIA-PET and HiChIP loops as compared to other loop callers HiCCUPS and SIP, identified 648 interactions on chromosome AgamP4_2L in 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e cells at 5kb resolution. In contrast, multHiCcompare\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e identified 309,139 interactions on chromosome AgamP4_2L in 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e cells at 5kb resolution. MultiHiCcompare identified 470 of 648 interactions that Mustache identified (72.5%), and the 178 interactions identified by Mustache that were not identified by multiHiCcompare all had average raw read counts\u0026thinsp;\u0026le;\u0026thinsp;5, which multiHiCcompare considers low average read count and intentionally filters out. If the low read count filter is removed, the overlap of Mustache-identified interactions also identified by multiHiCcompare increases from 72.5% to 100%. In addition to identifying the same interactions as Mustache, multiHiCcompare has a number of other advantages including (1) it takes multiple biological replicates as input data to identify interacting regions, and (2) it does not implement a distance cut off (as evidenced in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG). Given these advantages, we used multiHiCcompare for an agnostic identification of chromatin interactions.\u003c/p\u003e \u003cp\u003eFor comparative analysis, three biological replicates of 2La samples were compared to three biological replicates of 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e samples, both mapped to PEST (2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e reference genome) version Agam_P4 (VectorBase release 68)\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. Within-group replicate analysis was performed only on 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e samples mapped to PEST to facilitate analysis. Contact matrices generated by Juicer Tools\u003csup\u003e\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u003c/sup\u003e were converted into sparse files for each chromosome independently using straw (v0.1.0)\u003csup\u003e104\u003c/sup\u003e. R package multiHiCcompare (v1.24.0)\u003csup\u003e58\u003c/sup\u003e was used to import the sparse files of Micro-C replicates at 5kb resolution, perform cyclic loess normalization, and detect interaction differences, if applicable. The hicexp object was created using the default parameters, except for remove.regions\u0026thinsp;=\u0026thinsp;NULL because a non-human genome was used. Default parameters zero.p and Amin filtered out low interaction counts, thus only keeping interactions supported by all biological replicates. Zero.p\u0026thinsp;=\u0026thinsp;0.8 removed interactions in which\u0026thinsp;\u0026gt;\u0026thinsp;80% of samples had a raw interaction count of 0, and Amin\u0026thinsp;=\u0026thinsp;5 removed interactions in which the raw interaction counts across the biological replicates being analyzed averaged\u0026thinsp;\u0026le;\u0026thinsp;5. Normalization was performed across the biological replicates using the cyclic_loess function with default parameters. For comparative analysis, the hic_exactTest function was used with default parameters. Differentially interacting regions were defined as regions where |log\u003csub\u003e2\u003c/sub\u003efoldchange| \u0026ge;1, log counts per million\u0026thinsp;\u0026ge;\u0026thinsp;0.5, and adjusted p-value\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eIdentifying differentially interacting regions over inversion breakpoints\u003c/h2\u003e \u003cdiv id=\"Sec28\" class=\"Section4\"\u003e \u003ch2\u003eDefining the 2La breakpoint\u003c/h2\u003e \u003cp\u003ePositions of 2La inversion breakpoints in PEST version AgamP4 (VectorBase release 68) were determined using PCR primers for molecular karyotyping of 2La and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e chromosomes\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Primer DPCross5\u003csup\u003e46\u003c/sup\u003e blasts to PEST positions 20,528,072\u0026thinsp;\u0026minus;\u0026thinsp;20,528,094bp; therefore 20,528,072bp is used as the proximal breakpoint. Primer 27A2\u003csup\u003e46\u003c/sup\u003e blasts to PEST positions 42,165,607\u0026thinsp;\u0026minus;\u0026thinsp;42,165,626bp; therefore 42,165,626bp is used as the distal breakpoint. All mapping was to the PEST 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e reference genome. For visualization, the schematic of the 2La chromosome in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB was shown on the MOPTI 2La reference genome background (version 2021-03-25, VectorBase release 68). MOPTI breakpoints were assigned to a region analogous to PEST based on the position of genes internal vs external to each inversion breakpoint. MOPTI position 86,510,662bp is used for the proximal breakpoint, and 107,557,222bp is used for the distal breakpoint.