Association of Copy Number Variation at Intron 3 of HMGA2 With Navel Length in Bos indicus

Navel injuries caused by friction against the pasture can promote infection, reproductive problems and costly treatments in beef cattle raised in extensive systems. A haplotype-based genome-wide association study (GWAS) was performed for visual scores of navel length at yearling in Nellore cattle (Bos indicus) using data from 2,016 animals and 503,088 single nucleotide polymorphism (SNP) markers. The strongest signal (p = 1.01 × 10-9) was found on chromosome 5 spanning positions 47.9–48.2 Mbp. This region contains introns 3 and 4 and exons 4 and 5 of the high mobility group AT-hook 2 gene (HMGA2). Further inspection of the region with whole genome sequence data of 21 Nellore bulls revealed correlations between counts of the significant haplotype and copy number gains of a ∼6.2 kbp segment of intron 3 of HMGA2. Analysis of genome sequences from five African B. indicus and four European Bos taurus breeds revealed that the copy number variant (CNV) is indicine-specific. This intronic CNV was then validated through quantitative polymerase chain reaction (qPCR) using Angus animals as copy neutral controls. Importantly, the CNV was not detectable by means of conventional SNP-based GWAS or SNP probe intensity analyses. Given that HMGA2 affects the expression of the insulin-like growth factor 2 gene (IGF2) together with the pleomorphic adenoma gene 1 (PLAG1), and that the latter has been repeatedly shown to be associated with quantitative traits of economic importance in cattle, these findings highlight the emerging role of variants impacting the insulin-like growth factor pathway to cattle breeding

Detecting loci under recent positive selection in dairy and beef cattle by combining different genome-wide scan methods

As the methodologies available for the detection of positive selection from genomic data vary in terms of assumptions and execution, weak correlations are expected among them. However, if there is any given signal that is consistently supported across different methodologies, it is strong evidence that the locus has been under past selection. In this paper, a straightforward frequentist approach based on the Stouffer Method to combine P-values across different tests for evidence of recent positive selection in common variations, as well as strategies for extracting biological information from the detected signals, were described and applied to high density single nucleotide polymorphism (SNP) data generated from dairy and beef cattle (taurine and indicine). The ancestral Bovinae allele state of over 440,000 SNP is also reported. Using this combination of methods, highly significant (P<3.17×10(-7)) population-specific sweeps pointing out to candidate genes and pathways that may be involved in beef and dairy production were identified. The most significant signal was found in the Cornichon homolog 3 gene (CNIH3) in Brown Swiss (P = 3.82×10(-12)), and may be involved in the regulation of pre-ovulatory luteinizing hormone surge. Other putative pathways under selection are the glucolysis/gluconeogenesis, transcription machinery and chemokine/cytokine activity in Angus; calpain-calpastatin system and ribosome biogenesis in Brown Swiss; and gangliosides deposition in milk fat globules in Gyr. The composite method, combined with the strategies applied to retrieve functional information, may be a useful tool for surveying genome-wide selective sweeps and providing insights in to the source of selection

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

How bioinformatics enables livestock applied sciences in the genomic era

This review paper presents the three main approaches currently used in livestock genomic sciences where the bioinfomatics plays a critical role. They are named as Genomic Selection (GS), Genome Wide Association Study (GWAS) and Signatures of Selection (SS). The subsides for the construction of this article were generated in a current project (started in 2011), so called Zebu Genome Consortium (ZGC), which joins researchers from different institutions and countries, aiming to scientifically explore genomic information of Bos taurus indicus cattle breeds and deliver useful information to breeders and academic community, specially from the tropical regions of the world. © 2012 Springer-Verlag

Association of Copy Number Variation at Intron 3 of HMGA2 With Navel Length in Bos indicus

Navel injuries caused by friction against the pasture can promote infection, reproductive problems and costly treatments in beef cattle raised in extensive systems. A haplotype-based genome-wide association study (GWAS) was performed for visual scores of navel length at yearling in Nellore cattle (Bos indicus) using data from 2,016 animals and 503,088 single nucleotide polymorphism (SNP) markers. The strongest signal (p = 1.01 x 10(-9)) was found on chromosome 5 spanning positions 47.9-48.2 Mbp. This region contains introns 3 and 4 and exons 4 and 5 of the high mobility group AT-hook 2 gene (HMGA2). Further inspection of the region with whole genome sequence data of 21 Nellore bulls revealed correlations between counts of the significant haplotype and copy number gains of a similar to 6.2 kbp segment of intron 3 of HMGA2. Analysis of genome sequences from five African B. indicus and four European Bos taurus breeds revealed that the copy number variant (CNV) is indicine-specific. This intronic CNV was then validated through quantitative polymerase chain reaction (qPCR) using Angus animals as copy neutral controls. Importantly, the CNV was not detectable by means of conventional SNP-based GWAS or SNP probe intensity analyses. Given that HMGA2 affects the expression of the insulin-like growth factor 2 gene (IGF2) together with the pleomorphic adenoma gene 1 (PLAG1), and that the latter has been repeatedly shown to be associated with quantitative traits of economic importance in cattle, these findings highlight the emerging role of variants impacting the insulin-like growth factor pathway to cattle breeding

A PLAG1 mutation contributed to stature recovery in modern cattle

Abstract The recent evolution of cattle is marked by fluctuations in body size. Height in the Bos taurus lineage was reduced by a factor of ~1.5 from the Neolithic to the Middle Ages, and increased again only during the Early Modern Ages. Using haplotype analysis, we found evidence that the bovine PLAG1 mutation (Q) with major effects on body size, weight and reproduction is a >1,000 years old derived allele that increased rapidly in frequency in Northwestern European B. taurus between the 16th and 18th centuries. Towards the 19th and 20th centuries, Q was introgressed into non-European B. taurus and Bos indicus breeds. These data implicate a major role of Q in recent changes in body size in modern cattle, and represent one of the first examples of a genomic sweep in livestock that was driven by selection on a complex trait