Compact Personalized Models for Neural Machine Translation

We propose and compare methods for gradient-based domain adaptation of self-attentive neural machine translation models. We demonstrate that a large proportion of model parameters can be frozen during adaptation with minimal or no reduction in translation quality by encouraging structured sparsity in the set of offset tensors during learning via group lasso regularization. We evaluate this technique for both batch and incremental adaptation across multiple data sets and language pairs. Our system architecture - combining a state-of-the-art self-attentive model with compact domain adaptation - provides high quality personalized machine translation that is both space and time efficient.Comment: Published at the 2018 Conference on Empirical Methods in Natural Language Processin

Genetische Parameter für verschiedene euterviertelspezifische Merkmale beim Schweizer Braunvieh

Fragestellung: - Gibt es Unterschiede und Regelmäßigkeiten in den genetischen Parametern für die Milchinhaltsstoffe zwischen den Eutervierteln? - Lassen sich diese Informationen züchterisch nutzen

Optimum allocation of conservation funds and choice of conservation programs for a set of African cattle breeds

<p>Abstract</p> <p>Although funds for livestock conservation are limited there is little known about the optimal allocation of conservation funds. A new algorithm was used to allocate Mio US$1, 2, 3, 5 or unlimited funds, discounted over 50 years, on 23 African cattle breeds conserved with four different possible conservation programs. Additionally, Mio US$ 1 was preferably allocated to breeds with special traits. The conceptional <it>in situ </it>conservation programs strongly involve breeders and give them part of the responsibility for the conservation of the breed. Therefore, the pure <it>in situ </it>conservation was more efficient than cryoconservation or combined <it>in situ </it>and cryoconservation. The average annual discounted conservation cost for a breed can be as low as US$1000 to US$ 4400 depending on the design of the conservation program and the economic situation of the country of conservation. The choice of the breeds and the optimal conservation program and the amount of money allocated to each breed depend on many factors such as the amount of funds available, the conservation potential of each breed, the effects of the conservation program as well as its cost. With Mio US$1, 64$ 10, leaving 8% of the diversity to unpredictable happenings. The suggested algorithm proved to be useful for optimal allocation of conservation funds. It allocated the funds optimally among breeds by identifying the most suited conservation program for each breed, also accounting for differences in currency exchange rates between the different countries.</p

Comparison of traditional and genomic breeding programs for organic and low input dairy cattle accounting for traits relevant in different macro-climatic zones

In the past decade, successful selection on production traits for dairy cattle has greatly increased milk production. Recently, selection indices for female fertility were gradually and increasingly introduced into the overall breeding goals for dairy cattle (Miglior et al., 2005). As a by-product of fermention in ruminants, enteric methane emissions (ME) should also be controlled and mitigated due to their contribution to global warming (Forster et al., 2007) and as a cause for inefficient use of dietary energy. Moderate heritabilities ranging between 0.30 and 0.35 for predicted and real measurements of ME were reported for dairy cows and ewe lambs (de Haas et al., 2011; Pinares-Patiño et al., 2011), indicating that a heritable component for ME is available for implementing sustainable breeding strategies to reduce ME in dairy farms. In dairy cattle production systems, the traditional progeny testing substantially increases accuracy of selection especially for bulls. However, availability of high-density SNP arrays enable dairy cattle breeders to apply genomic selection in their breeding strategies. Consequently, the objective of this study was to compare selection response for a complex breeding goal comprising ME, milk yield (MY), days open (DO), clinical mastitis (CM), body condition score (BCS) and milking temperament (MT) and total discounted return for organic and low input dairy cattle (with organic Brown Swiss as an example) from progeny testing and genomic breeding program by applying ZPLAN+ (Täubert et al., 2010)

Accuracy of 54K to HD gebotype imputation in Brown Swiss cattle

Imputation of genotypes can be used to reduce the implementation costs of genomic selection. In this study, we evaluated the accuracy of genotype imputation from Illumina 54k to Illumina High Density (HD) in Brown Swiss cattle. Genotype data comprised 6,106 54k and 880 HD genotyped bulls and cows of Brown Swiss and Original Braunvieh cattle. Genotype data was checked for parentage conflicts and SNP were excluded if MAF was below 0.5% and SNP call rate was lower than 90%. The final data set included 39,004 SNP for the 54k and 627,306 SNP for the HD chip. HD genotypes of animals born between 2004 and 2008 (n=365) were masked to mimic animals genotyped with the 54k chip. Methods used for imputation were FImpute and Findhap V2. Both programs use pedigree information for imputation. The accuracy of imputation was assessed by the correlation (r) between true and imputed genotypes, the percentage of correctly and incorrectly imputed genotypes. Both programs gave high imputation accuracy with FImpute outperforming Findhap. Accuracy of imputation increased with increasing relationship between the HD genotyped reference population and 54k genotyped imputation candidates. Average r for FImpute and Findhap were 0.992 and 0.988 when both parents of the 54k genotyped candidate were HD genotyped, respectively. Correlations were lower when no direct relatives were HD genotyped (0.971 and 0.918 for FImpute and Findhap, respectively). Accuracy of imputation highly depended on MAF of the imputed SNP. For FImpute, average r ranged between 0.89 (MAF <0.025) and 0.99 (MAF between 0.4 and 0.5)