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eDefining differential interactions over inversion breakpoints containing enhancer-promoter pairs\u003c/h2\u003e \u003cp\u003e28,273 differential interactions between 2La and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e samples on chromosome AgamP4_2L were determined from multiHiCcompare exactTest\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e (see above). Three filters were applied to these AgamP4_2L differential interactions to find evidence of enhancer rewiring associated with the 2La inversion: 1) the interaction had to occur over a 2La breakpoint, 2) one anchor had to contain at least 1 enhancer and the other anchor had to contain the promoter region (defined as the 1000bp region upstream of the protein coding gene) for at least one DEG, and 3) each enhancer and DEG promoter had to interact over a 2La breakpoint in both 2La and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e samples. For filtering criteria (1), an interaction was defined as occurring over an inversion breakpoint if the breakpoint coordinate fell between the outermost coordinates of the two interaction anchors. There were 153 differential interactions over the proximal breakpoint (using PEST position 20528073bp), and 183 differential interactions over the distal breakpoint (using PEST position 42165625bp). Seven interactions occur over both the proximal and distal breakpoint, i.e. the interaction spans across the entire inversion and both breakpoints. All 7 of these interactions are present in 2La samples and absent in 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e samples; therefore, they are likely an artifact of mapping 2La samples to a 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e reference genome. These seven interactions were not double counted to arrive at the 329 total unique differential interactions occurring over a 2La inversion breakpoint, and they were filtered out in the downstream criteria. For filtering criteria (2), an enhancer was defined as being detected in at least 2 of 3 replicates from a previously published STARR-seq experiment\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, and DEGs were defined as having a |log\u003csub\u003e2\u003c/sub\u003efoldchange| \u0026ge;1 and adjusted p-value\u0026thinsp;\u0026le;\u0026thinsp;0.05 from our RNA-seq data. Promoters of the DEGs were defined as the 1000bp region upstream of the protein coding gene as described by VEuPathDB\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. A bed file of enhancers detected in at least 2 of 3 replicates from a previously published STARR-seq experiment\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e is found in Additional File 3. This list is inclusive of the previously published 3288 STARR-seq \u003cem\u003eAnopheles\u003c/em\u003e enhancers\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Of the 329 total unique differential interactions occurring over a 2La inversion breakpoint, 17 interactions contained at least 1 enhancer and at least one DEG promoter in each anchor (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Because of our interest in identifying enhancer rewiring, filtering criteria (3) required that each enhancer and DEG promoter interacted over a breakpoint in both 2La and 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e cells. This resulted in 13 interactions that satisfied all criteria, involving 5 candidate enhancers that interact with the promoter region of four different genes in an inversion-specific manner (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). A table of all 329 differential interactions and their reason for inclusion/exclusion are found in Additional File 4.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eComparing STARR-seq peaks with other published datasets\u003c/h3\u003e\n\u003cp\u003ePublished open chromatin and epigenetics marker information was extracted from previously published work, and STARR-seq peaks were compared to identify active enhancers as previously described\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Briefly, peaks within +/- 1500bp of a given STARR-seq peak were considered to be overlapping. Candidate STARR-seq peaks were compared to ATAC-seq data from 4a-3A hemocyte-like cells from our previous work\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, FAIRE-seq data from 4a-3B hemocyte-like cells\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, ChIP-seq data from blood-fed and \u003cem\u003ePlasmodium\u003c/em\u003e-infected mosquitoes\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, and ATAC-seq data from midgut and salivary gland tissues of \u003cem\u003ePlasmodium\u003c/em\u003e-infected mosquitoes\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003ePredicting enhancer-promoter interactions using PSYCHIC\u003c/h2\u003e \u003cp\u003ePSYCHIC\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e was run on a MacBook Pro using Python2.7 to enable python scripts to interact with MATLAB. PSYCHIC was run according to its GitHub instructions (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/dhkron/PSYCHIC\u003c/span\u003e\u003cspan address=\"https://github.com/dhkron/PSYCHIC\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). For input, PSYCHIC takes a Hi-C contact matrix, promoter bed file, and a series of other