Hybrid Versus Autochthonous Turkey Populations: Homozygous Genomic Regions Occurrences Due to Artiﬁcial and Natural Selection

Article Hybrid Versus Autochthonous Turkey Populations: Homozygous Genomic Regions Occurrences Due to Artiﬁcial and Natural Selection

Maria Giuseppina Strillacci 1,* , Stefano Paolo Marelli 1 and Guillermo Martinez-Velazquez 2 1 Department of Veterinary Medicine, University of Milan, Via Festa del Perdono, 7, 20122 Milano, Italy; [email protected] 2 INIFAP-Campo Experimental Santiago Ixcuintla, Apdo. Postal 100, Santiago Ixcuintla 63300, Mexico; [email protected] * Correspondence: [email protected]; Tel.: +39-025-033-4582

Received: 15 June 2020; Accepted: 28 July 2020; Published: 30 July 2020

Simple Summary: In this study we investigate the genomic differentiation of traditional Mexican turkey breeds and commercial hybrid strains. The analysis aimed to identify the effects of different types of selection on the birds’ genome structure. Mexican turkeys are characterized by an adaptive selection to their specific original environment; on the other hand, commercial hybrid strains are directionally selected to maximize productive traits and to reduce production costs. The Mexican turkeys were grouped in two geographic subpopulations, while high genomic homogeneity was found in hybrid birds. Traditional breeds and commercial strains are clearly differentiated from a genetic point of view. Inbreeding coefficients were here calculated with different approaches. A clear effect of selection for productive traits was recorded.

Abstract: The Mexican turkey population is considered to be the descendant of the original domesticated wild turkey and it is distinct from hybrid strains obtained by the intense artificial selection activity that has occurred during the last 40 years. In this study 30 Mexican turkeys were genomically compared to 38 commercial hybrids using 327,342 SNP markers in order to elucidate the differences in genome variability resulting from different types of selection, i.e., only adaptive for Mexican turkey, and strongly directional for hybrids. Runs of homozygosity (ROH) were detected and the two inbreeding coefficients (F and FROH) based on genomic information were calculated. Principal component and admixture analyses revealed two different clusters for Mexican turkeys (MEX_cl_1 and MEX_cl_2) showing genetic differentiation from hybrids (HYB) (FST equal 0.168 and 0.167, respectively). A total of 3602 ROH were found in the genome of the all turkeys populations. ROH resulted mainly short in length and the ROH_island identified in HYB (n = 9), MEX_cl_1 (n = 1), and MEX_cl_2 (n = 2) include annotated genes related to production traits: abdominal fat (percentage and weight) and egg characteristics (egg shell color and yolk weight). F and FROH resulted correlated to each other only for Mexican populations. Mexican turkey genomic variability allows us to separate the birds into two subgroups according to the geographical origin of samples, while the genomic homogeneity of hybrid birds reflected the strong directional selection occurring in this population.

Keywords: run of homozygosity; SNPs; turkey; inbreeding; ROH; genome variability; selected breeds; autochthonous populations

1. Introduction Turkey (Meleagris gallopavo) was the only vertebrate animal to be domesticated in ancient North America (i.e., the combined North and Central American sub-continents) [1]. The species has undergone

Animals 2020, 10, 1318; doi:10.3390/ani10081318 www.mdpi.com/journal/animals Animals 2020, 10, 1318 2 of 14 two main migratory process: in the 16th century turkeys have been introduced into Europe and from that time they underwent a quick diffusion in European counties [2]; in the 17th century European colonists brought them back to North America, where they were hybridized with the local wild eastern subspecies (Meleagris gallopavo silvestris)[3]. Turkeys have undergone a massive expansion since then, becoming the second source of poultry meat worldwide, in particular in developing countries. In the last 40 years turkey stocks have almost tripled, average meat production per bird doubled, and selection pressure for economically important traits such as egg production, meat quality and body weight were exponentially improved, showing the effects of intensive selection applied in turkeys [4]. A fast-growing meat commercial hybrid (HYB) has resulted from the strong directional selection. Mexican turkeys, always bred without directional selection, are characterized by large variability in plumage (type and color) and body weight. For native Mexican turkey populations, no structured selection program was developed and applied at a population level. Furthermore, in the traditional farming system, birds are not under direct reproductive control by humans, farmed in a complete free-range system and as such allowed to migrate, facilitating the genetic exchange across flocks, villages and regions [5]. Genomic research in turkeys quickly developed in the last years thanks to the availability of a reference genome [6] and individual sequences, which opened opportunities also in whole-genome SNP discovery. Studies characterizing the genetic/genomic variability of turkey populations using SNPs markers (including mtDNA) are still limited [7–11]. Among these studies, Marras et al. [8] analyzed for the first time runs of homozygosity (ROH) in commercial turkey hybrids but no study is available, at best of our knowledge, on any autochthonous turkey population not under such strong artificial selection. ROH are uninterrupted long genomic regions including homozygous genotypes in adjacent SNP markers inherited from a recent common ancestor. ROH are primarily caused by inbreeding and so they reflect the mating selection plan: recent inbreeding—long ROH; more ancient inbreeding—short ROH [12]. In addition to inbreeding level, ROH can reveal information about population history [13], effects of inbreeding on complex traits [14] and diseases [15]. The autochthonous turkeys’ populations genome has not still been explored for ROH characteristics. The aim of this study was to characterize genomic diversity and to estimate genomic inbreeding in Mexican turkey populations and then in commercial hybrids to provide information on genomic features. One of the targets of the research was to investigate the effects of selection in different breeding environments on the genome of these different turkey populations.

2. Materials and Methods

2.1. Sampling and Population Genetic Diversity The genotypes of all 38 hybrids and 30 Mexican turkeys used in this study are the ones previously analyzed by [7] and were obtained with the Axiom® Turkey Genotyping Array (Affymetrix, Santa Clara, CA, USA). As we analyze previously produced data, no ethical issue applies to data production in this research. In order to use the same number of SNPs for each animal, and then to reduce the bias ascribable to missing genotyping in inbreeding coefficients calculation and in other statistics, the original SNPs (400,451) dataset has been filtered maintaining for the analysis only SNP with call rate of at least 0.99. The final SNP dataset included 327,342 markers (for all animals), mapped on the Turkey_5.0 (GCA_000146605.1) genome assembly. On this data set the following analyses have been performed:

Principal components analysis (PCA) based on allele genotypes using the SVS software (SVS) • version 8.8.3 (Golden Helix Inc., Bozeman, MT, USA). The graphical visualization of PCA was obtained by the ggplot2 R package (https://CRAN.R-project.org/package=ggplot2)[16]. Estimation of pairwise Fixation Index (i.e., Wright’s F-statistic F ) using the dedicated module • ST of SVS. Animals 2020, 10, 1318 3 of 14

Determination of the most probable number of ancestral populations with the ADMIXTURE • v.1.3.0 software [17]. ADMIXTURE was run from K = 2 to K = 5, and the optimal number of clusters (K-value) was determined as the one having the lowest cross-validation error (CV). Data input ﬁles were generated for ADMIXTURE using PLINK software version 1.07 [18]. The R script suggested by ADMIXTURE procedure, was used to perform a graphical representation of ADMIXTURE results.

2.2. Identification of Runs of Homozygosity (ROH) ROH analyses were performed using the consecutive method implemented in the DetectRuns package [19] of R software setting a minimum of 1000 kb in size in order to exclude short and common ROH derived from strong LD [20] and 150 homozygous SNPs. In addition, no heterozygote and no missing SNPs were allowed in the ROH, and a maximum gap between SNPs of 1000 Kb was predefined in order to assure that the SNP density did not affect the ROH. ROHs were then grouped into 3 classes of length: 0–2 Mb, 2–4 Mb, 4–8 Mb for descriptive statistics. ROH statistics were calculated across individuals in each turkey population. The genomic regions with the highest frequency in ROH (ROH_island), have been identified by selecting the most frequent SNPs (where SNPs in a ROH were found in at least 70% of the birds of each cluster). The full turkey genes set (Annotation Release 103) was downloaded from NCBI online Database [21] and genes were catalogued within the ROH_island using the “intersectBed” command of BEDTools software [22]. Only genes with an official gene name were considered. A gene ontology (GO) functional annotation and KEGG pathway analyses was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.8 [23]. Chicken Quantitative Trait Loci (QTL) Database (Chicken QTLdb) was utilized (using “Search by associated gene” option) to catalogue QTL overlapping the identified ROH [24].

