Biology subjects

Cocco, A.

Publications and source records attributed to Cocco, A..

2 recordsLinked to original sources

bioRxiv2025

Whole genome sequencing reveals how plasticity and genetic differentiation underlie sympatric morphs of Arctic charr

Salmonids have a remarkable ability to form sympatric morphs after postglacial colonization of freshwater lakes. These morphs often exhibit differences in morphology, feeding, and spawning behaviour. Here we explore the genetics of morph differentiation by establishing a high-quality, annotated reference genome for the Arctic charr and use this as a resource for population genomic analysis of morphs from two Norwegian and two Icelandic lakes. The four lakes represent the spectrum of genetic differentiation between morphs from one lake with no genetic differentiation between morphs, implying phenotypic plasticity only, to two lakes with locus-specific genetic differentiation, implying incomplete reproductive isolation, and one lake with strong genome-wide divergence consistent with complete reproductive isolation. As many as 12 putative inversions ranging from 0.45 to 3.25 Mbp in size segregated among the four morphs present in one lake, Thingvallavatn, and these contributed significantly to the genetic differentiation among morphs. None of the putative inversions was found in any of the other lakes, but there were cases of partial haplotype sharing in similar morph contrasts in other lakes. The results are consistent with a highly polygenic basis of morph differentiation with limited genetic parallelism between lakes. The results support a model where morph differentiation is usually first established due to phenotypic plasticity that results in niche expansion and separation, followed by gradual development of reproductive isolation and locus-specific differentiation and eventually complete reproductive isolation and genome-wide divergence. A major explanation for salmonids ability to diversify into multiple sympatric morphs is likely the genome complexity caused by their ancient whole genome duplication that enhances evolvability.

evolutionary biology↗

bioRxiv2024

A Machine Learning Framework to Identify the Correlates of Disease Severity in Acute Arbovirus Infection

Most viral diseases display a variable clinical outcome due to differences in virus strain virulence and/or individual host susceptibility to infection. Understanding the biological mechanisms differentiating a viral infection displaying severe clinical manifestations from its milder forms can provide the intellectual framework toward therapies and early prognostic markers. This is especially true in arbovirus infections, where most clinical cases are present as mild febrile illness. Here, we used a naturally occurring vector-borne viral disease of ruminants, bluetongue, as an experimental system to uncover the fundamental mechanisms of virus-host interactions resulting in distinct clinical outcomes. As with most viral diseases, clinical symptoms in bluetongue can vary dramatically. We reproduced experimentally distinct clinical forms of bluetongue infection in sheep using three bluetongue virus (BTV) strains (BTV-1IT2006, BTV-1IT2013 and BTV-8FRA2017). Infected animals displayed clinical signs varying from clinically unapparent, to mild and severe disease. We collected and integrated clinical, haematological, virological, and histopathological data resulting in the analyses of 332 individual parameters from each infected and uninfected control animal. We subsequently used machine learning to identify the key viral and host processes associated with disease pathogenesis. We identified five different fundamental processes affecting the severity of bluetongue: (i) virus load and replication in target organs, (ii) modulation of the host type-I IFN response, (iii) pro-inflammatory responses, (iv) vascular damage, and (v) immunosuppression. Overall, our study using an agnostic machine learning approach, can be used to prioritise the different pathogenetic mechanisms affecting the disease outcome of an arbovirus infection.

microbiology↗