Genome wide screening of candidate genes for improving piglet birth weight using high and low estimated breeding value populations

Placental Transcriptome Analysis in Connection with Low Litter Birth Weight Phenotype (LBWP) Sows

It is possible to identify sub-populations of sows in every pig herd that consistently give birth to low birth weight (BW) piglets, irrespective of the litter size. A previous study from our group demonstrated that placental development is a main factor affecting the litter birth weight phenotype (LBWP) in sows, thereby impacting the BW of entire litters, but the biological and molecular pathways behind this phenomenon are largely unknown. The aim of this study was to investigate the differential gene expression in placental tissues at day 30 of gestation between low LBWP (LLBWP) vs. high LBWP (HLBWP) sows from a purebred Large White maternal line. Using mRNA sequencing, we found 45 differentially expressed genes (DEGs) in placental tissues of LLBWP and HLBWP sows. Furthermore, (GO) enrichment of upregulated DEGs predicted that there were two biological processes significantly related to cornification and regulation of cell population proliferation. To better understand the molecular interaction between cell proliferation and cornification, we conducted transcriptional factor binding site (TFBS) prediction analysis. The results indicated that a highly significant TFBS was located at the 5' upstream of all four upregulated genes (CDSN, DSG3, KLK14, KRT17), recognized by transcription factors EGR4 and FOSL1. Our findings provide novel insight into how transcriptional regulation of two different biological processes interact in placental tissues of LLBWP sows.

Utilizing Variants Identified with Multiple Genome-Wide Association Study Methods Optimizes Genomic Selection for Growth Traits in Pigs

Improving the prediction accuracies of economically important traits in genomic selection (GS) is a main objective for researchers and breeders in the livestock industry. This study aims at utilizing potentially functional SNPs and QTLs identified with various genome-wide association study (GWAS) models in GS of pig growth traits. We used three well-established GWAS methods, including the mixed linear model, Bayesian model and meta-analysis, as well as 60K SNP-chip and whole genome sequence (WGS) data from 1734 Yorkshire and 1123 Landrace pigs to detect SNPs related to four growth traits: average daily gain, backfat thickness, body weight and birth weight. A total of 1485 significant loci and 24 candidate genes which are involved in skeletal muscle development, fatty deposition, lipid metabolism and insulin resistance were identified. Compared with using all SNP-chip data, GS with the pre-selected functional SNPs in the standard genomic best linear unbiased prediction (GBLUP), and a two-kernel based GBLUP model yielded average gains in accuracy by 4 to 46% (from 0.19 ± 0.07 to 0.56 ± 0.07) and 5 to 27% (from 0.16 ± 0.06 to 0.57 ± 0.05) for the four traits, respectively, suggesting that the prioritization of preselected functional markers in GS models had the potential to improve prediction accuracies for certain traits in livestock breeding.

Genetic regulation and variation of expression of miRNA and mRNA transcripts in fetal muscle tissue in the context of sex, dam and variable fetal weight

BACKGROUND

Impaired skeletal muscle growth in utero can result in reduced birth weight and pathogenesis of intrauterine growth restriction. Fetal and placental growth is influenced by many factors including genetic, epigenetic and environmental factors. In fact, the sex and genotype of the fetus itself, as well as the mother providing it with a suitable environment, influence the growth of the fetus. Hence, our goal was to decipher and elucidate the molecular pathways of developmental processes mediated by miRNAs and mRNAs in fetal muscle tissue in the context of sex, dam, and fetal weight. Therefore, we analyse the variation of miRNA and mRNA expression in relation to these factors. In addition, the coincidence of genetic regulation of these mRNAs and miRNAs, as revealed by expression quantitative trait loci (eQTL) analyses, with sex-, mother- and weight-associated expression was investigated.

METHODS

A three-generation pig F2 population (n = 118) based on reciprocal crossing of German Landrace (DL) and Pietrain (Pi) was used. Genotype information and transcriptomic data (mRNA and miRNA) from longissimus dorsi muscle (LDM) of pig fetuses sampled at 63 days post-conception (dpc) were used for eQTL analyses.

