Editorial

4 pages, 192 KiB

Open AccessEditorial

Application of Genetics and Genomics in Livestock Production

by Heather Burrow and Michael Goddard

Agriculture 2023, 13(2), 386; https://doi.org/10.3390/agriculture13020386 - 06 Feb 2023

Cited by 1 | Viewed by 2102

The delivery of genomic sequences for most livestock species over the past 10–15 years has generated the potential to revolutionize livestock production globally, by providing farmers with the ability to match individual animals to the requirements of rapidly changing climates, production systems and [...] Read more.

The delivery of genomic sequences for most livestock species over the past 10–15 years has generated the potential to revolutionize livestock production globally, by providing farmers with the ability to match individual animals to the requirements of rapidly changing climates, production systems and markets [...] Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

Research

Jump to: Editorial, Review, Other

20 pages, 1340 KiB

Open AccessFeature PaperArticle

Genetic Correlations between Days to Calving across Joinings and Lactation Status in a Tropically Adapted Composite Beef Herd

by Madeliene L. Facy, Michelle L. Hebart, Helena Oakey, Rudi A. McEwin and Wayne S. Pitchford

Agriculture 2023, 13(1), 37; https://doi.org/10.3390/agriculture13010037 - 22 Dec 2022

Cited by 3 | Viewed by 1421

Abstract

Female fertility is essential to any beef breeding program. However, little genetic gain has been made due to long generation intervals and low levels of phenotyping. Days to calving (DC) is a fertility trait that may provide genetic gain and lead to an [...] Read more.

Female fertility is essential to any beef breeding program. However, little genetic gain has been made due to long generation intervals and low levels of phenotyping. Days to calving (DC) is a fertility trait that may provide genetic gain and lead to an increased weaning rate. Genetic parameters and correlations were estimated and compared for DC across multiple joinings (first, second and third+) and lactation status (lactating and non-lactating) for a tropical composite cattle population where cattle were first mated as yearlings. The genetic correlation between first joining DC and mature joining DC (third+) was moderate–high (0.55–0.83). DC was uncorrelated between multiparous lactating and non-lactating cows (r_G = −0.10). Mature joining DC was more strongly correlated with second joining lactating DC (0.41–0.69) than with second joining non-lactating DC (−0.14 to −0.16). Thus, first joining DC, second joining DC and mature joining DC should be treated as different traits to maximise genetic gain. Further, for multi-parous cows, lactating and non-lactating DC should be treated as different traits. Three traits were developed to report back to the breeding programs to maximise genetic gain: the first joining days to calving, the second joining days to calving lactating and mature days to calving lactating. Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

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19 pages, 260 KiB

Open AccessArticle

Evolution of Genetics Organisations’ Strategies through the Implementation of Genomic Selection: Learnings and Prospects

by Robert Banks

Agriculture 2022, 12(10), 1524; https://doi.org/10.3390/agriculture12101524 - 22 Sep 2022

Cited by 4 | Viewed by 1403

Abstract

Since its initial description in 2001, and with falling costs of genotyping, genomic selection has been implemented in a wide range of species. Theory predicts that the genomic selection approach to genetic improvement offers scope both for faster progress and the opportunity to [...] Read more.

Since its initial description in 2001, and with falling costs of genotyping, genomic selection has been implemented in a wide range of species. Theory predicts that the genomic selection approach to genetic improvement offers scope both for faster progress and the opportunity to make change in traits formerly less tractable to selection (hard-to-measure traits). This paper reports a survey of organisations involved in genetic improvement, across species, countries, and roles both public and private. While there are differences across organisations in what have been the most significant outcomes to date, both the increased accuracy of breeding values that underpins potentially faster progress, and the re-balancing of genetic change to include real progress in the hard-to-measure traits, have been widely observed. Across organisations, learnings have included the increasing importance of investment in phenotyping, and opportunities to evolve business models to engage more directly with a wider range of stakeholders. Genomic selection can be considered a more modular approach to genetic improvement, and its simplicity and effectiveness can transform both genetic improvement and the effectiveness of multi-disciplinary approaches to improving livestock and plant production, enabling potentially very significant increases in agricultural productivity, profitability and sustainability. Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

