The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection
Open accessAbstract
Significance: The introduction of genomic selection in dairy cattle improvement programs in 2008 was expected to increase rates of genetic gain, particularly for traits with low heritabilities, such as fertility and longevity. Our analysis of the US national dairy database found that generation intervals have decreased dramatically over the past 6 y, and selection intensity for lowly heritable traits has increased considerably. Genetic trends rapidly increased for fertility, lifespan, and udder health. These results clearly demonstrate the positive impact of genomic selection in US dairy cattle, even though this technology has only been in use for a short time. This progress in US Holsteins will have a favorable impact on other populations worldwide due to the widespread dissemination of US germplasm.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Introduction to Quantitative Genetics.
Edwards, A. W. F., & Falconer, D. S. (1982) · Biometrics · doi:10.2307/2529912 · Cited by 21,447
Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps
Meuwissen, T. H. E., Hayes, B. J., & Goddard, M. E. (2001) · Genetics · doi:10.1093/genetics/157.4.1819 · Cited by 7,917
Permutation tests for joinpoint regression with applications to cancer rates
Kim, H.-J., Fay, M. P., Feuer, E. J., & Midthune, D. N. (2000) · Statistics in Medicine · doi:10.1002/(sici)1097-0258(20000215)19:3<335::aid-sim336>3.0.co;2-z · Cited by 6,318
Sheep cloned by nuclear transfer from a cultured cell line
Campbell, K. H. S., McWhir, J., Ritchie, W. A., & Wilmut, I. (1996) · Nature · doi:10.1038/380064a0 · Cited by 1,844
Invited review: Genomic selection in dairy cattle: Progress and challenges
Hayes, B. J., Bowman, P. J., Chamberlain, A. J., & Goddard, M. E. (2009) · Journal of Dairy Science · doi:10.3168/jds.2008-1646 · Cited by 1,795
Aguilar, I., Misztal, I., Johnson, D. L., Legarra, A., Tsuruta, S., & Lawlor, T. J. (2010) · Journal of Dairy Science · doi:10.3168/jds.2009-2730 · Cited by 1,491
Reproductive Loss in High-Producing Dairy Cattle: Where Will It End?
Lucy, M. C. (2001) · Journal of Dairy Science · doi:10.3168/jds.s0022-0302(01)70158-0 · Cited by 1,485
Invited Review: Reliability of genomic predictions for North American Holstein bulls
VanRaden, P. M., Van Tassell, C. P., Wiggans, G. R., Sonstegard, T. S., Schnabel, R. D., Taylor, J. F., & Schenkel, F. S. (2009) · Journal of Dairy Science · doi:10.3168/jds.2008-1514 · Cited by 1,331
Self-citationStrategy for applying genome‐wide selection in dairy cattle
Schaeffer, L. R. (2006) · Journal of Animal Breeding and Genetics · doi:10.1111/j.1439-0388.2006.00595.x · Cited by 861
Economic aspects of mastitis: New developments
Hogeveen, H., Huijps, K., & Lam, T. (2011) · New Zealand Veterinary Journal · doi:10.1080/00480169.2011.547165 · Cited by 565
Cited by
De novo assembly of the cattle reference genome with single-molecule sequencing
Rosen, B. D., Bickhart, D. M., Schnabel, R. D., Koren, S., Elsik, C. G., Tseng, E., Rowan, T. N., Low, W. Y., Zimin, A., Couldrey, C., et al. (2020) · GigaScience · doi:10.1093/gigascience/giaa021 · Cited by 802
Large-scale ruminant genome sequencing provides insights into their evolution and distinct traits
Chen, L., Qiu, Q., Jiang, Y., Wang, K., Lin, Z., Li, Z., Bibi, F., Yang, Y., Wang, J., Nie, W., et al. (2019) · Science · doi:10.1126/science.aav6202 · Cited by 441
Accelerating crop genetic gains with genomic selection
Voss-Fels, K. P., Cooper, M., & Hayes, B. J. (2019) · Theoretical and Applied Genetics · doi:10.1007/s00122-018-3270-8 · Cited by 381
Harnessing genomic information for livestock improvement
Georges, M., Charlier, C., & Hayes, B. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-018-0082-2 · Cited by 384
Enhancing Genetic Gain through Genomic Selection: From Livestock to Plants
Xu, Y., Liu, X., Fu, J., Wang, H., Wang, J., Huang, C., Prasanna, B. M., Olsen, M. S., Wang, G., & Zhang, A. (2020) · Plant Communications · doi:10.1016/j.xplc.2019.100005 · Cited by 281
Metadata
- Authors
- García-Ruiz, A., Cole, J. B., VanRaden, P. M., Wiggans, G. R., Ruiz-López, F. J., & Van Tassell, C. P.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2016-06-27
- Volume
- 113
- Issue
- 28
- Pages
- E3995-4004
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2474436508
- Cited by
- 573
- References
- 26
- FWCI
- 33.02
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection. https://app.cochat.ai/papers/10.1073/pnas.1519061113
- The paper
- García-Ruiz, A., Cole, J. B., VanRaden, P. M., Wiggans, G. R., Ruiz-López, F. J., & Van Tassell, C. P. (2016). Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1519061113
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
