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Qi L, Xiao L, Fu R, Nie Q, Zhang X, Luo W. Genetic characteristics and selection signatures between Southern Chinese local and commercial chickens. Poult Sci 2024; 103:103863. [PMID: 38810566 PMCID: PMC11166977 DOI: 10.1016/j.psj.2024.103863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 04/25/2024] [Accepted: 05/13/2024] [Indexed: 05/31/2024] Open
Abstract
The introduction of exotic breeds and the cultivation of new lines by breeding companies have posed challenges to native chickens in South China, including loss of breed characteristics, decreased genetic diversity, and declining purity. Understanding the population genetic structure and genetic diversity of native chickens in South China is crucial for further advancements in breeding efforts. In this study, we analyzed the population genetic structure and genetic diversity of 321 individuals from 10 different breeds in South China. By comparing commercial chickens with native ones, we identified selection signatures occurring between local chickens and commercial breeds. The analysis of population genetic structure revealed that the native chicken populations in South China exhibited a considerable level of genetic diversity. Moreover, the commercial lines of Xiaobai chicken and Huangma chicken displayed even higher levels of genetic diversity, which distinguished them from other native varieties at the clustering level. However, certain individuals within these commercial varieties showed a discernible genetic relationship with the native populations. Notably, both commercial varieties also retained a significant degree of genetic similarity to their respective native counterparts. In order to investigate the genomic changes occurring during the commercialization of native chickens, we employed 4 methods (Fst, ROD, XPCLR, and XPEHH) to identify potential candidate regions displaying selective signatures in Southern Chinese native chicken population. A total of 168 (identified by Fst and ROD) and 86 (identified by XPCLR and XPEHH) overlapping genes were discovered. Functional annotation analysis revealed that these genes may be associated with reproduction and growth (SAMSN1, HYLS1, ROBO3, FGF14, PRSS23), musculoskeletal development (DNER, MYBPC1, DGKB, ORC1, KLF10), disease resistance and environmental adaptability (PUS3, CRB2, CALD1, USP15, SGCD, LTBP1), as well as egg production (ADGRB3, ACSF3). Overall, native chickens in South China harbor numerous selective sweep regions compared to commercial chickens, enriching valuable genomic resources for future genetic research and breeding conservation.
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Affiliation(s)
- Lin Qi
- State Key Laboratory of Livestock and Poultry Breeding, & Lingnan Guangdong Laboratory of Agriculture, South China Agricultural University, Guangzhou 510642, China; Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, 510642, China; Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou Guangzhou 510642, China
| | - Liangchao Xiao
- State Key Laboratory of Livestock and Poultry Breeding, & Lingnan Guangdong Laboratory of Agriculture, South China Agricultural University, Guangzhou 510642, China; Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, 510642, China; Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou Guangzhou 510642, China
| | - Rong Fu
- State Key Laboratory of Livestock and Poultry Breeding, & Lingnan Guangdong Laboratory of Agriculture, South China Agricultural University, Guangzhou 510642, China; Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, 510642, China; Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou Guangzhou 510642, China
| | - Qinghua Nie
- State Key Laboratory of Livestock and Poultry Breeding, & Lingnan Guangdong Laboratory of Agriculture, South China Agricultural University, Guangzhou 510642, China; Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, 510642, China; Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou Guangzhou 510642, China
| | - Xiquan Zhang
- State Key Laboratory of Livestock and Poultry Breeding, & Lingnan Guangdong Laboratory of Agriculture, South China Agricultural University, Guangzhou 510642, China; Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, 510642, China; Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou Guangzhou 510642, China
| | - Wen Luo
- State Key Laboratory of Livestock and Poultry Breeding, & Lingnan Guangdong Laboratory of Agriculture, South China Agricultural University, Guangzhou 510642, China; Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, 510642, China; Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou Guangzhou 510642, China.