14 pages, 2230 KiB

Open AccessArticle

Comprehensive Profiling of Circular RNAs in Goat Dermal Papilla Cells and Prediction of Their Modulatory Roles in Hair Growth

by Sen Ma, Xiaochun Xu, Xiaolong Wang, Yuxin Yang, Yinghua Shi and Yulin Chen

Agriculture 2022, 12(9), 1306; https://doi.org/10.3390/agriculture12091306 - 25 Aug 2022

Cited by 1 | Viewed by 1794

Abstract

Circular RNAs (circRNAs) are capable of finely modulating gene expression at transcriptional and post-transcriptional levels; however, their characters in dermal papilla cells (DPCs)—the signaling center of hair follicle—are still obscure. Herein, we established a comprehensive atlas of circRNAs in DPCs and their skin [...] Read more.

Circular RNAs (circRNAs) are capable of finely modulating gene expression at transcriptional and post-transcriptional levels; however, their characters in dermal papilla cells (DPCs)—the signaling center of hair follicle—are still obscure. Herein, we established a comprehensive atlas of circRNAs in DPCs and their skin counterparts—dermal fibroblasts (DFs)—from cashmere goats. In terms of the results, a sum of 3706 circRNAs were bioinformatically identified. Subsequent analysis suggested that the detected transcripts exhibited several prominent genomic features, including exons as their main sources. Compared with DFs, 76 circRNAs significantly displayed higher abundances in goat DPCs, with 45 transcripts markedly exhibiting adverse trends (p < 0.05). Furthermore, potential roles and underlying molecular mechanisms of circRNAs in goat DPCs were speculated through constructing their possible regulatory networks with mRNAs and microRNAs (miRNAs). We found that the circRNAs may serve as miRNA sponges to alleviate three hair growth-related functional genes (HOXC8, RSPO1, and CCBE1) of DPCs from miRNAs-imposed post-transcriptional modulation, further facilitating two critical processes (HOXC8 and RSPO1: hair follicle stem cell activation; CCBE1: follicular angiogenesis) closely involved in hair growth. In addition, we also speculated that two intron-derived circRNAs (chi_circ_0005569 and chi_circ_0005570) possibly affect the expression of their host gene CCBE1 at a transcriptional level in the nucleus. The above results demonstrated that circRNAs are abundantly expressed in goat DPCs, and certain circRNAs are potential participators in hair growth via the effects on the levels of related functional genes. Our study offers a preliminary clue for researchers hoping to untangle the roles of non-coding RNAs in hair growth. Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

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10 pages, 533 KiB

Open AccessArticle

Optimization of Dairy Cattle Breeding Programs with Genotype by Environment Interaction in Kenya

by Peter K. Wahinya, Gilbert M. Jeyaruban, Andrew A. Swan and Julius H. J. van der Werf

Agriculture 2022, 12(8), 1274; https://doi.org/10.3390/agriculture12081274 - 21 Aug 2022

Cited by 1 | Viewed by 1746

Abstract

Genotype by environment interaction influences the effectiveness of dairy cattle breeding programs in developing countries. This study aimed to investigate the optimization of dairy cattle breeding programs for three different environments within Kenya. Multi-trait selection index theory was applied using deterministic simulation in [...] Read more.

