Molecular identification of livestock breeds: a tool for modern conservation biology

Analysing the genetic diversity and population structure of five native Turkish cattle breeds using SNP data

The conservation and sustainable utilization of cattle genetic resources necessitate a comprehensive understanding of their genetic diversity and population structure. This study provides an analysis of five native Turkish cattle breeds: Anatolian Black (ANB), Turkish Grey (TUR), Anatolian Southern Yellow (ASY), East Anatolian Red (EAR), and South Anatolian Red (SAN) using 50 K SNP data. These breeds were compared with three European breeds, Simmental (SIM), Holstein (HOL), and Jersey (JER), and three Asian Zebu breeds: Arabic Zebu (ZAR), Nelore (NEL), and Red Sindhi (RSI). Genetic diversity indices demonstrated moderate heterogeneity among the breeds, with TUR exhibiting the highest observed heterozygosity (Ho = 0.35). Wright's Fst values indicated significant genetic differentiation, particularly between Turkish breeds and both European (Fst = 0.035-0.071) and Asian breeds (Fst = 0.025-0.150). Principal component analysis distinguished the unique genetic profiles of each breed cluster. Admixture analysis revealed degrees of shared genetic ancestry, suggesting historical gene flow between Turkish, European, and Asian breeds. Analysis of molecular variance (AMOVA) attributed approximately 58% of the variation to population differences. Nei's genetic distances highlighted the closer genetic relatedness within Turkish breeds (distance ranges between 0.032 and 0.046) and suggested a more relative affinity of TUR with European breeds. The study's phylogenetic assessments elucidate the nuanced genetic relationships among these breeds, with runs of homozygosity (ROH) analysis indicating patterns of ancestral relatedness and moderate levels of inbreeding, particularly evident in Turkish breeds. Our findings provide valuable insights into the genetic landscape of Turkish cattle, offering a crucial foundation for informed conservation and breeding strategies aimed at preserving these breeds' genetic integrity and heritage.

Evaluation of six machine learning classification algorithms in pig breed identification using SNPs array data

Breed identification utilizing multiple information sources and methods is widely applicated in the field of animal genetics and breeding. Simultaneously, with the development of artificial intelligence, the integration of high-throughput genomic data and machine learning techniques is increasingly used for breed identification. In this context, we used 654 individuals from 15 pig breeds, evaluating the performance of machine learning and stacking ensemble learning classifiers, as well as the function of feature selection and anomaly detection in different scenarios. Our results showed that, when using a training set of 16 individuals per breed and 32 features (SNPs), the accuracy of breed identification with feature selection (eXtreme Gradient Boosting, XGBoost) could exceed 95.00% (nine breeds), and was improved by 7.04% over the results with random selection. For stacking ensemble learning, feature selection methods (including random selection method) were used before different base learners. When these base learners' training set had 16 individuals per breed and 32 features, the accuracy of stacking ensemble learning improved by 9.24% over the best base learner (nine breeds), but did not significantly increase the advantage over the models with XGBoost feature selection. When using a training set of 16 individuals and 512 features per breed, breed identification with anomaly detection (local outlier factor, LOF) and random selection could achieve an accuracy of 89.06% (15 breeds). These results show that machine learning could be an effective tool for breed identification and this study will also provide useful information for the application of machine learning in animal genetics and breeding.

A web tool for the global identification of pig breeds

BACKGROUND

Natural and artificial selection for more than 9000 years have led to a variety of domestic pig breeds. Accurate identification of pig breeds is important for breed conservation, sustainable breeding, pork traceability, and local resource registration.

RESULTS

We evaluated the performance of four selectors and six classifiers for breed identification using a wide range of pig breeds (N = 91). The internal cross-validation and external independent testing showed that partial least squares regression (PLSR) was the most effective selector and partial least squares-discriminant analysis (PLS-DA) was the most powerful classifier for breed identification among many breeds. Five-fold cross-validation indicated that using PLSR as the selector and PLS-DA as the classifier to discriminate 91 pig breeds yielded 98.4% accuracy with only 3K single nucleotide polymorphisms (SNPs). We also constructed a reference dataset with 124 pig breeds and used it to develop the web tool iDIGs ( http://alphaindex.zju.edu.cn/iDIGs_en/ ) as a comprehensive application for global pig breed identification. iDIGs allows users to (1) identify pig breeds without a reference population and (2) design small panels to discriminate several specific pig breeds.