2.3. Inbreeding Coefficients Two genomic inbreeding coefficients for the all birds were estimated using the routine implemented within SVS (F)—based on the difference between the observed and expected numbers of homozygous genotypes—and within DetectRUNs (FROH)—based on the ratio between the total length of all ROH identified in a sample and the genome length covered by SNPs (in our study on chromosomes from 1 to 30, corresponding to 901,342,009 bp).

3. Results

3.1. Population Genetic Diversity The PCA result is displayed in Figure1A. On the ﬁrst principal component (x axis–PC_1 eigenvalue = 5.33) a clear separation of HYB turkey samples (red dots) from the MEX ones (green dots) is observable. On the second principal component (y axis PC_2 eigenvalue = 1.48) MEX turkeys is − clustered in two well separated groups of 19 and 11 animals (MEX_cl_1 and MEX_cl_2, respectively in Figure1A). As shown in Figure1B the two clusters of Mexican samples reﬂect the geographical area of sampling. Animals 2020, 10, 1318 4 of 14 Animals 2020, 10, x FOR PEER REVIEW 4 of 14

Animals 2020, 10, x FOR PEER REVIEW 4 of 14

Figure 1. (A) PCA result: red dots = Hybrid turkeys; green dots = Mexican turkeys. (B) Mexico States Figure 1. (A) PCA result: red dots = Hybrid turkeys; green dots = Mexican turkeys. (B) Mexico States involved in Mexican turkey sampling; map image has been modified from [25]. involved in Mexican turkey sampling; map image has been modiﬁed from [25].

To investigate the ancestry composition of MEX and HYB turkeys, ADMIXTURE analysis was These results are consistent with those obtained with the pairwise breed comparison using FST. run on the entire data set for values of possible ancestors (K) between 2 and 5. The lowest CV value Although the FST values appear low, a genetic differentiation is found between HYB vs. MEX_cl_1 has been obtained with K = 2 and K = 3 values (both values = 0.595–Figure 2A). At K = 2, MEX (FST = 0.168) and HYB vs. MEX_cl_2 (FST = 0.167). Differently, comparing MEX_cl_1 and MEX_cl_2 populationsFigure 1.(all (A )animals PCA result) displays: red dots only= Hybrid one turkeys common; green ancestor dots = Mexicanfor MEX_cl_1 turkeys . and(B) Mexico MEX_cl_2 States (light the FST value of 0.092 shows closer relatedness when comparing between these values and the one blue)between, involveddifferent the MEX in from Mexican and the HYB HYBturkey populations. one sampling; (red bars) map. Atimage K = has 3 birds been belongingmodified from to MEX_cl_[25]. 1 (green bars) differ in ancestralTo investigate composition the ancestry from the composition ones of MEX_cl_ of MEX2 ( andblueHYB bars) turkeys, and from ADMIXTURE those of HYB analysis (red bars) was To investigate the ancestry composition of MEX and HYB turkeys, ADMIXTURE analysis was (Figurerun on the2B). entire Figure data 2C setshows for valuesthe proportion of possible of ancestors contribution (K) betweenof each ancestor 2 and 5. Theto each lowest of the CV three value run on the entire data set for values of possible ancestors (K) between 2 and 5. The lowest CV value analyzedhas been population obtained withs. All K the= populations2 and K = 3 appear values to (both be mostly values unique= 0.595—Figure populations2A). being At Krepresented= 2, MEX has been obtained with K = 2 and K = 3 values (both values = 0.595–Figure 2A). At K = 2, MEX bypopulations an ancestral (all genetic animals) group displays in a onlyproportion one common larger ancestorthan 98% for (HYB MEX_cl_1–ANC_2 and in MEX_cl_2 red and MEX_cl_2 (light blue),– populations (all animals) displays only one common ancestor for MEX_cl_1 and MEX_cl_2 (light ANC_1 in blue) and 88% for MEX_cl_1 (ANC_3 in green). diblue)fferent, different from thefrom HYB the HYB one (redone (red bars). bars) At. At K =K 3= 3 birds birds belonging belonging toto MEX_cl_1MEX_cl_1 ( (greengreen bars) bars) differ differ inin ancestralancestral compositioncomposition from the the one oness of of MEX_cl_ MEX_cl_22 ( (blueblue bars) bars) and and from from those those of of HYB HYB (red (red bars) bars) (Figure(FigureA 2 B). 2B). Figure Figure 2 C 2CB shows shows the the proportion proportion of of contribution contribution C ofof eacheach ancestorancestor toto eacheach ofof thethe threethree ANC_1 ANC_2 ANC_3 analyzedanalyzed populations. populations. AllAll thethe populationspopulationsHYB appearappear to toM beE beX mostly mostly unique unique populations0 .5populations7% being being represented represented1.63% by

. an ancestral genetic group1 in a proportion larger than 98% (HYB–ANC_2 in red and MEX_cl_2–ANC_1

by an ancestral genetic0 group in a proportion larger than 98% (HYB–ANC_2 in red and MEX_cl_2–

t in blue) and 88% for MEX_cl_10 (ANC_3 in green).

ANC_1 in blue) and e 88% for MEX_cl_1 (ANC_3 in green).

n K. =2

0 88.39%

A B 1 C 98.97% 98.37% ANC_1 ANC_2 ANC_3

. 0 HYB Individual # MEX 0.57% 1.63%

e K=3

c 1.27%

. K. =2

2 HYB MEX _cl_1 MEX_cl_2 10.34% . 0.56%

0 Individual # 88.39%

0 HYB MEX_CL_1 MEX_CL_2

. 1 98.97% 98.37%

. 0 Individual #

. Figure 2. ADMIXTUREr results. (A) Cross-validation error values (CV) plotted at K from 1 to 5: lowest

e K=3

0 CV values were identifiedA at K = 2 and K = 3 (blue box). (B) K = 2 allowed ancestral distinction of

0 hybrids (vertical red bars) from Mexican birds (vertical light blue bars); K = 3 was taken1.27% as the most

0 HYB MEX _cl_1 MEX_cl_2 10.34% probable number of inferred ancestors. Individual vertical bars are grouped0.56% by population (red–HYB, Individual # green–Mex_cl_1, and blue–Mex_cl_2). (C) Proportion of identified ancestralHYB populationsMEX_CL_1 (ANC)MEX_CL_2 calculated as the average of genetic ADMIXTURE score within each population at K = 3. FigureFigure 2.2. ADMIXTURE results. ( (AA)) Cross Cross-validation-validation error error values values (CV) (CV) plotted plotted at at K K from from 11 to to 5: 5: lowest lowest CV values were identified at K = 2 and K = 3 (blue box). (B) K = 2 allowed ancestral distinction of ConsideringCV values were PCA identiﬁed and ADMIXTURE at K = 2 and results, K = 3 (blueROH box).descriptive (B)K = statistics2 allowed were ancestral performed distinction for MEX ofhybrids hybrids (vertical (vertical red red bars) bars) from from Mexican Mexican birds birds (vertical (vertical light lightblue bluebars); bars); K = 3 Kwas= 3taken was as taken the most as the turkeys taking into account the samples’ clustering into two groups (MEX_cl_1 and MEX_cl_2). mostprobable probable number number of inferred of inferred ancestors ancestors.. Individual Individual vertical bars vertical are grouped bars are by grouped population by (red population–HYB, (red–HYB,green–Mex_cl_1, green–Mex_cl_1, and blue–Mex_cl_2) and blue–Mex_cl_2).. (C) Proportion (C) Proportion of identified of identiﬁed ancestral ancestral populations populations (ANC) 3.2. Runs of Homozygosity (ROH) (ANC)calculated calculated as the a asverage the average of genetic of geneticADMIXTURE ADMIXTURE score within score each within population each population at K = 3. at K = 3. A total of 3602 runs of homozygosity (ROH) were found in the entire turkey populations: 1809, 1438 andConsidering 355 runs PCAin HYB, and MEX_cl_1 ADMIXTURE and results,MEX_cl_2, ROH respectively descriptive statistics(Tables 1 w andere performedS1). The descriptive for MEX statisticsturkeys oftaking ROH into across account samples the samples’ show clear clusteri differenng intoces amongtwo groups the three (MEX_cl_1 groups and (Table MEX 1)._cl_2) MEX_cl_1.

