Major advances in selection progress for cattle have been made following the introduction of genomic tools over the past 10–12 years. These tools depend upon the Bos taurus reference genome (UMD3.1.1), which was created using now-outdated technologies and is hindered by a variety of deficiencies and inaccuracies. We present the new reference genome for cattle, ARS-UCD1.2, based on the same animal as the original to facilitate transfer and interpretation of results obtained from the earlier version, but applying a combination of modern technologies in a de novo assembly to increase continuity, accuracy, and completeness. The assembly includes 2.7 Gb and is >250× more continuous than the original assembly, with contig N50 >25 Mb and L50 of 32. We also greatly expanded supporting RNA-based data for annotation that identifies 30,396 total genes (21,039 protein coding). The new reference assembly is accessible in annotated form for public use. We demonstrate that improved continuity of assembled sequence warrants the adoption of ARS-UCD1.2 as the new cattle reference genome and that increased assembly accuracy will benefit future research on this species.

Background: Bovine whole genome linkage disequilibrium maps were constructed for eight breeds of cattle. These data provide fundamental information concerning bovine genome organization which will allow the design of studies to associate genetic variation with economically important traits and also provides background information concerning the extent of long range linkage disequilibrium in cattle. Results: Linkage disequilibrium was assessed using r² among all pairs of syntenic markers within eight breeds of cattle from the Bos taurus and Bos indicus subspecies. Bos taurus breeds included Angus, Charolais, Dutch Black and White Dairy, Holstein, Japanese Black and Limousin while Bos indicus breeds included Brahman and Nelore. Approximately 2670 markers spanning the entire bovine autosomal genome were used to estimate pairwise r² values. We found that the extent of linkage disequilibrium is no more than 0.5 Mb in these eight breeds of cattle. Conclusion: Linkage disequilibrium in cattle has previously been reported to extend several tens of centimorgans. Our results, based on a much larger sample of marker loci and across eight breeds of cattle indicate that in cattle linkage disequilibrium persists over much more limited distances. Our findings suggest that 30,000–50,000 loci will be needed to conduct whole genome association studies in cattle.

Automated high-throughput phenotyping with sensors, imaging, and other on-farm technologies has resulted in a flood of data that are largely under-utilized. Drastic cost reductions in sequencing and other omics technology have also facilitated the ability for deep phenotyping of livestock at the molecular level. These advances have brought the animal sciences to a cross-roads in data science where increased training is needed to manage, record, and analyze data to generate knowledge and advances in agriscience related disciplines. This paper describes the opportunities and challenges in using high-throughput phenotyping, “big data,” analytics, and related technologies in the livestock industry based on discussions at the Livestock High-Throughput Phenotyping and Big Data Analytics meeting, held in November 2017 (see: https://www.animalgenome.org/bioinfo/community/workshops/2017/). Critical needs for investments in infrastructure for people (e.g. “big data” training), data (e.g. data transfer, management and analytics), and technology (e.g. development of low cost sensors) were defined by this group. Though some subgroups of animal science have extensive experience in predictive modeling, cross-training in computer science, statistics and related disciplines are needed to use big data for diverse applications in the field. Extensive opportunities exist for public and private entities to harness big data to develop valuable research knowledge and products to the benefit of society under the increased demands for food of a rapidly growing population.