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Deng C, Li M, Wang T, Duan W, Guo A, Ma G, Yang F, Dai F, Li Q. Integrating genomics and transcriptomics to identify candidate genes for high-altitude adaptation and egg production in Nixi chicken. Br Poult Sci 2024:1-13. [PMID: 38922310 DOI: 10.1080/00071668.2024.2367228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 05/17/2024] [Indexed: 06/27/2024]
Abstract
1. This study combined genome-wide selection signal analysis with RNA-sequencing to identify candidate genes associated with high altitude adaptation and egg production performance in Nixi chickens (NXC).2. Based on the whole-genome data from 20 NXC (♂:10; ♀:10), the population selection signal was analysed by sliding window analysis. The selected genes were screened by combination with the population differentiation statistic (FST). The sequence diversity statistic (θπ). RNA-seq was performed on the ovarian tissues of NXC (n = 6) and Lohmann laying hens (n = 6) to analyse the differentially expressed genes (DEGs) between the two groups. The functional enrichment analysis of the selected genes and differentially expressed genes was performed.3. There were 742 genes under strong positive selection and 509 differentially expressed genes screened in NXC. Integrated analysis of the genome and transcriptome revealing 26 overlapping genes. The candidate genes for adaptation to a high-altitude environment, as well as for egg production, disease resistance, vision and pigmentation in NXC were preliminarily screened.4. The results provided theoretical guidance for further research on the genetic resource protection and utilisation of NXC.
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Affiliation(s)
- C Deng
- College of Biology and Food Engineering, Southwest Forestry University, Kunming, China
| | - M Li
- School of Mathematics and Computer Science, Yunnan Nationalities University, Kunming, China
| | - T Wang
- School of Pharmacy, Chengdu University, Chengdu, China
| | - W Duan
- College of Veterinary Medicine, China Agricultural University, Beijing, China
| | - A Guo
- College of Biology and Food Engineering, Southwest Forestry University, Kunming, China
| | - G Ma
- Agricultural and Rural Bureau of Gejiu County, Honghe, China
| | - F Yang
- Agricultural and Rural Bureau of Gejiu County, Honghe, China
| | - F Dai
- College of Veterinary Medicine, Yunnan Agricultural University, Kunming, China
| | - Q Li
- College of Biology and Food Engineering, Southwest Forestry University, Kunming, China
- Kunming Xianghao Technology Co. Ltd., Kunming, China
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Tolone M, Sardina MT, Criscione A, Lasagna E, Senczuk G, Rizzuto I, Riggio S, Moscarelli A, Macaluso V, Di Gerlando R, Cassandro M, Portolano B, Mastrangelo S. High-density single nucleotide polymorphism markers reveal the population structure of 2 local chicken genetic resources. Poult Sci 2023; 102:102692. [PMID: 37120867 PMCID: PMC10172703 DOI: 10.1016/j.psj.2023.102692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 03/21/2023] [Accepted: 03/29/2023] [Indexed: 05/02/2023] Open
Abstract
Italy counts a large number of local chicken populations, some without a recognized genetic structure, such as Val Platani (VPL) and Cornuta (COS), which represent noteworthy local genetic resources. In this study, the genotype data of 34 COS and 42 VPL, obtained with the Affymetrix Axiom600KChicken Genotyping Array, were used with the aim to investigate the genetic diversity, the runs of homozygosity (ROH) pattern, as well as the population structure and relationship within the framework of other local Italian and commercial chickens. The genetic diversity indices, estimated using different approaches, displayed moderate levels of genetic diversity in both populations. The identified ROH hotspots harbored genes related to immune response and adaptation to local hot temperatures. The results on genetic relationship and population structure reported a clear clustering of the populations according to their geographic origin. The COS formed a nonoverlapping genomic cluster and clearly separated from the other populations, but showed evident proximity to the Siciliana breed (SIC). The VPL highlighted intermediate relationships between the COS-SIC group and the rest of the sample, but closer to the other Italian local chickens. Moreover, VPL showed a complex genomic structure, highlighting the presence of 2 subpopulations that match with the different source of the samples. The results obtained from the survey on genetic differentiation underline the hypothesis that Cornuta is a population with a defined genetic structure. The substructure that characterizes the Val Platani chicken is probably the consequence of the combined effects of genetic drift, small population size, reproductive isolation, and inbreeding. These findings contribute to the understanding of genetic diversity and population structure, and represent a starting point for designing programs to monitor and safeguard these local genetic resources, in order to define a possible official recognition program as breeds.