CONCLUSIONS

In this study, we proved that breed identification among a wide range of pig breeds is feasible and we developed a web tool for such pig breed identification.

Quality matters: International standards for biobanking

Human biospecimens provide the basis for research, leading to a better understanding of human disease biology and discovery of new treatments that are tailored to individual patients with cancer or other common complex diseases. The collection, processing, preservation, storage and providing access to these resources are key activities of biobanks. Biobanks must ensure proper quality of samples and data, ethical and legal compliance as well as transparent and efficient access procedures. The standards for biobanking outlined herein are intended to be implemented in biobanks and to supply researchers with high‐quality samples fitted for an intended use.

An Overview of the Use of Genotyping Techniques for Assessing Genetic Diversity in Local Farm Animal Breeds

Simple Summary

The number of local farm animal breeds is declining worldwide. However, these breeds have different degrees of genetic diversity. Measuring genetic diversity is important for the development of conservation strategies and, therefore, various genomic analysis techniques are available. The aim of the present work was to shed light on the use of these techniques in diversity studies of local breeds. In summary, a total of 133 worldwide studies that examined genetic diversity in local cattle, sheep, goat, chicken and pig breeds were reviewed. The results show that over time, almost all available genomic techniques were used and various diversity parameters were calculated. Therefore, the present results provide a comprehensive overview of the application of these techniques in the field of local breeds. This can provide helpful insights into the advancement of the conservation of breeds with high genetic diversity.

Abstract

Globally, many local farm animal breeds are threatened with extinction. However, these breeds contribute to the high amount of genetic diversity required to combat unforeseen future challenges of livestock production systems. To assess genetic diversity, various genotyping techniques have been developed. Based on the respective genomic information, different parameters, e.g., heterozygosity, allele frequencies and inbreeding coefficient, can be measured in order to reveal genetic diversity between and within breeds. The aim of the present work was to shed light on the use of genotyping techniques in the field of local farm animal breeds. Therefore, a total of 133 studies across the world that examined genetic diversity in local cattle, sheep, goat, chicken and pig breeds were reviewed. The results show that diversity of cattle was most often investigated with microsatellite use as the main technique. Furthermore, a large variety of diversity parameters that were calculated with different programs were identified. For 15% of the included studies, the used genotypes are publicly available, and, in 6%, phenotypes were recorded. In conclusion, the present results provide a comprehensive overview of the application of genotyping techniques in the field of local breeds. This can provide helpful insights to advance the conservation of breeds.

Genomic Characteristics and Selection Signatures in Indigenous Chongming White Goat (Capra hircus)

The Chongming white goat (CM) is an indigenous goat breed exhibits unique traits that are adapted to the local environment and artificial selection. By performing whole-genome re-sequencing, we generated 14–20× coverage sequences from 10 domestic goat breeds to explore the genomic characteristics and selection signatures of the CM breed. We identified a total of 23,508,551 single-nucleotide polymorphisms (SNPs) and 2,830,800 insertion–deletion mutations (indels) after read mapping and variant calling. We further specifically identified 1.2% SNPs (271,713) and 0.9% indels (24,843) unique to the CM breed in comparison with the other nine goat breeds. Missense (SIFT < 0.05), frameshift, splice-site, start-loss, stop-loss, and stop-gain variants were identified in 183 protein-coding genes of the CM breed. Of the 183, 36 genes, including AP4E1, FSHR, COL11A2, and DYSF, are involved in phenotype ontology terms related to the nervous system, short stature, and skeletal muscle morphology. Moreover, based on genome-wide F_ST and pooled heterozygosity (Hp) calculation, we further identified selection signature genes between the CM and the other nine goat breeds. These genes are significantly associated with the nervous system (C2CD3, DNAJB13, UCP2, ZMYND11, CEP126, SCAPER, and TSHR), growth (UCP2, UCP3, TSHR, FGFR1, ERLIN2, and ZNF703), and coat color (KITLG, ASIP, AHCY, RALY, and MC1R). Our results suggest that the CM breed may be differentiated from other goat breeds in terms of nervous system owing to natural or artificial selection. The whole-genome analysis provides an improved understanding of genetic diversity and trait exploration for this indigenous goat breed.

