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BackgroundThe 29-member ArabidopsisAHLgene family is classified into three main classes based on nucleotide and protein sequence evolutionary differences. These differences include the presence or absence of introns, type and/or number of conserved AT-hook and PPC domains.AHLgene family members are divided into two phylogenetic clades, Clade-A and Clade-B. A majority of the 29 members remain functionally uncharacterized. Furthermore, the biological significance of the DNA and peptide sequence diversity, observed in the conserved motifs and domains found in the different AHL types, is a subject area that remains largely unexplored.ResultsTransgenic plants overexpressingAtAHL20flowered later than the wild type under both short and long days. Transcript accumulation analyses showed that35S:AtAHL20plants contained reducedFT, TSF, AGL8andSPL3mRNA levels. Similarly, overexpression ofAtAHL20’sorthologue inCamelina sativa,Arabidopsis’ closely relatedBrassicaceaefamily member species, conferred a late-flowering phenotype via suppression ofCsFTexpression. However, overexpression of an aberrantAtAHL20gene harboring a missense mutation in the AT-hook domain’s highly conserved R-G-R core motif abolished the late-flowering phenotype. Data from targeted yeast-two-hybrid assays showed that AtAHL20 interacted with itself and several other Clade-A Type-I AHLs which have been previously implicated in flowering-time regulation: AtAHL19, AtAHL22 and AtAHL29.ConclusionWe showed via gain-of-function analysis thatAtAHL20is a negative regulator ofFTexpression, as well as other downstream flowering time regulating genes. A similar outcome inCamelina sativatransgenic plants overexpressingCsAHL20suggest that this is a conserved function. Our results demonstrate thatAtAHL20acts as a photoperiod-independent negative regulator of transition to flowering.

Grazing distribution is an important aspect of pasture management, yet measuring traits for sustainable forage consumption is challenging. Uplands are often un-grazed by beef cattle due to rugged terrain while riparian zones are often heavily grazed; thus, sustainable consumption may be achieved if improved landscape utilization by cattle is encouraged. Modifying grazing behaviour with fencing and (or) water-source and feeding location(s) is effective in improving grazing patterns; however, these infrastructure improvements are typically expensive, supporting the concept of genetic selection for improved grazing distribution. Efforts funded by the Western Sustainable Research and Education Program (WSARE; SW15-015) using global positioning systems (GPS) indicated a genetic influence on quantitative traits describing grazing distribution of 330 Angus-influenced cows (i.e. distance from water, slope, elevation, vertical climb, etc.). Collars fitted with GPS devices for data collection accrued measures at intervals of 5 to 15 min and 10 m resolution for 3-19 weeks in 16 pastures on 14 ranches and experiment stations. Genome-wide association studies involving trait-measures and high-density genotypes (n = 777,962 single nucleotide polymorphisms; SNP) indicated these traits were polygenic. Combining SNP genotypes with trait measures and pedigree has become the norm in genetic evaluation and improvement processes (i.e. genome-enhanced expected progeny difference (GE-EPD). These processes require data from large numbers of animals (n > 10,000). Collecting grazing distribution phenotypes with GPS collars is accurate, but time-consuming; therefore, collaborative research is being conducted in the 2019-2020 academic year exploring the use of unmanned aerial vehicles (UAV) and cameras to ascertain spatial measures of beef cow grazing distribution. This collaboration involves scientists in the Colorado State University Drone Center, Department of Mechanical Engineering, and Department of Animal Sciences. The project objective is to determine if UAV can expedite data collection to support development of genetic evaluation and improvement programs for grazing distribution.