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Affiliation(s)
- Marco Tolone
- Department of Agricultural, Food and Forest Sciences, University of Palermo, 90128 Palermo, Italy
| | - Maria Teresa Sardina
- Department of Agricultural, Food and Forest Sciences, University of Palermo, 90128 Palermo, Italy
| | - Andrea Criscione
- Department of Agriculture, Food and the Environment, University of Catania, 95131 Catania, Italy
| | - Emiliano Lasagna
- Department of Agricultural, Food and Environmental Sciences, University of Perugia, 06121 Perugia, Italy
| | - Gabriele Senczuk
- Department of Agricultural, Environmental and Food Sciences, University of Molise, 86100 Campobasso, Italy
| | - Ilaria Rizzuto
- Department of Agricultural, Food and Forest Sciences, University of Palermo, 90128 Palermo, Italy
| | - Silvia Riggio
- Department of Agricultural, Food and Forest Sciences, University of Palermo, 90128 Palermo, Italy
| | - Angelo Moscarelli
- Department of Agricultural, Food and Forest Sciences, University of Palermo, 90128 Palermo, Italy
| | - Vito Macaluso
- Department of Agricultural, Food and Forest Sciences, University of Palermo, 90128 Palermo, Italy
| | - Rosalia Di Gerlando
- Department of Agricultural, Food and Forest Sciences, University of Palermo, 90128 Palermo, Italy
| | - Martino Cassandro
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, 35020 Legnaro, Italy
| | - Baldassare Portolano
- Department of Agricultural, Food and Forest Sciences, University of Palermo, 90128 Palermo, Italy
| | - Salvatore Mastrangelo
- Department of Agricultural, Food and Forest Sciences, University of Palermo, 90128 Palermo, Italy.
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Genome-wide run of homozygosity analysis reveals candidate genomic regions associated with environmental adaptations of Tibetan native chickens. BMC Genomics 2022; 23:91. [PMID: 35100979 PMCID: PMC8805376 DOI: 10.1186/s12864-021-08280-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 12/23/2021] [Indexed: 01/12/2023] Open
Abstract
Background In Tibet, the two most important breeds are Tibetan chicken and Lhasa white chicken, and the duo exhibit specific adaptations to the high altitude thereby supplying proteins for humans living in the plateau. These breeds are partly included in the conservation plans because they represent important chicken genetic resources. However, the genetic diversity of these chickens is rarely investigated. Based on whole-genome sequencing data of 113 chickens from 4 populations of Tibetan chicken including Shigatse (SH), Nyemo (NM), Dagze (DZ) and Nyingchi (LZ), as well as Lhasa white (LW) chicken breed, we investigated the genetic diversity of these chicken breeds by genetic differentiation, run of homozygosity (ROH), genomic inbreeding and selection signature analyses. Results Our results revealed high genetic diversity across the five chicken populations. The linkage disequilibrium decay was highest in LZ, while subtle genetic differentiation was found between LZ and other populations (Fst ranging from 0.05 to 0.10). Furthermore, the highest ROH-based inbreeding estimate (FROH) of 0.11 was observed in LZ. In other populations, the FROH ranged from 0.04 to 0.06. In total, 74, 111, 62, 42 and 54 ROH islands containing SNPs ranked top 1% for concurrency were identified in SH, NM, DZ, LZ and LW, respectively. Genes common to the ROH islands in the five populations included BDNF, CCDC34, LGR4, LIN7C, GLS, LOC101747789, MYO1B, STAT1 and STAT4. This suggested their essential roles in adaptation of the chickens. We also identified a common candidate genomic region harboring AMY2A, NTNG1 and VAV3 genes in all populations. These genes had been implicated in digestion, neurite growth and high-altitude adaptation. Conclusions High genetic diversity is observed in Tibetan native chickens. Inbreeding is more intense in the Nyingchi population which is also genetically distant from other chicken populations. Candidate genes in ROH islands are likely to be the drivers of adaptation to high altitude exhibited by the five Tibetan native chicken populations. Our findings contribute to the understanding of genetic diversity offer valuable insights for the genetic mechanism of adaptation, and provide veritable tools that can help in the design and implementation of breeding and conservation strategies for Tibetan native chickens. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-08280-z.