RESULTS

The transcript abundances of 13, 853, and 275 probe-sets were influenced by sex, dam and fetal weight at 63 dpc, respectively (FDR < 5%). Most of significant transcripts affected by sex were located on the sex chromosomes including KDM6A and ANOS1 or autosomes including ANKS1B, LOC100155138 and miR-153. The fetal muscle transcripts associated with fetal weight indicated clearer metabolic directions than maternally influenced fetal muscle transcripts. Moreover, coincidence of genetic regulation (eQTL) and variation in transcript abundance due to sex, dam and fetal weight were identified.

CONCLUSIONS

Integrating information on eQTL, sex-, dam- and weight-associated differential expression and QTL for fetal weight allowed us to identify molecular pathways and shed light on the basic biological processes associated with differential muscle development in males and females, with implications for adaptive fetal programming.

In Utero Fetal Weight in Pigs Is Regulated by microRNAs and Their Target Genes

Impaired skeletal muscle growth in utero can result in reduced birth weight and poor carcass quality in pigs. Recently, we showed the role of microRNAs (miRNAs) and their target genes in prenatal skeletal muscle development and pathogenesis of intrauterine growth restriction (IUGR). In this study, we performed an integrative miRNA-mRNA transcriptomic analysis in longissimus dorsi muscle (LDM) of pig fetuses at 63 days post conception (dpc) to identify miRNAs and genes correlated to fetal weight. We found 13 miRNAs in LDM significantly correlated to fetal weight, including miR-140, miR-186, miR-101, miR-15, miR-24, miR-29, miR-449, miR-27, miR-142, miR-99, miR-181, miR-199, and miR-210. The expression of these miRNAs decreased with an increase in fetal weight. We also identified 1315 genes significantly correlated to fetal weight at 63 dpc, of which 135 genes were negatively correlated as well as identified as potential targets of the above-listed 13 miRNAs. These miRNAs and their target genes enriched pathways and biological processes important for fetal growth, development, and metabolism. These results indicate that the transcriptomic profile of skeletal muscle can be used to predict fetal weight, and miRNAs correlated to fetal weight can serve as potential biomarkers of prenatal fetal health and growth.

Prenatal Skeletal Muscle Transcriptome Analysis Reveals Novel MicroRNA-mRNA Networks Associated with Intrauterine Growth Restriction in Pigs

Intrauterine growth restriction (IUGR) occurs in 15–20% of pig neonates and poses huge economic losses to the pig industry. IUGR piglets have reduced skeletal muscle growth, which may persist after birth. Prenatal muscle growth is regulated by complex molecular pathways that are not well understood. MicroRNAs (miRNAs) have emerged as the main regulators of vital pathways and biological processes in the body. This study was designed to identify miRNA–mRNA networks regulating prenatal skeletal muscle development in pigs. We performed an integrative miRNA–mRNA transcriptomic analysis in longissimus dorsi muscle from IUGR fetuses and appropriate for gestational age (AGA) fetuses at 63 days post conception. Our data showed that 47 miRNAs and 3257 mRNAs were significantly upregulated, and six miRNAs and 477 mRNAs were significantly downregulated in IUGR compared to AGA fetuses. Moreover, 47 upregulated miRNAs were negatively correlated and can potentially target 326 downregulated genes, whereas six downregulated miRNAs were negatively correlated and can potentially target 1291 upregulated genes. These miRNA–mRNA networks showed enrichment in biological processes and pathways critical for fetal growth, development, and metabolism. The miRNA–mRNA networks identified in this study can potentially serve as indicators of prenatal fetal growth and development as well as postnatal carcass quality.

Estimation of Variance Components and Genomic Prediction for Individual Birth Weight Using Three Different Genome-Wide SNP Platforms in Yorkshire Pigs

Simple Summary

The individual birth weight (IBW) of pigs is an important trait regarding its relevance to mortality at weaning, sow prolificacy, and growth performance. This study investigates the variance component estimation, informative window regions, and the efficiency of genomic predictions associated with IBW traits in Yorkshire pigs. The low heritability (0.13) is estimated on the basis of a full model including individual genetic, sow genetic, and common environmental effects. Two common window regions of the genome are identified under three different genotyping platforms found within the ARAP2 and TSN genes concerning the IBW trait. The genomic prediction ability is improved using deregressed estimated breeding values including parental information as a response variable despite Bayesian methods and genotyping platforms for the IBW trait in Korean Yorkshire pigs.

