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Supported by National Science Foundation (NSF), International Society of Intelligent Biological Medicine (ISIBM), International Journal of Computational Biology and Drug Design and International Journal of Functional Informatics and Personalized Medicine, IEEE 7th Bioinformatics and Bioengineering attracted more than 600 papers and 500 researchers and medical doctors. It was the only synergistic inter/multidisciplinary IEEE conference with 24 Keynote Lectures, 7 Tutorials, 5 Cutting-Edge Research Workshops and 32 Scientific Sessions including 11 Special Research Interest Sessions that were designed dynamically at Harvard in response to the current research trends and advances. The committee was very grateful for the IEEE Plenary Keynote Lectures given by: Dr. A. Keith Dunker (Indiana), Dr. Jun Liu (Harvard), Dr. Brian Athey (Michigan), Dr. Mark Borodovsky (Georgia Tech and President of ISIBM), Dr. Hamid Arabnia (Georgia and Vice-President of ISIBM), Dr. Ruzena Bajcsy (Berkeley and Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Chih-Ming Ho (UCLA and Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Andy Baxevanis (United States National Institutes of Health), Dr. Arif Ghafoor (Purdue), Dr. John Quackenbush (Harvard), Dr. Eric Jakobsson (UIUC), Dr. Vladimir Uversky (Indiana), Dr. Laura Elnitski (United States National Institutes of Health) and other world-class scientific leaders. The Harvard meeting was a large academic event 100% full-sponsored by IEEE financially and academically. After a rigorous peerreview process, the committee selected 27 high-quality research papers from 600 submissions. The committee is grateful for contributions from keynote speakers Dr. Russ Altman (IEEE BIBM conference keynote lecturer on combining simulation and machine learning to recognize function in 4D), Dr. Mary Qu Yang (IEEE BIBM workshop keynote lecturer on new initiatives of detecting microscopic disease using machine learning and molecular biology, http:// ieeexplore.ieee.org/servlet/opac?punumber=4425386) and Dr. Jack Y. Yang (IEEE BIBM workshop keynote lecturer on data mining and knowledge discovery in translational medicine) from the first IEEE Computer Society BioInformatics and BioMedicine (IEEE BIBM) international conference and workshops, November 2-4, 2007, Silicon Valley, California, USA. [ABSTRACT FROM AUTHOR]

Advancing the production efficiency and profitability of aquaculture is dependent upon the ability to utilize a diverse array of genetic resources. The ultimate goals of aquaculture genomics, genetics and breeding research are to enhance aquaculture production efficiency, sustainability, product quality, and profitability in support of the commercial sector and for the benefit of consumers. In order to achieve these goals, it is important to understand the genomic structure and organization of aquaculture species, and their genomic and phenomic variations, as well as the genetic basis of traits and their interrelationships. In addition, it is also important to understand the mechanisms of regulation and evolutionary conservation at the levels of genome, transcriptome, proteome, epigenome, and systems biology. With genomic information and information between the genomes and phenomes, technologies for marker/causal mutation-assisted selection, genome selection, and genome editing can be developed for applications in aquaculture. A set of genomic tools and resources must be made available including reference genome sequences and their annotations (including coding and non-coding regulatory elements), genome-wide polymorphic markers, efficient genotyping platforms, highdensity and high-resolution linkage maps, and transcriptome resources including non-coding transcripts. Genomic and genetic control of important performance and production traits, such as disease resistance, feed conversion efficiency, growth rate, processing yield, behaviour, reproductive characteristics, and tolerance to environmental stressors like low dissolved oxygen, high or low water temperature and salinity, must be understood. QTL need to be identified, validated across strains, lines and populations, and their mechanisms of control understood. Causal gene(s) need to be identified. Genetic and epigenetic regulation of important aquaculture traits need to be determined, and technologies for marker-assisted selection, causal gene/mutation-assisted selection, genome selection, and genome editing using CRISPR and other technologies must be developed, demonstrated with applicability, and application to aquaculture industries. Major progress has been made in aquaculture genomics for dozens of fish and shellfish species including the development of genetic linkage maps, physical maps, microarrays, single nucleotide polymorphism (SNP) arrays, transcriptome databases and various stages of genome reference sequences. This paper provides a general review of the current status, challenges and future research needs of aquaculture genomics, genetics, and breeding, with a focus on major aquaculture species in the United States: catfish, rainbow trout, Atlantic salmon, tilapia, striped bass, oysters, and shrimp. While the overall research priorities and the practical goals are similar across various aquaculture species, the current status in each species should dictate the next priority areas within the species. This paper is an output of the USDA Workshop for Aquaculture Genomics, Genetics, and Breeding held in late March 2016 in Auburn, Alabama, with participants from all parts of the United States. [ABSTRACT FROM AUTHOR]