Isolation and cultivation of wild-type viruses in model organism cells or tissues is standard practice in virology. Oftentimes, the virus host species is distantly related to the species from which the culture system was developed. Thus, virus culture in these tissues and cells basically constitutes a host jump, which can lead to genomic changes through genetic drift and/or adaptation to the culture system. We directly sequenced 70 avian influenza virus (Orthomyxoviridae) genomes from oropharyngeal/cloacal swabs collected from wild bird species and paired virus isolates propagated from the same samples following isolation in specific-pathogen-free embryonated chicken eggs. The data were analyzed using population genetic approaches including evaluation of single nucleotide polymorphism (SNP) frequencies and divergence with pooled-sequencing analyses, consensus sequence placement in neighbor-joining trees, and haplotype reconstruction and networks. We found that propagation of virus in eggs leads to skewed SNP mutation spectra with some SNPs going to fixation. Both synonymous and nonsynonmous SNP frequencies shifted. We found multiple consensus sequences that differed between the swabs and the isolates, with some sequences from the same sample falling into divergent genetic clusters. Twenty of 23 coinfections detected had different dominant subtypes following virus isolation, thus sequences from both the swab and isolate were needed to obtain full subtype data. Haplotype networks revealed haplotype frequency shifts and the appearance or loss of low-frequency haplotypes following isolation. The results from this study revealed that isolation of wild bird avian influenza viruses in chicken eggs leads to skewed populations that are different than the input populations. Consensus sequence changes from virus isolation can lead to flawed phylogenetic inferences, and subtype detection is biased. These results suggest that for genomic studies of wild bird influenza viruses the biological field should move away from chicken egg isolation towards directly sequencing the virus from host samples.

SUPPRESSOR OF PHYB-4#5DOMINANT (sob5-D) was previously identified as a suppressor of the phyB-4 long-hypocotyl phenotype in Arabidopsis thaliana. Overexpression of SOB5 conferred dwarf phenotypes similar to those observed in plants containing elevated levels of cytokinin (CK) nucleotides and nucleosides. Two SOB-FIVE- LIKE (SOFL) proteins, AtSOFL1 and AtSOFL2, which are more similar at the protein level to each other than they are to SOB5, conferred similar phenotypes to the sob5-D mutant when overexpressed. We used protein sequences of founding SOFL gene family members to perform database searches and identified a total of 289 SOFL homologs in genomes of 89 angiosperm species. Phylogenetic analysis results implied that the SOFL gene family emerged during the expansion of angiosperms and later evolved into four distinct clades. Among the newly identified gene family members are four previously unreported Arabidopsis SOFLs. Multiple sequence alignment of the 289 SOFL protein sequences revealed two highly conserved domains; SOFL-A and SOFL-B. We used overexpression and site-directed mutagenesis studies to demonstrate that SOFL domains are necessary for SOB5 and AtSOFL1’s overexpression phenotypes. Examination of the subcellular localization patterns of founding Arabidopsis thaliana SOFLs suggested they may be localized in the cytoplasm and/or the nucleus. Overall, we report that SOFLs are a plant-specific gene family characterized by two conserved domains that are important for function.

Concentrated grazing may destroy wildlife habitat, reduce forage harvest, and degrade riparian areas; therefore, it is necessary to develop tools to improve grazing distribution for extensive pastures in beef production systems. A previous genome-wide association study identified 5 QTL on BTA 4, 12, 17, and 29 that were associated with grazing distribution indices (rolling and rough). The objective of this study was to validate these QTL using additional association analyses with a Bayesian approach. Global positioning system (GPS) technology was used to collect grazing distribution phenotypes from 80 beef cows on 5 ranches in New Mexico, Montana, and Arizona. Percent slope, elevation, and distance from water were calculated using GPS coordinates and incorporated into two terrain-use indices (rough and rolling). Cows were genotyped with 777,962 SNP and after applying standard SNP quality filters, 733,713 SNP from 75 cows were available for analysis. A single chromosome (BTA 4, 12, 17, 29) association analysis was performed for both the rough and rolling indices using Bayes C (within the BOLT software package. The posterior inclusion probability (PIP) for each SNP was estimated. The association between rs109619368 on BTA 17 and the rough index was confirmed (PIP = 2.1%); however, the QTL on BTA 4, 12, and 29 were not verified. To further investigate this, 50 SNP spanning 0.2 MB on BTA 29 were analyzed with the rolling index. Two SNP were confirmed in this analysis: rs42161939 (PIP = 54.9%) and rs43744222 (PIP = 21.6%). The Bayesian approach applied in this study, in which markers are simultaneously fit in the model, revealed 3 QTL concordant with previous analyses which used a single-marker regression approach. These results suggest that grazing distribution traits are under genetic control; however, a greater number of observations are needed to confirm the QTL associated with grazing distribution (SW15-015).