Immunogenetic variation in humans is important in research, clinical diagnosis and increasingly a target for therapeutic intervention. Two highly polymorphic loci play critical roles, namely the human leukocyte antigen (HLA) system, which is the human version of the major histocompatibility complex (MHC), and the Killer-cell immunoglobulin-like receptors (KIR) that are relevant for responses of natural killer (NK) and some subsets of T cells. Their accurate classification has typically required the use of dedicated biological specimens and a combination of in vitro and in silico efforts. Increased availability of next generation sequencing data has led to the development of ancillary computational solutions. Here, we report an evaluation of recently published algorithms to computationally infer complex immunogenetic variation in the form of HLA alleles and KIR haplotypes from whole-genome or whole-exome sequencing data. For both HLA allele and KIR gene typing, we identified tools that yielded >97% overall accuracy for four-digit HLA types, and >99% overall accuracy for KIR gene presence, suggesting the readiness of in silico solutions for use in clinical and high-throughput research settings.

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Human immunogenetic variation in the form of HLA and KIR types has been shown to be strongly associated with a multitude of immune-related phenotypes. However, association studies involving immunogenetic loci most commonly involve simple analyses of classical HLA allelic diversity, resulting in limitations regarding the interpretability and reproducibility of results. We here present MiDAS, a comprehensive R package for immunogenetic data transformation and statistical analysis. MiDAS recodes input data in the form of HLA alleles and KIR types into biologically meaningful variables, allowing HLA amino acid fine mapping, analyses of HLA evolutionary divergence as well as experimentally validated HLA-KIR interactions. Further, MiDAS enables comprehensive statistical association analysis workflows with phenotypes of diverse measurement scales. MiDAS thus closes the gap between the inference of immunogenetic variation and its efficient utilization to make relevant discoveries related to immune and disease biology. It is freely available under a MIT license.

The atrioventricular canal (AVC) is the site where key structures responsible for functional division between heart regions are established, most importantly, the atrioventricular (AV) conduction system and cardiac valves. To elucidate the mechanism underlying AVC development and function, we utilized transgenic zebrafish line sqet31Et expressing EGFP in the AVC to isolate this cell population and profile its transcriptome at 48 and 72 hpf. The zebrafish AVC transcriptome exhibits hallmarks of mammalian AV node, including the expression of genes implicated in its development and those encoding connexins forming low conductance gap junctions. Transcriptome analysis uncovered protein-coding and noncoding transcripts enriched in AVC, which have not been previously associated with this structure, as well as dynamic expression of epithelial-to-mesenchymal transition markers and components of TGF-β, Notch, and Wnt signaling pathways likely reflecting ongoing AVC and valve development. Using transgenic line Tg(myl7:mermaid) encoding voltage-sensitive fluorescent protein, we show that abolishing the pacemaker-containing sinoatrial ring (SAR) through Isl1 loss of function resulted in spontaneous activation in the AVC region, suggesting that it possesses inherent automaticity although insufficient to replace the SAR. The SAR and AVC transcriptomes express partially overlapping species of ion channels and gap junction proteins, reflecting their distinct roles. Besides identifying conserved aspects between zebrafish and mammalian conduction systems, our results established molecular hallmarks of the developing AVC which underlies its role in structural and electrophysiological separation between heart chambers. This data constitutes a valuable resource for studying AVC development and function, and identification of novel candidate genes implicated in these processes.