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Investigating inbreeding in the turkey (Meleagris gallopavo) genome. Poult Sci 2021; 100:101366. [PMID: 34525446 PMCID: PMC8445901 DOI: 10.1016/j.psj.2021.101366] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 06/02/2021] [Accepted: 06/24/2021] [Indexed: 02/06/2023] Open
Abstract
The detrimental effects of increased homozygosity due to inbreeding have prompted the development of methods to reduce inbreeding. The detection of runs of homozygosity (ROH), or contiguous stretches of homozygous marker genotypes, can be used to describe and quantify the level of inbreeding in an individual. The estimation of inbreeding coefficients can be calculated based on pedigree information, ROH, or the genomic relationship matrix. The aim of this study was to detect and describe ROH in the turkey genome and compare estimates of pedigree-based inbreeding coefficients (FPED) with genomic-based inbreeding coefficients estimated from ROH (FROH) and the genomic relationship matrix (FGRM). A total of 2,616,890 pedigree records were available. Of these records, 6,371 genotyped animals from three purebred turkey (Meleagris gallopavo) lines between 2013 and 2019 were available, and these were obtained using a dense single nucleotide polymorphism array (56,452 SNPs). The overall mean length of detected ROH was 2.87 ± 0.29 Mb with a mean number of 84.87 ± 8.79 ROH per animal. Short ROH with lengths of 1 to 2 Mb long were the most abundant throughout the genome. Mean ROH coverage differed greatly between chromosomes and lines. Considering inbreeding coefficient means across all lines, genomic derived inbreeding coefficients (FROH = 0.27; FGRM = 0.32) were higher than coefficients estimated from pedigree records (FPED = 0.14). Correlations between FROH and FPED, FROH and FGRM, and FPED and FGRM ranged between 0.19 to 0.31, 0.68 to 0.73, and 0.17 to 0.30, respectively. Additionally, correlations between FROH from different lengths and FPED substantially increased with ROH length from -0.06 to 0.33. Results of the current research, including the distribution of ROH throughout the genome and ROH-derived inbreeding estimates, can provide a more comprehensive description of inbreeding in the turkey genome. This knowledge can be used to evaluate genetic diversity, a requirement for genetic improvement, and develop methods to minimize inbreeding in turkey breeding programs.
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Malomane DK, Weigend S, Schmitt AO, Weigend A, Reimer C, Simianer H. Genetic diversity in global chicken breeds in relation to their genetic distances to wild populations. Genet Sel Evol 2021; 53:36. [PMID: 33853523 PMCID: PMC8048360 DOI: 10.1186/s12711-021-00628-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 03/30/2021] [Indexed: 12/03/2022] Open
Abstract
Background Migration of a population from its founder population is expected to cause a reduction of its genetic diversity and facilitates differentiation between the population and its founder population, as predicted by the theory of genetic isolation by distance. Consistent with that theory, a model of expansion from a single founder predicts that patterns of genetic diversity in populations can be explained well by their geographic expansion from their founders, which is correlated with genetic differentiation. Methods To investigate this in chicken, we estimated the relationship between the genetic diversity of 160 domesticated chicken populations and their genetic distances to wild chicken populations. Results Our results show a strong inverse relationship, i.e. 88.6% of the variation in the overall genetic diversity of domesticated chicken populations was explained by their genetic distance to the wild populations. We also investigated whether the patterns of genetic diversity of different types of single nucleotide polymorphisms (SNPs) and genes are similar to that of the overall genome. Among the SNP classes, the non-synonymous SNPs deviated most from the overall genome. However, genetic distance to the wild chicken still explained more variation in domesticated chicken diversity across all SNP classes, which ranged from 83.0 to 89.3%. Conclusions Genetic distance between domesticated chicken populations and their wild relatives can predict the genetic diversity of the domesticated populations. On the one hand, genes with little genetic variation across populations, regardless of the genetic distance to the wild population, are associated with major functions such as brain development. Changes in such genes may be detrimental to the species. On the other hand, genetic diversity seems to change at a faster rate within genes that are associated with e.g. protein transport and protein and lipid metabolic processes. In general, such genes may be flexible to changes according to the populations’ needs. These results contribute to the knowledge of the evolutionary patterns of different functional genomic regions in the chicken. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-021-00628-z.