information including resolution of the contact matrix, interaction distance cutoff, chromosome name, and chromosome size. The output from PSYCHIC is a bed file of predicted enhancer-promoter interactions with coordinates of the putative enhancer, the name of its candidate target gene, distance of the gene to putative enhancer, FDR, p-value, number of expected interactions, and number of observed interactions. Using a p-value cutoff of \u0026le;\u0026thinsp;0.05, we identified putative enhancer-promoter pairs in our 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e samples mapped to PEST 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e reference genome version AgamP4 (VectorBase release 68) and our 2La samples mapped to MOPTI 2La reference genome version 2021-03-25 (VectorBase release 68). We filtered to identify enhancer-DEG promotor pairs occurring over a 2La breakpoint, with PEST positions 20,528,072bp as the proximal breakpoint and 42,165,626bp as the distal breakpoint and MOPTI positions 86,510,662bp as the proximal breakpoint and 107,557,222bp as the distal breakpoint, as described in above methods.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003eCalculating distance-normalized interaction frequencies to correct for distance-decay\u003c/h2\u003e \u003cp\u003eChromatin interactions are expected to decay with physical distance because regions that are physically closer will inherently interact more frequently. To evaluate whether chromatin interactions are enriched, one must first understand the null expectation for interactions given the distance between two anchors. To achieve this, we calculated a local null distribution of expected interaction frequency for each distance by performing linear regression analysis on log\u003csub\u003e10\u003c/sub\u003e-transformed distance and log\u003csub\u003e10\u003c/sub\u003e-transformed average interaction frequency for all interactions with a given anchor. With a null distribution, we were able to calculate residuals, a z-score, and a corresponding two-tailed p-value to indicate how frequent or infrequent an interaction is relative to other interactions of that same distance. A Shapiro-Wilk test was performed to confirm a normal distribution of residuals prior to calculating a p-value for each z-score. If a p-value is not reported for a z-score (as was the case for candidate LRIM1 enhancer interactions), it is because the residuals failed the Shapiro-Wilk test for normality. However, even without a p-value, a z-score\u0026thinsp;\u0026gt;\u0026thinsp;0 still indicates that an interaction occurs more frequently than expected for its distance. These analytical and statistical methods enabled prioritization of enhancers or promoters for future investigation based on the z-score/p-value of their interaction. As above, an enhancer was defined as being detected in at least 2 of 3 replicates from a previously published STARR-seq experiment\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. The 1000bp region upstream of the protein coding gene as described by VEuPathDB is used as a proxy for a gene\u0026rsquo;s promoter. For visualization in Integrative Genomics Viewer (IGV)\u003csup\u003e\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e\u003c/sup\u003e, z-scores were plotted as a heatmap, and the colorimetric scale in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC was set to red for a z-score\u0026thinsp;\u0026ge;\u0026thinsp;2 (p-value\u0026thinsp;\u0026le;\u0026thinsp;0.0455), white for a z-score\u0026thinsp;=\u0026thinsp;0 (p-value\u0026thinsp;=\u0026thinsp;1), and blue for a z-score \u0026le;-2 (p-value\u0026thinsp;\u0026le;\u0026thinsp;0.0455).\u003c/p\u003e \u003cdiv id=\"Sec33\" class=\"Section3\"\u003e \u003ch2\u003eMeasurement of enhancer activity by luciferase reporter assays\u003c/h2\u003e \u003c/div\u003e \u003cdiv id=\"Sec34\" class=\"Section3\"\u003e \u003ch2\u003eCloning of candidate enhancers\u003c/h2\u003e \u003cp\u003eAs previously described\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, candidate enhancer regions were PCR amplified from genomic DNA isolated from either SUA4.0 (2La) or Ag55 (2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e) cells. PCR reactions consisted of 10ng template DNA, 1X High-Fidelity PCR Master Mix with HF (Thermo), and 0.5uM of each forward and reverse primer. Cycling conditions were initial denaturation at 98C for 30s, 30 cycles of a 10s denaturation at 98C, 55-62C annealing temperature for 30s, and a 45s extension at 72C, followed by a final 10min extension at 72C. Resulting PCR products were either restriction enzyme cloned or Gateway cloned into a Firefly luciferase reporter vector pGL-Gateway-DSCP (AddGene, vector ID# 71506). Ligation products were transformed into OneShot OmniMax 2T1 Phage-Resistant Cells (Invitrogen), then grown overnight, plasmid purified, and sequenced. Amplification primers for candidate enhancers can be found in Additional File 5. Note these primers are designed to be inclusive of published enhancers\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e; therefore, the amplicons are slightly larger than the STARR-seq published enhancer. Sequences of cloned alleles can be found in Additional File 7.