Developmental dyslexia is one of the most extensively researched and best-known developmental cognitive disorders. It is a specific cognitive disorder, with neurobiological and genetic traces. It is typically associated with phonological processing impairment leading to below-standard print processing – inaccurate and/or nonfluent and slow decoding (reading) as well as incorrect encoding (spelling) – much less skilful and proficient than would be expected of children at a given age (Hulme and Snowling 2009). Contrary to common belief dyslexia is perceived as a delay in reading and spelling development and should be viewed as a dimensional rather than a categorical phenomenon. It means that children with dyslexia, who encounter reading difficulties of varying degrees, are situated at the bottom end of the continuum of normal variation in the reading skill in the population (Hulme and Snowling 2009). Evidence shows that children tend to learn to read more rapidly in languages with more transparent orthographies than in opaque orthographic scripts such as English – greater consistency of grapheme-phoneme correspondences facilitates the rate of reading skill acquisition (Caravolas, Bruck, and Genessee 2003). there are universal cognitive prerequisites for learning to read and equivalent predictors of growth in reading operating across all alphabetic orthographies (e.g. Caravolas, Volin, and Hulme 2005; Caravolas et al. 2012, 2013; Ziegler et al. 2010). Research findings show that the more transparent the orthography of a given language is (e.g., Italian, Spanish, or Greek in contrast to English or French), the less pronounced the reading difficulties encountered by individuals with dyslexia are (de Jong and van der Leij 2003; Goswami 2000; Lundberg 2002; Miles 2000). Phoneme awareness tends to predict reading and spelling skills equally across languages with more and less transparent orthographies (e.g., Caravolas, Volin, and Hulme 2005; Patel, Snowling, and de Jong 2004; Caravolas et al. 2012, 2013). Impaired fluency and speed in word identification, which can lead to text processing difficulties resulting in poorer reading comprehension, are claimed to be the key markers for dyslexia in such languages (Snowling 2001; Vellutino et al. 2004). Still, even in highly transparent and regular orthographies several potential areas of difficulty for students with dyslexia might be enumerated. The study of dyslexia in Chinese, a logographic language, is relatively new and rather inconclusive. Ho, Law and Ng (2000) suggest that Chinese dyslexic children, similar to their alphabetic counterparts, experience problems in processing phonological information. Hu et al. (2010) in their functional magnetic resonance imaging study demonstrated that despite different brain activation patterns in Chinese and English normal readers, there tends to be a common activation in Chinese and English dyslexics. These findings seem to support the hypothesis of a common neural basis for dyslexia across languages and orthographies (Elliot and Grigorenko 2014). Also, Chinese dyslexic children learning English as a second language (ESL) tend to show low-grade phonological processing in both languages (Ho and Fong 2005). Phonological processing impairments causing dyslexia in L1 may similarly impede the acquisition of the reading and spelling skills in L2. It is crucial to differentiate between the phenomena that could be characterised as common, regular problems related to L2 acquisition and true warning signs of reading impairment as well as to observe whether the signs of dyslexic reading difficulty prevail in L1 and L2 alike (Geva 2000). In addition to examining phonological processing abilities and rapid basic reading skills, the recommended approach to an assessment towards dyslexia in a bilingual context would involve searching for a gap between listening and reading skills in L2. More research investigating dyslexia in bilingual and multilingual contexts is needed. Early identification of dyslexic literacy difficulties across languages as well as the provision of differentiated classroom instruction and specialised intervention programmes is highly recommended in the context of native, second and foreign language learning (Kormos and Kontra 2008; Kormos and Smith 2012; Martin 2013; Nijakowska 2010; Peer and Reid 2000, 2016). In light of the current knowledge of dyslexia, causality should be treated more as probability rather than certainty. The complex, multifaceted nature of dyslexia necessarily requires a multilevel description and an explanation involving biological, cognitive, and behavioural levels, with environmental impact operating at each of them (Frith 1999). The direction of the hypothesised causal links between the levels is both from the biological through the cognitive (related to mind and mental processes) to the behavioural levels and backwards. A contemporary coherent explanatory model or theory of dyslexia needs to address all three levels – biological (brain-based), cognitive, and behavioural – appropriately recognising the relations and indicating the causal links between these separate levels of explanation (Nicolson 2001). The dominant explanation of dyslexic reading difficulties at the cognitive level is provided by the phonological deficit hypothesis (Ramus et al. 2003; Vellutino et al. 2004). According to the phonological coding deficit hypothesis, individuals with dyslexia face disturbance in the encoding, storage and/or retrieval of speech sounds. Relatively transparent orthographies, offering more consistent letter to sound relations, facilitate the discovery of phonemes, and, hence, also facilitate reading skill acquisition and reading practice, which in turn allows to more successfully specify phoneme-level representations, despite phonological processing difficulties encountered by children with dyslexia. Multiple types of experimental studies have been conducted to verify the assumptions of the phonological deficit