Additional file 4: Figure S3. of Inferring synteny between genome assemblies: a systematic evaluation

Synteny blocks in C. elegans vs. 100kb fragmented C. elegans. Chromosomes are separated into panels labelled with Roman numerals. The Y axis stands for categories of distribution. Synteny blocks defined by five detection programs: DAGchainer (red), i-ADHoRe (yellow), MCScanX (green), SynChro (light blue), and Satsuma (blue) are drawn as rectangles. Gene distribution is represented by the bottom smaller rectangles in burgundy. The X axis is the chromosome position. (PNG 322 kb

Additional file 2: Table S1. of Inferring synteny between genome assemblies: a systematic evaluation

Quantification of synteny coverage and error rate. (DOCX 1 kb

Additional file 7: Table S2. of Inferring synteny between genome assemblies: a systematic evaluation

Gene ontology (GO) enrichment analysis of C. briggsae genes in synteny break between C. elegans and 100kb fragmented C. briggsae assemblies. Significant GO terms that appeared in the top 10 ranks of enrichment test either in the original comparison or after assemblies were fragmented, are displayed. The original rank, median rank and number of occurrences that reached top 10 in 100 replications are shown for each GO term. GO terms not belonging to original assembly but reached top 10 after fragmentation are shaded in red. GO:0043066, which was in the original top 10 rank but failed to reach top 10 in all of 100 replications, is shaded in deep red. GO terms belonging to original assembly and remained top 10 after fragmentation are shaded in green. All GO categories were significant after Fisher exact test and have adjusted p-value < 0.01. (DOCX 1 kb

Additional file 1: Figure S1. of Inferring synteny between genome assemblies: a systematic evaluation

Synteny coverage for different numbers of minimum anchors using DAGchainer. The Y axis shows synteny coverage (%). The X axis is the number of minimum anchors needed to identify a synteny block from 2 to 8. The 4 colorsare 4 combinations of synteny detection among species: C. elegans vs. C. elegans (CEvsCE, green), C. elegans vs. C. briggsae (CEvsCBG, orange), S. ratti vs. S. ratti (SRvsSR, blue) and S. ratti vs. S. stercoralis (SRvsSS, purple). (PNG 112 kb

Additional file 6: Figure S5. of Inferring synteny between genome assemblies: a systematic evaluation

Synteny blocks in C. elegans vs. C. briggsae. Chromosomes are separated into panels labelled with Roman numeral. The Y axis stands for categories of distribution. Synteny blocks defined by five detection programs: DAGchainer (red), i-ADHoRe (yellow), MCScanX (green), SynChro (light blue), and Satsuma (blue) are drawn as rectangles. The bottom four categories are orthologs between the two species assigned by Opscan (OP; burgundy) and OrthoFinder (OF; purple), and we further categorized orthologs into 1 to 1 orthology (1-1) or many to many orthology (N-N). The X axis is the chromosome position. (PNG 404 kb

Additional file 3: Figure S2. of Inferring synteny between genome assemblies: a systematic evaluation

Synteny blocks in C. elegans vs. 1Mb fragmented C. elegans. Chromosomes are separated into panels labelled with Roman numerals. The Y axis stands for categories of distribution. Synteny blocks defined by five detection programs: DAGchainer (red), i-ADHoRe (yellow), MCScanX (green), SynChro (light blue), and Satsuma (blue) are drawn as rectangles. Gene distribution is represented by the bottom smaller rectangles in burgundy. The X axis is the chromosome position. (PNG 286 kb

Additional file 8: Table S3. of Inferring synteny between genome assemblies: a systematic evaluation

Assembly statistics among Caenorhabditis species and Strongyloides species including ALLMAPS results. (DOCX 1 kb

Table1_Unravelling the determinants of human health in French Polynesia: the MATAEA project.docx

BackgroundFrench Polynesia is a French overseas collectivity in the Southeast Pacific, comprising 75 inhabited islands across five archipelagoes. The human settlement of the region corresponds to the last massive migration of humans to empty territories, but its timeline is still debated. Despite their recent population history and geographical isolation, inhabitants of French Polynesia experience health issues similar to those of continental countries. Modern lifestyles and increased longevity have led to a rise in non-communicable diseases (NCDs) such as obesity, diabetes, hypertension, and cardiovascular diseases. Likewise, international trade and people mobility have caused the emergence of communicable diseases (CDs) including mosquito-borne and respiratory diseases. Additionally, chronic pathologies including acute rheumatic fever, liver diseases, and ciguatera, are highly prevalent in French Polynesia. However, data on such diseases are scarce and not representative of the geographic fragmentation of the population.ObjectivesThe present project aims to estimate the prevalence of several NCDs and CDs in the population of the five archipelagoes, and identify associated risk factors. Moreover, genetic analyses will contribute to determine the sequence and timings of the peopling history of French Polynesia, and identify causal links between past genetic adaptation to island environments, and present-day susceptibility to certain diseases.MethodsThis cross-sectional survey is based on the random selection of 2,100 adults aged 18–69 years and residing on 18 islands from the five archipelagoes. Each participant answered a questionnaire on a wide range of topics (including demographic characteristics, lifestyle habits and medical history), underwent physical measurements (height, weight, waist circumference, arterial pressure, and skin pigmentation), and provided biological samples (blood, saliva, and stool) for biological, genetic and microbiological analyses.ConclusionFor the first time in French Polynesia, the present project allows to collect a wide range of data to explore the existence of indicators and/or risk factors for multiple pathologies of public health concern. The results will help health authorities to adapt actions and preventive measures aimed at reducing the incidence of NCDs and CDs. Moreover, the new genomic data generated in this study, combined with anthropological data, will increase our understanding of the peopling history of French Polynesia.Clinical trial registrationhttps://clinicaltrials.gov/, identifier: NCT06133400.</p