horse - PMC

Hongying Ma, Sheng Wang, Guorong Zeng, Jintu Guo, Minghao Guo, Xianggui Dong, Guoying Hua, Yu Liu, Min Wang, Yao Ling, Xiangdong Ding, Chunjiang Zhao, Changxin Wu

Genes (Basel) 2019 Mar; 10(3): 241. Published online 2019 Mar 21. doi: 10.3390/genes10030241

PMCID:: PMC6471023

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Welfare of equidae during transport

EFSA Panel on Animal Health and Welfare (AHAW), Søren Saxmose Nielsen, Julio Alvarez, Dominique Joseph Bicout, Paolo Calistri, Elisabetta Canali, Julian Ashley Drewe, Bruno Garin‐Bastuji, Jose Luis Gonzales Rojas, Christian Gortázar Schmidt, Virginie Michel, Miguel Ángel Miranda Chueca, Barbara Padalino, Paolo Pasquali, Helen Clare Roberts, Hans Spoolder, Karl Stahl, Antonio Velarde, Arvo Viltrop, Christoph Winckler, Bernadette Earley, Sandra Edwards, Luigi Faucitano, Sonia Marti, Genaro C Miranda de La Lama, Leonardo Nanni Costa, Peter T Thomsen, Sean Ashe, Lina Mur, Yves Van der Stede, Mette Herskin

EFSA J. 2022 Sep; 20(9): e07444. Published online 2022 Sep 7. doi: 10.2903/j.efsa.2022.7444

PMCID:: PMC9449990

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Whole-Genome Sequence Analysis Reveals the Origin of the Chakouyi Horse

Ying Li, Yu Liu, Min Wang, Xiaoran Lin, Yuanyuan Li, Tao Yang, Mo Feng, Yao Ling, Chunjiang Zhao

Genes (Basel) 2022 Dec; 13(12): 2411. Published online 2022 Dec 19. doi: 10.3390/genes13122411

PMCID:: PMC9778315

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Horses as Sentinels for the Circulation of Flaviviruses in Eastern–Central Germany

Leonard M. R. Gothe, Stefanie Ganzenberg, Ute Ziegler, Anna Obiegala, Katharina L. Lohmann, Michael Sieg, Thomas W. Vahlenkamp, Martin H. Groschup, Uwe Hörügel, Martin Pfeffer

Viruses. 2023 May; 15(5): 1108. Published online 2023 Apr 30. doi: 10.3390/v15051108

PMCID:: PMC10222594

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Relationship between anatomical characteristics and personality traits in Lipizzan horses

Nataša Debeljak, Aljaž Košmerlj, Jordi Altimiras, Manja Zupan Šemrov

Sci Rep. 2022; 12: 12618. Published online 2022 Jul 23. doi: 10.1038/s41598-022-16627-z

PMCID:: PMC9308772

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Body Condition Score in Danish Horses Related to Type, Use, and Training Level: Patterns, Risk, and Protective Factors

Mette Uldahl, Jan Dahl, Hilary Mary Clayton

Animals (Basel) 2023 Apr; 13(7): 1219. Published online 2023 Mar 31. doi: 10.3390/ani13071219

PMCID:: PMC10093332

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A genome-wide scan for diversifying selection signatures in selected horse breeds

Artur Gurgul, Igor Jasielczuk, Ewelina Semik-Gurgul, Klaudia Pawlina-Tyszko, Monika Stefaniuk-Szmukier, Tomasz Szmatoła, Grażyna Polak, Iwona Tomczyk-Wrona, Monika Bugno-Poniewierska

PLoS One. 2019; 14(1): e0210751. Published online 2019 Jan 30. doi: 10.1371/journal.pone.0210751

PMCID:: PMC6353161

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Tracking Five Millennia of Horse Management with Extensive Ancient Genome Time Series