29The development of an organ involves dynamic regulation of gene transcription and complex multi-30 pathway interactions. To better understand transcriptional regulatory mechanism driving heart 31 development and the consequences of its disruption, we isolated cardiomyocytes (CMs) from wild-32 type zebrafish embryos at 24, 48 and 72 hours post fertilization corresponding to heart looping, 33 chamber formation and heart maturation, and from mutant lines carrying loss-of-function mutations in 34 gata5, tbx5a and hand2, transcription factors (TFs) required for proper heart development. The 35 integration of CM transcriptomics (RNA-seq) and genome-wide chromatin accessibility maps 36 (ATAC-seq) unravelled dynamic regulatory networks driving crucial events of heart development. 37These networks contained key cardiac TFs including Gata5/6, Nkx2.5, Tbx5/20, and Hand2, and are 38 associated with open chromatin regions enriched for DNA sequence motifs belonging to the family of 39 the corresponding TFs. These networks were disrupted in cardiac TF mutants, indicating their 40 importance in proper heart development. The most prominent gene expression changes, which 41 correlated with chromatin accessibility modifications within their proximal promoter regions, 42 occurred between heart looping and chamber formation, and were associated with metabolic and 43 hematopoietic/cardiac switch during CM maturation. Furthermore, loss of function of cardiac TFs 44 Gata5, Tbx5a, and Hand2 affected the cardiac regulatory networks and caused global changes in 45 chromatin accessibility profile. Among regions with differential chromatin accessibility in mutants 46were highly conserved non-coding elements which represent putative cis regulatory elements with 47 65 CMs are specified early during embryogenesis and undergo various cellular processes of proliferation, 66 migration, and differentiation which collectively give rise to a fully formed and functioning heart. 67Crucial to regulating each step of heart morphogenesis are cardiac transcription factors (TFs) which 68 include Nkx2.5, Gata5, Tbx5, and Hand2 (Clark et al. 2006;Nemer 2008). These TFs are known to 69 play a role in establishing the CM identity of mesodermal progenitor cells, regulating the formation 70 and looping of the heart tube, as well as the specification of atrial and ventricular CMs. Specification 71 and differentiation of the cardiac progenitors are regulated by the interactions between several key 72 TFs -Nkx2.5, Gata5, Tbx5, and Hand2. Members of the GATA family of TFs, Gata4, Gata5, and 73Gata6, are responsible for the earliest step of cardiac progenitor specification (Jiang and Evans 1996; 74 Jiang et al. 1998;Reiter et al. 1999;Singh et al. 2010;Lou et al. 2011;Turbendian et al. 2013). Gata 75 factors activate the expression of nkx2.5, another early marker of CMs (Chen and Fishman 1996; Lien 76 et al. 1999). Although not essential for specification of CMs, Nkx2.5 plays an important role in 77 initiating the expression of many cardiac genes in mouse ...

Immunogenetic variation in humans is important in research, clinical diagnosis and increasingly a target for therapeutic intervention. Two highly polymorphic loci play critical roles, namely the human leukocyte antigen (HLA) system, which is the human version of the major histocompatibility complex (MHC), and the Killer-cell immunoglobulin-like receptors (KIR) that are relevant for responses of Natural Killer (NK) cells and some subsets of T cells. Their accurate classification has typically required the use of dedicated biological specimens and a combination of in vitro and in silico efforts. Increased availability of next generation sequencing data has led to the development of ancillary computational solutions. Here, we report an evaluation of recently published algorithms to computationally infer complex immunogenetic variation in the form of HLA alleles and KIR haplotypes from whole-genome or whole-exome sequencing data. For both HLA allele and KIR gene typing, we identified tools that yielded >97% overall accuracy for 4-digit HLA types, and >99% overall accuracy for KIR gene presence, suggesting the readiness of in silico solutions for use in clinical and high-throughput research settings.

Most mitochondrial proteins are encoded by nuclear genes, synthetized in the cytosol and targeted into the organelle. To characterize the spatial organization of mitochondrial gene products in zebrafish (Danio rerio), we sequenced RNA from different cellular fractions. Our results confirmed the presence of nuclear-encoded mRNAs in the mitochondrial fraction, which in unperturbed conditions, are mainly transcripts encoding large proteins with specific properties, like transmembrane domains. To further explore the principles of mitochondrial protein compartmentalization in zebrafish, we quantified the transcriptomic changes for each subcellular fraction triggered by thechchd4a−/−mutation, causing the disorders in the mitochondrial protein import. Our results indicate that the proteostatic stress further restricts the population of transcripts on the mitochondrial surface, allowing only the largest and the most evolutionary conserved proteins to be synthetized there. We also show that many nuclear-encoded mitochondrial transcripts translated by the cytosolic ribosomes stay resistant to the global translation shutdown. Thus, vertebrates, in contrast to yeast, are not likely to use localized translation to facilitate synthesis of mitochondrial proteins under proteostatic stress conditions.