The Medaka Inbred Kiyosu-Karlsruhe (MIKK) Panel

Overview

Journal Genome Biol

Specialties Biology
Genetics

Date 2022 Feb 22

PMID 35189950

Authors

Tomas Fitzgerald

Ian Brettell

Adrien Leger

Nadeshda Wolf

Natalja Kusminski

Jack Monahan

Carl Barton

Cathrin Herder

Narendar Aadepu

Jakob Gierten

Clara Becker

Omar T Hammouda

Eva Hasel

Colin Lischik

Katharina Lust

Natalia Sokolova

Risa Suzuki

Erika Tsingos

Tinatini Tavhelidse

Thomas Thumberger

Philip Watson

Bettina Welz

Nadia Khouja

Kiyoshi Naruse

Ewan Birney

Joachim Wittbrodt

Felix Loosli

Affiliations

Soon will be listed here.

Abstract

Background: Unraveling the relationship between genetic variation and phenotypic traits remains a fundamental challenge in biology. Mapping variants underlying complex traits while controlling for confounding environmental factors is often problematic. To address this, we establish a vertebrate genetic resource specifically to allow for robust genotype-to-phenotype investigations. The teleost medaka (Oryzias latipes) is an established genetic model system with a long history of genetic research and a high tolerance to inbreeding from the wild.

Results: Here we present the Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel: the first near-isogenic panel of 80 inbred lines in a vertebrate model derived from a wild founder population. Inbred lines provide fixed genomes that are a prerequisite for the replication of studies, studies which vary both the genetics and environment in a controlled manner, and functional testing. The MIKK panel will therefore enable phenotype-to-genotype association studies of complex genetic traits while allowing for careful control of interacting factors, with numerous applications in genetic research, human health, drug development, and fundamental biology.

Conclusions: Here we present a detailed characterization of the genetic variation across the MIKK panel, which provides a rich and unique genetic resource to the community by enabling large-scale experiments for mapping complex traits.

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