Genotype by environment interaction influences the effectiveness of dairy cattle breeding programs in developing countries. This study aimed to investigate the optimization of dairy cattle breeding programs for three different environments within Kenya. Multi-trait selection index theory was applied using deterministic simulation in SelAction software to determine the optimum strategy that would maximize genetic response for dairy cattle under low, medium, and high production systems. Four different breeding strategies were simulated: a single production system breeding program with progeny testing bulls in the high production system environment (HIGH); one joint breeding program with progeny testing bulls in three environments (JOINT); three environment-specific breeding programs each with testing of bulls within each environment (IND); and three environment-specific breeding programs each with testing of bulls within each environment using both phenotypic and genomic information (IND-GS). Breeding strategies were evaluated for the whole industry based on the predicted genetic response weighted by the relative size of each environment. The effect of increasing the size of the nucleus was also evaluated for all four strategies using 500, 1500, 2500, and 3000 cows in the nucleus. Correlated responses in the low and medium production systems when using a HIGH strategy were 18% and 3% lower, respectively, compared to direct responses achieved by progeny testing within each production system. The JOINT strategy with one joint breeding program with bull testing within the three production systems produced the highest response among the strategies using phenotypes only. The IND-GS strategy using phenotypic and genomic information produced extra responses compared to a similar strategy (IND) using phenotypes only, mainly due to a lower generation interval. Going forward, the dairy industry in Kenya would benefit from a breeding strategy involving progeny testing bulls within each production system. Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

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15 pages, 5470 KiB

Open AccessArticle

Time-Course Transcriptome Landscape of Bursa of Fabricius Development and Degeneration in Chickens

by Lan Huang, Yaodong Hu, Qixin Guo, Guobin Chang and Hao Bai

Agriculture 2022, 12(8), 1194; https://doi.org/10.3390/agriculture12081194 - 10 Aug 2022

Cited by 2 | Viewed by 1529

Abstract

The bursa of Fabricius (BF) is a target organ for various pathogenic microorganisms; however, the genes that regulate BF development and decline have not been fully characterized. Therefore, in this study, histological sections of the BF were obtained from black-boned chickens at 7 [...] Read more.

The bursa of Fabricius (BF) is a target organ for various pathogenic microorganisms; however, the genes that regulate BF development and decline have not been fully characterized. Therefore, in this study, histological sections of the BF were obtained from black-boned chickens at 7 (N7), 42 (N42), 90 (N90) and 120 days (N120) of age, and the differential expression and expression trends of the BF at different stages were analyzed by transcriptome analysis. The results showed that the growth of the BF progressively matured with age, followed by gradual shrinkage and disappearance. Transcriptome differential analysis revealed 5914, 5513, 4575, 577, 530 and 66 differentially expressed genes (DEG) in six different comparison groups: N7 vs. N42, N7 vs. N90, N7 vs. N120, N42 vs. N90, N42 vs. N120 and N90 vs. N120, respectively. Moreover, we performed transcriptomic analysis of the time series of BF development and identified the corresponding stages of biological process enrichment. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the expression of the 16 DEGs during bursal growth and development. These results were consistent with the transcriptome results, indicating that they reflect the expression of the BF during growth and development and that these genes reflect the characteristics of the BF at different times of development and decline. These findings reflect the characteristics of the BF at different time intervals. Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

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17 pages, 3654 KiB

Open AccessArticle

Positive Selection and Adaptive Introgression of Haplotypes from Bos indicus Improve the Modern Bos taurus Cattle

by Qianqian Zhang, Anna Amanda Schönherz, Mogens Sandø Lund and Bernt Guldbrandtsen

Agriculture 2022, 12(6), 844; https://doi.org/10.3390/agriculture12060844 - 11 Jun 2022

Cited by 3 | Viewed by 2139

Abstract

Complex evolutionary processes, such as positive selection and introgression can be characterized by in-depth assessment of sequence variation on a whole-genome scale. Here, we demonstrate the combined effects of positive selection and adaptive introgression on genomes, resulting in observed hotspots of runs of [...] Read more.