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Affiliation(s)
- Dorcus Kholofelo Malomane
- Animal Breeding and Genetics Group, Department of Animal Sciences, University of Goettingen, Goettingen, Germany. .,Center for Integrated Breeding Research, Department of Animal Sciences, University of Goettingen, Goettingen, Germany.
| | - Steffen Weigend
- Center for Integrated Breeding Research, Department of Animal Sciences, University of Goettingen, Goettingen, Germany.,Institute of Farm Animal Genetics, Friedrich-Loeffler-Institut, Neustadt, Germany
| | - Armin Otto Schmitt
- Center for Integrated Breeding Research, Department of Animal Sciences, University of Goettingen, Goettingen, Germany.,Breeding Informatics Group, Department of Animal Sciences, Georg August-Universität Goettingen, Goettingen, Germany
| | - Annett Weigend
- Institute of Farm Animal Genetics, Friedrich-Loeffler-Institut, Neustadt, Germany
| | - Christian Reimer
- Animal Breeding and Genetics Group, Department of Animal Sciences, University of Goettingen, Goettingen, Germany.,Center for Integrated Breeding Research, Department of Animal Sciences, University of Goettingen, Goettingen, Germany
| | - Henner Simianer
- Animal Breeding and Genetics Group, Department of Animal Sciences, University of Goettingen, Goettingen, Germany.,Center for Integrated Breeding Research, Department of Animal Sciences, University of Goettingen, Goettingen, Germany
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Cendron F, Mastrangelo S, Tolone M, Perini F, Lasagna E, Cassandro M. Genome-wide analysis reveals the patterns of genetic diversity and population structure of 8 Italian local chicken breeds. Poult Sci 2021; 100:441-451. [PMID: 33518095 PMCID: PMC7858015 DOI: 10.1016/j.psj.2020.10.023] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 10/16/2020] [Accepted: 10/22/2020] [Indexed: 12/25/2022] Open
Abstract
The aim of this study was to conduct a genome-wide comparative analysis of 8 local Italian chicken breeds (Ermellinata di Rovigo, Millefiori di Lonigo [PML], Polverara Bianca, Polverara Nera, Padovana, Pepoi [PPP], Robusta Lionata, and Robusta Maculata), all under a conservation plan, to understand their genetic diversity and population structure. A total of 152 animals were analyzed using the Affymetrix Axiom 600 K Chicken Genotyping Array. The levels of genetic diversity were highest and lowest in PML and PPP, respectively. The results of genomic inbreeding based on runs of homozygosity (ROH; FROH) showed marked differences among breeds and ranged from 0.161 (PML) to 0.478 (PPP). Furthermore, in all breeds, short ROH (<4 Mb in length) were more frequent than long segments. Patterns of genetic differentiation, model-based clustering, and neighbor networks showed that most breeds formed nonoverlapping clusters and were clearly separate populations. The 2 Polverara breeds shared a similar genetic background and showed the lowest genetic differentiation in comparison with purebred lines; the local populations showed separated groups. PPP and PML were closer to the group of the purebred broiler lines (BRSA, BRSB, BRDA, and BRDB). Six genomic regions are presented as hotspots of autozygosity among the Italian chicken breeds, with candidate genes involved in multiple morphological phenotypes as breast muscle, muscle dry matter content, and body weight. This study is the first exhaustive genome-wide analysis of the diversity of these Italian local chickens from Veneto region. We conclude that breeds have conserved authentic genetic patterns. The results are of significant importance because they will help design and implement conservation strategies. In fact, the conservation of these breeds may also have positive impacts on the local economy, niche traditional markets, and offering a source of high-quality products to consumers. In this context, genomic information may play a crucial role in the management of local breeds.
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Affiliation(s)
- F Cendron
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, 35020 Legnaro, PD, Italy.