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eLipid based transfection and luciferase reporter assays\u003c/h3\u003e\n\u003cp\u003e \u003cem\u003eAnopheles coluzzii\u003c/em\u003e SUA4.0 or Ag55 cells were seeded at 2.5x10^4 cells/well in 65ul in a 96 well plate. Cells were agitated on a MixMate (Eppendorf) for 30s at 300rpm for even distribution. Following a 24hr incubation period, lipid-based transfections were performed using Lipofectamine3000 (Invitrogen). Cells were transfected with two plasmids (1) the pGL-Gateway-DSCP (described above) carrying a single amplified fragment of the candidate enhancer upstream of a firefly luciferase gene and (2) a renilla control vector pRL-ubi-63E (AddGene, #74280). Plasmids were transfected at a ratio of 1:5 (renilla:firefly). Plates were agitated again for 30s at 300rpm on a MixMate (Eppendorf) and incubated for 24h at 27C. The Dual-Glo Luciferase Assay System (Promega) was used for luciferase assays, according to supplier instructions. Measurements were recorded on the GloMax Discover (Promega) at 25\u0026deg;C. All test plates contained cells transfected with control plasmid constructs: a negative control fragment, which was a size-matched fragment within intron 1 of AGAP007058 (DLX), and a highly active positive control enhancer peak nearby AGAP008980\u003csup\u003e70\u003c/sup\u003e. All samples were run in 6-fold technical replication within a single plate and across at least two independent plates for at least two biological replicates. Firefly luciferase measurements were normalized to renilla measurements from the same well. These measurements were then expressed relative to the firefly/renilla mean for the negative control on the same plate. An unpaired t-test comparing the mean enhancer activity with the mean of background (the negative control\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e) was the statistical test used to validate enhancer function.\u003c/p\u003e\n\u003ch3\u003eIdentifying chromatin interaction hubs\u003c/h3\u003e\n\u003cp\u003eWithin-group replicate analysis by multiHiCcompare\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e identified interacting regions supported by 3 biological replicates of 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e cells. To identify chromatin interaction hubs, partner count (number of distinct interacting partners per bin) was determined for each 5kb anchor region by counting the number of unique partner anchors it had. Chromatin interaction hubs were defined as the 5kb regions with the top 10% of partner counts (which for chromosome AgamP4_2L equated to interacting with \u0026ge;\u0026thinsp;102 other regions). Results were visualized in IGV\u003csup\u003e\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec37\" class=\"Section2\"\u003e \u003ch2\u003ePermutation testing using RegioneR\u003c/h2\u003e \u003cp\u003eTo determine whether the identified interaction hubs were closer to or farther from various genomic elements than expected by random chance, permutation testing was performed using R package regioneR (v1.38.0)\u003csup\u003e113\u003c/sup\u003e. The reference genome was manually set to the \u003cem\u003eA. gambiae\u003c/em\u003e PEST reference genome version AgamP4 (VectorBase release 68) for the chromosome of interest. We used the permTest meanDistance function to evaluate the statistical significance of the average distance between interaction hub (top 10% of interacting regions, described above) and enhancer (as defined as a genomic fragment detected in at least 2 of 3 replicates from a previous STARR-seq experiment\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e). To establish the null distribution and determine whether the identified interaction hubs were closer to or farther from enhancers than expected by random chance, the genomic coordinates of the interaction hubs were randomized using the randomizeRegions function. 1000 permutation tests were performed to generate the null distribution. RegioneR calculated the observed mean distance, the distribution of mean distances under randomization, z-score, and empirical p-value. Results were visualized using the plot function. Analysis was repeated replacing enhancers with promoters. The promoter bed file contained the 1000bp region upstream of each protein coding gene as described by VEuPathDB.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDEG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edifferentially expressed gene\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDIR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edifferentially interacting region\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIGV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntegrative Genomics Viewer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTFBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etranscription factor binding site\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTAD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etopologically associating domain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics Approval and consent to participate\u003c/strong\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eAll authors have seen and approved the manuscript, and it has not been accepted for publication elsewhere.