Thermal adaptation rather than demographic history drives genetic structure inferred by copy number variants in a marine fish

AbstractIncreasing evidence shows that structural variants represent an overlooked aspect of genetic variation with consequential evolutionary roles. Among those, copy number variants (CNVs), including duplicated genomic region and transposable elements (TEs) may contribute to local adaptation and/or reproductive isolation among divergent populations. Those mechanisms suppose that CNVs could be important drivers of population genetic structure, whose study is generally restricted to the use of SNPs. Taking advantage of recent developments allowing CNV analysis from RAD-seq data, we investigated how variation in fitness-related traits, local thermal conditions and demographic history are associated with CNVs, and how subsequent copy number variation drives population genetic structure in a marine fish, the capelin (Mallotus villosus). We collected 1536 DNA samples from 35 sampling sites in the north Atlantic Ocean and identified 6620 CNVs. We found associations between CNVs and the gonadosomatic index, suggesting that duplicated regions could affect female fitness by modulating oocyte production. We also detected 105 CNV candidates associated with water temperature, among which 20% corresponded to genomic regions located within the sequence of protein-coding genes, suggesting local adaptation to cold water by means of gene amplification. We also identified 175 CNVs associated with the divergence of three parapatric glacial lineages, of which 24% were located within protein-coding genes, which might contribute to genetic incompatibilities and ultimately, reproductive isolation. Lastly, our analyses unveiled a hierarchical, complex CNV population structure determined by temperature and local geography, that was very different from that inferred based on SNPs in a previous study. Our findings underscore the complementarity of those two types of markers in population genomics studies.

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CONGA: Copy number variation genotyping in ancient genomes and low-coverage sequencing data

10.1101/2021.12.17.473150 ◽

2021 ◽

Author(s):

Arda Soylev ◽

Sevim Seda Cokoglu ◽

Dilek Koptekin ◽

Can Alkan ◽

Mehmet Somel

Keyword(s):

Copy Number ◽

Demographic History ◽

Copy Number Variants ◽

Purifying Selection ◽

Gene Pools ◽

Nucleotide Polymorphisms ◽

Sequencing Data ◽

Duplication Events ◽

Highly Correlated ◽

Genome Analyses

To date, ancient genome analyses have been largely confined to the study of single nucleotide polymorphisms (SNPs). Copy number variants (CNVs) are a major contributor of disease and of evolutionary adaptation, but identifying CNVs in ancient shotgun-sequenced genomes is hampered by (a) most published genomes being <1x coverage, (ii) ancient DNA fragments being typically <80 bps. These characteristics preclude state-of-the-art CNV detection software to be effectively applied to ancient genomes. Here we present CONGA, an algorithm tailored for genotyping deletion and duplication events in genomes with low depths of coverage. Simulations show that CONGA can genotype deletions and duplications >1 Kbps with F-scores >0.77 and >0.82, respectively at >=0.5x. Further, down-sampling experiments using published ancient BAM files reveal that >1 Kbps deletions could be genotyped at F-score >0.75 at >=1x coverage. Using CONGA, we analyse deletion events at 10,018 loci in 56 ancient human genomes spanning the last 50,000 years, with coverages 0.4x-26x. We find inter-individual genetic diversity measured using deletions and SNPs to be highly correlated, suggesting that deletion frequencies broadly reflect demographic history. We also identify signatures of purifying selection on deletions, such as an excess of singletons compared to those in SNPs. CONGA paves the way for systematic studies of drift, mutation load, and adaptation in ancient and modern-day gene pools through the lens of CNVs.

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Understanding Schizophrenia: Genetic Causes and Treatment

Current Neuropsychiatry and Clinical Neuroscience Reports ◽

10.33702/cncnr.2019.1.1.2 ◽

2019 ◽

Vol 1 (1) ◽

pp. 6-12

Author(s):

Fatima Javeria ◽

Shazma Altaf ◽

Alishah Zair ◽

Rana Khalid Iqbal

Keyword(s):

Copy Number ◽

Drug Targets ◽

Disease Risk ◽

Mental Disease ◽

Copy Number Variants ◽

Aminobutyric Acid ◽

Epigenetic Mechanisms ◽

Gamma Aminobutyric Acid ◽

Wide Range ◽

Severe Mental Disease

Schizophrenia is a severe mental disease. The word schizophrenia literally means split mind. There are three major categories of symptoms which include positive, negative and cognitive symptoms. The disease is characterized by symptoms of hallucination, delusions, disorganized thinking and speech. Schizophrenia is related to many other mental and psychological problems like suicide, depression, hallucinations. Including these, it is also a problem for the patient’s family and the caregiver. There is no clear reason for the disease, but with the advances in molecular genetics; certain epigenetic mechanisms are involved in the pathophysiology of the disease. Epigenetic mechanisms that are mainly involved are the DNA methylation, copy number variants. With the advent of GWAS, a wide range of SNPs is found linked with the etiology of schizophrenia. These SNPs serve as ‘hubs’; because these all are integrating with each other in causing of schizophrenia risk. Until recently, there is no treatment available to cure the disease; but anti-psychotics can reduce the disease risk by minimizing its symptoms. Dopamine, serotonin, gamma-aminobutyric acid, are the neurotransmitters which serve as drug targets in the treatment of schizophrenia. Due to the involvement of genetic and epigenetic mechanisms, drugs available are already targeting certain genes involved in the etiology of the disease.

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