The Avian Genomics Conference and Gene Ontology Annotation Workshop brought together researchers and students from around the world to present their latest research addressing the delivery of value from the billions of base-pairs of Archosaur sequence that have become available in the last few years. This editorial describes the conference itself and introduces the ten peer-reviewed manuscripts accepted for publications in the proceedings. These manuscripts address issues ranging from the poultry industry view of USDA genomics policy to the genomics of a wide variety of Archeosaur species including chicken, duck, alligator, and condors and their pathogens. [ABSTRACT FROM AUTHOR]

In 2007, the USDA Animal Genomics Strategic Planning Task Force prepared a Blueprint to direct national needs for future research, education, and extension efforts in agricultural animal genomics. This plan is entitled "Blueprint for USDA Efforts in Agricultural Animal Genomics 2008-2017". The Blueprint is reviewed from the perspective of a molecular biologist working within the poultry breeding industry. The diverse species used in animal agriculture require different tools, resources and technologies for their improvement. The specific requirements for chickens are described in this report. [ABSTRACT FROM AUTHOR]

Background: Zinc (Zn) is an essential trace element. However, Zn bioavailability from commonly consumed plants may be reduced due to phytic acid. Zn supplementation has been used to treat diarrheal disease in children, and in the U.S. swine industry at pharmacological levels to promote growth and fecal consistency, but underlying mechanisms explaining these beneficial effects remain unknown. Moreover, adding supplemental phytase improves Zn bioavailability. Thus, we hypothesized that benefits of pharmacological Zn supplementation result from changes in gene expression that could be further affected by supplemental phytase. The goal of this study was to investigate the effects of feeding newly weaned pigs dietary Zn (150, 1,000, or 2,000 mg Zn/kg) as Zn oxide with or without phytase [500 phytase units (FTU)/kg] for 14 d on hepatic gene expression. Liver RNA from pigs fed 150, 1,000, or 2,000 mg Zn/kg, or 1,000 mg Zn/kg with phytase (n = 4 per treatment) was reverse transcribed and examined using the differential display reverse transcription polymerase chain reaction technique. Liver RNA from pigs fed 150 or 2,000 mg Zn/kg (n = 4 per treatment) was also evaluated using a 70-mer oligonucleotide microarray. Results: Expressed sequence tags for 61 putatively differentially expressed transcripts were cloned and sequenced. In addition, interrogation of a 13,297 element oligonucleotide microarray revealed 650 annotated transcripts (FDR ≤ 0.05) affected by pharmacological Zn supplementation. Seven transcripts exhibiting differential expression in pigs fed pharmacological Zn with sequence similarities to genes encoding GLO1, PRDX4, ACY1, ORM1, CPB2, GSTM4, and HSP70.2 were selected for confirmation. Relative hepatic GLO1 (P < 0.0007), PRDX4 (P < 0.009) and ACY1 (P < 0.01) mRNA abundances were confirmed to be greater in pigs fed 1,000 (n = 8) and 2,000 (n = 8) mg Zn/kg than in pigs fed 150 (n = 7) mg Zn/kg. Relative hepatic HSP70.2 (P < 0.002) mRNA abundance was confirmed to be lower in pigs fed 2,000 mg Zn/kg than in pigs fed 150 or 1,000 mg Zn/kg. Conclusion: Results suggest that feeding pharmacological Zn (1,000 or 2,000 mg Zn/kg) affects genes involved in reducing oxidative stress and in amino acid metabolism, which are essential for cell detoxification and proper cell function. [ABSTRACT FROM AUTHOR]