3.2. Runs of Homozygosity (ROH) A total of 3602 runs of homozygosity (ROH) were found in the entire turkey populations: 1809, 1438 and 355 runs in HYB, MEX_cl_1 and MEX_cl_2, respectively (Tables 1 and S1). The descriptive statistics of ROH across samples show clear differences among the three groups (Table 1). MEX_cl_1 Animals 2020, 10, x FOR PEER REVIEW 5 of 14 Animals 2020, 10, 1318 5 of 14 shows both the largest number of ROH (170) and largest average length of ROH (1.911 Mb) per sample. Considering PCA and ADMIXTURE results, ROH descriptive statistics were performed for MEX turkeysTable taking 1. Descriptive into account statistics the samples’for runs of clustering homozygosity into (ROHs) two groups identified (MEX_cl_1 in HYB (Hybrids) and MEX_cl_2). and in the two MEX (Mexican) subpopulations (MEX_cl_1 and MEX_cl_2). Values are expressed in Mega 3.2. Runs of Homozygosity (ROH) base pair (Mb).

A total of 3602 runs of homozygosity (ROH)Min–M wereax (M foundean) in theMin entire–Max turkey (Mean) populations: 1809, Pop Samples N. ROH 1438 and 355 runs in HYB, MEX_cl_1 and MEX_cl_2,N. ROH per respectively Sample ROH (Table Length1, Table per S1).Sample The descriptive statistics of ROHHYB across samples38 show1809 clear differences36-66 (47) among the three1–6.970 groups (1.717) (Table 1). MEX_cl_1 shows both theMEX_cl_1 largest number19 of ROH1438 (170) and largest2–170 (75) average length1– of7.652 ROH (1.911) (1.911 Mb) per sample. MEX_cl_2 11 355 11–120 (32) 1–7.999 (1.825) Table 1. Descriptive statistics for runs of homozygosity (ROHs) identified in HYB (Hybrids) and in the twoGraphical MEX (Mexican) representation subpopulationss of the ROH (MEX_cl_1 statistics and for MEX_cl_2). HYB and Values the two are expressedMEX subpopulation in Mega bases are shownpair separately (Mb). in Figure 3. In details, Figure 3A shows the relationship between ROH count and the average total length of ROH for each individual. In general, the graphical distribution allows to Min–Max (Mean) Min–Max (Mean) identify threePop groups Samples of birds: the N. ROH first includes all turkeys of MEX_cl_2 (except 1) and part of N. ROH per Sample ROH Length per Sample MEX_cl_1. These samples showed a relatively low number of runs and a ROH mean length ranging HYB 38 1809 36–66 (47) 1–6.970 (1.717) from 1.4 to 2 Mb. Few birds overlap with the group of HYB that appear the most homogeneous MEX_cl_1 19 1438 2–170 (75) 1–7.652 (1.911) showing limitedMEX_cl_2 variation 11 for ROH 355count per individual 11–120 (32) (36 to 66) and a 1–7.999 smaller (1.825) variation in size of ROH respect to MEX birds. The third group includes one turkey of MEX_cl_2 and the remaining birds of MEX_cl_1, all characterized by a high count of ROH. GraphicalAs shown representationsin Figure 3B, ROH of the of ROH< 2 Mb statistics are the formost HYB frequent and the class two in MEX all turkey subpopulationss being 1,369 are shown(76%) in separately HYB, 963 in (67%) Figure in3. MEX_cl_1 In details,, Figureand 2583A (73%) shows in the MEX_cl_2 relationship. Similar between mean ROH length count values and the(dashed average boxe totald in lengthFigure 3 ofB) ROH were forfound each in individual.each group of In birds general, within the class graphical of length. distribution allows to identifyIndividuals three groupsexhibiting of birds:the lowest the firstautozygosity includes belonged all turkeys to ofthe MEX_cl_2 MEX turkey (except population 1) and (n. part 3– of MEX_cl_1.MEX_cl_1 and These n. 2 samples–MEX_cl_1) showed show aing relatively a genome low coverage number ofof runsROH andencompassing a ROH mean less length than 2 ranging0 Mb. fromInstead, 1.4 8 to samples 2 Mb. of Few MEX_cl_1 birds overlap and 1 sample with the of groupMEX_cl_ of2 HYB with thatthe highest appear autozygosity the most homogeneous among all showinganimals ( limitedi.e., inbred variation ones), ha ford ROHa total count length per of the individual genome (36covered to 66) by and ROH a smaller larger than variation 200 Mb in. sizeHYB of ROHturkey respects had on to the MEX other birds. hand The a thirdmore grouphomogenous includes size one of turkeygenome of coverage MEX_cl_2 by and ROH the among remaining animals, birds ofranging MEX_cl_1, from all64 characterizedto 115 Mb. by a high count of ROH.

FigureFigure 3. 3.Graphical Graphical representation representation of runs of runs of homozygosity of homozygosity (ROH) (ROH) statistics. statistics. (A) Relationship (A) Relationship between numberbetween andnumber averaged and averaged total length total (bp) length of ROH (bp) inof eachROH bird;in each (B) bird; Frequencies (B) Frequencies and counts and ofcounts ROH of for eachROH class for each of length; class of the length values; the in thevalues dashed in the boxes dashed represent boxes therepresent mean length the mean of the length ROH of identiﬁed the ROH in eachidentified class ofin length.each class of length.

AsROH shown were in found Figure on3B,ly ROHon some of < of2 the Mb aut areosomes the most (Figure frequent 4): 23 class in HYB, in all turkeys29 in MEX_cl_1, being 1,369 and (76%) 22 inin HYB,MEX_cl_2. 963 (67%) On chromosome in MEX_cl_1, 18 andno ROH 258 (73%)was identified in MEX_cl_2. in any Similarof the analyzed mean length populations. values (dashedChr 18 boxedis short in in Figure length3B) (332,615 were found bp) and in includes each group the ofmajor birds histocompatibility within class of length. complex (MHC locus B) [26] Animals 2020, 10, 1318 6 of 14

Individuals exhibiting the lowest autozygosity belonged to the MEX turkey population (n. 3–MEX_cl_1 and n. 2–MEX_cl_1) showing a genome coverage of ROH encompassing less than 20 Mb. Instead, 8 samples of MEX_cl_1 and 1 sample of MEX_cl_2 with the highest autozygosity among all animals (i.e., inbred ones), had a total length of the genome covered by ROH larger than 200 Mb. HYB turkeys had on the other hand a more homogenous size of genome coverage by ROH among animals, ranging from 64 to 115 Mb. ROH were found only on some of the autosomes (Figure4): 23 in HYB, 29 in MEX_cl_1, and Animals 2020, 10, x FOR PEER REVIEW 6 of 14 22 in MEX_cl_2. On chromosome 18 no ROH was identiﬁed in any of the analyzed populations. thatChr it 18 is is well short known in length to be (332,615a highly bp)polymorphic and includes locus the involved major histocompatibilityin immune response. complex In HYB (MHC, no monomorphiclocus B) [26] that SNPs it isresulted well known for the to 62 be markers a highly mapping polymorphic on this locus chromosome involved; instead, in immune in MEX_cl_1 response. andIn HYB, MEX_cl_2 no monomorphic, 24 and 19 SNPs SNPs were resulted monomorphic for the 62 markers even if nonconsecutive mapping on this, thus chromosome; not being instead,a ROH. in MEX_cl_1No correlation and MEX_cl_2, between 24 and chromosomes 19 SNPs were length monomorphic and mean even ROH if nonconsecutive, length resulted thus in not these being populationsa ROH. (Figure 4).