Complex evolutionary processes, such as positive selection and introgression can be characterized by in-depth assessment of sequence variation on a whole-genome scale. Here, we demonstrate the combined effects of positive selection and adaptive introgression on genomes, resulting in observed hotspots of runs of homozygosity (ROH) haplotypes on the modern bovine (Bos taurus) genome. We first confirm that these observed ROH hotspot haplotypes are results of positive selection. The haplotypes under selection, including genes of biological interest, such as PLAG1, KIT, CYP19A1 and TSHB, were known to be associated with productive traits in modern Bos taurus cattle breeds. Among the haplotypes under selection, we demonstrate that the CYP19A1 haplotype under selection was associated with milk yield, a trait under strong recent selection, demonstrating a likely cause of the selective sweep. We further deduce that selection on haplotypes containing KIT variants affecting coat color occurred approximately 250 generations ago. The study on the genealogies and phylogenies of these haplotypes identifies that the introgression events of the RERE and REG3G haplotypes happened from Bos indicus to Bos taurus. With the aid of sequencing data and evolutionary analyses, we here report introgression events in the formation of the current bovine genome. Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

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10 pages, 1079 KiB

Open AccessArticle

Accounting for Missing Pedigree Information with Single-Step Random Regression Test-Day Models

by Minna Koivula, Ismo Strandén, Gert P. Aamand and Esa A. Mäntysaari

Agriculture 2022, 12(3), 388; https://doi.org/10.3390/agriculture12030388 - 10 Mar 2022

Cited by 3 | Viewed by 1869

Abstract

Genomic selection is widely used in dairy cattle breeding, but still, single-step models are rarely used in national dairy cattle evaluations. New computing methods have allowed the utilization of very large genomic data sets. However, an unsolved model problem is how to build [...] Read more.

Genomic selection is widely used in dairy cattle breeding, but still, single-step models are rarely used in national dairy cattle evaluations. New computing methods have allowed the utilization of very large genomic data sets. However, an unsolved model problem is how to build genomic- (G) and pedigree- (A₂₂) relationship matrices that satisfy the theoretical assumptions about the same scale and equal base populations. Incompatibility issues have also been observed in the manner in which the genetic groups are included in the model. In this study, we compared three approaches for accounting for missing pedigree information: (1) GT_H used the full Quaas and Pollak (QP) transformation for the genetic groups, including both the pedigree-based and the genomic-relationship matrices, (2) GT_A₂₂ used the partial QP transformation that omitted QP transformation in G⁻¹, and (3) GT_MF used the metafounder approach. In addition to the genomic models, (4) an official animal model with a unknown parent groups (UPG) from the QP transformation and (5) an animal model with the metafounder approach were used for comparison. These models were tested with Nordic Holstein test-day production data and models. The test-day data included 8.5 million cows with a total of 173.7 million records and 10.9 million animals in the pedigree, and there were 274,145 genotyped animals. All models used VanRaden method 1 in G and had a 30% residual polygenic proportion (RPG). The G matrices in GT_H and GT_A₂₂ were scaled to have an average diagonal equal to that of A₂₂. Comparisons between the models were based on Mendelian sampling terms and forward prediction validation using linear regression with solutions from the full- and reduced-data evaluations. Models GT_H and GT_A₂₂ gave very similar results in terms of overprediction. The MF approach showed the lowest bias. Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

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10 pages, 836 KiB

Open AccessArticle

Comparison of Methods to Select Candidates for High-Density Genotyping; Practical Observations in a Cattle Breeding Program

by Rudi A. McEwin, Michelle L. Hebart, Helena Oakey, Rick Tearle, Joe Grose, Greg Popplewell and Wayne S. Pitchford

Agriculture 2022, 12(2), 276; https://doi.org/10.3390/agriculture12020276 - 15 Feb 2022

Cited by 3 | Viewed by 2165

Abstract

Imputation can be used to obtain a large number of high-density genotypes at the cost of procuring low-density panels. Accurate imputation requires a well-formed reference population of high-density genotypes to enable statistical inference. Five methods were compared using commercial Wagyu genotype data to [...] Read more.

