Taming the Wilde: Collaborating with Expertise for Faster, Better, Smarter Collection Analysis

The importance of collection assessment and evaluation has been a hot topic due to increasing budget restrictions and the need to prove worth to stakeholders through evidence‐based evaluations. More robust collection analyses, like comparisons of holdings usage to ILL requests, and gap analyses, are increasingly embraced by the library community. Less thought, however, has been given to how to best conduct these analyses to ensure that the cleanest data is used and that the data tells the right story. The data to do these types of analyses often reside in complex systems and web‐environments, which may not be fully understood by the collection managers or subject librarians. The University of Houston Libraries embarked on a largescale gap analysis of the collection by subject area. The key component to success was quickly, accurately, and properly mining the data sources such as Sierra and the electronic resource management system. Our collection team contends that collaboration with expertise in the Resource Discovery Systems Department allowed the team to more quickly develop complete and accurate datasets, and helped to shape the analysis conducted. This paper discusses the challenges of defining project scope, the process of forming methodology, and the challenges of collecting the data. It will also review how experts were able to contribute to each step of this process. Finally it will outline some initial findings of the analysis, and how this research was accomplished in a realistic time frame

Developing an Information Literacy Assessment Rubric: A Case Study of Collaboration, Process, and Outcomes

A team of four librarians at the [Institution Name] ([Institution Initials]) Libraries partnered with the [Institution Initials] Office of Institutional Effectiveness and its Director of Assessment & Accreditation Services for General Education to conduct a campus-wide, exploratory assessment of undergraduate information literacy skills. The project evaluated a selection of graduating, senior-level student papers using a rubric developed as part of the collaboration. This paper describes and discusses the collaborative rubric development and rating process, the practical implications for other librarians seeking to conduct a similar assessment, and the impact the project is having on the library instruction program

A production process for library help videos

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Nucleotide polymorphism and copy number variant detection using exome capture and next-generation sequencing in the polyploid grass \u3ci\u3ePanicum virgatum\u3c/i\u3e

Switchgrass (Panicum virgatum) is a polyploid, outcrossing grass species native to North America and has recently been recognized as a potential biofuel feedstock crop. Significant phenotypic variation including ploidy is present across the two primary ecotypes of switchgrass, referred to as upland and lowland switchgrass. The tetraploid switchgrass genome is approximately 1400 Mbp, split between two subgenomes, with significant repetitive sequence content limiting the efficiency of re-sequencing approaches for determining genome diversity. To characterize genetic diversity in upland and lowland switchgrass as a first step in linking genotype to phenotype, we designed an exome capture probe set based on transcript assemblies that represent approximately 50 Mb of annotated switchgrass exome sequences. We then evaluated and optimized the probe set using solid phase comparative genome hybridization and liquid phase exome capture followed by next-generation sequencing. Using the optimized probe set, we assessed variation in the exomes of eight switchgrass genotypes representing tetraploid lowland and octoploid upland cultivars to benchmark our exome capture probe set design. We identified ample variation in the switchgrass genome including 1 395 501 single nucleotide polymorphisms (SNPs), 8173 putative copy number variants and 3336 presence/absence variants. While the majority of the SNPs (84%) detected was bi-allelic, a substantial number was tri-allelic with limited occurrence of tetra-allelic polymorphisms consistent with the heterozygous and polyploid nature of the switchgrass genome. Collectively, these data demonstrate the efficacy of exome capture for discovery of genome variation in a polyploid species with a large, repetitive and heterozygous genome

Genome-wide association analysis of stalk biomass and anatomical traits in maize.

BackgroundMaize stover is an important source of crop residues and a promising sustainable energy source in the United States. Stalk is the main component of stover, representing about half of stover dry weight. Characterization of genetic determinants of stalk traits provide a foundation to optimize maize stover as a biofuel feedstock. We investigated maize natural genetic variation in genome-wide association studies (GWAS) to detect candidate genes associated with traits related to stalk biomass (stalk diameter and plant height) and stalk anatomy (rind thickness, vascular bundle density and area).ResultsUsing a panel of 942 diverse inbred lines, 899,784 RNA-Seq derived single nucleotide polymorphism (SNP) markers were identified. Stalk traits were measured on 800 members of the panel in replicated field trials across years. GWAS revealed 16 candidate genes associated with four stalk traits. Most of the detected candidate genes were involved in fundamental cellular functions, such as regulation of gene expression and cell cycle progression. Two of the regulatory genes (Zmm22 and an ortholog of Fpa) that were associated with plant height were previously shown to be involved in regulating the vegetative to floral transition. The association of Zmm22 with plant height was confirmed using a transgenic approach. Transgenic lines with increased expression of Zmm22 showed a significant decrease in plant height as well as tassel branch number, indicating a pleiotropic effect of Zmm22.ConclusionSubstantial heritable variation was observed in the association panel for stalk traits, indicating a large potential for improving useful stalk traits in breeding programs. Genome-wide association analyses detected several candidate genes associated with multiple traits, suggesting common regulatory elements underlie various stalk traits. Results of this study provide insights into the genetic control of maize stalk anatomy and biomass

Maize (Zea mays L.) Genome Diversity as Revealed by RNA-Sequencing

Maize is rich in genetic and phenotypic diversity. Understanding the sequence, structural, and expression variation that contributes to phenotypic diversity would facilitate more efficient varietal improvement. RNA based sequencing (RNA-seq) is a powerful approach for transcriptional analysis, assessing sequence variation, and identifying novel transcript sequences, particularly in large, complex, repetitive genomes such as maize. In this study, we sequenced RNA from whole seedlings of 21 maize inbred lines representing diverse North American and exotic germplasm. Single nucleotide polymorphism (SNP) detection identified 351,710 polymorphic loci distributed throughout the genome covering 22,830 annotated genes. Tight clustering of two distinct heterotic groups and exotic lines was evident using these SNPs as genetic markers. Transcript abundance analysis revealed minimal variation in the total number of genes expressed across these 21 lines (57.1% to 66.0%). However, the transcribed gene set among the 21 lines varied, with 48.7% expressed in all of the lines, 27.9% expressed in one to 20 lines, and 23.4% expressed in none of the lines. De novo assembly of RNA-seq reads that did not map to the reference B73 genome sequence revealed 1,321 high confidence novel transcripts, of which, 564 loci were present in all 21 lines, including B73, and 757 loci were restricted to a subset of the lines. RT-PCR validation demonstrated 87.5% concordance with the computational prediction of these expressed novel transcripts. Intriguingly, 145 of the novel de novo assembled loci were present in lines from only one of the two heterotic groups consistent with the hypothesis that, in addition to sequence polymorphisms and transcript abundance, transcript presence/absence variation is present and, thereby, may be a mechanism contributing to the genetic basis of heterosis

Creating Customizable, Learner-centered Instruction Modules Using a Collaborative Design Process

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