Abstract

This study estimates the individual birth weight (IBW) trait heritability and investigates the genomic prediction efficiency using three types of high-density single nucleotide polymorphism (SNP) genotyping panels in Korean Yorkshire pigs. We use 38,864 IBW phenotypic records to identify a suitable model for statistical genetics, where 698 genotypes match our phenotypic records. During our genomic analysis, the deregressed estimated breeding values (DEBVs) and their reliabilities are used as derived response variables from the estimated breeding values (EBVs). Bayesian methods identify the informative regions and perform the genomic prediction using the IBW trait, in which two common significant window regions (SSC8 27 Mb and SSC15 29 Mb) are identified using the three genotyping platforms. Higher prediction ability is observed using the DEBV-including parent average as a response variable, regardless of the SNP genotyping panels and the Bayesian methods, relative to the DEBV-excluding parent average. Hence, we suggest that fine-mapping studies targeting the identified informative regions in this study are necessary to find the causal mutations to improve the IBW trait’s prediction ability. Furthermore, studying the IBW trait using a genomic prediction model with a larger genomic dataset may improve the genomic prediction accuracy in Korean Yorkshire pigs.

The Landscape of Genomic Imprinting at the Porcine SGCE/PEG10 Locus from Methylome and Transcriptome of Parthenogenetic Embryos

In mammals, imprinted genes often exist in the form of clusters in specific chromosome regions. However, in pigs, genomic imprinting of a relatively few genes and clusters has been identified, and genes within or adjacent to putative imprinted clusters need to be investigated including those at the SGCE/PEG10 locus. The objective of this study was to, using porcine parthenogenetic embryos, investigate imprinting status of genes within the genomic region spans between the COL1A2 and ASB4 genes in chromosome 9. Whole-genome bisulfite sequencing (WGBS) and RNA sequencing (RNA-seq) were conducted with normal and parthenogenetic embryos, and methylome and transcriptome were analyzed. As a result, differentially methylated regions (DMRs) between the embryos were identified, and parental allele-specific expressions of the SGCE and PEG10 genes were verified. The pig imprinted interval was limited between SGCE and PEG10, since both the COL1A2 and CASD1 genes at the centromere-proximal region and the genes between PPP1R9A and ASB4 toward the telomere were non-imprinted and biallelically expressed. Consequently, our combining analyses of methylome, transcriptome, and informative polymorphisms revealed the boundary of imprinting cluster at the SGCE/PEG10 locus in pig chromosome 9 and consolidated the landscape of genomic imprinting in pigs.

bta-miR-23a Regulates the Myogenic Differentiation of Fetal Bovine Skeletal Muscle-Derived Progenitor Cells by Targeting MDFIC Gene

miR-23a, a member of the miR-23a/24-2/27a cluster, has been demonstrated to play pivotal roles in many cellular activities. However, the mechanisms of how bta-miR-23a controls the myogenic differentiation (MD) of PDGFRα⁻ bovine progenitor cells (bPCs) remain poorly understood. In the present work, bta-miR-23a expression was increased during the MD of ^PDGFRα− bPCs. Moreover, bta-miR-23a overexpression significantly promoted the MD of ^PDGFRα− bPCs. Luciferase reporter assays showed that the 3’-UTR region of MDFIC (MyoD family inhibitor domain containing) could be a promising target of bta-miR-23a, which resulted in its post-transcriptional down-regulation. Additionally, the knockdown of MDFIC by siRNA facilitated the MD of ^PDGFRα− bPCs, while the overexpression of MDFIC inhibited the activating effect of bta-miR-23a during MD. Of note, MDFIC might function through the interaction between MyoG transcription factor and MEF2C promoter. This study reveals that bta-miR-23a can promote the MD of ^PDGFRα− bPCs through post-transcriptional downregulation of MDFIC.

Conservation Genomic Analysis of the Croatian Indigenous Black Slavonian and Turopolje Pig Breeds