Imputation can be used to obtain a large number of high-density genotypes at the cost of procuring low-density panels. Accurate imputation requires a well-formed reference population of high-density genotypes to enable statistical inference. Five methods were compared using commercial Wagyu genotype data to identify individuals to produce a “well-formed” reference population. Two methods utilised a relationship matrix (MCG and MCA), two of which utilised a haplotype block library (AHAP2 and IWS), and the last selected high influential sires with greater than 10 progeny (PROG). The efficacy of the methods was assessed based on the total proportion of genetic variance accounted for and the number of haplotypes captured, as well as practical considerations in implementing these methods. Concordance was high between the MCG and MCA and between AHAP2 and IWS but was low between these groupings. PROG-selected animals were most similar to MCA. MCG accounted for the greatest proportion of genetic variance in the population (35%, while the other methods accounted for approximately 30%) and the greatest number of unique haplotypes when a frequency threshold was applied. MCG was also relatively simple to implement, although modifications need to be made to account for DNA availability when running over a whole population. Of the methods compared, MCG is the recommended starting point for an ongoing sequencing project. Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

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13 pages, 1060 KiB

Open AccessArticle

OTUD7A Regulates Inflammation- and Immune-Related Gene Expression in Goose Fatty Liver

by Minmeng Zhao, Kang Wen, Xiang Fan, Qingyun Sun, Diego Jauregui, Mawahib K. Khogali, Long Liu, Tuoyu Geng and Daoqing Gong

Agriculture 2022, 12(1), 105; https://doi.org/10.3390/agriculture12010105 - 13 Jan 2022

Cited by 4 | Viewed by 2271

Abstract

OTU deubiquitinase 7A (OTUD7A) can suppress inflammation signaling pathways, but it is unclear whether the gene can inhibit inflammation in goose fatty liver. In order to investigate the functions of OTUD7A and identify the genes and pathways subjected to the regulation [...] Read more.

OTU deubiquitinase 7A (OTUD7A) can suppress inflammation signaling pathways, but it is unclear whether the gene can inhibit inflammation in goose fatty liver. In order to investigate the functions of OTUD7A and identify the genes and pathways subjected to the regulation of OTUD7A in the formation of goose fatty liver, we conducted transcriptomic analysis of cells, which revealed several genes related to inflammation and immunity that were significantly differentially expressed after OTUD7A overexpression. Moreover, the expression of interferon-induced protein with tetratricopeptide repeats 5 (IFIT5), tumor necrosis factor ligand superfamily member 8 (TNFSF8), sterile alpha motif domain-containing protein 9 (SAMD9), radical S-adenosyl methionine domain-containing protein 2 (RSAD2), interferon-induced GTP-binding protein Mx1 (MX1), and interferon-induced guanylate binding protein 1-like (GBP1) was inhibited by OTUD7A overexpression but induced by OTUD7A knockdown with small interfering RNA in goose hepatocytes. Furthermore, the mRNA expression of IFIT5, TNFSF8, SAMD9, RSAD2, MX1, and GBP1 was downregulated, whereas OTUD7A expression was upregulated in goose fatty liver after 12 days of overfeeding. In contrast, the expression patterns of these genes showed nearly the opposite trend after 24 days of overfeeding. Taken together, these findings indicate that OTUD7A regulates the expression of inflammation- and immune-related genes in the development of goose fatty liver. Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

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11 pages, 1487 KiB

Open AccessArticle

Estimation of Pool Construction and Technical Error

by John Keele, Tara McDaneld, Ty Lawrence, Jenny Jennings and Larry Kuehn

Agriculture 2021, 11(11), 1091; https://doi.org/10.3390/agriculture11111091 - 04 Nov 2021

Cited by 2 | Viewed by 1585

Abstract

Pooling animals with extreme phenotypes can improve the accuracy of genetic evaluation or provide genetic evaluation for novel traits at relatively low cost by exploiting large amounts of low-cost phenotypic data from animals in the commercial sector without pedigree (data from commercial ranches, [...] Read more.