Frequency mean length 0,25 3 2,5 0,20

c 2

e 0,15 t

q 1,5 n

0,10 n

a H 1

M R 0,05 0,5

0,00 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 HYB Turkey autosomes

0,20 Frequency mean length 3

2,5

c 0,15

e 2

f 0,10 1,5

O 1 a

e R 0,05 0,5 M 0,00 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 MEX_cl_1 Turkey autosomes

0,25 Frequency mean length 3 2,5 0,20

n 2

0,15 h

e 1,5

0,10

n H 1

R 0,05 0,5 M 0,00 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 MEX_cl_2 Turkey autosomes

FigureFigure 4 4.. FrequenciesFrequencies (columns) (columns) and and m meanean length length in in Mb Mb (line) (line) of of ROH ROH for for each each chromosome chromosome.. The graphs in Figure 5 show the proportion of SNP in ROH segments across the genome for the No correlation between chromosomes length and mean ROH length resulted in these populations three groups of birds, HYB, MEX_cl_1 and MEX_cl_2. (Figure4). A total of seven, one and two 2 ROH_islands (i.e., where SNPs in a ROH are found in at least The graphs in Figure5 show the proportion of SNP in ROH segments across the genome for the 70% of the birds of each specific group) were identified in HYB, MEX_cl_1, and MEX_cl_2, respectivelythree groups (Table of birds, 2). HYB, MEX_cl_1 and MEX_cl_2. Table 2 also reports the list of genes (n. 69–HYB; n. 3–MEX_cl_1, and n. 46–MEX_cl_2) harbored in each identified ROH_island. An overlap was observed for HYB and MEX_cl_2 ROH_island on chr 8; all 17 genes mapping in the ROH_island of MEX_cl_2 are also included in the ROH_island of HYB. Functional classification of genes annotated in turkey ROH_island provided by DAVID database is reported in Table S2. The Animal Genome Database was accessed to identify if genes in ROH_island also overlapped in QTL annotated in database. Considering that there is no specific QTL database for the turkey species, we consulted the one available for chicken. Two genes are associated with four QTLs for production traits: the BIRC5 gene on chr 7 (MEX_cl_2–eggshell color–QTL_ID:1914) and RET gene on chr 8 (HYB and MEX_cl_2–Yolk weight– QTL_ID: 62003 and 62004; Abdominal fat percentage–QTL_ID: 24505; Abdominal fat weight– QTL_ID: 24498). Animals 2020, 10, 1318 7 of 14 Animals 2020, 10, x FOR PEER REVIEW 7 of 14

FigureFigure 5. Proportion of SNPs in identified identiﬁed ROH for HYB, MEX_cl_1 and and MEX_cl_2. MEX_cl_2.

Animals 2020, 10, 1318 8 of 14

A total of seven, one and two 2 ROH_islands (i.e., where SNPs in a ROH are found in at least 70% of the birds of each speciﬁc group) were identiﬁed in HYB, MEX_cl_1, and MEX_cl_2, respectively (Table2).

Table2. Details of ROH_island deﬁned by SNP occurrences (>70%). Start and End ROH positions as well as the ROH length are expressed in bp and are in concordance with the Turkey_5.0 (GCA_000146605.1) genome assembly.

Chr Start ROH Position End ROH Position ROH Length Gene 1 ROH_island in HYB 2 23,019,543 23,992,770 973,227 MTA3, HAAO RBM47, CHRNA9, RHOH, N4BP2, PDS5A, UBE2K, SMIM14, UGDH, LIAS, RPL9, KLB, RFC1, 4 48,508,445 49,752,492 124,4047 WDR19, KLHL5, TMEM156, FAM114A1, KLF3, TBC1D1, PGM2, RELL1, C4H4orf19, NWD2 GHITM, NRG3, SH2D4B, TSPAN14, FAM213A, EXOSC3, DYDC1, MAT1A, RASGEF1A, 8 35,534 3,564,550 3,529,016 CSGALNACT2, RET, BMS1, PLAC9, ANXA11, ECD, FAM149B1, DNAJC9, TFAM, UBE2D1, CISD1, IPMK, PCDH15 CHAT, OGDHL, PARG, NCOA4, GPRIN2, SYT15, 8 4,968,066 5,916,410 948,344 FAM35A, GLUD1, ADIRF, SNCG, MMRN2, BMPR1A, LDB3, OPN4, WAPL 8 8,483,294 9,342,515 859,221 RTKN2, ARID5B, TMEM26, RHOBTB1, CDK1 11 3,058,621 3,097,354 38,733 - 22 1,595,252 1,986,192 390,940 ASIP, EIF2S2, RALY ROH_island in MEX_cl_1 13 11,244,459 11,371,128 126,669 HYDIN, MTSS1L, SF3B3 ROH_island in MEX_cl_2 DNAH7, BIRC5, STK17B, HECW2, GTF3C3, C7H2orf66, PGAP1, ANKRD44, SF3B1, COQ10B, 7 9,145,051 10,872,877 1,727,826 HSPD1, RFTN2, BOLL, PLCL1, SATB2, C7H2orf69, TYW5, MAIP1, SPATS2L, KCTD18, SGO2, AOX1, BZW1, CLK1, PPIL3, NIF3L1, ORC2, FAM126B EXOSC3, DYDC1, MAT1A, RASGEF1A, CSGALNACT2, RET, BMS1, PLAC9, ANXA11, ECD, 8 1,401,303 3,748,153 2,346,850 FAM149B1, DNAJC9, TFAM, UBE2D1, CISD1, IPMK, PCDH15, PRKG1 1 Italic: overlapped genes.

Table2 also reports the list of genes (n. 69–HYB; n. 3–MEX_cl_1, and n. 46–MEX_cl_2) harbored in each identified ROH_island. An overlap was observed for HYB and MEX_cl_2 ROH_island on chr 8; all 17 genes mapping in the ROH_island of MEX_cl_2 are also included in the ROH_island of HYB. Functional classification of genes annotated in turkey ROH_island provided by DAVID database is reported in Table S2. The Animal Genome Database was accessed to identify if genes in ROH_island also overlapped in QTL annotated in database. Considering that there is no specific QTL database for the turkey species, we consulted the one available for chicken. Two genes are associated with four QTLs for production traits: the BIRC5 gene on chr 7 (MEX_cl_2–eggshell color–QTL_ID:1914) and RET gene on chr 8 (HYB and MEX_cl_2–Yolk weight–QTL_ID: 62003 and 62004; Abdominal fat percentage–QTL_ID: 24505; Abdominal fat weight–QTL_ID: 24498). Table3 reports the list of genes (annotated in ROH_island) that have been associated with di fferent traits in different species. Animals 2020, 10, 1318 9 of 14

Table 3. Genes mapping in ROH_island in diﬀerent species for diﬀerent phenotypes.

