Analysis of Autozygosity Using Whole-Genome Sequence Data of Full-Sib Families in Pikeperch (Sander lucioperca)

Abstract

Pikeperch (Sander lucioperca) has emerged as a high value species to the aquaculture industry. However, its farming techniques are at an early stage and its production is often performed without a selective breeding program, potentially leading to high levels of inbreeding. In this study, we identified and characterized autozygosity based on genome-wide runs of homozygosity (ROH) on a sample of parental and offspring individuals, determined effective population size (Ne), and assessed relatedness among parental individuals. A mean of 2,235 ± 526 and 1,841 ± 363 ROH segments per individual, resulting in a mean inbreeding coefficient of 0.33 ± 0.06 and 0.25 ± 0.06 were estimated for the progeny and parents, respectively. Ne was about 12 until four generations ago and at most 106 for 63 generations in the past, with varying genetic relatedness amongst the parents. This study shows the importance of genomic information when family relationships are unknown and the need of selective breeding programs for reproductive management decisions in the aquaculture industry.

An empirical test of the estimation of historical effective population size using Drosophila melanogaster

“…For the analyses carried out so far, most of them have suggested declines in N e at different times and extents. This is something expected, as most analyses have been carried out for populations which are known to have declined in size for different reasons, or for populations that have entered a selection program, such as those maintained in aquaculture settings (e.g., turbot, seabream and seabass, Saura et al, 2021; coho salmon, Martinez et al, 2022; or pikeperch, De Los Ríos‐Pérez et al, 2022). One exception is the historical expansions detected by Magnier et al (2022) for Mayotte and Madagascar cattle breeds started about 80 generations ago, and coincident with the arrival of the Europeans to the islands and the massive use of cattle.…”

“…The method of Santiago et al (2020) has now been applied to different species, particularly in the last year, including insects, such as honeybees (Sang et al, 2022); birds, such as Black Robin (von Seth et al, 2022); fishes, such as turbot, seabream and seabass (Saura et al, 2021), Baltic herring (Atmore et al, 2022), pikeperch (De Los Ríos‐Pérez et al, 2022), coho salmon (Martinez et al, 2022), catfish (Coimbra et al, 2023) and sailfish (Ferrette et al, 2023); wild mammals, such as grey wolf (Pacheco et al, 2022), killer whales (Kardos et al, 2023), sika deer (Iijima et al, 2023), scimitar‐horned oryx (Humble et al, 2023) and gorilla (Alvarez‐Estape et al, 2023); humans (Bird et al, 2023); domestic species, such as pigs (Krupa et al, 2022), cattle (Jin et al, 2022; Magnier et al, 2022), sheep (Djokic et al, 2023; Drzaic et al, 2022), horse (Criscione et al, 2022) and chicken (Gao et al, 2023; Liu et al, 2023); plants, such as walnut (Ding et al, 2022); crustaceans, such as Daphnia (Wersebe & Weider, 2023) and fungi (Singh et al, 2021). As suggested by Santiago et al (2020), the method is generally reliable for about 200 generations in the past, although the software provides values up to about 600 generations.…”

Impact of population structure in the estimation of recent historical effective population size by the software GONE

“…The possibility of estimating changes in population size in the recent past is particularly useful in livestock species, for which the start of breeding programs may imply substantial changes in N e . To date, this software has been applied to various breeds of pigs [ 20 ], cattle [ 21 , 22 ], sheep [ 23 , 24 ], horses [ 25 ] and chickens [ 26 , 27 ], and fish species such as turbot, seabream and seabass [ 16 ], Baltic herring [ 28 ], pikeperch [ 29 ], coho salmon [ 30 ], catfish [ 31 ] and sailfish [ 32 ].…”