Integration of host-pathogen functional genomics data into the chromosome-level genome assembly of turbot (Scophthalmus maximus)

Non-synonymous variation and protein structure of candidate genes associated with selection in farm and wild populations of turbot (Scophthalmus maximus)

“…Pseudogene identification in the turbot genome using the vast functional information coming from the AQUA-FAANG project 87 will improve our ability to discriminate pseudogenes, resulting in a more refined list of NSVs. The second most important drop (from ~ 10,000 to ~ 1200) was related to previous functional information (differentially expressed genes in response to pathogen challenges or growth) or association (close to QTL for growth and resistance to pathologies) studies in farm populations 28,31 or with signals of selection related to environmental www.nature.com/scientificreports/ variables (temperature, salinity) in the wild across its distribution range 30 . The broad genomic information in turbot facilitated the targeting of this subset of NSVs on candidate genes under selection.…”

“…Population genetics criteria included: (i) discard SNPs deviated from Hardy–Weinberg proportions (P < 0.01); and (ii) remove tri-allelic SNPs. From this broad NSVs map, we performed additional filtering to focus on the main traits putatively associated with selection in wild or farm populations where previous information was available to choose a final manageable set of SNPs for validation: (i) select the most relevant candidate genes related to growth, osmoregulation and resistance to pathologies crossing previous literature, mostly on fishes, with previous QTL and functional (differentially expressed genes, DEG) data in turbot 28 , 29 , 31 ; (ii) identifying suggestive genes close to markers associated with signatures of selection (< 500 kb) 13 , 14 , 30 ; (iii) discarding deleterious variants from previous information in other species for the same genes available in public repositories (PROVEAN software 59 ; (iv) selecting the most diverse SNP per locus (higher MAF: minimum allele frequency). The conservation of the substituted residues in the 18 selected turbot protein variants was examined by blasting against the corresponding proteins in other teleost species available at NCBI ( https://www.ncbi.nlm.nih.gov/ ).…”

“…This information was integrated with previously reported QTL-associated markers, candidate genes and outlier loci related to natural or artificial selection, and a robust framework on selection signatures across the turbot genome was obtained 30 . Furthermore, functional data on resistance to the main industrial pathogens obtained from the main immune organs have been comparatively assessed and integrated with previous signatures of selection across the turbot genome 31 . The broad information gathered in this species, both in wild and farm populations, make it a suitable candidate for assessing the relevance of the different sources of genetic variation on turbot adaptation to different scenarios.…”

Multiomics uncovers the epigenomic and transcriptomic response to viral and bacterial stimulation in turbot

“…Functional annotation of the turbot transcriptome has been performed against high-quality reference genomes (Figueras et al, 2016; Maroso et al, 2018; Xu et al, 2020; Martinez et al, 2021), including for immune-organs stimulated with viruses (Diaz-Rosales et al, 2012), bacteria (Millán et al, 2011; Libran-Pérez et al, 2022) and parasites (Pardo et al, 2012; Robledo et al, 2014; Ronza et al, 2016; Valle et al, 2020). Candidate genes for disease resistance have been further explored by mapping differentially expressed genes (DEGs) within QTL regions (Martínez, 2016; Saura et al, 2019; Aramburu et al, 2023). However, limited attention has been given to non-coding regulatory elements, beyond a recent analysis of chromatin accessibility focussed on early development (Guerrero-Peña et al, 2023).…”

“…The head kidney has been targeted in all previous functional genomics studies in turbot investigating pathogen responses (Millán et al, 2011; Díaz-Rosales et al, 2012; Pardo et al, 2012; Robledo et al, 2014; Ronza et al, 2016; Librán-Pérez et al, 2022; Aramburu et al, 2023), due to its central role in fish immunity (Mokhtar et al, 2023). Head kidney is a key lymphoid organ in most marine fishes and, analogous to the mammalian bone marrow, responsible for the production of high leukocyte diversity, including B-lymphocytes, early-stage T-lymphocytes, as well myeloid cells such as granulocytes and monocytes/macrophages (Klosterhoff et al, 2015; Geven et al, 2017; Chen et al, 2022).…”