Feed intake and feed efficiency of beef cattle are economically relevant traits. The study was conducted to identify QTL for feed intake and feed efficiency of beef cattle by using genotype information from 100 microsatellite markers and 355 SNP genotyped across 400 progeny of 20 Angus, Charolais, or Alberta Hybrid bulls. Traits analyzed include feedlot ADG, daily DMI, feed-to-gain ratio [F:G, which is the reciprocal of the efficiency of gain (G:F)], and residual feed intake (RFI). A mixed model with sire as random and QTL effects as fixed was used to generate an F-statistic profile across and within families for each trait along each chromosome, followed by empirical permutation tests to determine significance thresholds for QTL detection. Putative QTL for ADG (chromosome-wise P < 0.05) were detected across families on chromosomes 5 (130 cM), 6 (42 cM), 7 (84 cM), 11 (20 cM), 14 (74 cM), 16 (22 cM), 17 (9 cM), 18 (46 cM), 19 (53 cM), and 28 (23 cM). For DMI, putative QTL that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (93 cM), 3 (123 cM), 15 (31 cM), 17 (81 cM), 18 (49 cM), 20 (56 cM), and 26 (69 cM) in the across-family analyses. Putative across-family QTL influencing F:G that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 3 (62 cM), 5 (129 cM), 7 (27 cM), 11 (16 cM), 16 (30 cM), 17 (81 cM), 22 (72 cM), 24 (55 cM), and 28 (24 cM). Putative QTL influencing RFI that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (90 cM), 5 (129 cM), 7 (22 cM), 8 (80 cM), 12 (89 cM), 16 (41 cM), 17 (19 cM), and 26 (48 cM) in the across-family analyses. In addition, a total of 4, 6, 1, and 8 chromosomes showed suggestive evidence (chromosome-wise, P < 0.10) for putative ADG, DMI, F:G, and RFI QTL, respectively. Most of the QTL detected across families were also detected within families, although the locations across families were not necessarily the locations within families, which is likely because of differences among families in marker informativeness for the different linkage groups. The locations and direction of some of the QTL effects reported in this study suggest potentially favorable pleiotropic effects for the underlying genes. Further studies will be required to confirm these QTL in other populations so that they can be fine-mapped for potential applications in marker-assisted selection and management of beef cattle. Copyright © 2007. . Copyright 2007 Journal of Animal Science

The domestic sheep (Ovis aries) is an important agricultural species raised for meat, wool, and milk across the world. A high-quality reference genome for this species enhances the ability to discover genetic mechanisms influencing biological traits. Furthermore, a high-quality reference genome allows for precise functional annotation of gene regulatory elements. The rapid advances in genome assembly algorithms and emergence of sequencing technologies with increasingly long reads provide the opportunity for an improved de novo assembly of the sheep reference genome. Short-read Illumina (55× coverage), long-read Pacific Biosciences (75× coverage), and Hi-C data from this ewe retrieved from public databases were combined with an additional 50× coverage of Oxford Nanopore data and assembled with canu v1.9. The assembled contigs were scaffolded using Hi-C data with Salsa v2.2, gaps filled with PBsuitev15.8.24, and polished with Nanopolish v0.12.5. After duplicate contig removal with PurgeDups v1.0.1, chromosomes were oriented and polished with 2 rounds of a pipeline that consisted of freebayes v1.3.1 to call variants, Merfin to validate them, and BCFtools to generate the consensus fasta. The ARS-UI_Ramb_v2.0 assembly is 2.63 Gb in length and has improved continuity (contig NG50 of 43.18 Mb), with a 19- and 38-fold decrease in the number of scaffolds compared with Oar_rambouillet_v1.0 and Oar_v4.0. ARS-UI_Ramb_v2.0 has greater per-base accuracy and fewer insertions and deletions identified from mapped RNA sequence than previous assemblies. The ARS-UI_Ramb_v2.0 assembly is a substantial improvement in contiguity that will optimize the functional annotation of the sheep genome and facilitate improved mapping accuracy of genetic variant and expression data for traits in sheep.

Background: Analyses of population structure and breed diversity have provided insight into the origin and evolution of cattle. Previously, these studies have used a low density of microsatellite markers, however, with the large number of single nucleotide polymorphism markers that are now available, it is possible to perform genome wide population genetic analyses in cattle. In this study, we used a high-density panel of SNP markers to examine population structure and diversity among eight cattle breeds sampled from Bos indicus and Bos taurus. Results: Two thousand six hundred and forty one single nucleotide polymorphisms (SNPs) spanning all of the bovine autosomal genome were genotyped in Angus, Brahman, Charolais, Dutch Black and White Dairy, Holstein, Japanese Black, Limousin and Nelore cattle. Population structure was examined using the linkage model in the program STRUCTURE and Fst estimates were used to construct a neighbor-joining tree to represent the phylogenetic relationship among these breeds. Conclusion: The whole-genome SNP panel identified several levels of population substructure in the set of examined cattle breeds. The greatest level of genetic differentiation was detected between the Bos taurus and Bos indicus breeds. When the Bos indicus breeds were excluded from the analysis, genetic differences among beef versus dairy and European versus Asian breeds were detected among the Bos taurus breeds. Exploration of the number of SNP loci required to differentiate between breeds showed that for 100 SNP loci, individuals could only be correctly clustered into breeds 50% of the time, thus a large number of SNP markers are required to replace the 30 microsatellite markers that are currently commonly used in genetic diversity studies.