Antoine Fages, Kristian Hanghøj, Naveed Khan, Charleen Gaunitz, Andaine Seguin-Orlando, Michela Leonardi, Christian McCrory Constantz, Cristina Gamba, Khaled A.S. Al-Rasheid, Silvia Albizuri, Ahmed H. Alfarhan, Morten Allentoft, Saleh Alquraishi, David Anthony, Nurbol Baimukhanov, James H. Barrett, Jamsranjav Bayarsaikhan, Norbert Benecke, Eloísa Bernáldez-Sánchez, Luis Berrocal-Rangel, Fereidoun Biglari, Sanne Boessenkool, Bazartseren Boldgiv, Gottfried Brem, Dorcas Brown, Joachim Burger, Eric Crubézy, Linas Daugnora, Hossein Davoudi, Peter de Barros Damgaard, María de los Ángeles de Chorro y de Villa-Ceballos, Sabine Deschler-Erb, Cleia Detry, Nadine Dill, Maria do Mar Oom, Anna Dohr, Sturla Ellingvåg, Diimaajav Erdenebaatar, Homa Fathi, Sabine Felkel, Carlos Fernández-Rodríguez, Esteban García-Viñas, Mietje Germonpré, José D. Granado, Jón H. Hallsson, Helmut Hemmer, Michael Hofreiter, Aleksei Kasparov, Mutalib Khasanov, Roya Khazaeli, Pavel Kosintsev, Kristian Kristiansen, Tabaldiev Kubatbek, Lukas Kuderna, Pavel Kuznetsov, Haeedeh Laleh, Jennifer A. Leonard, Johanna Lhuillier, Corina Liesau von Lettow-Vorbeck, Andrey Logvin, Lembi Lõugas, Arne Ludwig, Cristina Luis, Ana Margarida Arruda, Tomas Marques-Bonet, Raquel Matoso Silva, Victor Merz, Enkhbayar Mijiddorj, Bryan K. Miller, Oleg Monchalov, Fatemeh A. Mohaseb, Arturo Morales, Ariadna Nieto-Espinet, Heidi Nistelberger, Vedat Onar, Albína H. Pálsdóttir, Vladimir Pitulko, Konstantin Pitskhelauri, Mélanie Pruvost, Petra Rajic Sikanjic, Anita Rapan Papeša, Natalia Roslyakova, Alireza Sardari, Eberhard Sauer, Renate Schafberg, Amelie Scheu, Jörg Schibler, Angela Schlumbaum, Nathalie Serrand, Aitor Serres-Armero, Beth Shapiro, Shiva Sheikhi Seno, Irina Shevnina, Sonia Shidrang, John Southon, Bastiaan Star, Naomi Sykes, Kamal Taheri, William Taylor, Wolf-Rüdiger Teegen, Tajana Trbojević Vukičević, Simon Trixl, Dashzeveg Tumen, Sainbileg Undrakhbold, Emma Usmanova, Ali Vahdati, Silvia Valenzuela-Lamas, Catarina Viegas, Barbara Wallner, Jaco Weinstock, Victor Zaibert, Benoit Clavel, Sébastien Lepetz, Marjan Mashkour, Agnar Helgason, Kári Stefánsson, Eric Barrey, Eske Willerslev, Alan K. Outram, Pablo Librado, Ludovic Orlando

Cell. 2019 May 30; 177(6): 1419–1435.e31. doi: 10.1016/j.cell.2019.03.049

PMCID:: PMC6547883

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Select item 985517913.

Horse Housing on Prince Edward Island, Canada: Attitudes and Experiences Related to Keeping Horses Outdoors and in Groups

Megan Ross, Kathryn Proudfoot, Katrina Merkies, Ibrahim Elsohaby, Molly Mills, Kathleen Macmillan, Shawn Mckenna, Caroline Ritter

Animals (Basel) 2023 Jan; 13(2): 275. Published online 2023 Jan 13. doi: 10.3390/ani13020275

PMCID:: PMC9855179

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Development and Validation of a Test for the Classification of Horses as Broken or Unbroken

Laura Menchetti, Emanuela Dalla Costa, Michela Minero, Barbara Padalino

Animals (Basel) 2021 Aug; 11(8): 2303. Published online 2021 Aug 4. doi: 10.3390/ani11082303

PMCID:: PMC8388372

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The Genomic Makeup of Nine Horse Populations Sampled in the Netherlands

Anouk Schurink, Merina Shrestha, Susanne Eriksson, Mirte Bosse, Henk Bovenhuis, Willem Back, Anna M. Johansson, Bart J. Ducro

Genes (Basel) 2019 Jun; 10(6): 480. Published online 2019 Jun 25. doi: 10.3390/genes10060480

PMCID:: PMC6627704

Article PDF–7.0M

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Between Leisure and Pressure—Veterinarians’ Attitudes towards the Care of Competition Horses in Germany, Austria and Switzerland

Svenja Springer, Denise Isabell Mihatsch, Herwig Grimm, Florien Jenner

Animals (Basel) 2023 Jul; 13(13): 2126. Published online 2023 Jun 27. doi: 10.3390/ani13132126

PMCID:: PMC10339975

Article PDF–293K

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Population Genetic Analysis of the Estonian Native Horse Suggests Diverse and Distinct Genetics, Ancient Origin and Contribution from Unique Patrilines

Caitlin Castaneda, Rytis Juras, Anas Khanshour, Ingrid Randlaht, Barbara Wallner, Doris Rigler, Gabriella Lindgren, Terje Raudsepp, E. Gus Cothran

Genes (Basel) 2019 Aug; 10(8): 629. Published online 2019 Aug 20. doi: 10.3390/genes10080629