Background: Soybean cyst nematode (SCN), Heterodera glycines Ichinohe, has been one of the most devastating pathogens affecting soybean production. In the United States alone, SCN damage accounted for more than $1 billion loss annually. With a narrow genetic background of the currently available SCN-resistant commercial cultivars, high risk of resistance breakdown can occur. The objectives of this study were to conduct a genome-wide association study (GWAS) to identify QTL, SNP markers, and candidate genes associated with soybean leaf chlorophyll content tolerance to SCN infection, and to carry out a genomic selection (GS) study for the chlorophyll content tolerance. Results: A total of 172 soybean genotypes were evaluated for the effect of SCN HG Type 1.2.3.5.6.7 (race 4) on soybean leaf chlorophyll. The soybean lines were genotyped using a total of 4089 filtered and high-quality SNPs. Results showed that (1) a large variation in SCN tolerance based on leaf chlorophyll content indices (CCI); (2) a total of 22, 14, and 16 SNPs associated with CCI of non-SCN-infected plants, SCN-infected plants, and reduction of CCI SCN, respectively; (3) a new locus of chlorophyll content tolerance to SCN mapped on chromosome 3; (4) candidate genes encoding for Leucine-rich repeat protein, plant hormone signaling molecules, and biomolecule transporters; and (5) an average GS accuracy ranging from 0.31 to 0.46 with all SNPs and varying from 0.55 to 0.76 when GWAS-derived SNP markers were used across five models. This study demonstrated the potential of using genome-wide selection to breed chlorophyll-content-tolerant soybean for managing SCN. Conclusions: In this study, soybean accessions with higher CCI under SCN infestation, and molecular markers associated with chlorophyll content related to SCN were identified. In addition, a total of 15 candidate genes associated with chlorophyll content tolerance to SCN in soybean were also identified. These candidate genes will lead to a better understanding of the molecular mechanisms that control chlorophyll content tolerance to SCN in soybean. Genomic selection analysis of chlorophyll content tolerance to SCN showed that using significant SNPs obtained from GWAS could provide better GS accuracy. [ABSTRACT FROM AUTHOR]

Background: Gastrointestinal nematode infection (GNI) is the most important disease affecting the small ruminant industry in U.S. The environmental conditions in the southern United States are ideal for the survival of the most pathogenic gastrointestinal nematode, Haemonchus contortus. Host genetic variation for resistance to H. contortus allows selective breeding for increased resistance of animals. This selection process increases the prevalence of particular alleles in sheep and goats and creates unique genetic patterns in the genome of these species. The aim of this study was to identify loci with divergent allelic frequencies in a candidate gene panel of 100 genes using two different approaches (frequentist and Bayesian) to estimate Fst outliers in three different breeds of sheep and goats exposed to H. contortus. Results: Our results for sheep populations showed SNPs under selection in C3AR1, CSF3, SOCS2, NOS2, STAT5B, TGFB2 and IL2RA genes using frequentist and Bayesian approaches. For goats, SNPs in CD1D, ITGA9, IL12A, IL13RA1, CD86 and TGFB2 genes were under selection. Common signatures of selection in both species were observed in NOS2, TGFB2 and TLR4 genes. Directional selection was present in all SNPs evaluated in the present study. Conclusions: A total of 13 SNPs within 7 genes of our candidate gene panel related to H. contortus exposure were identified under selection in sheep populations. For goats, 11 SNPs within 7 genes were identified under selection. Results from this study support the hypothesis that resistance to H. contortus is likely to be controlled by many loci. Shared signatures of selection related to mechanisms of immune protection against H. contortus infection in sheep and goats could be useful targets in breeding programs aimed to produce resistant animals with low FEC. [ABSTRACT FROM AUTHOR]

Comparative genomics is the comparison of genetic information within and across organisms to understand the evolution, structure, and function of genes, proteins, and non-coding regions (Sivashankari and Shanmughavel, Bioinformation 1:376-8, 2007). Advances in sequencing technology and assembly algorithms have resulted in the ability to sequence large genomes and provided a wealth of data that are being used in comparative genomic analyses. Comparative analysis can be leveraged to systematically explore and evaluate the biological relationships and evolution between species, aid in understanding the structure and function of genes, and gain a better understanding of disease and potential drug targets. As our knowledge of genetics expands, comparative genomics can help identify emerging model organisms among a broader span of the tree of life, positively impacting human health. This impact includes, but is not limited to, zoonotic disease research, therapeutics development, microbiome research, xenotransplantation, oncology, and toxicology. Despite advancements in comparative genomics, new challenges have arisen around the quantity, quality assurance, annotation, and interoperability of genomic data and metadata. New tools and approaches are required to meet these challenges and fulfill the needs of researchers. This paper focuses on how the National Institutes of Health (NIH) Comparative Genomics Resource (CGR) can address both the opportunities for comparative genomics to further impact human health and confront an increasingly complex set of challenges facing researchers., (© 2023. BioMed Central Ltd., part of Springer Nature.)