Pop. Gene Phenotype Species References MEX_cl_2 ANKRD44 Skin thickness Swine [27] MEX_cl_2 AOX1 Residual feed intake Bovine [28] Animals 2020, 10, x FOR PEER REVIEW 9 of 14 HYB ARID5B Adaptive immunity Human [29] HYB/MEX_cl_2 DYDC1 Acrosome biogenesis; Spermiogenesis Mouse [30] MEX_cl_1HYB HYDIN TBC1D1 Thermal painCarcass response Chicken Mice [40] [31] MEX_cl_1HYB HYDIN TBC1D1 Growth Marblingand Serum score Clinical-Chemical Chicken Bovine [41] [32] HYBHYB MMRN2TBC1D1 Meat juicinessGrowth Rabbit Bovine [42] [33] HYB MMRN2 Meat tenderness Bovine [34] MEX_cl_2 NIF3L1 Skin thickness Swine [27] 3.3.MEX_cl_2 Inbreeding CoefficientsORC2 (F-FROH) Marbling score Bovine [32] HYB/MEX_cl_2 PCDH15 Femoral head separation Chicken [35] GenomicHYB inbreedingPGM2 parametersFeed efficiency; were Reduction calculated of environmental for all footprint genotyped Chickenanimals (Table [36] 4). ProportionMEX_cl_2s of homozygoPLCL1 us SNPs were significantlySkin thickness different between the Swine HYB and [27 ] MEX populationsMEX_cl_2 : 58.5%PRKG1 vs. 76.6%Humoral (MEX_cl_1) response and to Mycobacterium 72.7% (MEX_cl_2). avium ssp. Paratuberculosis Bovine [37] MEX_cl_2 SF3B1 Carcass merit and meat quality Swine [38] HYBThe/MEX_cl_2 inbreedingTFAM coefficients estimatedCORT-induced using fatty the liver proportion protection of homozygous Chicken SNP on [39 all] the autosomHYBal SNP markersTBC1D1 (F) were negative in HYB,Carcass positive for MEX_cl_1, and positive Chicken for MEX_cl_2 [40] (averagedHYB F-valuesTBC1D1 are shown in FigureGrowth 6A) and. The Serum minimum Clinical-Chemical and maximum F-values Chicken were −0.17 [41] and HYB TBC1D1 Growth Rabbit [42] 0.08 for HYB, −0.284 and 0.57 for MEX_cl_1, −0.04 and 0.30 for MEX_cl_2. FROH values were calculated based on the three classes of ROH length (Figure 6B) and on the 3.3. Inbreeding Coefficients (F-FROH) total lengths covered by ROH. As displayed in Figure 6 the FROH values are different for each class of ROHGenomic length: F inbreedingROH decrease parameters with increasing were calculated of ROH classes for all genotyped of length in animals all three (Table populations.4). Proportions In HYB of homozygousthe averaged SNPs FROH werevalue significantly clearly decreased different with between each thelength HYB class and, MEXbeing populations: the one of class58.5% 2– vs.4 half 76.6% of (MEX_cl_1)the value of and Class 72.7% < 2, (MEX_cl_2).and 5 times the value of Class 4–8. This drop was not so evident for Mexican turkeys FROH values. In addition, MEX_cl_1 individuals show higher average values and the highest Table 4. Descriptive statistics of homozygosity, heterozygosity and inbreeding coefficients (F F ). number of outlier animals. The average genomic inbreeding based on the total observed ROHs− ROH (FROH) is shown in Table 4. The minimum and maximum FROH values were 0.066 and 0.127 for HYB, 0.003 POP Obs Hom Exp Hom Obs Het Exp Het F Mean (SD) FROH Mean (SD) and 0.379 for MEX_cl_1, 0.020 and 0.272 for MEX_cl_2. Differences in FROH were found also along all HYB 58.5 63.3 41.5 36.2 0.129 (0.025) 0.130 (0.015) chromosomes of all populations (Figure S1). − MEX_cl_1 76.6 69.8 23.4 29.4 0.227 (0.23) 0.161 (0.13) MEX_cl_2 72.7 71.1 27.3 27.6 0.056 (0.10) 0.065 (0.07) Table 4. Descriptive statistics of homozygosity, heterozygosity and inbreeding coefficients (F - FROH). Obs Hom = Observed Homozygoty (%); Exp Hom = Expected Homozygoty (%); Obs Het = Observed Heterozygoty (%); ExpPOP Het = ExpectedObs Hom Heterozygoty Exp Hom (%). Obs Het Exp Het F Mean (SD) FROH Mean (SD) HYB 58.5 63.3 41.5 36.2 −0.129 (0.025) 0.130 (0.015) TheMEX_cl_1 inbreeding coe76.6ffi cients69.8 estimated 23.4 using the29.4 proportion 0.227 of(0.23) homozygous 0.161 (0.13) SNP on all the autosomalMEX_cl_2 SNP markers 72.7 (F ) were71.1 negative in27.3 HYB, positive27.6 for0.056 MEX_cl_1, (0.10) and positive0.065 (0.07) for MEX_cl_2 (averaged F-values are shown in Figure6A). The minimum and maximum F-values were 0.17 and Obs Hom = Observed Homozygoty (%); Exp Hom = Expected Homozygoty (%); Obs Het = Observed− 0.08 for HYB, 0.284 and 0.57 for MEX_cl_1, 0.04 and 0.30 for MEX_cl_2. Heterozygot− y (%); Exp Het = Expected Heterozygot− y (%).

FigureFigure 6.6. ((AA)) DistributionDistribution ofof averagedaveraged FF values.values. ((BB)) DistributionDistribution ofof averagedaveraged FFROHROH perper class class of of length. length.

F values were calculated based on the three classes of ROH length (Figure6B) and on the TheROH linear relationship between F and FROH in HYB (Figure 7) is weaker (R2 = 0.15) compared to totalthe one lengths for MEX_cl_1 covered by (R ROH.2 = 0.90) As and displayed Mex_cl_2 in Figure(R2 = 06.88) the. F ROH values are diﬀerent for each class of Animals 2020, 10, 1318 10 of 14

ROH length: FROH decrease with increasing of ROH classes of length in all three populations. In HYB the averaged FROH value clearly decreased with each length class, being the one of class 2–4 half of the value of Class < 2, and 5 times the value of Class 4–8. This drop was not so evident for Mexican turkeys FROH values. In addition, MEX_cl_1 individuals show higher average values and the highest number of outlier animals. The average genomic inbreeding based on the total observed ROHs (FROH) is shown in Table4. The minimum and maximum F ROH values were 0.066 and 0.127 for HYB, 0.003 and 0.379 for MEX_cl_1, 0.020 and 0.272 for MEX_cl_2. Diﬀerences in FROH were found also along all chromosomes of all populations (Figure S1). 2 The linear relationship between F and FROH in HYB (Figure7) is weaker (R = 0.15) compared to theAnimals one 2020 for, MEX_cl_110, x FOR PEER (R2 REVIEW= 0.90) and Mex_cl_2 (R2 = 0.88). 10 of 14

HYB y = 0.63x - 0.19 Mex_cl_1 y = 1.63x - 0.03 Mex_cl_2 y = 1.29x – 0.03 R² = 0.1466 R² = 0.90 R² = 0.88 0,.7 00.4,400 0 0.06 0.08 0.1 0.12 0.14 0,.6 0.5 0,5 00.3,300 -0.05 0,.4 0,.3 00.2,200 0,.2 -0.1 0,.1 00.1,100 00 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 -0.15 --0,.11 --0,.22 00.0,000 0.05 0.1 0.15 0.2 0.25 0.3 --0,.33 -0.2 --0,.44 -0.,10

Figure 7. Regression and coeﬃcient of determination (R2) calculated between F and F . y = F; x = F . Figure 7. Regression and coefficient of determination (R2) calculated between F andROH FROH. y = F; x ROH= 4. DiscussionFROH.

