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A New Approach for Accurate Detection of Chromosome Rearrangements That Affect Fertility in Cattle

SIMPLE SUMMARY: Globally, cattle production has more than doubled since the 1960s, with widespread use of artificial insemination (AI) and an emphasis on a small pool of high-genetic-merit animals. Selecting AI bulls with optimal fertility is therefore vital, as impaired fertility reduces genetic ga...

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Autores principales: Jennings, Rebecca L., Griffin, Darren K., O’Connor, Rebecca E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7023336/
https://www.ncbi.nlm.nih.gov/pubmed/31936776
http://dx.doi.org/10.3390/ani10010114
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author Jennings, Rebecca L.
Griffin, Darren K.
O’Connor, Rebecca E.
author_facet Jennings, Rebecca L.
Griffin, Darren K.
O’Connor, Rebecca E.
author_sort Jennings, Rebecca L.
collection PubMed
description SIMPLE SUMMARY: Globally, cattle production has more than doubled since the 1960s, with widespread use of artificial insemination (AI) and an emphasis on a small pool of high-genetic-merit animals. Selecting AI bulls with optimal fertility is therefore vital, as impaired fertility reduces genetic gains and reduces production, resulting in heavy financial and environmental losses. Chromosome translocations, where large parts of the genome are inappropriately attached in abnormal patterns, are a common cause of reduced fertility; however, reciprocal translocations are significantly underreported due to the difficulties inherent in analysing cattle chromosomes. Based on our previous work, we have developed an approach for the unambiguous detection of abnormalities that affect fertility. We applied this method on the chromosomes of 39 bulls, detecting multiple abnormalities that affect fertility, including those that would be undetectable using traditional screening techniques. With UK dairy calving rates of only 50–60%, it is vital to reduce further fertility loss in order to maximise productivity. The approach developed here identifies abnormalities that DNA sequencing will not, and has the potential to lead to long-term gains, delivering meat and milk products in a more cost-effective and environmentally-responsible manner to a growing population. ABSTRACT: Globally, cattle production has more than doubled since the 1960s, with widespread use of artificial insemination (AI) and an emphasis on a small pool of high genetic merit animals. Selecting AI bulls with optimal fertility is, therefore, vital, as impaired fertility reduces genetic gains and production, resulting in heavy financial and environmental losses. Chromosome translocations, particularly the 1;29 Robertsonian translocation, are a common cause of reduced fertility; however, reciprocal translocations are significantly underreported due to the difficulties inherent in analysing cattle chromosomes. Based on our porcine work, we have developed an approach for the unambiguous detection of Robertsonian and reciprocal translocations, using a multiple-hybridization probe detection strategy. We applied this method on the chromosomes of 39 bulls, detecting heterozygous and homozygous 1;29 translocations and a 12;23 reciprocal translocation in a total of seven animals. Previously, karyotype analysis was the only method of diagnosing chromosomal rearrangements in cattle, and was time-consuming and error-prone. With calving rates of only 50–60%, it is vital to reduce further fertility loss in order to maximise productivity. The approach developed here identifies abnormalities that DNA sequencing will not, and has the potential to lead to long-term gains, delivering meat and milk products in a more cost-effective and environmentally-responsible manner to a growing population.
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spelling pubmed-70233362020-03-12 A New Approach for Accurate Detection of Chromosome Rearrangements That Affect Fertility in Cattle Jennings, Rebecca L. Griffin, Darren K. O’Connor, Rebecca E. Animals (Basel) Technical Note SIMPLE SUMMARY: Globally, cattle production has more than doubled since the 1960s, with widespread use of artificial insemination (AI) and an emphasis on a small pool of high-genetic-merit animals. Selecting AI bulls with optimal fertility is therefore vital, as impaired fertility reduces genetic gains and reduces production, resulting in heavy financial and environmental losses. Chromosome translocations, where large parts of the genome are inappropriately attached in abnormal patterns, are a common cause of reduced fertility; however, reciprocal translocations are significantly underreported due to the difficulties inherent in analysing cattle chromosomes. Based on our previous work, we have developed an approach for the unambiguous detection of abnormalities that affect fertility. We applied this method on the chromosomes of 39 bulls, detecting multiple abnormalities that affect fertility, including those that would be undetectable using traditional screening techniques. With UK dairy calving rates of only 50–60%, it is vital to reduce further fertility loss in order to maximise productivity. The approach developed here identifies abnormalities that DNA sequencing will not, and has the potential to lead to long-term gains, delivering meat and milk products in a more cost-effective and environmentally-responsible manner to a growing population. ABSTRACT: Globally, cattle production has more than doubled since the 1960s, with widespread use of artificial insemination (AI) and an emphasis on a small pool of high genetic merit animals. Selecting AI bulls with optimal fertility is, therefore, vital, as impaired fertility reduces genetic gains and production, resulting in heavy financial and environmental losses. Chromosome translocations, particularly the 1;29 Robertsonian translocation, are a common cause of reduced fertility; however, reciprocal translocations are significantly underreported due to the difficulties inherent in analysing cattle chromosomes. Based on our porcine work, we have developed an approach for the unambiguous detection of Robertsonian and reciprocal translocations, using a multiple-hybridization probe detection strategy. We applied this method on the chromosomes of 39 bulls, detecting heterozygous and homozygous 1;29 translocations and a 12;23 reciprocal translocation in a total of seven animals. Previously, karyotype analysis was the only method of diagnosing chromosomal rearrangements in cattle, and was time-consuming and error-prone. With calving rates of only 50–60%, it is vital to reduce further fertility loss in order to maximise productivity. The approach developed here identifies abnormalities that DNA sequencing will not, and has the potential to lead to long-term gains, delivering meat and milk products in a more cost-effective and environmentally-responsible manner to a growing population. MDPI 2020-01-10 /pmc/articles/PMC7023336/ /pubmed/31936776 http://dx.doi.org/10.3390/ani10010114 Text en © 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/).
spellingShingle Technical Note
Jennings, Rebecca L.
Griffin, Darren K.
O’Connor, Rebecca E.
A New Approach for Accurate Detection of Chromosome Rearrangements That Affect Fertility in Cattle
title A New Approach for Accurate Detection of Chromosome Rearrangements That Affect Fertility in Cattle
title_full A New Approach for Accurate Detection of Chromosome Rearrangements That Affect Fertility in Cattle
title_fullStr A New Approach for Accurate Detection of Chromosome Rearrangements That Affect Fertility in Cattle
title_full_unstemmed A New Approach for Accurate Detection of Chromosome Rearrangements That Affect Fertility in Cattle
title_short A New Approach for Accurate Detection of Chromosome Rearrangements That Affect Fertility in Cattle
title_sort new approach for accurate detection of chromosome rearrangements that affect fertility in cattle
topic Technical Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7023336/
https://www.ncbi.nlm.nih.gov/pubmed/31936776
http://dx.doi.org/10.3390/ani10010114
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