Pooling animals with extreme phenotypes can improve the accuracy of genetic evaluation or provide genetic evaluation for novel traits at relatively low cost by exploiting large amounts of low-cost phenotypic data from animals in the commercial sector without pedigree (data from commercial ranches, feedlots, stocker grazing or processing plants). The average contribution of each animal to a pool is inversely proportional to the number of animals in the pool or pool size. We constructed pools with variable planned contributions from each animal to approximate errors with different numbers of animals per pool. We estimate pool construction error based on combining liver tissue, from pulverized frozen tissue mass from multiple animals, into eight sub-pools containing four animals with planned proportionality (1:2:3:4) by mass. Sub-pools were then extracted for DNA and genotyped using a commercial array. The extracted DNA from the sub-pools was used to form super pools based on DNA concentration as measured by spectrophotometry with planned contribution of sub-pools of 1:2:3:4. We estimate technical error by comparing estimated animal contribution using sub-samples of single nucleotide polymorphism (SNP). Overall, pool construction error increased with planned contribution of individual animals. Technical error in estimating animal contributions decreased with the number of SNP used. Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

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9 pages, 356 KiB

Open AccessArticle

Using Genomics to Measure Phenomics: Repeatability of Bull Prolificacy in Multiple-Bull Pastures

by Gary L. Bennett, John W. Keele, Larry A. Kuehn, Warren M. Snelling, Aaron M. Dickey, Darrell Light, Robert A. Cushman and Tara G. McDaneld

Agriculture 2021, 11(7), 603; https://doi.org/10.3390/agriculture11070603 - 28 Jun 2021

Cited by 3 | Viewed by 2046

Abstract

Phenotypes are necessary for genomic evaluations and management. Sometimes genomics can be used to measure phenotypes when other methods are difficult or expensive. Prolificacy of bulls used in multiple-bull pastures for commercial beef production is an example. A retrospective study of 79 bulls [...] Read more.

Phenotypes are necessary for genomic evaluations and management. Sometimes genomics can be used to measure phenotypes when other methods are difficult or expensive. Prolificacy of bulls used in multiple-bull pastures for commercial beef production is an example. A retrospective study of 79 bulls aged 2 and older used 141 times in 4–5 pastures across 4 years was used to estimate repeatability from variance components. Traits available before each season’s use were tested for predictive ability. Sires were matched to calves using individual genotypes and evaluating exclusions. A lower-cost method of measuring prolificacy was simulated for five pastures using the bulls’ genotypes and pooled genotypes to estimate average allele frequencies of calves and of cows. Repeatability of prolificacy was 0.62 ± 0.09. A combination of age-class and scrotal circumference accounted for less than 5% of variation. Simulated estimation of prolificacy by pooling DNA of calves was accurate. Adding pooling of cow DNA or actual genotypes both increased accuracy about the same. Knowing a bull’s prior prolificacy would help predict future prolificacy for management purposes and could be used in genomic evaluations and research with coordination of breeders and commercial beef producers. Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

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Review

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11 pages, 268 KiB

Open AccessFeature PaperReview

Identification of Genomic Variants Causing Variation in Quantitative Traits: A Review

by Theo Meuwissen, Ben Hayes, Iona MacLeod and Michael Goddard

Agriculture 2022, 12(10), 1713; https://doi.org/10.3390/agriculture12101713 - 17 Oct 2022

Cited by 7 | Viewed by 2018

Abstract

Many of the important traits of livestock are complex or quantitative traits controlled by thousands of variants in the DNA sequence of individual animals and environmental factors. Identification of these causal variants would be advantageous for genomic prediction, to understand the physiology and [...] Read more.