4. DiscussionTurkeys, like most domestic animals, have undergone multi-generational changes influenced by controlled mating according to human’s needs and choices. In this study two different turkey Turkeys, like most domestic animals, have undergone multi-generational changes influenced by populations (hybrid vs. autochthonous) were analyzed in order to compare the effects of more than controlled mating according to human’s needs and choices. In this study two different turkey 40 years of directional selection on heavy turkey hybrids’ genome structure vs a non-human controlled populations (hybrid vs. autochthonous) were analyzed in order to compare the effects of more than breeding of the Mexican turkeys farmed as a free-range population. According to the fact that no 40 years of directional selection on heavy turkey hybrids’ genome structure vs a non-human directional selection occurs in the MEX population, we can assume that only adaptive selection affected controlled breeding of the Mexican turkeys farmed as a free-range population. According to the fact the genome structure of the two MEX groups of birds. These two Mexican turkey subpopulations that no directional selection occurs in the MEX population, we can assume that only adaptive allow a very interesting comparison between birds of the same origin, where the HYB, highly selected selection affected the genome structure of the two MEX groups of birds. These two Mexican turkey in the last 40 years, derives from ancestral birds originally brought into Europe by Spanish conquerors, subpopulations allow a very interesting comparison between birds of the same origin, where the and then brought back to America from Europe by settlers. Even if MEX and HYB belong to the same HYB, highly selected in the last 40 years, derives from ancestral birds originally brought into Europe species, they represent two very well distinct groups: a wild type with no directional selection pressure by Spanish conquerors, and then brought back to America from Europe by settlers. Even if MEX and (MEX) and a very heavily selected one (HYB). Their genomes then independently evolved for more HYB belong to the same species, they represent two very well distinct groups: a wild type with no than 500 years: the MEX adapted to challenging natural environmental conditions for more than five directional selection pressure (MEX) and a very heavily selected one (HYB). Their genomes then centuries; the HYB, in the last 40 years, heavily directionally selected by humans to best perform in independently evolved for more than 500 years: the MEX adapted to challenging natural artificial controlled environmental conditions. environmental conditions for more than five centuries; the HYB, in the last 40 years, heavily directionallyInterestingly, selected the by spatial humans distribution to best perfo of Mexicanrm in artificial turkeys controlled resulted inenvironmental two well clustered conditions. groups, as shownInterestin in PCAgly, the (Figure spatial1A). distribution This bird’s of distributionMexican turkeys reflects resulted the geographical in two well clustered sampling group areass, characterizedas shown in byPCA diff erent(Figure environments: 1A). This bird MEX_cl_1’s distribution birds were reflects collected the geographicalin seven Mexican sampling States where areas mountaincharacterized areas by are different present environmentat several altitudes: MEX_cl_1 (Baja California birds were Sur, collected Coahuila, in Nuevoseven Leon,Mexican Guerrero, States Tlaxcala,where mountain Puebla, Tamaulipas,areas are present Guanajuato, at several Colima, altitude Durango, (Baja Nayarit,California Queretaro) Sur, Coahuila, and MEX_cl_2 Nuevo Leon, birds wereGuerrero, sampled Tlaxcala, in three Puebla, Mexican Tamaulipas, States (Campeche, Guanajuato, Tabasco, Colima, Quintana Durango, Roo), Naya thatrit, are Queretaro) mainly flat and and hillyMEX_cl_2 areas asbirds shown were in sampled the topographic in three physicalMexican mapStates in (Campeche, Figure1B. This Tabasco, result isQuintana also supported Roo), that by theare FmainlyST values flat and and from hilly theareas ADMIXTURE as shown in outcomesthe topographic that clearly physical provided map in indication Figure 1B of. This diff erentresult geneticis also background for the two subgroups of the Mexican turkeys. We speculate that the difference in genome supported by the FST values and from the ADMIXTURE outcomes that clearly provided indication of maydifferent be the genetic result background of adaptation for to the the two diff subgroupserent environments of the Mexican of the turkeys two sampling. We speculate areas of that Mexico the wheredifference the birds in genome originated, may lived be the and result evolved. of adaptation This may also to bethe interpreted different environments as the exchange of of the genetic two sampling areas of Mexico where the birds originated, lived and evolved. This may also be interpreted as the exchange of genetic material among states in the same geographical region, i.e., MEX_cl_1 and MEX_cl_2, but no exchange of birds across them. When analyzed according to ROH, the differences at genomic level among the three turkey groups are evident. Although the proportion of ROH within length classes is similar for Mexican turkeys and hybrids, the number of ROH, as well as the mean ROH length per sample, is different in MEX populations (Figure 3A,B) relatively to those identified for HYB that, in addition, appear less variable respect the MEX ROH. The two MEX clusters in fact exhibited both lowest and highest autozygosity (inbred animals) showing a ROH genome coverage encompassing less than 20 and ROH > 200 Mb, respectively. Instead, HYB turkeys had a genome coverage affected by ROH within a shorter range (64 to 115 Mb). Commercial HYB derives from the cross of heavily selected (and inbreed) lines, that we considered not related among them. As such their genome is expected to be highly heterozygous. Additionally, the genome of hybrid birds is the results of very few Animals 2020, 10, 1318 11 of 14 material among states in the same geographical region, i.e., MEX_cl_1 and MEX_cl_2, but no exchange of birds across them. When analyzed according to ROH, the differences at genomic level among the three turkey groups are evident. Although the proportion of ROH within length classes is similar for Mexican turkeys and hybrids, the number of ROH, as well as the mean ROH length per sample, is different in MEX populations (Figure3A,B) relatively to those identified for HYB that, in addition, appear less variable respect the MEX ROH. The two MEX clusters in fact exhibited both lowest and highest autozygosity (inbred animals) showing a ROH genome coverage encompassing less than 20 and ROH > 200 Mb, respectively. Instead, HYB turkeys had a genome coverage affected by ROH within a shorter range (64 to 115 Mb). Commercial HYB derives from the cross of heavily selected (and inbreed) lines, that we considered not related among them. As such their genome is expected to be highly heterozygous. Additionally, the genome of hybrid birds is the results of very few recombination events crossing the parental lines. A four-way cross (A B C D) see only one generation of recombination event × × × between A and B and between C and D. ROH are then identified when parental lines are homozygous for the same allele (SNP) in the same region of the genome. These regions, that in outbred populations represent sites of recent inbreeding, in HYB indicates regions under common selection in parental lines. According to this hypothesis, the ROH are then expected to be smaller and less variable in HYB and we can speculate that they harbor genes under common directional selection pressure in all parental lines. In MEX, where we assume no directional selection for productive performance, ROH are likely to indicate regions under adaptive positive selection and recent inbreeding possibly due to mating occurring among relatives in small flocks. The F values listed in Table4 and their distribution (Figure6A) confirm that HYB birds exhibit a large proportion of heterozygous genotype respect the expectation under HW equilibrium (average F = 0.129). This is expected due to the assortative mating realized crossing parental inbred lines. − Additionally, in HYB variation in F value is much lower than in MEX birds with MEX_cl_1 showing both larger inbreeding coefficients values (Table4) and larger standard deviation ( F = 0.227 +/ 0.23). − The linear relationship between F and FROH shown in Figure7 indicate that the homozygous SNPs are, for MEX, mainly in ROH, occurrence that is not realized in the same manner for HYB. These results could be explained by the higher number of heterozygous SNPs observed (Table4) and by the lower proportion of homozygous SNPs distributed on genome outside of the ROH in HYB. In fact, this last proportion, calculated within samples as total number of homozygous SNPs defining ROH over the total observed homozygous SNPs, is lower in HYB respect to MEX birds: 0.88–HYB and 0.92 for MEX_cl_1 and MEX_cl_2. Although individual variability exists in the ROH genomic location, regions with a high prevalence of ROH (ROH_island) were identified in all populations: seven in HYB, one in MEX_cl_1 and two in MEX_cl_2. Some of HYB regions (on chr 2, 4, 8, and 11) appear to overlap with the ones identified by [8] (according to the published Manhattan plot; no details on ROH_island provided by authors). In addition, the ROH_islandw identified on chr 8 partial overlap with those found in MEX_cl_2. No overlapping ROH_islandw have been identified between the two Mexican turkey groups, most likely because they ancestral origin is different, as shown by the ADMIXTURE results. Several genes harbored in ROH_island are known to be involved in expression for production, functional and health traits in different species (Table3). Turkey gene annotation is still not as complete as in other species where the genes mapping in ROH here found are available. Except for DYDC1 and PCDH15 all other genes were identified in association with productive or adaptive traits in livestock species. Particularly, the genes mapping in ROH for HYB, except for ARID5B are related to several meat production efficiency traits. On the contrary genes for MEX are mainly related to adaptation to harsh environment characteristics. These findings clearly show that genome of the MEX birds, here considered the wild type, subjected to a different selection pressure respect to HYB. Animals 2020, 10, 1318 12 of 14