Analysis of pooled genome sequences from Djallonke and Sahelian sheep of Ghana reveals co-localisation of regions of reduced heterozygosity with candidate genes for disease resistance and adaptation to a tropical environment

BACKGROUND

The Djallonke sheep is well adapted to harsh environmental conditions, and is relatively resistant to Haemonchosis and resilient to animal trypanosomiasis. The larger Sahelian sheep, which cohabit the same region, is less well adapted to these disease challenges. Haemonchosis and Trypanosomiasis collectively cost the worldwide animal industry billions of dollars in production losses annually.

RESULTS

Here, we separately sequenced and then pooled according to breed the genomes from five unrelated individuals from each of the Djallonke and Sahelian sheep breeds (sourced from Ghana), at greater than 22-fold combined coverage for each breed. A total of approximately 404 million (97%) and 343 million (97%) sequence reads from the Djallonke and Sahelian breeds respectively, were successfully mapped to the sheep reference genome Oar v3.1. We identified approximately 11.1 million and 10.9 million single nucleotide polymorphisms (SNPs) in the Djallonke and Sahelian breeds, with approximately 15 and 16% respectively of these not previously reported in sheep. Multiple regions of reduced heterozygosity were also found; 70 co-localised within genomic regions harbouring genes that mediate disease resistance, immune response and adaptation in sheep or cattle. Thirty- three of the regions of reduced heterozygosity co-localised with previously reported genes for resistance to haemonchosis and trypanosomiasis.

CONCLUSIONS

Our analyses suggest that these regions of reduced heterozygosity may be signatures of selection for these economically important diseases.

Resurrecting Darwin's Niata - anatomical, biomechanical, genetic, and morphometric studies of morphological novelty in cattle

The Niata was a cattle variety from South America that figured prominently in writings on evolution by Charles Darwin. Its shortened head and other aspects of its unusual morphology have been subject of unsettled discussions since Darwin’s time. Here, we examine the anatomy, cranial shape, skull biomechanics, and population genetics of the Niata. Our results show that the Niata was a viable variety of cattle and exhibited anatomical differences to known chondrodysplastic forms. In cranial shape and genetic analysis, the Niata occupies an isolated position clearly separated from other cattle. Computational biomechanical model comparison reveals that the shorter face of the Niata resulted in a restricted distribution and lower magnitude of stress during biting. Morphological and genetic data illustrate the acquisition of novelty in the domestication process and confirm the distinct nature of the Niata cattle, validating Darwin’s view that it was a true breed.

Combatting African Animal Trypanosomiasis (AAT) in livestock: The potential role of trypanotolerance

African Animal Trypanosomiasis (AAT) is endemic in at least 37 of the 54 countries in Africa. It is estimated to cause direct and indirect losses to the livestock production industry in excess of US$ 4.5 billion per annum. A century of intervention has yielded limited success, owing largely to the extraordinary complexity of the host-parasite interaction. Trypanotolerance, which refers to the inherent ability of some African livestock breeds, notably Djallonke sheep, N'Dama cattle and West African Dwarf goats, to withstand a trypanosomiasis challenge and still remain productive without any form of therapy, is an economically sustainable option for combatting this disease. Yet trypanotolerance has not been adequately exploited in the fight against AAT. In this review, we describe new insights into the genetic basis of trypanotolerance and discuss the potential of exploring this phenomenon as an integral part of the solution for AAT, particularly, in the context of African animal production systems.