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study received financial support to KST National Institutes of Health, # AI188600 and to MMR from National Institutes of Health, NIAID #AI145999 and #AI191531.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eKST, KDV, MMR designed the research. 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Bioinformatics. 2015;32(2):289\u0026ndash;91. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/bioinformatics/btv562\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btv562\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Biology](https://bmcbiol.biomedcentral.com/)","snPcode":"12915","submissionUrl":"https://submission.springernature.com/new-submission/12915/3","title":"BMC Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Anopheles, gene regulation, proximity-ligation, Micro-C, inversion biology","lastPublishedDoi":"10.21203/rs.3.rs-9213027/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9213027/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMalaria parasite transmission by \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes remains a worldwide health burden, and understanding factors underlying natural vector susceptibility would inform rational design of vector control. The 2La chromosomal inversion segregates in the major vectors of human malaria, \u003cem\u003eAnopheles coluzzii\u003c/em\u003e and \u003cem\u003egambiae\u003c/em\u003e, and is associated with natural variation for malaria susceptibility, though underlying mechanisms are unknown. Here, we characterize alterations of chromatin conformation and gene expression induced by the two 2La inversion allelic forms, the ancestral 2La and the derived 2L\u0026thinsp;+\u0026thinsp;\u003csup\u003ea\u003c/sup\u003e forms. We employ several novel applications of proximity ligation sequencing to refine the mosquito regulatory genome to a new level of resolution.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe analyzed the 2La inversion breakpoints in \u003cem\u003eA. coluzzii\u003c/em\u003e hemocyte-like cell lines for the allelic 2La inversion karyotypes. Utilizing a novel combination of Micro-C and bulk RNA-sequencing, our results detected transcriptional enhancers and genes that are rewired by the physical rearrangement caused by the inversion. Through development and application of novel distance-normalized interaction frequency analysis on Micro-C data, we identify a novel candidate enhancer for LRIM1, a major parasite antagonist immune gene within the 2La inversion. Our genome-wide analysis examines the distribution of all chromatin interactions across the genome and identifies chromatin interaction hubs that are positively associated with enhancers.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis multifaceted approach yields high resolution characterization of gene \u003cem\u003ecis\u003c/em\u003e-regulation within \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes, and specifically within the context of a malaria-associated paracentric inversion. Additionally, development and validation of analytical methods for proximity ligation data allow fine scale exploration of mosquito chromatin interactions and are broadly applicable across species.\u003c/p\u003e","manuscriptTitle":"The Anopheles gambiae 2La chromosomal inversion influences chromatin organization and 3D landscape of genes related to malaria transmission","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-09 18:45:52","doi":"10.21203/rs.3.rs-9213027/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-30T14:01:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-27T15:44:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"59512054852783615263422104064084361717","date":"2026-04-21T07:28:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"133117327635904658887971379550207903714","date":"2026-04-03T13:13:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-02T21:22:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-25T19:46:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-25T06:23:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Biology","date":"2026-03-24T14:05:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Biology](https://bmcbiol.biomedcentral.com/)","snPcode":"12915","submissionUrl":"https://submission.springernature.com/new-submission/12915/3","title":"BMC Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a5f67aa7-db6e-42df-a2f1-e78b0abe5ef8","owner":[],"postedDate":"April 9th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-04-30T14:01:36+00:00","index":20,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-09T18:45:52+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-09 18:45:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9213027","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9213027","identity":"rs-9213027","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}