Among the four genes included in Table3 for the chicken species, PCDH15 and TBC1D1 are those containing the largest number of homozygous SNPs. In particular, TBC1D1—which polymorphism has been related to several traits including glucose homeostasis, energy metabolism in skeletal muscle and blood, insulin resistance, adiposity, obesity, and type 2 diabetes [41,42]—seems to reflect the directional selection occurred in HYB turkeys. In support of this latter assumption, as reported for commercial broiler chickens, TBC1D1 is located within a QTL explaining differences in growth between broilers and layers and a haplotype sweep regarding this gene is fixed in the high and low growth lines [43].

5. Conclusions The evolution of the genome of Mexican turkey was shown to have occurred in a different manner respect to the one that has happened recently in the voluminous commercial turkey population. Even if the annotation in Turkey species is still at its infancy, genes in ROH_island can be ascribed to two groups of characteristics: production efficiency for HYB, and fitness to natural environment for MEX. The production efficiency in an artificial selection program, as the one occurring in HYB, can be ascribed to greater fitness. In fact, artificial selection is favoring the best performing animals in an artificially controlled environment for a desired trait, in the HYB meat production. This manuscript presents the first evidence that the comparison of a heavy selected Meleagris gallopavo strain versus an unselected one can disclose variations in genomic structure and identify regions in autozygosity due to different selection criteria.

Supplementary Materials: The following are available online at http://www.mdpi.com/2076-2615/10/8/1318/s1, Table S1: List of all ROH identified in commercial hybrid and Mexican turkeys, Table S2: Functional classification of genes annotated in turkey ROH_island provided by DAVID database, Figure S1: FROH calculated on all chromosomes of all turkey populations. Author Contributions: Conceptualization, M.G.S.; methodology, M.G.S., investigation, M.G.S.; formal analysis, M.G.S.; data curation, M.G.S., G.M.-V.;writing—original draft preparation, M.G.S., S.P.M.,G.M.-V.;writing—review and editing, M.G.S., S.P.M., G.M.-V.; project administration, M.G.S.; supervision M.G.S. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Acknowledgments: We acknowledge the availability of genotyping data available from previous research funded by the Ministry of Foreign affairs of Italy and Mexico. Conflicts of Interest: The authors declare no conflict of interest.

References

1. Thornton, E.K.; Emery, K.F. The uncertain origins of Mesoamerican turkey domestication. J. Archaeol. Method Theory 2017, 24, 328–351. [CrossRef] 2. Schorger, A.W. The Wild Turkey. Its History and Domestication; University of Ottawa Press: Ottawa, ON, Canada, 1996. 3. Crawford, R.D. Introduction to Europe and diﬀusion of domesticated turkeys from the America. Arch. Zootec. 1992, 41, 2. 4. FAO. The Second Report on the State of the World’s Animal Genetic Resources for Food and Agriculture; FAO: Rome, Italy, 2015. 5. Rios Utrera, A.; Roman Ponce, S.I.; Velez Izquierdo, A.; Cabrera Torre, E.; Cantu Covarrubias, A.; De la Cruz Colin, L.; Durán Aguilar, M.; Maldonado Jaquez, J.A.; Martínez Silva, F.E.; Martínez Velázquez, G.; et al. Analysis of morphological variables in Mexican backyard turkeys (Meleagris gallopavo gallopavo). Rev. Mex. Cienc. Pecu. 2016, 7, 377–389. [CrossRef] 6. Dalloul, R.A.; Long, J.A.; Zimin, A.V.; Aslam, L.; Beal, K.; Ann Blomberg, L.; Bouﬀard, P.; Burt, D.W.; Crasta, O.; Crooijmans, R.P.M.A.; et al. Multi-Platform Next-Generation Sequencing of the Domestic Turkey (Meleagris gallopavo): Genome Assembly and Analysis. PLoS Biol. 2010, 8, e1000475. [CrossRef] Animals 2020, 10, 1318 13 of 14

7. Strillacci, M.G.; Gorla, E.; Ríos-Utrera, A.; Vega-Murillo, V.E.; Montaño-Bermudez, M.; Garcia-Ruiz, A.; Cerolini, S.; Román-Ponce, S.I.; Bagnato, A. Copy Number Variation Mapping and Genomic Variation of Autochthonous and Commercial Turkey Populations. Front. Genet. 2019, 10, 982. [CrossRef] 8. Marras, G.; Wood, B.J.; Makanjuola, B.; Malchiodi, F.; Peeters, K.; van As, P.; Baes, C.F.; Biscarini, F. Characterization of runs of homozygosity and heterozygosity-rich regions in a commercial turkey (Meleagris gallopavo) population. In Proceedings of the 11th World Congress on Genetics Applied to Livestock Production, Auckland, New Zealand, 10–16 February 2018; p. 763. 9. Aslam, M.L.; Bastiaansen, J.W.M.; Elferink, M.G.; Megens, H.-J.; Crooijmans, R.P.M.A.; Blomberg, L.A.; Fleischer, R.C.; Van Tassell, C.P.; Sonstegard, T.S.; Schroeder, S.G.; et al. Whole genome SNP discovery and analysis of genetic diversity in Turkey (Meleagris gallopavo). BMC Genom. 2012, 13, 391. [CrossRef] 10. Guan, X.; Silva, P.; Gyenai, K.; Xu, J.; Geng, T.; Smith, E. Mitochondrial DNA-based analyses of relatedness among turkeys, Meleagris gallopavo. Biochem. Genet. 2015, 53, 29–41. [CrossRef] 11. Canales Vergara, A.M.; Landi, V.; Delgado Bermejo, J.V.; Martínez, A.; Cervantes Acosta, P.; Pons Barro, Á.; Bigi, D.; Sponenberg, P.; Helal, M.; Hossein Banabazi, M.; et al. Tracing Worldwide Turkey Genetic Diversity Using D-loop Sequence Mitochondrial DNA Analysis. Animals 2019, 9, 897. [CrossRef] 12. Ferenˇcaković,M.; Sölkner, J.; Curik, I. Estimating autozygosity from high-throughput information: Effects of SNP density and genotyping errors. Genet. Sel. Evol. 2013, 45, 42. [CrossRef] 13. Ceballos, F.C.; Joshi, P.K.; Clark, D.W.; Ramsay, M.; Wilson, J.F. Runs of homozygosity: Windows into population history and trait architecture. Nat. Rev. Genet. 2018, 19, 220. [CrossRef] 14. Johnson, E.C.; Evans, L.M.; Keller, M.C. Relationships between estimated autozygosity and complex traits in the UK Biobank. PLoS Genet. 2018, 14, e1007556. [CrossRef] 15. Sams, A.J.; Boyko, A.R. Fine-Scale Resolution of Runs of Homozygosity Reveal Patterns of Inbreeding and Substantial Overlap with Recessive Disease Genotypes in Domestic Dogs. G3 Genes Genomes Genet. 2019, 9, 117–123. [CrossRef][PubMed] 16. Wickham, H. ggplot2: Elegant Graphics for Data Analysis; Springer: New York, NY, USA, 2016; ISBN 978-3-319-24277-4. 17. Alexander, D.H.; Novembre, J.; Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 2009, 19, 1655–1664. [CrossRef][PubMed] 18. Purcell, S.; Neale, B.; Todd-Brown, K.; Thomas, L.; Ferreira, M.A.R.; Bender, D.; Maller, J.; Sklar, P.; de Bakker, P.I.W.; Daly, M.J.; et al. PLINK: A tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 2007, 81, 559–575. [CrossRef] 19. Biscarini, F.; Cozzi, P.; Gaspa, G.; Marras, G. detectRUNS: An R Package to Detect Runs of Homozygosity and Heterozygosity in Diploid Genomes Genomes. R Package Version 0.9.5. Available online: https://CRAN.R-project.org/package=detectRUNS (accessed on 1 July 2020). 20. Purfield, D.C.; Berry, D.P.; McParland, S.; Bradley, D.G. Runs of homozygosity and population history in cattle. BMC Genet. 2012, 13, 70. [CrossRef][PubMed] 21. NCBI Online Database. Available online: https://ftp.ncbi.nlm.nih.gov/genomes/all/annotation_releases/9103/ 103/GCF_000146605.3_Turkey_5.1 (accessed on 1 July 2020). 22. Quinlan, A.R.; Hall, I.M. BEDTools: A flexible suite of utilities for comparing genomic features. Bioinformatics 2010, 26, 841–842. [CrossRef][PubMed] 23. DAVID Online Database. Available online: http://david.abcc.ncifcrf.gov/summary.jsp (accessed on 1 July 2020). 24. Chicken Quantitative Trait Loci (QTL) Database (Chicken QTLdb). Available online: https://www.animalgenome.org/cgi-bin/QTLdb/GG/genesrch (accessed on 1 July 2020). 25. Google Earth. Available online: https://earth.google.com/web/search/M{é}xico/ @23.55407672,-102.62049061,571.6762355a,7328746.89000249d,35y,0h,0t,0r/data= CigiJgokCfVcOQAj8zhAEfVcOQAj8zjAGdmNrjOG80pAIdmNrjOG80rA (accessed on 27 July 2020). 26. Reed, K.M.; Bauer, M.M.; Monson, M.S.; Benoit, B.; Chaves, L.D.; O’Hare, T.H.; Delany, M.E. Defining the Turkey MHC: Identification of expressed class I- and class IIB-like genes independent of the MHC-B. Immunogenetics 2011, 63, 753. [CrossRef] 27. Ai, H.; Xiao, S.; Zhang, Z.; Yang, B.; Li, L.; Guo, Y.; Lin, G.; Ren, J.; Huang, L. Three novel quantitative trait loci for skin thickness in swine identified by linkage and genome-wide association studies. Anim. Genet. 2014, 45, 524–533. [CrossRef][PubMed] Animals 2020, 10, 1318 14 of 14