The majority of the nearly 400 existing local pig breeds are adapted to specific environments and human needs. The demand for large production quantities and the industrialized pig production have caused a rapid decline of many local pig breeds in recent decades. Black Slavonian pig and Turopolje pig, the latter highly threatened, are the two Croatian local indigenous breeds typically grown in extensive or semi-intensive systems. In order to guide a long-term breeding program to prevent the disappearance of these breeds, we analyzed their genetic diversity, inbreeding level and relationship with other local breeds across the world, as well as modern breeds and several wild populations, using high throughput genomic data obtained using the Illumina Infinium PorcineSNP60 v2 BeadChip. Multidimensional scaling analysis positioned Black Slavonian pigs close to the UK/North American breeds, while the Turopolje pig clustered within the Mediterranean breeds. Turopolje pig showed a very high inbreeding level (F_ROH>4Mb = 0.400 and F_ROH>8Mb = 0.332) that considerably exceeded the level of full-sib mating, while Black Slavonian pig showed much lower inbreeding (F_ROH>4Mb = 0.098 and F_ROH>8Mb = 0.074), indicating a planned mating strategy. In Croatian local breeds we identified several genome regions showing adaptive selection signals that were not present in commercial breeds. The results obtained in this study reflect the current genetic status and breeding management of the two Croatian indigenous local breeds. Given the small populations of both breeds, a controlled management activity has been implemented in Black Slavonian pigs since their commercial value has been recognized. In contrast, the extremely high inbreeding level observed in Turopolje pig argues for an urgent conservation plan with a long-term, diversity-oriented breeding program.

Genome-Wide Association Study and Fine Mapping Reveals Candidate Genes for Birth Weight of Yorkshire and Landrace Pigs

Birth weight of pigs is an important economic factor in the livestock industry. The identification of the genes and variants that underlie birth weight is of great importance. In this study, we integrated two genotyping methods, single nucleotide polymorphism (SNP) chip analysis and restriction site associated DNA sequencing (RAD-seq) to genotype genome-wide SNPs. In total, 45,175 and 139,634 SNPs were detected with the SNP chip and RAD-seq, respectively. The genome-wide association study (GWAS) of the combined SNP panels identified two significant loci located at chr1: 97,745,041 and chr4: 112,031,589, that explained 6.36% and 4.25% of the phenotypic variance respectively. To reduce interval containing causal variants, we imputed sequence-level SNPs in the GWAS identified regions and fine-mapped the causative variants into two narrower genomic intervals: a ∼100 kb interval containing 71 SNPs and a broader ∼870 kb interval with 432 SNPs. This fine-mapping highlighted four promising candidate genes, SKOR2, SMAD2, VAV3, and NTNG1. Additionally, the functional genes, SLC25A24, PRMT6 and STXBP3, are also located near the fine-mapping region. These results suggest that these candidate genes may have contribute substantially to the birth weight of pigs.

Being Born Large for Gestational Age is Associated with Increased Global Placental DNA Methylation

Being born small (SGA) or large for gestational age (LGA) is associated with adverse birth outcomes and metabolic diseases in later life of the offspring. It is known that aberrations in growth during gestation are related to altered placental function. Placental function is regulated by epigenetic mechanisms such as DNA methylation. Several studies in recent years have demonstrated associations between altered patterns of DNA methylation and adverse birth outcomes. However, larger studies that reliably investigated global DNA methylation are lacking. The aim of this study was to characterize global placental DNA methylation in relationship to size for gestational age. Global DNA methylation was assessed in 1023 placental samples by LC-MS/MS. LGA offspring displayed significantly higher global placental DNA methylation compared to appropriate for gestational age (AGA; p < 0.001). ANCOVA analyses adjusted for known factors impacting on DNA methylation demonstrated an independent association between placental global DNA methylation and LGA births (p < 0.001). Tertile stratification according to global placental DNA methylation levels revealed a significantly higher frequency of LGA births in the third tertile. Furthermore, a multiple logistic regression analysis corrected for known factors influencing birth weight highlighted an independent positive association between global placental DNA methylation and the frequency of LGA births (p = 0.001).

GWAS for Meat and Carcass Traits Using Imputed Sequence Level Genotypes in Pooled F2-Designs in Pigs

In order to gain insight into the genetic architecture of economically important traits in pigs and to derive suitable genetic markers to improve these traits in breeding programs, many studies have been conducted to map quantitative trait loci. Shortcomings of these studies were low mapping resolution, large confidence intervals for quantitative trait loci-positions and large linkage disequilibrium blocks. Here, we overcome these shortcomings by pooling four large F2 designs to produce smaller linkage disequilibrium blocks and by resequencing the founder generation at high coverage and the F1 generation at low coverage for subsequent imputation of the F2 generation to whole genome sequencing marker density. This lead to the discovery of more than 32 million variants, 8 million of which have not been previously reported. The pooling of the four F2 designs enabled us to perform a joint genome-wide association study, which lead to the identification of numerous significantly associated variant clusters on chromosomes 1, 2, 4, 7, 17 and 18 for the growth and carcass traits average daily gain, back fat thickness, meat fat ratio, and carcass length. We could not only confirm previously reported, but also discovered new quantitative trait loci. As a result, several new candidate genes are discussed, among them BMP2 (bone morphogenetic protein 2), which we recently discovered in a related study. Variant effect prediction revealed that 15 high impact variants for the traits back fat thickness, meat fat ratio and carcass length were among the statistically significantly associated variants.