hypothesis. These studies have gathered strong and converging evidence in support of the core phonological deficit in dyslexia. Still, some scholars undermine poor phonological coding as an exclusive and primary cause of dyslexia. A phonological processing deficit and a naming speed deficit constitute two independent underlying causes of dyslexic difficulties as assumed by the double-deficit hypothesis(DDH) (e.g., Lovett, Steinbach, and Frijters, 2000; Wolf and Bowers 1999). Since the evidence to date is mixed (for a review see Elliott and Grigorenko 2014), there is a need to collect a sufficient amount of research findings supporting the DDH, in particular with regard to the claimed independence of dyslexics’ naming speed skills and phonological processing skills and their respective roles in explaining dyslexic reading difficulties. Low-level sensory processing impairment theories such as the temporal auditory processing theory (Tallal 1980) and the magnocellular theory (Stein 2001) aim to elucidate more basic (and less reading-specific) causes of dyslexics’ reading difficulty. They refer to the faulty processing of rapidly changing, transient auditory and visual stimuli, respectively. These deficits are claimed to originate from the neurobiological underpinnings of language processing and to constitute the underlying cause of the phonological deficit, i.e., the ultimate basis for dyslexia. The auditory temporal processing deficit (a difficulty in processing short sounds and fast transitions; the inability to discriminate between certain phonemic contrasts, e.g., /ba/ and /da/) is claimed to hinder speech perception, thus causing the phonological deficit, which in turn leads to dyslexic problems (Tallal 1980). Some researchers claim that dyslexics’ auditory difficulties are insufficiently explained by the temporal auditory processing theory and suggest that the auditory deficit also involves a poor use of prosodic clues, a poor perception of speech rhythm, tempo, and stress (Goswami et al. 2013). All in all, low-level sensory processing impairments are generally considered not to be the cause of the phonological deficit in dyslexia (White et al. 2006; Ramus, White, and Frith, 2006). The automatization deficit hypothesis constitutes a cognitive level explanation of dyslexia and is traced back to an underlying cerebellar deficit (biological level) (Fawcett and Nicolson 2001, 2004; Nicolson and Fawcett 2008). It states that children with dyslexia find it notably difficult to automatize any motor or cognitive skill, regardless of the time and effort they invest in practice. This statement holds true for reading but would also explain dyslexics’ poor handwriting and their articulation. However, research evidence concerning the automatization deficit hypothesis (directly linked to the cerebellar deficit) is mixed and inconclusive, for instance Savage’s (2007) findings show that the cerebellar deficit is not specific to dyslexia. Biological level explanations of dyslexia are based on abnormalities in the brain anatomical structure and function, which could be the cause of dyslexia. According to Nicolson and Fawcett (2008), dyslexics’ reading difficulties can be explained by a cerebellar deficit in the brain. The above-mentioned puzzling range of anatomical differences between dyslexic and non-dyslexic brains confirms the complexity of the underlying neuroanatomical basis of dyslexia and indicates the existence of its several possible neuroanatomical substrates. However, the functional significance of these structural brain differences in dyslexic and non-dyslexic individuals requires further decent explanation. Functional brain imaging studies aim at identifying, registering, evaluating, characterising and then comparing brain function during reading and reading-related tasks in typical and dyslexic readers (e.g., Richards 2001; Temple 2002) in terms of place and/or time. The vast majority of functional imaging studies in dyslexia research fall back on the premises of the dominant cognitive level explanation of dyslexia, namely, the phonological deficit hypothesis. Generally, findings of the functional imaging studies tend to support the claim that brain activation patterns during reading tasks in dyslexics differ from non-dyslexic controls, which seems to be compatible with cognitive test results (e.g., Tanaka et al. 2011). More importantly, these findings also show that the differences are found especially with regard to the left posterior brain systems. Finally, we learn from functional imaging studies that, subsequent to systematic and specialised educational interventions, a considerable and consistent improvement in reading skills is accompanied by a significant functional reorganisation and change in the activated brain structures. Appropriate instructional practices and educational interventions not only play a vital role in causing successful reading in dyslexics but also in modifying dyslexia-specific brain activation patterns to become more typical, resembling patterns usually demonstrated by high-achieving readers. The fact that dyslexia tends to run in families was first reported at the turn of the last century, and since then converging research findings have accumulated in support of considerable heritability of dyslexia (Byrne et al. 2007; DeFries, Fulker and LaBuda 1987). Importantly though, the genetic risk for dyslexia cannot be considered to be deterministic in nature, due to the interplay between genes and the environment. In all likelihood it is the combination of the influence of many genes with a small effect and the environmental input that determines the risk of inheriting dyslexia (Galaburda et al. 2006; Ramus 2006). The scale and scope of research devoted to discovering the underlying cause of dyslexia is impressive. Clearly, a comprehensive causal theory of dyslexia, embracing, explaining and finding a single explanatory framework for the huge bulk of scientific findings, remains a future endeavour.