PMCID:: PMC6722507

Article PDF–2.6M

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A Relaxed Horse—A Relaxed Client? An Experimental Investigation of the Effects of Therapy Horses’ Stress on Clients’ Stress, Mood, and Anxiety

Alicia Müller-Klein, Moritz Nicolai Braun, Diana S. Ferreira de Sá, Tanja Michael, Ulrike Link-Dorner, Johanna Lass-Hennemann

Animals (Basel) 2024 Feb; 14(4): 604. Published online 2024 Feb 13. doi: 10.3390/ani14040604

PMCID:: PMC10886220

Article PDF–3.9M

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Horse Preferences for Insolation, Shade or Mist Curtain in the Paddock under Heat Conditions: Cardiac and Behavioural Response Analysis

Iwona Janczarek, Anna Stachurska, Izabela Wilk, Anna Wiśniewska, Monika Różańska-Boczula, Beata Kaczmarek, Jarosław Łuszczyński, Witold Kędzierski

Animals (Basel) 2021 Apr; 11(4): 933. Published online 2021 Mar 25. doi: 10.3390/ani11040933

PMCID:: PMC8064440

Article PDF–641K

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Evaluation of podocin in urine in horses using qualitative and quantitative methods

Natalia Siwińska, Urszula Pasławska, Remigiusz Bąchor, Barbara Szczepankiewicz, Agnieszka Żak, Paulina Grocholska, Zbigniew Szewczuk

PLoS One. 2020; 15(10): e0240586. Published online 2020 Oct 15. doi: 10.1371/journal.pone.0240586

PMCID:: PMC7561189

Article PDF–1.2M

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Figure 1Scaffolds of Y chromosome of wild horse and Mongolian horse.

Thirty-four scaffolds of wild horse and 48 scaffolds of Mongolian horse are shown in this figure, and collinearity regions are linked. Numbers located outside of the brackets are the scaffolds ID of wild horse (carmine) and Mongolian horse (green). Numbers located inside of the brackets represent count of markers detected in the scaffolds.

Analysis of horse genomes provides insight into the diversification and adaptive evolution of karyotype

Sci Rep. 2014;4:4958.
Figure 6

A neighbor-joining tree based on a distance matrix constructed in PLINK (version 1.9) [,] using genotype data of 184 horses from 9 populations sampled in the Netherlands. Each color represents a population: black = Friesian horse population, pink = Belgian draft horse population, yellow = Icelandic horse population, dark blue = Shetland pony population, red = Lipizzaner horse population, light blue = Gelder horse population, orange = harness horse population, grey = KWPN sport horse population and green = Groninger horse population. The arrows indicate the Groninger horse within the KWPN sport horse population clade and the KWPN sport horse within the Groninger horse population clade.

The Genomic Makeup of Nine Horse Populations Sampled in the Netherlands

Genes (Basel). 2019 Jun;10(6):480.
Figure 1

Geographic distribution of the Chinese horses studied. IMG, Mongolian horse; DA, Daan horse; CKY, Chakouyi horse; NQ, Naqu horse; KZK, Kazakh Horse; BS, Baise horse; JJ, Jinjiang horse; TC, Tengchong horse; ZT, Zhaotong horse; LJ, Lijiang horse. Red dots indicate the breeds in South China; black dots, the horses in North China. (The map was configured using R Packages).

The Origin of a Coastal Indigenous Horse Breed in China Revealed by Genome-Wide SNP Data

Genes (Basel). 2019 Mar;10(3):241.
Figure 2

Genetic relationships among the Jinjiang horse and 23 other horse populations and their population structures. (A) Relationships among the Jinjiang horse and the worldwide horse populations, illustrated by a neighbor-joining tree. The populations studied are indicated with different colors and the names of the breeds. Five donkeys were used as an outgroup. The neighbor-joining tree was constructed with 580 individuals from 10 Chinese indigenous horse breeds and 14 foreign horse populations, using 39,187 filtered single nucleotide polymorphisms (SNPs) per sample. (B) ADMIXTURE analysis of the Jinjiang horse and the worldwide horse populations. Results with K = 15 hypothetical ancestral populations. Each column indicates an individual. The column group represents a horse population. (C) Principal components analysis for the Jinjiang horses and the worldwide horse populations. The Chinese indigenous horse breeds and foreign horse populations are represented with different symbols (circles and triangles, respectively). The populations studied are indicated with different colors. (D) Migrations detected among the foreign and Chinese horse breeds studied by the TreeMix program with six migration events.

The Origin of a Coastal Indigenous Horse Breed in China Revealed by Genome-Wide SNP Data

Genes (Basel). 2019 Mar;10(3):241.