Signatures of selection in Charolais beef cattle identified by genome-wide analysis

Charolais cattle are one of the most important breeds for meat production worldwide; in México, its selection is mainly made by live weight traits. One strategy for mapping important genomic regions that might influence productive traits is the identification of signatures of selection. This type of genomic features contains loci with extended linkage disequilibrium (LD) and homozygosity patterns that are commonly associated with sites of quantitative trait locus (QTL). Therefore, the objective of this study was to identify the signatures of selection in Charolais cattle genotyped with the GeneSeek Genomic Profiler Bovine HD panel consisting of 77 K single nucleotide polymorphisms (SNPs). A total 61,311 SNPs and 819 samples were used for the analysis. Identification of signatures of selection was carried out using the integrated haplotype score (iHS) methodology implemented in the rehh R package. The top ten SNPs with the highest piHS values were located on BTA 4, 5, 6 and 14. By identifying markers in LD with top ten SNPs, the candidate regions defined were mapped to 52.8-59.3 Mb on BTA 4; 67.5-69.3 on BTA 5; 39.5-41.0 Mb on BTA 6; and 26.4-29.6 Mb on BTA 14. The comparison of these candidate regions with the bovine QTLdb effectively confirmed the association (p < 0.05) with QTL related to growth traits and other important productive traits. The genomic regions identified in this study indicated selection for growth traits on the Charolais population via the conservation of haplotypes on various chromosomes. These genomic regions and their associated genes could serve as the basis for haplotype association studies and for the identification of causal genes related to growth traits.

Genome-wide genetic structure and differentially selected regions among Landrace, Erhualian, and Meishan pigs using specific-locus amplified fragment sequencing

As typical Chinese indigenous pig breeds, Erhualian and Meishan have been widely used to produce new strain or breed in the world. However, the genetic basis of characteristics of these pig breeds is still limited. Moreover, considering cost and output of sequencing, it is necessary to further develop cost-effective method for pig genome screening. To contribute on this issue, we developed a SLAF-seq (specific-locus amplified fragment sequencing) method for pigs and applied it to analyze the genetic difference among Landrace, Erhualian, and Meishan pigs. A total of 453.75 million reads were produced by SLAF-seq. After quality-control, 165,670 SNPs (single nucleotide polymorphisms) were used in further analysis. The results showed that Landrace had distinct genetic relationship compared to Erhualian (F_ST = 0.5480) and Meishan (F_ST = 0.5800), respectively, while Erhualian and Meishan held the relatively close genetic relationship (F_ST = 0.2335). Furthermore, a genome-wide scanning revealed 268 differentially selected regions (DSRs) with 855 genes and 256 DSRs with 347 genes between Landrace and the two Chinese indigenous pig breeds and between Erhualian and Meishan, respectively. This study provides a new cost-effective method for pig genome study and might contribute to a better understanding on the formation mechanism of genetic difference among pigs with different geographical origins.

Determination of Genetic Structure and Signatures of Selection in Three Strains of Tanzania Shorthorn Zebu, Boran and Friesian Cattle by Genome-Wide SNP Analyses

Background

More than 90 percent of cattle in Tanzania belong to the indigenous Tanzania Short Horn Zebu (TSZ) population which has been classified into 12 strains based on historical evidence, morphological characteristics, and geographic distribution. However, specific genetic information of each TSZ population has been lacking and has caused difficulties in designing programs such as selection, crossbreeding, breed improvement or conservation. This study was designed to evaluate the genetic structure, assess genetic relationships, and to identify signatures of selection among cattle of Tanzania with the main goal of understanding genetic relationship, variation and uniqueness among them.