Ökologische Milchviehzucht: Entwicklung und Bewertung züchterischer Ansätze unter Berücksichtigung der Genotyp x Umwelt-Interaktion und Schaffung eines Informationssystems für nachhaltige Zuchtstrategien

In dem Projekt wurden für verschiedene Merkmalskomplexe an zwei verschiedenen Datensätzen Genotyp x Umwelt-Interaktionen zwischen ökologischen und konventionellen Produktionssystemen geschätzt. Anhand Schweizer Daten wurden für Braunvieh und Fleckvieh für Milchleistungsmerkmale Korrelationen > 0.9 zwischen beiden Betriebsformen geschätzt, wohingegen die genetische Korrelationen für funktionale Merkmale (Rastzeit, Zellzahl) geringer (0.8 bis 0.9) waren. Diese Korrelationen konnten für die Rasse Holstein Friesian auf Grund einer Auswertung Deutscher Daten bestätigt werden. Generell liegt für Leistungsmerkmale keine und für funktionale Merkmale eine geringe Genotyp x Umwelt-Interaktion zwischen ökologischen und konventionellen Betrieben vor, wobei insbesondere für letztere die Informationsbasis begrenzt ist. Auswertungen der Betriebsdaten von > 450 ökologisch wirtschaftenden Milchviehbetrieben und Befragungen der Betriebsleiter haben ergeben, dass sich diese Betriebe in ihren züchterischen Zielen kaum und in ihrem züchterischen Handeln gar nicht von konventionellen Betrieben unterscheiden. Zuchtplanerische Rechnungen haben ergeben, dass unter den gefundenen genetischen Parametern weder ein geschlossenes noch ein offenes eigenes Zuchtprogramm im ökologischen Sektor wirtschaftlich gerechtfertigt ist. Vielmehr ist anzustreben, dass sich ökologisch wirtschaftende Milchviehbetriebe stärker aktiv an etablierten Zuchtprogrammen beteiligen, z.B. durch den stärkeren Einsatz von Testbullen. Es wird vorgeschlagen, aufgrund der bestehenden Teilzuchtwerte einen Ökologischen Gesamtzuchtwert zu entwickeln, in dem funktionale Merkmale stärker gewichtet werden. Ein im Projekt entwickeltes Internetportal und eine entsprechend angepasste Anpaarungssoftware kann die Umsetzung dieses Vorschlags unterstützen. Erforderlich ist allerdings eine vollständigere Erfassung der ökologischen Milchviehbetriebe als Voraussetzung für eine bessere Unterstützung der ökologischen Milchviehzucht

Estimation of covariance components between one continuous and one binary trait

International audienc

Development of a high density 600K SNP genotyping array for chicken

Background: High density (HD) SNP genotyping arrays are an important tool for genetic analyses of animals and plants. Although the chicken is one of the most important farm animals, no HD array is yet available for high resolution genetic analysis of this species.Results: We report here the development of a 600 K Affymetrix® Axiom® HD genotyping array designed using SNPs segregating in a wide variety of chicken populations. In order to generate a large catalogue of segregating SNPs, we re-sequenced 243 chickens from 24 chicken lines derived from diverse sources (experimental, commercial broiler and layer lines) by pooling 10-15 samples within each line. About 139 million (M) putative SNPs were detected by mapping sequence reads to the new reference genome (Gallus_gallus_4.0) of which ~78 M appeared to be segregating in different lines. Using criteria such as high SNP-quality score, acceptable design scores predicting high conversion performance in the final array and uniformity of distribution across the genome, we selected ~1.8 M SNPs for validation through genotyping on an independent set of samples (n = 282). About 64% of the SNPs were polymorphic with high call rates (>98%), good cluster separation and stable Mendelian inheritance. Polymorphic SNPs were further analysed for their population characteristics and genomic effects. SNPs with extreme breach of Hardy-Weinberg equilibrium (P < 0.00001) were excluded from the panel. The final array, designed on the basis of these analyses, consists of 580,954 SNPs and includes 21,534 coding variants. SNPs were selected to achieve an essentially uniform distribution based on genetic map distance for both broiler and layer lines. Due to a lower extent of LD in broilers compared to layers, as reported in previous studies, the ratio of broiler and layer SNPs in the array was kept as 3:2. The final panel was shown to genotype a wide range of samples including broilers and layers with over 100 K to 450 K informative SNPs per line. A principal component analysis was used to demonstrate the ability of the array to detect the expected population structure which is an important pre-investigation step for many genome-wide analyses.Conclusions: This Affymetrix® Axiom® array is the first SNP genotyping array for chicken that has been made commercially available to the public as a product. This array is expected to find widespread usage both in research and commercial application such as in genomic selection, genome-wide association studies, selection signature analyses, fine mapping of QTLs and detection of copy number variants