Many of the important traits of livestock are complex or quantitative traits controlled by thousands of variants in the DNA sequence of individual animals and environmental factors. Identification of these causal variants would be advantageous for genomic prediction, to understand the physiology and evolution of important traits and for genome editing. However, it is difficult to identify these causal variants because their effects are small and they are in linkage disequilibrium with other DNA variants. Nevertheless, it should be possible to identify probable causal variants for complex traits just as we do for simple traits provided we compensate for the small effect size with larger sample size. In this review we consider eight types of evidence needed to identify causal variants. Large and diverse samples of animals, accurate genotypes, multiple phenotypes, annotation of genomic sites, comparisons across species, comparisons across the genome, the physiological role of candidate genes and experimental mutation of the candidate genomic site. Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

25 pages, 1472 KiB

Open AccessReview

Promoting Sustainable Utilization and Genetic Improvement of Indonesian Local Beef Cattle Breeds: A Review

by Nuzul Widyas, Tri Satya Mastuti Widi, Sigit Prastowo, Ika Sumantri, Ben J. Hayes and Heather M. Burrow

Agriculture 2022, 12(10), 1566; https://doi.org/10.3390/agriculture12101566 - 28 Sep 2022

Cited by 8 | Viewed by 4357

Abstract

This paper reviews the literature relevant to the breeding of cattle grazed in tropical environments and particularly Indonesia. The aim is to identify new breeding opportunities for cattle owned by Indonesia’s smallholder farmers, whilst also conserving unique local cattle beef breeds. Crossbreeding has [...] Read more.

This paper reviews the literature relevant to the breeding of cattle grazed in tropical environments and particularly Indonesia. The aim is to identify new breeding opportunities for cattle owned by Indonesia’s smallholder farmers, whilst also conserving unique local cattle beef breeds. Crossbreeding has been practiced extensively in Indonesia, but to date there have been no well-designed programs, resulting in many mixed-breed animals and no ability to determine their genetic composition, productive capabilities or adaptation to environmental stressors. An example of within-breed selection of Bali cattle based on measured live weight has similarly disregarded other productive and adaptive traits. It is unlikely that smallholder farmers could manage effective crossbreeding programs due to the complexities of management required. However, a tropically adapted composite breed(s) could perhaps be developed and improved using within-breed selection. Establishing reference population(s) of local breeds or composites and using within-breed selection to genetically improve those herds may be feasible, particularly if international collaborations can be established to allow data-pooling across countries. The use of genomic information and a strong focus on all economically important traits in practical breeding objectives is critical to enable genetic improvement and conservation of unique Indonesian cattle breeds. Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

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Other

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15 pages, 311 KiB

Open AccessPerspective

Challenges and Opportunities in Applying Genomic Selection to Ruminants Owned by Smallholder Farmers

by Heather M. Burrow, Raphael Mrode, Ally Okeyo Mwai, Mike P. Coffey and Ben J. Hayes

Agriculture 2021, 11(11), 1172; https://doi.org/10.3390/agriculture11111172 - 20 Nov 2021

Cited by 8 | Viewed by 3489

Abstract

Genomic selection has transformed animal and plant breeding in advanced economies globally, resulting in economic, social and environmental benefits worth billions of dollars annually. Although genomic selection offers great potential in low- to middle-income countries because detailed pedigrees are not required to estimate [...] Read more.

Genomic selection has transformed animal and plant breeding in advanced economies globally, resulting in economic, social and environmental benefits worth billions of dollars annually. Although genomic selection offers great potential in low- to middle-income countries because detailed pedigrees are not required to estimate breeding values with useful accuracy, the difficulty of effective phenotype recording, complex funding arrangements for a limited number of essential reference populations in only a handful of countries, questions around the sustainability of those livestock-resource populations, lack of on-farm, laboratory and computing infrastructure and lack of human capacity remain barriers to implementation. This paper examines those challenges and explores opportunities to mitigate or reduce the problems, with the aim of enabling smallholder livestock-keepers and their associated value chains in low- to middle-income countries to also benefit directly from genomic selection. Full article

(This article belongs to the Special Issue Application of Genetics and Genomics in Livestock Production)

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