Methodology/Principal findings

The Illumina Bos indicus SNP 80K BeadChip was used to genotype genome wide SNPs in 168 DNA samples obtained from three strains of TSZ cattle namely Maasai, Tarime and Sukuma as well as two comparative breeds; Boran and Friesian. Population structure and signatures of selection were examined using principal component analysis (PCA), admixture analysis, pairwise distances (F_ST), integrated haplotype score (iHS), identical by state (IBS) and runs of homozygosity (ROH). There was a low level of inbreeding (F~0.01) in the TSZ population compared to the Boran and Friesian breeds. The analyses of F_ST, IBS and admixture identified no considerable differentiation between TSZ trains. Importantly, common ancestry in Boran and TSZ were revealed based on admixture and IBD, implying gene flow between two populations. In addition, Friesian ancestry was found in Boran. A few common significant iHS were detected, which may reflect influence of recent selection in each breed or strain.

Conclusions

Population admixture and selection signatures could be applied to develop conservation plan of TSZ cattle as well as future breeding programs in East African cattle.

Genome Wide Sampling Sequencing for SNP Genotyping: Methods, Challenges and Future Development

Genetic polymorphisms, particularly single nucleotide polymorphisms (SNPs), have been widely used to advance quantitative, functional and evolutionary genomics. Ideally, all genetic variants among individuals should be discovered when next generation sequencing (NGS) technologies and platforms are used for whole genome sequencing or resequencing. In order to improve the cost-effectiveness of the process, however, the research community has mainly focused on developing genome-wide sampling sequencing (GWSS) methods, a collection of reduced genome complexity sequencing, reduced genome representation sequencing and selective genome target sequencing. Here we review the major steps involved in library preparation, the types of adapters used for ligation and the primers designed for amplification of ligated products for sequencing. Unfortunately, currently available GWSS methods have their drawbacks, such as inconsistency in the number of reads per sample library, the number of sites/targets per individual, and the number of reads per site/target, all of which result in missing data. Suggestions are proposed here to improve library construction, genotype calling accuracy, genome-wide marker density and read mapping rate. In brief, optimized GWSS library preparation should generate a unique set of target sites with dense distribution along chromosomes and even coverage per site across all individuals.

Quantitative Genetics of Food Intake in Drosophila melanogaster

Food intake is an essential animal activity, regulated by neural circuits that motivate food localization, evaluate nutritional content and acceptance or rejection responses through the gustatory system, and regulate neuroendocrine feedback loops that maintain energy homeostasis. Excess food consumption in people is associated with obesity and metabolic and cardiovascular disorders. However, little is known about the genetic basis of natural variation in food consumption. To gain insights in evolutionarily conserved genetic principles that regulate food intake, we took advantage of a model system, Drosophila melanogaster, in which food intake, environmental conditions and genetic background can be controlled precisely. We quantified variation in food intake among 182 inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel (DGRP). We found significant genetic variation in the mean and within-line environmental variance of food consumption and observed sexual dimorphism and genetic variation in sexual dimorphism for both food intake traits (mean and variance). We performed genome wide association (GWA) analyses for mean food intake and environmental variance of food intake (using the coefficient of environmental variation, CV_E, as the metric for environmental variance) and identified molecular polymorphisms associated with both traits. Validation experiments using RNAi-knockdown confirmed 24 of 31 (77%) candidate genes affecting food intake and/or variance of food intake, and a test cross between selected DGRP lines confirmed a SNP affecting mean food intake identified in the GWA analysis. The majority of the validated candidate genes were novel with respect to feeding behavior, and many had mammalian orthologs implicated in metabolic diseases.

Signatures of selection in tilapia revealed by whole genome resequencing

Natural selection and selective breeding for genetic improvement have left detectable signatures within the genome of a species. Identification of selection signatures is important in evolutionary biology and for detecting genes that facilitate to accelerate genetic improvement. However, selection signatures, including artificial selection and natural selection, have only been identified at the whole genome level in several genetically improved fish species. Tilapia is one of the most important genetically improved fish species in the world. Using next-generation sequencing, we sequenced the genomes of 47 tilapia individuals. We identified a total of 1.43 million high-quality SNPs and found that the LD block sizes ranged from 10–100 kb in tilapia. We detected over a hundred putative selective sweep regions in each line of tilapia. Most selection signatures were located in non-coding regions of the tilapia genome. The Wnt signaling, gonadotropin-releasing hormone receptor and integrin signaling pathways were under positive selection in all improved tilapia lines. Our study provides a genome-wide map of genetic variation and selection footprints in tilapia, which could be important for genetic studies and accelerating genetic improvement of tilapia.