28. Karisa, B.K.; Thomson, J.; Wang, Z.; Stothard, P.; Moore, S.S.; Plastow, G.S. Candidate genes and single nucleotide polymorphisms associated with variation in residual feed intake in beef cattle. J. Anim. Sci. 2013, 91, 3502–3513. [CrossRef] 29. Cichocki, F.; Wu, C.Y.; Zhang, B.; Felices, M.; Tesi, B.; Tuininga, K.; Dougherty, P.; Taras, E.; Hinderlie, P.; Blazar, B.R.; et al. ARID5B regulates metabolic programming in human adaptive NK cells. J. Exp. Med. 2018, 215, 2379–2395. [CrossRef] 30. Li, S.; Qiao, Y.; Di, Q.; Le, X.; Zhang, L.; Zhang, X.; Zhang, C.; Cheng, J.; Zong, S.; Koide, S.S.; et al. Interaction of SH3P13 and DYDC1 protein: A germ cell component that regulates acrosome biogenesis during spermiogenesis. Eur. J. Cell Biol. 2009, 88, 509–520. [CrossRef][PubMed] 31. Recla, J.M.; Robledo, R.F.; Gatti, D.M.; Bult, C.J.; Churchill, G.A.; Chesler, E.J. Precise genetic mapping and integrative bioinformatics in Diversity Outbred mice reveals Hydin as a novel pain gene. Mamm. Genome 2014, 25, 211–222. [CrossRef][PubMed] 32. Li, Y.; Gao, Y.; Kim, Y.S.; Iqbal, A.; Kim, J.J. A whole genome association study to detect additive and dominant single nucleotide polymorphisms for growth and carcass traits in Korean native cattle, Hanwoo. Asian-Australas. J. Anim. Sci. 2017, 30, 8–19. [CrossRef][PubMed] 33. Leal-Gutiérrez, J.D.; Elzo, M.A.; Johnson, D.D.; Hamblen, H.; Mateescu, R.G. Genome wide association and gene enrichment analysis reveal membrane anchoring and structural proteins associated with meat quality in beef. BMC Genom. 2019, 20, 151. [CrossRef][PubMed] 34. Castro, L.M.; Rosa, G.; Lopes, F.B.; Regitano, L.; Rosa, A.; Magnabosco, C.U. Genomewide association mapping and pathway analysis of meat tenderness in Polled Nellore cattle. J. Anim. Sci. 2017, 95, 1945–1956. [CrossRef] 35. Packialakshmi, B.; Liyanage, R.; Lay Jr, J.; Okimoto, R.; Rath, N. Prednisolone-induced predisposition to femoral head separation and the accompanying plasma protein changes in chickens. Biomark. Insights 2015, 10, 1–8. [CrossRef] 36. Sell-Kubiak, E.; Wimmers, K.; Reyer, H.; Szwaczkowski, T. Genetic aspects of feed efficiency and reduction of environmental footprint in broilers: A review. J. Appl. Genet. 2017, 58, 487–498. [CrossRef] 37. McGovern, S.P.; Purfield, D.C.; Ring, S.C.; Carthy, T.R.; Graham, D.A.; Berry, D.P. Candidate genes associated with the heritable humoral response to Mycobacterium avium ssp. paratuberculosis in dairy cows have factors in common with gastrointestinal diseases in humans. J. Dairy Sci. 2019, 102, 4249–4263. [CrossRef] 38. Choi, I.; Bates, R.O.; Raney, N.E.; Steibel, J.P.; Ernst, C.W. Evaluation of QTL for carcass merit and meat quality traits in a US commercial Duroc population. Meat Sci. 2012, 92, 132–138. [CrossRef] 39. Hu, Y.; Sun, Q.; Liu, J.; Jia, Y.; Cai, D.; Idriss, A.A.; Omer, N.A.; Zhao, R. In ovo injection of betaine alleviates corticosterone-induced fatty liver in chickens through epigenetic modifications. Sci. Rep. 2017, 7, 40251. [CrossRef] 40. Wang, Y.; Xu, H.Y.; Gilbert, E.R.; Peng, X.; Zhao, X.L.; Liu, Y.P.; Zhu, Q. Detection of SNPs in the TBC1D1 gene and their association with carcass traits in chicken. Gene 2014, 547, 288–294. [CrossRef][PubMed] 41. Manjula, P.; Cho, S.; Suh, K.J.; Seo, D.; Lee, J.H. Single Nucleotide Polymorphism of TBC1D1 Gene Association with Growth Traits and Serum Clinical-Chemical Traits in Chicken. Korean J. Poult. Sci. 2018, 45, 291–298. [CrossRef] 42. Yang, Z.J.; Fu, L.; Zhang, G.W.; Yang, Y.; Chen, S.Y.; Wang, J.; Lai, S.J. Identification and Association of SNPs in TBC1D1 Gene with Growth Traits in Two Rabbit Breeds. Asian-Australas. J. Anim Sci 2013, 26, 1529–1535. [CrossRef][PubMed] 43. Rubin, C.-J.; Zody, M.C.; Eriksson, J.; Meadows, J.R.S.; Sherwood, E.; Webster, M.T.; Jiang, L.; Ingman, M.; Sharpe, T.; Ka, S.; et al. Whole-genome resequencing reveals loci under selection during chicken domestication. Nature 2010, 464, 587–591. [CrossRef][PubMed]

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).