| | - S Mastrangelo
- Department of Agricultural, Food and Forest Sciences, University of Palermo 90128 Palermo, PA, Italy
| | - M Tolone
- Department of Agricultural, Food and Forest Sciences, University of Palermo 90128 Palermo, PA, Italy
| | - F Perini
- Department of Agricultural, Food and Environmental Sciences, University of Perugia 06121 Perugia, PG, Italy
| | - E Lasagna
- Department of Agricultural, Food and Environmental Sciences, University of Perugia 06121 Perugia, PG, Italy
| | - M Cassandro
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, 35020 Legnaro, PD, Italy
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Abstract
Runs of homozygosity (ROH) are chromosomal stretches that in a diploid genome appear in a homozygous state and display identical alleles at multiple contiguous loci. This study aimed to systematically compare the genomic distribution of the ROH islands among five populations of wild vs commercial chickens of both layer and broiler type. To this end, we analyzed whole genome sequences of 115 birds including white layer (WL, n = 25), brown layer (BL, n = 25), broiler line A (BRA, n = 20), broiler line B (BRB, n = 20) and Red Junglefowl (RJF, n = 25). The ROH segments varied in size markedly among populations, ranging from 0.3 to 21.83 Mb reflecting their past genealogy. White layers contained the largest portion of the genome in homozygous state with an average ROH length of 432.1 Mb (±18.7) per bird, despite carrying it in short segments (0.3-1 Mb). Population-wise inbreeding measures based on Wright's (Fis) and genomic (FROH) metrics revealed highly inbred genome of layer lines relative to the broilers and Red Junglefowl. We further revealed the ROH islands, among commercial lines overlapped with QTL related to limb development (GREM1, MEOX2), body weight (Meis2a.1, uc_338), eggshell color (GLCCI1, ICA1, UMAD1), antibody response to Newcastle virus (ROBO2), and feather pecking. Comparison of ROH landscape in sequencing resolution demonstrated that a sizable portion of genome of commercial lines segregates in homozygote state, reflecting many generations of assortative mating and intensive selection in their recent history. In contrary, wild birds carry shorter ROH segments, likely suggestive of older evolutionary events.
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Schiavo G, Bovo S, Tinarelli S, Kazemi H, Gallo M, Dall'Olio S, Fontanesi L. Comparative population genomic analyses of the reconstructed local breed “Nero di Parma” with other commercial and autochthonous Italian pig breeds. Livest Sci 2020. [DOI: 10.1016/j.livsci.2020.104014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
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Sexual Dimorphism and Breed Characterization of Creole Hens through Biometric Canonical Discriminant Analysis across Ecuadorian Agroecological Areas. Animals (Basel) 2019; 10:ani10010032. [PMID: 31877907 PMCID: PMC7022707 DOI: 10.3390/ani10010032] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2019] [Revised: 12/16/2019] [Accepted: 12/18/2019] [Indexed: 11/17/2022] Open
Abstract
Simple Summary The first step towards the protection and valorization of the genetic resources of a country is their definition. Although Ecuadorian zootechnical species are very diverse, they are scarcely characterized, and hence the efforts towards their protection are not as fruitful as they could be. The present paper approaches the biometric characterization of the Creole hen population in Ecuador through the study of sexual dimorphism and the differentiation of an agroecologically-based structured population using fourteen zoometric measures as differentiation criteria. Highlands region provinces of Cotopaxi and Tungurahua were the most zoometrically distant from the rest. However, Morona Santiago province population in the Amazonian region slightly differs from those in Guayas, Chimborazo and Bolívar in the Coastal and Highlands regions, respectively. The dual-purpose nature of Ecuadorian Creole hen resources enables the implementation of breeding programs that seek meeting a wider scope of public demands, through the definition of the agroecologically-based breed differentiated production of local hen eggs and meat. Abstract Despite Ecuador having a wide biodiversity of zootechnical species, characterization studies of these genetic resources are scarce. The objective of this research was to perform the biometric characterization of the Creole hen population through 14 quantitative zoometric measures. We evaluated 207 hens and 37 roosters from Ecuador’s three agro-ecological regions: the Sierra (highlands) region (Bolivar, Chimborazo, Tungurahua and Cotopaxi provinces); the Costa (coastal) region (Guayas); and the Oriente Amazonian region (Morona Santiago). Sexual dimorphism was assessed using one-way analysis of variance (ANOVA). Body dimensions were generally significantly higher for males (p < 0.05), especially for length of head, beak, neck, dorsum, tarsus, thigh, leg, and middle finger. Then, individuals were biometrically clustered into populations after a stepwise canonical discriminant analysis (CDA) computing interpopulation Mahalanobis distances. Agroecologically-based structured populations were identified when zoometrical criteria were used to classify the animals. Cotopaxi and Tungurahua provinces were reported to be the most distant from the rest, with a slight differentiation of the Morona Santiago province population from those in Guayas, Chimborazo and Bolívar. Conclusively, Ecuadorian Creole hens were higher than longer contrasting light hen breeds, which favors their dual-purpose aptitude. Hence, the development of selection programs aimed at Ecuadorian differentiated entity of production of eggs and meat across agro-ecological areas is feasible.
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